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A detailed mathematical model is presented for the temporal and spatial accurate modeling of solid-fluid reactions in porous particles for which volumetric reaction rate data is known a priori and both the porosity and the permeability of the particle are large enough to allow for continuous gas flow.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
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 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.
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/).
The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the five Earth-observing instruments on-board the National Aeronautics and Space Administration (NASA) Earth-Observing System(EOS) Terra spacecraft, launched in December 1999. It has 36 spectral bands with wavelengths ranging from 0.41 to 14.4 mm and collects data at three nadir spatial resolutions: 0.25 km for 2 bands with 40 detectors each, 0.5 km for 5 bands with 20 detectors each and 1 km for the remaining 29 bands with 10 detectors each. MODIS bands are located on four separate focal plane assemblies (FPAs) according to their spectral wavelengths and aligned in the cross-track direction. Detectors of each spectral band are aligned in the along-track direction. MODIS makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the reflective solar bands (RSBs) include a solar diffuser (SD), a solar diffuser stability monitor (SDSM) and a spectral-radiometric calibration assembly (SRCA). Calibration is performed for each band, detector, sub-sample (for sub-kilometer resolution bands) and mirror side. In this study, a ratio approach is applied to MODIS observed Earth scene reflectances to track the detector-to-detector and mirror side differences. Simultaneous observed reflectances from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with MODIS observed reflectances in this ratio approach for four closely matched spectral bands. Results show that the detector-to-detector difference between two adjacent detectors within each spectral band is typically less than 0.2% and, depending on the wavelengths, the maximum difference among all detectors varies from 0.5% to 0.8%. The mirror side differences are found to be very small for all bands except for band 3 at 0.44 mm. This is the band with the shortest wavelength among the selected matching bands, showing a time-dependent increase for the mirror side difference. This study is part of the effort by the MODIS Characterization Support Team (MCST) in order to track the RSB on-orbit performance for MODIS collection 5 data products. To support MCST efforts for future data re-processing, this analysis will be extended to include more spectral bands and temporal coverage.
Human activities have directly altered the water cycle through water management, aquifer pumping, agricultural irrigation, and land use change. Although satellite gravimetry has transformed global hydrological research, its coarse resolution limits attribution of freshwater change to human activities at many management-relevant scales. Here we assessed global terrestrial water storage (TWS) trends from April 2002 to November 2025 using “stacked” regression of Level-1B intersatellite ranging data, which leverages temporal information and variability to dramatically improve effective spatial resolution relative to standard approaches. We combined this refined product with rigorous uncertainty analysis, autocorrelation-robust geostatistical methods, and literature assessment to evaluate TWS trend associations with land and water use, climate variability, and glacial mass loss. We identified TWS trend hotspots exhibiting significant spatial associations with anthropogenic 40 drivers, including groundwater and surface-water irrigation, rainfed agriculture, deforestation, and reservoir impoundment. Across these regions, cumulative TWS losses (3,122 Gt) substantially exceeded gains (2,432 Gt). Compared with traditional regression of monthly mascons, our approach yielded regional trend magnitudes that are on average 33% larger, revealing that global freshwater depletion, particularly from groundwater pumping, is considerably more acute than previously estimated. Multivariate regression models show that humans account for a significant share of the spatial variability in TWS trends on every non-polar continent except Australia. We detected localized TWS gains linked to rainfed agriculture, surface water irrigation, and reservoir filling that were unresolved in earlier gravimetric studies. The methodology provides a foundation for future gravity missions to independently track decadal freshwater change with unprecedented spatial fidelity.
A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.
Examination of temporal and spatial CH4 variability is crucial for better understanding the human and natural processes driving climate change and ultimately designing mitigation strategies. Here we present an analysis framework that uses NASA’s GEOS General Circulation Model (GCM) to construct a high-resolution, time varying picture of atmospheric CH4 consistent with measurements from a variety of platforms, both in situ and remotely sensed. The resulting time varying atmospheric CH4 product can (i) support interpretation of high-resolution point source detection approaches, (ii) provide reanalysis fields for CH4 and other greenhouse gases, and (iii) supply boundary conditions for regional models. Our approach starts with a set of CH4 emissions from various inventories that have been adjusted to match the global annual growth rate over recent decades. These emissions are transported by the GEOS GCM, which in turn is constrained by meteorology from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product. The simulated atmospheric field is compared with CH4 measurements, such as those from the TROPOspheric Monitoring Instrument (TROPOMI), and adjustments calculated following a Bayesian protocol. The accuracy of the resultant optimal atmospheric CH4 field can be demonstrated by its improved agreement (compared to a direct simulation of the CH4 inventories) with a host of independent CH4 measurements, such as those from the Total Carbon Column Observation Network (TCCON) and in situ observations from surface and airborne platforms.