Cloud Property Retrieval from Multiband Infrared Measurements by Himawari-8

Iwabuchi, Hironobu; Putri, Nurfiena Sagita; Saito, Masanori; Tokoro, Yuka; Sekiguchi, M; Yang, Ping; Baum, Bryan A.

doi:10.2151/jmsj.2018-001

Cited by 64 publications

(41 citation statements)

References 35 publications

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“…These results clearly demonstrate that the consideration of cloud vertical inhomogeneity can improve CTH retrieval in TIR‐based passive remote sensing. Our current finding partially addresses the issue identified in the past studies regarding the underestimation of CTH by TIR‐based passive remote sensing with the assumption of PPH cloud layers (e.g., Holz et al, ; Iwabuchi et al, , ). As discussed in section 4.3.3, the CTH is slightly higher in VIH than in PPH, indicating that cloud vertical inhomogeneity can be one reason for such underestimated CTH values in the past studies.…”

Section: Resultssupporting

confidence: 83%

Vertical Profiles of Ice Cloud Microphysical Properties and Their Impacts on Cloud Retrieval Using Thermal Infrared Measurements

2018

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Despite the vertically inhomogeneous (VIH) structure of ice clouds, current passive remote sensing methods assume plane‐parallel homogeneous (PPH) layers, which can lead to retrieval errors. An adequate VIH cloud model is required to improve retrieval performance. In this study, CloudSat and CALIPSO satellite measurements in a 1‐year period were analyzed to model cloud vertical inhomogeneity, and its impacts on cloud retrieval were assessed using thermal infrared (TIR) measurements. The satellite measurements revealed that the peak ice water content (IWC) located around the cloud vertical midpoint moved toward the cloud base as the ice water path (IWP) increased in clouds with small IWP values; thicker clouds exhibited a gradual shift in IWC peak location toward the cloud top as IWP increased. The vertical profiles of both the cloud‐particle effective radius (CER) and a proxy of cloud‐particle number concentration showed close associations with the vertical IWC profile. An empirical model linking cloud geometrical thickness to columnar optical properties (IWP and column‐mean CER) as a function of cloud‐top temperature was also proposed. Compared with a model assuming PPH clouds, the VIH cloud model improved retrieval performance by reducing the retrieval error of the TIR‐based passive remote sensing algorithm. Further, by increasing the retrieved values of cloud‐top height noticeably for high‐level clouds and column‐mean CER considerably, with minimal effects on cloud optical thickness retrieval, the VIH cloud model yielded results that were in better agreement with radar/lidar ice cloud products than those obtained under the assumption of PPH cloud layers.

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Section: Resultssupporting

confidence: 83%

Vertical Profiles of Ice Cloud Microphysical Properties and Their Impacts on Cloud Retrieval Using Thermal Infrared Measurements

2018

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“…The Advanced Himawari Imager has 16 observational bands, from the visible to thermal infrared spectral regions with a nadir spatial resolution of 0.5 km (1 band), 1 km (2 bands), and 2 km (13 bands). The Advanced Himawari Imager has been used for the retrieval of cloud properties, including the cloud optical depth (COD), r e , cloud top temperature, and cloud top height (Iwabuchi et al, 2018; Letu et al, 2018). The H‐8 beta data, which were announced to have serious retrieval issue by its official team, are the only available one from the official website during the period of SOCRATES.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Cloud Microphysical Properties Derived From MODIS and Himawari‐8 Using In Situ Aircraft Measurements Over the Southern Ocean

Zhao

Wang

et al. 2020

Earth and Space Science

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Cloud microphysical properties from aircraft measurements during the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study are used to evaluate the cloud products from the geostationary satellite Himawari-8 (H-8) and the polar-orbiting satellite the Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to the in situ aircraft observations when aircraft flew horizontally near cloud tops, the cloud droplet effective radius (r e ) and number concentration (N d ) from H-8 (MODIS) are 33% (26%-31%) and 2% (9-13%) larger. Both the H-8 and MODIS retrievals behave similarly for liquid-only and mixed-phase low-level clouds, indicating the weak sensitivity of the satellite cloud retrieval performance to cloud phase. The r e and N d of the cloud profiles from aircraft measurements were also used to compare with the satellite product. It shows that H-8 r e and N d agree better with aircraft measurements when considering only the in situ data acquired in the upper portions (highest 20%) of the clouds. Roughly, the r e overestimation by H-8 decreases from 18% to 3% when considering the upper portions of clouds compared to all cloud layer averages, except for one case with drizzles appeared. In addition, the performance of MODIS r e and N d is highly dependent on the wavelengths the retrieval method uses. The droplet r e retrievals using wavelength of 1.6 μm have much larger biases than that using the other two channels. The potential effects of the cloud vertical variation and the photon penetration depth, the cloud heterogeneity, the cloud droplet size spectra, and the drizzle on satellite retrievals have also been discussed. is a co-corresponding author with Chuanfeng Zhao Key Points:• Himawari-8 (MODIS) cloud product overestimates r e near cloud top by 33% (26-31%) over Southern Ocean • Himawari8 r e and N d agree better with aircraft measurements when considering only the in situ data acquired in the upper portions of clouds • The performance of MODIS retrievals depends on the wavelength, with larger biases at 1.6 μm than 2.1 and 3.7 μm

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“…4c and 4d. This could be ascribed that PCR tends to underestimate COT greater than 6 (Iwabuchi et al 2018). According to Figs.…”

Section: Comparison With Physics-based Cloud Retrievalmentioning

confidence: 99%

“…The main objective of this study is development of a rapid calculation method which well match with the PCR by using the same data (infrared measurement, MERRA-2 atmospheric and MODIS surface products). Iwabuchi et al (2018) showed comparisons between the PCR and radar and lidar cloud product.…”

Section: Comparison With Physics-based Cloud Retrievalmentioning

confidence: 99%

“…Modern methods for cloud remote sensing can retrieve more cloud properties (e.g., COT, effective particle radius, and cloud thermodynamic phase) based on a rigorous radiative-transfer model and the use of three or more spectral bands and instantaneous atmospheric and surface data. The Integrated Cloud Analysis System (ICAS) performs cloud analysis using eight AHI bands (Iwabuchi et al 2016(Iwabuchi et al , 2018. Cloud retrieval in the ICAS uses the optimal estimation method (Rodgers 2000), which fits the physics model to the measurements using optimization.…”

Section: Introductionmentioning

confidence: 99%

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Development of a Rapid Retrieval Method for Cloud Optical Thickness and Cloud-Top Height Using Himawari-8 Infrared Measurements

Sakai

Iwabuchi

Zhang

2019

SOLA

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We have developed a rapid simplified algorithm to retrieve cloud optical thickness and cloud-top height from measurements of the infrared split-window bands of Himawari-8. The method is based on a rapid calculation model for clear-sky brightness temperatures and empirical equations for cloud, for which the coefficients are determined by a fit to a more rigorous radiative-transfer model. This method can be applied regardless of regions excluding the polar regions and season by taking into account the temperature, humidity, sea surface temperature, and surface emissivity. In this study, we have demonstrated that this method captures well the diurnal cycle of cloud amounts of different cloud types in the warm-pool region around Indonesia. With an accelerated retrieval process by a factor of around 1,000 compared with the the physics-based retrieval, our rapid cloud retrieval algorithm yielded cloud amounts that agree quantitatively with those from a more rigorous, physics-based cloud retrieval method.(Citation: Sakai, S., H. Iwabuchi, and F. Zhang, 2019: Development of a rapid retrieval method for cloud optical thickness and cloud-top height using Himawari-8 infrared measurements. SOLA, 15, 57−61,

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Cloud Property Retrieval from Multiband Infrared Measurements by Himawari-8

Cited by 64 publications

References 35 publications

Vertical Profiles of Ice Cloud Microphysical Properties and Their Impacts on Cloud Retrieval Using Thermal Infrared Measurements

Vertical Profiles of Ice Cloud Microphysical Properties and Their Impacts on Cloud Retrieval Using Thermal Infrared Measurements

Evaluation of Cloud Microphysical Properties Derived From MODIS and Himawari‐8 Using In Situ Aircraft Measurements Over the Southern Ocean

Development of a Rapid Retrieval Method for Cloud Optical Thickness and Cloud-Top Height Using Himawari-8 Infrared Measurements

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