A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three-dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.
Bibliographical noteFunding Information:
The authors are thankful to the Editor-in-Chief (Robert Pincus), Associate Editor (Dick Dee), and two anonymous reviewers for their valuable comments and suggestions. This work has been supported by Korea Institute of Science and Technology Information, with the project of ?Construction of HPC-based Service Infrastructure Responding to National Scale Disaster (K-17-L03-C03)?. This work was also supported by the National Institute of Supercomputing and Network/Korea Institute of Science and Technology Information with supercomputing resources including technical support (KSC-2015-C2-005). The authors are grateful to Chris Snyder for fruitful discussions. The NCEP GFS analysis and forecast data are available from the National Oceanic and Atmospheric Administration (NOAA) National Operational Model Archive and Distribution System (NOMADS) web site (http://nomads.ncdc.noaa.gov/cgi-bin/ncdc-ui/define-collection.pl?model_sys=gfs4&model_name=gfs&grid_name=4). All observational data including conventional, satellite-derived wind, GPS refractivity, and satellite radiance observations can be freely obtained from the NOAA NOMADS web site (http://nomads.ncdc.noaa.gov/cgi-bin/ncdc-ui/define-collection.pl?model_sys=gdas&model_name=gdas&grid_name=999). The RSMC best track data and the ECMWF ERA Interim reanalysis data are available from the RSMC Tokyo typhoon center (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html) and the ECMWF (http://apps.ecmwf.int/datasets) web sites, respectively.
© 2017. The Authors.
All Science Journal Classification (ASJC) codes
- Global and Planetary Change
- Environmental Chemistry
- Earth and Planetary Sciences(all)