Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite

Abstract A satellite product that displays regions of aircraft icing potential, along with corresponding cloud-top heights, has been developed using data from the Geostationary Operational Environmental Satellite (GOES) imager and sounder. The icing product, referred to as the Icing Enhanced Cloud-top Altitude Product (ICECAP), is created hourly for the continental United States and southern Canada, and is color coded to show cloud-top altitudes in 1.9-km (6000 ft) intervals. Experimental ICECAP images became routinely available on the Internet during the spring of 2004. Verification of separate ICECAP components (imager icing potential and sounder cloud-top heights) using aircraft pilot reports (PIREPs) indicates that the product provides useful guidance on the spatial coverage and maximum altitude of current icing conditions, but not icing intensity, stratification, or minimum altitude. The imager icing potential component of ICECAP was compared with the operational 40-km resolution National Weather Service (NWS) current icing potential and NWS Airman’s Meteorological Advisories via the NOAA Real-Time Verification System, while GOES cloud-top heights were compared with altitudes of moderate or greater icing from PIREPs. Benefits and deficiencies of the GOES icing product are discussed.

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A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation

International Journal for Numerical Methods in Engineering ◽

10.1002/nme.6713 ◽

2021 ◽

Author(s):

Umberto Emil Morelli ◽

Patricia Barral ◽

Peregrina Quintela ◽

Gianluigi Rozza ◽

Giovanni Stabile

Keyword(s):

Heat Flux ◽

Data Assimilation ◽

Continuous Casting ◽

Numerical Approach ◽

Heat Flux Estimation ◽

Flux Estimation ◽

Using Data

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Enhancing CFD-LES air pollution prediction accuracy using data assimilation

Building and Environment ◽

10.1016/j.buildenv.2019.106383 ◽

2019 ◽

Vol 165 ◽

pp. 106383 ◽

Cited By ~ 4

Author(s):

Elsa Aristodemou ◽

Rossella Arcucci ◽

Laetitia Mottet ◽

Alan Robins ◽

Christopher Pain ◽

...

Keyword(s):

Air Pollution ◽

Data Assimilation ◽

Prediction Accuracy ◽

Using Data ◽

Air Pollution Prediction ◽

Pollution Prediction

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Study on the transport of COD in the sea area around Maidao off Qingdao coast using data assimilation

Journal of Ocean University of China ◽

10.1007/s11802-007-0339-4 ◽

2007 ◽

Vol 6 (4) ◽

pp. 339-344 ◽

Cited By ~ 3

Author(s):

Qiang Zhao ◽

Xiaomin Hu ◽

Xianqing Lü ◽

Xuejun Xiong ◽

Bo Yang

Keyword(s):

Data Assimilation ◽

Qingdao Coast ◽

Using Data ◽

Sea Area

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Aerosol Data Assimilation Using Data from Fengyun-3A and MODIS: Application to a Dust Storm over East Asia in 2011

Advances in Atmospheric Sciences ◽

10.1007/s00376-018-8075-9 ◽

2018 ◽

Vol 36 (1) ◽

pp. 1-14 ◽

Cited By ~ 5

Author(s):

Xiaoli Xia ◽

Jinzhong Min ◽

Feifei Shen ◽

Yuanbing Wang ◽

Chun Yang

Keyword(s):

Data Assimilation ◽

East Asia ◽

Dust Storm ◽

Using Data

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Data assimilation for volcanic ash plumes using a satellite observational operator: a case study on the 2010 Eyjafjallajökull volcanic eruption

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-1187-2017 ◽

2017 ◽

Vol 17 (2) ◽

pp. 1187-1205 ◽

Cited By ~ 11

Author(s):

Guangliang Fu ◽

Fred Prata ◽

Hai Xiang Lin ◽

Arnold Heemink ◽

Arjo Segers ◽

...

Keyword(s):

Data Assimilation ◽

Volcanic Ash ◽

Three Dimensional ◽

Forecast Accuracy ◽

Improve Model ◽

Powerful Approach ◽

Using Data ◽

D Model

Abstract. Using data assimilation (DA) to improve model forecast accuracy is a powerful approach that requires available observations. Infrared satellite measurements of volcanic ash mass loadings are often used as input observations for the assimilation scheme. However, because these primary satellite-retrieved data are often two-dimensional (2-D) and the ash plume is usually vertically located in a narrow band, directly assimilating the 2-D ash mass loadings in a three-dimensional (3-D) volcanic ash model (with an integral observational operator) can usually introduce large artificial/spurious vertical correlations.In this study, we look at an approach to avoid the artificial vertical correlations by not involving the integral operator. By integrating available data of ash mass loadings and cloud top heights, as well as data-based assumptions on thickness, we propose a satellite observational operator (SOO) that translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The 3-D SOO makes the analysis step of assimilation comparable in the 3-D model space.Ensemble-based DA is used to assimilate the extracted measurements of ash concentrations. The results show that satellite DA with SOO can improve the estimate of volcanic ash state and the forecast. Comparison with both satellite-retrieved data and aircraft in situ measurements shows that the effective duration of the improved volcanic ash forecasts for the distal part of the Eyjafjallajökull volcano is about 6 h.

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