Articles | Volume 18, issue 4
https://doi.org/10.5194/tc-18-1835-2024
https://doi.org/10.5194/tc-18-1835-2024
Research article
 | 
18 Apr 2024
Research article |  | 18 Apr 2024

Validation of pan-Arctic soil temperatures in modern reanalysis and data assimilation systems

Tyler C. Herrington, Christopher G. Fletcher, and Heather Kropp

Data sets

Ensemble Mean Reanalysis Soil Temperature Dataset (1982–2018) Tyler Herrington and Christopher G. Fletcher https://doi.org/10.18739/A2GF0MZ00

GTN-P global mean annual ground temperature data for permafrost near the depth of zero annual amplitude (2007-2016) GTN-P https://doi.org/10.1594/PANGAEA.884711

Synthesis of soil-air temperature and vegetation measurements in the pan-Arctic. 1990-2016 Heather Kropp et al. https://doi.org/10.18739/A2736M31X

NCEP Climate Forecast System Version 2 (CFSv2) Monthly Products S. Saha et al. https://doi.org/10.5065/D69021ZF

FLDAS Noah Land Surface Model L4 Global Monthly 0.1 x 0.1 degree (MERRA-2 and CHIRPS) Amy McNally NASA/GSFC/HSL https://doi.org/10.5067/5NHC22T9375G

MERRA-2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Land Surface Diagnostics V5.12.4 Global Modeling and Assimilation Office (GMAO) https://doi.org/10.5067/RKPHT8KC1Y1T

Ground Temperature Map, 2000-2016, North- ern Hemisphere Permafros J. Obu et al. https://doi.org/10.1594/PANGAEA.888600

NCEP Climate Forecast System Reanalysis (CFSR) Monthly Products, January 1979 to December 2010 S. Saha et al. https://doi.org/10.5065/D6DN438J

Copernicus Global Digital Elevation Model GLO-90 European Space Agency https://doi.org/10.5069/G9028PQB

ERA5 Re- analysis (Monthly Mean 0.25 Degree Latitude-Longitude Grid) European Centre for Medium-Range Weather Forecasts https://doi.org/10.5065/P8GT-0R61

ERA5-Land monthly averaged data from 1950 to present J. Muñoz Sabater https://doi.org/10.24381/cds.68d2bb30

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Short summary
Here we validate soil temperatures from eight reanalysis products across the pan-Arctic and compare their performance to a newly calculated ensemble mean soil temperature product. We find that most product soil temperatures have a relatively large RMSE of 2–9 K. It is found that the ensemble mean product outperforms individual reanalysis products. Therefore, we recommend the ensemble mean soil temperature product for the validation of climate models and for input to hydrological models.