An ensemble soil moisture dataset was produced from 11 of 25 global climate model (GCM) simulations for two climate scenarios spanning 1900 to 2099; this dataset was based on an evaluation of the spatial correlation of means and trends in reference to soil moisture simulations conducted using the community land model driven by observed atmospheric forcing. Using the ensemble soil moisture index, we analyzed the dry-wet climate variability and the dynamics of the climate zone boundaries in China over this 199-year period. The results showed that soil moisture increased in the typically arid regions, but with insignificant trends in the humid regions; furthermore, the soil moisture exhibited strong oscillations with significant drought trends in the transition zones between arid and humid regions. The dynamics of climate zone boundaries indicated that the expansion of semiarid regions and the contraction of semi-humid regions are typical characteristics of the dry-wet climate variability for two scenarios in China. During the 20th century, the total area of semiarid regions expanded by 11.5% north of 30°N in China, compared to the average area for 1970-1999, but that of semi-humid regions decreased by approximately 9.8% in comparison to the average for the period of 1970-1999, even though the transfer area of the humid to the semi-humid regions was taken into account. For the 21st century, the dynamics exhibit similar trends of climate boundaries, but with greater intensity.
Abstract The authors evaluate the performance of models from Coupled Model Intercomparison Project Phase 5(CMIP5)in simulating the historical(1951-2000)modes of interannual variability in the seasonal mean Northern Hemisphere(NH)500 hPa geopotential height during winter(December-January-February,DJF).The analysis is done by using a variance decomposition method,which is suitable for studying patterns of interannual variability arising from intraseasonal variability and slow variability(time scales of a season or longer).Overall,compared with reanalysis data,the spatial structure and variance of the leading modes in the intraseasonal component are generally well reproduced by the CMIP5 models,with few clear differences between the models.However,there are systematic discrepancies among the models in their reproduction of the leading modes in the slow component.These modes include the dominant slow patterns,which can be seen as features of the Pacific-North American pattern,the North Atlantic Oscillation/Arctic Oscillation,and the Western Pacific pattern.An overall score is calculated to quantify how well models reproduce the three leading slow modes of variability.Ten models that reproduce the slow modes of variability relatively well are identified.
Soil moisture droughts can trigger abnormal changes of material and energy cycles in the soil-vegetation-atmosphere system,leading to important effects on local ecosystem,weather,and climate.Drought detection and understanding benefit disaster alleviation,as well as weather and climate predictions based on the understanding the land-atmosphere interactions.We thus simulated soil moisture using land surface model CLM3.5 driven with observed climate in China,and corrected wet bias in soil moisture simulations via introducing soil porosity parameter into soil water parameterization scheme.Then we defined soil moisture drought to quantify spatiotemporal variability of droughts.Over the period from 1951 to 2008,40%of months(to the sum of 12×58)underwent droughts,with the average area of 54.6%of total land area of China's Mainland.The annual monthly drought numbers presented a significant decrease in arid regions,but a significant increase in semi-arid and semi-humid regions,a decrease in humid regions but not significant.The Mainland as a whole experienced an increasing drought trend,with77.3%of areal ratio of decrease to increase.The monthly droughts in winter were the strongest but the weakest in summer,impacting 54.3%and 8.4%total area of the Mainland,respectively.The drought lasting three months or more occurred mainly in the semi-arid and semi-humid regions,with probability>51.7%,even>77.6%,whereas those lasting 6 and 12 months or more impacted mainly across arid and semi-arid regions.
Long-term meteorological observation series are fundamental for reflecting climate changes.However,almost all meteorological stations inevitably undergo relocation or changes in observation instruments,rules,and methods,which can result in systematic biases in the observation series for corresponding periods.Homogenization is a technique for adjusting these biases in order to assess the true trends in the time series.In recent years,homogenization has shifted its focus from the adjustments to climate mean status to the adjustments to information about climate extremes or extreme weather.Using case analyses of ideal and actual climate series,here we demonstrate the basic idea of homogenization,introduce new understanding obtained from recent studies of homogenization of climate series in China,and raise issues for further studies in this field,especially with regards to climate extremes,uncertainty of the statistical adjustments,and biased physical relationships among different climate variables due to adjustments in single variable series.
