Advancements in the RUC land-surface model for use in the next-generation high-resolution weather prediction models

Smirnova, Tatiana G.; Benjamin, Stanley G.

doi:10.25923/55x8-cy36

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The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

i

Advancements in the RUC land-surface model for use in the next-generation high-resolution weather prediction models

2025
By Smirnova, Tatiana G. ; Benjamin, Stanley G.
Series: NOAA technical memorandum OAR GSL ; 73

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Details:

Personal Author:

Smirnova, Tatiana G. ; Benjamin, Stanley G.

Smirnova, Tatiana G. ; Benjamin, Stanley G. Less -
Corporate Authors:

Global Systems Laboratory (U.S.) ; University of Colorado Boulder. Cooperative Institute for Research in Environmental Sciences.

Global Systems Laboratory (U.S.) ; University of Colorado Boulder. Cooperative Institute for Research in Environmental Sciences. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; GSL (Global Systems Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences)

OAR (Oceanic and Atmospheric Research) ; GSL (Global Systems Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences) Less -
Description:

Weather prediction models are, in fact, coupled earth-system models requiring accurate representation of land-surface processes to provide accurate atmospheric predictions. From continued evaluation of the NOAA HRRR weather prediction model, the RUC land-surface model (RUC LSM) has been refined yet more to improve near-surface temperature and moisture predictions. In this paper, we describe the RUC LSM changes since 2015 including improvements for evaporation and soil moisture processes, for snow-cover fraction processes, and of new land-use datasets including satellite-based green vegetation fraction not previously available. This resulted in improvements in predictions of near-surface air temperature and moisture.
Keywords:

[+]

GSL Weather Modeling
Series:

NOAA technical memorandum OAR GSL ; 73
DOI:

https://doi.org/10.25923/55x8-cy36
Format:

pdf
Publisher:

NOAA Oceanic and Atmospheric Research - https://ror.org/02kgve346 ; NOAA Global Systems Laboratory - https://ror.org/006ddyp05 ; Cooperative Institute for Research in Environmental Sciences - https://ror.org/00bdqav06

NOAA Oceanic and Atmospheric Research - https://ror.org/02kgve346 ; NOAA Global Systems Laboratory - https://ror.org/006ddyp05 ; Cooperative Institute for Research in Environmental Sciences - https://ror.org/00bdqav06 Less -
Document Type:

Technical Memorandum
License:

https://creativecommons.org/publicdomain/zero/1.0/
Rights Information:

CC0 Public Domain
Compliance:

Submitted
Main Document Checksum:

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urn:sha-512:65719facd3399e6d5f0ad600f93961451fc35071197d04932805aac69ba595dd5123dd2c8f1c145f9b1794550346fe0bdb61c60df546bbeed300cbfee572dfd0
Download URL:

https://repository.library.noaa.gov/view/noaa/67053/noaa_67053_DS1.pdf
File Type:

[PDF-2.83 MB]