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- Author or Editor: H-Y. M. Yeh x
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Abstract
Aircraft passive microwave observations of deep atmospheric convection at frequencies between 18 and 183 GHz are presented in conjunction with visible and infrared satellite and aircraft observations and ground-based radar observations. Deep convective cores are indicated in the microwave data by negative brightness temperature (TB ) deviations from the land background (270 K) to extreme TB values below 100 K at 37, 92, and 183 GHz and below 200 K at 18 GHz. These TB minima, due to scattering by ice held aloft by the intense updrafts, are well correlated with areas of high radar reflectivity. For this land background case, TB is inversely correlated with rain rate at all frequencies due to TB -ice-rain correlations. Mean ΔT between vertically polarized and horizontally polarized radiance in precipitation areas is approximately 6 K at both 18 GHz and 37 GHz, indicating nonspherical precipitation size ice particles with a preferred horizontal orientation. Convective cores not observed in the visible and infrared data are clearly defined in the microwave observations and borders of convective rain areas are well defined using the high-frequency (90 GHz and greater) microwave observations.
Abstract
Aircraft passive microwave observations of deep atmospheric convection at frequencies between 18 and 183 GHz are presented in conjunction with visible and infrared satellite and aircraft observations and ground-based radar observations. Deep convective cores are indicated in the microwave data by negative brightness temperature (TB ) deviations from the land background (270 K) to extreme TB values below 100 K at 37, 92, and 183 GHz and below 200 K at 18 GHz. These TB minima, due to scattering by ice held aloft by the intense updrafts, are well correlated with areas of high radar reflectivity. For this land background case, TB is inversely correlated with rain rate at all frequencies due to TB -ice-rain correlations. Mean ΔT between vertically polarized and horizontally polarized radiance in precipitation areas is approximately 6 K at both 18 GHz and 37 GHz, indicating nonspherical precipitation size ice particles with a preferred horizontal orientation. Convective cores not observed in the visible and infrared data are clearly defined in the microwave observations and borders of convective rain areas are well defined using the high-frequency (90 GHz and greater) microwave observations.
Abstract
Arctic sea ice area (SIA) during late summer and early fall decreased substantially over the last four decades, and its decline accelerated beginning in the early 2000s. Statistical analyses of observations show that enhanced poleward moisture transport from the North Pacific to the Arctic Ocean contributed to the accelerated SIA decrease during the most recent period. As a consequence, specific humidity in the Arctic Pacific sector significantly increased along with an increase of downward longwave radiation beginning in 2002, which led to a significant acceleration in the decline of SIA in the Arctic Pacific sector. The resulting sea ice loss led to increased evaporation in the Arctic Ocean, resulting in a further increase of the specific humidity in mid-to-late fall, thus acting as a positive feedback to the sea ice loss. The overall set of processes is also found in a long control simulation of a coupled climate model.
Abstract
Arctic sea ice area (SIA) during late summer and early fall decreased substantially over the last four decades, and its decline accelerated beginning in the early 2000s. Statistical analyses of observations show that enhanced poleward moisture transport from the North Pacific to the Arctic Ocean contributed to the accelerated SIA decrease during the most recent period. As a consequence, specific humidity in the Arctic Pacific sector significantly increased along with an increase of downward longwave radiation beginning in 2002, which led to a significant acceleration in the decline of SIA in the Arctic Pacific sector. The resulting sea ice loss led to increased evaporation in the Arctic Ocean, resulting in a further increase of the specific humidity in mid-to-late fall, thus acting as a positive feedback to the sea ice loss. The overall set of processes is also found in a long control simulation of a coupled climate model.
Abstract
Simulations of observations from potential spaceborne radars are made based on storm structure generated from the three-dimensional (3D) Goddard cumulus ensemble model simulation of an intense overland convective system. Five frequencies of 3, 10, 14, 35, and 95 GHz are discussed, but the Tropical Rainfall Measuring Mission precipitation radar sensor frequency ( 14 GHz) is the focus of this study. Radar reflectivities and their attenuation in various atmospheric conditions are studied in this simulation. With the attenuation from cloud and precipitation in the estimation of reflectivity factor (dBZ), the reflectivities in the lower atmosphere in the convective coresare significantly reduced. With spatial resolution of 4 km X 4 km, attenuation at 14 GHz may cause as large as a 20-dBZ difference between the simulated measurements of the peak (Zmp) and near-surface reflectivity (Zmp) in the most intense convective region. The Zmp occurs at various altitudes depending on the hydrometeor concentrations and their vertical distribution. Despite the significant attenuation in the intense cores, the presence of the rain maximum is easily detected by using information of Zmp. In the stratiform region, the attenuation is quite limited (usually less than 5 dBZ), and the reduction of reflectivity is mostly related to the actual vertical structure of cloud distribution. Since Zmp suffers severe attenuation and tends to underestimate surface rainfall intensity in convective regions, Zmp can be more representative for rainfall retrieval in the lower atmosphere in these regions. In the stratiform region where attenuation is negligible, however, Zmp tends to overestimate surface rainfall and Zmp is more appropriate for rainfall retrieval. A hybrid technique using a weight between the two rain intensities is testedand found potentially useful for future applications. The estimated surface rain-rate map based on this hybrid approach captures many of the details of the cloud model rain field but still slightly underestimates the rain-rate maximum.
Abstract
Simulations of observations from potential spaceborne radars are made based on storm structure generated from the three-dimensional (3D) Goddard cumulus ensemble model simulation of an intense overland convective system. Five frequencies of 3, 10, 14, 35, and 95 GHz are discussed, but the Tropical Rainfall Measuring Mission precipitation radar sensor frequency ( 14 GHz) is the focus of this study. Radar reflectivities and their attenuation in various atmospheric conditions are studied in this simulation. With the attenuation from cloud and precipitation in the estimation of reflectivity factor (dBZ), the reflectivities in the lower atmosphere in the convective coresare significantly reduced. With spatial resolution of 4 km X 4 km, attenuation at 14 GHz may cause as large as a 20-dBZ difference between the simulated measurements of the peak (Zmp) and near-surface reflectivity (Zmp) in the most intense convective region. The Zmp occurs at various altitudes depending on the hydrometeor concentrations and their vertical distribution. Despite the significant attenuation in the intense cores, the presence of the rain maximum is easily detected by using information of Zmp. In the stratiform region, the attenuation is quite limited (usually less than 5 dBZ), and the reduction of reflectivity is mostly related to the actual vertical structure of cloud distribution. Since Zmp suffers severe attenuation and tends to underestimate surface rainfall intensity in convective regions, Zmp can be more representative for rainfall retrieval in the lower atmosphere in these regions. In the stratiform region where attenuation is negligible, however, Zmp tends to overestimate surface rainfall and Zmp is more appropriate for rainfall retrieval. A hybrid technique using a weight between the two rain intensities is testedand found potentially useful for future applications. The estimated surface rain-rate map based on this hybrid approach captures many of the details of the cloud model rain field but still slightly underestimates the rain-rate maximum.
Abstract
Data from the Temperature Humidity Infrared Radiometer (THIR) and the Total Ozone Mapping Spectrometer (TOMS), both aboard the Nimbus-7 satellite, are used to determine cloudiness parameters for the globe. The 11.5 μm THIR radiances and the 0.36 μm and 0.38 μm TOMS reflectivities, along with concurrent surface temperature data from the Air Force 3-D nephanalysis, are the primary data sources. They are processed by an algorithm that determines total cloud amount, cloud amount in three altitude categories, cirrus cloud, deep convective cloud, warm cloud, and the radiance of radiation emitted by the clouds. and the underlying surface. The algorithm is of the bispectral threshold type, which yields two independent estimates of total cloud, one from the infrared algorithm and one from the UV reflectivity algorithm. For the daytime observations (local noon at the equator), these two independent estimates are combined to determine a composite estimate, while at night (local midnight at the equator), only the infrared threshold algorithm is used in the estimate. Quantitative validation of total cloud amount was performed by comparing the algorithm results with estimates derived by an analyst interpreting geosynchronous satellite (GOES) images, along with auxiliary meteorological data. It has been concluded that the systematic errors of the Nimbus-7 total cloud amount algorithm relative to the analyst are less than 10%, and that the random errors of daily estimates range between 7% and 16%, day or night. These empirical results are consistent with results from a theoretical sensitivity study. Qualitative validation has also been performed by making comparisons with GOES visible and infrared images for specific days. Results indicate that the TOMS cloud estimates improve the IR algorithm estimates of low cloud amount and provide for the identification of cirrus and deep convective cloud, but cloud amounts over humid tropical regions tend to be overestimated even with the use of TOMS. These results suggest that the spatial and temporal characteristics of daily and monthly averaged global cloud cover, including cirrus acid deep convective cloud types, which are presented in Part II, are generally well represented by the Nimbus-7 dataset, which covers a six-year period from April 1979 to March 1985.
Abstract
Data from the Temperature Humidity Infrared Radiometer (THIR) and the Total Ozone Mapping Spectrometer (TOMS), both aboard the Nimbus-7 satellite, are used to determine cloudiness parameters for the globe. The 11.5 μm THIR radiances and the 0.36 μm and 0.38 μm TOMS reflectivities, along with concurrent surface temperature data from the Air Force 3-D nephanalysis, are the primary data sources. They are processed by an algorithm that determines total cloud amount, cloud amount in three altitude categories, cirrus cloud, deep convective cloud, warm cloud, and the radiance of radiation emitted by the clouds. and the underlying surface. The algorithm is of the bispectral threshold type, which yields two independent estimates of total cloud, one from the infrared algorithm and one from the UV reflectivity algorithm. For the daytime observations (local noon at the equator), these two independent estimates are combined to determine a composite estimate, while at night (local midnight at the equator), only the infrared threshold algorithm is used in the estimate. Quantitative validation of total cloud amount was performed by comparing the algorithm results with estimates derived by an analyst interpreting geosynchronous satellite (GOES) images, along with auxiliary meteorological data. It has been concluded that the systematic errors of the Nimbus-7 total cloud amount algorithm relative to the analyst are less than 10%, and that the random errors of daily estimates range between 7% and 16%, day or night. These empirical results are consistent with results from a theoretical sensitivity study. Qualitative validation has also been performed by making comparisons with GOES visible and infrared images for specific days. Results indicate that the TOMS cloud estimates improve the IR algorithm estimates of low cloud amount and provide for the identification of cirrus and deep convective cloud, but cloud amounts over humid tropical regions tend to be overestimated even with the use of TOMS. These results suggest that the spatial and temporal characteristics of daily and monthly averaged global cloud cover, including cirrus acid deep convective cloud types, which are presented in Part II, are generally well represented by the Nimbus-7 dataset, which covers a six-year period from April 1979 to March 1985.
