Title:

Monthly drought index for the conterminous United States: 6-month and 36-month Standardized Precipitation Evapotranspiration Index (SPEI) for 10 climate scenarios, 1950-2070

Author(s):

Costanza, Jennifer K.; Koch, Frank H.; Reeves, Matthew C.

Publication Year:

2023

How to Cite:

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Costanza, Jennifer K.; Koch, Frank H.; Reeves, Matthew C. 2023. Monthly drought index for the conterminous United States: 6-month and 36-month Standardized Precipitation Evapotranspiration Index (SPEI) for 10 climate scenarios, 1950-2070. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0075

Abstract:

Drought is an important stressor affecting forests and rangelands. The Standardized Precipitation Evapotranspiration Index (SPEI) is a meteorological drought index that can be used to investigate trends in drought over time. The SPEI allows for comparisons among locations for historical as well as future conditions, and can be computed over multiple time scales, making it useful for monitoring drought in different ecological contexts. We calculated the 6-month and 36-month SPEI, which assigns values for a given month by comparing the cumulative climatic water balance (precipitation minus potential evapotranspiration, or PET) for the previous 6- or 36-month period to the same cumulative 6- or 36-month water balance for all months in a reference period (defined here as 1950 to 2005). Because of the 6- and 36-month lags in the calculation, the first month in these data sets with data are July 1950 (6-month SPEI) and January 1953 (36-month SPEI).

This data publication consists of 10 sets of geoTIFF (TIF) raster files with monthly values for the SPEI for the period 1950-2070. We calculated the SPEI using temperature and potential evapotranspiration (PET) data from the MACAv2-METDATA for five global climate models for a historical modeled period (1950-2005) and a future period (2006-2070). For the future period, two Representative Concentration Pathways (RCPs), RCP 4.5 and 8.5 were used. The five global climate models used were: MRI-CGCM3, HadGEM2-ES, IPSL-CM5A-MR, CNRM-CM5, NorESM-M. The result was a total of ten future climates. Those are the same ten climates used in the 2020 Resources Planning Act (RPA) Assessment. The spatial extent and resolution of the data match those of the MACAv2-METDATA, covering the conterminous United States at a grid cell size of approximately 4 kilometers (1/24 degree) on a side.

Keywords:

climatologyMeteorologyAtmosphere; environment; Climate change; drought; Standardized Precipitation Evapotranspiration Index; RPA Assessment; Resources Planning Act Assessment; conterminous United States; CONUS

Related publications:

• Abatzoglou, John T.; Brown, Timothy J. 2012. A comparison of statistical downscaling methods suited for wildfire applications. International Journal of Climatology. 32(5): 772-780. https://doi.org/10.1002/joc.2312
• Costanza, Jennifer K.; Koch, Frank H.; Reeves, Matthew C. 2023. Future exposure of forest ecosystems to multi-year drought in the United States. Ecosphere. 14(5): e525. https://doi.org/10.1002/ecs2.4525 https://research.fs.usda.gov/treesearch/66126
• Costanza, Jennifer K.; Koch, Frank H.; Reeves, Matthew C. 2023. Monthly drought index for the conterminous United States: 6-month and 36-month Standardized Precipitation Evapotranspiration Index (SPEI) for observed climate data, 1950-2018. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0086
• More (5 total)

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  • RDS-2022-0075_Metadata_Fileindex.zip (16.82 KB; Checksum)
  • RDS-2022-0075_Supplements.zip (3.06 KB; Checksum)
  • RDS-2022-0075_Data_spei_06_cnrm_cm5.zip (4.58 GB; Checksum)
  • RDS-2022-0075_Data_spei_06_hadgem2_es365.zip (4.56 GB; Checksum)
  • RDS-2022-0075_Data_spei_06_ipsl_cm5a_mr.zip (4.56 GB; Checksum)
  • RDS-2022-0075_Data_spei_06_mri_cgcm3.zip (4.6 GB; Checksum)
  • RDS-2022-0075_Data_spei_06_noresm1_m.zip (4.57 GB; Checksum)
  • RDS-2022-0075_Data_spei_36_cnrm_cm5.zip (4.51 GB; Checksum)
  • RDS-2022-0075_Data_spei_36_hadgem2_es365.zip (4.45 GB; Checksum)
  • RDS-2022-0075_Data_spei_36_ipsl_cm5a_mr.zip (4.45 GB; Checksum)
  • RDS-2022-0075_Data_spei_36_mri_cgcm3.zip (4.54 GB; Checksum)
  • RDS-2022-0075_Data_spei_36_noresm1_m.zip (4.48 GB; Checksum)

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