scholarly journals Reanalysis and Reforecast of Typhoon Vera (1959) Using a Mesoscale Four-Dimensional Variational Assimilation System

2012 ◽  
Vol 90 (4) ◽  
pp. 467-491 ◽  
Author(s):  
Takuya KAWABATA ◽  
Masaru KUNII ◽  
Kotaro BESSHO ◽  
Tetsuo NAKAZAWA ◽  
Nadao KOHNO ◽  
...  
Keyword(s):  
Variational Assimilation ◽  
Typhoon Vera ◽  
Assimilation System

Direct assimilation of satellite radiance data in GRAPES variational assimilation system

2008 ◽  
Vol 53 (22) ◽  
pp. 3465-3469 ◽  
Author(s):  
GuoFu Zhu ◽  
JiShan Xue ◽  
Hua Zhang ◽  
ZhiQuan Liu ◽  
ShiYu Zhuang ◽  
...  
Keyword(s):  
Variational Assimilation ◽  
Satellite Radiance Data ◽  
Radiance Data ◽  
Assimilation System

Impact of Altika Sea Level Anomaly Data on a Variational Assimilation System

2020 ◽  
Vol 89 (sp1) ◽  
pp. 46
Author(s):  
Mohsinali Momin Imranali ◽  
Ashis Kumar Mitra ◽  
Jennifer Waters ◽  
Mathew James Martin ◽  
Ekkattil Rajagopal
Keyword(s):  
Sea Level ◽  
Sea Level Anomaly ◽  
Variational Assimilation ◽  
Assimilation System

Assimilation of MODIS Cloud Optical Depths in the ECMWF Model

2008 ◽  
Vol 136 (5) ◽  
pp. 1727-1746 ◽  
Author(s):  
Angela Benedetti ◽  
Marta Janisková
Keyword(s):  
Research Effort ◽  
Current Application ◽  
Variational Assimilation ◽  
Medium Range Forecast ◽  
Medium Range ◽  
Temperature And Humidity ◽  
Independent Observations ◽  
Ice Water ◽  
The Impact ◽  
Assimilation System

Abstract At the European Centre for Medium-Range Weather Forecasts (ECMWF), a large effort has recently been devoted to define and implement moist physics schemes for variational assimilation of rain- and cloud-affected brightness temperatures. This study expands on the current application of the new linearized moist physics schemes to assimilate cloud optical depths retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua platform for the first time in the ECMWF operational four-dimensional assimilation system. Model optical depths are functions of ice water and liquid water contents through established parameterizations. Linearized cloud schemes in turn link these cloud variables with temperature and humidity. A bias correction is applied to the optical depths to minimize the differences between model and observations. The control variables in the assimilation are temperature, humidity, winds, and surface pressure. One-month assimilation experiments for April 2006 demonstrated an impact of the assimilated MODIS cloud optical depths on the model fields, particularly temperature and humidity. Comparison with independent observations indicates a positive effect of the cloud information assimilated into the model, especially on the amount and distribution of the ice water content. The impact of the cloud assimilation on the medium-range forecast is neutral to slightly positive. Most importantly, this study demonstrates that global assimilation of cloud observations in ECMWF four-dimensional variational assimilation system (4DVAR) is technically doable but a continued research effort is necessary to achieve clear positive impacts with such data.

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