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NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2009

The Influence of the 2006 Indonesian Biomass Burning Aerosols on Tropical Dynamics Studied with the GEOS-5 AGCM

The direct and semi-direct effects of aerosols produced by Indonesian biomass burning (BB) during August November 2006 on tropical dynamics have been examined using NASA's Goddard Earth Observing System, Version 5 (GEOS-5) atmospheric general circulation model (AGCM). The AGCM includes CO, which is transported by resolved and sub-grid processes and subject to a linearized chemical loss rate. Simulations were driven by two sets of aerosol forcing fields calculated offline, one that included Indonesian BB aerosol emissions and one that did not. In order to separate the influence of the aerosols from internal model variability, the means of two ten-member ensembles were compared. Diabatic heating from BB aerosols increased temperatures over Indonesia between 150 and 400 hPa. The higher temperatures resulted in strong increases in upward grid-scale vertical motion, which increased water vapor and CO over Indonesia. In October, the largest increases in water vapor were found in the mid-troposphere (~25%) while the largest increases in CO occurred just below the tropopause (80 ppbv or ~50%). Diabatic heating from the Indonesian BB aerosols caused CO to increase by 9% throughout the tropical tropopause layer in November and 5% in the lower stratosphere in December. The results demonstrate that aerosol heating plays an important role in the transport of BB pollution and troposphere-to-stratosphere transport. Changes in vertical motion and cloudiness induced by aerosol heating can also alter the transport and phase of water vapor in the upper troposphere/lower stratosphere.

Ott, Lesley↗
NASA NTRS1993

ER-2 investigations of lightning and thunderstorms

The primary objective of the ER-2 lightning program is to investigate relationships between lightning and storm electrification and a number of underlying and interrelated phenomena including the structure, dynamics, and evolution of thunderstorms and thunderstorm systems, precipitation distribution and amounts, atmospheric chemistry processes, and the global electric circuit. This research is motivated by the desire to develop an understanding needed for the effective utilization and interpretation of data from the Lighting Imaging Sensor (LIS), the Lightning Mapper Sensor (LMS), and other satellite-based lightning detectors planned for the late 1900's and early 2000's. These satellite lightning detection systems will be characterized by high detection efficiencies (i.e., 90 percent) and the capability to detect both intracloud and cloud-to-ground discharges during day and night. The Lightning Imaging Sensor (LIS) is being developed by NASA for the Tropical Rainfall Measuring Mission (TRMM) satellite. In the ER-2 and related investigations, the emphasis is on establishing quantitative relationships and developing practical algorithms that employ lightning data, such as could be derived from satellite observations of optical lightning emissions, as the independent variable. Significant accomplishments made during the past year are presented.

Blakeslee, Richard↗
NASA NTRS1996

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

Rafael, Qihang Li↗
NASA NTRS2003

Representativeness Uncertainty in Chemical Data Assimilation Highlight Mixing Barriers

When performing chemical data assimilation the observational, representativeness, and theoretical uncertainties have very different characteristics. In this study we have accurately characterized the representativeness uncertainty by studying the probability distribution function (PDF) of the observations. The average deviation has been used as a measure of the width of the PDF and of the variability (representativeness uncertainty) for the grid cell. It turns out that for long-lived tracers such as N2O and CH4 the representativeness uncertainty is markedly different from the observational uncertainty and clearly delineates mixing barriers such as the polar vortex edge, the tropical pipe and the tropopause.

Lary, David John↗
NASA NTRS2008

TES Carbon Monoxide Validation during the Two AVE Campaigns using the Argus and ALIAS Instruments on NASA's WB-57F

The Aura Validation Experiment (AVE) focuses on validating Aura satellite measurements of important atmospheric trace gases using ground-based, aircraft, and balloon-borne instruments. Global satellite observations of CO from the Tropospheric Emission Spectrometer (TES) on the EOS Aura satellite have been ongoing since September 2004. This paper discusses CO validation experiments during the Oct-AVE (2004 Houston, Texas) and CR-AVE (2006 San Jose, Costa Rica) campaigns. The coincidences in location and time between the satellite observations and the available in situ profiles for some cases are not ideal. However, the CO distribution patterns in the two validation flight areas are shown to have very little variability in the aircraft and satellite . observations, thereby making them suitable for validation comparisons. TES CO profiles, which typically have a retrieval uncertainty of 10-20%, are compared with in situ CO measurements from NASA Ames Research Center's Argus instrument taken on board the WB-57F aircraft during Oct-AVE. TES CO retrievals during CR-AVE are compared with in situ measurements from Jet Propulsion Laboratory's Aircraft Laser Infrared Absorption Spectrometer (ALIAS) instrument as well as with the Argus instrument, both taken on board the WB-57F aircraft. During CR-AVE, the average overall difference between ALIAS and Argus CO was 4%, with the ALIAS measurement higher. During individual flights, 2-min time-averaged differences between the two in situ instruments had standard deviation of 14%. The TES averaging kernels and a priori constraint profiles for CO are applied to the in situ data for proper comparisons to account for the reduced vertical resolution and the influence of the a priori in the satellite-derived profile. In the TES sensitive pressure range, approx.700-200 hPa, the in situ profiles and TES profiles agree within 5-10%, less than the variability in CO distributions obtained by both TES and the aircraft instruments in the two regions. TES CO is slightly lower than in situ measurements in the Houston area (midlatitudes) and slightly higher than in situ CO measurements in the Costa Rica region (tropical).

Lopez, Jinena P.↗
NASA NTRS2010

Utilizing TRMM to Analyze Sea Breeze Thunderstorm Patterns During El Nino Southern Oscillations and Their Effects upon Available Fresh Water for South Florida Agricultural Planning and Management

Water is in high demand for farmers regardless of where you go. Unfortunately, farmers in southern Florida have fewer options for water supplies than public users and are often limited to using available supplies from surface and ground water sources which depend in part upon variable weather patterns. There is an interest by the agricultural community about the effect weather has on usable surface water, however, research into viable weather patterns during La Nina and El Nino has yet to be researched. Using rainfall accumulation data from NASA Tropical Rainfall Measurement Mission (TRMM) satellite, this project s purpose was to assess the influence of El Nino and La Nina Oscillations on sea breeze thunderstorm patterns, as well as general rainfall patterns during the summer season in South Florida. Through this research we were able to illustrate the spatial and temporal variations in rainfall accumulation for each oscillation in relation to major agricultural areas. The study period for this project is from 1998, when TRMM was first launched, to 2009. Since sea breezes in Florida typically occur in the months of May through October, these months were chosen to be the months of the study. During this time, there were five periods of El Nino and two periods of La Nina, with a neutral period separating each oscillation. In order to eliminate rainfall from systems other than sea breeze thunderstorms, only days that were conducive to the development of a sea breeze front were selected.

Cooley, Clayton↗
NASA NTRS2014

Configuration and Assessment of the GISS ModelE2 Contributions to the CMIP5 Archive

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.

ocean model↗
NASA NTRS2007

Mechanisms for the Intraseasonal Variability of Tropospheric Ozone over the Indian Ocean during the Winter Monsoon

We synthesize daily sonde (vertical) information and daily satellite (horizontal) information to provide an empirical description of ozone origins over the northern Indian Ocean during the INDOEX (Indian Ocean Experiment) field campaign (February-March 1999). This area is shown to be a significant portion of the "high-ozone tropics". East-west O3 features and their flow are identified, and ozone origins are compared to other tropical regions, using water vapor as a second tracer. In the study period, multiple processes contribute to O3 column enhancements, their importance varying strongly by latitude: (1) Low-altitude O3 pollution over the northern Indian Ocean mainly originates from the Indian subcontinent and is traceable to high emission areas. Convective activity south of Sri Lanka helps direct ozone outflow from the northern Indian subcontinent. (2) Middle tropospheric O3 maxima over the northern Indian Ocean originate from various sources, often transitioning within a few hours. Convective venting of Asian pollutants can add 20-30 ppbv to the middle troposphere at 5degN-10degN, alternating with stratospheric influence. (3) A number of cases suggest that strong mixing-in of stratospheric air along the subtropical jet raised tropospheric O3 in early March by approx.40-50 ppbv, especially poleward of approx. 10degN. (4) Influences of lightning and large-scale biomass burning were not strong during this period, in contrast to the situation in Africa and the South Atlantic or locally in Southeast Asia. This work illustrates successes and limitations in approaches to synthesizing disparate information on trace-gas distributions taken from satellite retrieval products and ozonesondes.

Chatfield, R. b.↗
NASA NTRS1999

Correlations Between Topex Altimeter and Temperature Profile Data in the Equatorial Pacific

Observations of sea-surface heights from satellite altimeters have been a major contributor to monitoring the evolution of the recent major El Nino event. Assimilating altimeter data directly into numerical models only takes advantage of the surface signature provided by the data. However, that surface signature is usually indicative of processes occurring at depth, especially in the equatorial Pacific. In order for assimilation schemes to make maximum use of surface data, it is helpful to have knowledge of how to best extend that data in the vertical to account for that variability. Toward that end, the vertical correlation structure between satellite-observed sea-surface heights and in situ temperature measurements is examined using TOPEX altimeter and TOGA TAO profile data for the period 1993-1998. This time period includes several states of the tropical Pacific, including a perturbed state from 1993-1994, a quiescent state encompassing 1995-1996, and the major ENSO event of 1997-1998. Analyses for each of these periods, as well as the total period will be presented. In addition to analyses at specific depth levels, analyses for particular density surfaces will also be presented.

Adamec, David↗
NASA NTRS1991

Comparison of aerosol extinction profiles from lidar and SAGE II data at a tropical station

Aerosol extinction profiles obtained from lidar data at Trivandrum (8.6 deg N, 77 deg E) are compared with corresponding Stratospheric Aerosol and Gas Experiment II extinction profiles. The agreement between the two is found to be satisfactory. The extinction profiles obtained by both the experiments showed a prominent peak at 23-24 km altitude in the stratosphere. The study revealed large variability in upper tropospheric extinction with location (latitude).

Parameswaran, K.↗
NASA NTRS2000

Water Vapor Transport Over the Tropical Oceans During ENSO as Diagnosed from TRMM and SSM/I Data

Traditionally, large-scale water vapor transport [div Q] has been derived directly from circulation statistics in which transport processes are often depicted by mean and eddy motions. Thus detailed and accurate calculations of moisture transport terms over the globe are required. Notably, the lack of systematically spaced conventional measurements of meteorological variables over oceans has hindered understanding of the distribution and transport of water vapor. This motivates the use of indirect calculation methods in which horizontal divergence of water vapor is balanced by the evaporation minus precipitation, assuming the rate of changes of precipitable water and condensates is small over a sufficiently long time period. In order to obtain the water vapor transport, we need evaporation rate minus precipitation (E-P). Focussing on the differences in water vapor transport between El Nino and La Nina periods and their influences on atmospheric circulations, we study January, February, and March of 1998 and 1999 periods which represent El Nino and La Nina respectively. SSM/I-derived precipitation and evaporation rate from SSM/I wind and total precipitable water, in conjunction with NCEP SST and surface air temperature, are used for the calculation of the transport potential function. For the retrieval of evaporation we use a stability-dependent aerodynamic bulk scheme developed by Chou (1993). It was tested against aircraft covariance fluxes measured during cold air outbreaks over the North Atlantic Ocean. Chou et al. (1997) reported that the SSM/I retrieved latent heat flux over the western Pacific warm pool area were found to be comparable with daily mean fluxes of a ship measurements during TOGA/COARE.

Robertson, Franklin R.↗
NASA NTRS2018

Quantifying Long-Term Changes in Carbon Stocks and Forest Structure from Amazon Forest Degradation

Despite sustained declines in Amazon deforestation, forest degradation from logging and firecontinues to threaten carbon stocks, habitat, and biodiversity in frontier forests along the Amazon arcof deforestation. Limited data on the magnitude of carbon losses and rates of carbon recoveryfollowing forest degradation have hindered carbon accounting efforts and contributed to incompletenational reporting to reduce emissions from deforestation and forest degradation (REDD+). Wecombined annual time series of Landsat imagery and high-density airborne lidar data to characterizethe variability, magnitude, and persistence of Amazon forest degradation impacts on abovegroundcarbon density (ACD) and canopy structure. On average, degraded forests contained 45.1% of thecarbon stocks in intact forests, and differences persisted even after 15 years of regrowth. Incomparison to logging, understory fires resulted in the largest and longest-lasting differences in ACD.Heterogeneity in burned forest structure varied by fire severity and frequency. Forests with a historyof one, two, and three or more fires retained only 54.4%, 25.2%, and 7.6% of intact ACD,respectively, when measured after a year of regrowth. Unlike the additive impact of successive fires,selective logging before burning did not explain additional variability in modeled ACD loss andrecovery of burned forests. Airborne lidar also provides quantitative measures of habitat structure thatcan aid the estimation of co-benefits of avoided degradation. Notably, forest carbon stocks recoveredfaster than attributes of canopy structure that are critical for biodiversity in tropical forests, includingthe abundance of tall trees. We provide the first comprehensive look-up table of emissions factors forspecific degradation pathways at standard reporting intervals in the Amazon. Estimated carbon lossand recovery trajectories provide an important foundation for assessing the long-term contributionsfrom forest degradation to regional carbon cycling and advance our understanding of the currentstate of frontier forests.

Rappaport, Danielle I.↗
NASA NTRS2021

FLUXNET-CH4: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20°S to 20°N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

FLUXNET-CH4↗
NASA NTRS2023

Convective Impact on the Global Lower Stratospheric Water Vapor Budget

Water vapor in the stratosphere is primarily controlled by temperatures in the tropical upper troposphere and lower stratosphere. However, the direct impact of deep convection on the global lower stratospheric water vapor budget is still an actively debated issue. Two complementary modeling approaches are used to investigate the convective impact in boreal winter and summer. Convective influence is diagnosed by tracing trajectories through convective cloud top altitude fields derived from global rainfall and brightness temperature data. Backward trajectory model simulations coupled with a detailed treatment of cloud microphysical processes indicate that convection moistens the global lower stratosphere by approximately 0.3 ppmv in boreal winter and summer 2010. The diurnal peak in convection is responsible for about half of the total convective moistening during winter and nearly all of the convective moistening during summer. Deep convective clouds overshooting the tropopause have relatively minor effect on global lower stratospheric water vapor. A forward trajectory model coupled with a simplified cloud module is used to estimate the relative magnitude of the interannual variability of the convective impact. Combining the results from the two models, we find that the convective impact on the global lower stratospheric water vapor during 2006-2016 is approximately 0.3 ppmv with year-to-year variations of up to 0.1 ppmv. An important mechanism of convective hydration of the lower stratosphere is via the detrainment of saturated air and ice into the tropical uppermost troposphere and the subsequent upward transport of some of these moist air parcels across relatively warm and subsaturated tropopause.

CONVECTION↗
NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗