ALBERT

Description: Linpan settlements (abbreviated as Linpan) are the most important traditional type of rural settlement in the Chengdu Plain, and they are an important part of the agroforestry ecological system in southwest China. In this study, we measured the micrometeorological parameters (air temperature, solar radiation, relative humidity, and wind speed) in 12 Linpans for two years to determine the seasonal micrometeorology variations; then, we explored the impacts of Linpan size and tree distribution on the Linpan micrometeorology. The results show that the Linpans undergo seasonal cooling (from 0.6 to 1.3°C), humidification (from 0.9% to 4.1%), reduction in solar radiation flux (from 92.1 to 496.0 W/m2), and changes in wind speed (by 0.4 to 0.5 m/s) compared to the surrounding environment. Both solar radiation flux and wind speed showed the following decreasing trend with respect to sampling positions in the Linpan: outside 〉 edge 〉 center. The Linpan size did not affect the solar radiation flux or wind speed over the four seasons. The main factor affecting solar radiation flux and wind speed was the horizontal tree distribution not the Linpan size. However, the Linpan size was significantly correlated with the air temperature in summer and winter. Large Linpans (〉5 × 103 m2) showed better ability to control the temperature to within a comfortable range in extremely hot and cold seasons. The Linpan size also showed a negative relationship with the relative humidity, but only in winter. Among the tree distribution patterns, a scattered distribution was optimal to achieve a comfortable micrometeorology over the course of the year. In addition, we suggest some ways to adapt the Linpan micrometeorology, which could be used to protect traditional Linpans, as well as for ecological restoration.

Description: Utilising climate funds properly to reduce the impact of potential risks of climate change at the local level is essential for successful adaptation to climate change. Climate change has been disrupting the lives of millions of households along the coastal region of Bangladesh. The country has allocated support from its national funds and accessed international funds for the implementation of adaptation interventions. With the focus of the scientific community on climate finance mechanisms and governance at the global and the national level, there is a lacuna in empirical evidence of how climate finance affects risk appraisal and engagement in adaptation measures at the local level. This paper aims to examine how the support from climate finance affects risk appraisal in terms of the perceived probability and severity and the factors which influence risk appraisal. A field survey was conducted on 240 climate finance recipient households (CF HHs) and 120 nonclimate finance recipient households (non-CF HHs) in Galachipa Upazila of Patuakhali District in coastal Bangladesh. The results indicate that both CF and non-CF HHs experience a high probability of facing climatic events in the future; however, CF HHs anticipated a higher severity of impacts of climatic events on different dimensions of their households. With higher income and social capital, the overall risk appraisal decreases for CF HHs. CF HHs have higher engagement in adaptation measures and social groups and maintain alternative sources of income. Climate finance played a critical role in supporting households in understanding the risks that they were facing, assisting them in exploring as well as enhancing their engagement in adaptation options.

Description: Carrying global positioning system (GPS) radio occultation (RO) receiver, Chinese meteorological satellite Fengyun-3C (FY-3C) was launched on September 23, 2013, which provides new observation data for observations and studies of weather and climate change. In this paper, the results of FY-3C GPS RO atmospheric sounding are presented for the first time, including high-order ionospheric correction, atmospheric parameters estimation, and evaluation by COSMIC and radiosonde observations as well as applications in estimating gravity wave activities. It is found that the effect of the ionospheric correction residual on the phase delay is below 20 mm, which has minimal impact on bending angle estimation and generates differences of about 1 K in the average temperature profile. The difference between FY-3C and COSMIC temperatures at all heights is within 1°C, and the tropopause temperature and height have a good consistency. Deviations from Radiosonde measurements are within 2°C, and the tropopause temperature and height results also have a strong consistency. Furthermore, global gravity wave potential energy is estimated from FY-3C GPS RO, exhibiting similar behavior to results derived from COSMIC radio occultation measurements. The mean value of the gravity wave potential energy near the equator is 10 J/kg and decreases toward the two poles while in the northern hemisphere, it is stronger than that in the southern hemisphere.

Description: The temperature readings for all the 365 days and the 24 hours may be fitted through a 3 × 3 matrix (the so-called T-matrix). The mean square deviation between this fit and the actual meteorological measurements is smaller than three degrees Celsius. Four entries of this (nonsymmetric) matrix may be fixed by other means, leaving only five independent components. However, the same method applied to the humidity measurements produces a larger mean square deviation. A strong stochastical connection is found between the T-temperature matrix and the U-humidity matrix. The computer program, in C, may be used to adjust a (2M + 1) × (2m + 1) matrix simply by changing the arguments at the command line and has been tested with m and M ranging from zero to 11 (eleven) (more than 24 readings per day are necessary for larger values of m). The physical meaning of these constants is given only in the case m = M = 1. Our results have also been connected to fundamental cosmological properties: Earth’s orbit, the ecliptic angle, and the latitude of Querétaro (or whatever geographical location is chosen). A separate program calculates the angular position of the Sun as measured in the sky of Querétaro, to determine the length of the day or the mean value of the solar cosine. This work introduces several new variables which happen to be stochastically connected.

Description: This study investigates the impacts of different physical parameterization schemes in the Weather Research and Forecasting model with the ARW dynamical core (WRF-ARW model) on the forecasts of heavy rainfall over the northern part of Vietnam (Bac Bo area). Various physical model configurations generated from different typical cumulus, shortwave radiation, and boundary layer and from simple to complex cloud microphysics schemes are examined and verified for the cases of extreme heavy rainfall during 2012–2016. It is found that the most skilled forecasts come from the Kain–Fritsch (KF) scheme. However, relating to the different causes of the heavy rainfall events, the forecast cycles using the Betts–Miller–Janjic (BMJ) scheme show better skills for tropical cyclones or slowly moving surface low-pressure system situations compared to KF scheme experiments. Most of the sensitivities to KF scheme experiments are related to boundary layer schemes. Both configurations using KF or BMJ schemes show that more complex cloud microphysics schemes can also improve the heavy rain forecast with the WRF-ARW model for the Bac Bo area of Vietnam.

Description: Floods and droughts are more closely related to the extreme precipitation over longer periods of time. The spatial and temporal changes and frequency analysis of 5-day and 10-day extreme precipitations (PX5D and PX10D) in the Huai River basin (HRB) are investigated by means of correlation analysis, trend and abrupt change analysis, EOF analysis, and hydrological frequency analysis based on the daily precipitation data from 1960 to 2014. The results indicate (1) PX5D and PX10D indices have a weak upward trend in HRB, and the weak upward trend may be due to the significant downward trend in the 21st century, (2) the multiday (5-day and 10-day) extreme precipitation is closely associated with flood/drought disasters in the HRB, and (3) for stations of nonstationary changes with significant upward trend after the abrupt change, if the whole extreme precipitation series are used for frequency analysis, the risk of future floods will be underestimated, and this effect is more pronounced for longer return periods.

Description: In accordance with the China Meteorological Administration definition, this study considered a weather process with a maximum surface temperature of ≥35°C for more than three consecutive days as a heatwave event. Based on a dataset of daily maximum temperatures from meteorological stations on the North China Plain, including ordinary and national basic/reference surface stations, the intensity-area-duration method was used to analyze the spatiotemporal distribution characteristics of heatwave events on the North China Plain (1961–2017). Moreover, based on demographic data from the Statistical Yearbook and Greenhouse Gas Initiative (GGI) Population Scenario Database of the Austrian Institute for International Applied Systems Analysis (IIASA), population exposure to heatwave events was also studied. The results showed that the frequency, intensity, and area of impact of heatwave events on the North China Plain initially decreased (becoming weaker and less extensive) and then increased (becoming stronger and more extensive). Similarly, the trend of population exposure to heatwave events initially decreased and then increased, and the central position of exposure initially moved southward and then returned northward. Population exposure in the eastern Taihang Mountains was found significantly higher than in the western Taihang Mountains. In relation to the change of population exposure to heatwave events on the North China Plain, the influence of climatic factors was found dominant with an absolute contribution rate of 〉75%. Except for 2011–2017, increase in population also increased the exposure to heatwaves, particularly in the first half of the study period. Interaction between climatic and population factors generally had less impact on population exposure than either climatic factors or population factors alone. This study demonstrated a method for assessing the impact of heatwave events on population exposure, which could form a scientific basis for the development of government policy regarding adaption to climate change.

Description: Temperature changes have a major impact on all aspects of human society and have attracted global attention. The scarcity of observation data and the inaccuracy of the models make obtaining accurate temperature distributions a challenge. This study introduces high-accuracy surface modeling (HASM) combined with temperature simulations from the Weather Research and Forecasting (WRF) model and temperature records from observation stations to investigate the spatiotemporal characteristics of temperature in the Beijing-Tianjin-Hebei region during the period of 1956–2005. Leave-one-out cross-validation is applied to verify the temperature fields before and after the fusion of the models. The results indicate that the WRF model has a limited ability to simulate temperature conditions, but the overall deviation across the region is relatively large. The fusion results of the HASM decrease the mean absolute error (MAE) and the root-mean-square error (RMSE) by half in most instances, and the correlation between the fusion data and observation data is approximately 0.01–0.03 higher than that with the WRF simulation data. Based on the fusion data, obvious warming trends are observed during 1976–2005. In general, temperatures in spring, summer, and autumn increase rapidly from 1996 to 2005 but from 1976 to 1995 in winter. The substantial fluctuations in the interannual temperature during 1996–2005 in summer, autumn, and winter may be related to the frequent occurrence of extreme weather. The spatial distribution of temperature change differs in each season during 1956–1995. A dramatic increase in temperature occurs in the western part of the study area during 1996–2005 but with no seasonal difference.

Description: Accurate estimation of reference evapotranspiration (ETo) is key to agricultural irrigation scheduling and water resources management in arid and semiarid areas. This study evaluates the capability of coupling a Bat algorithm with the XGBoost method (i.e., the BAXGB model) for estimating monthly ETo in the arid and semiarid regions of China. Meteorological data from three stations (Datong, Yinchuan, and Taiyuan) during 1991–2015 were used to build the BAXGB model, the multivariate adaptive regression splines (MARS), and the gaussian process regression (GPR) model. Six input combinations with different sets of meteorological parameters were applied for model training and testing, which included mean air temperature (), maximum air temperature (), minimum air temperature (), wind speed (U), relative humidity (RH), and solar radiation () or extraterrestrial radiation (, MJ m−2·d−1). The results indicated that BAXGB models (RMSE = 0.114–0.412 mm·d−1, MAE = 0.087–0.302 mm·d−1, and R2 = 0.937–0.996) were more accurate than either MARS (RMSE = 0.146–0.512 mm·d−1, MAE = 0.112–0.37 mm·d−1, and R2 = 0.935–0.994) or GPR (RMSE = 0.289–0.714 mm·d−1, MAE = 0.197–0.564 mm·d−1, and R2 = 0.817–0.980) model for estimating ETo. Findings of this study would be helpful for agricultural irrigation scheduling in the arid and semiarid regions and may be used as reference in other regions where accurate models for improving local water management are needed.

Description: The East Asian summer monsoon (EASM), which is an important influencing summer climate of East Asia, is associated with large-scale change of the land-sea thermal contrast. The Asian-Pacific Oscillation (APO) can modulate the EASM because it not only represents the upper-tropospheric zonal land-sea thermal contrast over Asia and the Pacific region, but it also affects the sea surface temperature (SST) over the North Pacific, which can tune the land-sea thermal contrast for the EASM. This study revealed weakening of the APO-EASM relationship since the 1990s. It was found that the relationship between the APO and the EASM during 1948–1990 (1991–2016) was statistically significant (insignificant). Further study indicated that the APO was concurrent with significant positive SST in the central North Pacific and subtropical central-western Pacific during 1948–1990, which contributed to the shift of the Pacific Decadal Oscillation (PDO) from its cold to warm phase and led to a weakened EASM. The APO-related SST and atmospheric circulation anomalies were found statistically to be insignificant during 1991–2016, which indicates a weakening of influence of the APO on shift of the PDO, and even a weaker link to the EASM.

Description: A full analysis of 3-month Standardized Precipitation-Evapotranspiration index (SPEI-3) changes and attribution analyses are of significance for deeply understanding dryness/wetness evolutions and thus formulating specific measures to sustain regional development. In this study, we analyze monthly and annual SPEI-3 changes over Southwest China (SWC; including Sichuan (SC), Chongqing (CQ), Guizhou (GZ), Yunnan (YN), and west Guangxi (wGX)) during 1961–2012, using the SPEI model and routine meteorological measurements at 269 weather sites. For SWC and each subregion (excluding wGX), annual SPEI-3 during 1961–2012 tends to decrease, and drying is at most of months in January and September–December, but wetting is in February–August (excluding March for wGX). Additionally, more than 50% of sites show declined and increased SPEI-3 in January, April, June, and August–December and the remaining months, respectively. Except for wGX with dominant of ET0, annual SPEI-3 changes in SWC and other four subregions have dominant of precipitation. Spatially, annual SPEI-3 changes at 59% of sites are because of precipitation, generally located in southeast SC, south YN, CQ, GZ, and south and northeast wGX. Nevertheless, dominants at regional and site scales vary among months, e.g., SWC, SC, CQ, and GZ, having dominant of precipitation (ET0) during September–December (most of months during January–August), YN always with dominant of precipitation, and wGX with dominant of precipitation (ET0) in February–April and July–December (January, May, and June). Importantly, this study provides a reference for quantitatively evaluating spatiotemporal dryness/wetness variations with climate change, especially for regions with significant drying/wetting.

Description: Machine learning algorithms should be tested for use in quantitative precipitation estimation models of rain radar data in South Korea because such an application can provide a more accurate estimate of rainfall than the conventional ZR relationship-based model. The applicability of random forest, stochastic gradient boosted model, and extreme learning machine methods to quantitative precipitation estimation models was investigated using case studies with polarization radar data from Gwangdeoksan radar station. Various combinations of input variable sets were tested, and results showed that machine learning algorithms can be applied to build the quantitative precipitation estimation model of the polarization radar data in South Korea. The machine learning-based quantitative precipitation estimation models led to better performances than ZR relationship-based models, particularly for heavy rainfall events. The extreme learning machine is considered the best of the algorithms used based on evaluation criteria.

Description: Monsoon rainfall is the principle source of fresh water essential for agricultural practices and human sustenance in the Indian subcontinent during summer. This study is primarily designed to analyse the extent of rainfall and temperature variations in Pakistan over the northern monsoon belt by using satellite and ground-based observations. The satellite gridded data for rainfall are acquired from Tropical Rainfall Measuring Mission (TRMM) along with rainfall and temperature data from 15 ground stations of Pakistan Meteorological Department (PMD). Data were analysed to identify changes in climatic parameters and spatiotemporal shift in monsoon precipitation in Pakistan. Analysis shows that there is significant correlation between TRMM and PMD datasets. Decrease in monsoon rainfall is observed during the last two decades. A more pronounced decrease is observed in monsoon rainfall during the years 2010–2017, i.e., 17.58 mm/year accompanied by 0.18°C increase in temperature. A southward spatial shift in monsoon rainfall occurrence (rainfall ≥2.5 mm/day) is observed while an eastward shift in moderate to heavy monsoon rainfall is identified. This study may be helpful for an agricultural country like Pakistan which is heavily dependent on monsoon rainfalls for assessing the impacts of changing monsoon season and to adapt towards changing climate.

Description: Compared with other regions in China, air pollution on the North China Plain (NCP) is serious. Fine particle pollution has been studied in-depth, but there is less research on long-term troposphere ozone (O3) variation. This study focuses on the summer interannual tropospheric O3 variation on the NCP and its influential factors. Our analysis relies on satellite observations (O3, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO), determined as vertical column density of the troposphere) and dynamical processes (El Niño-Southern Oscillation (ENSO), potential vorticity (PV), the quasibiennial oscillation (QBO), and East Asian summer monsoon index (EASMI)). Our results show the vertical column density of tropospheric O3 has a transition from the increasing trend to decreasing trend during the summer of 2005–2016. The summer series of tropospheric O3 show two distinct phases: the first phase (2005–2011), with an average growth rate of 0.55 ± 0.20 DU/yr, and a second phase (2012–2016), with an average reduction rate of 0.16 ± 0.23 DU/yr. The tropospheric NO2 column in the NCP also has a transition from the increasing trend to decreasing trend during the summer of 2005–2016. Tropospheric NO2 and CO column concentrations obtained from satellite observations indicate that emission reductions might be the main cause of the tropospheric O3 decrease. Particularly, the reduction of nitrogen oxides (NOx) is more significant, and NO2 decreased by (0.45 ± 0.11) × 1015 molec·cm−2 per year in summer since 2012. However, tropospheric column HCHO shows an increase of 0.05 × 1015 molec·cm−2 per year during the whole period of 2005 to 2016. An O3-NOx-VOC sensitivity experiment in the NCP showed that the O3 is still in a NOx-saturated state in some heavily polluted cities, although the NOx emissions are decreasing overall. In addition to the chemical reactions, atmospheric dynamic processes also have an effect on tropospheric O3. Finally, we built a model to analyze the contributions of chemical processes and dynamic processes to the tropospheric O3 column in the NCP. For the chemical process variables, 69.73% of the observed trend of tropospheric O3 could be explained by the NO2 tropospheric column. Therefore, the reduction of tropospheric O3 since 2012 is associated with the reduction of NOx. For the dynamical process variables, ENSO, PV, and EASMI can explain 60.64% of the observed trend of tropospheric O3. This result indicates that the atmospheric circulation of the western Pacific Ocean in summer has a significant impact on the interannual trends of tropospheric O3 in the NCP. It is also found that chemical processes had a more important impact on interannual tropospheric O3 than dynamic processes, although the dynamic processes cannot be neglected.

Description: Use of the satellite and reanalysis precipitation products, as supplementary data sources, are steadily rising for hydrometeorological applications, especially in data-sparse areas. However, the accuracy of these data sets is often lacking, especially in Turkey. This study evaluates the accuracy of satellite precipitation product (TRMM 3B42V7) and reanalysis precipitation product (NCEP-CFSR) against rain gauge observations for the 1998–2010 periods. Average annual precipitation for the 25 basins in Turkey was calculated using rain gauge precipitation data from 225 stations. The inverse distance weighting (IDW) method was used to calculate areal precipitation for each basin using GIS. According to the results of statistical analysis, the coefficient of determination for the TRMM product gave satisfactory results (R2 〉 0.88). However, R2 for the CFSR data set ranges from 0.35 for the Eastern Black Sea basin to 0.93 for the West Mediterranean basin. RMSE was calculated to be 95.679 mm and 128.097 mm for the TRMM and CFSR data, respectively. The NSE results of TRMM data showed very good performance for 6 basins, while the PBias value showed very good performance for 7 basins. The NSE results of CFSR data showed very good performance for 3 basins, while the PBias value showed very good performance for 6 basins.

Description: As a tipping bucket rain gauge, the HOBO Data Logging Rain Gauge RG3-M (RG3-M) has been widely used for the field precipitation observation owing to its superiority of independent power supply by a small portable battery. To quantify the measurement accuracy of the RG3-M gauge, a standard Manual Gauge (MG) and eight other models of tipping bucket rain gauges were installed at the Chuzhou hydrological experiment station of China. In this study, we first compared and investigated the accumulated mounts of 18 rainfall events of two RG3-M gauges benchmarked by the standard MG. Then, five typical rainfall events were chosen to further analyse the observed accuracy of the RG3-M gauge for different rainfall intensities at hourly temporal scale. Finally, the impacts of wind speed and rainfall intensity on the precipitation measurements of the RG3-M gauge were preliminarily explored. Results indicate that the RG3-M gauge measurement generally underestimates rainfall approximately −4% against the standard MG observation, but the maximum deviation even reaches −12.87%. In terms of the hourly rainfall process, the reliable measurement scope of the RG3-M gauge is ranging from 1.5 to 3 mm/h; however, it should be noted that the underestimation is rather significant at the higher rainfall rates (〉6 mm/h). Last, it was found that rainfall intensity is a nonnegligible factor for influencing the measurement of the RG3-M gauge. But the windy effect seems to be insignificant in our experiments, which might be attributed to the similar exposure of the compared gauges.

Description: This study investigated the effects of climatic changes on temperature, rainfall, and runoff in the Doroudzan catchment in the northeast of Fars province, Iran. Temperature and rainfall changes in three periods including 2011–2030, 2046–2065, and 2080–2099 were downscaled and studied using 15 Coupled Model Intercomparison Project, Phase 3 (CMIP3) climatic models, under three scenarios of greenhouse gas emissions A2, B1, and A1B, from the database of the LARS-WG model. The difference in the amount of changes in temperature and rainfall in these three periods and the observational amounts under the 15 models indicated the uncertainty of the changes values. To reduce this uncertainty and limit the results to the management and planning of water resources, ensemble approach was considered. For the preparation of the ensemble approach, the parameters from the files of the 15-model scenarios were averaged so that a climatic ensemble model could be obtained for each period. Then, the runoffs of the next three periods, under the second approach and three emission scenarios, were produced using the feedforwad neural network. The results indicated an increase in the average monthly maximum temperature and the minimum temperature in all three periods under the three scenarios. The results also showed a decrease in the rainfall in the early months of the year as well as an increase in the rainfall in the spring in most scenarios. Generally, the average annual rainfall in all these three periods under the climatic ensemble model, and three emission scenarios showed a reduction in the average annual rainfall in the three periods. The maximum amount of reduction was in 2080–2099 (101 mm) under the scenario B1. Besides, a reduction occurred in the average runoff of the catchment under three ensemble models and the emission scenario in all three periods, as compared to the average of the long-term observational values in most years.

Description: Using the data of CloudSat satellite, FY series satellite, CMORPH hourly precipitation, and ERA-interim reanalysis products, this paper aims to reveal the cloud features of Tibetan Plateau Vortex (TPV) category cloud clusters over its eastward-moving regions. 107 cases of eastward-moving TPV category that occurred in the summer half-year (April to September) are picked out, and then the cloud features of them are further analyzed by statistics. The results show that the eastward-moving TPV category occurs mostly in May and June, but leastly in July and September. With consecutive enhancement of precipitation intensity and convection intensity, an increasing trend is found in the proportions of deep convection clouds and multiple layer clouds during the TPV category eastward movement. In order to reveal the inner connection among the precipitation intensity, the convection intensity, and the microphysical characteristics of TPV category cloud clusters, the TPV category cloud clusters are classified into different categories by the criteria of the precipitation intensity and the convection intensity separately. Consequently, the two different criteria share the commonality that the number concentration of both ice crystal and cloud droplets increases obviously with the enhancement of precipitation intensity or convection intensity. However, the discrepancy of conclusions also exists between the two classification criteria. A notable stretching upward trend is found in the number concentration distribution of the ice crystal and downward trend in the number concentration distribution of the cloud droplet. The same increasing trend is also discovered in the effective average radius of the ice crystal and cloud droplet. But the TPV category cloud clusters with severe convection do not present the similar variation trend both in the number concentration and the effective average radius. Hence, although the above findings confirm that the precipitation intensity, the convection intensity, and the distribution of cloud hydrometers are associated and interacting mutually, the closed function relationship among them cannot be established, and other meteorology factors related to the ambient conditions should also be taken into consideration as a complete cloud microphysical system.

Description: In this paper, spatial domain verification of the haze of dependence and the dynamic evolution process of the spatial panel data model was based on the estimation of different factors that influence on the horizon haze effect and spillover effect from the perspective of spatial economics. The study found that the provincial space is dependent on Chinese haze; the influence of haze on neighboring provinces of the spatial spillover effect factors is obvious during the period of 2000∼2015; the effect of elastic coefficient of industrial structures on the haze near the space overflow area energy is high; thus the industrial structure has a significant inhibitory effect on the haze; the role of regional industrial transfer haze governance has been very fruitful; population, economic growth, financial development, and fiscal decentralization to reduce haze inhibiting the spillover effect of regional haze were increasing. In the formulation of haze-related policies and development planning, the government departments must take into account the spatial mechanism of regional haze and influencing factors and realize the overall reduction of haze amount in time dimension and spatial dimension in China.

Description: The Oceansat-2 satellite was launched on 23 September 2009 by the Indian Space Research Organization (ISRO). In this study, the historic archived OSCAT wind vectors are compared with the global moored buoys’ wind observations, including the U.S. National Data Buoy Center (NDBC), the Tropical Atmosphere Ocean (TAO), the Pilot Research Moored Array in the Tropical Atlantic (PIRATA), the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA), and Advanced Scatterometer (ASCAT) wind data in the same period of OSCAT by calculating the statistical parameters, namely, the root mean square error (RMSE), bias (mean of residuals), and correlation coefficient (R) between the collocated data. The comparisons with the global moored buoys show that the OSCAT wind vectors are consistent with buoys’ wind measurements. The average errors of the OSCAT wind vectors are 1.20 m/s and 17.7°. The analysis of the OSCAT wind vector errors at different buoy wind speeds in bins of 1 m/s indicates that the accuracy of the OSCAT wind speed first increases and then decreases with the increasing wind speed. The comparisons of OSCAT wind vectors and ASCAT wind vectors show that the average RMSEs of their differences are 1.27 m/s and 20.17°. In general, the accuracies of the OSCAT wind vectors satisfy the general scatterometer’s mission requirement and are consistent with ASCAT wind data. OSCAT wind vectors can be used in the global change study by the combination with other scatterometer data.

Description: Autumn phenology plays a critical role in terrestrial ecosystem circulations. However, the changes in autumn phenology and their correlation with temperature remain uncertain because mean temperature alone was not able to determine the changes in autumn phenology at various sites. Here, the leaf coloring season (LCS) was defined as the period when the leaves of more than half of the species had recognized changes in color. We systematically studied the changes in peak, start, end, and duration of LCS and their correlations with five temperature parameters (mean temperature, accumulated cold temperature, day temperature, night temperature, and temperature difference between day and night) in four periods. Similarly to previous findings, the start date of LCS advanced and the end of LCS delayed over the past 50 years, which consequently led to a lengthened duration of LCS in Xi’an, Harbin, Minqin, and Shenyang. In general, the rise in mean temperature, day temperature, and night temperature would delay the peak, start, and end of LCS and lengthen the duration of LCS in most cases. We also proved that the changes in LCS metrics not only could completely be explained by mean temperature but also were influenced by day temperature, night temperature, temperature difference, and even other climatic factors such as precipitation, at different sites.

Description: The northeastern coast of the U.S. is projected to expand its offshore wind capacity from the existing 30 MW to over 22 GW in the next decade, yet, only a few wind measurements are available in the region and none at hub height (around 100 m today); thus, extrapolations are needed to estimate wind speed as a function of height. A common method is the log-law, which is based on surface roughness length (). No reliable estimates of for the region have been presented in the literature. Here, we fill this knowledge gap using two field campaigns that were conducted in the Nantucket Sound at the Cape Wind (CW) platform: the 2003–2009 “CW Historical”, which collected wind measurements on a meteorological tower at three levels (20, 41, and 60 m AMSL) with sonic and cup/vane anemometers, and the 2013–2014 IMPOWR (Improving the Mapping and Prediction of Offshore Wind Resources), which collected high-frequency wind and flux measurements at 12 m AMSL. We tested three different methods to calculate : (1) analytical method, dependent on friction velocity and a stability function ψ; (2) the Charnock relationship between and ; and (3) a statistical method based on wind speed observed at the three levels. The first two methods are physical, whereas the statistical method is purely mathematical. Comparing mean and median of , we find that the median is a more robust statistics because the mean varies by over four orders of magnitude across the three methods and the two campaigns. In general, the median exhibits little seasonal variability and a weak dependency on atmospheric stability, which was predominantly unstable (54–67%). With the goal of providing the most accurate estimates of wind speed near the hub height of modern turbines, the statistical method, despite delivering unrealistic values at times, gives the best estimates of 60 m winds, even when the 5 m wind speed from a nearby buoy is used as the reference. The unrealistic values are caused by nonmonotonic wind speed profiles, occurring about 41% of the time, and should not be rejected because they produce realistic fits. Furthermore, the statistical method outperforms the other two even though it does not need any stability information. In summary, if wind speed data from multiple levels are available, as is the case with vertically pointing floating lidar and meteorological towers, the statistical method is recommended, regardless of the seemingly unrealistic values at times. If multilevel wind speeds are not available but advanced sonic anemometry is available at one level, the analytical method is recommended over Charnock’s. Lastly, if a single, constant value of is sought after to characterize the region, we recommend the median from the statistical method, i.e., , which is typical of rough seas.

Description: The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987–2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. The large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. The frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. This bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. The results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region.

Description: Precipitation and temperature are very important climatic parameters as their changes may affect life conditions. Therefore, predicting temporal trends of precipitation and temperature is very useful for societal and urban planning. In this research, in order to study the future trends in precipitation and temperature, we have applied scenarios of the fifth assessment report of IPCC. The results suggest that both parameters will be increasing in the studied area (Iran) in future. Since there is interdependence between these two climatic parameters, the independent analysis of the two fields will generate errors in the interpretation of model simulations. Therefore, in this study, copula theory was used for joint modeling of precipitation and temperature under climate change scenarios. By the joint distribution, we can find the structure of interdependence of precipitation and temperature in current and future under climate change conditions, which can assist in the risk assessment of extreme hydrological and meteorological events. Based on the results of goodness of fit test, the Frank copula function was selected for modeling of recorded and constructed data under RCP2.6 scenario and the Gaussian copula function was used for joint modeling of the constructed data under the RCP4.5 and RCP8.5 scenarios.

Description: Exploring the impacts of climate change on agriculture is one of important topics with respect to climate change. We quantitatively examined the impacts of climate change on winter wheat yield in Northern China using the Cobb–Douglas production function. Utilizing time-series data of agricultural production and meteorological observations from 1981 to 2016, the impacts of climatic factors on wheat production were assessed. It was found that the contribution of climatic factors to winter wheat yield per unit area (WYPA) was 0.762–1.921% in absolute terms. Growing season average temperature (GSAT) had a negative impact on WYPA for the period of 1981–2016. A 1% increase in GSAT could lead to a loss of 0.109% of WYPA when the other factors were constant. While growing season precipitation (GSP) had a positive impact on WYPA, as a 1% increase in GSP could result in 0.186% increase in WYPA, other factors kept constant. Then, the impacts on WYPA for the period 2021–2050 under two different emissions scenarios RCP4.5 and RCP8.5 were forecasted. For the whole study area, GSAT is projected to increase 1.37°C under RCP4.5 and 1.54°C under RCP8.5 for the period 2021–2050, which will lower the average WYPA by 1.75% and 1.97%, respectively. GSP is tended to increase by 17.31% under RCP4.5 and 22.22% under RCP8.5 and will give a rise of 3.22% and 4.13% in WYPA. The comprehensive effect of GSAT and GSP will increase WYPA by 1.47% under RCP4.5 and 2.16% under RCP8.5.

Description: Ecosystem water use efficiency (WUE) and carbon use efficiency (CUE), as two of the most important ecological indicators of an ecosystem, represent the carbon assimilation rate of unit water consumption and the capacity of transferring carbon from the atmosphere to potential carbon sinks. Revealing WUE and CUE changes and their impact factors is vital for regional carbon-water interactions and carbon budget assessment. Climate affects carbon and water processes differently. Compared to WUE, the variations in CUE in response to climate factors and human activity remain inadequately understood. In this study, ecosystem-level WUE and CUE variations in the Songnen Plain (SNP), Northeast China, during 2001–2015, were investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The relationships between WUE, CUE, main climate factors, and human impacts were explored. The results showed that ecosystem WUE and CUE have fluctuated over time, with regional average values of 1.319 gC·kg−1H2O and 0.516, respectively. Deciduous broad-leaved forests had the highest average WUE but the lowest CUE. The multiyear average CUE of grassland ranked in first place, while the lowest WUE indicated that a lesser capacity of net productivity was generated by the use of limited water supply. WUE and CUE showed a downward trend in most areas of the SNP, indicating that the carbon sequestration capacity of the terrestrial ecosystem became weaker in the past 15 years. Annual precipitation and relative humidity had positive influences on WUE and CUE in more than 60% of the study area. The total annual sunshine duration and annual average temperature negatively affected WUE and CUE in most areas. Human activities had a positive effect on ecosystem WUE changes in the SNP but might inhibit CUE variations. Our findings aid in understanding the biological regulation mechanisms of carbon-water cycle coupling and provide a scientific basis for formulating sustainable regional development strategies and guiding water and land resources management.

Description: Based on hourly precipitation data and FY-2 satellite infrared (IR) digital satellite imagery collected during the warm season from 2005 to 2015 in the Tianshan Mountains and the adjacent areas in Xinjiang, China, the definition of mesoscale convective systems (MCSs) was revised based on short-duration heavy precipitation processes. The spatiotemporal development of MCSs in terms of the initiation, maturation, dissipation, duration, and movement was statistically analyzed. Most mesoscale systems in the area were dominated by meso-β convective systems (MβCSs), which was in line with the annual heavy precipitation frequency. In meso-α convective systems (MαCSs), persistent elongated convective systems (PECSs) occurred more commonly than mesoscale convective complexes (MCCs). MCSs were common in summer, with the peak frequency of MαCS occurrence in June and the peak frequency of MβCS occurrence mainly in July and August. From the perspective of diurnal variations, MCSs initiated in the late afternoon, developed during the evening, and dissipated before midnight. MCSs in general lasted 6∼9 h between June and July and 9∼11 h in August. The MαCSs lasted approximately 14 h, and the MβCSs lasted from 7 h to 12 h. The development and termination stages of MCSs lasted 3∼6 h and 2∼7 h, respectively. In low-elevation areas and on the windward slope of the mountains, MCSs initiated more easily and more frequently over the northern and western slopes than that over the southern and eastern slopes. The central area of the Junggar basin hosted the development of MCSs, but the distribution of the convective systems at different scales varied. During the termination stage, these mesoscale systems were mainly located at the basin edges. In terms of tracks, most MCSs moved eastward under the influence of the westerlies and the MαCSs moved faster but in a more scattered manner than the MβCSs. Additionally, some unusual tracks appeared because of the effects of the underlying surface topography and environmental wind.

Description: The thermal environment is closely related to human well-being. Determinants of surface urban heat islands (SUHIs) have been extensively studied. Nevertheless, some research fields remain blank or have conflicting findings, which need to be further addressed. Particularly, few studies focus on drivers of SUHIs in massive cities with different sizes under various contexts at large scales. Using multisource data, we explored 11 determinants of surface urban heat island intensity (SUHII) for 1449 cities in different ecological contexts throughout China in 2010, adopting the Spearman and partial correlation analysis and machine learning method. The main results were as follows: (1) Significant positive partial correlations existed between daytime SUHII and the differences in nighttime light intensity and built-up intensity between cities and their corresponding villages except in arid or semiarid western China. The differences in the enhanced vegetation index were generally partially negatively correlated with daytime and nighttime SUHII. The differences in white sky albedo were usually partially negatively correlated with nighttime SUHII. The mean air temperature was partially positively correlated with nighttime SUHII in 40% of cases. Only a few significant partial relationships existed between SUHII and urban area, total population, and differences in aerosol optical depth. The explanation rates during daytime were larger than during nighttime in 72% of cases. The largest and smallest rates occurred during summer days in humid cold northeastern China (63.84%) and in southern China (10.44%), respectively. (2) Both the daytime and nighttime SUHII could be well determined by drivers using the machine learning method. The RMSE ranged from 0.49°C to 1.54°C at a national scale. The simulation SUHII values were always significantly correlated with the actual SUHII values. The simulation accuracies were always higher during nighttime than daytime. The highest accuracies occurred in central-northern China and were lowest in western China during both daytime and nighttime.

Description: This study focuses on the characterization of historical drought occurrences in the Horné Požitavie region of Slovakia over the period 1966–2013 using Standardized Precipitation-Evapotranspiration Index (SPEI). Trend analyses were evaluated by the Mann–Kendall (MK) test as well as cumulative sum of rank difference (CRD) test. The results showed that drought occurs in the region regularly (recurrent climate feature), while the trend analysis indicated the trend toward more arid climatic conditions. However, CRD trend analyses showed that the subtrend changed direction toward less drier conditions in the late 1980s and early 1990s. Analyses of SPEI trends in individual months showed a decreasing trend of drought occurrences during the cold months of the year (i.e., October to March), while an increasing trend was indicated from April to August. The evaluation of the impact of drought on agricultural production based on the oilseed rape yield indicated that drought represents a significant natural risk for the agrarian sector of the region. In addition, August value of the SPEI for six months was evaluated as a good indicator of drought impacts on agriculture. The trend analyses revealed no significant increase of drought impacts on agricultural production within the studied period.

Description: This study examined smallholder farmers’ perception about climate change and variability compared with the observed metrological data and their adaptation strategies in response to the perceived impacts of climate change. The multistage sampling method was employed to select 358 rural farmers in Hawzen and Irob districts located in semiarid highlands of Eastern Tigray, northern Ethiopia. Moreover, areal gridded surface monthly rainfall and temperature data between 1983 and 2015 were collected from National Meteorology Agency of Ethiopia. The results revealed that about 98.56 and 92 percent of farmers perceived a decrease in annual rainfall. In addition, 87 and 90 percent of farmers noticed that temperature was increased in Hawzen and Irob districts, respectively. Harmoniously, the modified Mann–Kendall trend test confirmed that annual rainfall was decreased by 32.38 mm and 121.33 mm during the period of analysis. Furthermore, mean annual temperature increased statistically significant () by about 0.40°C and 0.39°C per decade during the period of analysis cognate with the farmers’ perception. To reduce the perceived impacts of climate change, farmers adopted various farm-level adaptation strategies that vary significantly between the two groups. Soil and water conservation, planting trees, crop varieties, changing crop calendar, biological conservation, and irrigation were among the dominant adaptation strategies, respectively, in the study area. The results of this study provide baseline information for local governments, subsequent researchers, and policy-makers in terms of farmers’ perception of climate change and adaptation strategies.

Description: As a method that does not require additional cost, precipitation measurement by microwave links (MLs) has quickly attracted the attention of experts in meteorological, hydrological, and other related fields, of which wet-dry classification by MLs is one of the most important methods. Considering that existing commercial MLs are usually single-path, single-polarization, or low-frequency MLs, this paper uses the C-band ML and analyzes the variation in the receive signal level (RSL) of the C-band ML under the conditions of no rain, drizzle, light rain, and moderate rain. The RSL data are analyzed at different time scales by using long short-term memory (LSTM) network techniques, and then the method for distinguishing parts of the precipitation period by using the RSL from low-frequency MLs is proposed and validated. The results show that wet-dry classification is ideal. The accuracy on each day was higher than 60%, and some days had accuracies that were even higher than 98%. MLs below 10 GHz also had the potential to monitor ground rainfall. This study will broaden the range of available equipment for MLs for precipitation measurement.

Description: Based on the daily temperature data from 26 meteorological stations in the Minjiang River Basin, for 1961 to 2016, the temporal trend and spatial distribution of extreme temperature in this region were analyzed using 16 extreme temperature indices. The results show that in terms of time variation, determined using linear trend analysis and a Mann–Kendall trend test, the warm and day indices mainly show an upward trend while the cold and night indices mainly show a downward trend in the entire basin. Among them, FD0, TN10, and CSDI significantly decrease at −1.3, −2.9, and −1.1 d/10a, respectively. TN90, TX90, SU25, and TR20 significantly increase at 3.0, 2.6, 2.1, and 2.2 d/10a, respectively. The crop growth period in the basin showed a significant increasing trend at 1.4 days/decade, while the diurnal temperature range showed a nonsignificant increasing trend at 0.03 days/decade. On comparing the change range of each index, it was found that the change range of the warm index is greater than that of the cold index, while the change range of the day index is smaller than that of the night index; thus, the change trends of the maximum and minimum temperatures in the whole basin are not obvious. Analysis of the changing trend at each station showed that the relative index of the extreme temperature in the basin has good climatic consistency in terms of spatial distribution. The distributions of the absolute and extreme indices are not uniform, which is consistent with the change in elevation in the basin. Further, the diurnal temperature range in the upper reaches of the basin is greater than that in the middle and lower reaches. However, because of the more obvious upward trends of the day and warm indices in the middle and lower reaches, and the more obvious downward trends of the night and cold indices in the upper reaches, the daily temperature differences in the upper, middle, and lower reaches of the Minjiang River Basin tend to be consistent. Therefore, the precipitation in the Minjiang River Basin shows a significant decreasing trend; thus, the basin shows a trend of drying and warming.

Description: Ozone (O3) flux-based indices are considered better than O3 concentration-based indices in assessing the effects of ground O3 on ecosystem and crop yields. However, O3 flux (Fo) measurements are often lacking due to technical reasons and environmental conditions. This hampers the calculation of flux-based indices. In this paper, an artificial neural network (ANN) method was attempted to simulate the relationships between Fo and environmental factors measured over a wheat field in Yucheng, China. The results show that the ANN-modeled Fo values were in good agreement with the measured Fo values. The R2 of an ANN model with 6 routine independent environmental variables exceeded 0.8 for training datasets, and the RMSE and MAE were 3.074 nmol·m−2·s and 2.276 nmol·m−2·s for test dataset, respectively. CO2 flux and water vapor flux have strong correlations with Fo and could improve the fitness of ANN models. Besides the combinations of included variables and selection of training data, the number of neurons is also a source of uncertainties in an ANN model. The fitness of the modeled Fo was sensitive to the neuron number when it ranged from 1 to 10. The ANN model consists of complex arithmetic expressions between Fo and independent variables, and the response analysis shows that the model can reflect their basic physical relationships and importance. O3 concentration, global radiation, and wind speed are the important factors affecting O3 deposition. ANN methods exhibit significant value for filling the gaps of Fo measured with micrometeorological methods.

Description: Hallasan Mountain is located at the center of Jeju Island, Korea. Even though Hallasan Mountain has a height of just 1,950 m, the temperature during the winter decreases below −20 degrees Celsius. On the contrary, the temperature on the coastal areas remains just above freezing. Therefore, large snowfalls in the mountain and rainfall in the coastal areas are very common in Jeju Island. Most of the rain gauges are available around highly populated coastal areas, and snow measurements are available at just four locations on the coastal areas. Therefore, it is practically impossible to distinguish the rainfall and snowfall in Jeju Island. Fortunately, two radars (Seongsan and Gosan radars) operate on Jeju Island, which fully covers Hallasan Mountain. This study proposes a method of using both the radar and rain gauge information to map the snowy region in Jeju Island, including Hallasan Mountain. As a first step, this study analyzed the Z-R and Z-S relationships to derive a fixed threshold of radar reflectivity to separate snowfall from rainfall, and, in the second step, this study additionally considered the observed rain rate information to implement the problem of using the fixed threshold. This proposed method was applied to radar reflectivity data collected during November 1, 2014, to April 30, 2015, and the results indicate that the method considering both the radar and rain gauge information was satisfactory. This method also showed good performance, especially when the rain rate was very low.

Description: Estimation of raindrop size distribution (DSD) is essential in many meteorological and hydrologic fields. This paper proposes a method for retrieving path-averaged DSD parameters using joint dual-frequency and dual-polarization microwave links of the telecommunication system. Detailed analyses of the rain-induced attenuation calculation are performed based on the T-matrix method. A forward model is established for describing the relation between the DSD and the rain-induced attenuation. Then, the method is proposed to retrieve propagation path DSD parameters based on Levenberg–Marquardt optimization algorithm. The numerical simulation for path-averaged DSD retrieval shows that the RMSEs of three gamma DSD parameters are 0.34 mm−1, 0.81, and 3.21×103 m−3·mm−1, respectively, in rainfall intensity above 30 mm/h. Meanwhile, the method can retrieve the rainfall intensity without the influence of variational DSD. Theoretical analyses and numerical simulations confirm that the method for retrieving path-averaged DSD parameters is promising. The method can complement existing DSD monitoring systems such as the disdrometer and provide high-resolution rainfall measurements with widely distributed microwave links without additional cost.

Description: The study aims to analyze climate variability and farmers’ perception in Southern Ethiopia. Gridded annual temperature and precipitation data were obtained from the National Meteorological Agency (NMA) of Ethiopia for the period between 1983 and 2014. Using a multistage sampling technique, 403 farm households were surveyed to substantiate farmers’ perceptions about climate variability and change. The study applied a nonparametric Sen’s slope estimator and Mann–Kendall’s trend tests to detect the magnitude and statistical significance of climate variability and binary logit regression model to find factors influencing farm households’ perceptions about climate variability over three agroecological zones (AEZs). The trend analysis reveals that positive trends were observed in the annual maximum temperature, 0.02°C/year () in the lowland and 0.04°C/year () in the highland AEZs. The positive trend in annual minimum temperature was consistent in all AEZs and significant (). An upward trend in the annual total rainfall (10 mm/year) () was recorded in the midland AEZ. Over 60% of farmers have perceived increasing temperature and decreasing rainfall in all AEZs. However, farmers’ perception about rainfall in the midland AEZ contradicts with meteorological analysis. Results from the binary logit model inform that farmers’ climate change perceptions are significantly influenced by their access to climate and market information, agroecology, education, agricultural input, and village market distance. Based on these results, it is recommended to enhance farm households’ capacity by providing timely weather and climate information along with institutional actions such as agricultural extension services.

Description: This study applied the remote sensing-based drought index, namely, the Energy-Based Water Deficit Index (EWDI), across Mongolia, Australia, and Korean Peninsula for the period between 2000 and 2010. The EWDI is estimated based on the hydrometeorological variables such as evapotranspiration, soil moisture, solar radiation, and vegetation activity which are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) imageries. The estimated EWDI was compared with the Evaporative Stress Index (ESI), the Vegetation Condition Index (VCI), and the Standardized Precipitation Index (SPI). The correlation coefficients between the drought indices are as follows: 0.73–0.76 (EWDI vs ESI), 0.64–0.71 (EWDI vs VCI), 0.54–0.64 (EWDI vs SPI-3), 0.69–0.71 (ESI vs VCI), 0.55–0.62 (ESI vs SPI-3), and 0.53–0.57 (VCI vs SPI-3). The drought prediction accuracy of each index according to error matrix analysis is as follows: 83.33–94.17% (EWDI), 70.00–91.67% (ESI), 47.50–85.00% (VCI), and 61.67–88.33% (SPI-3). Based on the results, the EWDI and ESI were found to be more accurate in capturing moderate drought conditions than the SPI at different geographical regions.

Description: In this study, the effects of surface air temperature (SAT) and sea surface temperature (SST) changes on typhoon rainfall maximization are analysed. Based on the numerically reproduced Typhoon Maemi, this study tried to maximize the typhoon-induced rainfall by increasing the amount of saturated water vapour in the atmosphere and the amount of water vapour entering the typhoon. Using the Weather Research and Forecasting (WRF) model, which is one of the regional climate models (RCMs), the rainfall simulated by WRF while increasing the SAT and SST to various sizes at initial conditions and boundary conditions of the model was analysed. As a result of the simulated typhoon rainfall, the spatial distribution of total rainfall depth on the land due to the increase combination of SAT and SST showed a wide variety without showing a certain pattern. This is attributed to the geographical location of the Korean peninsula, which is a peninsula between the continent and the ocean. In other words, under certain conditions, typhoons may drop most of the rainfall on the southern sea of the peninsula before landing on the peninsula. For instance, the 6-hour duration maximum precipitation (MP) in Busan Metropolitan City was 472.1 mm when the SST increased by 2.0°C. However, when the SST increased by 4.0°C, the MP was found to be 395.3 mm, despite the further increase in SST. This indicates that the MP at a particular area and the increase in temperature do not have a linear relationship. Therefore, in order to maximize typhoon rainfall, it is necessary to repeat the numerical experiment on various conditions and search for the combination of SAT and SST increase which is most suitable for the target typhoon.

Description: Key microphysical processes whose parameterizations have substantial impacts on the simulation of updraft mass fluxes and their response to aerosol are investigated in this study. For this investigation, comparisons of these parameterizations are made between a bin scheme and a bulk scheme. These comparisons show that the differences in the prediction of cloud droplet number concentration (CDNC) between the two schemes determine whether aerosol-induced invigoration of updrafts or convection occurs. While the CDNC prediction leads to aerosol-induced invigoration of updrafts and an associated 20% increase in the peak value of the updraft-mass-flux vertical profile in the bin scheme, it leads to aerosol-induced suppression of updrafts and an associated 7% decrease in the peak value in the bulk scheme. The comparison also shows that the differences in ice processes, in particular, in the snow loading lead to the different vertical patterns of the updraft-mass-flux profile, which is represented by the peak value and its altitude, between the schemes. Higher loading of snow leads to around 20–30% higher mean peak value and its around 40% higher altitude in the bin scheme than in the bulk scheme. When differences in the CDNC prediction and ice processes are removed, differences in the invigoration and the vertical pattern disappear between the schemes. However, despite this removal, differences in the magnitude of updraft mass fluxes still remain between the schemes. Associated with this, the peak value is around 10% different between the schemes. Also, after the removal, there are differences in the magnitude between cases with different aerosol concentrations for each scheme. Associated with this, the peak value is also around 10% different between those cases for each scheme. The differences between the cases with different aerosol concentrations for each scheme are generated by different evaporative cooling and different intensity of gust fronts between those cases. The remaining differences between the schemes are generated by different treatments of collection and sedimentation processes.

Description: The main objective of this study was to analyze the perception of the influence of various weather conditions on patients with rheumatic pathology. A group of 394 patients, aged between 39 and 87 years and diagnosed with degenerative rheumatic diseases, were interviewed individually by using a questionnaire created specifically for this study. Further on, to assess the relationship between pain intensity and weather conditions, a frequency analysis based on Pearson’s correlation matrix was employed. The most important results are as follows: the great majority of the participants (more than 75%) believe that their rheumatic pain is definitely or to a great extent influenced by different weather conditions; most of the patients reported intensification of their pain with weather worsening, especially when cloudiness and humidity suddenly increase (83.8% and 82.0%, respectively), air temperature suddenly decreases (81.5%), and in fog or rain conditions (81.2%). In our research, alongside simple meteorological variables, we established that complex weather variables such as atmospheric fronts, in particular, the cold ones and winter anticyclonic conditions, greatly intensify the rheumatic pain, whereas summer anticyclonic conditions usually lead to a decrease in pain severity. In terms of relationships between pain intensity and weather conditions, we found the strongest correlations (ranging between 0.725 and 0.830) when temperature, relative humidity, and cloudiness are constantly high.

Description: Surface albedo is one of the key parameters of land surface radiation and energy balance. As surface albedoes for visible and near-infrared solar radiation are quite different, solar radiation partitioning is important to parameterize the total surface albedo and upward solar radiation. In this paper, a surface albedo parameterization scheme was introduced and a solar radiation partitioning method was developed to improve the simulation of the upward solar radiation. The simulation results were validated in a hinterland site of the Taklimakan Desert. The surface albedo is not only associated with the soil moisture, but associated with the solar zenith angle. The solar radiation partitioning method considers the joint influences of cloud cover, near-surface air pressure, and solar zenith angle and was compared with the method using the Simple Biosphere Model version 3 (SiB3). The total albedo depends on the partitioning of the total visible and near-infrared radiations. The results indicate the surface albedo parameterization scheme is important to parameterize the upward solar radiation. The new solar radiation partitioning method could improve the simulation result.

Description: The thermal environment is closely related to human well-being. Diurnal and seasonal variations in surface urban heat islands (SUHIs) have been extensively studied. Nevertheless, interannual changes in SUHIs as well as in land surface temperatures (LSTs) in cities and their corresponding villages remain poorly understood, particularly using data from several continuous years to analyse change rates and corresponding significance levels. Using Aqua/Terra moderate resolution imaging spectroradiometer (MODIS) data for 2003–2013, we explored not only the interannual changes in annual and seasonal mean LSTs in rural and urban regions which were identified based on modified criteria, but also the SUHI intensities (SUHIIs) for these cities. The results showed that most of LSTs and SUHIIs did not change significantly (). Their changes exhibited clear spatiotemporal agglomeration and variation laws. The rural region LST change rates, which exhibited significant changes, were generally highest in the summer, with most of values of 0.1–0.5°C (yr−1) during the daytime across China, except for the Xinjiang autonomous regions, and 0.1–0.2°C (yr−1) during the night-time. The rates were lowest in the winter, with most of values of −0.4 to −0.1°C (yr−1). The rates of daytime SUHIIs with significant changes were generally highest in the summer, with most of values of 0.1–0.3°C (yr−1), and lowest in the winter, even with most of values of −0.4 to −0.1°C (yr−1) in northern central China. During the night-time, most of rates were 0.0–0.1°C (yr−1). In China, most of the changes in the surface thermal environment were harmful to humans at both large national and local urban scales. The changes could lower thermal comfort levels, harm human health, affect human reproduction rates and lives, and increase the energy consumed for refrigeration or heating, thereby increase emissions of greenhouse gases.

Description: The Weather Research and Forecasting model version 3.2.1 with the Lin microphysics scheme was used herein to simulate super typhoon Usagi, which occurred in 2013. To investigate the effect of the concentration of cloud condensation nuclei (CCN) on the development of typhoon Usagi, a control simulation was performed with a CCN concentration of 100 cm−3, together with two sensitivity tests: C10 and C1000, having CCN concentrations of 10 cm−3 and 1000 cm−3, respectively. The path, intensity, precipitation, microphysical processes, and the release of latent heat resulting from the typhoon in all three simulations were analyzed to show that an increase in CCN concentration leads to decreases in intensity and precipitation, an increase of the cloudless area in the eye of the typhoon, a more disordered cloud system, and less latent heat released through microphysical processes, especially the automatic conversion of cloud water into rainwater. Overall, an increase in CCN concentration reduces the total latent heat released during the typhoon suggesting that typhoon modification by aerosol injection may be optimized using numerical simulations to ensure the strongest release of latent heat within the typhoon.

Description: The current study aimed at investigating cycles and the spatial autocorrelation pattern of anomalies of thunderstorms in Iran during different periods from 1961 to 2010. In this analysis, 50-year periods (1961–2010) of thunderstorm codes have been collected from 283 synoptic stations of Meteorological Organization of Iran. The study period has been divided into five different decades (1961–1970, 1971–1980, 1981–1990, 1991–2000, and 2001–2010). Spectral analysis and Moran’s I were used to analyze cycles and the spatial autocorrelation pattern, respectively. Furthermore, in order to conduct the calculations, programming facilities of MATLAB have been explored. Finally, Surfer and GIS were employed to come up with the graphical depiction of the maps. The results showed that the maximum of positive anomalies mainly occurred in the northwestern and western parts of Iran due to their special topography, during all the five studied periods. On the other hand, the minimum of negative anomalies took place in central regions of the country because of lack of appropriate conditions (e.g., enough humidity). Moran’s I spatial analysis further confirmed these findings as Moran’s I depicts the positive and negative spatial autocorrelation patterns in line with negative and positive anomalies, respectively. However, in recent decades, this pattern has experienced a declining trend, especially in southern areas of Iran. The results of harmonic analysis indicated that mainly short-term and midterm cycles dominated Iran’s thunderstorms.

Description: Land-use and land cover changes may have important local, regional, and global climatic impacts by modifying the underlying land surface conditions, which in turn influence the exchange of energy and moisture between the land surface and atmosphere. Many studies have shown that urbanization has contributed to climate warming, and the amount of warming has varied. As the capital of China and one of the world’s megacities, Beijing has experienced rapid urbanization over the past 30 years. In this study, we quantitatively investigated the impacts of urbanization on regional temperatures based on observations from meteorological stations and National Centers for Environmental Prediction (NCEP) reanalysis data and overestimating of the impacts were found. Comparing the temperature trends of land-use types, forest showed stronger inhibitory effects on temperature increase (−0.085°C/10a). Cropland also had a negative effect on climate warming yearly and seasonally, especially in winter (−1.133°C/10a) and spring (−0.299°C/10a). Conversely, the urban area showed strong warming effects (0.438°C/10a). The conversion of cropland to urban land appeared to show the highest warming trend (0.548°C/10a). However, the cooling effect of forest and grassland with high vegetation coverage inhibited climatic warming attributed to rapid urbanization. In addition, planting trees or grass along roadsides and increasing green parks and green roofs can also suppress surface warming. Therefore, the actual warming effects of urbanization on temperatures were overestimated in megacities or urban agglomeration regions. The results showed that the green space and landscape configuration should be considered in urban planning to increase green space and reduce the influence of urban heat island effect.

Description: The focus of the current paper is to explore the influence of meteorological variables on atmospheric CO2 and CH4 mean annual cycles at a rural site. Four variables were investigated: boundary layer height, recirculation factor, trajectory direction, and wind speed modelled at the altitude of the site. Boundary layer height and wind speed were provided by the METeorological data EXplorer (METEX) model. Recirculation factor and trajectory direction were obtained from calculations based on this trajectory model, and a nonparametric procedure was used to obtain a smooth evolution. The main results are higher concentrations obtained during the night, attributed to lower dispersion in this period. The smoothed values of the boundary layer height reached nearly 1200 m AGL during the day in August, and its low values caused high concentrations in spring. During the night, the recirculation factor and wind speed showed a sharp contrast between summer and winter. The average recirculation factor was low, 0.10, and average wind speed was 5.1 m·s−1. Trajectories were directionally distributed in four quadrants. Different tests were performed by selecting values of meteorological variables above or below certain thresholds. The influence of these variables reached values around 6.3 and 0.023 ppm for CO2 and CH4 average concentrations, respectively, during the day when the boundary layer was below 400 m. The main conclusion of this study is that the influence of meteorological variables should not be ignored. In particular, extremely low boundary layer heights may have noticeable effects on both gases.

Description: Spatiotemporal changes in extreme precipitation at local scales in the context of climate warming are overwhelmingly important for prevention and mitigation of water-related disasters and also provide critical information for effective water resources management. In this study, the variability and trends of extreme precipitation in both time and space in the Poyang Lake basin over the period of 1960–2012 are analyzed. Also, changes in precipitation extremes with topography are investigated, and possible causes are briefly discussed. The results show that extreme precipitation over the Poyang Lake basin is intensified during the last 50 years, especially the increasing trends are more significant before the end of the 1990s. Moreover, high contribution rates of extreme precipitation to the total rainfall (40–60%) indicated that extreme precipitation plays an important role to the total water resources in this area. The precipitation extremes also exhibited a significant spatial dependence in the basin. The northeastern and eastern areas are exposed to high risk of flood disaster with the higher frequency of extreme precipitation events. In addition, the distribution of precipitation extremes had a clear dependence on elevation, and the topography is an important factor affecting the variability of extreme precipitation over the Poyang Lake basin.

Description: The threshold exposure time for synthesis of vitamin D was simulated by using a radiative transfer model considering variations in total ozone, cloud, and surface conditions. The prediction of total ozone took the form of an empirical linear regression with the variables of meteorological parameters in the upper troposphere and lower stratosphere and the climatology value of total ozone. Additionally, to consider cloud extinction after the estimation of clear-sky UV radiation using a radiative transfer model simulation, a cloud modification factor was applied. The UV irradiance was estimated at one-hour intervals, and then, to improve the temporal resolution of the exposure time simulation, it was interpolated to a one-minute resolution. Exposure times from the simulation clearly followed seasonal and diurnal cycles. However, upon comparison with observations, biases with large variations were found, and the discrepancy in the exposure time between the observations and simulations was higher in low UV irradiance conditions. The large deviations in the prediction errors for total ozone and the simplified assumption for the cloud modification factor contributed to the large deviations in exposure time differences between the model estimation and observations. To improve the accuracy of the simulated exposure time, improved predictions of total ozone with a more detailed cloud treatment will be essential.

Description: China is suffering severe ambient air pollution in recent decades and particulate matter (PM) has become the major pollutant, especially for PM2.5 and PM10, which have highly raised scholars and policy-makers’ attention in last few years. The existing research has focused on the characteristics of PM2.5 and PM10, respectively, or analyzed the correlation between the two pollutants, while the ratio of PM2.5 to PM10 has been taken less consideration. In this study, daily mean PM2.5 and PM10 mass concentrations in 31 provincial capitals from 2014 to 2016 were used to present the temporal variations and spatial distribution of PM2.5/PM10 ratios among eight economic regions. And then, statistical method and correlation analysis were adopted to investigate the relationship between the ratios and AQI, the rate of change on the ratios, and the impact of meteorological parameters on the ratios. The results indicated that PM2.5/PM10 ratios showed an increasing trend from northwest to southeast due to different economic development and industrial types. The highest values were observed in winter among all regions, and the ratios on weekends were higher than that of on weekdays in most of the regions. Besides, domestic heating in northern China had a significant contribution to the ratios. Moreover, ratios had less changes, and the rate of change was stable in summer. As for air quality, the higher the ratio, the larger the possibility of high AQI so that the air pollution will be more severe. In terms of meteorological factors, the results demonstrated that relative humidity, precipitation, and pressure were the most important factors and had significantly positive impacts, while sunshine duration, temperature, and wind speed had negative effects on the ratios. The findings could identify the pollution sources among PM10 and be helpful for making regulation locally to reduce emission which considers anthropogenic sources and meteorological diffusion simultaneously.

Description: The diurnal variations in summer precipitation over the Yellow River Basin (YRB) are investigated based on the National Centers for Environmental Prediction reanalysis dataset and hourly precipitation data from 481 gauge stations over the YRB during the time period 1981–2013. Three stair steps are identified to represent the upper, middle, and lower reaches of the YRB due to complex topography elevations over the different subregions of the YRB. The summer diurnal precipitation over the YRB shows significant spatial and temporal variations. The diurnal peaks in precipitation over the upper and middle reaches of the YRB occur in the evening and late afternoon, respectively. By contrast, double peaks in diurnal precipitation occur in the early morning and late afternoon over the lower reaches of the YRB. The diurnal peaks in summer precipitation along the YRB have an eastward transition, suggested to be associated with the westerlies transporting water vapor. Differing from the increasing tendency of summer hourly precipitation from west to east across the YRB with topography elevations decreased, a distinct reduction in hourly precipitation is observed over the transition region between the first and second stair steps in the YRB. Further analysis attributes this phenomenon to the regional descending airflow induced by the steep terrain along the slope of the Tibetan Plateau (TP).

Description: The binary interaction is one of the most challenging factors to improve the forecast accuracy of multiple tropical cyclones (TCs) in close vicinity. The effect of binary interaction usually results in anomalous track and variable intensity of TCs. A typical interaction type, one-way influence mode, has been investigated by many studies which mainly focused on the anomalous track and record-breaking precipitation, such as typhoons Morakot and Goni. In this paper, a typical case of this type, typhoons Tembin and Bolaven, occurred in the western North Pacific in August 2012, was selected to study how one typhoon impacts the track and intensity of the other one. The vortex of Tembin or Bolaven and the monsoon circulation were removed by a TC bogus scheme and a low-pass Lanczos filter, respectively, to carry out the numerical experiments. The results show that the presence of monsoon made the binary interaction more complex by affecting the tracks and the translation speeds of the TCs. The influence of Bolaven on the track of Tembin was more significant than the influence of Tembin on the track of Bolaven, and the looping track of Tembin was also affected by the external surrounding circulation associated with Bolaven. The absence of Tembin was not conducive to the development of Bolaven due to stronger vertical wind shear condition and the less kinetic energy being transported to upper troposphere. Note that the above analysis demonstrates the interacting processes between TCs and sheds some light on the prediction of binary TCs.

Description: The standard boxplot is one of the most popular nonparametric tools for detecting outliers in univariate datasets. For Gaussian or symmetric distributions, the chance of data occurring outside of the standard boxplot fence is only 0.7%. However, for skewed data, such as telemetric rain observations in a real-time flood forecasting system, the probability is significantly higher. To overcome this problem, a medcouple (MC) that is robust to resisting outliers and sensitive to detecting skewness was introduced to construct a new robust skewed boxplot fence. Three types of boxplot fences related to MC were analyzed and compared, and the exponential function boxplot fence was selected. Operating on uncontaminated as well as simulated contaminated data, the results showed that the proposed method could produce a lower swamping rate and higher accuracy than the standard boxplot and semi-interquartile range boxplot. The outcomes of this study demonstrated that it is reasonable to use the new robust skewed boxplot method to detect outliers in skewed rain distributions.

Description: Floods are the leading cause of hydrometeorological disasters in East Africa. Regardless of where, when, and how the event has happened, floods affect social security as well as environmental damages. Understanding floods dynamics, their impacts, and management is thus critical, especially in climate risk assessment. In the present study, a flash flood (a case of an episodic hydrological event) which happened on January 11, 2018, in Morogoro, Tanzania, is examined and synthesized. Data were courtesy of the National Oceanic and Atmospheric Administration Global Forecasting System (NOAA GFS) (forecast data), Tanzania Meteorological Agency (TMA), and Sokoine University of Agriculture (for the automatic weather data). With the help of ZyGRIB-grib file visualization software (version 8.01, under General Public License (GNU GPL v3)), the forecast data and patterns of the observation from the automatic weather station (temperatures, wind speed and directions, rainfall, humidity, and pressure) and the long-term rainfall data analysis in the study area made it possible. This study contributes to the knowledge of understanding the changing weather for planning and management purposes. Both forecasts and the observations captured the flash flood event. The rain was in the category of heavy rainfall (more than 50 mm per day) as per the regional guidelines. The synergy between the forecasts and the 30-minute weather observation interval captured the fundamental weather patterns that describe the event. For studying the nature and impacts of flash floods in the region, the integration of automatic weather observation into the systems of national meteorological centers is inevitable. Additionally, as part of an integrated disaster risk reduction effort, there is a need for a review on catchment management strategies.

Description: Long-term automated synoptic observing system (ASOS) data collected from 101 stations over a period of 50 years (1967–2016) were analyzed to investigate the distribution of strong winds on the Korean peninsula by utilizing a statistical method. The Gumbel distribution was used to estimate the wind speed for recurrence periods of 1, 10, 50, 75, and 100 years. For all recurrence periods, the coastal regions experienced higher wind speeds, which exceeded the strong wind advisory level, than the inland and metropolitan regions. The strong winds were predominantly induced by summertime typhoons, especially in the south and west coastal regions. In addition, nontyphoon factors, such as a topographical factor with atmospheric instability in a mountainous coastal region, can cause localized severe weather in the form of strong wind. By performing the weather research and forecasting (WRF) model simulation, an abrupt increase in wind speed up to 20 m·s−1 was reproduced under the condition of onshore prevailing winds heading toward a mountain ridge in a coastal region. Estimation of strong wind spatial distribution can help the region-to-region establishment of an action plan to prepare for damage caused by strong winds.

Description: Agroecosystems are important for food production and conservation of biodiversity while continuing to provide several ecosystem services within the landscape. Despite their economic and ecological benefits, most agroecosystems in Tanzania are degraded at alarming rates. Rapid increase of human population and unprecedented impacts of climate change have influenced depletion of natural resource base within agroecosystem in recent decades compared to what communities have experienced before. Increased food demands owing to population increase have increased pressure on exploitation of land resources including water. Cultivation area and irrigation water demands have increased steadily in the last six decades. Nevertheless, approaches used for water supply have not been improved; thus, water use efficiency in most irrigation schemes is quite poor. Conversely, climate smart agricultural practices are practiced less in Tanzania. There is poor adoption of recommended adaptation among smallholder farmers due to several socioeconomic reasons. One of the key objectives of climate smart agriculture is to improve bio-geochemical interactions within landscape and decrease competition of natural resources between humans and other component of agroecosystems. This underscores the assumptions that most cropping systems in Tanzania are not managed sustainably. Moreover, comprehensive assessment of hydrological dynamics within smallholder farming in Tanzania is highly lacking. Therefore, actual causes and extent of water resources depletion are largely unknown among stakeholders. In most tropical landscapes, water resources degradation is influenced by interaction of both anthropogenic and biophysical factors operating at different times and space scales. As the capacity of water-supplying sources continues to decline, Tanzania needs profound changes in agricultural production systems in order to nourish the growing human population. This calls for strategic approaches that have wider adaptability. A literature survey study with the following objectives was conducted (i) to assess current state of agricultural water use and irrigation activities in Tanzania and (ii) to determine major constraints for sustainable water management and identify appropriate adaptation measures for their improvement across diverse cropping systems.

Description: Although tropical cyclone (TC) rain fields assume varying spatial configurations, many studies only use areal coverage to compare TCs. To provide additional spatial information, this study calculates metrics of closure, or the tangential completeness of reflectivity regions surrounding the circulation center, and dispersion, or the spread of reflectivity outwards from the storm center. Two hurricanes that encountered different conditions after landfall are compared. Humberto (2007) experienced rapid intensification (RI), stronger vertical wind shear, and more moisture than Jeanne (2004), which was more intense, weakened gradually, and became extratropical. A GIS framework was used to convert radar reflectivity regions into polygons and measure their area, closure, and dispersion. Closure corresponded most closely to storm intensity, as the eye became exposed when both TCs weakened to tropical storm intensity. Dispersion increased by 10 km·hr−1 as both TCs developed precipitation along frontal boundaries. As closure tended to change earlier than dispersion and area, closure may be most sensitive to subtle changes in environmental conditions, particularly as the storm’s core experiences the entrainment of dry air and erodes. Displacement provided a combined radial and tangential component to the location of the rainfall regions to confirm placement along the frontal boundaries. Examining area alone cannot reveal these patterns. The spatial metrics reveal changes in TC structure, such as the lag between onset of RI and maximum closure, which should be generalizable to TCs experiencing similar conditions. Future work will calculate these metrics for additional TCs to quantify structural changes in response to their surrounding environment.

Description: The characteristics of the wind vertical profile over the coast of Cotonou during wind convective diurnal cycle were explored in this study. Wind data at 10 m above the ground and the radiosonde data in the lower 60 m of the surface boundary layer were used over the period from January 2013 to December 2016. Based on Monin–Obukhov theory, the logarithmic and power laws have allowed characterizing the wind profile. The error estimators of the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) were, respectively, evaluated at 0.025; 0.016 (RMSE; MAE) and 0.018; 0.015. At the site of Cotonou, the atmosphere is generally unstable from 09:00 to 18:00 MST and stable for the remainder of the time. The annual mean value of the wind shear coefficient is estimated at 0.20 and that of the ground surface roughness length and friction velocity are, respectively, of 0.007 m, 0.38 m·s−1. A comparative study between the wind extrapolation models and the data was carried out in order to test their reliability on our study site. The result of this is that whatever the time of the year is, only the models proposed (best fitting equation) are always in good agreement with the data unlike the other models evaluated. Finally, from the models suitable for our site, the profile of wind convective diurnal cycle was obtained by extrapolation of the wind data measured at 10 m from the ground. The average wind speed during this cycle is therefore evaluated to 8.07 m·s−1 for August which is the windiest month and to 4.98 m·s−1 for the least windy month (November) at 60 m of the ground. Considering these results, we can so consider that the site of Cotonou coastal could be suitable for the installation of wind turbines.

Description: This study analyzed the long-term memory (LTM) in precipitation over Bénin synoptic stations from 1951 to 2010 using the detrended fluctuation analysis (DFA) method. Results reveal the existence of positive long-term memory characteristic in rainfall field. DFA exponent values are different regarding the concerned synoptic stations, reflecting the effect of geographical position and climate on the LTM. These values were related to the type of climate. The best DFA1-4 method depends on the geographical position of the studied station. However, DFA2 is generally the best in terms of spatial average from DFA1 to DFA4. In Bénin synoptic stations, except the Parakou station, the long-term temporal correlations are systematically the source of multifractality in rainfall. Except Natitingou, the strength of long-term memory characteristic decreases each twenty years in the study period. Considering the fractal approach, our results show that the subperiod 1991–2010 is not really a transition period as shown before. Thus, the drought is prolonging until 2010. So, fractal theory reveals more Bénin climatic characteristics.

Description: Tornadoes are violent and destructive natural phenomena that occur on a local scale in most regions around the world. Severe storms occasionally lead to the formation of mesocyclones, whose direction or sense of rotation is often determined by the Coriolis force, among other factors. In the Northern Hemisphere, more than 99% of all tornadoes rotate anticlockwise. The present research shows that, in topographically complex regions, tornadoes have a different probability of rotating clockwise or anticlockwise. Our ongoing research programme on tornadoes in Mexico has shown that the number of tornadoes is significantly higher than previously thought. About 40% of all tornadoes occur in the complex topographic region of the Trans-Mexican Volcanic Belt. Data collected (from Internet videos) on the rotation of tornadoes formed in this region showed that about 50% of them rotated in a clockwise direction, contradicting tornado statistics for most of North America. Time series of the helicity parameter showed that tornadoes formed in topographically complex areas exhibited different behaviours compared to those formed in plains that are related with supercell systems.

Description: Evaluation of different reanalysis precipitation datasets is of great importance to understanding the hydrological processes and water resource management practice in the Qinling-Daba Mountains (QDM), located at the eastern fringe of the Tibetan Plateau. Although the evaluation of satellite precipitation data in this region has been performed, another kind of popular precipitation product-reanalysis dataset has not been assessed in depth. Three popular reanalysis precipitation datasets, including ERA-Interim Reanalysis of European Centre for Medium Forecasts (ERA-Interim), Japanese 55-year Reanalysis (JRA-55), and National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis-1 (NCEP/NCAR-1) were evaluated against rain gauge data over the Qinling-Daba Mountains from 2000 to 2014 on monthly, seasonal, and annual scales. Different statistical measures based on the Correlation Coefficient (CC), relative BIAS (BIAS), Root-Mean-Square Error (RMSE), and Mean Absolute Error (MAE) were adopted to determine the performance of the above reanalysis datasets. Results show that ERA-Interim and JRA-55 have good performance on a monthly scale and annual scale. However, the NCEP/NCAR-1 has the least BIAS with the observed precipitation in annual scale in QDM. All reanalysis datasets performed better in spring, summer, and autumn than in winter. The advantages of involving more precipitation observation stations was probably the main reason of the different performance of three precipitation reanalysis products, and the benefit of a four-dimensional variational analysis model over a three-dimensional variational analysis model may be another reason. The evaluation suggested that ERA-Interim is more suitable for study the precipitation and water cycles in the QDM.

Description: Understanding errors in surface air temperature (SAT) data and related uncertainties is crucial for climate studies because of their impact on the accuracy of statistical inferences in scientific conclusions. In recent decades, considerable research has focused on the trends and evolution of SAT on the Tibetan Plateau (TP). However, assessment of the uncertainties in SAT change on the TP has not been done adequately, which is of considerable importance for climate research. Using station-observed SAT data from the TP, this study estimates long-term variations and trends of sampling error variances in gridded monthly SAT data over recent decades. Results revealed large sampling error variances in northern and western parts of the TP but small variances in eastern, southern, and central areas. The sampling error variances also exhibited strong monthly variations with maximum errors in winter and minimum values in summer. Furthermore, spatial distributions of the trends of seasonal and annual mean sampling error variances were found distributed unevenly with decreasing trends found mainly in central and southern parts of the TP and increasing trends in northeastern, southeastern, and northwestern areas. Additionally, differences were also found in the trends of seasonal and annual mean sampling error variances on various timescales.

Description: The Chinese Academy of Meteorological Sciences Lightning Nowcasting and Warning System (CAMS_LNWS) was designed to predict lightning within the upcoming 0-1 h and provide lightning activity potential and warning products. Multiple remote sensing data and numerical simulation of an electrification and discharge model were integrated in the system. Two core algorithms were implemented: (1) an area identification, tracking, and extrapolating algorithm and (2) a decision tree algorithm. The system was designed using a framework and modular structure, and integrated warning methods were applied in the warning program. Two new algorithms related to the early warning of the first lightning and thunderstorm dissipation were also introduced into the system during the upgrade process. Thunderstorms occurring in Beijing, Tianjin, and Hebei during 2016-2017 were used to evaluate the CAMS_LNWS by the low-frequency cloud to ground lightning detection data, and the results showed that the system has good forecasting and warning ability for local lightning activities. The TS score in 0-1 h ranged from 0.11 to 0.32, with a mean of 0.20. Operational experiments and promotional work for the CAMS_LNWS are now in progress.

Description: Land surface evaporation is not only an important parameter in natural land surface modeling, but a crucial important parameter in urban hydrology modeling. A whole-layer soil evaporation scheme was developed in the integrated urban land model (IUM) to improve the soil evaporation simulation. The impervious surface evaporation (ISE) was used as a component of urban water balance equation. In this paper, the integrated urban land model was validated at one desert site and six urban road sites to emphasize the improvement in the evaporation simulations for arid and urban areas. A sensitivity analysis was implemented in seven basins to expand the utility of the whole layer soil evaporation scheme. For the urban road sites, the validation results indicate that imperious surface evaporation (ISE) plays a crucial role in road surface temperature (RST) simulations on rainy days. For the desert site, the validation results show that the inner layer evaporation is very important in arid regions. For the basins, the analysis results indicate that the relative monthly mean differences in the evapotranspiration (ET) between the simulations with (IUM) and without (Common Land Model (CoLM)) considering the inner layer evaporation range from −8% to 8%, which is proportional to the degree of dryness. In arid areas, especially deserts, the inner layer soil evaporation could not be neglected.

Description: An observational and simulation study of a tornado event in Hong Kong that occurred in the morning of 29 August 2018 is documented in this paper. Rotating airflow associated with the tornado is well captured by the Doppler velocity from a Terminal Doppler Weather Radar (TDWR) in Hong Kong. The Doppler velocity patterns show the typical signature of a velocity couplet associated with a meso/microcyclone, and for most part of its lifetime, it captures clearly the evolution with time. Weather radar echoes of those thunderstorms inducing the current tornado, as well as the meso/microcyclone itself, are also successfully reproduced in a real-time simulation by a fine-resolution numerical weather prediction (NWP) model initialised 3 hours earlier, albeit with a time lag of about 15 minutes when compared to the actual event. The model simulation displays some interesting features of the cyclone, including the vertical structure of horizontal and vertical velocities and cloud liquid water content, which are consistent with literature that accounts in other parts of the world. The vertical profile of maximum radial velocity associated with the velocity couplet also compares well between the actual weather radar observation and numerical simulation. The results in this paper could serve as an interesting reference for both meteorologists and wind engineers, also demonstrating the power of very high-resolution NWP in predicting such events in a real-time fashion.

Description: Evapotranspiration (ET) is a significant component in the water cycle, and the estimation of it is imperative in water resource management. Regional ET can be derived by using remote sensing technology which combines remote sensing inputs with ground-based measurements. However, instantaneous ET values estimated through remote sensing directly need to be converted into daily totals. In this study, we attempted to retrieve daily ET from remotely sensed instantaneous ET. The study found that the Gaussian fitting curve closely followed the ET measurements during the daytime and hence put forward the Gaussian fitting method to convert the remotely sensed instantaneous ET into daily ETs. The method was applied to the middle reaches of Heihe River in China. Daily ETs on four days were derived and evaluated with ET measurements from the eddy covariance (EC) system. The correlation between daily ET estimates and measurements showed high accuracy, with a coefficient of determination (R2) of 0.82, a mean average error (MAE) of 0.41 mm, and a root mean square error (RMSE) of 0.46 mm. To make more scientific assessments, percent errors were calculated on the estimation accuracy, which ranged from 0% to 18%, with more than 80% of locations having the percent errors within 10%. Analyses on the relationship between daily ET estimates and land use status were also made to assess the Gaussian fitting method, and the results showed that the spatial distribution of daily ET estimates well demonstrated ET differences caused by land use types and was intimately linked with the vegetation pattern. The comparison between the Gaussian fitting method and the sine function method and the ETrF method indicated that results derived through the Gaussian fitting method had higher precision than that obtained by the sine function method and the ETrF method.

Description: We study summer heat waves and winter cold spells and their links to atmospheric circulation in an ensemble of EURO-CORDEX RCMs in Central Europe. Results of 19 simulations were compared against observations over 1980–2005. Atmospheric circulation was represented by circulation types and supertypes derived from daily gridded mean sea level pressure. We examined observed and simulated characteristics of hot and cold days (defined using percentiles of temperature anomalies from the mean annual cycle) and heat waves and cold spells (periods of at least three hot/cold days in summer/winter). Although the ensemble of RCMs reproduces on average the frequency and the mean length of heat waves and cold spells relatively well, individual simulations suffer from biases. Most model runs have an enhanced tendency to group hot/cold days into sequences, with several simulations leading to extremely long heat waves or cold spells (the maximum length overestimated by up to 2-3 times). All simulations also produce an extreme winter season with (often considerably) higher number of cold days than in any observed winter. The RCMs reproduce in general the observed circulation significantly conducive to heat waves and cold spells. Zonal flow reduces the probability of temperature extremes in both seasons, while advection of warm/cold air from the south-easterly/north-easterly quadrant plays a dominant role in developing heat waves/cold spells. Because of these links, the simulation of temperature extremes in RCMs is strongly affected by biases in atmospheric circulation. For almost all simulations and all circulation supertypes, the persistence of supertypes is significantly overestimated (even if the frequency of a given supertype is underestimated), which may contribute to development of too-long heat waves/cold spells. We did not identify any substantial improvement in the EURO-CORDEX RCMs in comparison to previous ENSEMBLES RCMs, but the patterns of the biases are generally less conclusive as to general RCMs’ drawbacks.

Description: Climate change directly impacts the hydrological cycle via increasing temperatures and seasonal precipitation shifts, which are variable at local scales. The water resources of the Upper Yangtze River Basin (UYRB) account for almost 40% and 15% of all water resources used in the Yangtze Basin and China, respectively. Future climate change and the possible responses of surface runoff in this region are urgent issues for China’s water security and sustainable socioeconomic development. This study evaluated the potential impacts of future climate change on the hydrological regimes (high flow (Q5), low flow (Q95), and mean annual runoff (MAR)) of the UYRB using global climate models (GCMs) and a variable infiltration capacity (VIC) model. We used the eight bias-corrected GCM outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) to examine the effects of climate change under two future representative concentration pathways (RCP4.5 and RCP8.5). The direct variance method was adopted to analyze the contributions of precipitation and temperature to future Q5, Q95, and MAR. The results showed that the equidistant cumulative distribution function (EDCDF) can considerably reduce biases in the temperature and precipitation fields of CMIP5 models and that the EDCDF captured the extreme values and spatial pattern of the climate fields. Relative to the baseline period (1961–1990), precipitation is projected to slightly increase in the future, while temperature is projected to considerably increase. Furthermore, Q5, Q95, and MAR are projected to decrease. The projected decreases in the median value of Q95 were 21.08% to 24.88% and 16.05% to 26.70% under RCP4.5 and RCP8.5, respectively; these decreases were larger than those of MAR and Q5. Temperature increases accounted for more than 99% of the projected changes, whereas precipitation had limited projected effects on Q95 and MAR. These results indicate the drought risk over the UYRB will increase considerably in the future.

Description: The rainfall and temperature conditions are evaluated for the first time during the 1989–2006 period, in six main cocoa production areas (Abengourou, Agboville, Daloa, Dimbokro, Guiglo, and Soubre) of Côte d’Ivoire using data from SODEXAM (ground-based observation) and the ex-CAISTAB. Statistical analysis shows an important sensitivity of cocoa production to rainfall conditions in all regions. It is worth noting that only the major rainy season from April to July and the rainfall amount of the little dry season from August to September affect the cocoa production for an 80% confidence level. This influence varies from one cacao production area to another. Moreover, the effects related to temperature on the cocoa yield seem to represent a smaller contribution of climate impact than those related to precipitation during the studied period. The temperature change remains in the acceptable range of values, between 25°C and 29°C, which is a favorable condition for cocoa growing. These findings are obtained despite the significant contributions from nonclimatic factors, to year-to-year variability in cocoa production.

Description: Temporal and spatial variations in reference evapotranspiration (ET0) and aridity index (AI) can be used as important indexes for understanding climate change and its effects on ecosystem stability. Thus, in this work, we comprehensively investigated 71 meteorological stations in Northeast China from 1965 to 2017 to analyze the spatial-temporal variation and trend of ET0 and AI using the nonparametric Mann–Kendall test, the linear regression, and the Morlet wavelet methods. The results elucidated that ET0 for Northeast China as a whole exhibited a decrease at a rate of −1.97 mm/yr, AI declined at a rate of −0.01/yr during 1965–2017, and approximately 94% stations showed a decrease trend. Spatially, the high values of AI and ET0 were primarily at the western part of the study area except for the Heilongjiang province, and the stations showing low values were mainly distributed in the central and eastern part. The decreasing trends for AI were more obvious in the eastern part compared with the western part over the study region. The abrupt changes in AI occurred in 2005 and 2007, whereas only one abrupt change for ET0 occurred in 1995. For annual ET0, there were periods of 3, 7, 11, and 15 yr, and there existed periods of 1, 7, 11, and 13 yr for annual AI. The correlation coefficients implied wind speed and precipitation were the dominant meteorological factors resulting in the ET0 and AI decrease, respectively. Additionally, the change of the Indian summer monsoon index (ISMI) may also contribute to the weakened AI in the study area. Nevertheless, further investigation is still required to clarify the mechanisms for AI and ET0 variations in the future.

Description: This study was aimed at presenting a continuous and spatially coherent picture of ammonia (NH3) distribution over the Indo-Gangetic Plain (IGP) by exploiting satellite observations. Atmospheric columns of ammonia were mapped over South Asia by using TES observations on board NASA’s Aura satellite. Monthly mean data were used to identify emission sources of atmospheric ammonia across the South Asian region. Data were analysed to explore temporal trends, seasonal cycles, and hot spots of atmospheric ammonia within the study area. The results show that the IGP region has the most ammonia concentrations in terms of column densities, and hence this region has been identified as an ammonia hot spot. This is attributed majorly to extensive agricultural activity. Time series showed a slight increase in ammonia column densities over the study area from 2004 to 2011. Different seasonal cycles were identified across the IGP region with maximum NH3 columns observed during the month of July in most of the subregions. Seasonality in an ammonia column is driven by different cropping patterns and meteorological conditions in the IGP subregions. Global emission inventories of atmospheric ammonia were largely overestimating as compared to satellite observations.

Description: The interannual variability of autumn rainfall in Southeast China (SEC) is significant, with two major modes, namely, monopole and dipole modes. It is found that the monopole mode is closely related to EP ENSO-like sea surface temperature anomaly (SSTA), and the dipole mode is related to CP ENSO-like SSTA. During the warm phase of EP ENSO-like SSTA, an anomalous anti-Walker circulation emerges in the tropical Pacific, with an anomalous subsiding during 110°E–120°E and an anomalous ascending branch in SEC. These two branches of anomalous current are in the same longitude and form a closed meridional circulation. Besides, there also exists an anticyclone anomaly in the Northwest Pacific (NWP), transporting water vapor into SEC. These circulation configurations induced by the warm phase of EP ENSO-like SSTA are consistent with those of monopole mode positive anomaly year. The good correspondence between EP ENSO warm event and the positive monopole mode also helps to support the corresponding relationship between the EP ENSO-like SSTA and monopole mode of SEC autumn rainfall. After the diagnosis of the perturbation omega equation, the anomalous subsiding branch over SEC, as the key link of EP ENSO-like warm phase SSTA exerting impact on the monopole mode during positive anomaly year, is mainly related with the anomalous relative vorticity advection transported by basic zonal wind and temperature advection transported by meridional wind anomaly. As for the dipole mode, it is related to the CP ENSO-like SSTA, but the corresponding relationship is weaker than that of the monopole mode and EP ENSO-like SSTA. In special, during the warm phase of CP ENSO-like SSTA, an anomalous cyclone appears in the NWP and prevailing sinking motion over SEC, both of which favors the appearance of positive anomaly of the dipole mode. Specially, the local anomalous vertical motion mainly depends on anomalous relative vorticity transported by basic meridional wind. Generally speaking, the monopole (dipole) mode is closely associated with the EP (CP) ENSO-like SSTA, demonstrating some correspondence.

Description: In this study, we analyzed the meteorological processes associated with 2018 tropical cyclone No. 14, “Yagi.” TC Yagi continued moving northeastward after losing its numerical designation from the National Meteorological Center of the China Meteorological Administration (CMA) because of weakening and then restrengthened when it moved over the Bohai Sea, inducing an ocean gale on 14-15 August 2018. The results of our investigation revealed that the continued northeastward movement of Yagi on 14 August was related to the divergence of the upper-level westerly jet stream, the northward shift of the subtropical high in the midtroposphere, as well as the steering flow and asymmetrical air flow around the disturbance itself in the lower troposphere. The enhancement of Yagi over the Bohai Sea on the night of 14 August was related to the decrease of friction over the ocean and the increase of diabatic heating from the sea surface flux. The wind speed increased to a maximum when the depression moved over the Bohai Sea, an occurrence that was not only due to the enhancement of the cyclone itself but also due to the flow of cold air from high latitudes along the north side of the Bohai Sea. The behavior of the cold air was related to the shift of the convergence zone in the upper-level westerly jet at 200 hPa, long-wave troughs and ridges at 500 hPa, and terrain effects. Thus, the gale development in the Bohai Sea was due to both the enhancement of tropical cyclone Yagi after it moved over the ocean and the flow of cold air from high latitudes.

Description: There are continuous precipitation systems moving eastward from the Tibetan Plateau to the middle and lower reaches of the Yangtze-Huai River during the Mei-yu period. We selected 20 typical Mei-yu front precipitation cases from 2010 to 2015 based on observational and reanalysis data and studied the characteristics of their environmental fields. We quantitatively analyzed the transport and sources of water vapor in the rainstorms using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT_4.9) model. All 20 Mei-yu front precipitation cases occurred in a wide region from the Tibetan Plateau to the Yangtze-Huai River. The South Asian high and upper level jet stream both had strong intensities during the Mei-yu front rainstorm periods. Heavy rainfall mainly occurred in the divergence zone to the right of the high-level jet and in the convergence zone of the low-level jet, where strong vertical upward flows provided the dynamic conditions required for heavy rainfall. The water vapor mainly originated from the Indian Ocean, Bay of Bengal, and South China Sea. 52% of the air masses over the western Tibetan Plateau originated from Central Asia, which were rich in water vapor. The water vapor contribution at the initial position was only 41.5% due to the dry, cold air mass over Eurasia, but increased to 47.6% at the final position. Over the eastern Tibetan Plateau to the Sichuan Basin region, 40% of the air parcels came from the Indian Ocean, which was the main channel for water vapor transport. For the middle and lower reaches of the Yangtze River, 37% of the air parcels originated from the warm and humid Indian Ocean. The water vapor contribution at the initial position was 38.6%, but increased to 40.2% after long-distance transportation.

Description: Recurrent extreme drought and flood in Ethiopia lead to more economic loss. This study examines change and trends of 21 climate extremes of temperature and precipitation over Ethiopia by using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on the records of observed meteorological data and the future projected from the CMIP5 model under RCP 4.5 and RCP 8.5 scenarios. The results of the seasonal standardized rainfall anomaly and EOF analysis show a decreasing rainfall in JJAS season and significant variability in the FMAM season. The first mode of EOF in FMAM shows that 49.6% was mostly negative with a high amount of variability. The observed precipitation extreme of annual total precipitation (PRCPTOT), consecutive wet days (CWD), and the number of heavy precipitation days (R10) show a decreasing trend, and consecutive dry days (CDD) shows an increasing trend. Additionally, temperature extremes like tropical nights (TR20) and daily maximum and minimum temperatures show a significantly increasing trend. The projected precipitation extremes of CWD, PRCPTOT, very wet day annual total (R95p), and the number of heavy precipitation days (R10) show a decreasing trend. CDD shows longer periods of dryness and a substantial increase which is conducive to the increase of drought. The projected temperature extremes of the warm spell duration indicator (WSDI), daily maximum temperature (TXx) and daily minimum temperature (TNx), summer days (SU25), and tropical nights (TR20) show an increasing trend, while the diurnal temperature range shows a decreasing trend. The projected changes in temperature and precipitation extremes are likely to have significant negative impacts on various socioeconomic activities over Ethiopia. These results highlight the need for planning and developing effective adaptation strategies for disaster prevention.

Description: Cloud vertical structures over the Tibetan Plateau (TP) and Eastern China Plains (ECP) were analyzed by using data in rainy seasons from 2006 to 2009, in order to clarify the cloud development over adjacent regions but with distinct topographies. Results indicate that the largest occurrences of cloud top height over the TP are at 7-8 km above mean sea level, which is about 4 km lower than that over the ECP. Mixed-phase clouds dominated more than 30% over the TP, while it is lower than 10% over the ECP. The infrequent mixed-phase clouds over the ECP are attributed to the unique dynamic and moisture situations over the downstream areas of the TP. Ice clouds have similar occurrences over the two regions. The prominent distinctions are manifested by the probability density of cloud thickness. The probability density of cloud thickness around 4–8 km is about 2% higher over the TP than the ECP. However, there is almost no ice cloud thicker than 10 km over the TP, while it is about 1% over the ECP. Compared with those over the ECP, every cloud layer within multilayered clouds is generally higher and thinner over the TP, which is closely related to the elevated surface and the resulting thinner troposphere. The significant differences in cloud vertical structures between the TP and the ECP present in this study emphasize that topographical characteristics and the resulting moisture and circulation conditions have strong impacts on the cloud vertical structures.

Description: This study evaluates the performances of all forty different global climate models (GCMs) that participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for simulating climatological temperature and precipitation for Southeast Asia. Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. The results show that the performances of different GCMs vary greatly. CNRM-CM5-2 performs best among the 40 GCMs, where its total error is 3.25 times less than that of GCM performing worst. The performance of CNRM-CM5-2 is compared with those of the ensemble average of all 40 GCMs (40-GCM-Ensemble) and the ensemble average of the 6 best GCMs (6-GCM-Ensemble) for four categories, i.e., temperature only, precipitation only, land only, and sea only. While 40-GCM-Ensemble performs best for temperature, 6-GCM-Ensemble performs best for precipitation. 6-GCM-Ensemble performs best for temperature and precipitation simulations over sea, whereas CNRM-CM5-2 performs best over land. Overall results show that 6-GCM-Ensemble performs best and is followed by CNRM-CM5-2 and 40-GCM-Ensemble, respectively. The total errors of 6-GCM-Ensemble, CNRM-CM5-2, and 40-GCM-Ensemble are 11.84, 13.69, and 14.09, respectively. 6-GCM-Ensemble and CNRM-CM5-2 agree well with observations and can provide useful climate simulations for Southeast Asia. This suggests the use of 6-GCM-Ensemble and CNRM-CM5-2 for climate studies and projections for Southeast Asia.

Description: Eleven tropical cyclones that landed in Guangdong Province since 2012 and experienced strengthening or weakening over the offshore area were studied. Since the structure of the tropical cyclone boundary layer significantly influences the variation of the intensity of the cyclone, continuous observations of the wind profile radar at a coastal radar station in Guangdong Province were combined with aircraft observation data of the No. 1604 “Nida” cyclone to analyse the variations in the distributions of the radial wind, tangential wind, and angular momentum in the typhoon boundary layer and the similarities and differences between the boundary layers of the 11 tropical cyclones during the strengthening or weakening of their intensities. The analysis results show that the presence of the supergradient wind and the enhancement effect of the radial inflow play important roles in enhancing the intensity of a tropical cyclone. The observations indicate that when the tangential wind velocity in the maximum wind velocity radius reaches the velocity of the supergradient wind and when the radial inflow either gradually increases towards the centre of the tropical cyclone or gradually covers the entire boundary layer, the angular momentum tends to be shifted towards the centre. At this time, the maximum radial inflow, maximum tangential wind, and maximum angular momentum are in the same height range in the vertical direction. When a strong radial outflow occurs in the boundary layer of a tropical cyclone or the area with maximum wind velocity is located in the air outflow, the angular momentum cannot easily be transported towards the centre of the typhoon. Therefore, the spatial configuration of the three physical quantities will determine future changes in the intensity of tropical cyclones. The scope of the results presented here is limited to the 11 selected cases and suggests extending the analysis to more data.

Description: A Multi-Model Ensemble (MME) based seasonal rainfall forecast customization tool called FOCUS was developed for Myanmar in order to provide improved seasonal rainfall forecast to the country. The tool was developed using hindcast data from 7 Global Climate Models (GCMs) and observed rainfall data from 49 meteorological surface observatories for the period of 1982 to 2011 from the Department of Meteorology and Hydrology. Based on the homogeneity in terms of the rainfall received annually, the country was divided into six climatological zones. Three different operational MME techniques, namely, (a) arithmetic mean (AM-MME), (b) weighted average (WA-MME), and (c) supervised principal component regression (PCR-MME), were used and built-in to the tool developed. For this study, all 7 GCMs were initialized with forecast data of May month to predict the rainfall during June to September (JJAS) period, which is the predominant rainfall season for Myanmar. The predictability of raw GCMs, bias-corrected GCMs, and the MMEs was evaluated using RMSE, correlation coefficients, and standard deviations. The probabilistic forecasts for the terciles were also evaluated using the relative operating characteristics (ROC) scores, to quantify the uncertainty in the GCMs. The results suggested that MME forecasts have shown improved performance (RMSE = 1.29), compared to the raw individual models (ECMWF, which is comparatively better among the selected models) with RMSE = 4.4 and bias-corrected RMSE = 4.3, over Myanmar. Specifically, WA-MME (CC = 0.64) and PCR-MME (CC = 0.68) methods have shown significant improvement in the high rainfall (delta) zone compared with WA-MME (CC = 0.57) and PCR-MME (CC = 0.56) techniques for the southern zone. The PCR method suggests higher predictability skill for the upper tercile (ROC = 0.78) and lower tercile categories (ROC = 0.85) for the delta region and is less skillful over lower rainfall zones like dry zones with ROC = 0.6 and 0.63 for upper and lower terciles, respectively. The model is thus suggested to perform relatively well over the higher rainfall (Wet) zones compared to the lower (Dry) zone during the JJAS period.

Description: This study proposed an instantaneous summer air temperature (Tair) estimation model using the Himawari-8 Advanced Himawari Imager (AHI) brightness temperatures (BTs) in split-window channels and other auxiliary data. Correlation analysis and stepwise linear regression were used to select the predictors for Tair estimation. Nine predictors such as AHI BTs in channels 14 and 15, elevation, precipitable water vapor (PWV), and relative humidity (RH) were finally selected. Stepwise linear regression and neural network (NN) methods were applied to construct summer Tair estimation models over China, respectively. The estimated Tair by linear and NN models was evaluated using the observed Tair from 272 meteorological stations over China. The results showed that AHI BTs in channels 14 and 15, elevation, PWV, and RH were more important for Tair estimation than other predictors. The accuracy of the NN models was better than the linear models. The correlation coefficient (R), root mean square error (RMSE), and bias were 0.97, 1.72°C, and 0.04°C, respectively, for the NN model and were 0.89, 3.28°C, and 0.07°C, respectively, for the linear model. About 75.6% of the Tair differences by the NN model were within 2.0°C, and even 45.8% were within 1.0°C. The performance of the Tair estimation model for each site was also investigated, and the accuracy of Tair estimation in southeast China is better than northwest China.

Description: The study focuses on the transport of aerosol particles resulting from biomass burning in central South America towards the megacity of Buenos Aires by the South American Low-Level Jet. In particular, the cases are studied in which the exit area of the Jet reaches the La Plata Basin with no precipitation associated, herein called Chaco Jet 1 (CJ1), which could remove aerosols from the atmosphere on their way towards the city. CJ1 events registered within the five-year period of 2001–2005 are examined along with changes in the optical properties of aerosols over the city from measurements from the Aerosol Robotic Network (AERONET) site. Three-dimensional backward trajectories of CJ1 were obtained to verify the connection between the receptor site and the biomass-burning source region. A cluster analysis of the trajectories allows further characterizing the features and impacts of regionally transported aerosols. A subsample of days on which impacts of the contribution of biomass burning could have occurred, showed a statistically significant increase in aerosol optical depth and Ångström exponent, reflected by an increase in the peak of the derived volume size distribution in the fine fraction size range, which also shifts slightly towards bigger radii. The days with AOD greater than 0.15 show overall behaviour like other urban sites with pollution of different origins. The evaluation of the selected data reveals that higher values of AOD and changes in the Ångström exponent are linked to the dispersion of biomass-burning aerosols. Air mass trajectories coinciding with the CJ1 core present the strongest impact on aerosol characteristics, which can be seen in spectral measurements.

Description: A survey was conducted in the summer monsoon transition region of China. By combining data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSOs) and Moderate Resolution Imaging Spectroradiometer (MODIS), the effects of East Asian summer monsoon circulation on the spatial distribution of aerosol, as well as the response mechanisms of different aerosols in an abundant and a deficient summer monsoon year, were analyzed. It was found that, in the summer monsoon transition region, the aerosol optical depth (AOD) in abundant monsoon years was lower than that in deficient years. Only in the Gobi Desert region of the Loess Plateau, the AOD in abundant monsoon years was significantly larger than that in deficient years. When the AOD was less than 0.06, the frequency of dust aerosol was higher than that of polluted aerosol in both the abundant and deficient monsoon years. When the AOD was over 0.06, the frequency of polluted aerosol was higher than that of dust aerosol in both the abundant and deficient monsoon years. In summer, the AOD was larger and the frequency of polluted aerosol in abundant monsoon years was higher than that in deficient years.

Description: Climate change has emerged as a significant man-made global environmental challenge marked by rising temperature. The global rising temperature is supposed to alter climatic patterns like floods and droughts, thereby affecting human life supporting system and global food production. In order to clarify the impact of weather events on agricultural production in karst landforms, this study selected the indices of the growth period of crops (start time and duration), growing season precipitation, intense precipitation, number of consecutive rainless days, and number of drought-flood abrupt alternation events to evaluate the variation trend of future weather events and their impact on crop growth in Guizhou Province, China. The results show that (1) the climate is generally getting warmer. From 2019 to 2050, the sowing period of winter wheat and rice tends to be postponed. The duration of maize and rice’s growth period will be shortened, and the life cycle of wheat also emerges as having a decreasing tendency except for those from the southern region. Comparing with the mean value during 1961 to 2018, the average crop cycle length of winter wheat, summer maize, and rice was shortened. The rate of shortening of crop cycle length is faster than the value during 1961 to 2018. (2) In the next 30 years, extreme precipitation concentrates in June and mainly falls in the central and southeast parts of Guizhou Province. In addition, summer is the outbreak period of drought events and drought-flood abrupt alternation events, which has a great impact on crop’s growth. This study can provide references for the planting system, structure, layout, and management of crops in the karst region.

Description: Due to limited number of weather stations and interruption of data collection, the temperature field data may be incomplete. In the past, spatial interpolation is usually used for filling the data gap. However, the interpolation method does not work well for the case of the large-scale data loss. Matrix completion has emerged very recently and provides a global optimization for temperature field data reconstruction. A recovery method is proposed for improving the accuracy of temperature field data by using sparse low-rank matrix completion (SLR-MC). The method is tested using continuous gridded data provided by ERA Interim and the station temperature data provided by Jiangxi Meteorological Bureau. Experimental results show that the average signal-to-noise ratio can be increased by 12.5%, and the average reconstruction error is reduced by 29.3% compared with the matrix completion (MC) method.

Description: This paper employs metafrontier Malmquist-Luenberger index to measure green total factor productivity and then builds panel model to investigate the nonlinear effects of both governmental and civil environmental regulation on green total factor productivity in 30 provinces of China in 2007–2016, where the threshold variables are environmental awareness and regulatory foundation. The results show that green total factor productivity takes the characteristic of cyclical fluctuation, and the magnitude and its growth rate in the eastern region are higher than those in the midwestern region. The degrees of the governmental and civil environmental regulation and green total factor productivity display single environmental awareness threshold and regulatory foundation threshold. It should be noted that the sign of governmental and civil environmental regulation on green total factor productivity will transform from negative to positive, if and only if threshold variables ascend and surpass the threshold value. Under the condition of metafrontier technology, governmental environmental awareness threshold value, based on the investigated corruption and malpractice cases by the procuratorates among every hundred thousand people, reaches 0.2158, and civil environmental awareness threshold value based on the per capita education level will attain 12.2330 years, and the corresponding regulatory foundation index threshold values are 0.0163 and 0.0154. These findings show clear policy implications: rather than continually promoting the level of governmental environmental regulation, civil performance, environmental awareness, and regulatory foundation should be considered.

Description: The influence of global change on vegetation cover and processes has drawn increasing attention in the past few decades. In this study, we used remotely sensed rainfall and land surface temperature to investigate the spatiotemporal pattern and trend in vegetation condition using NDVI as proxy from 2001 to 2017 in a humid and dry tropical region. We also determined the partial correlation coefficient of temperature and rainfall with NDVI and the response of NDVI to changes in landcover categories due to human activities. We found that the mean annual maximum NDVI was 0.42, decreasing at a rate of 0.06 per decade. About 27.4% of the area was found to have experienced a significant negative trend in vegetation cover, while only 0.34% exhibited significant increasing vegetation vigour. Land surface temperature increased at a mean rate of 0.75°C/decade, with higher rates in agriculture, savanna, settlements, woodlands, and riparian vegetation than in forest and mangrove vegetations. Precipitation also reduced at a mean rate of 58.69 mm/decade, with higher rates in agriculture savanna and riparian vegetation than in sahelian grasslands, mangrove, forest, and woodlands. NDVI was negatively correlated with temperature in savanna, settlements, degraded forest, and sahelian grasslands providing confirmation of ongoing land degradation. It was concluded that vegetation vigour will continue to decline under rainfall and increasing temperature conditions especially in dryer regions. The use of land surface temperature in this study is particularly valuable in highlighting areas where changes in NDVI occurred as a result of synergistic action between climate and human-induced landcover changes. Our findings underscore the importance of landuse policies that account for spatial variation in synergistic relationships between the nexus of climate and land conversion processes that influence vegetation cover change in different landcover types in tropical regions.

Description: Tibetan Plateau (TP) mesoscale vortex (TPMV) was regarded as one of the most important rain bearing systems in China. Previous studies focused on the mechanisms of the TPMV in the viewpoint of deterministic forecast; however, few studies investigate the predictability of the TPMV using the Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) from the European Center for Medium Range Weather Forecasts (ECWMF). This paper investigates the location and the intensity of the larger-scale synoptic systems that influenced the development of the TPMV and its associated heavy rainfall by correlation and composite analysis. The case study on 18 July 2013 shows that stronger Balkhash Lake ridge, weaker Baikal Lake trough, and weaker western Pacific subtropical high (WPSH) are favorable to formation of TPMV over the Sichuan basin (SCB); otherwise, weaker Balkhash Lake ridge, stronger Baikal Lake trough, and stronger WPSH result in formation of TPMV to west of the SCB slightly. After the initial time, forecast for next 48 h of the geopotential height over the SCB can be viewed as a precursor of the subsequent time-averaged 90–108 h forecast of TPMV. TPMV had critical contributions to the heavy rainfall over the SCB on 18 July 2013.

Description: The effect of climate variability on the rainfall pattern is canvassed on the Uma Oya river basin, Sri Lanka, consisting of 5 rainfall gauging stations. The Uma Oya basin (720 km2) is given utmost precedence due to environmental concerns seen in the ongoing Uma Oya multipurpose development project (529 million USD worth) which is expected to divert water to the southeast dry zone of the country while adding 231 GWh/year electricity to the national grid. The rainfall data for a period of 26 years (1992–2017) were analysed using Mann–Kendall’s test and Sen’s slope estimator test to identify the rainfall trends. Both of these trend analysis test results depict only one negative trend for Hilpankandura Estate for the month of June; however, the seasonal trend analysis and annual trend analysis do not support this observation. Nevertheless, Mann–Kendall’s test showed potential positive trends for the 3 rainfall gauging stations Kirklees Estate, Ledgerwatte Estate, and Welimada Group only in the 1st intermediate period (March-April), and this is well supported by the monthly trend analysis. Other than these trends, the results do not show any significant negative trends in the Uma Oya catchment. Therefore, the results vividly explain that there is no threat of water scarcity to the catchment area being resistant to changing global climate for the past 26 years.

Description: In the past two decades, global navigation satellite system-reflectometry (GNSS-R) has emerged as a new remote sensing technique for soil moisture monitoring. Some experiments showed that the antenna of V polarization is more favorable to receive the reflected signals, and the interference pattern technique (IPT) was used for soil moisture and retrieval of other geophysical parameters. Meanwhile, the lower satellite elevation angles are most impacted by the multipath. However, electromagnetic theoretical properties are not clear for GNSS-R soil moisture retrieval. In this paper, the advanced integral equation model (AIEM) is employed using the wave-synthesis technique to simulate different polarimetric scatterings in the specular directions. Results show when the incident angles are larger than 70°, scattering at RR polarization (the transmitted signal is right-hand circular polarization (RHCP), while the received one is also RHCP) is larger than that at LR polarization (the transmitted signal is RHCP, while the received one is left-hand circular polarization (LHCP)), while scattering at LR polarization is larger than that at RR polarization for the other incident angles (1°∼70°). There is an apparent dip for VV and VR scatterings due to the Brewster angle, which will result in the notch in the final receiving power, and this phenomenon can be used for soil moisture retrieval or vegetation corrections. The volumetric soil moisture (vms) effects on their scattering are also presented. The larger soil moisture will result in lower scattering at RR polarization, and this is very different from the scattering of the other polarizations. It is interesting to note that the surface correlation function only affects the amplitudes of the scattering coefficients at much less level, but it has no effects on the angular trends of RR and LR polarizations.

Description: The China Meteorological Administration has deployed the China New Generation Weather Radar (CINRAD) network for severe weather detection and to improve initial conditions for numerical weather prediction models. The CINRAD network consists of 217 radars comprising 123 S-band and 94 C-band radars over mainland China. In this paper, a high-resolution digital elevation model (DEM) and beam propagation simulations are used to compute radar beam blockage and evaluate the effective radar coverage over China. Results show that the radar coverage at a height of 1 km above ground level (AGL) is restricted in complex terrain regions. The effective coverage maps at heights of 2 km and 3 km AGL indicate that the Yangtze River Delta, the Pearl River Delta, and North China Plain have more overlapping radar coverage than other regions in China. Over eastern China, almost all areas can be sampled by more than 2 radars within 5 km above mean sea level (MSL), but the radars operating in Qinghai-Tibet Plateau still suffer from serious beam blockage caused by intervening terrain. Overall, the radars installed in western China suffer from much more severe beam blockage than those deployed in eastern China. Maps generated in this study will inform users of the CINRAD data of their limitations for use in precipitation estimation, as inputs to other weather and hydrological models, and for satellite validation studies.

Description: Precipitation pattern has changed over many regions in recent decades, which may cause the risk of flood or drought. In this study, the main objective is to evaluate the spatiotemporal variability of precipitation in Beijing from 1960 to 2012. First, the mean monthly, seasonal, and annual precipitation series were used to analyze the temporal variation using regression, Mann–Kendall (M-K) test, Sen’s slope, and Pettitt tests. The results showed that the annual mean precipitation had a clear decreasing trend, with the statistically significant decrease in summer (especially in July and August) and significant increase in spring (especially in May). Although the decreasing trend is shown in the precipitation concentration indicators, the temporal uneven distribution of precipitation has unchanged. Subsequently, the precipitation time series at 30 stations over Beijing were used to evaluate the changes in precipitation pattern. The results showed that the annual series for the most rain gauges had decreasing trends with gradual changes. The spatial distribution of precipitation and other indices is geographically consistent, reflecting the principal physiographic and climatic conditions. At the same time, the effects of the terrain and urban development on the precipitation spatial distribution were detected. Generally, the large and heavy precipitations frequently occur in the plain areas, while the precipitation in the mountain areas is dominated by the small and medium precipitation. As a whole, the total precipitation in the plain areas (558.8 mm) was slightly higher than that in the mountainous areas (533.0 mm), while the precipitation in the urban areas (575.9 mm) was much higher than in the surrounding suburb areas (538.9 mm) during 1960–2012. The differences between the plain and mountainous areas during the period of 1960–1979, 1980–1999, and 2000–2012 were 24.2 mm, 32.6 mm, and 17.7 mm, respectively. The differences in precipitation between the urban and suburb areas for the three periods were 32.9 mm, 45.2 mm, and 31.0 mm, respectively, with the amount accounting for 5.51%, 7.66%, and 5.94% of the mean precipitation in the urban areas for the corresponding periods.

Description: The spatial and temporal distribution characteristics of high clouds over the Tibetan Plateau (TP) were studied using the Atmospheric Infrared Sounder (AIRS) and the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) monthly mean cloud products from 2007 to 2017. The high clouds over the TP are dominated by cirrus and show seasonal variation characteristics. There were two distinct areas with the high occurrence of cirrus clouds in the area (0°–60°N, 75°–103°E). One was located in the regions from the equator to 25°N, and the other was within the latitude belt from 30° to 40°N. From January to May, cirrus clouds mainly occurred in the central and northern parts of the TP (30° to 40°N), and the cirrus cloud fraction increased from January and reached its maximum (∼0.51) in April. From June to August, cirrus clouds mainly occurred in the southern part of the TP during summer. The cirrus clouds over the southern TP were relatively high (located in 10–17 km) and manifested northward and southward movements. The ice clouds in the southern TP are associated with plateau deep convection activities and abundant vapor transmitted by the Asian monsoon. Cirrus clouds over the northern and central TP may be relevant to the atmospheric lift by an approaching cold front and topographic lifting. Moreover, the high clouds below 11 km are dominated by opaque clouds, while the nonopaque (or thin) and opaque (or thick) clouds above 11 km are comparable.

Description: The Abbay River Basin, which originates in Ethiopia, is a major tributary and main source of the Nile River Basin. Land cover and vegetation in the Abbay River Basin is highly susceptible to climate change. This study was conducted to investigate the trends of climate change for a period of thirty-six years (1980–2016) within selected stations of the basin by using the innovative trend analysis method, Mann–Kendall test, and Sen’s slope estimator test to investigate the mean annual precipitation and temperature variables. Changes in land cover and vegetation in the Abbay River Basin were studied for a period of thirteen years (2001–2013) by using remote sensing, GIS analysis, land cover classification, and vegetation detection methods to assess the land cover and vegetation in the basin. In addition, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Transformation Matrix were employed to analyze the spatial and temporal patterns of land cover and vegetation impacted by changes in climate. The result reflects that the trend of average annual temperature was remarkably increased ( = 0.12, Z = 0.75) in the 36-year period, and the temperature was increased by 0.5°C, although precipitation had slightly decreased during the same period. In the thirteen years’ period, forest land and water resource decreased by 3429.62 km2 and 81.45 km2, respectively. In contrast, an increment was observed in grassland (2779.33 km2), cultivated land (535.34 km2), bare land (43.08 km2), urban land (0.65 km2), and wetland (152.66 km2) in the same period. In the study, it was also observed a decrease of an NDVI value by 0.1 was observed in 2013 in the southern part of the basin. The findings of the present study illustrate a significant change in eco-hydrological conditions in the ARB with an adverse impact on the environment. Hydroclimatic changes caused the increase in temperature and decreasing trend in precipitation which significantly impacted the land cover and vegetation in the basin. The changes in land cover were mostly caused by global and local climate influence which mainly affects the hydroclimate and eco-hydrology systems of the basin. The result is consistent with that of the previous studies conducted elsewhere. The findings of this paper could help researchers to understand the eco-hydrological condition of the study basin and become a foundation for further studies.

Description: Urbanization, industrialization, and regional economic integration have developed rapidly in China in recent years. Air pollution has attracted more and more attention. However, PM2.5 is the main particulate matter in air pollution. Therefore, how to predict PM2.5 accurately and effectively has become a concern of experts and scholars. For the problem, atmosphere PM2.5 concentration prediction algorithm is proposed based on time series and interactive multiple model in this paper. PM2.5 concentration is collected by using the monitor at different air quality levels. The time series models are established by historical PM2.5 concentration data, which were given by the autoregressive model (AR). In the paper, three PM2.5 time series models are established for three different air quality levels. Then, the three models are converted to state equation, respectively, by autoregressive integrated with Kalman filter (AR-Kalman) approaches. Besides, the proposed interactive multiple model (IMM) algorithm is, respectively, compared with autoregressive (AR) model algorithm and AR-Kalman prediction algorithm. It is turned out the proposed IMM algorithm is more accurate than the other two approaches for PM2.5 prediction, and it is effective.

Description: The connection between drought early warning information and the timing of rangeland managers’ response actions is not well understood. This study investigates U.S. Northern Plains range and livestock managers’ decision-making in response to the 2016 flash drought, by means of a postdrought survey of agricultural landowners and using the Protective Action Decision Model theoretical framework. The study found that managers acted in response to environmental cues, but that their responses were significantly delayed compared to when drought conditions emerged. External warnings did not influence the timing of their decisions, though on-farm monitoring and assessment of conditions did. Though this case focused only on a one-year flash drought characterized by rapid drought intensification, waiting to destock pastures was associated with greater losses to range productivity and health and diversity. This study finds evidence of unrealized potential for drought early warning information to support proactive response and improved outcomes for rangeland management.

Description: The accurate simulation of typhoon hydrometeors remains a challenge. This study attempts to evaluate the performances of five microphysics schemes (MPSs) in the Weather Research and Forecasting (WRF) model in simulating the supertyphoon Neoguri in July 2014. The observed microwave brightness temperature, as well as retrieved data from the microwave radiometer imager (MWRI) onboard Chinese FY-3B satellite, are used to test hydrometeor simulations. In particular, two MWRI radiance indices, including the emission index (EI) and scattering index (SI), are used to assess the performance of five MPSs in simulating liquid and frozen hydrometeors, respectively. Overall, the WRF model can well reproduce the overall pattern of typhoon-produced precipitation, albeit with slightly overestimated precipitation in the inner rainband and underestimated precipitation in the stratiform rainband. Moreover, ice water paths (IWPs) from all five MPS simulations are higher than those estimated from MWRI retrieval in most areas, and the spatial pattern and values of IWP for the National Severe Storms Laboratory double-moment MPS (NSSL) are much closer to those for MWRI. The NSSL scheme reproduces a more realistic joint histogram distribution of SI and EI than other MPSs do, relative to the observation. Besides, the nonlinear Lucas–Kanade optical flow approach has been used to reflect the horizontal distribution of hydrometeors in the typhoon. The results show that the simulated EI and SI from the five MPSs show a systematic southwest bias of approximately about 10∼20 km and significant intensity bias in the convection area. Further model sensitivity tests confirm that the NSSL scheme generates more realistic graupel and supercooled water close to the observations among all MPSs. The findings suggest that satellite measurements would be helpful to assess MPSs in numeric weather models, especially for hydrometeor distributions in the whole typhoon system.

Description: Climate change has become a global concern for scientists as it is affecting almost every ecosystem. Larix gmelinii and Betula platyphylla are native and dominant forest species in the Daxing’anling Mountains of Inner Mongolia, playing a major role in carbon sequestration of this region. This study was carried out to assess the effect of climate variables including precipitation and temperature on the biomass of Larix gmelinii and Betula platyphylla forests. For this purpose, we used the climate-sensitive stem biomass allometric model for both species separately to find out accurate stem biomass along with climatic factors from 1950 to 2016. A total of 66 random plots were taken to attain the data from this study area. Larix gmelinii and Betula platyphylla stem biomass have a strong correlation with annual precipitation (R2 = 0.86, R2 = 0.71, R2 = 0.79, and R2 = 0.59) and maximum temperature (R2 = 0.76, R2 = 0.64, R2 = 0.67, and R2 = 0.52). However, annual minimum temperature (R2 = 0.58, R2 = 0.43, R2 = 0.55, and R2 = 0.46) and annual mean temperature (R2 = 0.40, R2 = 0.22, R2 = 0.36, and R2 = 0.19) have a relatively negative impact on tree biomass. Therefore, we suggest that both species have a very strong adaptive nature with climatic variation and hence can survive under drought and high-temperature stress climatic conditions.

Description: According to the correlation of tree ring and solar activity, the cycle analysis method based on variational mode decomposition (VMD) and Hilbert transform is proposed. Firstly, the tree ring width of cypress during 1700 to 1955 beside the Huangdi Tomb and the long-term sunspot number during 1700 to 1955, respectively, are decomposed by VMD into a series of intrinsic mode functions (IMFs). Secondly, Hilbert transformation on the decomposed IMF component is performed. Then, the marginal spectra are given and analyzed. Finally, their quasiperiodic properties are obtained as follows: the tree ring width has the quasiperiodicity of 2 to 7a, 10.8a, and 25a; the sunspot number has the quasiperiodicity of 8.3a, 9.9a, 11.1a, 52.2a, and 101.2a. The result obtained by analyzing that quasiperiodicity shows that the main periods of tree ring width and the sunspot number in the same period are basically consistent, and tree ring width has other cycles. This shows that sunspot activity is an important factor affecting tree ring growth, and tree ring width is influenced by other external environments.