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NASA NTRSDate not supplied

Creating Satellite Data Products in the Cloud: SatCORPS Global Cloud Composites

Real time satellite observations and real time derived cloud products are becoming an important tool for both science as well as business ventures. The SatCORPS group leverages public and private cloud-based sources of satellite observations to create its Global Cloud Composite product in near real-time. This dataset allows others access to cloud information that can be accessed directly from the cloud. In this work, we describe the software algorithms and software infrastructure that we have created to create and distribute this product through our hybrid cloud and on-premises system that leverages the strengths and weaknesses of each platform. We will also describe the GCC product itself in terms of the scientific parameters available, resolution and temporal availability. Finally, we will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global cloud products with very low latency which we see that as filling a rapidly growing need in the research, modelling and business community. We present a detailed description of the SatCORPS GCC product in terms of the capabilities and research benefits as well as the delivery architecture in AWS. We take the discussion further and describe the web tools that the SatCORPS group has developed that allow users to access and use the GIS data that it creates.

Global Cloud Composite SatCORPS SMCE AWS↗

DOE OSTI2024

Source apportionment of airborne volatile organic compounds near unconventional oil and gas development

Oil and natural gas (ONG) extraction emits volatile organic compounds (VOCs). Certain VOCs are identified as hazardous air pollutants (HAPS) while others contribute to ozone formation. This study examines the impact of ONG operations on VOC levels during the development of multi-well ONG pads in suburban Broomfield, Colorado. From October 2018 to December 2020, weekly VOC measurements were taken at 18 sites across the area. These included spots near well pads, in adjacent neighborhoods, and at a background site, covering various stages of well pad development including drilling, hydraulic fracturing, flowback, and production. Analysis using Positive Matrix Factorization (PMF) identified six factors, including combustion, background/biogenic sources, light and complex alkanes, drilling activities, and ONG acetylene. Factors linked to local ONG activities exhibited clear temporal and spatial correlations with Broomfield well development. Benzene source analysis revealed distinct contribution gradients, with ONG-related sources notably influencing areas near the well pads, particularly in pre-production. ONG-related weekly benzene contributions varied from 9% to 63% at a community background site and 18% to 89% in a neighborhood close to a well pad.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

$K^{*}(892)^0$ production and the time between freeze-outs in $^{40}$Ar+$^{45}$Sc collisions by NA61/SHINE at the CERN SPS

The analysis of the production of strange $K^{*}(892)^0$ resonances allows us to better understand the temporal evolution of high-energy nucleus--nucleus collisions. In particular, the ratio of $K^{*}(892)^0$ to charged kaon yields is used to determine the time interval between chemical and kinetic freeze-outs. In this paper, the first measurements of $K^{*}(892)^0$ production in central $^{40}$Ar+$^{45}$Sc collisions at the CERN Super Proton Synchrotron are reported. They were performed by NA61/SHINE at collision center-of-mass energies per nucleon pair $\sqrt{s_\mathrm{NN}}$ = 8.8, 11.9, 16.8 GeV. The obtained $\langle K^{*}(892)^0 \rangle/\langle K^{+} \rangle $ and $\langle K^{*}(892)^0 \rangle/\langle K^{-} \rangle$ mean multiplicity ratios are compared with corresponding results in $p$+$p$ collisions, allowing for an estimate of the time interval between chemical and thermal freeze-outs in the $^{40}$Ar+$^{45}$Sc system. These are the first such results reported for $^{40}$Ar+$^{45}$Sc collisions.

Adrich, P. [NCBJ, Warsaw] (ORCID:0000000270195451)↗

NASA NTRS1973

Analysis of noise produced by an orderly structure of turbulent jets

The orderly structure which has been observed recently by numerous researchers within the transition region of subsonic turbulent jets is analyzed to reveal its noise-producing potential. For a circular jet, this structure is molded as a train of toroidal vortex rings which are formed near the jet exit and propagate downstream. The noise produced by the model is evaluated from a reformulation of Lighthill's expression for the far-field acoustic density, which emphasizes the importance of the vorticity within the turbulent flow field. It is shown that the noise production occurs mainly close to the jet exit and depends primarily upon temporal changes in the toroidal radii. The analysis suggests that the process of formation of this regular structure may also be an important contribution of the high-frequency jet noise. These results may be helpful in the understanding of jet-noise generation and in new approaches to jet-noise suppression.

Hardin, J. C.↗

NASA NTRS2019

Generating Accurate and Consistent Top-Of-Atmosphere Reflectance Products from the New Generation Geostationary Satellite Sensors

GeoNEX is a collaborative project by scientists from NASA, NOAA, JAXA, and other organizations around the world with the purpose of generating a suite of Earth-monitoring products using data streams from the latest geostationary (GEO) sensors including the GOES-16/17 ABI and the Himawari-8/9 AHI. An accurate and consistent top-of-atmosphere (TOA) reflectance product, in particular the bidirectional reflectance factor (BRF), is the starting point in the scientific processing chain. We describe the main considerations and corresponding algorithms in generating the GeoNEX TOA BRF product. First, a special advantage of geostationary data streams is their high temporal resolution (~10 minutes per full-disk scan), providing a key source of information for many downstream products. To fully utilize this high temporal frequency demands a high georegistration accuracy for every acquired image. Our analysis shows that there can be substantial georegistration uncertainties in both GOES and Himawari L1b data which we addressed by implementing a phase-based correction algorithm to remove residual errors. Second, geostationary sensors have distinct illumination-view geometry features in that the solar angle changes for every pixel. Therefore, to accurately derive a BRF requires a solar position algorithm and the estimation of the pixel-wise acquisition time within an uncertainty of 10 seconds. Third, we discuss the measures we adopted to check and correct residual radiometric calibration issues of individual sensors to enable time-series analysis as well as the cross calibration between different satellite sensors (including those from low-Earth orbit). Finally, we also explain the rationale for the choice of the global grid/tile system of the GeoNEX TOA BRF product.

Wang, Weile↗

NASA NTRSDate not supplied

Developing A Continuous Ozone Record Through the SAGE and Aura Missions With NASA Reanalysis Products

During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the loss and subsequent recovery of the stratospheric ozone layer. Due to the employed solar occultation and self-calibration method, the SAGE monitors have produced stable data throughout the lifetime of each instrument. However, over ten years passed between the end of the SAGE II and SAGE III/M3M missions in 2005 and the launch of SAGE III/ISS instrument in 2017, leaving a gap in the data that must be bridged in order to assess trends in the ozone record. The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis product, with output available starting in 1980, is an attractive candidate for trend analysis due to the statistically optimized combination of multiple observing systems and the regular temporal and spatial coverage. However, changes in the assimilated observation systems can introduce discontinuities within the MERRA-2 ozone record, such as in 2004 when the MERRA-2 system shifted from assimilating ozone retrievals collected by SBUV instruments to those collected by instruments onboard the Aura satellite. In this study, we explore using the SAGE II record as a transfer function to develop a stable reanalysis data product, suitable for trend analysis, from the start of the SAGE II record in 1984 through the present. We follow the procedure outlined by Wargan et al. (2018) to address discontinuities in the MERRA-2 ozone dataset at the 2004 transition and during the Aura record. SAGE II ozone profiles are used to correct discontinuities in upper stratospheric ozone associated with changes in the MERRA-2 meteorological observing system in 1998 and 1995. We will then assess the relative performance of the data from different SAGE sensors using the resulting bias-corrected MERRA-2 ozone fields.

Pamela Wales↗

NASA NTRS2012

Online Assessment of Satellite-Derived Global Precipitation Products

Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by inter-comparing both versions of TRMM products in their areas of interest. Making this service available to users will help them to better understand associated changes. We plan to implement this inter-comparison in TRMM standard monthly products with the IPWG algorithms. The plans outlined above will complement and accelerate the existing and ongoing validation activities in the community as well as enhance data services for TRMM and the future Global Precipitation Mission (GPM).

Liu, Zhong↗

NASA NTRS2014

Comparing and Reconciling Traditional Field and Photogeologic Mapping Techniques: Lessons from the San Francisco Volcanic Field, Arizona

Cartographic products and - specifically - geologic maps provide critical assistance for establishing physical and temporal frameworks of planetary surfaces. The technical methods that result in the creation of geologic maps vary depending on how observations are made as well as the overall intent of the final products [1-3]. These methods tend to follow a common linear work flow, including the identification and delineation of spatially and temporally discrete materials (units), the documentation of their primary (emplacement) and secondary (erosional) characteristics, analysis of the relative and absolute age relationships between these materials, and the collation of observations and interpretations into an objective map product. The "objectivity" of a map is critical cross comparison with overlapping maps and topical studies as well as its relevance to scientific posterity. However, the "accuracy" and "correctness" of a geologic map is very subject to debate. This can be evidenced by comparison of existing geologic maps at various scales, particularly those compiled through field- and remote-based mapped efforts. Our study focuses on comparing the fidelity of (1) "Apollo-style" geologic investigations, where typically non-geologist crew members follow static traverse routes established through pre-mission planning, and (2) "traditional" field-based investigations, where geologists are given free rein to observe without preplanned routes. This abstract summarizes the regional geology wherein our study was conducted, presents the geologic map created from traditional field mapping techniques, and offers basic insights into how geologic maps created from different tactics can be reconciled in support of exploratory missions. Additional abstracts [4-6] from this study discuss various exploration and science results of these efforts.

Skinner, J. A., Jr.↗

NASA NTRS2007

A Comprehensive Plan for the Long-Term Calibration and Validation of Oceanic Biogeochemical Satellite Data

The primary objective of this planning document is to establish a long-term capability and validating oceanic biogeochemical satellite data. It is a pragmatic solution to a practical problem based primarily o the lessons learned from prior satellite missions. All of the plan's elements are seen to be interdependent, so a horizontal organizational scheme is anticipated wherein the overall leadership comes from the NASA Ocean Biology and Biogeochemistry (OBB) Program Manager and the entire enterprise is split into two components of equal sature: calibration and validation plus satellite data processing. The detailed elements of the activity are based on the basic tasks of the two main components plus the current objectives of the Carbon Cycle and Ecosystems Roadmap. The former is distinguished by an internal core set of responsibilities and the latter is facilitated through an external connecting-core ring of competed or contracted activities. The core elements for the calibration and validation component include a) publish protocols and performance metrics; b) verify uncertainty budgets; c) manage the development and evaluation of instrumentation; and d) coordinate international partnerships. The core elements for the satellite data processing component are e) process and reprocess multisensor data; f) acquire, distribute, and archive data products; and g) implement new data products. Both components have shared responsibilities for initializing and temporally monitoring satellite calibration. Connecting-core elements include (but are not restricted to) atmospheric correction and characterization, standards and traceability, instrument and analysis round robins, field campaigns and vicarious calibration sites, in situ database, bio-optical algorithm (and product) validation, satellite characterization and vicarious calibration, and image processing software. The plan also includes an accountability process, creating a Calibration and Validation Team (to help manage the activity), and a discussion of issues associated with the plan's scientific focus.

Hooker, Stanford B.↗

NASA NTRS1997

Study of the solid-phase thermal decomposition of NTO using Simultaneous Thermogravimetric Modulated Beam Mass Spectrometry (STMBMS)

The solid phase thermal reaction chemistry of NTO between 190 and 250 C is presently being evaluated by utilizing STMBMS, a technique that enables the authors to measure the vapor pressure of NTO and to explore the reaction mechanisms and chemical kinetics associated with the NTO thermal decomposition process. The vapor pressure of NTO is expressed as Log(sub 10) p(torr) = 12.5137 + 6,296.553(1/t(k)) and the Delta-H(sub subl) = 28.71 +/- 0.07 kcal/mol (120.01 +/- 0.29 kJ/mol). The pyrolysis of NTO results in the formation of gaseous products and a condensed-phase residue. The identity of the major gaseous products and their origin from within the NTO molecules are determined based on the results from pyrolysis of NTO, NTO-3-C-13, NTO-1,2- (15)N2 and NTO-(2)H2. Identification of the products show the major gaseous products to be N2, CO2, NO, HNCO, H2O and some N2O, CO, HCN and NH3. The N2 is mostly derived from the N-1 and N-2 positions with some being from the N-4 and N-1 or N-2 positions. The CO2 is derived from both carbons in the NTO molecule in comparable amounts. The residue has an elemental formula of C(2.1)H(.26)N(2.9)O and FTIR analysis suggests that the residue is polyurea- and polycarbamate- like in nature. The temporal behaviors of the rates of formation of the gaseous products indicate that the overall thermal decomposition of NTO in the temperature range evaluated involves four major processes: (1) NTO sublimation; (2) an apparent solid-solid phase transition between 190 and 195 C; (3) a decomposition regime induced by the presence of exogenous H2O at the onset of decomposition; and (4) a decomposition regime that occurs at the onset of decomposition and continues until the depletion of NTO. Decomposition pathways that are consistent with the data are presented.

Minier, L.↗

DOE OSTI2026

Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities

The North American arctic and boreal regions (ABRs) are rapidly warming and experiencing intensifying disturbances. Accurately quantifying aboveground biomass (AGB) is critical for understanding the impacts of these changes on the carbon cycle and for designing climate change mitigation strategies. Several AGB maps have been developed for the North American ABRs, including recent contributions from National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment (ABoVE) campaign. However, these maps differ widely in training data, methodology, and resulting AGB density estimates. Presently, a comprehensive comparative evaluation is lacking, making it difficult for users to select datasets suited to their research or management needs. Here, in this study, we conducted a comparative analysis of nine AGB density datasets across North American ABRs, specifically for Alaska and Canada. We (1) summarized AGB by ecoregion and Canadian provinces, (2) evaluated their accuracy against field-based measurements, (3) analyzed spatial and temporal similarities among datasets, and (4) assessed their ability to capture disturbance (fire and harvest) impacts on AGB. We found substantial variation in regional and local AGB estimates across datasets, with overall accuracy ranging from R 2 = 0.25–0.62 and Bias% from −47.8% to 69.9% when validated against field plots. Despite these differences, most datasets have comparatively consistent spatial patterns in AGB (r > 0.8 for most cases). In contrast, agreement on the temporal patterns of AGB change is generally low. We found datasets with spatial resolutions ⩽300 m are capable of capturing disturbance impacts on AGB dynamics, though sensitivity varies across products. Our findings and dataset summary provide guidance for selecting appropriate AGB datasets for different applications within our study area. Our analysis also highlights the need to decrease map bias and increase capability to detect temporal change to decrease uncertainty of AGB datasets potentially by using training data which is representative of major plant functional types within the mapped area.

ABoVE↗

NASA NTRS2000

TRMM Surface Backscatter Measurements - Temporal and Spatial Analysis: Inter-Comparison with NSCAT

Global rainfall is the primary redistributor of earth's energy by the process of latent heat release. This forms the main driving force for the tropical circulation, which in turn impacts the global circulation .through transient events-such as El Nino. Hence, more precise and long-term time series of the rainfall and its variability is crucial to the understanding and prediction of the global climate and climate change. The Precipitation Radar (PR) abroad the US/Japan Tropical Rainfall Measuring Mission (TRMM) is the first radar ever launched into space that measures detailed vertical profiles of rain intensity over the tropics. One of the challenges in estimating rainfall from spaceborne radars is the presence of attenuation at frequencies, such as 14 GHz of the TRMM PR and future planned systems at this and higher frequencies. A common approach in current rainfall retrieval algorithms is to employed the path integrated attenuation (PIA) as a constraint to the retrieval, and hence overcome errors in the radar calibration or in the assumed rainfall parameters. PIA can either be derived from a radiometer or from the surface reference technique, in which a clear air radar measurement is compared with the measurement in the raining area. The current TRMM 2A21 PIA data product makes use of both a temporal and spatial clear air database for comparison to rainy measurements. In this paper we present results from analysis of TRMM surface backscatter cross-section (sigmaO) measurements from Nov 97-Feb99, and a comparison with sigmaO measurements obtained by the NASA Scatterometer (NSCAT) between Sept96-June97. Measurements for a given month from both instruments are compiled on a 1 deg. (lat.) x 1 deg. (lon.) x 1 hr. grid. This enables TRMM--NSCAT comparison and the investigation of seasonal and diurnal trends in both data sets. From preliminary analysis of TRMM sigmaO's we have decided not to treat the ocean as a single homogeneous region but to select a number of ocean sub-regions and individually analyze their trends. Likewise, and in a similar approach to previous studies of Seasat over-land data, we have selected a number of over-land regions for study. From said sigmaO maps and regional trend analysis we investigate possible sources of trends and variability. In addition, we study the effects of TRMM PR sensitivity through the PR "possible rain" class. Given NSCAT's inability to flag rain contaminated measurements we are able to gauge the impact of rain contamination on NSCAT monthly sigmaO maps, using TRMM measurements. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA), U.S.A.

Im, Eastwood↗

NASA NTRS2011

Exploring Fermi-LAT Extended GeV Emission with Stacking Analysis

Temporally extended emission at energies> 100 MeV have been seen nearly all of the bright GRBs detected by Fermi-LAT. The production mechanism and relationship to broadband afterglow emission remains controversial without detailed simultaneous multi-wavelength observations on individual sources. We explore this problem by stacking separately, the gamma-ray and X-ray emission for -150 Swift GRBs over the first few thousand seconds of overlapping observations after a trigger, and discuss the potential presence of an additional spectral component.

Racusin, Judith L.↗

DOE OSTI2026

Daily, 30 m Resolution NDSI Data for the East River Watershed, CO for 2000-2020

This dataset contains daily Normalized Difference Snow Index (NDSI) values at 30 m spatial resolution for the East River watershed in Colorado, USA. The temporal range of these data includes water years 2001-2020. These data were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). This model fuses low spatial and high temporal resolution data from MODIS (500 m, daily) with high spatial and low temporal resolution data from Landsat (30 m, 16 days) to create a 30m synthetic daily snow product. This product allows for the analysis of historical snow covered area trends in the East River Watershed at fine spatiotemporal resolutions where it was not available previously. This research was performed as a part of the Department of Energy’s Subsurface Biogeochemical Research Program with the primary intent of better understanding the timing and spatial patterns of water delivery to the Critical Zone in mountain watersheds. Each .zip file contains one "water year" of data (October 1 - September 30; i.e., water year 2010 starts October 1, 2010 and ends September 30, 2011). Each zip file contains the following: STARFM daily Normalized Difference Snow Index (NDSI) fusion data files in GeoTiff format with one layer for each day between Landsat data acquisition dates (i.e., for dates of Landsat acquisition, the Landsat image is included for that date). The study area is located in an area of Landsat path overlap, so Landsat dates acquisitions are every 7-9 days. Landsat NDSI files containing the high spatial (30m), low temporal (7-9 days due to Landsat path overlap) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Dates for which no Landsat data were obtained are included as NoData layers. MODIS NDSI files containing the high temporal (daily), low spatial (500m) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Please note the MODIS data were resampled to 30m pixels for input into the STARFM model. The data have a scale factor of 10,000 and a no data value of -32767. The projection of all datasets is WGS 84 (EPSG: 4326), which has a latitude/longitude based degree resolution of 0.0002694946 X 0.0002694946, and approximates to the 30 m spatial resolution mentioned above. The Layer Index files in .csv format. They contain information for each layer in the above GeoTiff files regarding the corresponding date for each layer, the fraction of pixels in the image that contain valid data (missing data is due to either cloud cover or poor data quality; these values are not percent snow cover). Dates of Landsat overpass are indicated in these files. If no Landsat data were able to be obtained due to cloud cover or lack of Landsat Tier 1 data available on Google Earth Engine, this is also noted.

EARTH SCIENCE > CRYOSPHERE > SNOW/ICE↗

DOE OSTI2026

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space-for-time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water-limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall. Our analysis identified the cause of the difference to be primarily driven by the seasonal variability of water availability, rooting depth, and soil properties. When using soil moisture instead of precipitation, we observed widespread convergence in the spatial and temporal sensitivities—that is, the two sensitivities became much more similar in magnitude across all water-limited ecosystems within CONUS. These results show that overlooking soil hydrology can inflate perceived discrepancies between spatial and temporal vegetation sensitivities, leading to biased projections of ecosystem dynamics under future hydro-climatic change.

Wang, Huiqi [University of California, Berkeley, C↗

NASA NTRS2016

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Climate↗

NASA NTRS2015

Implications of Climate Mitigation for Future Agricultural Production

Climate change is projected to negatively impact biophysical agricultural productivity in much of the world. Actions taken to reduce greenhouse gas emissions and mitigate future climate changes, are thus of central importance for agricultural production. Climate impacts are, however, not unidirectional; some crops in some regions (primarily higher latitudes) are projected to benefit, particularly if increased atmospheric carbon dioxide is assumed to strongly increase crop productivity at large spatial and temporal scales. Climate mitigation measures that are implemented by reducing atmospheric carbon dioxide concentrations lead to reductions both in the strength of climate change and in the benefits of carbon dioxide fertilization. Consequently, analysis of the effects of climate mitigation on agricultural productivity must address not only regions for which mitigation is likely to reduce or even reverse climate damages. There are also regions that are likely to see increased crop yields due to climate change, which may lose these added potentials under mitigation action. Comparing data from the most comprehensive archive of crop yield projections publicly available, we find that climate mitigation leads to overall benefits from avoided damages at the global scale and especially in many regions that are already at risk of food insecurity today. Ignoring controversial carbon dioxide fertilization effects on crop productivity, we find that for the median projection aggressive mitigation could eliminate approximately 81% of the negative impacts of climate change on biophysical agricultural productivity globally by the end of the century. In this case, the benefits of mitigation typically extend well into temperate regions, but vary by crop and underlying climate model projections. Should large benefits to crop yields from carbon dioxide fertilization be realized, the effects of mitigation become much more mixed, though still positive globally and beneficial in many food insecure countries.

Mueller, Christoph↗

NASA NTRS2018

Application of Aura OMI L2G Products Compared with NASA MERRA-2 Assimilation

The Ozone Monitoring Instrument (OMI) is one of the instruments aboard NASA's Aura satellite. It measures ozone total column and vertical profile, aerosols, clouds, and trace gases including NO2, SO2, HCHO, BrO, and OClO using absorption in the ultraviolet electromagnetic spectrum (280 - 400 nm). OMI Level-2G (L2G) products are based on the pixel-level OMI granule satellite measurements stored within global 0.25 deg. X 0.25 deg. grids, therefore they conserve all the Level 2 (L2) spatial and temporal details for 24 hours of scientific data in one file. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis, using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. MERRA-2 includes aerosol data reanalysis and improved representations of stratospheric ozone, compared with its predecessor MERRA, in both instantaneous and time-averaged collections. It is found that simply comparing satellite Level-3 products might cause biases, due to lack of detailed temporal and original retrieval information. It is therefore preferable to inter-compare or implement satellite derived physical quantities directly with/to model assimilation with as high temporal and spatial resolutions as possible. This study will demonstrate utilization of OMI L2G daily aerosol and ozone products by comparing them with MERRA-2 hourly aerosol/ozone simulations, matched in both space and time aspects. Both OMI and MERRA-2 products are accessible online through NASA Goddard Earth Sciences Data Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/).

OMI L2G products↗