Glacier parameterization in SLAV numerical weather prediction model-Reference-Cited by-同舟云学术

Glacier parameterization in SLAV numerical weather prediction model

Published:2022-08-01 Issue:4 Volume:37 Page:189-201
ISSN:0927-6467
Container-title:Russian Journal of Numerical Analysis and Mathematical Modelling
language:en
Short-container-title:

Author:

Fadeev Rostislav Yu.¹²³⁴,Alipova Kseniya A.¹²,Koshkina Anna S.⁵,Lapin Timofey E.³,Ozerova Nadezhda A.⁵,Pereladova Alina E.⁶,Sakhno Andrey V.⁷,Tolstykh Mikhail A.¹²³⁴

Affiliation:

1. Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences , Moscow 119333 , Russia

2. Hydrometeorological Centre of Russia , Moscow 123376 , Russia

3. Moscow institute of Physics and Technology (National Research University) , Dolgoprudnii 141700 , Russia

4. Moscow Center for Fundamental and Applied Mathematics at INM RAS , Moscow 119333 , Russia

5. Russian State Hydrometeorological University , Saint Petersburg 192007 , Russia

6. Novosibirsk State University , Novosibirsk 630090 , Russia

7. National Research University of Electronic Technology , Zelenograd 124498 , Moscow , Russia

Abstract

Abstract In the present paper, we describe a one-dimensional glacier parameterization for use in the numerical weather prediction models. The proposed scheme is implemented into the global atmospheric model SLAV. To avoid inconsistency of surface temperature and turbulent heat fluxes in the lower troposphere, glacier parameterization has been iteratively coupled with both planetary boundary layer and land surface schemes. First results from numerical experiments with the SLAV model show that the introduction of a simplified description of the glacier heat capacity can significantly improve the 2-meter temperature long-range weather forecast skill.

Publisher

Walter de Gruyter GmbH

Subject

Modeling and Simulation,Numerical Analysis

Link

https://www.degruyter.com/document/doi/10.1515/rnam-2022-0016/pdf

Reference38 articles.

1. S. Boussetta, G. Balsamo, G. Arduini, E. Dutra, J. McNorton, M. Choulga, A. Agusti-Panareda, A. Beljaars, N. Wedi, J. Munoz-Sabater, P. de Rosnay, I. Sandu, I. Hadade, G. Carver, C. Mazzetti, C. Prudhomme, D. Yamazaki, and E. Zsoter, ECLand: The ECMWF Land Surface Modelling System. Atmosphere 12 (2021), 723.

2. J. G. Charney, W. J. Quirk, S. H. Chow, and J. Kornfield, A comparative study of the effects of albedo change on drought in semiarid regions. J. Atmos. Sci. 34 (1977), 1366–1385.

3. Y. Cheng, V. M. Canuto, and A. M. Howard, An improved model for the turbulent PBL. J. Atmos. Sci. 59 (2002), 1550–1565.

4. M.-D. Chou and M. J. Suarez, A solar radiation parameterization (CLIRAD-SW) for atmospheric studies. NASA Tech. Memo. 10460 (1999), No. 15. https://ntrs.nasa.gov/api/citations/19990060930/downloads/19990060930.pdf

5. A. Davison and D. Hinkley, Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics). Cambridge, Cambridge University Press, 1997.