Initialisation of Land Surface Variables for Numerical Weather Prediction

被引：146

作者：

de Rosnay, Patricia ^{[1
]}

Balsamo, Gianpaolo ^{[1
]}

Albergel, Clement ^{[1
]}

Munoz-Sabater, Joaquin ^{[1
]}

Isaksen, Lars ^{[1
]}

机构：

[1] European Ctr Medium Range Weather Forecasts, Reading RG2 9AX, Berks, England

来源：

SURVEYS IN GEOPHYSICS | 2014年 / 35卷 / 03期

关键词：

Land surface; Data assimilation; Numerical weather prediction; Soil moisture; Snow; INTERACTIVE MULTISENSOR SNOW; SOIL-MOISTURE; MODEL DESCRIPTION; FORECAST SYSTEM; ASSIMILATION; CLIMATE; SCHEME; IMPACT; IMPLEMENTATION; TEMPERATURE;

D O I：

10.1007/s10712-012-9207-x

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Land surface processes and their initialisation are of crucial importance for Numerical Weather Prediction (NWP). Current land data assimilation systems used to initialise NWP models include snow depth analysis, soil moisture analysis, soil temperature and snow temperature analysis. This paper gives a review of different approaches used in NWP to initialise land surface variables. It discusses the observation availability and quality, and it addresses the combined use of conventional observations and satellite data. Based on results from the European Centre for Medium-Range Weather Forecasts (ECMWF), results from different soil moisture and snow depth data assimilation schemes are shown. Both surface fields and low-level atmospheric variables are highly sensitive to the soil moisture and snow initialisation methods. Recent developments of ECMWF in soil moisture and snow data assimilation improved surface and atmospheric forecast performance.

引用

页码：607 / 621

页数：15

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