Engineering topics

Tao, Wei-Kuo

Publications and source records attributed to Tao, Wei-Kuo.

At least 145 records · Page 8

NASA NTRS2004

High-Resolution Mesoscale Simulations of the 6-7 May 2000 Missouri Flash Flood: Impact of Model Initialization and Land Surface Treatment

High-resolution mesoscale model simulations of the 6-7 May 2000 Missouri flash flood event were performed to test the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation. In this flash flood event, a mesoscale convective system (MCS) produced over 340 mm of rain in roughly 9 hours in some locations. Two different types of model initialization were employed: 1) NCEP global reanalysis with 2.5-degree grid spacing and 12-hour temporal resolution, and 2) Eta reanalysis with 40- km grid spacing and $hour temporal resolution. In addition, two different land surface treatments were considered. A simple land scheme. (SLAB) keeps soil moisture fixed at initial values throughout the simulation, while a more sophisticated land model (PLACE) allows for r interactive feedback. Simulations with high-resolution Eta model initialization show considerable improvement in the intensity of precipitation due to the presence in the initialization of a residual mesoscale convective vortex (hlCV) from a previous MCS. Simulations with the PLACE land model show improved location of heavy precipitation. Since soil moisture can vary over time in the PLACE model, surface energy fluxes exhibit strong spatial gradients. These surface energy flux gradients help produce a strong low-level jet (LLJ) in the correct location. The LLJ then interacts with the cold outflow boundary of the MCS to produce new convective cells. The simulation with both high-resolution model initialization and time-varying soil moisture test reproduces the intensity and location of observed rainfall.

Baker, R. David↗

NASA NTRS2004

Characteristics of Heavy Summer Rainfall in Southwestern Taiwan in Relation to Orographic Effects

On the windward side of southwestern Taiwan, about a quarter to a half of all rainfall during mid-July through August from 1994 to 2000 came from convective systems embedded in the southwesterly monsoon flow. k this study, the causes of two heavy rainfall events (daily rainfall exceeding 100 mm day over at least three rainfall stations) observed over the slopes and/or lowlands of southwestern Taiwan were examined. Data from European Center for Medium-Range Weather Forecasts /Tropical Ocean- Global Atmosphere (EC/TOGA) analyses, the rainfall stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) and the conventional surface stations over Taiwan, and the simulation results from a regional-scale numerical model were used to accomplish the objectives. In one event (393 mm day on 9 August 1999), heavy rainfall was observed over the windward slopes of southern Taiwan in a potentially unstable environment with very humid air around 850 hPa. The extreme accumulation was simulated and attributed to orographic lifting effects. No preexisting convection drifted in from the Taiwan Strait into western Taiwan.

Chen, Ching-Sen↗

NASA NTRS2004

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

Tao, Wei-Kuo↗

NASA NTRS2004

Sensitivity of a Cloud-Resolving Model to the Bulk and Explicit Bin Microphysical Schemes

A cloud-resolving model is used to study sensitivities of two different microphysical schemes, one is the traditional bulk type, and the other is an explicit bin scheme, in simulating a mid-latitude squall line case (PRE-STORM, June 10-1 1,1985). Simulations using different microphysical schemes are compared with each other and also with the observations. Both the bulk and bin models reproduce the general features during the developing and mature stage of the system. Furthermore, the observations and the well-proven bulk scheme simulation serve as validations for the newly incorporated bin scheme. However, it is also shown that the bulk and bin simulations have distinct differences, most notably in the stratiform region of the squall line system. Weak convective cells exist in the stratiform region in the bulk simulation, but not in the bin simulation. These weak convective cells in the stratiform region simulated in the bulk scheme model are remnants of the stronger convections previously at the leading edge of the system, sustained by horizontal vorticity generated by its own cool pool near the surface. The bin simulation, on the other hand, has a horizontally homogeneous stratiform cloud structure, which agrees better with the observations. Examinations of the downdraft core strength, the potential temperature perturbation, and the evaporative cooling rate show that the differences between the bulk and bin models are due mainly to the stronger low-level evaporative cooling in the convective zone simulated in the bulk microphysical scheme, which is unrealistic because of the assumptions made in raindrop size distribution. Further sensitivity tests that reduce the evaporation rate in bulk scheme artificially produce more upright convective core and less weak cores in stratiform region. However, they produce weaker upper level outflow and consequently less stratiform rain area. The addition of a more realistic raindrop breakup scheme in the bin scheme results more realistic radar reflectivity and stronger surface rainfall. Despite the increase of the rain evaporation and strengthening of the near surface cool pool, bin scheme with rain breakup shows homogeneous stratiform rain. These sensitivity tests prove the robustness of the bin microphysical scheme and the difficulty of tuning the limited parameters in the bulk microphysical scheme to realistically reproduce detail structures in a mid-latitude squall line case study.

Li, Xiao-Wen↗

NASA NTRS2004

Coupled fvGCM-GCE Modeling System, TRMM Latent Heating and Cloud Library

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to imiprove the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. I this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the Goddard research plan of using Weather Research Forecast (WRF) model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Tao, Wei-Kuo↗

NASA NTRS2004

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Olson, William S.↗

NASA NTRS2004

A Meteorological Model's Dependence on Radiation Update Frequency

Numerical weather models are used to simulate circulations in the atmosphere including clouds and precipitation by applying a set of mathematical equations over a three-dimensional grid. The grid is composed of discrete points at which the meteorological variables are defined. As computing power continues to rise these models are being used at finer grid spacing, but they must still cover a wide range of scales. Some of the physics that must be accounted for in the model cannot be explicitly resolved, and their effects, therefore, must be estimated or "parameterized". Some of these parameterizations are computationally expensive. To alleviate the problem, they are not always updated at the time resolution of the model with the assumption being that the impact will be small. In this study, a coupled land-atmosphere model is used to assess the impact of less frequent updates of the computationally expensive radiation physics for a case on June 6, 2002, that occurred during a field experiment over the central plains known as International H20 Project (IHOP). The model was tested using both the original conditions, which were dry, and with modified conditions wherein moisture was added to the lower part of the atmosphere to produce clouds and precipitation (i.e., a wet case). For each of the conditions (i.e., dry and wet), four set of experiments were conducted wherein the model was run for a period of 24 hours and the radiation fields (including both incoming solar and outgoing longwave) were updated every 1, 3, 10, and 100 time steps. Statistical tests indicated that average quantities of surface variables for both the dry and wet cases were the same for the various update frequencies. However, spatially the results could be quite different especially in the wet case after it began to rain. The near-surface wind field was found to be different most of the time even for the dry case. In the wet case, rain intensities and average vertical profiles of heating associated with cloudy areas were found to differ for the various radiation update frequencies. The latter implies that the mean state of the model could be different as a result of not updating the radiation fields every time step and has important implications for longer term climate studies

Eastman, Joseph L.↗

NASA NTRS2003

Mesoscale Assimilation of TMI Rainfall Data with 4DVAR: Sensitivity Studies

Sensitivity studies are performed on the assimilation of TRMM (Tropical Rainfall Measurement Mission) Microwave Imager (TMI) derived rainfall data into a mesoscale model using a four-dimensional variational data assimilation (4DVAR) technique. A series of numerical experiments is conducted to evaluate the impact of TMI rainfall data on the numerical simulation of Hurricane Bonnie (1998). The results indicate that rainfall data assimilation is sensitive to the error characteristics of the data and the inclusion of physics in the adjoint and forward models. In addition, assimilating the rainfall data alone is helpful for producing a more realistic eye and rain bands in the hurricane but does not ensure improvements in hurricane intensity forecasts. Further study indicated that it is necessary to incorporate TMI rainfall data together with other types of data such as wind data into the model, in which case the inclusion of the rainfall data further improves the intensity forecast of the hurricane. This implies that proper constraints may be needed for rainfall assimilation.

Tao, Wei-Kuo↗

NASA NTRS2003

A Discrete Constraint for Entropy Conservation and Sound Waves in Cloud-Resolving Modeling

Ideal cloud-resolving models contain little-accumulative errors. When their domain is so large that synoptic large-scale circulations are accommodated, they can be used for the simulation of the interaction between convective clouds and the large-scale circulations. This paper sets up a framework for the models, using moist entropy as a prognostic variable and employing conservative numerical schemes. The models possess no accumulative errors of thermodynamic variables when they comply with a discrete constraint on entropy conservation and sound waves. Alternatively speaking, the discrete constraint is related to the correct representation of the large-scale convergence and advection of moist entropy. Since air density is involved in entropy conservation and sound waves, the challenge is how to compute sound waves efficiently under the constraint. To address the challenge, a compensation method is introduced on the basis of a reference isothermal atmosphere whose governing equations are solved analytically. Stability analysis and numerical experiments show that the method allows the models to integrate efficiently with a large time step.

Zeng, Xi-Ping↗

NASA NTRS2003

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fewer droplets, larger sized develop due to the greater condensational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.

Tao, Wei-Kuo↗

NASA NTRS2003

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud-resolving Model

The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution on the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulate squall lines that developed in the western Pacific, South China Sea, eastern Atlantic, South America and central US. For the cloud ensemble, the GCE model was integrated for several days in order to have a good sampling of cloud statistics.

Tao, Wei-Kuo↗

NASA NTRS2003

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud-Resolving Model

The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution on the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes, and with surface processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulate squall lines that developed in the western Pacific, eastern Atlantic and central US. For the cloud ensemble, the GCE model was integrated for several days in order to have good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolution will be examined.

Tao, Wei-Kuo↗

NASA NTRS2003

Radar Reflectivity Simulated by a 2-D Spectra Bin Model: Sensitivity of Cloud-aerosol Interaction

The Goddard Cumulus Ensemble (GCE) model with bin spectra microphysics is used to simulate mesoscale convective systems.The model uses explicit bins to represent size spectra of cloud nuclei, water drops, ice crystals, snow and graupel. Each hydrometeorite category is described by 33 mass bins. The simulations provide a unique data set of simulated raindrop size distribution in a realistic dynamic frame. Calculations of radar parameters using simulated drop size distribution serve as an evaluation of numerical model performance. In addition, the GCE bin spectra modes is a very useful tool to study uncertainties related to radar observations; all the environmental parameters are precisely known. In this presentation, we concentrate on the discussion of Z-R (ZDR-R) relation in the simulated systems. Due to computational limitations, the spectra bin model has been run in two dimensions with 31 stretched vertical layers and 1026 horizontal grid points (1 km resolution). Two different cases, one in midlatitude continent, the other in tropical ocean, have been simulated. The continental case is a strong convection which lasted for two hours. The oceanic case is a persistent system with more than 10 hours' life span. It is shown that the simulated Z-R (ZDR-R) relations generally agree with observations using radar and rain gauge data. The spatial and temporal variations of Z-R relation in different locations are also analyzed. Impact of aerosols on cloud formation and raindrop size distribution was studied. Both clean (low CCN) and dirty (high CCN) cases are simulated. The Z-R relation is shown to vary considerable in the initial CCN concentrations.

Li, Kiaowen↗

NASA NTRS2003

Simulated KWAJEX Convective Systems Using a 2D and 3D Cloud Resolving Model and Their Comparisons with Radar Observations

The 1999 Kwajalein Atoll field experiment (KWAJEX), one of several major TRMM (Tropical Rainfall Measuring Mission) field experiments, has successfully obtained a wealth of information and observation data on tropical convective systems over the western Central Pacific region. In this paper, clouds and convective systems that developed during three active periods (Aug 7-12, Aug 17-21, and Aug 29-Sep 13) around Kwajalein Atoll site are simulated using both 2D and 3D Goddard Cumulus Ensemble (GCE) models. Based on numerical results, the clouds and cloud systems are generally unorganized and short lived. These features are validated by radar observations that support the model results. Both the 2D and 3D simulated rainfall amounts and their stratiform contribution as well as the heat, water vapor, and moist static energy budgets are examined for the three convective episodes. Rainfall amounts are quantitatively similar between the two simulations, but the stratiform contribution is considerably larger in the 2D simulation. Regardless of dimension, fo all three cases, the large-scale forcing and net condensation are the two major physical processes that account for the evolution of the budgets with surface latent heat flux and net radiation solar and long-wave radiation)being secondary processes. Quantitative budget differences between 2D and 3D as well as between various episodes will be detailed.Morover, simulated radar signatures and Q1/Q2 fields from the three simulations are compared to each other and with radar and sounding observations.

Shie, Chung-Lin↗

NASA NTRS2003

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud Resolving Model

The Goddard Cumulus Ensemble (GCE) model examines the impact of various microphysical schemes, and vertical and horizontal resolution in the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing rations of all water phases (vapor, liquid and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes and with surface processes. For idealized hurricanes, an axisymmetric version of the GCE model was developed and used to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was use to simulate squall lines that developed in the western Pacific, South China Sea, eastern Atlantic, South America and central U.S. FOr the cloud ensemble, the GCE model was integrated for several days in order to have a good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolutio will be examined. This will be mainly achieved by performing sensitivity tests using various horizontal (from 1-to 5-km) and vertical resolutions (from 20- to 200-m in the lower troposphere to 200- to 500m in the middle and upper troposphere). Sensitivity test using various microphysical schemes (warm rain only, and three ice with either graupel or hail) will also be performed. The thermodynamic and water budget associated with various types of precipitation systems will also be evaluated. The budgets will be calculated for different regions (i.e., convective and stratiform regions).

Tao, Wei-Kuo↗

NASA NTRS2003

Precipitation Processes developed during ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999), Consistent 2D, semi-3D and 3D Cloud Resolving Model Simulations

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique (i.e. is 2D or semi-3D CRM appropriate for the super-parameterization?); (2) calculate and examine the surface energy (especially radiation) and water budgets; (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

Tao, Wei-Kuo↗

NASA NTRS2003

Simulated Radar Characteristics of LBA Convective Systems: Easterly and Westerly Regimes

The 3D Goddard Cumulus Ensemble (GCE) model was used to simulate convection that occurred during the TRMM LBA field experiment in Brazil. Convection in this region can be categorized into two different regimes. Low-level easterly flow results in moderate to high CAPE and a drier environment. Convection is more intense like that seen over continents. Low-level westerly flow results in low CAPE and a moist environment. Convection is weaker and more widespread characteristic of oceanic or monsoon-like systems. The GCE model has been used to study both regimes n order to provide cloud datasets that are representative of both environments in support of TRMM rainfall and heating algorithm development. Two different cases are analyzed: Jan 26, 1999, an eastely regime case, and Feb 23, 1999, a westerly regime case. The Jan 26 case is an organized squall line, while the Feb 23 case is less organized with only transient lines. Radar signatures, including CFADs, from the two simulated cases are compared to each other and with observations. The microphysical processes simulated in the model are also compared between the two cases.

Lang, Stephen E.↗

NASA NTRS2003

Cloud-Resolving Model and GPM

Over the past twenty years, rainfall retrieval algorithms have been developed to retrieve rainfall and vertical hydrometeor structures from passive microwave observations by making use of the fact that weighting functions for various frequencies peak at different levels within a rainy atmosphere. GPROF is one of two TMI rainfall algorithms. It is physically based retrieval that finds the vertical hydrometeor profile that best fits the brightness temperatures in the available passive radiometer channels. Matching is achieved using a library of hydrometeor profiles generated by cloud-resolving models (CRMs). The hydrometeor profiles have a corresponding surface precipitation rate. The algorithm retrieves the hydrometeor profiles and associated surface rainfall using a Bayesian approach that gives the estimated expected values. The ability of CRMs to produce cloud structures that are reliable and representative of observed storms is crucial for the success of GPROF. The cloud mycrophysics are one of the keys to achieving this. In addition, CRMs have been a very useful tool for GPM-algorithm developers through Cloud-Radiation Simulations (CRS), one of the nine GPM disciplinary research themes. This paper will discuss how to generate consistent and comprehensive 4D cloud datasets from an improved (i.e., in regard to bulk and multi-moment microphysics) CRM for TRMM and GPM rainfall retrieval algorithm developers. These cloud datasets include CRM-simulated clouds and cloud systems from different geographic locations in the tropics and midlatitudes. By linking the CRM with a passive microwave radiative-transfer model and using satellite and airborne data, the performance of the "cloud physics" can be assessed and in turn modified and improved. This paper will also address how to assess and improve the performance of various latent and diabatic heating algorithms and develop an algorithm to retrieve the vertical structure of apparent moistening (Q2). Considering that the GPM will produce high (temporal and spatial) resolution heating and rainfall data, these algorithms will be used to obtain the temporal and spatial distributions of surface rainfall and the associated vertical heating and moistening profiles throughout the subtropical and midlatitudes.

Tao, Wei-Kuo↗