ALBERT

Description: Weekly PM2.5 samples were collected for one year (1999-2000) in Beijing and Shanghai and the carbonaceous species analyzed to investigate and compare their time series patterns and possible sources in the two biggest cities of China. Weekly carbonaceous concentrations varied in wide ranges with 8.6-59µg m-3 for OC and 1.5-25.4µg m-3 for EC in Beijing, and with 5.1-38.4µg m-3 for OC and 2.3-13.0µg m-3 for EC in Shanghai. Similar weekly and seasonal variations of OC and EC concentrations were found in each city though major combustion sources presented source-dependent emission characteristics and seasonal differences in emission amount for carbonaceous species. Both OC and EC maintained much higher concentrations in late fall through winter, probably due to enhanced emissions coupled with unfavorable meteorological conditions. In Beijing, the 14C analysis of limited samples suggested there was a significant contribution (33-48%) of modern carbon to the total fine carbonaceous PM burden with higher fractions in the harvest seasons. The high mass ratios of excessive potassium to EC in both Beijing and Shanghai also indicated that biomass burning had important contribution to fine carbonaceous particles.

Description: In this study, a parameterization methodology based on MODIS (Moderate Resolution Imaging Spectroradiometer) and in situ data is proposed and tested for deriving the regional surface reflectance, surface temperature, net radiation flux, soil heat flux, sensible heat flux and latent heat flux over heterogeneous landscape. As a case study, the methodology was applied to the Tibetan Plateau area. Four images of MODIS data (30 January 2007, 15 April 2007, 1 August 2007 and 25 October 2007) were used in this study for the comparison among winter, spring, summer and autumn. The derived results were also validated by using the "ground truth" measured in the stations of the Tibetan Observation and Research Platform (TORP). The results show that the derived surface variables (surface reflectance and surface temperature) and surface heat fluxes (net radiation flux, soil heat flux, sensible heat flux and latent heat flux) in four different seasons over the Tibetan Plateau area are in good accordance with the land surface status. These parameters show a wide range due to the strong contrast of surface features over the Tibetan Plateau. Also, the estimated land surface variables and surface heat fluxes are in good agreement with the ground measurements, and all their absolute percent difference (APD) is less than 10% in the validation sites. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface variables and surface heat fluxes using the MODIS and in situ data over the Tibetan Plateau area. The shortage and further improvement of the methodology were also discussed.

Description: Due to its harsh natural conditions, there had not been any intensive radiosonde observations over the Tibetan Plateau (TP) before the year 2008, when a regional radiosonde observation network was implemented through a Sino-Japan joint cooperation project. This paper reports, on the basis of these observations, on an analysis of the structure of upper troposphere and lower stratosphere (UTLS) and provides observations of stratosphere and troposphere exchange (STE) over the TP. Due to sparseness of high resolution radiosonde data, many previous studies assumed that there was only one thermal tropopause over the TP. Actually, the radiosonde temperature profiles in winter time over the TP often exhibit a multiple tropopause (MT). The MT occurs in winter with a high frequency over the Plateau. MT events during this time are associated with tropopause folds near the subtropical westerly jet. The MT consistently varied with the movement of the jet. The MT becomes a single tropopause with the development of the monsoon. The detailed analyses of MT characteristics are reported in this paper. Earlier analyses of global MT events (with data based on GPS radio occultation, ERA-40 data and Integrated Global Radiosonde Archive database) resulted in a climatic frequency of MT occurrences in the winter season over the Plateau is not more than 40 %. Based on high resolution data of intensive radiosonde observations, our estimations of MT occurrence over the Plateau can be as high as 80 % during certain winters. This reminds us to pay more attention to the MT events above the Plateau. The influence of the coarse vertical resolution and other effects on the estimation of MT occurrence frequency are also discussed. The stratospheric intruding episodes are generally associated with the presence of subtropical jet stream over the Plateau. The complex structure of dynamic tropopause folding over the Plateau have been reflected by the thermal MT events observed by radiosondes. The intrusion of air masses from the stratosphere may contribute to a higher upper tropospheric ozone concentration in winter than in summer above the plateau.

Description: Although the concept of producing higher yields with reduced greenhouse gas (GHG) emissions is a goal that attracts increasing public and scientific attention, the tradeoff between crop productivity and GHG emissions in intensive agricultural production is not well understood. In this study, we investigated 33 sites of on-farm experiments to evaluate the tradeoff between grain yield and GHG emissions using two systems (conventional practice, CP; high-yielding systems, HY) of intensive irrigation wheat (Triticum aestivum L.) in China. Furthermore, we discussed the potential to produce higher yields with lower GHG emissions based on a survey of 2938 farmers. However, in both the HY and CP systems, wheat grain yield response to GHG emissions fit a linear-plateau model, whereas the curve for grain yield from the HY system was always higher than that from the CP system. Compared to the CP system, grain yield was 44% (2.6 Mg ha–1) higher in the HY system, while GHG emissions increased by only 2.5%, and GHG emission intensity was reduced by 29%. The current intensive irrigation wheat system with farmers' practice had a median yield and maximum GHG emission rate of 6.05 Mg ha–1 and 4783 kg CO2 eq ha–1, respectively; however, this system can be transformed to maintain yields while reducing GHG emissions by 40% (5.96 Mg ha–1, and 2890 kg CO2 eq ha–1). Further, the HY system was found to increase grain yield by 41% with a simultaneous reduction in GHG emissions by 38% (8.55 Mg ha–1, and 2961 kg CO2 eq ha–1, respectively). In the future, we suggest moving the tradeoff relationships and calculations from grain yield and GHG emissions, to new measures of productivity and environmental protection using innovative management technologies. This shift in focus is critical to achieve food and environmental security.

Description: Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m−2 yr−1 to 4.8 g C m−2 yr−1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m−2 yr−1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.

Description: Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of Ts determines the active-layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts not only drives permafrost thaw/retreat but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960–2000, to characterize the warming rate of Ts in permafrost regions. There is a large spread of Ts trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 °C yr−1. Most models show smaller increase in Ts with increasing depth. Air temperature (Tsub〉a) and longwave downward radiation (LWDR) are the main drivers of Ts trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61 % of their differences in Ts trends, while trends of Ta only explain 5 % of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts trends (0.021 ± 0.008 °C yr−1, mean ± standard deviation) than the uncertainty of model structure (0.012 ± 0.001 °C yr−1), diagnosed from the range of response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active-layer thickness (ALT) is less than 3 m loss rate, is found to be significantly correlated with the magnitude of the trends of Ts at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total near-surface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to Ts at 1 m is estimated to be of −2.80 ± 0.67 million km2 °C−1. Finally, by using two long-term LWDR data sets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprising between 39 ± 14  ×  103 and 75 ± 14  ×  103 km2 yr−1 from 1960 to 2000. This corresponds to 9–18 % degradation of the current permafrost area.

Description: Hydrological multivariate analysis has been widely studied using copula-based modelling, in which marginal distribution inference is one of the key issues. The main object of this study is to discuss the applicability of the principle of maximum entropy (POME) in marginal distribution inference, thus to develop a POME-copula framework to analyse the dependence of hydrological variables. Marginal distributions are derived with the POME approach before bivariate copulas constructed with corresponding parameters estimated by the dependence of the derived margins. The proposed POME-copula has been employed in hydrological dependence analyses, with the annual maximum streamflow and water level collected from the Yangtze River, and the monthly streamflow from the Yellow River. Results show that the POME-copula method performs well in capturing dependence patterns of various hydrological variables.

Description: The paper aims to evaluate the impacts of the average hydraulic conductivity of the heterogeneous aquifer on the estimated hydraulic conductivity using the observations from pumping tests. The results of aquifer tests conducted at a karst aquifer are first introduced. A MODFLOW groundwater flow model was developed to perform numerical pumping tests, and the heterogeneous hydraulic conductivity (K) field was generated using the Monte Carlo method. The K was estimated by the Theis solution for an unconfined aquifer. The effective hydraulic conductivity (Ke) was calculated to represent the hydraulic conductivity of a heterogeneous aquifer. The results of numerical simulations demonstrate that Ke increase with the mean of hydraulic conductivity (EK), and decrease with the coefficient of variation of the hydraulic conductivity (Cv). The impact of spatial variability of K on the estimated Ke at two observation wells with smaller EK is less significant compared to the cases with larger EK.

Description: The Tibetan Plateau and nearby surrounding area (the Third Pole area) dramatically impacts the world’s environment and especially controls climatic and environmental changes in China, Asia and even in the Northern Hemisphere. Supported by the Chinese Academy of Sciences (CAS) and some international organizations, the Third Pole Environment (TPE) Programme is now under way. First, the background of the establishment of the TPE, the establishment and monitoring plans on long-term for the TPE and six comprehensive observation and study stations are introduced. Then the preliminary observational analysis results on atmosphere−land interaction are presented. The study on the regional distribution of land surface heat fluxes is of paramount importance over the heterogeneous landscape of the Third Pole area. A parameterization methodology based on satellite and in situ data is described and tested for deriving the regional surface heat fluxes (net radiation flux, soil heat flux, sensible heat flux and latent heat flux) over the heterogeneous landscape. As a case study, the methodology was applied to the whole Tibetan Plateau area. Eight images of MODIS data and four images of AVHRR data were used for the comparison among winter, spring, summer and autumn, and the annual variation analyses. The derived results were also validated by using the ‘‘ground truth’’ measured in the stations of the TPE. The results show that the derived surface heat fluxes in the four different seasons over the Tibetan Plateau area are in good agreement with the ground measurements. The results from AVHRR were also in agreement with MODIS. It is therefore concluded that the proposed methodology is successful for the retrieval of surface heat fluxes using the MODIS data, AVHRR data and in situ data over the Tibetan Plateau area.

Description: Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and inter-annual time scales, the variability of Ts determines the active layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts not only drives permafrost thaw/retreat, but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960–2000, to characterize the warming rate of Ts in permafrost regions. There is a large spread of Ts trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 °C yr−1. Most models show smaller increase in Ts with increasing depth. Air temperature (Ta) and longwave downward radiation (LWDR) are the main drivers of Ts trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61% of their differences in Ts trends, while trends of Ta only explain 5% of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts trends (0.021 ± 0.008 °C yr−1, mean ± SD) than the uncertainty of model structure (0.012 ± 0.001 °C yr−1), diagnosed from the range of response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active layer thickness (ALT) is less than 3 m loss rate is found to be significantly correlated with the magnitude of the trends of Ts at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total near-surface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to Ts at 1 m, is estimated to be of −2.80 ± 0.67 million km2 °C−1. Finally, by using two long-term LWDR datasets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000. This corresponds to 9–18% degradation of the current permafrost area.