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NASA NTRS2003

Precipitation Processes Developed During ARM (1997), TOGA COARE (1992) GATE (1974), SCSMEX (1998), and KWAJEX (1999): Consistent 3D, 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) have been used to study the response of clouds to large-scale forcing. IN these 3D simulators, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical clouds systems with large horizontal domains at the National Center of Atmospheric Research (NCAR) and at NASA Goddard Space Center. At Goddard, a 3D cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE, GATE, SCSMEX, ARM, and KWAJEX using a 512 by 512 km domain (with 2-km resolution). The result indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D GCE model simulation. The major objective of this paper are: (1) to assess the performance of the super-parametrization technique, (2) calculate and examine the surface energy (especially radiation) and water budget, and (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

Tao, W.-K.↗
NASA NTRS1980

Deep convection on day 261 of GATE

The structural features of the deep convection observed on September 18, 1974, day 261 of the GARP Atlantic Tropical Experiment (GATE), as the ridge axis of a 700 mb wave passed the center of the GATE B-scale network are reported. Satellite and aircraft maps indicate the presence of clouds penetrating above 2.5 km into the middle troposphere organized in bands about 9 km apart and aligned roughly along the direction of the wind shear in the cloud layer. Radar echoes corresponding to cumulus convection of lifetime, peak height and peak rainfall rates on the orders of 30 min, 6 km and 1.3 mm/h, respectively, were observed to triple in number density as convergence at 950 hPa increased from 1.5 to 3 x 10 to the -5th/sec. The structural features of the radar echoes indicate that the day was similar to a mesoscale precipitation feature of Leary and Houe (1979), with the cluster consisting of many echoes appearing in succession. Data from aircraft penetrations of the deep convection reveal downdrafts accompanying the precipitation and updrafts immediately to their south. Shipboard and rawinsonde observations show that the convective downdrafts brought down air of low pseudo-equivalent potential temperature, with local surface convergence of up to 0.001/sec. Mean wind shears through the cloud layer to the top of a main cloud layer are found to be only 75% greater than those of Malkus (1958) for the Caribbean, with shears just above the cloud base several factors larger.

Warner, C.↗
NASA NTRS2011

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/ WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June July August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

Teixeira, J.↗
NASA NTRS2020

A New Look at the Environmental Conditions Favorable to Secondary Ice Production

This study attempts a new identification of mechanisms of secondary ice production (SIP) based on the observation of small faceted ice crystals (hexagonal plates or columns) with typical sizes smaller than 100µm. Due to their young age, such small ice crystals can be used as tracers for identifying the conditions for SIP. Observations reported here were conducted in oceanic tropical mesoscale convective systems (MCSs) and midlatitude frontal clouds in the temperature range from 0 to −15◦C and heavily seeded by aged ice particles. It was found that in both MCSs and frontal clouds, SIP was observed right above the melting layer and extended to higher altitudes with colder temperatures. The roles of six possible mechanisms to generate the SIP particles are assessed using additional observations. In most observed SIP cases, small secondary ice particles spatially correlated with liquid-phase, vertical updrafts and aged rimed ice particles. However, in many cases, neither graupel nor liquid drops were observed in the SIP regions, and therefore, the conditions for an active Hallett–Mossop process were not met. In many cases, large concentrations of small pristine ice particles were observed right above the melting layer, starting at temperatures as warm as −0.5◦C. It is proposed that the initiation of SIP above the melting layer is stimulated by the recirculation of large liquid drops through the melting layer with convective turbulent updrafts. After re-entering a super cooled environment above the melting layer, they impact with aged ice, freeze, and shatter. The size of the splinters generated during SIP was estimated as 10µm or less. A principal conclusion of this work is that only the freezing drop-shattering mechanism could be clearly supported by the airborne in situ observations.

Korolev, Alexei↗
NASA NTRS1987

Parametric representation of heat and moisture fluxes in cloud-topped mixed layers

The Betts (1973, 1978) parametrization of heat and moisture fluxes is tested using measurements made in thin, broken, and solid stratocumulus clouds by the NCAR Electra off the California coast in June 1976. The turbulence data are used to determine updraft-downdraft properties, heat and moisture fluxes, spectra, and cospectra. From the convective properties, vertical mass flux profiles are obtained and examined for consistency. A convective scaling which is appropriate for cloud-topped mixed layers is discussed. The results demonstrate the usefulness of a mass flux formulation in modeling applications for cloud conditions varying between solid and broken.

Penc, Richard S.↗
NASA NTRS1993

The seasonal cycle of low stratiform clouds

The seasonal cycle of low stratiform clouds is studied using data from surface-based cloud climatologies. The impact of low clouds on the radiation budget is illustrated by comparison of data from the Earth Radiation Budget Experiment with the cloud climatologies. Ten regions of active stratocumulus convection are identified. These regions fall into four categories: subtropical marine, midlatitude marine, Arctic stratus, and Chinese stratus. With the exception of the Chinese region, all the regions with high amounts of stratus clouds are over the oceans. In all regions except the Arctic, the season of maximum stratus corresponds to the season of greatest lower-troposphere static stability. Interannual variations in stratus cloud amount also are related to changes in static stability. A linear analysis indicates that a 6 percent increase in stratus fractional area coverage is associated with each 1 C increase in static stability. Over midlatitude oceans, sky-obscuring fog is a large component of the summertime stratus amount. The amount of fog appears to be related to warm advection across sharp gradients of SST.

Klein, Stephen A.↗
NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS2005

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial-lkm scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard wlll be is presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS1986

Forecasting sea breeze thunderstorms at the Kennedy Space Center using the Prognostic Three-Dimensional Mesoscale Model (P 3DM)

A Prognostic Three-Dimensional Model (P3DM) to produce 1- to 12-hr predictions of sea breeze convective (SBC) storms at KSC is described. The P3DM was developed to account for a scale of about 10 km, interactions between surface heat and moisture fluxes, boundary layer convergence, the movement of moisture into cloud formation zones, and alterations in the convective potential in the lower levels of the atmosphere during the diurnal cycle. Initialized with wind, temperature, specific humidity and local water temperature data, the model allows for the distortion of the boundary layer moisture and thermal fields by sea breeze conditions. The results of three simulations of events leading to the onset of SBC storms are presented to demonstrate the model's capabilities, and techniques which may enhance the accuracy of the predictions are discussed.

Lyons, Walter A.↗
NASA NTRS2002

Convective Systems during the South China Sea Monsoon Onset and Post-Onset Simulated by a Cloud Resolving Model Using SCSMEX Data

South China Sea Monsoon Experiment (SCSMEX, 1998), one of several major TRMM field experiments, has successfully obtained a wealth of information and observational data on the summer monsoon onset and evolution in the South China Sea region. The primary goal of the experiment is to provide a better understanding of the key physical processes for the onset and maintenance of the monsoon over Southeast Asia and southern China leading to improved predictions. In this paper, our objective is to investigate the major physical and microphysical processes involved in the convective systems that developed during the onset and post-onset of the South China Sea monsoon - for both the similarities and differences between these two phases. There are two episodes simulated in this study, one of the onset period (May 18-26, 1998) and one of the post-onset period (June 2-11, 1998). The focus of this paper is to study four major aspects between these two different episodes. First, characteristics of rainfall such as rainfall amount and occurrence in the convective and stratiform regions are investigated, as well as the propagation of convective systems. The numerical precipitation fields are also validated against both the TRMM Microwave Imager (TMI) soundings and Precipitation Radar (PR) observations. Second, the domain-averaged heat and moisture budgets are analyzed to comprehend the essential roles played by physical processes such as the large-scale forcing and latent heat flux. Third, the microphysical processes associated with warm rain or ice are also closely examined during these two episodes. Finally, vertical distributions of Q1 and Q2 budgets are presented to perform a detailed discussion on the energy and moisture cascade in the vertical direction.

Shie, C.-L.↗
NASA NTRSDate not supplied

Exploring Environmental and Aerosol Impacts on Maritime Tropical Convection using Airborne Radiometer, Radar, Lidar, and Dropsondes

The field deployment phase of NASA’s Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) took place around the Philippines during August–October 2019, with the primary goal of jointly investigating aerosols and tropical meteorology at the micro-β to meso-β scales. A suite of instruments was deployed on NASA’s P-3B Orion aircraft to accomplish this mission, including: the Advanced Microwave Precipitation Radiometer (AMPR), Airborne Precipitation and cloud Radar 3rd Generation (APR-3), High Spectral Resolution Lidar 2 (HSRL2), and Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes. To examine potential aerosol influences on maritime tropical convection, P-3 flight segments throughout CAMP2Ex were binned into similar environmental groups using “low,” “medium,” and “high” values of nine AVAPS-derived parameters with known physical connections to convective frequency and/or intensity. Aerosol concentrations in each flight segment were evaluated using three HSRL2 variables at 355 and 532 nm: aerosol backscatter, aerosol extinction, and aerosol optical thickness. A set of radiometer- and radar-derived variables directly related to convective frequency and/or intensity was used to characterize convection, which included: AMPR-derived integrated cloud liquid water; polarization-corrected temperatures at 10.7, 19.35, 37.1, and 85.5 GHz; peak equivalent radar reflectivity factor (ZH); peak height of 30-dBZ ZH; and the number of radar data columns with composite ZH > 30 dBZ. The ZH analyses were performed using both Ku- and Ka-band APR-3 data. For each flight segment, correlation coefficients were calculated between each convective parameter and aerosol concentrations within the “low,” “medium,” and “high” groups for each environmental variable. The environmental stratification thresholds were then varied in a series of sensitivity tests. Several noteworthy correlations were observed between the convective and aerosol parameters within the environmental groups, especially when stratifying the environments based on their 850–500-hPa temperature lapse rate, 700–500-hPa temperature lapse rate, and K-Index. The convective parameters were often correlated most strongly with 355-nm extinction, 532-nm extinction, and 532-nm backscatter, while the presence of precipitation-sized liquid and ice hydrometeors contributed to some unexpected negative correlations. In general, as environmental conditions became more favorable for convection, a stronger correlation was observed between the convective parameters and aerosol concentrations. However, a “Goldilocks” zone of medium aerosol concentration was correlated most strongly with the convective parameters in many cases. These results stress the importance of considering environmental and aerosol conditions together when evaluating their impacts on convection. This presentation will provide a detailed discussion of these results and their implications, a summary of the limitations associated with such an analysis, and suggestions for future work.

Corey G. Amiot↗
NASA NTRS1995

Comparison of simulated cloud cover with satellite obsrvations over the Western United States

Satellite imagery datasets and regional climate model results are intercompared for evaluation of model accuracy in the simulation of cloud cover. Both monthly average individual simulation times are analyzed. To provide a consistent comparison, satellite data are first mapped into the model's geographic projection, grid domain, and resolution. It is found that September 1988 monthly average cloud fraction results from the modeled simulations correspond to observations, in both spatial pattern and magnitude, with bias less than +/- 20% cloud fraction over the entire inland West. Agreement in the pattern of cloud fraction also is evident for monthly average cloud fraction in July, but there is no negative bias of 10%-30% cloud fraction in the model diagnosis of cloud cover. Correlations between the spatial distributions of model-derived and observed cloud fractions are found to exceed 0.80 for certain geographic regions of the West, and these correlations are largest over mountainous areas during summer. Case studies of a series of daily cloud cover demonstrate the ability of the model to simulate the effects of frontal passage on cloud distribution. The ability of the RegCM1 to simulate daily cloud fraction and diurnal cloud evolution is somewhat weak for the summer convective season. It is anticipated that a more recent version of the regional climate model may improve the simulation of summer season cloud cover, through changes in cloud parameterization and improvements in model resolution.

Wetzel, Melanie A.↗
NASA NTRS1990

A comparison of cloud radiation fields obtained by in-situ aircraft measurements and a numerical simulation of a tropical mesoscale convective system

The radiation budget of a tropical mesoscale convective system (MCS) is investigated by comparing in situ aircraft measurements obtained in a tropical MCS during the Equatorial Mesoscale Experiment (EMEX), and coordinated aircraft radiation measurements, with radiation profiles calculated using cloud properties obtained from a cloud model simulation of a tropical MCS. Preliminary results indicate that the stratiform region of the tropical System B simulation represents the gross properties of the observed stratiform system between 4.5 to 15 km. The flux profiles predicted by the model are consistent with observed fluxes.

Wong, Takmeng↗
NASA NTRS1993

CAPE for CaPE

In an effort to improve short-term forecasting for the Kennedy Space Center region, Holle et al. (1992) investigated the effects of low level wind regimes on the distribution of cloud-to-ground lightning in central Florida. With a study period of 455 days, Holle et al. (1992) found 'southwest flow contributed 66 percent of the total network flashes while also occurring on the most days (142).' Relationships among mesoscale thermodynamic variables and precipitation and/or lightning have been addressed in previous studies in Canada and the Tennessee valley. Zawadzki et al. (1981) found 'soundings, surface pressure, temperature and humidity obtained from a standard observation network were correlated with rain rates given by raingages and radar.' Buechler et al. (1990) found 'a fair relationship between CAPE (convective available potential energy) and daily cloud-to-ground activity' with a correlation coefficient of r = 0.68. The present research will investigate the relationships among rainfall, cloud-to-ground (CG) lightning, CAPE, and low level wind flow using data collected during the CaPE (Convection and Precipitation/Electrification Experiment) field program. The CaPE field program was conducted in east central Florida from July 8, 1991 to August 18, 1991.

Brooks, Joni↗