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.
Accurate and up-to-date land cover data are important for climate-change modeling. Quality assessment is becoming critical, as many satellite-based land cover products of differing scales have been released to meet the needs of scientific studies. In this study, the authors assessed the Moderate Resolution Imaging Spectroradiometer(MODIS) land cover products by analyzing the probability of interannual change from 2001 to 2012. The authors found that, cumulatively, 43.0% of MODIS land cover had changed over China from 2001 to 2012 at least once. Of this percentage, 12.1% was considered unreasonable change, 6.1% was considered reasonable change, and areas of confusion accounted for about 24.8%, giving rise to great uncertainty in the products. MODIS Collection 51 products clearly have less uncertainty than the Collection 5 products. Areas of reasonable change occurred in transition zones of ecological, biophysical, and climate gradients, while areas of unreasonable change appeared in heterogeneous landscapes. The misclassifications at three spatial scales of horizontal grids used in regional climate models occurred largely in the heterogeneous landscapes, and the areal percentage of misclassification decreased with larger horizontal grid spacing. In addition, the misclassifications in MODIS products often occurred among specific classes, which are geographically, ecologically, and spectrally similar, with low discriminative spectral-temporal signals. The effect of classification uncertainty should be made known, and further improvements are still needed for application in regional climate models. The authors' findings have important implications for better understanding the uncertainties of MODIS land cover products, and for improving the land surface parameterization for regional climate models.
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.
As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting(WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme(IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer(MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further;the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.
In this paper, based on the analysis of satellite measurements, the authors conclude that the continuous seasonal droughts intensify the browning of woody vegetation and that evergreen needleleaf forest(ENF) shows a larger browning percentage than other woody vegetation types over Yunnan Province. Based on the Tropical Rainfall Measuring Mission(TRMM) precipitation standardized anomaly, in the dry season, which is from October to March, the 2010 drought affected an area of Yunnan Province 1.77 times larger than the 2012 drought, but in the post-drought months(April to June), the browning area of all woody vegetation in 2012 was 1.11 times larger than that in 2010 on the basis of the enhanced vegetation index(EVI) standardized anomaly. The reduction of vegetation greenness over large areas of Yunnan Province represents a photosynthetic capacity loss which will have an impact on carbon fluxes to the atmosphere.
The changes in hydrological processes in the Yellow River basin were simulated by using the Community Land Model(CLM,version 3.5),driven by historical climate data observed from 1951 to 2008.A comparison of modeled soil moisture and runoff with limited observations in the basin suggests a general drying trend in simulated soil moisture,runoff,and precipitation-evaporation balance(P-E) in most areas of the Yellow River basin during the observation period.Furthermore,annual soil moisture,runoff,and P-E averaged over the entire basin have declined by 3.3%,82.2%,and 32.1%,respectively.Significant drying trends in soil moisture appear in the upper and middle reaches of the basin,whereas a significant trend in declining surface runoff and P-E occurred in the middle reaches and the southeastern part of the upper reaches.The overall decreasing water availability is characterized by large spatial and temporal variability.
Regional estimates of evapotranspiration (ET) are critical for a wide range of applications. Satellite remote sensing is a promising tool for obtaining reasonable ET spatial distribution data. However, there are at least two major problems that exist in the regional estimation of ET from remote sensing data. One is the conflicting requirements of simple data over a wide region, and accuracy of those data. The second is the lack of regional ET products that cover the entire region of northern China. In this study, we first retrieved the evaporative fraction (EF) by interpolating from the difference of day/night land surface temperature ( T ) and the normalized difference vegetation index (NDVI) triangular-shaped scatter space. Then, ET was generated from EF and land surface meteorological data. The estimated eight-day EF and ET results were validated with 14 eddy covariance (EC) flux measurements in the growing season (July-September) for the year2008 over the study area. The estimated values agreed well with flux tower measurements, and this agreement was highly statistically significant for both EF and ET (p <0.01), with the correlation coefficient for EF (R2 =0.64) being relatively higher than for ET (R2 =0.57). Validation with EC-measured ET showed the mean RMSE and bias were 0.78 mm d-1 (22.03 W m-2 ) and 0.31 mm d-1 (8.86 W m-2 ), respectively. The ET over the study area increased along a clear longitudinal gradient, which was probably controlled by the gradient of precipitation, green vegetation fractions, and the intensity of human activities. The satellite-based estimates adequately captured the spatial and seasonal structure of ET. Overall, our results demonstrate the potential of this simple but practical method for monitoring ET over regions with heterogeneous surface areas.
