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A Synthesis of Light Absorption Properties of the Arctic Ocean: Application to Semi-analytical Estimates of Dissolved Organic Carbon Concentrations from Space

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean [e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012], the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher 74 than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained 75 by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian 76 side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off 77 North America. In contrast, the relationship between the phytoplankton absorption (a()) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific a() values [Matsuoka et al., 2013], this result indirectly suggests that CDOM absorption can be appropriately erived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

Pan-Arctic↗

Concepts for NASA longitudinal health studies

Clinical data collected from a 15-year study of the homogenous group of pre-Shuttle astronauts have revealed no significant long-term effects from spaceflight. The current hypothesis suggests that repeated exposures to the space environment in the Shuttle era will similarly have no long-term health effects. However, a much more heterogenous group of astronauts and non-astronaut scientists will fly in Shuttle, and data on this group's adaptation to the space environment and readaptation to earth are currently sparse. In addition, very little information is available concerning the short- and long-term medical consequences of long duration exposure to space and subsequent readaptation to the earth environment. In this paper, retrospective clinical information on astronauts is reviewed and concepts for conducting epidemiological studies examining long-term health effects of spaceflight on humans, including associated occupational risks factors, are presented.

Nicogossian, A. E.↗

A Chess-Like Game for Teaching Engineering Students to Solve Large System of Simultaneous Linear Equations

Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]!

Nguyen, Duc T.↗

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

Modeling↗

The three-dimensional structure of the infrared cirrus

This project was carried out over a period of four years, beginning 6/15/89 and continuing through 9/15/93. Intermediate results have been reported as poster papers at several meetings of the American Astronomical Society. A brief summary was presented in April 1993 at a symposium on the infrared cirrus. The final results were published in late 1993. The measurements have been deposited in NASA's Astronomical Data Center. Briefly, the results are as follows: Using the IRAS data base, we surveyed the 1808 06-B9.5 stars in the Bright Star Catalog for extended excess emission at 60 micrometers, indicating the presence of heated dust (cirrus hotspots) at the location of the star. Measurements of the angular size and infrared flux at 12, 25, 60 and 100 micrometers were obtained for 302 objects. From these basic data we calculated the radius, absorption, optical depth, color temperature, and dust density for each object. Arguing that the stars are randomly distributed point probes of the ISM, we showed that the filling factor of the dust-bearing component of the ISM is 14.6 + 2.4 percent within 400 pc of the sun for clouds with an equivalent hydrogen density greater than 0.5 cm(exp -3). Above a density of 1.0 cm(exp -3) the density distribution function appears to follow a power law of index -1.25. Further, we showed that the dust is distributed more sparsely in a region near the sun about 60 pc wide and extending several hundred parsecs in the direction of longitudes 80-260 deg. The distances to the dust clouds were determined from the spectroscopic parallaxes of the embedded stars; when the HIPPARCOS parallaxes become available, we will be able to produce a more accurate three-dimensional view of the local ISM.

Gaustad, John E.↗

Trends in Europe Storm Surge Extremes Match the Rate of Sea-level Rise

Coastal communities across the world are already feeling the disastrous impacts of climate change through variations in extreme sea levels1. These variations reflect the combined effect of sea-level rise and changes in storm surge activity. Understanding the relative importance of these two factors in altering the likelihood of extreme events is crucial to the success of coastal adaptation measures. Existing analyses of tide gauge records agree that sea-level rise has been a considerable driver of trends in sea-level extremes since at least 1960. However, the contribution from changes in storminess remains unclear, owing to the difficulty of inferring this contribution from sparse data and the consequent inconclusive results that have accumulated in the literature. Here we analyse tide gauge observations using spatial Bayesian methods to show that, contrary to current thought, trends in surge extremes and sea-level rise both made comparable contributions to the overall change in extreme sea levels in Europe since 1960 . We determine that the trend pattern of surge extremes reflects the contributions from a dominant north–south dipole associated with internal climate variability and a single-sign positive pattern related to anthropogenic forcing. Our results demonstrate that both external and internal influences can considerably affect the likelihood of surge extremes over periods as long as 60 years, suggesting that the current coastal planning practice of assuming stationary surge extremes might be inadequate.

Francisco M Calafat↗

Sedimentary Parameters Controlling Occurrence and Preservation of Microbial Mats in Siliciclastic Depositional Systems

Shallow-marine, siliciclastic depositional systems are governed by physical sedimentary processes. Mineral precipitation or penecontemporaneous cementation play minor roles. Today, coastal siliciclastic environments may be colonized by a variety of epibenthic, mat-forming cyanobacteria. Studies on microbial mats showed that they are not randomly distributed in modern tidal environments. Distribution and abundancy is mainly function of a particular sedimentary facies. Fine-grained sands composed of "clear" (translucent) quartz particles constitute preferred substrates for cyanobacteria. Mat-builders also favor sites characterized by moderate hydrodynamic flow regimes, which permit biomass enrichment and construction of mat fabrics without lethal burial of mat populations by fine sediments. A comparable facies relationship can be observed in ancient siliciclastic shelf successions from the terminal Neoproterozoic Nama Group, Namibia. Wrinkle structures that record microbial mats are present but sparsely distributed in mid- to inner shelf sandstones of the Nudaus Formation. The sporadic distribution of these structures reflects both the narrow ecological window that governs mat development and the distinctive taphonomic conditions needed to preserve the structures. These observations caution that statements about changing mat abundance across the Proterozoic-Cambrian boundary must be firmly rooted in paleoenvironmental and taphonomic analysis. Understanding the factors that influence the formation and preservation of microbial structures in siliciclastic regimes can facilitate exploration for biological signatures in Earth's oldest rocks. Moreover, insofar as these structures can be preserved on bedding surfaces and are not easily mimicked by physical processes, they constitute a set of biological markers that can be searched for on Mars by remotely controlled rovers.

Noffke, Nora↗

Coherence Analysis of the Space Launch System using Unsteady Pressure Sensitive Paint

Transonic buffet during atmospheric ascent is a major source of unsteady loading on launch vehicles that, in the past, has led to structural failures. Thus, determining accurate buffet forcing functions (BFFs) to properly predict the vehicle response to buffet is of vital importance in launch vehicle design. The state of the art for obtaining the BFFs relies on wind-tunnel tests where the fluctuating pressures are measured by pressure transducers (PTs) at sparse locations on a rigid, geometrically-scaled buffet model. To compute the BFFs, the outer mold line (OML) of the vehicle is mapped onto contiguous panels centered at the location of the PTs and the measured fluctuating pressures are integrated over the panels’ areas. To mitigate conservatism due to the assumption that the measured buffet pressures act in phase across each panel, coherence factors are applied, effectively reducing the integration areas and, therefore, the buffet forces. For coherence factors to provide the proper level of BFF attenuation, accurate knowledge of the spatial and temporal correlation of the buffet pressures is paramount. Unfortunately, even with hundreds of unsteady pressure transducers instrumenting the models, compromises must be made on the spatial resolution of the PTs. Typically, the PT layout aims at resolving the pressure correlation along the longitudinal axis of the vehicle, assuming that coherent structures propagate mostly in the longitudinal direction. As a result, the distribution of azimuthal/cross-stream correlation is not well known and its impact on the estimated BFFs is often neglected. To fill this and other knowledge gaps, extremely high spatial-resolution uPSP data were collected for three different production-design configurations of the Space Launch System in the NASA Ames Research Center Unitary Plan Wind Tunnel 11-Foot Transonic Wind Tunnel. Specifically, two cargo configurations, the Block 1 and Block 1B, and one crew configuration, the Block 1B crew, were surveyed at resolutions ranging from 600,000 to over 1 million uPSP measurement locations. To shed light on the temporal and spectral behavior of are presented. Several OML regions and flow features of interest are investigated, from theexpansion/shock on the Orion Multi-Purpose Crew Vehicle, to the terminal shock environment on the core stage, and the Strouhal shedding behind the boosters forward attach. The sensitivity of these environments to the vehicle attitude is examined. Furthermore, for selected panels,coherence factors that accurately capture the azimuthal coherence distribution of the buffetpressures are derived and their impact on the estimated BFFs is discussed. Finally, distributions of the local convection velocity and cross spectrum phase are presented.

buffet↗

Historical (1700–2012) Global Multi-Model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP)

Fire emissions are critical for carbon and nutrient cycles, climate, and air quality. Dynamic Global Vegetation Models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes of fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700-2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table from field and laboratory studies over various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. Evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products, and can capture the high emissions over the tropical savannas, low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most of the models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Historically, all models show only a weak trend in global fire emissions before ~1850s, consistent with multi-source merged historical reconstructions. The long-term trends among DGVMs are quite different for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land-use and land-cover change (LULCC). Our study provides a basic dataset for developing regional and global multi-source merged historical reconstructions and merging methods, and analyzing historical changes of fire emissions and their uncertainties as well as their role in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.

Li, Fang↗

Evaluating an Automated Approach for Monitoring Forest Disturbances in the Pacific Northwest from Logging, Fire and Insect Outbreaks with Landsat Time Series Data

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometers (AVHRRs). To understand the causal factors of this decline, we evaluated an automated classification method developed for Landsat time series stacks (LTSS) to map forest change. This method included: (1) multiple disturbance index thresholds; and (2) a spectral trajectory-based image analysis with multiple confidence thresholds. We produced 48 maps and verified their accuracy with air photos, monitoring trends in burn severity data and insect aerial detection survey data. Area-based accuracy estimates for change in forest cover resulted in producer's and user's accuracies of 0.21 +/- 0.06 to 0.38 +/- 0.05 for insect disturbance, 0.23 +/- 0.07 to 1 +/- 0 for burned area and 0.74 +/- 0.03 to 0.76 +/- 0.03 for logging. We believe that accuracy was low for insect disturbance because air photo reference data were temporally sparse, hence missing some outbreaks, and the annual anniversary time step is not dense enough to track defoliation and progressive stand mortality. Producer's and user's accuracy for burned area was low due to the temporally abrupt nature of fire and harvest with a similar response of spectral indices between the disturbance index and normalized burn ratio. We conclude that the spectral trajectory approach also captures multi-year stress that could be caused by climate, acid deposition, pathogens, partial harvest, thinning, etc. Our study focused on understanding the transferability of previously successful methods to new ecosystems and found that this automated method does not perform with the same accuracy in Pacific Northwest forests. Using a robust accuracy assessment, we demonstrate the difficulty of transferring change attribution methods to other ecosystems, which has implications for the development of automated detection/attribution approaches. Widespread disturbance was found within AVHRR-negative anomalies, but identifying causal factors in LTSS with adequate mapping accuracy for fire and insects proved to be elusive. Our results provide a background framework for future studies to improve methods for the accuracy assessment of automated LTSS classifications.

Landsat↗

Megadroughts in the Common Era and the Anthropocene

Megadroughts, often lasting multiple decades, have caused major ecological and societal disturbances in the past. While most research has focused on megadroughts in North America, the concept has gained increased international attention in recent years. In this Review, we discuss shared causes and features of Common Era and future megadroughts. Paleoclimate reconstructions spanning the last 2,000 years document the occurrence of megadroughts on every continent, save Antarctica. Megadroughts are often linked to decadal variations in sea surface temperatures, with radiative forcing and land-atmosphere interactions acting as secondary factors. Anthropogenic climate change has already contributed to recent megadroughts in southwestern North America and Chile-Argentina and will likely increase future megadrought risk and severity in many regions. Notably, future megadroughts will be differentiated from past events through higher temperatures, which act as the main driver of increased risk, severity, and impacts. Major deficiencies in our understanding of natural and anthropogenic megadrought processes remain, however. These include 1) sparse high-resolution paleoclimate information over some regions, 2) incomplete representations of internal variability and land-surface processes in climate models, and 3) the undetermined capacity of water-resource management systems to manage megadrought impacts. Resolving these key uncertainties will be necessary to increase confidence in projections of future megadrought risk and resiliency planning.

Droughts↗

Parallel Preconditioning for CFD Problems on the CM-5

Up to today, preconditioning methods on massively parallel systems have faced a major difficulty. The most successful preconditioning methods in terms of accelerating the convergence of the iterative solver such as incomplete LU factorizations are notoriously difficult to implement on parallel machines for two reasons: (1) the actual computation of the preconditioner is not very floating-point intensive, but requires a large amount of unstructured communication, and (2) the application of the preconditioning matrix in the iteration phase (i.e. triangular solves) are difficult to parallelize because of the recursive nature of the computation. Here we present a new approach to preconditioning for very large, sparse, unsymmetric, linear systems, which avoids both difficulties. We explicitly compute an approximate inverse to our original matrix. This new preconditioning matrix can be applied most efficiently for iterative methods on massively parallel machines, since the preconditioning phase involves only a matrix-vector multiplication, with possibly a dense matrix. Furthermore the actual computation of the preconditioning matrix has natural parallelism. For a problem of size n, the preconditioning matrix can be computed by solving n independent small least squares problems. The algorithm and its implementation on the Connection Machine CM-5 are discussed in detail and supported by extensive timings obtained from real problem data.

Simon, Horst D.↗

Manufacture of Sparse-Spectrum Optical Microresonators

An alternative design for dielectric optical microresonators and a relatively simple process to fabricate them have been proposed. The proposed microresonators would exploit the same basic physical phenomena as those of microtorus optical resonators and of the microsphere optical resonators described elsewhere. The resonances in such devices are associated with the propagation of electromagnetic waves along circumferential paths in "whispering-gallery" modes. The main advantage afforded by the proposal is that the design and the fabrication process are expected to be amenable to production of multiple microresonators having reproducible spectral parameters -- including, most notably, high values of the resonance quality factor (Q) and reproducible resonance frequencies.

Savchenkov, Anatoliy↗

Modeling the radiant transfers of sparse vegetation canopies

The scattering dynamics of sparse vegetation canopies were studied within the framework of the three-dimensional radiative transfer model of Kimes (1984). The model was upgraded by including an algorithm for the anisotropic scattering of a soil boundary. Validation of the model was carried out using measured directional reflectance data for two canopies exhibiting typical scattering behavior with low and intermediate vegetation density. The canopies were: an orchard grass canopy; and a hard wheat canopy. A number of factors were found contributing to the final reflectance distribution of the canopies, including: (1) the strong anisotropic scattering properties of the soil; (2) the geometric effect of the vegetation probability gap function on the soil anisotropy and solar irradiance; and (3) the anisotropic scattering of vegetation which is controlled by the phase function and the layering of leaves. The application of the theoretical results to the development of earth-observing sensor systems is discussed.

Kimes, D. S.↗

Superhumps in cataclysmic binaries. 3: V795 Herculis

We report photometry of the cataclysmic variable V795 Herculis during 1990-1994. Comparison of recent with previously published data shows that the 2.78-hr periodicity has essentially disappeared; the amplitude has diminished by a factor of at least 10. In its place, there is a low-amplitude signal near the radial-velocity (orbital?) period of 2.60 hr. During 1983-1989, the star did show an obvious 2.78-hr signal. We study the published data on this signal, together with our own data under the (questionable) assumption that the signal still exists with an amplitude too small to survive the rigors of unbiased period detection. The data are really too sparse and too poorly distributed to decide the issue of phase stability. But since the photometric signal is transient and exceeds the likely orbital period by approximately 8%, the photometric waves are likely to be yet another example of 'superhumps', the phenomenon made famous by dwarf novae in superoutburst. At high frequencies, the star shows a quasi-periodic signal with P approximately 1160 s, and possibly also a stable signal with P = 1310.2 s (or 1330.4 s, the one-day alias). The beat period between these signals could be the orbital period, or that of the vanished superhump.

Patterson, Joseph↗

Crater Morphometry and Crater Degradation on Mercury: Mercury Laser Altimeter (MLA) Measurements and Comparison to Stereo-DTM Derived Results

Two types of measurements of Mercury's surface topography were obtained by the MESSENGER (MErcury Surface Space ENvironment, GEochemisty and Ranging) spacecraft: laser ranging data from Mercury Laser Altimeter (MLA) [1], and stereo imagery from the Mercury Dual Imaging System (MDIS) camera [e.g., 2, 3]. MLA data provide precise and accurate elevation meaurements, but with sparse spatial sampling except at the highest northern latitudes. Digital terrain models (DTMs) from MDIS have superior resolution but with less vertical accuracy, limited approximately to the pixel resolution of the original images (in the case of [3], 15-75 m). Last year [4], we reported topographic measurements of craters in the D=2.5 to 5 km diameter range from stereo images and suggested that craters on Mercury degrade more quickly than on the Moon (by a factor of up to approximately 10×). However, we listed several alternative explanations for this finding, including the hypothesis that the lower depth/diameter ratios we observe might be a result of the resolution and accuracy of the stereo DTMs. Thus, additional measurements were undertaken using MLA data to examine the morphometry of craters in this diameter range and assess whether the faster crater degradation rates proposed to occur on Mercury is robust.

morphometry↗

Remote Sensing of Hail from Space: Retrievals, Climatologies, 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 subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: 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 used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. 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. There are 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↗

Spaceborne Remote Sensing of Hail: Retrievals, Climatologies, 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 subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: 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 used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. 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. There are 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↗