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PREP Downscaled Climate Indicators

Summary climate indicators derived from the downscaled CMIP5 datasets NEX-GDDP (global) and LOCA (continental US).

Citation: Gassert, Francis, Enrique Cornejo, and Emily Nilson. 2021. "Making Climate Data Accessible: Methods for Producing NEX-GDDP and LOCA Downscaled Climate Indicators." Technical Note. World Resources Institute. Washington DC. Available at https://www.wri.org/research/making-climate-data-accessible

Background

This repository contains ensemble indicators derived from the downscaled CMIP5 datasets: NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) (Thrasher and Nemani 2015) for the globe and Localized Constructed Analogs (LOCA) CMIP5 projections for the continental United States (Pierce, Cayan, and Thrasher 2014; Maurer et al. 2007). NEX-GDDP and LOCA contain daily minimum and maximum temperature and precipitation values from several dozen models for two climate scenarios over the period of 1950-2100.

The data are derived following four steps:

  1. For each model, scenario, and year: compute annual indicators
  2. For each indicator, model, and scenario: compute moving averages (typically 30yrs)
  3. For each indicator, model, and scenario: compute difference and/or change layers
  4. For each indicator and scenario: compute statistics across the ensemble of models (e.g. median)

Filenames

Filenames are composed of the following parts, joined by underscores:

                        {formula}_{variable}_{scenario}_{model}_{years}_{dataset}.tif
# or expanding {formula} into subcomponents:
{ensemble}-{timefunc}-{indicator}_{variable}_{scenario}_{model}_{years}_{dataset}.tif

e.g. q50-abs-annual_pr_rcp85_ens_2035-2065_nexgddp.tif - Median absolute average annual (q50-abs-annual) precipitation (pr) for the high emissions scenario (rcp85) across the ensemble (ens) for the 31yr period centered on 2050 (2035-2065) derived from NEX-GDDP (nexgddp).

Formula

The formula defines what computations to run, the remainder of the keyname defines what data to run the computationts against. The {formula} can be decomposed further as follows:

# {formula} can be decompose into:
                      {indicator}_...
           {timefunc}-{indicator}_...
# or
{ensemble}-{timefunc}-{indicator}_...

Each of these components is a reducing function that depends on the previous. For example, computing ensemble median average annual (q50-abs-annual) precipitation from individual models' average annual (abs-annual) precipitation:

key is derived from
q50-abs-annual_..._ens_... abs-annual_..._ACCESS1-0_... abs-annual_..._BNU-ESM_... abs-annual_..._CCSM4_... abs-annual_..._CESM1-BGC_... abs-annual_..._CNRM-CM5_... ...

Or computing the 31yr average (abs-annual) precipitation from annual (annual) precipitation:

key is derived from
abs-annual_..._2035-2065_... annual_..._2035_... annual_..._2036_... annual_..._2037_... ... annual_..._2065_...

Valid values for keynames

  • ensemble
value description
q25 25th percentile
q50 median
q75 75th percentile
iqr interquartile range
mean mean
  • timefunc
value description
abs absolute i.e. the average value over the range of years
diff linear change from baseline (1960-1990) (i.e. abs_..._{startyear}-{endyear}_... minus abs_..._1960-1990_...)
ch multiplicative change from baseline (1960-1990) (i.e. abs_..._{startyear}-{endyear}_... divided by abs_..._1960-1990_...)
  • indicator
value description
annual annual average
q98 98th percentile for the year
q99 99th percentile for the year
gt-q98 number of days/yr exceeding the 98th percentile for the baseline period (1960-1990)
gt-q99 number of days/yr exceeding the 99th percentile for the baseline period (1960-1990)
gt50mm number of days/yr exceeding 0.0005787037037 (kg/m2/s) (50mm/day)
gt95f number of days/yr exceeding 308.15 (Kelvin)
gt90f number of days/yr exceeding 305.37 (Kelvin)
gt85f number of days/yr exceeding 302.59 (Kelvin)
gt32f number of days/yr exceeding 273.15 (Kelvin)
frostfree length of longest run of days in a year exceeding 273.15 (Kelvin)
drydays length of longest run of days in a year less than 0.000011574 (kg/m2/s) (1mm/day)
dryspells number of runs of at least 5 days in a year with less than 0.000011574 (kg/m2/s) (1mm/day). Each day over 5 days counts as 0.2 of a run.
tavg-tasmin Use with tasmax. Daily average temperature. (Specifically, daily value plus tasmin divided by 2.)
hdd65f-tasmin Use with tasmax. Heating degree days. The sum of 291.48 - value (Kelvin) (65ºF), where positive, for each day in a year.
cdd65f-tasmin Use with tasmax. Cooling degree days. The sum of value - 291.48 (Kelvin) (65ºF), where positive, for each day in a year.
  • variables
value description
pr precipitation (kg/ms/s)
tasmin daily minimum temperature
tasmax daily maximum temperature
  • scenario
value description
rcp45 Low emissions scenario
rcp85 High emissions scenario
historical Retrospective data (1990-2005 only)
  • model
value description
ACCESS1-0 BNU-ESM CCSM4 CESM1-BGC CNRM-CM5 CSIRO-Mk3-6-0 CanESM2 GFDL-CM3 GFDL-ESM2G GFDL-ESM2M IPSL-CM5A-LR IPSL-CM5A-MR MIROC-ESM-CHEM MIROC-ESM MIROC5 MPI-ESM-LR MPI-ESM-MR MRI-CGCM3 NorESM1-M bcc-csm1-1 inmcm4 Models included in NEX-GDDP
ACCESS1-0 ACCESS1-3 CCSM4 CESM1-BGC CESM1-CAM5 CMCC-CM CMCC-CMS CNRM-CM5 CSIRO-Mk3-6-0 CanESM2 EC-EARTH FGOALS-g2 GFDL-CM3 GFDL-ESM2G GFDL-ESM2M GISS-E2-H GISS-E2-R HadGEM2-AO HadGEM2-CC HadGEM2-ES IPSL-CM5A-LR IPSL-CM5A-MR MIROC-ESM MIROC-ESM-CHEM MIROC5 MPI-ESM-LR MPI-ESM-MR MRI-CGCM3 NorESM1-M bcc-csm1-1 bcc-csm1-1-m inmcm4 Models included in LOCA
ens For ensemble functions
  • years
value description
A single {year} between 1950 and 2100 Year of data (functions without a {timefunc})
A range of years {startyear}-{endyear} For multi-year averages (functions with a {timefunc})
  • dataset
value description
nexgddp Derive from NEX GDDP
loca Derive from LOCA

References

Thrasher, Bridget, and Rama Nemani. 2015. “NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP).” https://nex.nasa.gov/nex/projects/1356/.

Pierce, David W., Daniel R. Cayan, and Bridget L. Thrasher. 2014. “Statistical Downscaling Using Localized Constructed Analogs (LOCA).” Journal of Hydrometeorology 15 (6): 2558–2585. doi:10.1175/JHM-D-14-0082.1.

Maurer, Edwin P., Levi Brekke, Tom Pruitt, and Philip B. Duffy. 2007. “Fine-Resolution Climate Projections Enhance Regional Climate Change Impact Studies.” Eos, Transactions American Geophysical Union 88 (47). John Wiley & Sons, Ltd: 504–504. doi:10.1029/2007EO470006.

We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.