A Global Land Data Assimilation System (GLDAS) has been developed. Its purpose is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes. GLDAS is unique in that it is an uncoupled land surface modeling system that drives multiple models, integrates a huge quantity of observation-based data, runs globally at high resolution (0.25°), and produces results in near–real time (typically within 48 h of the present). GLDAS is also a test bed for innovative modeling and assimilation capabilities. A vegetation-based “tiling” approach is used to simulate subgrid-scale variability, with a 1-km global vegetation dataset as its basis. Soil and elevation parameters are based on high-resolution global datasets. Observation-based precipitation and downward radiation and output fields from the best available global coupled atmospheric data assimilation systems are employe...

The Global Land Data Assimilation System

Investigating soil moisture-climate interactions in a changing climate: A review

A review of drought concepts

The Intergovernmental Panel on Climate Change (IPCC) Technical Paper Climate Change and Water draws together and evaluates the information in IPCC Assessment and Special Reports concerning the impacts of climate change on hydrological processes and regimes, and on freshwater resources – their availability, quality, use and management. It takes into account current and projected regional key vulnerabilities, prospects for adaptation, and the relationships between climate change mitigation and water. Its objectives are:

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Climate change and water.

Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a lack of observational data and by the model dependence of computational estimates. To counter the second limitation, a dozen climate-modeling groups have recently performed the same highly controlled numerical experiment as part of a coordinated comparison project. This allows a multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Potential benefits of this estimation may include improved seasonal rainfall forecasts.

https://science.sciencemag.org/content/sci/305/5687/1138.full.pdf

Regions of Strong Coupling Between Soil Moisture and Precipitation

Soil moisture is an important variable in the climate system. Understanding and predicting variations of surface temperature, drought, and flood depend critically on knowledge of soil moisture variations, as do impacts of climate change and weather forecasting. An observational dataset of actual in situ measurements is crucial for climatological analysis, for model development and evaluation, and as ground truth for remote sensing. To that end, the Global Soil Moisture Data Bank, a Web site (http://climate.envsci.rutgers.edu/soil—moisture) dedicated to collection, dissemination, and analysis of soil moisture data from around the globe, is described. The data bank currently has soil moisture observations for over 600 stations from a large variety of global climates, including the former Soviet Union, China, Mongolia, India, and the United States. Most of the data are in situ gravimetric observations of soil moisture; all extend for at least 6 years and most for more than 15 years. Most of the stat...

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The Global Soil Moisture Data Bank

Scales of soil moisture variations are important for understanding patterns of climate change, for developing and evaluating land surface models, for designing surface soil moisture observation networks, and for determining the appropriate resolution for satellite-based remote sensing instruments for soil moisture. Here we take advantage of a new archive of in situ soil moisture observations from Illinois and Iowa in the United States, and from Russia, Mongolia, and China, to evaluate the observed temporal and spatial scales of soil moisture variations. We separate the variance into two components, the very small scale, determined by soils, topography, vegetation, and root structure, and the large scale forced by the atmosphere. This larger scale, determined by precipitation and evaporation patterns, is of interest for global climate modeling. We characterize the small scale as white noise for our analysis, keeping in mind that it is an important component of soil moisture variations for other problems. We find that the atmospheric spatial scale for all regions is about 500 km. The atmospheric temporal scale is about 2 months for the top 1-m soil layer. The temporal scale for the top 10-cm layer is slightly less than 2 months. The white noise component of the variance for temporal variations ranges from 50% for the top 10 cm to 20–40% for the top 1 m. For spatial variations the white noise component is the same for all depths but varies with region from 30% for Illinois to around 70% for Mongolia. Nevertheless, the red noise (atmospheric component) can be seen in all regions. These results are for Northern Hemisphere midlatitudes and would not necessarily apply to other latitudes. The results are based on observations taken from grassland or agricultural areas, and may not be similar to those of areas with other vegetation types. In China, a region with substantial latitudinal variation, the temporal scale for the top 1 m varies from 1 month in the south to 2.5 months in the north, demonstrating the control of potential evaporation on the temporal scales. Seasonal analysis of the scales of soil moisture for Illinois shows that during the winter the temporal scales are long, though the spatial scales are short. We suggest that these variations are both attributable to the seasonal cycle of potential evaporation.

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Temporal and spatial scales of observed soil moisture variations in the extratropics

An assessment of storage terms in the surface energy balance of maize and soybean

Ten years of soil moisture measurements (biweekly from March through September and monthly during winter) within the top 1 m of soil at 17 grass-covered sites across Illinois are analyzed to provide a climatology of soil moisture for this important Midwest agricultural region. Sod moisture measurements were obtained with neutron probes that were calibrated for each site. Measurement errors are dependent upon the volumetric water content with errors less than 20 percent when soil moisture is above 10 percent of soil volume. Single point errors in moisture measurements from the top 1 m of soil range from 6 percent to 13 percent when volumetric soil moisture is 30 percent of soil volume. The average depletion in moisture between winter and summer over the 10-year period for the top 2 m of soil in Illinois was 72.3 mm. Three-quarters of this decrease occurred above 0.5 m and only 5 percent occurred between the 1.0-m and 2.0-m depths. The average moisture decrease between winter and summer during a we...

Steven E. Hollinger

Papers

The Global Soil Moisture Data Bank

Temporal and spatial scales of observed soil moisture variations in the extratropics

An assessment of storage terms in the surface energy balance of maize and soybean

A Soil Moisture Climatology of Illinois

Application of MODIS derived parameters for regional crop yield assessment