Assessment of a Long-Term High-Resolution Hydroclimatic Dataset for the US Midwest

作者：Niyogi Dev; Jacobs Elin M^*; Liu Xing; Kumar Anil; Biehl Larry; Rao P Suresh C

来源：Earth Interactions, 2017, 21(4): 4.

DOI：10.1175/EI-D-16-0022.1

• Physical meteorology and climatology
• Evapotranspiration
• Soil moisture
• Soil temperature
• Models and modeling
• Data assimilation
• Land surface model
• Model evaluation

A new, high-resolution (4 km), gridded land surface dataset produced with the Land Information System (LIS) is introduced, and the first set of synthesis of key hydroclimatic variables is reported. The dataset is produced over a 33-yr time period (1980-2012) for the U.S. Midwest with the intent to aid the agricultural community in understanding hydroclimatic impacts on crop production and decision-making in operational practices. While approximately 20 hydroclimatic variables are available through the LIS dataset, the focus here is on soil water content, soil temperature, and evapotranspiration. To assess the performance of the model, the LIS dataset is compared with in situ hydrome-teorological observations across the study domain and with coarse-resolution reanalysis products [NARR, MERRA, and NLDAS-2 (phase 2 of the North American Land Data Assimilation System)]. In agricultural regions such as the U.S. Midwest, finescale hydroclimatic mapping that links the regional scale to the field scale is necessary. The new dataset provides this link as an intermediate-scale product that links point observations and coarse gridded datasets. In general, the LIS dataset compares well with in situ observations and coarser gridded products in terms of both temporal and spatial patterns, but cases of strong disagreement exist particularly in areas with sandy soils. The dataset is made available to the broader research community as an effort to fill the gap in spatial hydroclimatic data availability.

• 出版日期2017-5