Modeling spatial and temporal variations in soil moisture in China

Abstract

On the basis of station observations, an atmospheric field (ObsFC) was constructed for the Community Land Model version 3.5 (CLM3.5). The model (CLM3.5 driven with ObsFC, hereafter referred as to CLM3.5/ObsFC) was used to simulate soil moisture (SM) from 1951 to 2008 in China. The resulting SM was compared with in situ observations, remote-sensing data and estimations made by various land models, indicating that CLM3.5/ObsFC is capable of reproducing the temporospatial characteristics and long-term variation trends of SM over China. Using an in situ observation-based forcing field improves the simulation of SM. Analysis of SM simulated using CLM3.5/ObsFC shows that the overall spatial pattern of SM was characterized by a gradually decreasing and alternating distribution of arid-humid zones from the southeast to northwest. Regionally averaged SM was the driest over southern Xinjiang Province and western Inner Mongolia, while the most humid regions were located over the Northeast Plain, Jianghuai region and the Yangtze River basin. The long-term variation trends of SM were generally characterized by increases in arid and humid regions and decreases in semiarid regions. Moreover, the variation was relatively intense from the mid-1970s to the mid-1990s in the arid region. The time series was more stable in the humid region except for a period near 1970 and after the year 2003. A downward trend was most prominent in the semiarid region from the 1990s to the end of the time series. Koster et al. [3] supported the mechanism of feedback between SM and precipitation on regional and continental scales. SM alters the processes of the water cycle between the land surface and the atmosphere, influencing precipitation, energy-cycle processes, and temperature [4]. Dai et al. in 1999 [5], demonstrated that SM reduces the diurnal temperature range in the lower atmosphere via evaporative cooling. In addition, SM is a relatively slowly varying component, having several months of "memory" of climatic information [6]. The Global Land-

Soil moisture-based study of the variability of dry-wet climate and climate zones in China

“…The above validation indicated that the ensemble soil moisture well reproduced the spatial distribution and linear trends, which can be further used to research regional climate change. Figure 3 shows the spatial distributions of soil moisture and their variances for scenario 20C3M for 1900-1999 and A1B for 2001-2099, which are generally in agreement with the historical simulations for the period of 1951-2008 [22] and which also both agree well with the distributions based on precipitation and temperature [60,61]. The soil moisture decreased gradually from southeast to northwest China, exhibiting high values in the northeast and middle and lower reaches of the Yangtze River.…”

“…Therefore, the monthly series of the ensemble soil moisture cannot be evaluated by using observations. Considering the fidelity of the spatial-temporal variations of the CLM3.5/ ObsFC soil moisture compared to the observations on various time scales (for example, the correlation coefficient is 0.84 for CLM3.5/ObsFC and observations in northeast China for 1990-2000, showing decreasing trends) [22], Figure 6 shows a comparison of the CLM3.5/ObsFC results and the ensemble soil moisture series, indicating that the variations agree well with each other on the decadal scale, especially over the latter 20 years. The results suggest that this is a practical approach for analyzing the dry-wet conditions and boundary dynamics of climate zones on a decadal scale.…”

“…Du and Liu [20] used the community land model (CLM) to analyze the potential response of soil moisture variability to global warming. Li et al [21,22] reported modeling patterns that illustrated the spatial-temporal characteristics of soil moisture variability in China using land and hydrological models driven by observed climate data. Agricultural droughts and their evolution have also been researched using land or hydrology models in China [23,24].…”

Variability of modeled runoff over China and its links to climate change

“…However, the soil moisture variability remains low compared with observations (Lawrence et al 2011). Based on our assessment of the applicability of CLM 3.5 across China and the observation-based datasets (Li and Ma 2010;Li et al 2011), we opted for CLM 3.5 to regenerate the long-term runoff variability. For a detailed description of CLM 3.5, the readers are referred to Oleson et al (2004) and the references therein.…”

Methodologies and applications in Digital China

“…Li et al [32] simulated SM from 1951 to 2008 using station observations and constructed an atmospheric field (ObsFC) for the Community Land Model version 3.5 (CLM3.5). CLM 3.5 is an improved and updated version of community land module derived from the Common Land Model and the Land Surface Model (LSM) of the National Center for Atmospheric Research.…”