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- Author or Editor: Daniel J. Cecil x
- Global Precipitation Measurement (GPM): Science and Applications x
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Abstract
Coefficients are derived for computing the polarization-corrected temperature (PCT) for 10-, 19-, 37- and 89-GHz (and similar) frequencies, with applicability to satellites in the Global Precipitation Measurement mission constellation and their predecessors. PCTs for 10- and 19-GHz frequencies have been nonexistent or seldom used in the past; developing those is the main goal of this study. For 37 and 89 GHz, other formulations of PCT have already become well established. We consider those frequencies here in order to test whether the large sample sizes that are readily available now would point to different formulations of PCT. The purpose of the PCT is to reduce the effects of surface emissivity differences in a scene and draw attention to ice scattering signals related to precipitation. In particular, our intention is to develop a PCT formula that minimizes the differences between land and water surfaces, so that signatures resulting from deep convection are not easily confused with water surfaces. The new formulations of PCT for 10- and 19-GHz measurements hold promise for identifying and investigating intense convection. Four examples are shown from relevant cases. The PCT for each frequency is effective at drawing attention to the most intense convection, and removing ambiguous signals that are related to underlying land or water surfaces. For 37 and 89 GHz, the older formulations of PCT from the literature yield generally similar values as ours, with the differences mainly being a few kelvins over oceans. An optimal formulation of PCT can depend on location and season; results are presented here separated by latitude and month.
Abstract
Coefficients are derived for computing the polarization-corrected temperature (PCT) for 10-, 19-, 37- and 89-GHz (and similar) frequencies, with applicability to satellites in the Global Precipitation Measurement mission constellation and their predecessors. PCTs for 10- and 19-GHz frequencies have been nonexistent or seldom used in the past; developing those is the main goal of this study. For 37 and 89 GHz, other formulations of PCT have already become well established. We consider those frequencies here in order to test whether the large sample sizes that are readily available now would point to different formulations of PCT. The purpose of the PCT is to reduce the effects of surface emissivity differences in a scene and draw attention to ice scattering signals related to precipitation. In particular, our intention is to develop a PCT formula that minimizes the differences between land and water surfaces, so that signatures resulting from deep convection are not easily confused with water surfaces. The new formulations of PCT for 10- and 19-GHz measurements hold promise for identifying and investigating intense convection. Four examples are shown from relevant cases. The PCT for each frequency is effective at drawing attention to the most intense convection, and removing ambiguous signals that are related to underlying land or water surfaces. For 37 and 89 GHz, the older formulations of PCT from the literature yield generally similar values as ours, with the differences mainly being a few kelvins over oceans. An optimal formulation of PCT can depend on location and season; results are presented here separated by latitude and month.
Abstract
Large hail is a primary contributor to damages and loss around the world, in both agriculture and infrastructure. The sensitivity of passive microwave radiometer measurements to scattering by hail led to the development of proxies for severe hail, most of which use brightness temperature thresholds from 37-GHz and higher-frequency microwave channels on board weather satellites in low-Earth orbit. Using 16+ years of data from the Tropical Rainfall Measuring Mission (TRMM; 36°S–36°N), we pair TRMM brightness temperature–derived precipitation features with surface hail reports in the United States to train a hail retrieval on passive microwave data from the 10-, 19-, 37-, and 85-GHz channels based on probability curves fit to the microwave data. We then apply this hail retrieval to features in the Global Precipitation Measurement (GPM) domain (from 69°S to 69°N) to develop a nearly global passive microwave–based climatology of hail. The extended domain of the GPM satellite into higher latitudes requires filtering out features that we believe are over icy and snowy surface regimes. We also normalize brightness temperature depression by tropopause height in an effort to account for differences in storm depth between the tropics and higher latitudes. Our results show the highest hail frequencies in the region of northern Argentina through Paraguay, Uruguay, and southern Brazil; the central United States; and a swath of Africa just south of the Sahel. Smaller hot spots include Pakistan, eastern India, and Bangladesh. A notable difference between these results and many prior satellite-based studies is that central Africa, while still active in our climatology, does not rival the aforementioned regions in retrieved hailstorm frequency.
Abstract
Large hail is a primary contributor to damages and loss around the world, in both agriculture and infrastructure. The sensitivity of passive microwave radiometer measurements to scattering by hail led to the development of proxies for severe hail, most of which use brightness temperature thresholds from 37-GHz and higher-frequency microwave channels on board weather satellites in low-Earth orbit. Using 16+ years of data from the Tropical Rainfall Measuring Mission (TRMM; 36°S–36°N), we pair TRMM brightness temperature–derived precipitation features with surface hail reports in the United States to train a hail retrieval on passive microwave data from the 10-, 19-, 37-, and 85-GHz channels based on probability curves fit to the microwave data. We then apply this hail retrieval to features in the Global Precipitation Measurement (GPM) domain (from 69°S to 69°N) to develop a nearly global passive microwave–based climatology of hail. The extended domain of the GPM satellite into higher latitudes requires filtering out features that we believe are over icy and snowy surface regimes. We also normalize brightness temperature depression by tropopause height in an effort to account for differences in storm depth between the tropics and higher latitudes. Our results show the highest hail frequencies in the region of northern Argentina through Paraguay, Uruguay, and southern Brazil; the central United States; and a swath of Africa just south of the Sahel. Smaller hot spots include Pakistan, eastern India, and Bangladesh. A notable difference between these results and many prior satellite-based studies is that central Africa, while still active in our climatology, does not rival the aforementioned regions in retrieved hailstorm frequency.
Abstract
Global Precipitation Measurement (GPM) Microwave Imager (GMI) brightness temperatures (BTs) were simulated over a case of severe convection in Texas using ground-based S-band radar and the Atmospheric Radiative Transfer Simulator. The median particle diameter D o of a normalized gamma distribution was varied for different hydrometeor types under the constraint of fixed radar reflectivity to better understand how simulated GMI BTs respond to changing particle size distribution parameters. In addition, simulations were conducted to assess how low BTs may be expected to reach from realistic (although extreme) particle sizes or concentrations. Results indicate that increasing D o for cloud ice, graupel, and/or hail leads to warmer BTs (i.e., weaker scattering signature) at various frequencies. Channels at 166.0 and 183.31 ± 7 GHz are most sensitive to changing D o of cloud ice, channels at ≥89.0 GHz are most sensitive to changing D o of graupel, and at 18.7 and 36.5 GHz they show the greatest sensitivity to hail D o . Simulations contrasting BTs above high concentrations of small (0.5-cm diameter) and low concentrations of large (20-cm diameter) hailstones distributed evenly across a satellite pixel showed much greater scattering using the higher concentration of smaller hailstones with BTs as low as ~110, ~33, ~22, ~46, ~100, and ~106 K at 10.65, 18.7, 36.5, 89.0, 166.0, and 183.31 ± 7 GHz, respectively. These results suggest that number concentration is more important for scattering than particle size given a constant S-band radar reflectivity.
Abstract
Global Precipitation Measurement (GPM) Microwave Imager (GMI) brightness temperatures (BTs) were simulated over a case of severe convection in Texas using ground-based S-band radar and the Atmospheric Radiative Transfer Simulator. The median particle diameter D o of a normalized gamma distribution was varied for different hydrometeor types under the constraint of fixed radar reflectivity to better understand how simulated GMI BTs respond to changing particle size distribution parameters. In addition, simulations were conducted to assess how low BTs may be expected to reach from realistic (although extreme) particle sizes or concentrations. Results indicate that increasing D o for cloud ice, graupel, and/or hail leads to warmer BTs (i.e., weaker scattering signature) at various frequencies. Channels at 166.0 and 183.31 ± 7 GHz are most sensitive to changing D o of cloud ice, channels at ≥89.0 GHz are most sensitive to changing D o of graupel, and at 18.7 and 36.5 GHz they show the greatest sensitivity to hail D o . Simulations contrasting BTs above high concentrations of small (0.5-cm diameter) and low concentrations of large (20-cm diameter) hailstones distributed evenly across a satellite pixel showed much greater scattering using the higher concentration of smaller hailstones with BTs as low as ~110, ~33, ~22, ~46, ~100, and ~106 K at 10.65, 18.7, 36.5, 89.0, 166.0, and 183.31 ± 7 GHz, respectively. These results suggest that number concentration is more important for scattering than particle size given a constant S-band radar reflectivity.
Abstract
In previous studies, remote sensing properties of hailstorms have been discussed using various spaceborne sensors. Relationships between hail occurrence and strong passive microwave brightness temperature depressions have been established. Using a 16-yr precipitation-feature database derived from the Tropical Rainfall Measuring Mission (TRMM) satellite, the performance of the TRMM Precipitation Radar and TRMM Microwave Imager is further investigated for hail detection. Detection criteria for hail larger than 19 mm are separately developed from Ku-band radar reflectivity and microwave brightness temperature properties of precipitation features that are collocated with surface hail reports over the southeastern and south-central United States. A threshold of 44 dBZ at −22°C is found to have the highest critical success index and Heidke skill score. The threshold of 230 K at 37 GHz yields the best scores among passive microwave properties. Using these two thresholds, global distributions of possible hail events are generated over 65°S–65°N using two years of observations from the Global Precipitation Measurement Core Observatory satellite. Differences in the derived hail geographical distributions are found between radar and passive microwave methods over tropical South America, the “Maritime Continent,” west-central Africa, Argentina, and South Africa. These discrepancies result from different vertical structures of the maximum radar reflectivity profiles over these regions relative to the southeastern and south-central United States, where the thresholds were established. Those differences generally led to overestimates in the tropics from the passive microwave methods, relative to the radar-based methods.
Abstract
In previous studies, remote sensing properties of hailstorms have been discussed using various spaceborne sensors. Relationships between hail occurrence and strong passive microwave brightness temperature depressions have been established. Using a 16-yr precipitation-feature database derived from the Tropical Rainfall Measuring Mission (TRMM) satellite, the performance of the TRMM Precipitation Radar and TRMM Microwave Imager is further investigated for hail detection. Detection criteria for hail larger than 19 mm are separately developed from Ku-band radar reflectivity and microwave brightness temperature properties of precipitation features that are collocated with surface hail reports over the southeastern and south-central United States. A threshold of 44 dBZ at −22°C is found to have the highest critical success index and Heidke skill score. The threshold of 230 K at 37 GHz yields the best scores among passive microwave properties. Using these two thresholds, global distributions of possible hail events are generated over 65°S–65°N using two years of observations from the Global Precipitation Measurement Core Observatory satellite. Differences in the derived hail geographical distributions are found between radar and passive microwave methods over tropical South America, the “Maritime Continent,” west-central Africa, Argentina, and South Africa. These discrepancies result from different vertical structures of the maximum radar reflectivity profiles over these regions relative to the southeastern and south-central United States, where the thresholds were established. Those differences generally led to overestimates in the tropics from the passive microwave methods, relative to the radar-based methods.
Abstract
Using passive microwave brightness temperatures Tb from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and hydrometeor identification (HID) data from dual-polarization ground radars, empirical lookup tables are developed for a multifrequency estimation of the likelihood a precipitation column includes certain hydrometeor types, as a function of Tb . Eight years of collocated Tb and HID data from the GPM Validation Network are used for development and testing of the GMI-based HID retrieval, with 2015–20 used for training and 2021–22 used for testing the GMI-based HID retrieval. The occurrence of profiles with hail and graupel are both slightly underpredicted by the lookup tables, but the percentage of profiles predicted is highly correlated with the percentage observed (0.98 correlation coefficient for hail and 0.99 for graupel). By having snow appear before rain in the hierarchy, the sample size for rain, without ice aloft, is fairly small, and the percentage of rain profiles is less than snow for all Tb .
Abstract
Using passive microwave brightness temperatures Tb from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and hydrometeor identification (HID) data from dual-polarization ground radars, empirical lookup tables are developed for a multifrequency estimation of the likelihood a precipitation column includes certain hydrometeor types, as a function of Tb . Eight years of collocated Tb and HID data from the GPM Validation Network are used for development and testing of the GMI-based HID retrieval, with 2015–20 used for training and 2021–22 used for testing the GMI-based HID retrieval. The occurrence of profiles with hail and graupel are both slightly underpredicted by the lookup tables, but the percentage of profiles predicted is highly correlated with the percentage observed (0.98 correlation coefficient for hail and 0.99 for graupel). By having snow appear before rain in the hierarchy, the sample size for rain, without ice aloft, is fairly small, and the percentage of rain profiles is less than snow for all Tb .
