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- Author or Editor: Seung-Hee Ham x
- Journal of Applied Meteorology and Climatology x
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Abstract
The authors examined the possible use of deep convective clouds (DCCs), defined as clouds that overshoot the tropical tropopause layer (TTL), for the calibration of satellite measurements at solar channels. DCCs are identified in terms of the Moderate Resolution Imaging Spectroradiometer (MODIS) 10.8-μm brightness temperature (TB11) on the basis of a criterion specified by TB11 ≤ 190 K. To determine the characteristics of these clouds, the MODIS-based cloud optical thickness (COT) and effective radius (re ) for a number of identified DCCs are analyzed. It is found that COT values for most of the 4249 DCC pixels observed in January 2006 are close to 100. Based on the MODIS quality-assurance information, 90% and 70.2% of the 4249 pixels have COT larger than 100 and 150, respectively. On the other hand, the re values distributed between 15 and 25 μm show a sharp peak centered approximately at 20 μm. Radiances are simulated at the MODIS 0.646-μm channel by using a radiative transfer model under homogeneous overcast ice cloudy conditions for COT = 200 and re = 20 μm. These COT and re values are assumed to be typical for DCCs. A comparison between the simulated radiances and the corresponding Terra/Aqua MODIS measurements for 6 months in 2006 demonstrates that, on a daily basis, visible-channel measurements can be calibrated within an uncertainty range of ±5%. Because DCCs are abundant over the tropics and can be identified from infrared measurements, the present method can be applied to the calibration of a visible-channel sensor aboard a geostationary or low-orbiting satellite platform.
Abstract
The authors examined the possible use of deep convective clouds (DCCs), defined as clouds that overshoot the tropical tropopause layer (TTL), for the calibration of satellite measurements at solar channels. DCCs are identified in terms of the Moderate Resolution Imaging Spectroradiometer (MODIS) 10.8-μm brightness temperature (TB11) on the basis of a criterion specified by TB11 ≤ 190 K. To determine the characteristics of these clouds, the MODIS-based cloud optical thickness (COT) and effective radius (re ) for a number of identified DCCs are analyzed. It is found that COT values for most of the 4249 DCC pixels observed in January 2006 are close to 100. Based on the MODIS quality-assurance information, 90% and 70.2% of the 4249 pixels have COT larger than 100 and 150, respectively. On the other hand, the re values distributed between 15 and 25 μm show a sharp peak centered approximately at 20 μm. Radiances are simulated at the MODIS 0.646-μm channel by using a radiative transfer model under homogeneous overcast ice cloudy conditions for COT = 200 and re = 20 μm. These COT and re values are assumed to be typical for DCCs. A comparison between the simulated radiances and the corresponding Terra/Aqua MODIS measurements for 6 months in 2006 demonstrates that, on a daily basis, visible-channel measurements can be calibrated within an uncertainty range of ±5%. Because DCCs are abundant over the tropics and can be identified from infrared measurements, the present method can be applied to the calibration of a visible-channel sensor aboard a geostationary or low-orbiting satellite platform.
Abstract
Observations made by the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS), the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and CloudSat are synergistically used to evaluate the accuracy of theoretical simulations of the radiances at the top of the atmosphere (TOA). Specifically, TOA radiances of 15 MODIS bands are simulated for overcast, optically thick, and single-phase clouds only over the ocean from 60°N to 60°S, corresponding to about 12% of all the MODIS cloud observations. Plane parallel atmosphere is assumed in the simulation by restricting viewing/solar zenith angle to be less than 40°. Input data for the radiative transfer model (RTM) are obtained from the operational MODIS-retrieved cloud optical thickness, effective radius, and cloud-top pressure (converted to height) collocated with the AIRS-retrieved temperature and humidity profiles. In the RTM, ice cloud bulk scattering properties, based on theoretical scattering computations and in situ microphysical data, are used for the radiative transfer simulations. The results show that radiances for shortwave bands between 0.466 and 0.857 μm appear to be very accurate with errors on the order of 5%, implying that MODIS cloud parameters provide sufficient information for the radiance simulations. However, simulated radiances for the 1.24-, 1.63-, and 3.78-μm bands do not agree as well with the observed radiances as a result of the use of a single effective radius for a cloud layer that may be vertically inhomogeneous in reality. Furthermore, simulated radiances for the water vapor absorption bands located near 0.93 and 1.38 μm show positive biases, whereas the window bands from 8.5 to 12 μm show negative biases compared to observations, likely due to the less accurate estimate of cloud-top and cloud-base heights. It is further shown that the accuracies of the simulations for water vapor and window bands can be substantially improved by accounting for the vertical cloud distribution provided by the CALIPSO and CloudSat measurements.
Abstract
Observations made by the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS), the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and CloudSat are synergistically used to evaluate the accuracy of theoretical simulations of the radiances at the top of the atmosphere (TOA). Specifically, TOA radiances of 15 MODIS bands are simulated for overcast, optically thick, and single-phase clouds only over the ocean from 60°N to 60°S, corresponding to about 12% of all the MODIS cloud observations. Plane parallel atmosphere is assumed in the simulation by restricting viewing/solar zenith angle to be less than 40°. Input data for the radiative transfer model (RTM) are obtained from the operational MODIS-retrieved cloud optical thickness, effective radius, and cloud-top pressure (converted to height) collocated with the AIRS-retrieved temperature and humidity profiles. In the RTM, ice cloud bulk scattering properties, based on theoretical scattering computations and in situ microphysical data, are used for the radiative transfer simulations. The results show that radiances for shortwave bands between 0.466 and 0.857 μm appear to be very accurate with errors on the order of 5%, implying that MODIS cloud parameters provide sufficient information for the radiance simulations. However, simulated radiances for the 1.24-, 1.63-, and 3.78-μm bands do not agree as well with the observed radiances as a result of the use of a single effective radius for a cloud layer that may be vertically inhomogeneous in reality. Furthermore, simulated radiances for the water vapor absorption bands located near 0.93 and 1.38 μm show positive biases, whereas the window bands from 8.5 to 12 μm show negative biases compared to observations, likely due to the less accurate estimate of cloud-top and cloud-base heights. It is further shown that the accuracies of the simulations for water vapor and window bands can be substantially improved by accounting for the vertical cloud distribution provided by the CALIPSO and CloudSat measurements.
Abstract
Cloud vertical profile measurements from the CALIPSO and CloudSat active sensors are used to improve top-of-atmosphere (TOA) shortwave (SW) broadband (BB) irradiance computations. The active sensor measurements, which occasionally miss parts of the cloud columns because of the full attenuation of sensor signals, surface clutter, or insensitivity to a certain range of cloud particle sizes, are adjusted using column-integrated cloud optical depth derived from the passive MODIS sensor. Specifically, we consider two steps in generating cloud profiles from multiple sensors for irradiance computations. First, cloud extinction coefficient and cloud effective radius (CER) profiles are merged using available active and passive measurements. Second, the merged cloud extinction profiles are constrained by the MODIS visible scaled cloud optical depth, defined as a visible cloud optical depth multiplied by (1 − asymmetry parameter), to compensate for missing cloud parts by active sensors. It is shown that the multisensor-combined cloud profiles significantly reduce positive TOA SW BB biases, relative to those with MODIS-derived cloud properties only. The improvement is more pronounced for optically thick clouds, where MODIS ice CER is largely underestimated. Within the SW BB (0.18–4 μm), the 1.04–1.90-μm spectral region is mainly affected by the CER, where both the cloud absorption and solar incoming irradiance are considerable.
Significance Statement
The purpose of this study is to improve shortwave irradiance computations at the top of the atmosphere by using combined cloud properties from active and passive sensor measurements. Relative to the simulation results with passive sensor cloud measurements only, the combined cloud profiles provide more accurate shortwave simulation results. This is achieved by more realistic profiles of cloud extinction coefficient and cloud particle effective radius. The benefit is pronounced for optically thick clouds composed of large ice particles.
Abstract
Cloud vertical profile measurements from the CALIPSO and CloudSat active sensors are used to improve top-of-atmosphere (TOA) shortwave (SW) broadband (BB) irradiance computations. The active sensor measurements, which occasionally miss parts of the cloud columns because of the full attenuation of sensor signals, surface clutter, or insensitivity to a certain range of cloud particle sizes, are adjusted using column-integrated cloud optical depth derived from the passive MODIS sensor. Specifically, we consider two steps in generating cloud profiles from multiple sensors for irradiance computations. First, cloud extinction coefficient and cloud effective radius (CER) profiles are merged using available active and passive measurements. Second, the merged cloud extinction profiles are constrained by the MODIS visible scaled cloud optical depth, defined as a visible cloud optical depth multiplied by (1 − asymmetry parameter), to compensate for missing cloud parts by active sensors. It is shown that the multisensor-combined cloud profiles significantly reduce positive TOA SW BB biases, relative to those with MODIS-derived cloud properties only. The improvement is more pronounced for optically thick clouds, where MODIS ice CER is largely underestimated. Within the SW BB (0.18–4 μm), the 1.04–1.90-μm spectral region is mainly affected by the CER, where both the cloud absorption and solar incoming irradiance are considerable.
Significance Statement
The purpose of this study is to improve shortwave irradiance computations at the top of the atmosphere by using combined cloud properties from active and passive sensor measurements. Relative to the simulation results with passive sensor cloud measurements only, the combined cloud profiles provide more accurate shortwave simulation results. This is achieved by more realistic profiles of cloud extinction coefficient and cloud particle effective radius. The benefit is pronounced for optically thick clouds composed of large ice particles.
Abstract
Cloud macrophysical changes over the Pacific Ocean from 2007 to 2017 are examined by combining CALIPSO and CloudSat (CALCS) active-sensor measurements, and these are compared with MODIS passive-sensor observations. Both CALCS and MODIS capture well-known features of cloud changes over the Pacific associated with meteorological conditions during El Niño–Southern Oscillation (ENSO) events. For example, midcloud (cloud tops at 3–10 km) and high cloud (cloud tops at 10–18 km) amounts increase with relative humidity (RH) anomalies. However, a better correlation is obtained between CALCS cloud volume and RH anomalies, confirming more accurate CALCS cloud boundaries than MODIS. Both CALCS and MODIS show that low cloud (cloud tops at 0–3 km) amounts increase with EIS and decrease with SST over the eastern Pacific, consistent with earlier studies. It is also further shown that the low cloud amounts do not increase with positive EIS anomalies if SST anomalies are positive. While similar features are found between CALCS and MODIS low cloud anomalies, differences also exist. First, relative to CALCS, MODIS shows stronger anticorrelation between low and mid/high cloud anomalies over the central and western Pacific, which is largely due to the limitation in detecting overlapping clouds from passive MODIS measurements. Second, relative to CALCS, MODIS shows smaller impacts of mid- and high clouds on the low troposphere (<3 km). The differences are due to the underestimation of MODIS cloud layer thicknesses of mid- and high clouds.
Abstract
Cloud macrophysical changes over the Pacific Ocean from 2007 to 2017 are examined by combining CALIPSO and CloudSat (CALCS) active-sensor measurements, and these are compared with MODIS passive-sensor observations. Both CALCS and MODIS capture well-known features of cloud changes over the Pacific associated with meteorological conditions during El Niño–Southern Oscillation (ENSO) events. For example, midcloud (cloud tops at 3–10 km) and high cloud (cloud tops at 10–18 km) amounts increase with relative humidity (RH) anomalies. However, a better correlation is obtained between CALCS cloud volume and RH anomalies, confirming more accurate CALCS cloud boundaries than MODIS. Both CALCS and MODIS show that low cloud (cloud tops at 0–3 km) amounts increase with EIS and decrease with SST over the eastern Pacific, consistent with earlier studies. It is also further shown that the low cloud amounts do not increase with positive EIS anomalies if SST anomalies are positive. While similar features are found between CALCS and MODIS low cloud anomalies, differences also exist. First, relative to CALCS, MODIS shows stronger anticorrelation between low and mid/high cloud anomalies over the central and western Pacific, which is largely due to the limitation in detecting overlapping clouds from passive MODIS measurements. Second, relative to CALCS, MODIS shows smaller impacts of mid- and high clouds on the low troposphere (<3 km). The differences are due to the underestimation of MODIS cloud layer thicknesses of mid- and high clouds.
