Evaluation of soil moisture in CMIP5 simulations over the contiguous United States using in situ and satellite observations
This study provides a comprehensive evaluation of soil moisture simulations in the Coupled Model Intercomparison Project Phase 5 (CMIP5) extended historical experiment (2003 to 2012). Soil moisture from in situ and satellite sources is used to evaluate CMIP5 simulations in the contiguous United Stat...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-04-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | http://www.hydrol-earth-syst-sci.net/21/2203/2017/hess-21-2203-2017.pdf |
Summary: | This study provides a comprehensive evaluation of soil moisture
simulations in the Coupled Model Intercomparison Project Phase 5 (CMIP5)
extended historical experiment (2003 to 2012). Soil moisture from in situ and
satellite sources is used to evaluate CMIP5 simulations in the contiguous
United States (CONUS). Both near-surface (0–10 cm) and soil column (0–100 cm) simulations from more than 14 CMIP5 models are evaluated during the warm
season (April–September). Multimodel ensemble means and the performance of
individual models are assessed at a monthly timescale. Our results indicate
that CMIP5 models can reproduce the seasonal variability in soil moisture
over CONUS. However, the models tend to overestimate the amount of both
near-surface and soil column soil moisture in the western US and
underestimate it in the eastern US. There are large variations across
models, especially for the near-surface soil moisture. There are significant
regional variations in performance as well. Results of a regional analysis
show that in the deeper soil layers, the CMIP5 soil moisture simulations tend
to be most skillful in the southern US. Based on both the satellite-derived
and in situ soil moisture, CESM1, CCSM4 and GFDL-ESM2M perform best in the
0–10 cm soil layer and CESM1, CCSM4, GFDL-ESM2M and HadGEM2-ES perform best
in the 0–100 cm soil layer. |
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ISSN: | 1027-5606 1607-7938 |