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NASA NTRSDate not supplied

Hailstorm Analyses and Detection Derived from Current and Historical Satellite Data and Convective Environmental Parameters

We seek to demonstrate the extent to which hailstorms can be detected using a combination of geostationary (GEO) visible and infrared metrics of storm intensity and convective environmental parameters from reanalysis. Hailstorm identifications from low-Earth-orbiting (LEO) passive microwave sensors and maximum expected size of hail (MESH) from ground-based radar serve as a proxy for hail events. Data are analyzed for two warm seasons over the contiguous United States (CONUS). A neural network (NN) is trained to predict hailstorm detection dependent on optimal multi-variate weighting of observed and modeled input. The NN results are then applied to a 15-year Meteosat Second Generation climatology over South Africa to depict where hailstorms are most likely to occur. We also explore the impact of GEO imager resolution on our ability to discriminate hailstorms by matching GOES-13 (4 km) and GOES-16 (2 km) storm intensity metrics against hail characteristics using LEO, MESH, and spotter reports over CONUS during 2017, when both satellites were simultaneously imaging. Such analysis allows us to assess the feasibility of assembling a severe storm climate data record back to GOES-8, in the mid-1990’s. Finer spatial resolution of GOES-16 better resolves the updraft characteristics and intensities that are inherently linked to hail formation; however, GOES-13 can be normalized to achieve comparable detection capability. When intelligently combined with model-derived convective environmental parameters, GEO-derived storm intensity metrics enable high-spatial resolution hail risk assessment at hourly intervals throughout the diurnal cycle anywhere around the world and an improved understanding of hailstorms in the climate system.

Kyle F Itterly↗
NASA NTRS2017

Development of High-Resolution Dynamic Dust Source Function - A Case Study with a Strong Dust Storm in a Regional Model

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 0203 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

Dynamic dust source↗
NASA NTRS2001

A Cloud-Resolving Simulation of Hurricane Bob (1991): Storm Structure and Eyewall Buoyancy

A numerical simulation of Hurricane Bob (1991) is conducted using the Penn State University-National Center for Atmospheric Research mesoscale model MM5 with a horizontal grid spacing of 1.3 Km on the finest nested mesh The model produces a realistic hurricane that intensifies slowly during the period of fine-scale simulation. Time-averaged results reveal the effects of storm motion. vertical shear, beta gyres and deformation forcing on the structure of radial inflow, vertical motion, and precipitation. Instantaneous model fields show that radial inflow in the eyewall is very intense near the surface but transitions to strong low-level outflow near the top of the boundary layer. The low-level structure is modulated by a wavenumber 2 disturbance that rotates around the eyewall at half the speed of the maximum tangential winds and is consistent with a vortex Rossby edge wave. The statistical distribution of vertical velocity in the eyewall indicates that the eyewall is composed of a small number of intense updrafts that account for the majority of the upward mass flux rather than a more gradual and symmetric eyewall circulation, consistent with the concept of hot towers. Tongues of high equivalent potential temperature, Theta(sub e), are seen along the inner edge of the eyewall updraft and within the low-level outflow. This air originates from outside of the eyewall with the highest theta(sub e) air coming from the layer closest to the surface after penetrating closest to the center. Occasionally, high Theta(sub e), air within the eye is drawn into the eyewall updrafts. The high Theta(sub e), air rising within the eyewall is shown to be associated with positive eyewall buoyancy with sufficient convective available potential energy along its path to produce relatively strong convective updrafts. Although the requirements for conditional symmetric instability are met within the eyewall and the air parcel trajectories follow slanted paths, the radial displacement of air parcels in the low-level outflow moves the air parcel sufficiently far away from the upper- warm core that the air becomes unstable to vertical displacements. Hence, convective instability rather than symmetric instability accounts for the stronger updrafts in the eyewall.

Braun, Scott A.↗
NASA NTRS2002

Convective Systems Over the Japan Sea: Cloud-Resolving Model Simulations

Wintertime observations of MCSs (Mesoscale Convective Systems) over the Sea of Japan - 2001 (WMO-01) were collected from January 12 to February 1, 2001. One of the major objectives is to better understand and forecast snow systems and accompanying disturbances and the associated key physical processes involved in the formation and development of these disturbances. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, wind profilers, radiometers, etc.) during WMO-01 provided a first attempt at investigating the detailed characteristics of convective storms and air pattern changes associated with winter storms over the Sea of Japan region. WMO-01 also provided estimates of the apparent heat source (Q1) and apparent moisture sink (Q2). The vertical integrals of Q1 and Q2 are equal to the surface precipitation rates. The horizontal and vertical adjective components of Q1 and Q2 can be used as large-scale forcing for the Cloud Resolving Models (CRMs). The Goddard Cumulus Ensemble (GCE) model is a CRM (typically run with a 1-km grid size). The GCE model has sophisticated microphysics and allows explicit interactions between clouds, radiation, and surface processes. It will be used to understand and quantify precipitation processes associated with wintertime convective systems over the Sea of Japan (using data collected during the WMO-01). This is the first cloud-resolving model used to simulate precipitation processes in this particular region. The GCE model-simulated WMO-01 results will also be compared to other GCE model-simulated weather systems that developed during other field campaigns (i.e., South China Sea, west Pacific warm pool region, eastern Atlantic region and central USA).

Tao, Wei-Kuo↗
NASA NTRSDate not supplied

Improving the Time Resolution of Hyper-Spectral Infrared Sounding Observations With Trajectory Enhancement

Low Earth orbit (LEO) hyper-spectral infrared (IR) sounders have significant potential for characterizing the complex evolution of thermodynamic environments favorable for convective initiation and ongoing convection. The snapshots at fixed local times are unable to provide the temporal resolution needed to resolve the rapidly evolving convective environment. A novel methodology using trajectory modeling coupled with satellite soundings was developed to create proximity soundings near NCEI Storm Events to investigate differences in severe weather environments (Kalmus et al., 2019, https://doi.org/10.1175/MWR-D-18-0055.1). This methodology was recently extended to entire satellite swaths forward in time up to six hours into the future and was evaluated during NOAA’s Hazardous Weather Testbed (HWT) in a quasi-operational setting (Kahn et al., 2023, https://doi.org/10.1175/WAF-D-22-0204.1). This methodology is based on parcel forward-trajectory calculations from the satellite observing time to recreate future soundings of temperature and moisture at regularly gridded intervals in space and time. Using coincident Multi-Radar Multi-Sensor (MRMS) rainfall estimates, we show that convective available potential energy (CAPE) is increased and convective inhibition (CIN) is decreased at times and locations where convection initiated. This methodology was evaluated with ERA5 data sampled to mimic the satellite observing swaths (Richardson et al., 2023, https://doi.org/10.5194/egusphere-2023-97). Approximately 60–90% of the temporal and spatial variability in temperature and humidity is explained by parcel advection using trajectory modeling. This method will be applied to the multi-decadal LEO satellite record and could be used to examine capabilities of future satellite missions such as the GeoXO mission.

Emily Berndt↗
NASA NTRS2010

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Nigro, Joseph↗
NASA NTRS2008

The Sheath Transport Observer for the Redistribution of Mass (STORM) Image

All of the solar wind energy that powers magnetospheric processes passes through the magnetosheath and magnetopause. Global images of the magnetosheath and magnetopause boundary layers will resolve longstanding controversy surrounding fundamental phenomena that occur at the magnetopause and provide information needed to improve operational space weather models. Recent developments showing that soft X-rays (0.15-1 keV) result from high charge state solar wind ions undergoing charge exchange recombination through collisions with exospheric neutral atoms has led to the realization that soft X-ray imaging can provide global maps of the high-density shocked solar wind within the magnetosheath and cusps, regions lying between the lower density solar wind and magnetosphere. We discuss an instrument concept called the Sheath Transport Observer for the Redistribution of Mass (STORM), an X-ray imager suitable for simultaneously imaging the dayside magnetosheath, the magnetopause boundary layers, and the cusps.

Kuntz, Kip↗
NASA NTRS2010

The Sheath Transport Observer for the Redistribution of Mass (STORM) Imager

All of the solar wind energy that powers magnetospheric processes passes through the magnetosheath and magnetopause. Global images of the magnetosheath and magnetopause boundary layers will resolve longstanding controversies surrounding fundamental phenomena that occur at the magnetopause and provide information needed to improve operational space weather models. Recent developments showing that soft X-rays (0.15-1 keV) result from high charge state solar wind ions undergoing charge exchange recombination through collisions with exospheric neutral atoms has led to the realization that soft X-ray imaging can provide global maps of the high-density shocked solar wind within the magnetosheath and cusps, regions lying between the lower density solar wind and magnetosphere. We discuss an instrument concept called the Sheath Transport Observer for the Redistribution of Mass (STORM), an X-ray imager suitable for simultaneously imaging the dayside magnetosheath, the magnetopause boundary layers, and the cusps.

Collier, Michael R.↗
NASA NTRS2002

Convective Systems Over the South China Sea: Cloud-Resolving Model Simulations

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convective storms and air pattern changes associated with monsoons over the South China Sea region. SCSMEX also provided rainfall estimates which allows for comparisons with those obtained from the Tropical Rainfall Measuring Mission (TRMM), a low earth orbit satellite designed to measure rainfall from space. The Goddard Cumulus Ensemble (GCE) model (with 1-km grid size) is used to understand and quantify the precipitation processes associated with the summer monsoon over the South China Sea. This is the first (loud-resolving model used to simulate precipitation processes in this particular region. The GCE-model results captured many of the observed precipitation characteristics because it used a fine grid size. For example, the temporal variation of the simulated rainfall compares quite well to the sounding-estimated rainfall variation. The time and domain-averaged temperature (heating/cooling) and water vapor (drying/ moistening) budgets are in good agreement with observations. The GCE-model-simulated rainfall amount also agrees well with TRMM rainfall data. The results show there is more evaporation from the ocean surface prior to the onset of the monsoon than after the on-~et of monsoon when rainfall increases. Forcing due to net radiation (solar heating minus longwave cooling) is responsible for about 25% of the precipitation in SCSMEX The transfer of heat from the ocean into the atmosphere does not contribute significantly to the rainfall in SCSMEX. Model sensitivity tests indicated that total rain production is reduced 17-18% in runs neglecting the ice phase. The SCSMEX results are compared to other GCE-model-simulated weather systems that developed during other field campaigns (i.e., west Pacific warm pool region, eastern Atlantic region and central USA). Large-scale forcing vie temperature and water vapor tendency, is the major energy source for net condensation in the tropical cases. The effects of large-scale cooling exceed that of large-scale moistening in the west pacific warm pool region and eastern Atlantic region. For SCSMEX, however, the effects of large-scale moistening predominate. Net radiation and sensible and latent hc,it fluxes play a much more important role in the central USA.

Tao, Wei-Kuo↗
NASA NTRS2002

Simulation of the Climate of South-West Asia with a Regional Model

The ability of the regional model RegCM2 to simulate the climate of South-West Asia is examined. The climate of the region displays high spatial, seasonal and interannual variability, providing a strong test of climate model capabilities. RegCM2 captures the spatial variability of temperature and precipitation despite cold biases being present in the model. RegCM2 does not capture the annual cycle of precipitation on the Black and Caspian Sea coasts where very steep topography exists, nor on the eastern Mediterranean coast where the coastal mountains are not resolvable. RegCM2 does capture the seasonal cycle in the Fertile Crescent and Zagros mountains, where it is strongly influenced by a plateau circulation above the Iranian plateau. It is shown that accurate simulation of precipitation in these regions, including the inter-annual variability, requires the correct simulation of both storm tracks and topographic interactions. Through the use of regional climate models the concentration and transport pathways of water vapor through the Middle East can be explored. The results demonstrate that short lived 'events' have little impact on monthly mean atmospheric fields yet provide a significant amount of the precipitated water which flows in the Tigris river.

Evans, J. P.↗
NASA NTRS2015

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

Lightning observations are collected using ground-based and satellite-based sensors. The National Lightning Detection Network (NLDN) in the United States uses multiple ground sensors to triangulate the electromagnetic signals created when lightning strikes the Earth's surface. Satellite-based lightning observations have been made from 1998 to present using the Lightning Imaging Sensor (LIS) on the NASA Tropical Rainfall Measuring Mission (TRMM) satellite, and from 1995 to 2000 using the Optical Transient Detector (OTD) on the Microlab-1 satellite. Both LIS and OTD are staring imagers that detect lightning as momentary changes in an optical scene. Passive microwave remote sensing (85 and 37 GHz brightness temperatures) from the TRMM Microwave Imager (TMI) has also been used to quantify characteristics of thunderstorms related to lightning. Each lightning detection system has fundamental limitations. TRMM satellite coverage is limited to the tropics and subtropics between 38 deg N and 38 deg S, so lightning at the higher latitudes of the northern and southern hemispheres is not observed. The detection efficiency of NLDN sensors exceeds 95%, but the sensors are only located in the USA. Even if data from other ground-based lightning sensors (World Wide Lightning Location Network, the European Cooperation for Lightning Detection, and Canadian Lightning Detection Network) were combined with TRMM and NLDN, there would be enormous spatial gaps in present-day coverage of lightning. In addition, a globally-complete time history of observed lightning activity is currently not available either, with network coverage and detection efficiencies varying through the years. Previous research using the TRMM LIS and Microwave Imager (TMI) showed that there is a statistically significant correlation between lightning flash rates and passive microwave brightness temperatures. The physical basis for this correlation emerges because lightning in a thunderstorm occurs where ice is first present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the flash rate) was calculated for storms having 85 GHz PCT greater than 150 K. NLDN data was used to determine if a CG strike occurred for a storm. This probability of CG lightning was plotted as a function of minimum 85 GHz PCT and minimum 37 GHz PCT. These probabilities were used in conjunction with the linear model to estimate the CG flash rate for weaker storms with minimum 85 GHz PCTs greater than 150 K. Results from the investigation of CG lightning and passive microwave radiation signals agree with the previous research investigating total lightning and brightness temperature. Future work will take the established relationships and apply them to the decades of available DMSP data for the USA to derive a map of CG lightning flash rates. Validation of this method and uncertainty analysis will be done by comparing the derived maps of CG lightning flash rates against existing NLDN maps of CG lightning flash rates.

Winesett, Thomas↗
NASA NTRS2013

Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.

Smith, William L., Jr.↗
NASA NTRS2004

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

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

Li, Xiao-Wen↗
NASA NTRS1999

The Dependence on Grid Resolution of Numerically Simulated Convective Cloud Systems Using Ice Microphysics

Mesoscale research and forecast models are increasingly being used at horizontal resolutions of 1-8 km to simulate a variety of precipitating systems. When the model is used to simulate convective systems, it is uncertain to what extent the dynamics and microphysics of convective updrafts can be resolved with grids larger than 1 km. In this study, two- and three-dimensional versions of the Goddard Cumulus Ensemble model are used to determine the impact of horizontal grid resolution on the behavior of the simulated storms and on the characteristics of the cloud microphysical fields. It will be shown that as resolution decreases from about 1 km to greater than 3 km, there is a fairly rapid degradation of the storm structure in the form of reduced convective mass fluxes, updraft tilts, and cloud microphysics. A high-resolution simulation of hurricane outer rainbands using the MM5 mesoscale model shows also that there can be a substantial modification of the key microphysical processes that contribute to rainfall as a result of reducing the horizontal resolution.

Braun, Scott A.↗
NASA NTRS2015

Kinematic and Microphysical Control of Lightning Flash Rate over Northern Alabama

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to examine the relationship between deep convection and the production of nitrogen oxides (NO (sub x)) via lightning (LNO (sub x)). A critical step in estimating LNO (sub x) production in a cloud-resolving model (CRM) without explicit lightning is to estimate the flash rate from available model parameters that are statistically and physically correlated. As such, the objective of this study is to develop, improve and evaluate lightning flash rate parameterizations in a variety of meteorological environments and storm types using radar and lightning mapping array (LMA) observations taken over Northern Alabama from 2005-2012, including during DC3. UAH's Advanced Radar for Meteorological and Operational Research (ARMOR) and the Weather Surveillance Radar - 1988 Doppler (WSR 88D) located at Hytop (KHTX) comprises the dual-Doppler and polarimetric radar network, which has been in operation since 2004. The northern Alabama LMA (NA LMA) in conjunction with Vaisala's National Lightning Detection Network (NLDN) allow for a detailed depiction of total lightning during this period. This study will integrate ARMOR-KHTX dual Doppler/polarimetric radar and NA LMA lightning observations from past and ongoing studies, including the more recent DC3 results, over northern Alabama to form a large data set of 15-20 case days and over 20 individual storms, including both ordinary multicell and supercell convection. Several flash rate parameterizations will be developed and tested, including those based on 1) graupel/small hail volume; 2) graupel/small hail mass, and 3) convective updraft volume. Sensitivity of the flash rate parameterizations to storm intensity, storm morphology and environmental conditions will be explored.

Carey, Lawrence D.↗
NASA NTRS1990

Impulsive microwave burst and solar noise storm emission resolved with the VLA

The evolution of a microwave burst at 20.7 cm wavelength and a type I noise storm at 91.6 cm wavelength are examined using VLA. The magnetic loops in the two spectral regions are studied. The sizes and brightness temperatures of the 20.7 cm burst sources are compared with those predicted by multithermal and nonthermal models of microwave burst emission of Dulk and Dennis (1982). The data reveal that: (1) the precursor, impulsive, and post-impulsive phases of the 20.7 cm burst are located in spatially separated sources; (2) the gradual enhancement of a 91.6 cm noise storm continuum source suggests a feed-back mechanism exists between activity in higher and lower lying loops; and (3) the derived magnetic field strengths at 20.7 cm for the nonthermal models are 35-160 G with core field strengths of 125-220 G.

Willson, Robert F.↗
NASA NTRSDate not supplied

Mars Global Climate Modeling.

Scientists use Global Climate Models (GCMs) to better under the current and past climate states of terrestrial (solid surface) bodies in our solar system and beyond, and the physical processes that control them. GCMs are complex, multi-dimensional computer codes that can generally be divided into two parts: the geophysical fluid dynamics (GFD) framework, which represents accelerations and spatially resolved processes, and the physics routines, which provide the forcing functions for the circulation. Producing a GCM that is appropriate for a particular body—Mars, for example—requires implementing the appropriate physics routines (e.g., radiative transfer, planetary boundary layer physics, dust lifting physics to generate dust storms, etc.) for that body. In this talk, I will give an overview of the components of the NASA Ames Mars GCM and discuss some of the scientific questions we address with this state-of-the-art numerical model.

Melinda A. Kahre↗
NASA NTRS2003

Cloud-Resolving Model and GPM

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

Tao, Wei-Kuo↗