Abstract
Investigation of cloud top temperature (CTT) and its diurnal variation is highly reliant on high spatial and temporal resolution satellite data, which is lacking over the Indian region. An algorithm has been developed for detection of clouds and retrieval of CTT from the geostationary satellite INSAT-3D. These retrievals are validated (inter-compared) with collocated in-situ (satellite) measurements with specific intent to generate climate-quality data. The cloud detection algorithm employs nine different tests, in accordance with solar illumination, satellite angle and surface type conditions to generate pixel-resolution cloud mask. Validation of cloud mask with cloud-aerosol lidar with orthogonal polarization (CALIOP) shows that probability of detection (POD) of cloudy (clear) sky is 81% (85%), with 83% hit rate. The algorithm is also implemented on similar channels of moderate resolution imaging spectroradiometer (MODIS), which provides 88% (83%) POD of cloudy (clear) sky, with 86% hit rate. CTT retrieval is done at the pixel level, for all cloud pixels, by employing appropriate methods for various types of clouds. Comparison of CTT with radiosonde and cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO) shows mean absolute error less than 3%. The study also examines sensitivity of retrieved CTT to the cloud classification scheme and retrieval criteria. Validation results and their close agreements with those of similar satellites demonstrate the reliability of the retrieved product for climate studies.
Highlights
Clouds play a vital role in determining and governing weather and climate as they influence solar and terrestrial radiative transfer in the earth-atmosphere system, which makes cloud properties an essential climate variable [1,2]
For semi-transparent cirrus (STC) and partial clouds, a method based on two dimensional scatter plot between BT at TIR1 and brightness temperature difference (BTD) of TIR1 and TIR2 is used for cloud top temperature (CTT) retrieval
The cloud detection algorithm is implemented on INSAT-3D observations and the retrieved cloud mask is shown in Figure 3, for representative days in each season
Summary
Clouds play a vital role in determining and governing weather and climate as they influence solar and terrestrial radiative transfer in the earth-atmosphere system, which makes cloud properties an essential climate variable [1,2]. Spatial coverage and optical thickness of clouds influence the radiative transfer and together with cloud top temperature (CTT) determine the thermal effect [3]. CTT is a crucial parameter in estimating short-wave and long-wave radiative effects of clouds, by confidently classifying clouds into different categories. Radiative impacts of different types of clouds vary, depending on their properties and accurate representation of clouds in climate models is essential for realistic simulations of Earth’s current and future climate [15,16]. Continuous and detailed monitoring of cloud properties is necessary to realistically represent them in models to understand the role of clouds in the weather and climate system, apart from their inevitability in other applications such as nowcasting
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