An example of data assimilation from several lightning detection networks in numerical weather forecast

2021 ◽  
Vol 34 (10) ◽  
pp. 803-807
Author(s):  
I.M. Gubenko ◽  
K.G. Rubinstein
Keyword(s):  
Data Assimilation ◽  
Weather Forecast ◽  
Numerical Weather ◽  
Lightning Detection ◽  
Numerical Weather Forecast

Numerical weather forecast at Mauna Kea Astronomical Observatory by Subaru telescope supercomputer

2002 ◽  
Author(s):  
Ryusuke Ogasawara ◽  
Akihiko Miyashita ◽  
George Kosugi ◽  
Tadafumi Takata ◽  
Kazuhiro Sekiguchi ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Astronomical Observatory ◽  
Numerical Weather ◽  
Numerical Weather Forecast

scholarly journals Thermographic measurement and numerical weather forecast along a highway road surface

2010 ◽  
Vol 17 (4) ◽  
pp. 474-484 ◽  
Author(s):  
D. Bouris ◽  
T. Theodosiou ◽  
K. Rados ◽  
M. Makrogianni ◽  
K. Koutsoukos ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Road Surface ◽  
Numerical Weather ◽  
Numerical Weather Forecast ◽  
Thermographic Measurement

scholarly journals Studies of FY-3 Observations over the Past 10 Years: A Review

2021 ◽  
Vol 13 (4) ◽  
pp. 673
Author(s):  
Xiaolei Zou
Keyword(s):  
Data Assimilation ◽  
Weather Forecast ◽  
Cloud Detection ◽  
Bias Estimation ◽  
Weather And Climate ◽  
Numerical Weather Forecast ◽  
Noise Characterization ◽  
Quality Assessments ◽  
Climate Studies ◽  
Geolocation Accuracy

With the rapid advances and abundant observations from Chinese Fengyun-3 (FY-3) meteorological satellites, it is of great interest to summarize a decade of quality assessments of FY-3 observations. The topics covered are noise characterization, bias estimation, striping noise detection and mitigation of striping noise, radio frequency interference detection, geolocation accuracy estimation and improvement, data assimilation cloud detection and quality control for observations from the MicroWave Temperature Sounder (MWTS), the MicroWave Humidity Sounder (MWHS), the MicroWave Radiation Imager (MWRI) and the Hyperspectral Infrared Atmospheric Sounder (HIRAS) instruments on board FY-3A/B/C/D. Whether and how much FY-3 data assimilation could improve the numerical weather forecast skill strongly depends on how well the FY-3 data characteristics and errors listed above are known. This review article shall contribute to promoting internal and national usages of FY-3 observations for weather and climate studies.

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