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PRIMA_CLM4

CLM4 configuration and driving scripts under the PRIMA Initiative (https://im3.pnnl.gov/platform-regional-integrated-modeling-and-analysis-prima)

Repository for driving scripts and CLM4 NLDAS compsets (hist, RCP4.5, RCP8.5) developed under the PRIMA initiative, to be used on PNNL Institutional Computing facility, Constance

Repository structure

---scripts/shell | ---inputdata

Tutorial to configure the PRIMA CLM4 HIST, RCP4.5, and RCP8.5 cases

We provide detailed notes on running the CLM4 compsets on PIC Constance cluster.

Download script, data, and code repositories

Download script and data repository

setenv BASE_DIR <directory-of-choice>
cd $BASE_DIR
mkdir cases
git clone git@github.com:IMMM-SFA/PRIMA_CLM4.git
setenv CASE_DIR $BASE_DIR/cases
setenv INPUTDATA_DIR $BASE_DIR/PRIMA_CLM4/inputdata

Download CLM code, please check http://www.cesm.ucar.edu/models/ccsm4.0/index.html for instructions to download a released CLM4 version

cd $BASE_DIR
svn co https://svn-ccsm-release.cgd.ucar.edu/model_versions/ccsm4_0 clm4
setenv CLM_SRC_DIR $BASE_DIR/clm4
cd $CLM_SRC_DIR

Download data from NCAR repo, instruction for registration can be found at http://www.cesm.ucar.edu/models/cesm1.2

svn export https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/lnd/clm2/pftdata/pft-physiology.c100226 ${INPUTDATA_DIR}/cesm_inputdata/lnd/clm2/pftdata/pft-physiology.c100226
svn export https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/lnd/clm2/snicardata/snicar_drdt_bst_fit_60_c070416.nc ${INPUTDATA_DIR}/cesm_inputdata/lnd/clm2/snicardata/snicar_optics_5bnd_c090915.nc
svn export https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/lnd/clm2/snicardata/snicar_optics_5bnd_c090915.nc ${INPUTDATA_DIR}/cesm_inputdata/lnd/clm2/snicardata/snicar_optics_5bnd_c090915.nc
svn export https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/lnd/clm2/rtmdata/rdirc.05.061026 ${INPUTDATA_DIR}/cesm_inputdata/lnd/clm2/rtmdata/rdirc.05.061026

Download the NLDAS input datasets from https://dtn2.pnl.gov/data/im3/PRIMA/CLM

NOTE: NOT NECESSARY on Constance as symbolic links exist
Download data from https://dtn2.pnl.gov/data/im3/PRIMA/CLM/forcing to $INPUTDATA_DIR/user_inputdata/nldas2_forcing
Download data from https://dtn2.pnl.gov/data/im3/PRIMA/CLM/inputdata to $INPUTDATA_DIR/user_inputdata/nldas2_clm4

Configure the PRIMA CLM4 historical simulation

setenv PERIOD hist
cd $BASE_DIR/PRIMA_CLM4/scripts/shell
./setup_prima_clm4_hist.sh
cd $CASE_DIR/clm4_nldas_hist

Configure the PRIMA CLM4 RCP4.5 simulation

setenv PERIOD rcp45
cd $BASE_DIR/PRIMA_CLM4/scripts/shell
./setup_prima_clm4_rcp45.sh
cd $CASE_DIR/clm4_nldas_rcp45

Configure the PRIMA CLM4 RCP8.5 simulation

setenv PERIOD rcp85
cd $BASE_DIR/PRIMA_CLM4/scripts/shell
./setup_prima_clm4_rcp85.sh
cd $CASE_DIR/clm4_nldas_rcp85

Who do I talk to?

maoyi.huang at pnnl.gov

Description of the PRIMA CLM4 compsets

Note: associated datasets can be found at https://dtn2.pnl.gov/data/im3/PRIMA/CLM

The RESM simulations (Ke et al., 2012; Gao et al., 2014; Kraucunas et al. 2015) were postprocessed using bias correction to provide meteorological forcing for offline simulations using version 4 of the Community Land Model (CLM) (Oleson et al., 2010) at a resolution of one-eighth of a degree. The bias correction followed the method described by Wood et al. (2004). Data input to CLM, such as land cover, soil properties, and vegetation phenology, were retrieved from datasets developed by Ke et al. (2012) at a resolution of 0.05 degree and were aggregated to a resolution of one-eighth of a degree. CLM was spun up by recycling the meteorological forcing over the historical period (1975-2004) until all state variables, including soil moisture, soil temperature, and groundwater table depth, reached equilibrium.Then the model was forced by the two bias-corrected RESM downscaled climate scenarios, RCP4.5 and RCP8.5, to simulate terrestrial hydrological states and fluxes from 2005-2100.

Reference:

Kraucunas IP, LE Clarke, JA Dirks, JE Hathaway, MI Hejazi, KA Hibbard, M Huang, C Jin, MCW Kintner-Meyer, K Kleese van Dam, LYR Leung, H Li, RH Moss, MJ Peterson, JS Rice, MJ Scott, AM Thomson, N Voisin, and TO West. 2015. "Investigating the Nexus of Climate, Energy, Water, and Land at Decision-Relevant Scales: The Platform for Regional Integrated Modeling and Analysis (PRIMA)." Climatic Change 129(3-4):573-588. doi:10.1007/s10584-014-1064-9

Hejazi MI, N Voisin, L Liu, LM Bramer, DC Fortin, JE Hathaway, M Huang, GP Kyle, LYR Leung, H Li, Y Liu, PL Patel, TC Pulsipher, JS Rice, TK Tesfa, CR Vernon, and Y Zhou. 2015. "21st Century United States Emissions Mitigation Could Increase Water Stress more than the Climate Change it is Mitigating." Proceedings of the National Academy of Sciences of the United States of America 112(34):10635-10640. doi:10.1073/pnas.1421675112

Additional References:

Ke Y, et al. (2012) Development of High Resolution Land Surface Parameters for the Community Land Model. Geoscientific Model Development 5(6):1341-1362, https://doi.org/10.5194/gmd-5-1341-2012

Oleson KW, et al. (2010) Technical Description of version 4.0 of the Community Land Model (CLM). NCAR Technical Note NCAR/TN-478+STR (National Center for Atmospheric Research, Boulder, CO), 257 pp

Wood A, Leung L, Sridhar V, Lettenmaier D (2004) Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Change 62(1-3):189-216

Gao Y, LYR Leung, J Lu, Y Liu, M Huang, and Y Qian. 2014. "Robust Spring Drying in the Southwestern U.S. and Seasonal Migration of Wet/Dry Patterns in a Warmer Climate ." Geophysical Research Letters 41:1745-1751. doi:10.1002/2014GL059562

Recommended acknowledgement for using the compsets and driving scripts:

The authors would like to acknowledge M. Huang at Pacific Northwest National Laboratory (PNNL) for sharing the PRIMA CLM4 compsets and driving scripts, supported by the Platform for Regional Integrated Modeling and Analysis (PRIMA) Initiative and the U.S. Department of Energy, Office of Science as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program.

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