Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Massoud, Elias C.; Andrews, Lauren; Reichle, Rolf; Molod, Andrea; Park, Jongmin; Ruehr, Sophie; Girotto, Manuela

doi:https://doi.org/10.5194/esd-14-147-2023

Articles | Volume 14, issue 1

https://doi.org/10.5194/esd-14-147-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-14-147-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 1

Research article

|

08 Feb 2023

Research article |

| 08 Feb 2023

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Elias C. Massoud, Lauren Andrews, Rolf Reichle, Andrea Molod, Jongmin Park, Sophie Ruehr, and Manuela Girotto

Supplement

https://doi.org/10.5194/esd-14-147-2023-supplement

Data sets

S2S-2\_1: File Specification, GMAO Office Note No. 16 (Version 1.0) K. Nakada, R. Kovach, J. Marshak, and A. Molod http://gmao.gsfc.nasa.gov/pubs/office_notes

MERRA-2 tavgM\_2d\_slv\_Nx: 2d Global Modeling and Assimilation Office https://doi.org/10.5067/AP1B0BA5PD2K

MERRA-2 tavgM\_2d\_slv\_Nx: 2d Global Modeling and Assimilation Office https://doi.org/10.5067/0JRLVL8YV2Y4

MERRA-2 MERRA-2 tavgM\_2d\_slv\_Nx: 2d Global Modeling and Assimilation Office https://doi.org/10.5067/8S35XF81C28F

ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate Copernicus Climate Change Service https://cds.climate.copernicus.eu/cdsapp\#/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview

MODIS/Terra Snow Cover Daily L3 Global 0.05Deg CMG D. K. Hall and G. A. Riggs https://doi.org/10.5067/MODIS/MOD10C1.006

MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid D. K. Hall and G. A. Riggs https://doi.org/10.5067/MODIS/MOD10A1.006

igh Mountain Asia UCLA Daily Snow Reanalysis Y. Liu, Y. Fang, and S. A. Margulis https://doi.org/10.5067/HNAUGJQXSCVU

TELLUS\_GRAC\_L3\_CSR\_RL06\_LND\_v04, Ver. RL06 v04 F. Landerer https://doi.org/10.5067/TELND-3AC64

Download

Article (14074 KB)
Full-text XML

Short summary

In this study, we benchmark the forecast skill of the NASA’s Goddard Earth Observing System subseasonal-to-seasonal (GEOS-S2S version 2) hydrometeorological forecasts in the High Mountain Asia (HMA) region. Hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system’s ability to forecast HMA hydrometeorology on the seasonal timescale.