ALBERT

Description: ABSTRACT In this observational research, the seasonally stratified (October to December) Indian Ocean Dipole mode (IOD) behaviour in the tropical Indian Ocean since 1870 is investigated. Three significant climate shifts manifested themselves in the Indian Ocean during the years 1918, 1961 and 1997. Each shift is preceded by a 3-year sequence of IOD events that are unique in the entire time series. The order is such that a relatively moderate negative sea surface temperature (SST) anomaly gradient intensifies to an extreme negative IOD event which then reverses in the shift year to an extreme positive event. The last two extreme IOD events reach record-breaking magnitudes during each shift implying intensification of the shift process with time. During the year before the shift, the Mascarene High (MH) is anomalously displaced poleward and westward, while it intensifies as it anomalously moves equatorward during the shift year. Therefore the maximum contrast of south Indian Ocean pressure pattern and hence the intensity of the MH, from one year to the other within an epoch, is achieved during the shift years. The intensity of this process has been escalating during each of the three successive shifts. Despite involving to a greater extent the IOD dynamics, these IOD shifts may primarily be an expression of the south Indian Ocean basinwide dynamics rather than a direct response to internal tropical influences.

Description: ABSTRACT Monthly total precipitation and mean temperature climate surfaces, gridded to 30-arcseconds (≈1 km at the equator) and available for all global land areas, are presented. These datasets are generated with a Delta downscaling method, using the 30-arcsecond WorldClim climatologies to scale monthly anomaly grids. For monthly mean temperature, the anomalies are constructed from both the Climate Research Unit (CRU) and Willmott & Matsuura (W&M) 0.5 degree time-series datasets, whereas for monthly precipitation Global Precipitation Climatology Centre (GPCC) data are also used. The 0.5 degree anomalies are then interpolated to the 30-arcsecond resolution. Use of piecewise cubic Hermite interpolating polynomials (PCHIP) to interpolate the anomaly grids results in more physically representative Delta downscaled surfaces, compared to bilinear and cubic spline interpolation. The Delta downscaled products are compared to Global Historical Climatology Network (GHCN) station records for six test regions distributed globally. In this analysis, the Delta grids produced using the W&M time-series dataset perform better than grids produced using GPCC or CRU. Using Oregon, USA as a test region, the Delta downscaled datasets are compared to the Parameter-elevation Regressions on Independent Slopes Model (PRISM) datasets. For monthly precipitation, PRISM performs better than each of the three Delta downscaled datasets, but for mean temperature both Delta downscaled datasets outperform PRISM. Through computing the Pearson product–moment correlation coefficient between GHCN station delineated errors in the WorldClim climatologies and the Delta downscaled W&M data, it is shown that performance of the Delta grids corresponds strongly to performance of the reference climatologies. Therefore, future improvement of the 30-arcsecond Delta grids described in this article is strongly tied to advances in the high-resolution climatological data for all global land surfaces. The Delta downscaled datasets discussed herein are open-source and freely distributed at http://www.globalclimatedata.org .

Description: ABSTRACT This study demonstrates the capability of the Weather Research and Forecasting (WRF) model with four-dimensional data assimilation (WRF-FDDA) to produce a high-resolution climatography of seasonal precipitation over Israel and the surrounding areas. The system was used to dynamically downscale global Climate Forecast System (CFS) reanalysis with continuous assimilation of conventional and unconventional observations. Precipitation seasons (December-January-February) in 7 years, including two extreme dry and wet seasons observed in the past decades, were generated at 2-km spatial resolution. Verification against rain-gauge observations shows that the WRF-FDDA system effectively reproduces the spatial and inter-annual variability, as well as the timing, intensity, and length of wet and dry spells. The best agreement between model and observations was obtained at areas dominated by complex terrain, illustrating the benefit of the high-resolution lower boundary forcing in the dynamical downscaling process. In contrast, some biases were observed over coastal-flat terrain. The model was able to reproduce some of the extreme events, but exhibited limitations in the case of rare events. This specific discrepancy between the model and observations suggests that further fine tuning and different model configurations may be needed to correctly simulate extreme events. The use of an objective weather-regimes verification procedure reveals the skill of the climatography for different types of extra-tropical cyclones: while biases are larger at coastal-flat areas under shallow-cyclonic conditions, deep-cyclonic conditions lead to more significant biases in complex terrain regions. The weather-regimes dependent information may be used for further calibration of the downscaled precipitation.

Description: ABSTRACT The source region of Yangtze River in China is a part of Tibet Plateau where the hydrological processes are sensitive to climatic change. The impacts of precipitation, air temperature and evapotranspiration on annual runoff in the source region of Yangtze River during 1957–2009 are investigated in the time-period domain using wavelet analysis method and multiple regression method. Annual evapotranspiration is calculated with data of precipitation and air temperature based on Takahashi's empirical equation. This approximation of actual evapotranspiration successfully matches the mean annual water balance. Significant periods of runoff, 7–8 year, 20–21 year and 42–43 year, are revealed by using Morlet wavelet. Different significant periods are found for annual precipitation, air temperature and evapotranspiration, whereas the 7–8 year and 42–43 year periods are the same of the runoff. It is indicated by wavelet correlation coefficients that the correlations between runoff and these climatic components depends on periods. Change in the summation of runoff wavelet coefficients at different period can approximately represents the change pattern of real runoff and is correlated with the wavelet coefficients of the climatic components. The correlation can be expressed with a linear multiple regression equation which indicates that the change in annual runoff is contributed by change in annual precipitation rather than change in air temperature. This relationship between runoff and climatic components are different from that in the source region of Yellow River, in China.

Description: ABSTRACT Global solar radiation (G) and ultraviolet radiation (UV) observed at Wuhan, China from 2006 to 2012 have been used to investigate the temporal variability of both radiant fluxes and the UV/G ratios (F UV ) at different time scales for the first time in central China. Clearness index (Kt) was used to study the cloud effects on F UV in each month under different sky conditions. It turned out that F UV reached higher values in summer and lower values in winter; F UV also increased generally with cloudiness. A UV model for cloud-free condition was developed by studying the dependence of hourly UV irradiations on the relative optical air mass (m), which has been assessed through the statistical indices: mean bias error (mbe), mean-absolute bias error (mabe) and root-mean-square error (rmse) whose values were 0.32, 7.3 and 8.64%, respectively. UV clearness index, m and Kt were further used for analysing the cloud effects, and different UV models under any sky conditions have been established and validated. Meanwhile, as a modulation for different sky conditions, both cloud modification factors were also used in the construction of a new type of UV model. Finally, by comparing the statistical indices from different models, the most suitable model was chosen for validating at Wuhan University (WHU) and two other sites in different regions of China under any atmospheric conditions, which suggested that the proposed model should be modified to account for local differences to produce better estimations in larger areas.

Description: This study analyses the spatial and temporal variability and trends of rainfall, mean maximum and minimum temperatures at seasonal and annual timescales over the Upper Blue Nile River Basin, Ethiopia. Statistical and geostatistical techniques were applied to 1634 points on 10 × 10 km gridded data reconstructed from weather stations and meteorological satellite records. The data were obtained from the National Meteorological Agency of Ethiopia and cover the period between 1981 and 2010. Trends were evaluated from slopes of regression lines using the least squares method. The F -distribution test was used to determine the statistical significance of the trends. Minimum temperatures significantly increased in northern, central, southern and southeastern parts of the Basin in all seasons. At the annual scale, maximum and minimum temperatures significantly increased in over 33% of the Basin at a rate of 0.1 and 0.15 °C per decade, respectively; however, the western part (12%) of the Basin experienced declining trends on annual and seasonal timescales. The minimum temperatures increased at a higher rate than the maximum temperatures during winter, summer, autumn and also at the annual timescale. Mean annual minimum and maximum temperatures increased from 12.69 to 13.32 °C and 26.43 to 26.91 °C from 1981 to 2010, respectively. Rainfall showed statistically non-significant increasing trends of 35 mm per decade at the annual timescale. All seasons except spring season exhibited similar statistically non-significant trends. The spring season, however, showed a statistically non-significant declining trend in the north eastern (11%) part of the Basin.

Description: This study investigates whether a regional climate model (RCM) driven by a global general circulation model (GCM) in a nesting approach with observed atmospheric CO 2 concentrations shows predictability for temperature and precipitation trends during 1961–1990 in the Mediterranean area, a region strongly influenced by large-scale circulation. Resulting discrepancies between model and observations raise the question whether the model predictability increases after removing impacts of mid-latitude circulation variability. For temperature and precipitation trends we use the RCM REMO and the observational dataset E-OBS, and for atmospheric circulation the driving coupled GCM ECHAM5/MPI-OM and NCEP/NCAR reanalyses. Cross-validated multiple regression analyses between large-scale circulation and regional temperature and precipitation are performed for observed and simulated data. The impact of circulation is removed from the original temperature and precipitation data, and the trends of circulation-related and circulation-unrelated parts are compared. The circulation-related trends of models and observations show discrepancies owing to differing observed and simulated mid-latitude circulation dynamics, i.e. different temporal evolutions of North Atlantic Oscillation and East Atlantic pattern in winter and East Atlantic Jet and a blocking pattern in summer. Such differences can be related to unknown initial conditions of GCM simulations. In fact, we find strong impacts of initial conditions on mid-latitude circulation dynamics of ECHAM5/MPI-OM ensemble members over 30-year periods. The agreement between simulated and observed circulation-unrelated trends is generally higher than for original trends indicating that the predictability of this nesting approach increases by removing impacts of mid-latitude circulation variability. We conclude that initial conditions affect climate variability up to the multi-decadal timescale, at least in parts of the globe which are governed by extratropical circulation modes, and hence, hinder the comparability of simulated and observed climate trends over time periods shorter than the timescale dominated by radiative forcing. In the Mediterranean Basin the latter is definitely beyond 30 years.

Description: The impact of heating by black carbon aerosols on Indian summer monsoon has remained inconclusive. Some investigators have predicted that black carbon aerosols reduce monsoon rainfall while others have argued that it will increase monsoon rainfall. These conclusions have been based on local influence of aerosols on the radiative fluxes. The impact of aerosol-like heating in one region on the rainfall in a remote region has not been examined in detail. Here, using an atmospheric general circulation model, it has been shown that remote influence of aerosol-like heating can be as important as local influence on Indian summer monsoon. Precipitation in northern Arabian Sea and north-west Indian region increased by 16% in June to July when aerosol-like heating were present globally. The corresponding increase in precipitation due to presence of aerosol-like heating only over South Asia (local impact) and East Asia (remote impact) were 28 and 13%, respectively. This enhancement in precipitation was due to destabilization of the atmosphere in pre-monsoon season that affected subsequent convection. Moreover, pre-monsoon heating of the lower troposphere changed the circulation substantially that enabled influx of more moisture over certain regions and reduced the moist static stability of the atmosphere. It has been shown that regional aerosol heating can have large impact on the phase of upper tropospheric Rossby wave in pre-monsoon season, which acts as a primary mechanism behind teleconnection and leads to the change in precipitation during monsoon season. These results demonstrate that changes in aerosol in one region can influence the precipitation in a remote region through changes in circulation.

Description: ABSTRACT Ensembles of high-resolution regional climate model (RCM) simulations are crucial for assessing regional climate change and the associated uncertainties. This article presents an RCM ensemble generation technique which explores uncertainties arising from the positioning of synoptic systems in the large-scale atmospheric forcing by shifting the atmospheric fields from global climate model (GCM) runs horizontally. Here, we discuss how the so-called Atmospheric Forcing Shifting (AFS) affects temperature and precipitation over Europe for the period 1980–1984. We use ERA-40 reanalysis data in which the atmospheric fields are shifted to each direction by 25 and 50 km, respectively, to run RCM simulations with COSMO-CLM at 50-km resolution. The analysis of the AFS ensemble includes comparisons with E-OBS observations and COSMO-CLM runs driven by different GCMs. AFS has an evident effect on the spatiotemporal distributions of temperature and particularly precipitation, which is most pronounced during hydrological summer (May to October) when spatial weather patterns are more variable. Furthermore, AFS produces realistic changes in the likelihood and intensity of extreme precipitation. The changes induced by AFS depend strongly on orography, i.e. precipitation increases are likely to occur where moist air masses are shifted towards the windward mountain side and vice versa. Thus, increasing the RCM ensemble spread by means of AFS is a simple and useful method for sampling observed climate statistics and assessing the variability and changes in mean and extreme climate.