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Cloud and precipitation simulated using the three-dimensional (3D) Goddard Cumulus Ensemble (GCE) model are compared to Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) rainfall measurements and Clouds and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. Both the model simulation and retrieved parameters are based upon observations made during the South China Sea Monsoon Experiment (SCSMEX) field campaign. The model-simulated cloud and rain systems are evaluated by systematically examining important parameters such as the surface rain rate, convective/stratiform percentage, rain profiles, cloud properties, and precipitation efficiency. It is demonstrated that the GCE model is capable of simulating major convective system development and reproduces the total surface rainfall amount as compared to rainfall estimated from the SCSMEX sounding network. The model yields a slightly higher total convective rain/stratiform rain ratio than the TMI and PR observations. The GCE rainfall spectrum exhibits a greater contribution from heavy rains than those estimated from PR or TMI observations. In addition, the GCE simulation produces much greater amounts of snow and graupel than the TRMM retrievals. The model's precipitation efficiency of convective rain is close to the observations, but the precipitation efficiency of stratiform rain is much lower than the observations because of large amounts of slowly falling simulated snow and graupel. Compared to observations, the GCE produces more compact areas of intense convection and less anvil cloud, which are consistent with a smaller total cloud fraction and larger domain-averaged outgoing longwave radiation.

Rainfall is a fundamental process within the Earth's hydrological cycle because it represents a principal forcing term in surface water budgets, while its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating well into the middle latitudes. Latent heat production itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the Tropics, as well as modify the energetic efficiencies of midlatitude weather systems. This paper highlights the retrieval of latent heating from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing credible four-dimensional accounts of rainfall over the global Tropics and subtropics, information that can be used to estimate the space-time structure of latent heating across the Earth's low latitudes. A set of algorithm methodologies for estimating latent heating based on precipitation-rate profile retrievals obtained from TRMM measurements has been under continuous development since the advent of the mission's research program. These algorithms are briefly described, followed by a discussion of the latent heating products that they generate. The paper then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

This paper presents an analysis of a unique radar and radiometer dataset from the National Aeronautics and Space Administration (NASA) ER-2 high-altitude aircraft overflying Florida thunderstorms on 5 October 1993 during the Convection and Moisture Experiment (CAMEX). The observations represent the first ER-2 Doppler radar (EDOP) measurements and perhaps the most comprehensive multispectral precipitation measurements collected from a single aircraft. The objectives of this paper are to 1) examine the relation of the vertical radar reflectivity structure to the radiometric responses over a wide range of remote sensing frequencies, 2) examine the limitations of rain estimation schemes over land and ocean backgrounds based on the observed vertical reflectivity structures and brightness temperatures, and 3) assess the usefulness of scattering-based microwave frequencies (86 GHz and above) to provide information on vertical structure in the ice region. Analysis focused on two types of convection: a small group of thunderstorms over the Florida Straits and sea-breeze-initiated convection along the Florida Atlantic coast. Various radiometric datasets are synthesized including visible, infrared (IR), and microwave (10-220 GHz). The rain cores observed over an ocean background by EDOP, compared quite well with elevated brightness temperatures from the Advanced Microwave Precipitation Radiometer (AMPR) 10.7-GHz channel. However, at higher microwave frequencies, which are ice-scattering based, storm evolution and vertical wind shear were found to be important in interpretation of the radiometric observations. As found in previous studies, the ice-scattering region was displaced significantly downshear of the convective and surface rainfall regions due to upper-level wind advection. The ice region above the rain layer was more opaque in the IR, although the 150- and 220-GHz brightness temperatures [T.sub.b] approached the IR measurements and both corresponded well with the radar-detected ice regions. It was found that ice layer reflectivities and thicknesses were approximately 15 dBZ and a few kilometers, respectively, for detectable ice scattering to be present at these higher microwave frequencies. The EDOP-derived rainfall rates and the simultaneous microwave [T.sub.b]'s were compared with single-frequency forward radiative transfer calculations using a family of vertical cloud and precipitation water profiles derived from a three-dimensional cloud model. Over water backgrounds, the lower-frequency emission-based theoretical curves agreed in a rough sense with the observed radar rainfall rate-[T.sub.b] data points, in view of the uncertainties in the measurements and the scatter of the cloud model profiles. The characteristics of the ice regions of the thunderstorms were examined using brightness temperature differences [Delta][T.sub.b] such as [T.sub.b] (37 GHz) - [T.sub.b] (220 GHz). The [Delta][T.sub.b]'s (150-220, 89-220, and 37-86 GHz) suggested a possible classification of the clouds and precipitation according to convective cores, elevated ice layers, and rain without significant ice above the melting layer. Although some qualitative classification of the ice is possible, the quantitative connection with ice path was difficult to obtain from the present observations.

This paper describes the latest improvements applied to the Goddard profiling algorithm (GPROF), particularly as they apply to the Tropical Rainfall Measuring Mission (TRMM). Most of these improvements, however, are conceptual in nature and apply equally to other passive microwave sensors. The improvements were motivated by a notable overestimation of precipitation in the intertropical convergence zone. This problem was traced back to the algorithm's poor separation between convective and stratiform precipitation coupled with a poor separation between stratiform and transition regions in the a priori cloud model database. In addition to now using an improved convective-stratiform classification scheme, the new algorithm also makes use of emission and scattering indices instead of individual brightness temperatures. Brightness temperature indices have the advantage of being monotonic functions of rainfall. This, in turn, has allowed the algorithm to better define the uncertainties needed by the scheme's Bayesian inversion approach. Last, the algorithm over land has been modified primarily to better account for ambiguous classification where the scattering signature of precipitation could be confused with surface signals. All these changes have been implemented for both the TRMM Microwave Imager (TMI) and the Special Sensor Microwave Imager (SSM/I). Results from both sensors are very similar at the storm scale and for global averages. Surface rainfall products from the algorithm's operational version have been compared with conventional rainfall data over both land and oceans. Over oceans, GPROF results compare well with atoll gauge data. GPROF is biased negatively by 9% with a correlation of 0.86 for monthly 2.5 [degrees] averages over the atolls. If only grid boxes with two or more atolls are used, the correlation increases to 0.91 but GPROF becomes positively biased by 6%. Comparisons with TRMM ground validation products from Kwajalein reveal that GPROF is negatively biased by 32%, with a correlation of 0.95 when coincident images of the TMI and Kwajalein radar are used. The absolute magnitude of rainfall measured from the Kwajalein radar, however, remains uncertain, and GPROF overestimates the rainfall by approximately 18% when compared with estimates done by a different research group. Over land, GPROF shows a positive bias of 17% and a correlation of 0.80 over monthly 5 [degrees] grids when compared with the Global precipitation Climatology Center (GPCC) gauge network. When compared with the precipitation radar (PR) over land, GPROF also retrieves higher rainfall amounts (20%). No vertical hydrometeor profile information is available over land. The correlation with the TRMM precipitation radar is 0.92 over monthly 5 [degrees] grids, but GPROF is positively biased by 24% relative to the radar over oceans. Differences between TMI- and PR-derived vertical hydrometeor profiles below 2 km are consistent with this bias but become more significant with altitude. Above 8 km, the sensors disagree significantly, but the information content is low from both TMI and PR. The consistent bias between these two sensors without clear guidance from the ground-based data reinforces the need for better understanding of the physical assumptions going into these retrievals.

Focuses on the first attempt to use Tropical Rainfall Measuring Mission (TRMM) rainfall information to estimate the latent heating structure over the global Tropics for February 1998. Comparison and validation of different latent heating algorithms; Impact of different TRMM Microwave Imager and precipitation radar rainfall information on latent heating structures.