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NASA NTRS1985

Results from a limited area mesoscale numerical simulation for 10 April 1979

Results are presented from a nine-hour limited area fine mesh (35-km) mesoscale model simulation initialized with SESAME-AVE I radiosonde data for Apr. 10, 1979 at 2100 GMT. Emphasis is on the diagnosis of mesoscale structure in the mass and precipitation fields. Along the Texas/Oklahoma border, independent of the short wave, convective precipitation formed several hours into the simulation and was organized into a narrow band suggestive of the observed April 10 squall line.

Kalb, M. W.↗
NASA NTRS2008

Cloud-System Resolving Models: Status and Prospects

Cloud-system resolving models (CRM), which are based on the nonhydrostatic equations of motion and typically have a grid-spacing of about a kilometer, originated as cloud-process models in the 1970s. This paper reviews the status and prospects of CRMs across a wide range of issues, such as microphysics and precipitation; interaction between clouds and radiation; and the effects of boundary-layer and surface-processes on cloud systems. Since CRMs resolve organized convection, tropical waves and the large-scale circulation, there is the prospect for several advances in both basic knowledge of scale-interaction requisite to parameterizing mesoscale processes in climate models. In superparameterization, CRMs represent convection, explicitly replacing many of the assumptions necessary in contemporary parameterization. Global CRMs have been run on an experimental basis, giving prospect to a new generation of climate weather prediction in a decade, and climate models due course. CRMs play a major role in the retrieval of surface-rain and latent heating from satellite measurements. Finally, enormous wide dynamic ranges of CRM simulations present new challenges for model validation against observations.

Tao, Wei-Kuo↗
NASA NTRS1983

Some potential research applications of GOES/VAS data in meteorology

The understanding and utilization of radiance data from the VAS instrument for meteorological purposes which requires an extensive and organized research plan whose ultimate goal is to provide quantitative measurements of the structure/dynamics of the atmosphere is outlined. The unique multispectral VAS data are potentially useful in almost all aspects of meteorology but have immediate applications in the mesoscale and severe storm research area since measurements are available over regional areas at time intervals of less than 1 hour. The higher priority research applications of VAS data pertaining to the interpretation and utilization of the passive VAS radiance measurements for mesoscale and severe-storm research are reviewed.

Wilson, G. S.↗
NASA NTRS2014

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

GEOS-5↗
NASA NTRS2014

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Case. Jonathan↗
NASA NTRS1999

Radar Observations of Convective Systems from a High-Altitude Aircraft

Reflectivity data collected by the precipitation radar on board the tropical Rainfall Measuring Mission (TRMM) satellite, orbiting at 350 km altitude, are compared to reflectivity data collected nearly simultaneously by a doppler radar aboard the NASA ER-2 flying at 19-20 km altitude, i.e. above even the deepest convection. The TRMM precipitation radar is a scanning device with a ground swath width of 215 km, and has a resolution of about a4.4 km in the horizontal and 250 m in the vertical (125 m in the core swath 48 km wide). The TRMM radar has a wavelength of 217 cm (13.8 GHz) and the Nadir mirror echo below the surface is used to correct reflectivity for loss by attenuation. The ER-2 Doppler radar (EDOP) has two antennas, one pointing to the nadir, 34 degrees forward. The forward pointing beam receives both the normal and the cross-polarized echos, so the linear polarization ratio field can be monitored. EDOP has a wavelength of 3.12 cm (9.6 GHz), a vertical resolution of 37.5 m and a horizontal along-track resolution of about 100 m. The 2-D along track airflow field can be synthesized from the radial velocities of both beams, if a reflectivity-based hydrometer fall speed relation can be assumed. It is primarily the superb vertical resolution that distinguishes EDOP from other ground-based or airborne radars. Two experiments were conducted during 1998 into validate TRMM reflectivity data over convection and convectively-generated stratiform precipitation regions. The Teflun-A (TEXAS-Florida Underflight) experiment, was conducted in April and May and focused on mesoscale convective systems mainly in southeast Texas. TEFLUN-B was conducted in August-September in central Florida, in coordination with CAMEX-3 (Convection and Moisture Experiment). The latter was focused on hurricanes, especially during landfall, whereas TEFLUN-B concentrated on central; Florida convection, which is largely driven and organized by surface heating and ensuing sea breeze circulations. Both TEFLUN-A and B were amply supported by surface data, in particular a dense raingauge network, a polarization radar, wind profilers, a mobile radiosonde system, a cloud physics aircraft penetrating the overflown storms, and a network of 10 cm Doppler radars(WSR-88D). This presentation will show some preliminary comparisons between TRMM, EDOP, and WSR-88D reflectivity fields in the case of an MCS, a hurricane, and less organized convection in central Florida. A validation of TRMM reflectivity is important, because TRMM's primary objective is to estimate the rainfall climatology with 35 degrees of the equator. Rainfall is estimated from the radar reflectivity, as well from TRMM's Microwave Imager, which measures at 10.7, 19.4, 21.3, 37, and 85.5 GHz over a broader swath (78 km). While the experiments lasted about three months the cumulative period of near simultaneous observations of storms by ground-based, airborne and space borne radars is only about an hour long. Therefore the comparison is case-study-based, not climatological. We will highlight fundamental differences in the typical reflectivity profiles in stratiform regions of MCS's, Florida convection and hurricanes and will explain why Z-R relationships based on ground-based radar data for convective systems over land should be different from those for hurricanes. These catastrophically intense rainfall from hurricane Georges in Hispaniola and from Mitch in Honduras highlights the importance of accurate Z-R relationships, It will be shown that a Z-R relationship that uses the entire reflectivity profile (rather than just a 1 level) works much better in a variety of cases, making an adjustment of the constants for different precipitation system categories redundant.

Heymsfield, G.↗
NASA NTRS1989

Moisture structure of tropical cloud systems as inferred from SSM/I

The structure of tropical cloud systems was examined using data obtained by the Special Sensor Microwave/Imager on vertically-integrated vapor, ice, and liquid water (including precipitable water) in a cloud cluster associated with a Pacific easterly wave. The cloud cluster provided a sample of the varying signatures of bulk microphysical processes in organized tropical convection. Composition techniques were used to interpret this variability and its significance in terms of the response of convection to its thermodynamic environment. The relative intensities of the ice and liquid-water signatures should provide insight on the relative contribution of stratiform vs convective rain and the characteristics of the water budgets of mesoscale convective systems.

Robertson, Franklin R.↗
NASA NTRS2015

High-Resolution NU-WRF Simulations of a Deep Convective-Precipitation System During MC3E: Comparisons Between Goddard Microphysics Schemes and Observations - Part 1

The Goddard microphysics scheme was recently improved by adding a 4th ice class (frozen dropshail). This new 4ICE scheme was implemented and tested in the Goddard Cumulus Ensemble model (GCE) for an intense continental squall line and a moderate,less-organized continental case. Simulated peak radar reflectivity profiles were improved both in intensity and shape for both cases as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified - Weather Research and Forecasting model (NU-WRF) and tested on an intense mesoscale convective system that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). The NU42WRF simulated radar reflectivities, rainfall intensities, and vertical and horizontal structure using the new 4ICE scheme agree as well as or significantly better with observations than when using previous versions of the Goddard 3ICE (graupel or hail) schemes. In the 4ICE scheme, the bin microphysics-based rain evaporation correction produces more erect convective cores, while modification of the unrealistic collection of ice by dry hail produces narrow and intense cores, allowing more slow-falling snow to be transported rearward. Together with a revised snow size mapping, the 4ICE scheme produces a more horizontally stratified trailing stratiform region with a broad, more coherent light rain area. In addition, the NU-WRF 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive open lateral boundaries

Regional Scale Model↗
NASA NTRS2017

GEOS Atmospheric Model: Challenges at Exascale

The Goddard Earth Observing System (GEOS) model at NASA's Global Modeling and Assimilation Office (GMAO) is used to simulate the multi-scale variability of the Earth's weather and climate, and is used primarily to assimilate conventional and satellite-based observations for weather forecasting and reanalysis. In addition, assimilations coupled to an ocean model are used for longer-term forecasting (e.g., El Nino) on seasonal to interannual times-scales. The GMAO's research activities, including system development, focus on numerous time and space scales, as detailed on the GMAO website, where they are tabbed under five major themes: Weather Analysis and Prediction; Seasonal-Decadal Analysis and Prediction; Reanalysis; Global Mesoscale Modeling, and Observing System Science. A brief description of the GEOS systems can also be found at the GMAO website. GEOS executes as a collection of earth system components connected through the Earth System Modeling Framework (ESMF). The ESMF layer is supplemented with the MAPL (Modeling, Analysis, and Prediction Layer) software toolkit developed at the GMAO, which facilitates the organization of the computational components into a hierarchical architecture. GEOS systems run in parallel using a horizontal decomposition of the Earth's sphere into processing elements (PEs). Communication between PEs is primarily through a message passing framework, using the message passing interface (MPI), and through explicit use of node-level shared memory access via the SHMEM (Symmetric Hierarchical Memory access) protocol. Production GEOS weather prediction systems currently run at 12.5-kilometer horizontal resolution with 72 vertical levels decomposed into PEs associated with 5,400 MPI processes. Research GEOS systems run at resolutions as fine as 1.5 kilometers globally using as many as 30,000 MPI processes. Looking forward, these systems can be expected to see a 2 times increase in horizontal resolution every two to three years, as well as less frequent increases in vertical resolution. Coupling these resolution changes with increases in complexity, the computational demands on the GEOS production and research systems should easily increase 100-fold over the next five years. Currently, our 12.5 kilometer weather prediction system narrowly meets the time-to-solution demands of a near-real-time production system. Work is now in progress to take advantage of a hybrid MPI-OpenMP parallelism strategy, in an attempt to achieve a modest two-fold speed-up to accommodate an immediate demand due to increased scientific complexity and an increase in vertical resolution. Pursuing demands that require a 10- to 100-fold increases or more, however, would require a detailed exploration of the computational profile of GEOS, as well as targeted solutions using more advanced high-performance computing technologies. Increased computing demands of 100-fold will be required within five years based on anticipated changes in the GEOS production systems, increases of 1000-fold can be anticipated over the next ten years.

ESMF↗
NASA NTRS2022

Atmospheric Research 2021 Technical Highlights

Welcome to the 2021 Atmospheres Highlights report. Here, we summarize research and scientific communication/outreach accomplishments from the portion of atmospheric science activities at NASA’s Goddard Space Flight Center (GSFC) that comprises the Earth Science Division’s Atmospheres organization. As in previous years, this report is intended for a broad audience, including colleagues within NASA, scientists outside the Agency, science graduate students, and members of the public. Organizationally, the report covers research activities under the Office of Deputy Director for Atmospheres (610AT), which is within Earth Sciences Division (Code 610) in the Sciences and Exploration Directorate (600). Laboratories and office within 610AT include: Mesoscale Atmospheric Processes Laboratory (612), Climate and Radiation Laboratory (613), Atmospheric Chemistry and Dynamics Laboratory (614), and the Wallops Field Support Office (610.W). As of this writing, the 266 personnel in Code 610AT consist of 53 civil servants and 213 cooperative agreement associates, postdoctoral fellows and contractors.

Annual Report↗
NASA NTRS2020

Linkage among Ice Crystal Microphysics, Mesoscale Dynamics and Cloud and Precipitation Structures Revealed By Collocated Microwave Radiometer and Multi-Frequency Radar Observations

Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth’s radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and orientation) are not only influenced by ambient environment’s dynamic and thermodynamic conditions, but also intimately connect to the cloud radiative effects and particle fall speeds, which therefore impact up to the future climate projection and down to the details of the surface precipitation (e.g., onset-time, location, type and strength). Our previous work revealed that high-frequency Polarimetric radiance Difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that are often occur inside anvil clouds and/or stratiform precipitations. In this current work, we further investigate the dynamic/thermodynamic mechanisms and cloud/precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM-DPR, Ku/Ka bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally-oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or super-cooled water. Further, high (low) PD scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers respectively, suggesting the potential usefulness of PD as a proxy of stratiform/convective precipitation flag, as well as a proxy of convection life stage.

Ice crystal microphysics↗
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 NTRS1990

Convective dynamics - Panel report

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

Carbone, Richard↗
NASA NTRS2017

Classification of Meteorological Influences Surrounding Extreme Precipitation Events in the United States using the MERRA-2 Reanalysis

Extreme precipitation events can have a large impact on society through flooding that can result in property destruction, crop losses, economic losses, the spread of water-borne diseases, and fatalities. Observations indicate there has been a statistically significant increase in extreme precipitation events over the past 15 years in the Northeastern United States and other localized regions of the country have become crippled with record flooding events, for example, the flooding that occurred in the Southeast United States associated with Hurricane Matthew in October 2016. Extreme precipitation events in the United States can be caused by various meteorological influences such as extratropical cyclones, tropical cyclones, mesoscale convective complexes, general air mass thunderstorms, upslope flow, fronts, and the North American Monsoon. Reanalyses, such as the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), have become a pivotal tool to study the meteorology surrounding extreme precipitation events. Using days classified as an extreme precipitation events based on a combination of observational gauge and radar data, two techniques for the classification of these events are used to gather additional information that can be used to determine how events have changed over time using atmospheric data from MERRA-2. The first is self organizing maps, which is an artificial neural network that uses unsupervised learning to cluster like patterns and the second is an automated detection technique that searches for characteristics in the atmosphere that define a meteorological phenomena. For example, the automated detection for tropical cycles searches for a defined area of suppressed sea level pressure, alongside thickness anomalies aloft, indicating the presence of a warm core. These techniques are employed for extreme precipitation events in preselected regions that were chosen based an analysis of the climatology of precipitation.

Monsoon↗
NASA NTRS2022

Atmospheric Research 2020 Technical Highlights

Welcome to the 2020 Atmospheres Highlights report. Here we summarize research and scientific communication/outreach accomplishments from the portion of atmospheric science activities at NASA’s Goddard Space Flight Center (GSFC) that comprises the Earth Science Division’s Atmospheres organization. As in previous years, this report is intended for a broad audience, including colleagues within NASA, scientists outside the Agency, science graduate students, and members of the public. Organizationally, the report covers research activities under the Office of Deputy Organizationally, the report covers research activities under the Office of Deputy Director for Atmospheres (610AT), which is within Earth Sciences Division (Code Director for Atmospheres (610AT), which is within Earth Sciences Division (Code 610) in the Sciences and Exploration Directorate (600). Laboratories and office within 610) in the Sciences and Exploration Directorate (600). Laboratories and office within 610AT include: Mesoscale Atmospheric Processes Laboratory (612), Climate and 610AT include: Mesoscale Atmospheric Processes Laboratory (612), Climate and Radiation Laboratory (613), Atmospheric Chemistry and Dynamics Laboratory (614), Radiation Laboratory (613), Atmospheric Chemistry and Dynamics Laboratory (614), and the Wallops Field Support Office (610.W). As of this writing, the 277 personnel and the Wallops Field Support Office (610.W). As of this writing, the 277 personnel in Code 610AT consist of 53 civil servants and 224 cooperative agreement associates, in Code 610AT consist of 53 civil servants and 224 cooperative agreement associates, postdoctoral fellows and contractors, postdoctoral fellows and contractors.

Annual Report↗
NASA NTRS2005

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) for which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities from National Lightning Detection Network (NLDN) data. The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at the two organizations provided this data and supporting software for the work performed by the AMU. The densities were first stratified by flow regime, then by time in 1-, 3-, 6-, 12-, and 24-hour increments while maintaining the 2.5 km x 2.5 km grid resolution. A CG frequency of occurrence was calculated for each stratification and grid box by counting the number of days with lightning and dividing by the total number of days in the data set. New CG strike densities were calculated for each stratification and grid box by summing the strike number values over all warm seasons, then normalized by dividing the summed values by the number of lightning days. This makes the densities conditional on whether lightning occurred. The frequency climatology values will be used by forecasters as proxy inputs for lightning prObability, while the density climatology values will be used for CG amount. In addition to the benefits outlined above, these climatologies will provide improved temporal and spatial resolution, expansion of the lightning threat area to include adjacent coastal waters, and potential to extend the forecast to include the day-2 period. This presentation will describe the lightning threat index map, discuss the work done to create the maps initialized with climatological guidance, and show examples of the climatological CG lightning densities and frequencies of occurren based on flow regime.

Lambert, Winnie↗
NASA NTRS2010

NASA Giovanni Tool for Visualization and Analysis Support for the YOTC Program

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been two folds: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. Because the goal of Overview of Year Of Tropical Convection (YOTC) involves examining a scientifically complex, multi-scale "process", rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 - April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO, and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO).

Ostrenga, Dana↗
NASA NTRS1982

Doppler-radar observation of the evolution of downdrafts in convective clouds

A detailed analysis of the 20 July 1977 thunderstorm complex which formed and evolve over the South Park region in Central Colorado is presented. The storm was extensively analyzed using multiple Doppler radar and surface mesonet data, developed within an environment having very weak wind shear. The storm owed its intensification to the strength of the downdraft, which was nearly coincident with the region where the cloud had grown. The noteworthy features of this storm were its motion to the right of the cloud-level winds, its multicellular nature and discrete propagation, its north-south orientation, and its relatively large storm size and high reflectivity factor (55 dBZ). This scenario accounts for the observed mesoscale and cloud-scale event. A line of convergence was generated at the interface between the easterly upslope winds and westerly winds. During stage II, the convergence line subsequently propagated down the slopes of the Mosquito Range, and was the main forcing mechanism for the development of updraft on the west flank of the storm. The formation of downdraft on the eastern side of updraft blacked surface inflow, and created a detectable gust front. As the original downdraft intensified, the accumulation of evaporatively-chilled air caused the intensification of the mesohigh, which likely destroyed the earlier convergence line and created a stronger convergence line to the east, which forced up-lifting of the moist, westerly inflow and caused the formation of updraft to the east. An organized downdraft circulation, apparently maintained by precipitation drag and evaporational cooling, was responsible in sustaining a well-defined gust front. The storm attained its highest intensity as a consequence of merging with a neighboring cloud. The interaction of downdrafts or gust fronts from two intense cells appeared to be the primary mechanism of this merging process as suggested by Simpson et al. (1980). The merging process coincided with more rain than occurred in unmerged echoes.

Motallebi, N.↗