Evaluation of hydrologic components of community land model 4 and bias identification

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM...

Full description

Bibliographic Details
Published in:International Journal of Applied Earth Observation and Geoinformation
Main Authors: Du, Enhao, Vittorio, Alan Di, Collins, William D.
Language:unknown
Published: 2021
Subjects:
Online Access:http://www.osti.gov/servlets/purl/1421795
https://www.osti.gov/biblio/1421795
https://doi.org/10.1016/j.jag.2015.03.013
id ftosti:oai:osti.gov:1421795
record_format openpolar
spelling ftosti:oai:osti.gov:1421795 2023-07-30T04:02:06+02:00 Evaluation of hydrologic components of community land model 4 and bias identification Du, Enhao Vittorio, Alan Di Collins, William D. 2021-07-26 application/pdf http://www.osti.gov/servlets/purl/1421795 https://www.osti.gov/biblio/1421795 https://doi.org/10.1016/j.jag.2015.03.013 unknown http://www.osti.gov/servlets/purl/1421795 https://www.osti.gov/biblio/1421795 https://doi.org/10.1016/j.jag.2015.03.013 doi:10.1016/j.jag.2015.03.013 54 ENVIRONMENTAL SCIENCES 2021 ftosti https://doi.org/10.1016/j.jag.2015.03.013 2023-07-11T09:24:15Z Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties in the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation. Other/Unknown Material Arctic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic International Journal of Applied Earth Observation and Geoinformation 48 5 16
institution Open Polar
collection SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
op_collection_id ftosti
language unknown
topic 54 ENVIRONMENTAL SCIENCES
spellingShingle 54 ENVIRONMENTAL SCIENCES
Du, Enhao
Vittorio, Alan Di
Collins, William D.
Evaluation of hydrologic components of community land model 4 and bias identification
topic_facet 54 ENVIRONMENTAL SCIENCES
description Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties in the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.
author Du, Enhao
Vittorio, Alan Di
Collins, William D.
author_facet Du, Enhao
Vittorio, Alan Di
Collins, William D.
author_sort Du, Enhao
title Evaluation of hydrologic components of community land model 4 and bias identification
title_short Evaluation of hydrologic components of community land model 4 and bias identification
title_full Evaluation of hydrologic components of community land model 4 and bias identification
title_fullStr Evaluation of hydrologic components of community land model 4 and bias identification
title_full_unstemmed Evaluation of hydrologic components of community land model 4 and bias identification
title_sort evaluation of hydrologic components of community land model 4 and bias identification
publishDate 2021
url http://www.osti.gov/servlets/purl/1421795
https://www.osti.gov/biblio/1421795
https://doi.org/10.1016/j.jag.2015.03.013
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation http://www.osti.gov/servlets/purl/1421795
https://www.osti.gov/biblio/1421795
https://doi.org/10.1016/j.jag.2015.03.013
doi:10.1016/j.jag.2015.03.013
op_doi https://doi.org/10.1016/j.jag.2015.03.013
container_title International Journal of Applied Earth Observation and Geoinformation
container_volume 48
container_start_page 5
op_container_end_page 16
_version_ 1772812817004494848