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At least 163 records · Page 9
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NASA NTRS2001

The Evaluation of the Regional Atmospheric Modeling System in the Eastern Range Dispersion Assessment System

The Applied Meteorology Unit (AMU) evaluated the Regional Atmospheric Modeling System (RAMS) contained within the Eastern Range Dispersion Assessment System (ERDAS). ERDAS provides emergency response guidance for Cape Canaveral Air Force Station and Kennedy Space Center operations in the event of an accidental hazardous material release or aborted vehicle launch. The RAMS prognostic data are available to ERDAS for display and are used to initialize the 45th Space Wing/Range Safety dispersion model. Thus, the accuracy of the dispersion predictions is dependent upon the accuracy of RAMS forecasts. The RAMS evaluation consisted of an objective and subjective component for the 1999 and 2000 Florida warm seasons, and the 1999-2000 cool season. In the objective evaluation, the AMU generated model error statistics at surface and upper-level observational sites, compared RAMS errors to a coarser RAMS grid configuration, and benchmarked RAMS against the nationally-used Eta model. In the subjective evaluation, the AMU compared forecast cold fronts, low-level temperature inversions, and precipitation to observations during the 1999-2000 cool season, verified the development of the RAMS forecast east coast sea breeze during both warm seasons, and examined the RAMS daily thunderstorm initiation and precipitation patterns during the 2000 warm season. This report summarizes the objective and subjective verification for all three seasons.

Case, Jonathan↗
NASA NTRS2002

Urban Surface Radiative Energy Budgets Determined Using Aircraft Scanner Data

It is estimated that by the year 2025, 80% of the world's population will live in cities. The extent of these urban areas across the world can be seen in an image of city lights from the Defense Meteorological Satellite Program. In many areas of North America and Europe, it is difficult to separate individual cities because of the dramatic growth and sprawl of urbanized areas. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. One of the earliest recognized and measured phenomena of urbanization is the urban heat island (UHI) which was reported as early as 1833 for London and 1862 for Paris. The urban heat island results from the energy that is absorbed by man-made materials during the day and is released at night resulting in the heating of the air within the urban area. The magnitude of the air temperature difference between the urban and surrounding countryside is highly dependent on the structure of the urban area, amount of solar immolation received during the day, and atmospheric conditions during the night. These night time air temperature differences can be in the range of 2 to 5 C. or greater. Although day time air temperature differences between urban areas and the countryside exists during the day, atmospheric mixing and stability reduce the magnitude. This phenomena is not limited to large urban areas, but also occurs in smaller metropolitan areas. The UHI has significant impacts on the urban air quality, meteorology, energy use, and human health. The UPI can be mitigated through increasing the amount of vegetation and modification of urban surfaces using high albedo materials for roofs and paved surfaces. To understand why the urban heat island phenomenon exists it is useful to define the surface in terms of the surface energy budget. Surface temperature and albedo is a major component of the surface energy budget. Knowledge of it is important in any attempt to describe the radiative and mass fluxes which occur at the surface. Use of energy terms in modeling surface energy budgets allows the direct comparison of various land surfaces encountered in a urban landscape, from vegetated (forest and herbaceous) to non-vegetated (bare soil, roads, and buildings). These terms are also easily measured using remote sensing from aircraft or satellite platforms allowing one to examine the spacial variability. The partitioning of energy budget terms depends on the surface type. In natural landscapes, the partitioning is dependent on canopy biomass, leaf area index, aerodynamic roughness, and moisture status, all of which are influenced by the development stage of the ecosystem. In urban landscapes, coverage by man-made materials substantially alters the surface face energy budget. The remotely sensed data obtained from aircraft and satellites, when properly calibrated allows the measurement of important terms in the radiative surface energy budget a urban landscape scale.

Luvall, Jeffrey C.↗
NASA NTRS2002

Energetic Electron Populations in the Magnetosphere During Geomagnetic Storms and Substorms

This report summarizes the scientific work performed by the Aerospace Corporation under NASA Grant NAG5-10278, 'Energetic Electron Populations in the Magnetosphere during Geomagnetic Storms and Subsisting.' The period of performance for the Grant was March 1, 2001 to February 28, 2002. The following is a summary of the Statement of Work for this Grant. Use data from the PIXIE instrument on the Polar spacecraft from September 1998 onward to derive the statistical relationship between particle precipitation patterns and various geomagnetic activity indices. We are particularly interested in the occurrence of substorms during storm main phase and the efficacy of storms and substorms in injecting ring-current particles. We will compare stormtime simulations of the diffuse aurora using the models of Chen and Schulz with stormtime PIXIE measurements.

McKenzie, David L.↗
NASA NTRS2003

Dayside Proton Aurora: Comparisons between Global MHD Simulations and Image Observations

The IMAGE mission provides a unique opportunity to evaluate the accuracy of current global models of the solar wind interaction with the Earth's magnetosphere. In particular, images of proton auroras from the Far Ultraviolet Instrument (FUV) onboard the IMAGE spacecraft are well suited to support investigations of the response of the Earth's magnetosphere to interplanetary disturbances. Accordingly, we have modeled two events that occurred on June 8 and July 28, 2000, using plasma and magnetic field parameters measured upstream of the bow shock as input to three-dimensional magnetohydrodynamic (MHD) simulations. This paper begins with a discussion of images of proton auroras from the FUV SI-12 instrument in comparison with the simulation results. The comparison showed a very good agreement between intensifications in the auroral emissions measured by FUV SI-12 and the enhancement of plasma flows into the dayside ionosphere predicted by the global simulations. Subsequently, the IMAGE observations are analyzed in the context of the dayside magnetosphere's topological changes in magnetic field and plasma flows inferred from the simulation results. Finding include that the global dynamics of the auroral proton precipitation patterns observed by IMAGE are consistent with magnetic field reconnection occurring as a continuous process while the iMF changes in direction and the solar wind dynamic pressure varies. The global simulations also indicate that some of the transient patterns observed by IMAGE are consistent with sporadic reconnection processes. Global merging patterns found in the simulations agree with the antiparallel merging model. though locally component merging might broaden the merging region, especially in the region where shocked solar wind discontinuities first reach the magnetopause. Finally, the simulations predict the accretion of plasma near the bow shock in the regions threaded by newly open field lines on which plasma flows into the dayside ionosphere are enhanced. Overall the results of these initial comparisons between global MHD simulation results and IMAGE observations emphasize the interplay between reconnection and dynamic pressure processes at the dayside magnetopause. as well as the intricate connection between the bow shock and the auroral region.

Berchem, J.↗
NASA NTRS2006

Self-Consistent Model of Magnetospheric Ring Current and Propagating Electromagnetic Ion Cyclotron Waves: Waves, Precipitating Ring Current Ions, and Thermal Electron Heating - 2

This paper is dedicated to further presentations and discussions of the results from our new global self-consistent theoretical model of interacting ring current ions and electromagnetic ion cyclotron waves [Khazanov et al., 2006; here referred to as Paper 1]. In order to adequately take into account the wave propagation and refraction in a multi-ion plasmasphere, we explicitly include the ray tracing equations in our previous self-consistent model and use the general form of the wave kinetic equation [for details see Paper 1]. To demonstrate the effects of the EMIC wave propagation and refraction on the RC proton precipitations and heating of the thermal plasmaspheric electrons we simulate the May 1998 storm. The main findings of our simulation can be summarized as follows. Firstly, the wave induced precipitations have a quite fine structure, and are highly organized by location of the plasmapause gradient. The strongest fluxes of about 4 (raised dot) 10(exp 6) [(cm (raised dot) s (raised dot) sr)(sup -l)] are observed during the main and early recovery phases of the storm. The very interesting and probably more important finding is that in a number of cases the most intense precipitating fluxes are not simply connected to the most intense EMIC waves. The character of the EMIC wave power spectral density distribution over the equatorial wave normal angle is an extremely crucial for the effectiveness of the RC ion scattering. Secondly, comparison of the global proton precipitating patterns with the results from other ring current model [Kozyra et al., 1997] reveals that although we observe a qualitative agreement between localizations of the wave induced fluxes in the models, there is no quantitative agreement between the magnitudes of these fluxes. These differences are mainly due to a qualitative difference between the characters of the EMIC wave power spectral density distributions over the equatorial wave normal angle. Finally, the two energy sources to the plasmaspheric electrons are considered; (i) the heat fluxes caused by the EMIC wave energy absorption due to Landau resonance, and (ii) the heat fluxes due to Coulomb energy degradation of the RC o(+) ions. The heat fluxes caused by the EMIC wave energy absorption due to Landau resonance are observed in the postnoon-premidnight MLT sector, and maximize at the magnitude of 10l1 (eV/(cm(sup 2)(raised dot) s) at L=3.25, MLT=22 at 3400 UT after 1 May, 0000 UT. The greatest Coulomb energy deposition rates are about 2 (raised dot) 10(sup 10)(eV/(cm(sup 2)(raised dot) s) and observed during two periods; 32-48 hours, and 76-86 hours after 1 May, 0000 UT. The theoretically derived spatial structure of the thermal electron heating caused by interaction of the RC with plasmasphere is strongly supported by concurrent and conjugate plasma measurements from the plasmasphere, the RC, and the topside ionosphere [Gurgiolo et al., 20051.

Khazanov, G. V.↗
NASA NTRS2007

TRMM's Contribution to Our Knowledge of Climatology, Storms and Floods

The Tropical Rainfall Measuring Mission (TRMM) has successfully completed nearly ten years in orbit. A brief review of the history and accomplishments of this joint mission between the U.S. and Japan is presented. Research highlights will focus on the seasonal cycle of a TRMM-based rainfall climatology, which takes advantage of the multiple rain estimates available from TRMM. Examples will be given of the use of TRMM data to diagnose the impact of man on precipitation patterns through urbanization and the effect of pollution. Use of TRMM data for tropical cyclone operational analysis in the U.S. will also be shown. Methods for generating 3-hourly rainfall information from multiple satellites using TRMM to calibrate all the information will be described as will application of such information to study extreme rainfall events and associated floods and landslides. These results will emphasize the breadth of science success achieved with the 10-year record of observations from the only rain radar and passive microwave instrument combination in space. The outlook for continued operation of the TRMM satellite and progress in TRMM science and applications will be addressed.

Adler, Robert↗
NASA NTRS2010

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily morning forecast for ground and space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45th Weather Squadron (45 WS) must issue forecast advisories for KSC/CCAFS when they expect peak gusts for >= 25, >= 35, and >= 50 kt thresholds at any level from the surface to 300 ft. In Phase I of this task, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a cool-season (October - April) tool to help forecast the non-convective peak wind from the surface to 300 ft at KSC/CCAFS. During the warm season, these wind speeds are rarely exceeded except during convective winds or under the influence of tropical cyclones, for which other techniques are already in use. The tool used single and multiple linear regression equations to predict the peak wind from the morning sounding. The forecaster manually entered several observed sounding parameters into a Microsoft Excel graphical user interface (GUI), and then the tool displayed the forecast peak wind speed, average wind speed at the time of the peak wind, the timing of the peak wind and the probability the peak wind will meet or exceed 35, 50 and 60 kt. The 45 WS customers later dropped the requirement for >= 60 kt wind warnings. During Phase II of this task, the AMU expanded the period of record (POR) by six years to increase the number of observations used to create the forecast equations. A large number of possible predictors were evaluated from archived soundings, including inversion depth and strength, low-level wind shear, mixing height, temperature lapse rate and winds from the surface to 3000 ft. Each day in the POR was stratified in a number of ways, such as by low-level wind direction, synoptic weather pattern, precipitation and Bulk Richardson number. The most accurate Phase II equations were then selected for an independent verification. The Phase I and II forecast methods were compared using an independent verification data set. The two methods were compared to climatology, wind warnings and advisories issued by the 45 WS, and North American Mesoscale (NAM) model (MesoNAM) forecast winds. The performance of the Phase I and II methods were similar with respect to mean absolute error. Since the Phase I data were not stratified by precipitation, this method's peak wind forecasts had a large negative bias on days with precipitation and a small positive bias on days with no precipitation. Overall, the climatology methods performed the worst while the MesoNAM performed the best. Since the MesoNAM winds were the most accurate in the comparison, the final version of the tool was based on the MesoNAM winds. The probability the peak wind will meet or exceed the warning thresholds were based on the one standard deviation error bars from the linear regression. For example, the linear regression might forecast the most likely peak speed to be 35 kt and the error bars used to calculate that the probability of >= 25 kt = 76%, the probability of >= 35 kt = 50%, and the probability of >= 50 kt = 19%. The authors have not seen this application of linear regression error bars in any other meteorological applications. Although probability forecast tools should usually be developed with logistic regression, this technique could be easily generalized to any linear regression forecast tool to estimate the probability of exceeding any desired threshold . This could be useful for previously developed linear regression forecast tools or new forecast applications where statistical analysis software to perform logistic regression is not available. The tool was delivered in two formats - a Microsoft Excel GUI and a Tool Command Language/Tool Kit (Tcl/Tk) GUI in the Meteorological Interactive Data Display System (MIDDS). The Microsoft Excel GUI reads a MesoNAM text file containing hourly forecasts from 0 to 84 hours, from one model run (00 or 12 UTC). The GUI then displays e peak wind speed, average wind speed, and the probability the peak wind will meet or exceed the 25-, 35- and 50-kt thresholds. The user can display the Day-1 through Day-3 peak wind forecasts, and separate forecasts are made for precipitation and non-precipitation days. The MIDDS GUI uses data from the NAM and Global Forecast System (GFS), instead of the MesoNAM. It can display Day-1 and Day-2 forecasts using NAM data, and Day-1 through Day-5 forecasts using GFS data. The timing of the peak wind is not displayed, since the independent verification showed that none of the forecast methods performed significantly better than climatology. The forecaster should use the climatological timing of the peak wind (2248 UTC) as a first guess and then adjust it based on the movement of weather features.

Barrett, Joe H., III↗
NASA NTRS2011

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via satellite is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and satellite data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). In the current project MODIS data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability over large regions. Hence the use of satellite data is critical to observe Juniperus spp. pollen phenology. MODIS data was used to observe Juniperus spp. pollen phenology. The MODIS surface reflectance product(MOD09) provided information on the Juniper spp. cone formation and cone density (Fig 1). Ground based observational records of pollen release timing and quantities were used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS.

Luvall, J. C.↗
NASA NTRS2011

Urban Heat Islands

It is estimated that by the year 2025, 80% of the world's population will live in cities. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. Research studies from many cities have documented these effects range from decreases in air quality, increased energy consumption and alteration of regional climate to direct effects on human health.

Luvall, Jeffrey C.↗
NASA NTRS2012

Linking Plasma Conditions in the Magnetosphere with Ionospheric Signatures

Modeling of the full magnetosphere, ring current and ionosphere system has become an indispensable tool in analyzing the series of events that occur during geomagnetic storms. The CCMC has a full model suite available for the magnetosphere, together with visualization tools that allow a user to perform a large variety of analyses. The January, 21, 2005 storm was a moderate-size storm that has been found to feature a large penetration electric field and unusually large polar caps (low-latitude precipitation patterns) that are otherwise found in super storms. Based on simulations runs at CCMC we can outline the likely causes of this behavior. Using visualization tools available to the online user we compare results from different magnetosphere models and present connections found between features in the magnetosphere and the ionosphere that are connected magnetically. The range of magnetic mappings found with different models can be compared with statistical models (Tsyganenko) and the model's fidelity can be verified with observations from low earth orbiting satellites such as DMSP and TIMED.

Rastaetter, Lutz↗
NASA NTRS2016

CubeSat Constellation Cloud Winds(C3Winds) A New Wind Observing System to Study Mesoscale Cloud Dynamics and Processes

The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to better understand mesoscale dynamics and their structures in severe weather systems. With potential catastrophic damage and loss of life, strong extratropical and tropical cyclones (ETCs and TCs) have profound three-dimensional impacts on the atmospheric dynamic and thermodynamic structures, producing complex cloud precipitation patterns, strong low-level winds, extensive tropopause folds, and intense stratosphere-troposphere exchange. Employing a compact, stereo IR-visible imaging technique from two formation-flying CubeSats, C3Winds seeks to measure and map high-resolution (2 km) cloud motion vectors (CMVs) and cloud geometric height (CGH) accurately by tracking cloud features within 5-15 min. Complementary to lidar wind observations from space, the high-resolution wind fields from C3Winds will allow detailed investigations on strong low-level wind formation in an occluded ETC development, structural variations of TC inner-core rotation, and impacts of tropopause folding events on tropospheric ozone and air quality. Together with scatterometer ocean surface winds, C3Winds will provide a more comprehensive depiction of atmosphere-boundary-layer dynamics and interactive processes. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with potential of increased diurnal sampling via CubeSat constellation.

mesoscale dynamics↗
NASA NTRS2016

Precipitation and Carbon-Water Coupling Jointly Control the Interannual Variability of Global Land Gross Primary Production

Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.

chlorophyll fluorescence↗
NASA NTRS2017

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Perlwitz, J.↗
NASA NTRS2018

Sub-Seasonal Forecasting of the Stratospheric Wave Events, Sudden Stratospheric Warmings, and Their Influence on the Troposphere

Stratospheric wave events and major sudden stratospheric warming (SSW) events are well captured in high-resolution global forecasts out to 10 days. Tropospheric influences of SSW include statistically significant shifts in the storm tracks and associated surface temperature and precipitation pattern changes. Since these events can in turn influence the troposphere on time scales of 30-60 days the ability to predict these events and the subsequent long-term response on time scales beyond 10 days is of interest. Here we examine the prediction of stratospheric wave events and their evolution using the NASA GMAO (Global Modeling and Assimilation Office) Sub-Seasonal to Seasonal (S2S) system. This is a recently released subseasonal to seasonal forecast system, GEOS-S2S version 2.1. Compared to GMAO's previous system, the new version runs at higher atmospheric resolution (approximately 1/2 degree globally), contains a substantially improved model of the cryosphere, includes additional interactive aerosol model components, and the ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter. Results are based on a comprehensive series of hindcasts starting from the year 2000. They show that while the S2S system is not as accurate at 10 days in forecasting major SSW events as the NASA GMAO Forward Processing system, it can usefully predict stratospheric anomalies out to 20 days and the subsequent stratospheric/tropospheric evolution beyond 30 days.

Coy, L.↗
NASA NTRS2018

Climate Change Impacts on Agriculture: Challenges, Opportunities, and AgMIP Frameworks for Foresight

Agricultural systems are currently undergoing rapid shifts owing to socioeconomic development, technological change, population growth, economic opportunity, evolving demand for commodities, and the need for sustainability amid global environmental change. It is not sufficient to maintain current harvest levels; rather, there is a need to rapidly increase production in light of a population growing to nearly 10 billion by mid-century and to more than 11 billion by 2100 (FAO, 2016; UN, 2016; Popkin et al., 2012). Current and future agricultural systems are additionally burdened by human-caused climate change, the result of accumulating greenhouse gas and aerosol emissions, ecological destruction, and land use changes that have altered the chemical composition of Earth’s atmosphere and trapped energy in the Earth system (IPCC, 2013; Porter et al., 2014). This increased energy has already raised average surface temperatures by approximately 1 degree Centigrade (GISTEMP Team, 2017; Hansen et al., 2010), leading early on to the term “global warming,” but this phenomenon is now more accurately referred to as “climate change” because it also modifies atmospheric circulation, adjusts regional and seasonal precipitation patterns, and shifts the distribution and characteristics of extreme events (Bindoff et al., 2013; Collins et al., 2013). Food and health systems face increasing risk owing to progressive climate change now manifesting itself as more frequent, severe extreme weather events—heat waves, droughts, and floods (IPCC, 2013). Often without warning, weather-related shocks can have catastrophic and reverberating impacts on the increasingly exposed global food system—through production, processing, distribution, retail, disposal, and waste. Simultaneously, malnutrition and ill health are arising from lack of access to nutritious food, exacerbated in crises such as food price spikes or shortages. For some countries, particularly import-dependent low-income countries, weather shocks and price spikes can lead to social unrest, famine, and migration.

Ruane, Alex C.↗
NASA NTRS2019

Significant Spatial Variability in Radar-Derived West Antarctic Accumulation Linked to Surface Winds and Topography

Across the Antarctic Ice Sheet, accumulation heavily influences firn compaction and surface height changes. Therefore, accumulation varies over short distances (<25 km), complicating the derivation of ice sheet mass changes from altimetry and reducing how accurately field measurements can be spatially extrapolated. However, current atmospheric reanalyses have grid spacings (>25 km) that are too coarse to resolve this variability. To address this limitation, we construct a fine-scale accumulation product from airborne snow radar observations by superimposing along-track fluctuations in accumulation onto an atmospheric reanalysis product. Our resulting airborne product reflects large-scale (>25 km) orographic precipitation patterns while providing robust and unprecedented insight into Antarctic accumulation variability on subgrid scales. On these smaller scales, we find significant, regionally dependent accumulation variability (𝜎(sub relative) > 40%). This variability in accumulation is correlated with variability in topographic surface slope in the wind direction (p < 0.01), confirming that subgrid-scale accumulation variability is driven by snow redistribution by wind.

Dattler, Marissa E.↗
NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Agriculture and Food Security Applications: A Summary of NASA’s DEVELOP Program and Projects in Central and South America

NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including two feasibility studies that focused on monitoring drought and precipitation patterns and their impacts on agriculture in Guatemala, Honduras, El Salvador, and Nicaragua using EO from Terra MODIS and GPM. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of agriculture and food security.

Capacity Building↗
NASA NTRSDate not supplied

Auroral ovals versus flare ribbons: Optical footprints of explosive magnetic field reconfiguration in Earth’s magnetosphere and the Sun’s corona

Despite drastically different plasma conditions in the two systems, eruptive energy release events in solar active regions and in Earth’s magnetosphere have a lot in common. Both solar active region eruptions and the substorm activity in the nightside magnetosphere are known to be associated with an abrupt large-scale reorganization of the supporting magnetic systems enabling the conversion and dissipation of the stored free magnetic energy. The rate of energy accumulation in either system tends to be by orders of magnitude slower than the energy release rate, leading to the formation of an impulsive loading-unloading cycle involving a relatively long pre-reconnection phase (substorm growth phase, pre-flare stressing of an active region magnetic field), a short and explosive reconnection phase (substorm breakup and expansion, eruptive flares and CMEs), and a prolonged post-reconnection phase (substorm recovery phase and the post-flare active region reconfiguration). In Earth’s magnetosphere, this loading-unloading cycle is diagnosed by monitoring characteristic changes in the particle precipitation pattern in the northern and southern auroral ovals marking the boundary between the open and close magnetic flux. The position, shape, structure, and dynamics of the auroral borealis were shown to communicate critically important information about an upcoming substorm, the location and timing of the initial reconnection onset, and the subsequent return of the magnetosphere to a lower-energy state. On the Sun, a similar role is played by the chromospheric flare ribbons which enable a detailed diagnostics of the overlying reconnecting magnetic field. In this talk, we’ll discuss similarities and differences in using auroral and flare ribbon observations for monitoring eruptive energy release in respectively Earth’s magnetosphere and solar corona. Special emphasis will be placed on the quantitative interpretation of the two types of optical signatures for empirical diagnostics of the underlying reconnection activity and for constraining its theoretical models. We’ll also compare forecasting capabilities of the two types of optical signatures in the context of space weather prediction objectives.

V. M. Uritskiy↗