Search Results
(1982) and Johnson and Young (1983) , there is a remarkable difference in the heating profiles between convective and stratiform regions of mesoscale convective systems (MCSs). They found that in convective regions of MCSs, the heating profile has positive heating throughout the troposphere with a maximum in the midtroposphere, while, in stratiform regions, there is an upper-level heating and cooling below the melting level. Hartmann et al. (1984) showed that the pattern of the large
(1982) and Johnson and Young (1983) , there is a remarkable difference in the heating profiles between convective and stratiform regions of mesoscale convective systems (MCSs). They found that in convective regions of MCSs, the heating profile has positive heating throughout the troposphere with a maximum in the midtroposphere, while, in stratiform regions, there is an upper-level heating and cooling below the melting level. Hartmann et al. (1984) showed that the pattern of the large
warm rain processes but perhaps may include ice and/or mixed phase processes. On the other hand, heating profiles associated with stratiform rain are characterized with positive heating in the upper troposphere with a peak at ∼8 km and cooling in the lower troposphere with a peak at ∼4 km, both over the ocean and over land. Deep stratiform rain comes from the nimbostratus clouds, which are associated primarily with the widespread continuous clouds of mesoscale convective systems, hurricanes, and
warm rain processes but perhaps may include ice and/or mixed phase processes. On the other hand, heating profiles associated with stratiform rain are characterized with positive heating in the upper troposphere with a peak at ∼8 km and cooling in the lower troposphere with a peak at ∼4 km, both over the ocean and over land. Deep stratiform rain comes from the nimbostratus clouds, which are associated primarily with the widespread continuous clouds of mesoscale convective systems, hurricanes, and
the TWP-ICE soundings and background European Centre for Medium-Range Weather Forecasts (ECMWF) analyses using an interpolation scheme described by Cressman (1959) . The Cressman scheme uses a weighting function that depends on the distance between an observation station and an analysis grid point, as well as the difference between observations and the background. The interpolation is carried out for the difference field between observations and the background. If there is no measurement within a
the TWP-ICE soundings and background European Centre for Medium-Range Weather Forecasts (ECMWF) analyses using an interpolation scheme described by Cressman (1959) . The Cressman scheme uses a weighting function that depends on the distance between an observation station and an analysis grid point, as well as the difference between observations and the background. The interpolation is carried out for the difference field between observations and the background. If there is no measurement within a
resource for scientific research and applications (see a review by Tao et al. 2006 ). Such products enable new insights and investigations into the complexities of convective system life cycles, diabatic heating controls and feedbacks related to mesoscale to synoptic-scale circulations and their forecasting, the relationship of tropical patterns of LH to the global circulation and climate, and strategies for improving cloud parameterizations in environmental prediction models. Five different TRMM LH
resource for scientific research and applications (see a review by Tao et al. 2006 ). Such products enable new insights and investigations into the complexities of convective system life cycles, diabatic heating controls and feedbacks related to mesoscale to synoptic-scale circulations and their forecasting, the relationship of tropical patterns of LH to the global circulation and climate, and strategies for improving cloud parameterizations in environmental prediction models. Five different TRMM LH
, 2007) . Briefly, HERB synthesizes ice cloud microphysical property information from VIRS; liquid cloud properties, precipitation profiles, SST, and water vapor retrievals from the TRMM TMI; and vertical profiles of temperature and humidity from the European Center for Medium-Range Weather Forecasts (ECMWF) reanalyses to characterize the three-dimensional structure of clouds and precipitation in the atmosphere. These provide input to a broadband radiative transfer model that simulates vertical
, 2007) . Briefly, HERB synthesizes ice cloud microphysical property information from VIRS; liquid cloud properties, precipitation profiles, SST, and water vapor retrievals from the TRMM TMI; and vertical profiles of temperature and humidity from the European Center for Medium-Range Weather Forecasts (ECMWF) reanalyses to characterize the three-dimensional structure of clouds and precipitation in the atmosphere. These provide input to a broadband radiative transfer model that simulates vertical
dataset is used for comparison. TMI 2A12 data for the summer seasons of the 1998–2006 period, between May and September, were acquired through the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC; online at http://disc.sci.gsfc.nasa.gov/ ). The TRMM CSH datasets were obtained from two sources: the GES DAAC system (monthly resolution dataset from 1998 to 2006) and directly from W. K. Tao’s group in National Aeronautics and Space Administration’s (NASA’s) Mesoscale Atmospheric
dataset is used for comparison. TMI 2A12 data for the summer seasons of the 1998–2006 period, between May and September, were acquired through the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC; online at http://disc.sci.gsfc.nasa.gov/ ). The TRMM CSH datasets were obtained from two sources: the GES DAAC system (monthly resolution dataset from 1998 to 2006) and directly from W. K. Tao’s group in National Aeronautics and Space Administration’s (NASA’s) Mesoscale Atmospheric
