A Cloud Top-Height Retrieval Algorithm Using Simultaneous Observations from the Himawari-8 and FY-2E Satellites

Lee, Jonghyuk; Shin, Dong Bin; Chung, Chu-Yong; Kim, Jae Gwan

doi:10.3390/rs12121953

Cited by 12 publications

(10 citation statements)

References 33 publications

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“…This effect (the parallax effect) becomes more notable when comparing two simultaneous satellite images. The prototype dual-GEO CTH algorithm [16] retrieves CTHs from the parallax of the cloud fields in VIS images. Because the improved dual-GEO CTH algorithm is based on the prototype dual-GEO CTH algorithm, we briefly review the prototype dual-GEO CTH algorithm.…”

Section: Prototype Dual-geo Cth Algorithmmentioning

confidence: 99%

“…Moreover, stereoscopic methods can be easily applied to any combination of satellites. For example, stereoscopic methods have been applied to combinations of two geostationary orbit (GEO) satellites, which are located at two different locations [11][12][13][14][15][16][17], and combinations of GEO and low Earth orbit (LEO) satellites [10,18,19]. Stereoscopic methods have also been used by multi-view instruments onboard a single LEO satellite [9,[20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…Lee et al [16] proposed a stereoscopic-based CTH retrieval algorithm (hereafter, the prototype dual-GEO CTH algorithm) based on simultaneous measurements of Himawari-8 and FengYun (FY)-2E GEO satellites. This algorithm uses a visible (VIS) band to retrieve stereoscopic CTHs (VIS-band-based approach), and the retrieval accuracy generally tends to lie within the theoretical accuracy range.…”

Section: Introductionmentioning

confidence: 99%

“…Section 2 provides a brief description of the input and inter-comparison datasets used in this study. Section 3 presents an overview of the prototype dual-GEO CTH algorithm reported in [16]. Section 4 describes the improved dual-GEO CTH algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Algorithm for Improved Stereoscopic Cloud-Top Height Retrieval Based on Visible and Infrared Bands for Himawari-8 and FY-4A

Lee

Shin

2021

Remote Sensing

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Stereoscopic cloud-top height (CTH) retrieval from two geostationary (GEO) satellites is usually realized through a visible (VIS) band with a high horizontal resolution. A stereoscopic-based CTH retrieval algorithm (prototype dual-GEO CTH algorithm) proposed in our previous study also adopts this approach. Although this approach can retrieve accurate stereoscopic CTHs, the heights of optically thin upper clouds overlying the lower clouds are challenging to retrieve because the parallax difference between two GEOs is determined by the lower clouds owing to the low reflectance from the upper clouds. To address this problem, this paper proposes an improved stereoscopic CTH retrieval algorithm, named the improved dual-GEO CTH algorithm, for Himawari-8 and FengYun (FY)-4A GEOs. The proposed algorithm employs an infrared (IR) band in addition to a VIS band. A seamless image cloning technique is adopted to blend the VIS and IR images, which are then used to retrieve the stereoscopic CTHs. The retrieved CTHs are compared with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) CTHs for three occasions involving upper clouds overlying lower clouds. Results show that the proposed algorithm outperforms the prototype dual-GEO CTH algorithm in the case of upper clouds overlying lower clouds. Notably, although the proposed algorithm is intended for Himawari-8 and FY-4A GEOs, it can be easily extended to any combination of two GEOs.

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Section: Prototype Dual-geo Cth Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Algorithm for Improved Stereoscopic Cloud-Top Height Retrieval Based on Visible and Infrared Bands for Himawari-8 and FY-4A

Lee

Shin

2021

Remote Sensing

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“…However, most of these methods need the auxiliary of numerical weather prediction (NWP) model data. The stereoscopic method is also an accurate method for cloud-top height derivation, which uses the slanted views of joint satellites but can only be used for limited regions [21,22]. Besides, the length of shadow above the anvil using visible-channel imagery [23] could also be used to determine the magnitude of penetration, which can be transformed to the relative height between penetration and anvil cloud height.…”

Section: Introductionmentioning

confidence: 99%

Tropical Overshooting Cloud-Top Height Retrieval from Himawari-8 Imagery Based on Random Forest Model

Wang

Zhuang

et al. 2021

Atmosphere

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Tropical overshooting convection has a strong impact on both heat budget and moisture distribution in the upper troposphere and lower stratosphere, and it can pose a great risk to aviation safety. Cloud-top height is one of the essential concerns of overshooting convection for both the climate system and the aviation weather forecast. The main purpose of our work is to verify the application of the machine learning method, taking the random forest (RF) model as an instance, in overshooting cloud-top height retrieval from Himawari-8 data. By using collocated CloudSat observations as a reference, we utilize several infrared indicators of Himawari-8 that are commonly recognized to relate to cloud-top height, along with some temporal and geographical parameters (latitude, month, satellite zenith angle, etc.), as predictors to construct and validate the model. Analysis of variable importance shows that the brightness temperature of 6.2 um acts as the dominant predictor, followed by satellite zenith angle, brightness temperature of 13.3 um, latitude, and month. In the comparison between the RF model and the traditional single-channel interpolation method, retrievals from the RF model agree well with observation with a high correlation coefficient (0.92), small RMSE (222 m), and small MAE (164 m), while these metrics from traditional single-channel interpolation method shows lower skills (0.70, 1305 m, and 1179 m). This work presents a new sight of overshooting cloud-top height retrieval based on the machine learning method.

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Severe convective outbreak in Siberia in May 2020: Event analysis and high-resolution simulation

Shikhov,

Antokhina,

Gochakov

et al. 2024

Atmospheric Research

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A Cloud Top-Height Retrieval Algorithm Using Simultaneous Observations from the Himawari-8 and FY-2E Satellites

Cited by 12 publications

References 33 publications

Algorithm for Improved Stereoscopic Cloud-Top Height Retrieval Based on Visible and Infrared Bands for Himawari-8 and FY-4A

Algorithm for Improved Stereoscopic Cloud-Top Height Retrieval Based on Visible and Infrared Bands for Himawari-8 and FY-4A

Tropical Overshooting Cloud-Top Height Retrieval from Himawari-8 Imagery Based on Random Forest Model

Severe convective outbreak in Siberia in May 2020: Event analysis and high-resolution simulation

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