Published December 14, 2020 | Version v1
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Data processing pipeline and additional input files for Müller et al. (2021): Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios, Environmental Research Letters

  • 1. Potsdam Institute for Climate Impact Research

Description

Data processing for computing yield projections with GGCMI Phase 2 (Franke et al. 2020a) emulators (Franke et al. 2020b) for CMIP5 and CMIP6 climate projections.

TOC

1. data and scripts included here
2. get climate projection data
3. get GGCMI Phase 2 emulator parameters and growing season data
4. concatenate climate files, regrid
5. process data


## 1. data and scripts included here

This archive contains:
a) fertilizer data from Elliott et al. 2015, also published elsewhere
b) a boolean mask for spring and winter wheat areas used in the processing (Jägermeyr et al. under review)
c) scripts to process climate data, including the target grid description file
d) scripts to process climate and emulator data to produce results and analyze data

## 2. get climate projection data

monthly resolution (Amon) climate projections for precipitation (pr) and daily average surface temperatures (tas) need to be downloaded from the CMIP5 and CMIP6 archives
I used a synda setup getting finding suitable data sets by e.g.

synda search realm=atmos limit=1000 table_id=Amon mip_era=CMIP6 latest=true variable_id=tas,pr experiment_id=historical,ssp126,ssp245,ssp585 > cmip_list

 

## 3. get GGCMI Phase 2 emulator parameters and growing season data

download crop model emulator parameter sets (Franke et al. 2020b) from https://doi.org/10.5281/zenodo.2605373

download growing season data from Elliott et al. (2015) and Franke et al. (2020a) https://doi.org/10.5281/zenodo.3773819

## 4. concatenate climate files, regrid

adjust paths and other settings in script 'process_raw_cmip6_inputs_01.sh' to process data. This works similarly for CMIP5.

Needs the target grid description file 'lonlat05_grid.des' included here.

## 5. process data

execute script 'processing_data_master.R'
This script will take a lot of computation time, so you need to parallelize the execution and compute bits and pieces in the right sequence.

Select individual processing steps by setting 'if(F)' to 'if(T)'

References

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015.

Franke JA, Müller C, Elliott J, Ruane AC, Jägermeyr J, Balkovic J, Ciais P, Dury M, Falloon PD, Folberth C, François L, Hank T, Hoffmann M, Izaurralde RC, Jacquemin I, Jones C, Khabarov N, Koch M, Li M, Liu W, Olin S, Phillips M, Pugh TAM, Reddy A, Wang X, Williams K, Zabel F, and Moyer EJ. 2020a, The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0), Geosci. Model Dev., 13, 2315-2336, doi: 10.5194/gmd-13-2315-2020.

Franke JA, Müller C, Elliott J, Ruane AC, Jägermeyr J, Snyder A, Dury M, Falloon PD, Folberth C, François L, Hank T, Izaurralde RC, Jacquemin I, Jones C, Li M, Liu W, Olin S, Phillips M, Pugh TAM, Reddy A, Williams K, Wang Z, Zabel F, and Moyer EJ. 2020, The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0), Geosci. Model Dev., 13, 3995-4018, doi: 10.5194/gmd-13-3995-2020.

Jägermeyr J et al. under review

Müller C, Franke J, Jägermeyr J, Ruane AC, Elliott J, Moyer E, Heinke J, Falloon P, Folberth C, Francois L, Hank T, Izaurralde RC, Jacquemin I, Liu W, Olin S, Pugh T, Williams KE, and Zabel F. 2021, Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios, 2021, Environmental Research Letters, doi: 10.1088/1748-9326/abd8fc.

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Additional details

References

  • Franke JA, Müller C, Elliott J, Ruane AC, Jägermeyr J, Balkovic J, Ciais P, Dury M, Falloon PD, Folberth C, François L, Hank T, Hoffmann M, Izaurralde RC, Jacquemin I, Jones C, Khabarov N, Koch M, Li M, Liu W, Olin S, Phillips M, Pugh TAM, Reddy A, Wang X, Williams K, Zabel F, and Moyer EJ. 2020, The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0), Geosci. Model Dev., 13, 2315-2336, doi: 10.5194/gmd-13-2315-2020
  • Franke JA, Müller C, Elliott J, Ruane AC, Jägermeyr J, Snyder A, Dury M, Falloon PD, Folberth C, François L, Hank T, Izaurralde RC, Jacquemin I, Jones C, Li M, Liu W, Olin S, Phillips M, Pugh TAM, Reddy A, Williams K, Wang Z, Zabel F, and Moyer EJ. 2020, The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0), Geosci. Model Dev., 13, 3995-4018, doi: 10.5194/gmd-13-3995-2020
  • Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015
  • Müller et al. (2021): Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios, Environmental Research Letters, doi: 10.1088/1748-9326/abd8fc.