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NASA NTRS2016

Cloud Regimes as a Tool for Systematic Study of Various Aerosol-Cloud-Precipitation Interactions

Systematic changes of clouds and precipitation are notoriously difficult to ascribe to aerosols. This presentation will showcase yet one more attempt to at least credibly detect the signal of aerosol-cloud-precipitation interactions. We surmise that the concept of cloud regimes (CRs) is appropriate to conduct such an investigation. Previous studies focused on what we call here dynamical CRs, and while we continue to adopt those too for our analysis, we have found that a different way of organizing cloud systems, namely via microphysical regimes is also promising. Our analysis relies on MODIS Collection 6 Level-3 data for clouds and aerosols, and TRMM-TMPA data for precipitation. The regimes are derived by applying clustering analysis on MODIS joint histograms, and once each grid cell is assigned a regime, aerosol and precipitation data can be spatiotemporally matched and composited by regime. The composites of various cloud and precipitation variables for high (upper quartile of distribution) and low (lower quartile) aerosol loadings can then be contrasted. We seek evidence of aerosol effects both in regimes with large fractions of deep ice-rich clouds, as well as regimes where low liquid phase clouds dominate. Signals can be seen, especially when the analysis is broken by land-ocean and when additional filters are applied, but there are of course caveats which will be discussed.

cloud regimes↗
NASA NTRS1993

Global and regional/seasonal color mosaics of Mars

Four regional mosaics of Mars acquired during different seasons, along with their composite as a single global mosaic, have been completed in two colors (red and violet) at scales of 1/16 and 1/64 degrees/pixel. These mosaics were put together from a set of 51 separate mosaics, each acquired from a single Viking orbiter spacecraft orbital revolution. Special techniques were developed and applied to suppress large variations between mosaics introcued by highly variable, optically thin, condensate hazes. The techniques utilize a combination of the spatial characteristics of the hazes (generally broad, low-frequency) along with their modulation of the reginal color ratios (strongly enhancing the violet/red ratios). Photometric-function normalization was applied following the haze removal. Most of the single-orbit mosaics consist of red and violet or red, green, and violet filters, but a few mosaics with only red-filter data were included to fill gaps in global coverage at high northern latitudes. Global coverage is approximately 99 percent complete in red-filter mosaics and approximately 95 percent and approximately 60 percent complete in corresponding violet- and green-filter mosaics, respectively. All of the mosaics are geometrically tied to the 1/256 deg per pixel Mars Digital Image Map (MDIM), which is available on Compact Disk (CD), and which will be used as the base map for Mars Observer data sets. Early in 1993, the single-orbit color mosaics will be distributed to the science community in a six-volume set of CDs. Perhaps the most scientifically interesting parts of this dataset are the overlap regions, which show significant temporal variations in surface and atmospheric features. Surface changes can be categorized as (1) changes that probably occurred during the great dust storms of 1977; (2) changes that occurred soon after 1977 storms due to removal of redistribution of recently deposited dust; (3) changes in the northern lowlands that probably occurred during the dusty southern summer of 1979 (when no great dust storm occurred); and (4) changes associated with strong slope winds in the Tharsis and Elysium regions.

Mcewen, Alfred S.↗
NASA NTRS2016

Safety and Certification Considerations for Expanding the Use of UAS in Precision Agriculture

The agricultural community is actively engaged in adopting new technologies such as unmanned aircraft systems (UAS) to help assess the condition of crops and develop appropriate treatment plans. In the United States, agricultural use of UAS has largely been limited to small UAS, generally weighing less than 55 lb and operating within the line of sight of a remote pilot. A variety of small UAS are being used to monitor and map crops, while only a few are being used to apply agricultural inputs based on the results of remote sensing. Larger UAS with substantial payload capacity could provide an option for site-specific application of agricultural inputs in a timely fashion, without substantive damage to the crops or soil. A recent study by the National Aeronautics and Space Administration (NASA) investigated certification requirements needed to enable the use of larger UAS to support the precision agriculture industry. This paper provides a brief introduction to aircraft certification relevant to agricultural UAS, an overview of and results from the NASA study, and a discussion of how those results might affect the precision agriculture community. Specific topics of interest include business model considerations for unmanned aerial applicators and a comparison with current means of variable rate application. The intent of the paper is to inform the precision agriculture community of evolving technologies that will enable broader use of unmanned vehicles to reduce costs, reduce environmental impacts, and enhance yield, especially for specialty crops that are grown on small to medium size farms.

Hayhurst, Kelly J.↗
NASA NTRS1988

Coastal Zone Color Scanner

The Coastal Zone Color Scanner (CZCS) spacecraft ocean color instrument is capable of measuring and mapping global ocean surface chlorophyll concentration. It is a scanning radiometer with multiband capability. With new electronics and some mechanical, and optical re-work, it probably can be made flight worthy. Some additional components of a second flight model are also available. An engineering study and further tests are necessary to determine exactly what effort is required to properly prepare the instrument for spaceflight and the nature of interfaces to prospective spacecraft. The CZCS provides operational instrument capability for monitoring of ocean productivity and currents. It could be a simple, low cost alternative to developing new instruments for ocean color imaging. Researchers have determined that with global ocean color data they can: specify quantitatively the role of oceans in the global carbon cycle and other major biogeochemical cycles; determine the magnitude and variability of annual primary production by marine phytoplankton on a global scale; understand the fate of fluvial nutrients and their possible affect on carbon budgets; elucidate the coupling mechanism between upwelling and large scale patterns in ocean basins; answer questions concerning the large scale distribution and timing of spring blooms in the global ocean; acquire a better understanding of the processes associated with mixing along the edge of eddies, coastal currents, western boundary currents, etc., and acquire global data on marine optical properties.

Johnson, B.↗
NASA NTRS1985

Optical characteristics of lightning

A study of the optical characteristics of cloud-to-ground dischargers and how they compare with intracloud flashes was completed. Time resolved optical (7774A) and electric field-change waveforms were measured above clouds from a U2 airplane coincident with ground-based measurements of lightning. The optical pulse trains are studied for within and between flash variability. Specifically, for each flash researchers examine the 10, 50 (full width half maximum), and 90 percent pulse widths; the 10-10, 10-50, 10-90, and 10-peak percent amplitude rise times; the radiances (optical power densities); radiant energy densities; and pulse intervals. The optical pulse characteristics of first strokes, subsequent strokes, the intracloud components of cloud-to-ground flashes and intracloud flashes as viewed from above cloud are shown to exhibit very similar waveshapes, radiances and radiant energy densities. Descriptive statistics on these pulse categories were tabulated for 25 visually confirmed cloud-to-ground flashes (229 optical pulses) and 232 intracloud flashes (3126 optical pulses). A companion study of lightning observations above and below cloud in storms, storm complexes, and mesoscale convective systems has also been completed. Researchers compared the mapping of total lightning activity from above clouds with ground-based measurements and storm evolution. Although the total (IC + CG) lightning activity is the more representative indication of thunderstorm growth and decay, the ground strike data can be used to locate, diagnose, and track storm evolution in a number of instances.

Goodman, S. J.↗
NASA NTRS2023

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗
NASA NTRS2017

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗
NASA NTRS2020

Spatial U-Pb Age Distribution in Shock-Recrystallized Zircon – A Case Study from the Rochechouart Impact Structure, France

Age determination of impact structures via the zircon U–Pb system remains challenging and often ambiguous due to highly variable effects of shock metamorphism on U-Pb geochronology. It is, therefore, crucial to link the observed zircon microtextures, including their temperature and pressure conditions associated with their formation, directly to the U–Pb ages preserved. Here, we analyzed three recrystallized zircon grains and one plastically deformed zircon crystal from the medium-sized Rochechouart impact structure in the northwestern Massif Central of France. For the Rochechouart impact structure the impact age (206.92 ± 0.32 Ma [40Ar/39Ar]) as well as the 2 tectono-themal history is well established making this study site ideal to test concepts about U-Pb systematics in shocked zircon and to differentiate between shock-driven age resetting and preimpact crystallization and metamorphic overprinting. Zircon microstructures were studied using scanning electron imaging, cathodoluminescence imaging, and electron backscatter diffraction (EBSD) mapping. Further, we conducted U–Pb Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) depth-profiling analysis, allowing us to interpret the resultant age data in discrete steps with increasing ablation time/depth. The U–Pb depth profiling data demonstrate that plastically strained grains are incompletely reset and preserve rim and interior age domains reflecting typical pre-impact (pre-Variscan and Variscan) regional tectonic ages. Our results also reveal that the granular crystals encountered contain microstructural evidence for “former reidite in granular neoblastic” (FRIGN) zircon, reflecting both high-pressure (⩾30GPa) and high temperature (⩾1200℃) conditions. This signifies that FRIGN zircon is now known from an additional, medium sized, impact structure further supporting the hypothesis that this impact induced microstructure is commonly preserved. In addition, FRIGN zircon has a high potential to preserve completely impact-reset crystal domains (~204 to 207 Ma) that can be identified by our combined analytical approach of U–Pb depth profiling and EBSD mapping, and thus are suitable for determining reliable impact ages

U-Pb depth profiling↗
NASA NTRS2021

An Investigation on Seasonal and Diurnal Cycles of TOA Shortwave Radiations from DSCOVR/EPIC, CERES, MERRA-2, and ERA5

Reflected shortwave (SW) solar radiations at the top of atmosphere from Clouds and the Earth’s Radiant Energy System (CERES), Modern Era-Retrospective analysis for Research and Applications version 2 (MERRA-2), and ECMWF Reanalysis 5th Generation (ERA5) are examined to better under-stand their differences in spatial and temporal variations (seasonal and diurnal cycle time-scale) with respect to the observations from the Earth Polychromatic Imaging Camera (EPIC) on Deep Space Climate Observatory (DSCOVR) satellite. Comparisons between two reanalyses (MERRA-2 and ERA5) and EPIC reveal that MERRA-2 has a generally larger deviation from EPIC than ERA5, in terms of the SW radiance and diurnal variability in all seasons, which can be attributed to larger cloud biases in MERRA-2. MERRA-2 produces more ice/liquid water content than ERA5 over the tropical warm pool, leading to positive SW biases in cloud and radiance, while both reanalyses underestimate the observed SW radiance from EPIC in the stratus-topped region off the western coast of US/Mexico in the boreal summer. Himalaya/Tibet region in the boreal spring/summer and the midlatitude Southern Hemisphere in the boreal winter are the regions where MERRA-2 and ERA5 deviate largely from EPIC but their deviations have the opposite sign. Vertical structures of cloud ice/liquid water content explain reasonably well these contrasting differences between the two reanalyses. As two independent observa-ions, CERES and EPIC agree well with each other in terms of the SW radiance maps, showing 2-3% mean absolute errors over the tropical-midlatitudes. The CERES-EPIC consistency further confirms that the reanalyses still have challenges in representing the SW flux and its global distribution. In the CERES-EPIC observation differences, CERES slightly overestimates the diurnal cycle (as a function of local solar time) of the observed EPIC irradiance in the morning and underestimates in the after-noon, while the opposite is the case in the reanalyses.

Reflected shortwave radiance↗
NASA NTRS2021

A Sulfur Dioxide Covariance-Based Retrieval Algorithm (COBRA): Application to TROPOMI Reveals New Emission Sources

Sensitive and accurate detection of sulfur dioxide (SO 2 ) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO 2 columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO 2 -free radiance variability, so that the SO 2 slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO 2 retrievals. The performance of this technique is also benchmarked against that of the Principal Component Algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO 2 accurately is also further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO 2 map, considering two and a half years of TROPOMI data. In addition to the known sources, we detect many new SO 2 emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO 2 emission rates. Results are comparable to other recently published TROPOMI-based SO 2 emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO 2 emissions with a detection limit of about 8 kt yr -1 , a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO 2 column data set at a global scale will allow identifying and quantifying missing sources, and help improving SO 2 emission inventories.

SO2↗
NASA NTRS2023

Modeling Global Indices for Estimating Non-Photosynthetic Vegetation Cover

Non-photosynthetic vegetation (NPV) includes plant litter, senesced leaves, and crop residues. NPV plays an essential role in terrestrial ecosystem processes, and is an important indicator of drought severity, ecosystem disturbance, agricultural resilience, and wildfire danger. Current moderate spatial resolution multispectral satellite systems (e.g., Landsat and Sentinel-2) have only a single band in the 2000–2500 nm shortwave infrared “SWIR2” range where non-pigment biochemical constituents of NPV, including cellulose and lignin, have important spectral absorption features. Thus, these current systems have suboptimal capabilities for characterizing NPV cover. This research used simulated spectral mixtures accounting for variability among NPV and soils to evaluate globally-appropriate hyperspectral and multispectral indices for estimation of fractional NPV cover. The Continuum Interpolated NPV Depth Index (CINDI), a weighted ratio index measuring lignocellulose absorption near 2100 nm, was found to produce the lowest error in estimating NPV cover. CINDI was less sensitive to variability in soil spectra and green vegetation cover than competing indices. While CINDI was sensitive to the relative water content of soil and NPV, this sensitivity allowed for correcting error in estimated NPV cover as water content increased. CINDI bands were less capable than Dual Absorption NPV Index (DANI) bands for maintaining continuity with the heritage Landsat SWIR2 band, but combining multiple CINDI bands demonstrated adequate continuity. Three SWIR2 bands with band centers at 2038, 2108, and 2211 nm can provide superior capabilities for future moderate resolution multispectral/superspectral systems targeting NPV monitoring, including the next generation Landsat mission (Landsat Next). These bands and the associated CINDI index provide potential for global NPV monitoring using a constellation of future superspectral sensors and imaging spectrometers, with applications including improving soil management, preventing land degradation, evaluating impacts of drought, mapping ecosystem disturbance, and assessing wildfire danger.

Index optimization↗
NASA NTRS1999

Antigen S1, encoded by the MIC1 gene, is characterized as an epitope of human CD59, enabling measurement of mutagen-induced intragenic deletions in the AL cell system

S1 cell membrane antigen is encoded by the MIC1 gene on human chromosome 11. This antigen has been widely used as a marker for studies in gene mapping or in analysis of mutagen-induced gene deletions/mutations, which utilized the human-hamster hybrid cell-line, AL-J1, carrying human chromosome 11. Evidence is presented here which identifies S1 as an epitope of CD59, a cell membrane complement inhibiting protein. E7.1 monoclonal antibody, specific for the S1 determinant, was found to react strongly with membrane CD59 in Western blotting, and to bind to purified, urinary form of CD59 in ELISAs. Cell membrane expression of S1 on various cell lines always correlated with that of CD59 when examined by immunofluorescent staining. In addition, E7.1 antibody inhibited the complement regulatory function of CD59. Identification of S1 protein as CD59 has increased the scope of the AL cell system by enabling analysis of intragenic mutations, and multiplex PCR analysis of mutated cells is described, showing variable loss of CD59 exons.

Non-NASA Center↗
NASA NTRS2017

Variability and Trends in the Arctic Sea Ice Cover: Results from Different Techniques

Variability and trend studies of sea ice in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and trends in the Arctic sea ice cover. All four provide generally similar ice patterns but significant disagreements in ice concentration distributions especially in the marginal ice zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new ice and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea ice cover. Hadley and NT1 data usually provide the highest and lowest monthly ice extents, respectively. The Hadley data also show the lowest trends in ice extent and ice area at negative 3.88 percent decade and negative 4.37 percent decade, respectively, compared to an average of negative 4.36 percent decade and negative 4.57 percent decade for all four. Trend maps also show similar spatial distribution for all four with the largest negative trends occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea ice has been retreating the fastest. The good agreement of the trends especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea ice cover.

Arctic↗
NASA NTRSDate not supplied

Building a Bilingual Google Earth Engine Dashboard to Increase Accessibility to Long-term Time Series Remote Sensing Data for Monitoring Saline System Changes in Chile’s Atacama Desert

Saline systems, consisting of salt flats, ponds, and marshes, provide vital water resources to wildlife and communities in northern Chile’s Atacama Desert, one of the driest regions in the world. Mining is extensive in the Atacama, which contains 30% of the world’s lithium reserves and is abundant in potassium and boron. The groundwater that feeds into salt marshes and ponds is extracted in large volumes for mining operations, limiting the availability of water for ecosystems. However, identifying long-term and large-scale environmental impacts from local lithium mining on the saline systems is limited by region inaccessibility and terrain variability. Open access satellite imagery and cloud computing technology has made studying Atacama saline systems feasible and allowed for collaboration across different agencies and countries. The NASA DEVELOP Program partnered with Chile’s la Universidad de La Serena and Servicio Nacional de Geología y Minería (SERNAGEOMIN) to create the Saline Analysis Tool (SalT) in Google Earth Engine (GEE). SalT is used to analyze the extent and distribution of remote saline systems in the Atacama from 1986 to the present day. The tool filters Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data from GEE’s data catalog and creates a single composite image per year for analysis. Additional output analyses include land cover classification, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) raster images that can be displayed on the map interface or exported. The tool can also generate time-lapse videos and charts displaying NDVI, NDWI, and land cover over time. A key feature of the tool is the use of a bilingual graphical user interface to make analysis accessible and customizable to different users’ needs—SalT provides options to select an analysis area, analysis time period, and outputs to display or export. The tool also incorporates new Earth observations as they are added to GEE’s catalog. The ability to easily visualize and analyze long-term remote sensing imagery will enable SERNAGEOMIN and la Universidad de la Serena to continually monitor changes in these saline systems and inform future land management policy.

NASA DEVELOP↗
NASA NTRS1998

Clear-Sky UV-B trends over Northern Midlatitudes derived from TOMS Low-Reflectivity Footprint Measurements

This study investigates the distribution of clear-sky ultraviolet-B (UV-B, wavelengths 290-320 nm) trends in northern midlatitudes using 1979-1991 Nimbus 7 total ozone mapping spectrometer (TOMS) version 7 low-reflectivity (R<0.2) total ozone footprint measurements. The incorporation of essentially cloud-free ozone data from TOMS provides a direct method for separating transient cloud effects from anthropogenic and other dynamical factors present in UV-B. This study has also included both National Oceanic and Atmospheric Administration (NOAA) microwave sounding unit channel 4 (MSU4) and National Centers for Environmental Prediction (NCEP) 500 hPa temperature (T500) fields in our trend models to improve UV-Index (UVI) trend statistics and to investigate the effects of interannual changes in UVI caused by synoptic-scale (horizontal wavelengths 4000-8000 km) and planetary-scale (horizontal wavelengths greater than 8000 km) dynamical events. Clear-sky UVI trends in the northern midlatitudes show large increases (exceeding 10 % per decade) and distinct regional variability especially during winter-spring months which can be attributed to topography and dynamical forcing effects. In the UV-important summer-autumn months, these trends are more uniformly distributed and still statistically significant, although smaller at around +2 to +3 % per decade. Specifically, during April largest increases in midlatitude UVI are seen to extend from near the dateline eastward across North America. In June months largest UVI increases occur over the east Asian continent with values around +5 to +6 % per decade. These increases in UVI over both the Pacific and Asian continent regions persist through summer into Autumn. In the the European sector, statistically significant increases in clear-sky UVI are found over central Europe with values around +2 to +3 % per decade and +8 to +9 % per decade during summer and winter-spring months, respectively. Over the nearby Mediterranean region these seasonal trends are around +2 to +3 and +5 to +6 % per decade.

Ziemke, Jerry↗
NASA NTRS2013

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗
NASA NTRS2014

Grail Refinements to Lunar Seismic Structure

To probe a planet's interior, seismology provides the most direct constraints on the variables that govern the dynamic properties of the body. However, the GRAIL (Gravity Recovery and Interior Laboratory) mission's high-resolution measurements of the lunar gravity field provide constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten). These data complement seismic investigations, and joint interpretation permits improved constraints on the Moon's internal structure. Joint interpretation of disparate geophysical datasets helps reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co-located at one corner. Due to this limited geographical extent, near-surface ray coverage from moonquakes is low, but increase with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefor well suited to joint inversion, since the complementary information reduces inherent model ambiguity. We will perform a joint inversion of Apollo seismic delay times and gravity data collected by GRAIL lunar gravity mission, in order to recover seismic velocity and density as a function of latitude, longitude and depth within the Moon. We will relate density (rho) to seismic velocity (v) using a linear relationship that is allowed to be depth-dependent. The corresponding coefficient (B) can reflect a variety of material properties that vary with depth, including temperature and composition. The inversion seeks to recover the set of rho, v, and B perturbations that minimize (in a least-squares sense) the difference between the observed and calculated data.

Weber, Renee C.↗
NASA NTRS2022

Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case Over Bangladesh

Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.

flood detection↗