Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. 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 tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

A two-dimensional cloud-resolving model is used to study the sensitivities of two microphysical schemes, a bulk scheme and an explicit spectral bin scheme, in simulating a midlatitude summertime squall line [Preliminary Regional Experiment for Storm-Scale Operational and Research Meteorology (PRE-STORM), 10-11 June 1985]. In this first part of a two-part paper, the developing and mature stages of simulated storms are compared in detail. Some variables observed during the field campaign are also presented for validation. It is found that both schemes agree well with each other, and also with published observations and retrievals, in terms of storm structures and evolution, average storm flow patterns, pressure and temperature perturbations, and total heating profiles. The bin scheme is able to produce a much more extensive and homogeneous stratiform region, which compares better with observations.However, instantaneous fields and high temporal resolution analyses show distinct characteristics in the two simulations. During the mature stage, the bulk simulation produces a multicell storm with convective cells embedded in its stratiform region. Its leading convection also shows a distinct life cycle (strong evolution). In contrast, the bin simulation produces a unicell storm with little temporal variation in its leading cell regeneration (weak evolution). More detailed, high-resolution observations are needed to validate and, perhaps, generalize these model results. Interactions between the cloud microphysics and storm dynamics that produce the sensitivities described here are discussed in detail in Part II of this paper.

Part I of this paper compares two simulations, one using a bulk and the other a detailed bin microphysical scheme, of a long-lasting, continental mesoscale convective system with leading convection and trailing stratiform region. Diagnostic studies and sensitivity tests are carried out in Part II to explain the simulated contrasts in the spatial and temporal variations by the two microphysical schemes and to understand the interactions between cloud microphysics and storm dynamics. It is found that the fixed raindrop size distribution in the bulk scheme artificially enhances rain evaporation rate and produces a stronger near-surface cool pool compared with the bin simulation. In the bulk simulation, cool pool circulation dominates the near-surface environmental wind shear in contrast to the near-balance between cool pool and wind shear in the bin simulation. This is the main reason for the contrasting quasi-steady states simulated in Part I. Sensitivity tests also show that large amounts of fast-falling hail produced in the original bulk scheme not only result in a narrow trailing stratiform region but also act to further exacerbate the strong cool pool simulated in the bulk parameterization.An empirical formula for a correction factor, r(q(r)) = 0.11q(r)(-1.27) + 0.98, is developed to correct the overestimation of rain evaporation in the bulk model, where r is the ratio of the rain evaporation rate between the bulk and bin simulations and q(r)(g kg(-1)) is the rain mixing ratio. This formula offers a practical fix for the simple bulk scheme in rain evaporation parameterization.

Recent modeling studies have revealed that ice crystal number concentration is one of the dominant factors in the effect of clouds on radiation. Since the ice crystal enhancement factor and ice nuclei concentration determine the concentration, they are both important in quantifying the contribution of increased ice nuclei to global warming. In this study, long-term cloud-resolving model (CRM) simulations are compared with field observations to estimate the ice crystal enhancement factor in tropical and midlatitudinal clouds, respectively. It is found that the factor in tropical clouds is ~10 3-104 times larger than that of mid-latitudinal ones, which makes physical sense because entrainment and detrainment in the Tropics are much stronger than in middle latitudes. The effect of entrainment/detrainment on the enhancement factor, especially in tropical clouds, suggests that cloud microphysical parameterizations should be coupled with subgrid turbulence parameterizations within CRMs to obtain a more accurate depiction of cloud-radiative forcing.

An airflow trajectory analysis was carried out based on an idealized numerical simulation of the nocturnal 9 February 1993 equatorial oceanic squall line observed over the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) ship array. This simulation employed a nonhydrostatic numerical cloud model, which features a sophisticated 12-class bulk microphysics scheme. A second convective system that developed immediately south of the ship array a few hours later under similar environmental conditions was the subject of intensive airborne quad-Doppler radar observations, allowing observed airflow trajectories to be meaningfully compared to those from the model simulation. The results serve to refine the so-called hot tower hypothesis, which postulated the notion of undiluted ascent of boundary layer air to the high troposphere, which has for the first time been tested through coordinated comparisons with both model output and detailed observations.For parcels originating ahead ( north) of the system near or below cloud base in the boundary layer (BL), the model showed that a majority (>62%) of these trajectories were able to surmount the 10-km level in their lifetime, with about 5% exceeding 14-km altitude, which was near the modeled cloud top (15.5 km). These trajectories revealed that during ascent, most air parcels first experienced a quick decrease of equivalent potential temperature (theta(e)) below 5-km MSL as a result of entrainment of lower ambient theta(e) air. Above the freezing level, ascending parcels experienced an increase in theta(e) with height attributable to latent heat release from ice processes consistent with previous hypotheses. Analogous trajectories derived from the evolving observed airflow during the mature stage of the airborne radar-observed system identified far fewer (similar to 5%) near-BL parcels reaching heights above 10 km than shown by the corresponding simulation. This is attributed to both the idealized nature of the simulation and to the limitations inherent to the radar observations of near-surface convergence in the subcloud layer.This study shows that latent heat released above the freezing level can compensate for buoyancy reduction by mixing at lower levels, thus enabling air originating in the boundary layer to contribute to the maintenance of both local buoyancy and the large-scale Hadley cell despite acknowledged dilution by mixing along updraft trajectories. A tropical "hot tower'' should thus be redefined as any deep convective cloud with a base in the boundary layer and reaching near the upper-tropospheric outflow layer.

The Tropical Rainfall Measuring Mission-based National Aeronautics and Space Administration Goddard Multisatellite Precipitation Analysis (MPA) product is used to quantify the rainfall distribution in tropical cyclones that made landfall in the United States during 1998-2004. A total of 37 tropical cyclones (TC) are examined, including 2680 three-hourly MPA precipitation observations. Rainfall distributions for overland and overocean observations are compared. It is found that the TC rainfall over ocean bears a strong relationship with the TC maximum wind, whereas the relationship for overland conditions is much weaker. The rainfall potential is defined by using the satellite-derived rain rate, the satellite-derived storm size, and the storm translation speed. This study examines the capability of the overocean rainfall potential to predict a storm's likelihood of producing heavy rain over land. High correlations between rain potentials before landfall and the maximum storm total rain over land are found using the dataset of the 37 landfalling TCs. Correlations are higher with the average rain potential on the day prior to landfall than with averages over any other time period. A TC overland rainfall index is introduced based on the rainfall potential study. This index can be used to predict the storm peak rainfall accumulation over land. Six landfalling storms during the 2005 Atlantic Ocean hurricane season are examined to verify the capability of using this index to forecast the maximum storm total rain over land in the United States. The range of the maximum storm overland rain forecast error for these six storms is between 2.5% and 24.8%.

A three-dimensional cloud-resolving model (CRM) with observed large-scale forcing is used to study how ice nuclei (IN) affect the net radiative flux at the top of the atmosphere (TOA). In all the numerical experiments carried out, the cloud ice content in the upper troposphere increases with IN number concentration via the Bergeron process. As a result, the upward solar flux at the TOA increases whereas the infrared one decreases. Because of the opposite response of the two fluxes to IN concentration, the sensitivity of the net radiative flux at the TOA to IN concentration varies from one case to another. Six tropical and three midlatitudinal field campaigns provide data to model the effect of IN on radiation in different latitudes. Classifying the CRM simulations into tropical and midlatitudinal and then comparing the two types reveals that the indirect effect of IN on radiation is greater in the middle latitudes than in the tropics. Furthermore, comparisons between model results and observations suggest that observational IN data are necessary to evaluate long-term CRM simulations.

A multiscale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach for climate modeling. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The CRM allows for explicit simulation of cloud processes and their interactions with radiation and surface processes, and the GCM allows for global coverage.A new MMF has been developed that is based on the NASA Goddard Space Flight Center (GSFC) finite-volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using traditional cloud parameterizations. Both MMFs also produce a large and positive precipitation bias in the Indian Ocean and western Pacific during the Northern Hemisphere summer. However, there are also notable differences between the two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF simulates more global rainfall than its parent GCM because of the high contribution from the oceanic component. A number of critical issues (i.e., the CRM's physical processes and its configuration) involving the Goddard MMF are discussed in this paper.

Independent prognostic variables in cloud-resolving modeling are chosen on the basis of the analysis of microphysical timescales in clouds versus a time step for numerical integration. Two of them are the moist entropy and the total mixing ratio of airborne water with no contributions from precipitating particles. As a result, temperature can be diagnosed easily from those prognostic variables, and cloud microphysics be separated (or modularized) from moist thermodynamics. Numerical comparison experiments show that those prognostic variables can work well while a large time step (e.g., 10 s) is used for numerical integration.

Massively parallel computing, using a message passing interface (MPI), has been implemented into a three-dimensional version of the Goddard Cumulus Ensemble (GCE) model. The implementation uses the domainresemble concept to design a code structure for both the whole domain and sub-domains after decomposition. Instead of inserting a group of MPI related statements into the model routine, these statements are packed into a single routine. In other words, only a single call statement to the model code is utilized once in a place, thus there is minimal impact on the original code. Therefore, the model is easily modified and/or managed by the model developers and/or users, who have little knowledge of massively parallel computing.The model decomposition is highly flexible such that the entire model domain can be sliced into any number of partial domains in one- or twodimensional decomposition. Data exchange is through a halo-region, which is overlaid with neighboring partial domains. A halo-region is also known as a ghost-cell region. For reproducibility purposes, transposing data among tasks into different decompositions is required, such as Fourier transform and full domain summation.The well-behaved performance of the implemented codes with anelastic and compressible versions on three different computing platforms indicates a successful implementation.. The parallelization of both versions has speedup of 99% for up to 256 tasks. The anelastic version has better speedup and efficiency because its numerical algorithm is preferred by the parallelization than that of the compressible version.

Abstract The 3D Goddard Cumulus Ensemble model is used to simulate two convective events observed during the Tropical Rainfall Measuring Mission Large-Scale Biosphere–Atmosphere (TRMM LBA) experiment in Brazil. These two events epitomized the type of convective systems that formed in two distinctly different environments observed during TRMM LBA. The 26 January 1999 squall line formed within a sheared low-level easterly wind flow. On 23 February 1999, convection developed in weak low-level westerly flow, resulting in weakly organized, less intense convection. Initial simulations captured the basic organization and intensity of each event. However, improvements to the model resolution and microphysics produced better simulations as compared to observations. More realistic diurnal convective growth was achieved by lowering the horizontal grid spacing from 1000 to 250 m. This produced a gradual transition from shallow to deep convection that occurred over a span of hours as opposed to an abrupt appearance of...

The Goddard Cumulus Ensemble (GCE) model is used to examine the sensitivities of multiday 2D simulations of deep tropical convection to surface fluxes, interactive radiation, and ice microphysical processes. The simulations incorporate large-scale temperature, moisture, and momentum forcings, from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) for the period 19-27 December 1992.This study shows that, when surface fluxes are eliminated, the mean simulated atmosphere is much cooler and drier, convection and CAPE are much weaker, precipitation is less, and low-level to midlevel cloudiness is much greater. Surface fluxes using the TOGA COARE flux algorithm are weaker than with the aerodynamic formulation, but closer to the observed fluxes. In addition, trends similar to those noted above for the case without surface fluxes are produced for the TOGA COARE flux case, albeit to a much lesser extent. The elimination of shortwave and longwave radiation is found to have only minimal effects on the mean thermodynamics, convection, and precipitation. However, exclusion of radiation in the model does have a significant impact on cloud temperatures and structure above 200 mb.The removal of ice microphysical processes produces major changes in the structure of the clouds. Much of the liquid water is transported to the upper levels of the troposphere and evaporates, resulting in less mean total surface precipitation. The precipitation primarily occurs in regions of narrow, but intense, convective rainfall bands. The elimination of melting processes (diabatic cooling and conversions to rain) leads to greater (ice) hydrometeor mass below the 0 degrees C level and reduced latent cooling. This, along with weaker vertical cloud mass fluxes, produces a much warmer and moister boundary layer, and a greater mean CAPE. Finally, the elimination of the graupel species has only a small impact on mean total precipitation, thermodynamics, and dynamics of the simulation, but does produce much greater snow mass just above the melting layer.

Abstract Two 20-day, continental midlatitude cases are simulated with a three-dimensional (3D) cloud-resolving model (CRM) and are compared to Atmospheric Radiation Measurement Program (ARM) data. Surface fluxes from ARM ground stations and a land data assimilation system are used to drive the CRM. This modeling evaluation shows that the model simulates precipitation well but overpredicts clouds, especially in the upper troposphere. The evaluation also shows that the ARM surface fluxes can have noticeable errors in summertime. Theoretical analysis reveals that buoyancy damping is sensitive to spatial smoothers in two-dimensional (2D) CRMs, but not in 3D ones. With this theoretical analysis and the ARM cloud observations as background, 2D and 3D simulations are compared, showing that the 2D CRM has not only rapid fluctuations in surface precipitation but also spurious dehumidification (or a decrease in cloud amount). The present study suggests that the rapid precipitation fluctuation and spurious dehumidif...

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.

An ideal and simple formulation is successfully derived that well represents a quasi-linear relationship found between the domain-averaged water vapor, Q (mm), and temperature, T (K), fields for the three tropical oceans (i.e., the Pacific, Atlantic and Indian Oceans) based on eleven GEOS-3 [Goddard Earth Observing System (EOS) Version-3] global re-analysis monthly products. A Q-T distribution analysis is also performed for the tropical and extra-tropical regions based on in-situ sounding data and numerical simulations [GEOS-3 and the Goddard Cumulus Ensemble (GCE) model]. A similar positively correlated Q-T distribution is found over the entire oceanic and tropical regions; however, Q increases faster with T for the former region. It is suspected that the tropical oceans may possess a moister boundary layer than the Tropics. The oceanic regime falls within the lower bound of the tropical regime embedded in a global, curvilinear Q-T relationship. A positive correlation is also found between T and sea surface temperature (SST); however, for one degree of increase in T , SST is found to increase 1.1 degrees for a warmer ocean, which is slightly less than an increase of 1.25 degrees for a colder ocean. This seemingly indicates that more (less) heat is needed for an open ocean to maintain an air mass above it with a same degree of temperature rise during a colder (warmer) season [or in a colder (warmer) region]. Q and SST are also found to be positively correlated. Relative humidity (RH) exhibits similar behaviors for oceanic and tropical regions. RH increases with increasing SST and T over oceans, while it increases with increasing T in the Tropics. RH, however, decreases with increasing temperature in the extratropics. It is suspected that the tropical and oceanic regions may possess a moister local boundary layer than the extratropics so that a faster moisture increase than a saturated moisture increase is favored for the former regions. T, Q , saturated water vapor, RH, and SST are also examined with regard to the warm and cold “seasons” over individual oceans. The Indian Ocean warm season dominates in each of the five quantities, while the Atlantic Ocean cold season has the lowest values in most categories. The higher values for the Indian Ocean may be due to its relatively high percentage of tropical coverage compared to the other two oceans. However, Q is found to increase faster for colder months from individual oceans, which differs from the general finding in the global Q-T relationship that Q increases slower for a colder climate. The modified relationship may be attributed to a possible seasonal (warm and cold) variability in boundary layer depth over oceans, or to the small sample size used in each individual oceanic group.

This paper addresses an equation for moist entropy in the framework of cloud-resolving models. After rewriting the energy equation with moist entropy in the place of temperature, an equation for moist entropy is obtained. The equation expresses the internal and external sources of moist entropy explicitly, providing a basis for the use of moist entropy as a prognostic variable in long-term cloud-resolving modeling. In addition, a precise formula for the surface flux of moist entropy from the underlying surface into the air above is derived.The equation for moist entropy is used to express the Neelin-Held model for the diagnosis of large-scale vertical velocity. After applying the model to a tropical oceanic atmosphere with mean annual soundings, the paper shows the sensitivity of large-scale vertical circulations to the radiative cooling rate and the surface flux of moist entropy, which demonstrates the necessity for a precise equation for moist entropy in the analysis and modeling of large-scale tropical circulations.

The Goddard Cumulus Ensemble (GCE) model is used to examine the sensitivities of surface fluxes, explicit radiation, and ice microphysical processes on multi-day simulations of deep tropical convection over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). The simulations incorporate large-scale advective temperature and moisture forcing, as well as large-scale momentum, that are updated every time step on a periodic lateral boundary grid. This study shows that when surface fluxes are eliminated, the mean atmosphere is much cooler and drier, convection and CAPE are much weaker, precipitation is less, and cloud coverage in stratiform regions much greater. Surface fluxes using the TOGA COARE flux algorithm are weaker than with the aerodynamic formulation, but closer to the observed fluxes. In addition, similar trends noted above for the case without surface fluxes are produced for the TOGA flux case, albeit to a much lesser extent. The elimination of explicit shortwave and longwave radiation is found to have only minimal effects on the mean thermodynamics, convection, and precipitation. However explicit radiation does have a significant impact on cloud temperatures and structure above 200 mb and on the overall mean vertical circulation. The removal of ice processes produces major changes in the structure of the cloud. Much of the liquid water is transported aloft and into anvils above the melting layer (600 mb), leaving narrow, but intense bands of rainfall in convective regions. The elimination of melting processes leads to greater hydrometeor mass below the melting layer, and produces a much warmer and moister boundary layer, leading to a greater mean CAPE. Finally, the elimination of the graupel species has only a small impact on mean total precipitation, thermodynamics, and dynamics of the simulation, but does produce much greater snow mass just above the melting layer. Some of these results differ from previous CRM studies of tropical systems, which is likely due to the type of simulated system, total time integration, and model setup.

A cloud-resolving model is used to study sensitivities of two different microphysical schemes, one is the bulk type, and the other is an explicit bin scheme, in simulating a mid-latitude squall line case (PRE-STORM, June 10-11, 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. The leading convective zone, the trailing stratiform region, the horizontal wind flow patterns, pressure perturbation associated with the storm dynamics, and the cool pool in front of the system all agree well with the observations. Both the observations and the 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. 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 are remnants of the previous stronger convections at the leading edge of the system. The bin simulation, on the other hand, has a horizontally homogeneous stratiform cloud structure, which agrees better with the observations. Preliminary 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 convective zone simulated in the bulk model. Further quantitative analysis and sensitivity tests for this case using both the bulk and bin models will be presented in a companion paper.