Rainfall Retrieval and Nowcasting Based on Multispectral Satellite Images. Part I: Retrieval Study on Daytime 10-Minute Rain Rate

Zhuge, Xiaoyong; Yu, Fan; Zhang, Chengwei

doi:10.1175/2011jhm1373.1

Cited by 11 publications

(4 citation statements)

References 44 publications

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“…These radars are similar to WSR‐88Ds in terms of both their hardware and software (Zhu & Zhu, ). Visible images from Fengyun‐2C ( FY‐2C ), a geosynchronous meteorological satellite operated by the National Satellite Meteorological Center of the China Meteorological Administration, were available every 30‐min with a resolution of 1.25 km at nadir (Zhuge et al, ). Given the generally good representation of the synoptic atmospheric features and the 3‐hr availability for the Global Forecast System (GFS) analysis (gridded on 0.5° × 0.5°) in this case, we used the GFS analysis data mainly for synoptic‐scale analysis.…”

Section: Methodsmentioning

confidence: 99%

Convection Initiation Resulting From the Interaction Between a Quasi‐Stationary Dryline and Intersecting Gust Fronts: A Case Study

et al. 2019

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This study explores the convection initiation (CI) of a high‐impact squall line that occurred in central eastern China on 3 June 2009 based on observations and numerical modeling. The CI occurred in a scenario in which a set of intersecting gust fronts, organized in a distinct scalloped pattern, propagated toward an area of enhanced moisture produced by a near‐surface convergence line. This convergence line developed in a quasi‐stationary dryline zone. The dryline primed the preconvective environment by deepening the moist layer prior to the arrival of the intersecting gust fronts. The onset of CI occurred approximately 30 min after these intersecting gust fronts passed through the CI location, which was on the dry side of the dryline. Although these gust fronts acted as a strong signal for CI potential, CI did not occur along the entire length of the scalloped pattern of the intersecting gust fronts. The exact locations of the initiated convective cells were at the vertices of the scalloped pattern. An idealized simulation using a cloud model was conducted, demonstrating that the vertex regions were characterized by more favorable dynamical conditions for CI compared to the nonvertex regions along the scalloped outflow boundary. The greater CI probability over the vertex region was attributed to the greater magnitudes and larger vertical and horizontal extents of updrafts.

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Section: Methodsmentioning

confidence: 99%

Convection Initiation Resulting From the Interaction Between a Quasi‐Stationary Dryline and Intersecting Gust Fronts: A Case Study

et al. 2019

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“…To quantitatively evaluate the cloud mask retrievals, the following four indices are introduced: probability of detection (POD), false-alarm rate (FAR), Heidke skill score (HSS), and equitable threat score (ETS). The definitions of the POD, FAR, HSS, and ETS are described in Zhuge et al (2011). Table 5 lists the scores of POD, FAR, HSS, and ETS for cloud mask retrievals of three datasets.…”

Section: Cloud Mask Resultsmentioning

confidence: 99%

Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research

Zhuge,

Zou,

et al. 2024

Earth Syst. Sci. Data

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Abstract. The use of remote sensing methods to accurately measure cloud properties and their spatiotemporal changes has been widely welcomed in many fields of atmospheric research. The Nanjing Joint Institute for Atmospheric Sciences (NJIAS) Himawari-8/9 Cloud Feature Dataset (HCFD) provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the 7-year period from April 2016 to December 2022. Multiple cloud variables, such as cloud mask, phase/type, top height, optical thickness, and particle effective radius, as well as snow, dust, and haze masks, were generated from the visible and infrared measurements of the Advanced Himawari Imager (AHI) on board the Japanese geostationary satellites Himawari-8 and Himawari-9 using a series of recently developed cloud retrieval algorithms. Verifications with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) 1 km cloud layer product and the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 cloud product (MYD06) demonstrate that the NJIAS HCFD gives higher skill scores than the Japanese Himawari-8/9 operational cloud product for all cloud variables except for cloud particle effective radius. The NJIAS HCFD even outperforms the MYD06 in nighttime cloud detection; cloud-top height, pressure, and temperature estimation; and infrared-only cloud-top phase determination. All evaluations are performed at the nominal 2 km scale, not including the effects of sub-pixel cloudiness or very thin cirrus. Two examples are presented to demonstrate applications of the NJIAS HCFD for climate and typhoon research. The NJIAS HCFD has been published in the Science Data Bank (https://doi.org/10.57760/sciencedb.09950, Zhuge 2023a; https://doi.org/10.57760/sciencedb.09953, Zhuge 2023b; https://doi.org/10.57760/sciencedb.09954, Zhuge 2023c; https://doi.org/10.57760/sciencedb.10158, Zhuge 2023d; https://doi.org/10.57760/sciencedb.09945, Zhuge 2023e).

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“…probability of detection (POD), false-alarm rate (FAR), Heike skill score (HSS), and the equitable threat score (ETS). The definitions of the POD, FAR, HSS and ETS were described in Zhuge et al (2011).…”

Section: Cloud Mask Resultsmentioning

confidence: 99%

Introduction to the NJIAS Himawari-8/9 cloud feature dataset for climate and typhoon research

Zhuge,

Zou,

et al. 2023

Preprint

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Abstract. The use of remote sensing method to accurately measure cloud properties and their spatiotemporal changes has been widely welcomed in many fields of atmospheric research. The Nanjing Joint Institute for Atmospheric Sciences (NJIAS) Himawari-8/9 Cloud Feature Dataset (HCFD) provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the 7 yr period from April 2016 to December 2022. Multiple cloud variables, such as cloud mask, phase/type, top height, optical thickness, and particle effective radius, as well as snow, dust and haze masks, were generated from the visible and infrared measurements of the Advanced Himawari Imager (AHI) onboard the Japanese geostationary satellites Himawari-8/9 using a series of cloud retrieval algorithms developed by Dr. Zhuge and his colleagues. Verifications with the Cloud–Aerosol Lidar with Orthogonal Polarization 1-km cloud layer product and the Moderate Resolution Imaging Spectroradiometer Level-2 cloud product (MYD06) demonstrates that the NJIAS HCFD gives higher skill scores than the Japanese Himawari-8/9 operational cloud product for all cloud variables except for the particle effective radius. The NJIAS HCFD even outperforms the MYD06 in the nighttime continental cloud detection and the infrared-only cloud-top phase determination. Then, two application examples are presented, to demonstrate the use of the NJIAS HCFD for climate and typhoon research. The NJIAS HCFD has been published at the Science Data Bank (https://doi.org/10.57760/sciencedb.09950, Zhuge 2023a; https://doi.org/10.57760/sciencedb.09953, Zhuge 2023b; https://doi.org/10.57760/sciencedb.09954, Zhuge 2023c; https://doi.org/10.57760/sciencedb.10158, Zhuge 2023d; https://doi.org/10.57760/sciencedb.09945, Zhuge 2023e).

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Rainfall Retrieval and Nowcasting Based on Multispectral Satellite Images. Part I: Retrieval Study on Daytime 10-Minute Rain Rate

Cited by 11 publications

References 44 publications

Convection Initiation Resulting From the Interaction Between a Quasi‐Stationary Dryline and Intersecting Gust Fronts: A Case Study

Convection Initiation Resulting From the Interaction Between a Quasi‐Stationary Dryline and Intersecting Gust Fronts: A Case Study

Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research

Introduction to the NJIAS Himawari-8/9 cloud feature dataset for climate and typhoon research

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