skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Simulating International Drought Experiment field observations using the Community Land Model

Abstract

Anthropogenic climate change will alter regional hydrologic cycles around the world, in part by increasing the frequency or duration of droughts in some areas. The International Drought Experiment (IDE) is investigating the impact of severe drought on terrestrial vegetation by experimentally reducing precipitation at dozens of sites. Here we implement the IDE precipitation reduction protocol using the Community Land Model (CLM). Though many model results suggest that carbon fertilization will outpace drought-caused reduction of terrestrial carbon uptake, uncertainty is large. We therefore configure CLM to consider carbon cycling impacts of reduced moisture availability without intertwining the effects of carbon fertilization or phenological changes. California hosts a number of IDE sites and a wide range of topography, climate, and biomes. CMIP5 predictions suggest 21st century California will experience droughts in excess of the 1000-year climatological record for both frequency and magnitude. CLM suggests that some regions, including much of Northern California, may experience a steeper decline in gross primary productivity (GPP) during 21st century severe droughts than during 20th century severe droughts. Vegetation in Northern California experiences virtually all of this GPP reduction during the dry season, with little wet season GPP reduction even during severe drought. Southern California vegetation experiencesmore » soil moisture GPP limitation at virtually all times, increasing substantially with drought severity. Southern California should experience a more pronounced shift in GPP seasonality and decline in magnitude relative to Northern California during droughts. Some parts of every vegetated continent see changes to drought response and seasonality similar to Southern California. Our CLM results provide drought impacts that forthcoming IDE field observations may test, can help to spatially upscale site-based IDE observations of drought impact, and provide CLM's prediction of reduced precipitation impacts per unit leaf area index.« less

Authors:
ORCiD logo [1];  [2];  [1]
  1. Univ. of California, Merced, CA (United States). Sierra Nevada Research Inst.
  2. Univ. of California, Santa Cruz, CA (United States). Environmental Studies Dept.
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory-National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1530405
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Agricultural and Forest Meteorology
Additional Journal Information:
Journal Volume: 266-267; Journal Issue: C; Journal ID: ISSN 0168-1923
Country of Publication:
United States
Language:
English

Citation Formats

Hilton, Timothy W., Loik, Michael E., and Campbell, J. Elliott. Simulating International Drought Experiment field observations using the Community Land Model. United States: N. p., 2019. Web. doi:10.1016/j.agrformet.2018.12.016.
Hilton, Timothy W., Loik, Michael E., & Campbell, J. Elliott. Simulating International Drought Experiment field observations using the Community Land Model. United States. doi:10.1016/j.agrformet.2018.12.016.
Hilton, Timothy W., Loik, Michael E., and Campbell, J. Elliott. Fri . "Simulating International Drought Experiment field observations using the Community Land Model". United States. doi:10.1016/j.agrformet.2018.12.016.
@article{osti_1530405,
title = {Simulating International Drought Experiment field observations using the Community Land Model},
author = {Hilton, Timothy W. and Loik, Michael E. and Campbell, J. Elliott},
abstractNote = {Anthropogenic climate change will alter regional hydrologic cycles around the world, in part by increasing the frequency or duration of droughts in some areas. The International Drought Experiment (IDE) is investigating the impact of severe drought on terrestrial vegetation by experimentally reducing precipitation at dozens of sites. Here we implement the IDE precipitation reduction protocol using the Community Land Model (CLM). Though many model results suggest that carbon fertilization will outpace drought-caused reduction of terrestrial carbon uptake, uncertainty is large. We therefore configure CLM to consider carbon cycling impacts of reduced moisture availability without intertwining the effects of carbon fertilization or phenological changes. California hosts a number of IDE sites and a wide range of topography, climate, and biomes. CMIP5 predictions suggest 21st century California will experience droughts in excess of the 1000-year climatological record for both frequency and magnitude. CLM suggests that some regions, including much of Northern California, may experience a steeper decline in gross primary productivity (GPP) during 21st century severe droughts than during 20th century severe droughts. Vegetation in Northern California experiences virtually all of this GPP reduction during the dry season, with little wet season GPP reduction even during severe drought. Southern California vegetation experiences soil moisture GPP limitation at virtually all times, increasing substantially with drought severity. Southern California should experience a more pronounced shift in GPP seasonality and decline in magnitude relative to Northern California during droughts. Some parts of every vegetated continent see changes to drought response and seasonality similar to Southern California. Our CLM results provide drought impacts that forthcoming IDE field observations may test, can help to spatially upscale site-based IDE observations of drought impact, and provide CLM's prediction of reduced precipitation impacts per unit leaf area index.},
doi = {10.1016/j.agrformet.2018.12.016},
journal = {Agricultural and Forest Meteorology},
issn = {0168-1923},
number = C,
volume = 266-267,
place = {United States},
year = {2019},
month = {3}
}