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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2007

Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

Imhoff, Marc L.↗
NASA NTRS2008

How Very Massive Metal-Free Stars Start Cosmological Reionization

The initial conditions and relevant physics for the formation of the earliest galaxies are well specified in the concordance cosmology. Using ab initio cosmological Eulerian adaptive mesh refinement radiation hydrodynamical calculations, we discuss how very massive stars start the process of cosmological reionization. The models include nonequilibrium primordial gas chemistry and cooling processes and accurate radiation transport in the case B approximation using adaptively ray-traced photon packages, retaining the time derivative in the transport equation. Supernova feedback is modeled by thermal explosions triggered at parsec scales. All calculations resolve the local Jeans length by at least 16 grid cells at all times and as such cover a spatial dynamic range of approx.10(exp 6). These first sources of reionization are highly intermittent and anisotropic and first photoionize the small-scale voids surrounding the halos they form in, rather than the dense filaments they are embedded in. As the merging objects form larger, dwarf-sized galaxies, the escape fraction of UV radiation decreases and the H II regions only break out on some sides of the galaxies, making them even more anisotropic. In three cases, SN blast waves induce star formation in overdense regions that were formed earlier from ionization front instabilities. These stars form tens of parsecs away from the center of their parent DM halo. Approximately five ionizing photons are needed per sustained ionization when star formation in 10(exp 6) stellar Mass halos is dominant in the calculation. As the halos become larger than approx.10(exp 7) Stellar Mass, the ionizing photon escape fraction decreases, which in turn increases the number of photons per ionization to 15-50, in calculations with stellar feedback only. Radiative feedback decreases clumping factors by 25% when compared to simulations without star formation and increases the average temperature of ionized gas to values between 3000 and 10,000 K.

Wise, John H.↗
NASA NTRS2008

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Wemet, Mark P.↗
NASA NTRS2009

Tracking Debris Shed by a Space-Shuttle Launch Vehicle

The DEBRIS software predicts the trajectories of debris particles shed by a space-shuttle launch vehicle during ascent, to aid in assessing potential harm to the space-shuttle orbiter and crew. The user specifies the location of release and other initial conditions for a debris particle. DEBRIS tracks the particle within an overset grid system by means of a computational fluid dynamics (CFD) simulation of the local flow field and a ballistic simulation that takes account of the mass of the particle and its aerodynamic properties in the flow field. The computed particle trajectory is stored in a file to be post-processed by other software for viewing and analyzing the trajectory. DEBRIS supplants a prior debris tracking code that took .15 minutes to calculate a single particle trajectory: DEBRIS can calculate 1,000 trajectories in .20 seconds on a desktop computer. Other improvements over the prior code include adaptive time-stepping to ensure accuracy, forcing at least one step per grid cell to ensure resolution of all CFD-resolved flow features, ability to simulate rebound of debris from surfaces, extensive error checking, a builtin suite of test cases, and dynamic allocation of memory.

Stuart, Phillip C.↗
NASA NTRS2007

Displaying Properties of PDFs

PDFVis is a computer program that assists in visualization of uncertainty as represented by a probability density function (PDF) located at each grid cell in a spatial domain. The functions that PDFV performs are listed.

Kao, David↗
NASA NTRS2009

Momentum Flux Estimates for South Georgia Island Mountain Waves in the Stratosphere Observed via Satellite

We show high-resolution satellite observations of mountain wave events in the stratosphere above South Georgia Island in the remote southern Atlantic Ocean and compute the wave momentum fluxes for these events. The fluxes are large, and they imply important drag forces on the circulation. Small island orography is generally neglected in mountain wave parameterizations used in global climate models because limited model resolution treats the grid cell containing the island as ocean rather than land. Our results show that satellite observations can be used to quantitatively constrain mountain wave momentum fluxes, and they suggest that mountain waves from island topography may be an important missing source of drag on the atmospheric circulation.

SOUTH GEORGIA ISLANDS↗
NASA NTRS2004

Partitioning a Gridded Rectangle into Smaller Rectangles

A relatively simple algorithm, devised for use in an image-data-compression application, partitions a rectangular pixelated image (or any other rectangle on which a regular rectangular grid has already been superimposed) into a specified number of smaller rectangles, hereafter denoted segments. The algorithm has the following properties: No floating-point operations are needed. The segments tend to be nearly square (in the sense that their widths and heights in pixel units tend to be nearly equal). The segments tend to have nearly equal areas. The algorithm yields valid results (no zero-width or zero-height segments) as long as the specified number of segments, s, does not exceed the number of pixels (equivalently, the number of grid cells). The inputs to the algorithm are the positive integer s plus the positive integers h and w, denoting the height and width, respectively, of the rectangle in pixel units. The limit on s for a valid result is given by s less than or equal to wh.

Klimesh, Matthew↗
NASA NTRS2012

Low-Dissipation Advection Schemes Designed for Large Eddy Simulations of Hypersonic Propulsion Systems

The 2nd-order upwind inviscid flux scheme implemented in the multi-block, structured grid, cell centered, finite volume, high-speed reacting flow code VULCAN has been modified to reduce numerical dissipation. This modification was motivated by the desire to improve the codes ability to perform large eddy simulations. The reduction in dissipation was accomplished through a hybridization of non-dissipative and dissipative discontinuity-capturing advection schemes that reduces numerical dissipation while maintaining the ability to capture shocks. A methodology for constructing hybrid-advection schemes that blends nondissipative fluxes consisting of linear combinations of divergence and product rule forms discretized using 4th-order symmetric operators, with dissipative, 3rd or 4th-order reconstruction based upwind flux schemes was developed and implemented. A series of benchmark problems with increasing spatial and fluid dynamical complexity were utilized to examine the ability of the candidate schemes to resolve and propagate structures typical of turbulent flow, their discontinuity capturing capability and their robustness. A realistic geometry typical of a high-speed propulsion system flowpath was computed using the most promising of the examined schemes and was compared with available experimental data to demonstrate simulation fidelity.

White, Jeffrey A.↗
NASA NTRS2012

Spatial Variability in Column CO2 Inferred from High Resolution GEOS-5 Global Model Simulations: Implications for Remote Sensing and Inversions

Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement concepts to create realistic pseudo-datasets. Pseudo-data are averaged over coarse model grid cell areas to better understand the ability of measurements to characterize CO2 distributions and spatial gradients on both short (daily to weekly) and long (monthly to seasonal) time scales

Ott, L.↗
NASA NTRS2011

Enhancements in Deriving Smoke Emission Coefficients from Fire Radiative Power Measurements

Smoke emissions have long been quantified after-the-fact by simple multiplication of burned area, biomass density, fraction of above-ground biomass, and burn efficiency. A new algorithm has been suggested, as described in Ichoku & Kaufman (2005), for use in calculating smoke emissions directly from fire radiative power (FRP) measurements such that the latency and uncertainty associated with the previously listed variables are avoided. Application of this new, simpler and more direct algorithm is automatic, based only on a fire's FRP measurement and a predetermined coefficient of smoke emission for a given location. Attaining accurate coefficients of smoke emission is therefore critical to the success of this algorithm. In the aforementioned paper, an initial effort was made to derive coefficients of smoke emission for different large regions of interest using calculations of smoke emission rates from MODIS FRP and aerosol optical depth (AOD) measurements. Further work had resulted in a first draft of a 1 1 resolution map of these coefficients. This poster will present the work done to refine this algorithm toward the first production of global smoke emission coefficients. Main updates in the algorithm include: 1) inclusion of wind vectors to help refine several parameters, 2) defining new methods for calculating the fire-emitted AOD fractions, and 3) calculating smoke emission rates on a per-pixel basis and aggregating to grid cells instead of doing so later on in the process. In addition to a presentation of the methodology used to derive this product, maps displaying preliminary results as well as an outline of the future application of such a product into specific research opportunities will be shown.

Ellison, Luke↗
NASA NTRS2013

High resolution wind measurements for offshore wind energy development

A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to measure wind. Data at a first resolution (i.e., low resolution data) is collected by a satellite scatterometer. Thin slices of the data are determined. A collocation of the data slices are determined at each grid cell center to obtain ensembles of collocated data slices. Each ensemble of collocated data slices is decomposed into a mean part and a fluctuating part. The data is reconstructed at a second resolution from the mean part and a residue of the fluctuating part. A wind measurement is determined from the data at the second resolution using a wind model function. A description of the wind measurement is output.

Nghiem, Son Van↗
NASA NTRS2013

Recent Development in the CESE Method for the Solution of the Navier-Stokes Equations Using Unstructured Triangular or Tetrahedral Meshes With High Aspect Ratio

In the multidimensional CESE development, triangles and tetrahedra turn out to be the most natural building blocks for 2D and 3D spatial meshes. As such the CESE method is compatible with the simplest unstructured meshes and thus can be easily applied to solve problems with complex geometries. However, because the method uses space-time staggered stencils, solution decoupling may become a real nuisance in applications involving unstructured meshes. In this paper we will describe a simple and general remedy which, according to numerical experiments, has removed any possibility of solution decoupling. Moreover, in a real-world viscous flow simulation near a solid wall, one often encounters a case where a boundary with high curvature or sharp corner is surrounded by triangular/tetrahedral meshes of extremely high aspect ratio (up to 106). For such an extreme case, the spatial projection of a space-time compounded conservation element constructed using the original CESE design may become highly concave and thus its centroid (referred to as a spatial solution point) may lie far outside of the spatial projection. It could even be embedded beyond a solid wall boundary and causes serious numerical difficulties. In this paper we will also present a new procedure for constructing conservation elements and solution elements which effectively overcomes the difficulties associated with the original design. Another difficulty issue which was addressed more recently is the wellknown fact that accuracy of gradient computations involving triangular/tetrahedral grids deteriorates rapidly as the aspect ratio of grid cells increases. The root cause of this difficulty was clearly identified and several remedies to overcome it were found through a rigorous mathematical analysis. However, because of the length of the current paper and the complexity of mathematics involved, this new work will be presented in another paper.

Chang, Sin-Chung↗
NASA NTRS2014

Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) ≤ 35◦ to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA ≤ 35◦. The fourth experiment included only backscatter observations with VZA ≤ 35◦. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation footprint impact whereas comparison of experiment 4 vs. experiment 3 was used to examine the BRDF impact. Changes in R2, RMSE,CV and changes in model coefficients "a" and "b" (experiment 2 vs. experiment 1; and experiment 4 vs. experiment 3) were indicators of the impacts. The second experiment produced better performance than the first experiment, increasing R2 (↑0.13) and reducing RMSE (↓0.68 g C m−2 d−1) and CV (↓9%). For each VI, the slope of GPP = a × VI × PAR in the second experiment for each crop type changed little while the slope and intercept of GPP = a × VI × PAR + b varied field by field. The CIgreen was least affected by the MODIS observation footprint in estimating crop daily GPP (R2, ↑0.08; RMSE, ↓0.42 g C m−2 d−1; and CV, ↓7%). Footprint most affected the NDVI (R2, ↑0.15; CV, ↓10%) and the EVI (RMSE, ↓0.84 g C m−2 d−1). The vegetation BRDF impact also caused variation of model performance and change of model coefficients. Significantly different slopes were obtained for forward vs. backscatter observations, especially for the CIgreen and the NDVI. Both the footprint impact and the BRDF impact varied with crop types, irrigation options, model options and VI options.

Chlorophyll↗
NASA NTRS2013

A Long-Term and Reproducible Passive Microwave Sea Ice Concentration Data Record for Climate Studies and Monitoring

A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N5B56GN3.

monitoring↗
NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗
NASA NTRS2014

An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W/sq m and 0.18 (0.06-0.28) W/sq m in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W/sq m for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

carbon↗
NASA NTRS2014

Observation-Corrected Precipitation Estimates in GEOS-5

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Data Assimilation↗
NASA NTRS2014

Verification of a New NOAA/NSIDC Passive Microwave Sea-Ice Concentration Climate Record

A new satellite-based passive microwave sea-ice concentration product developed for the National Oceanic and Atmospheric Administration (NOAA)Climate Data Record (CDR) programme is evaluated via comparison with other passive microwave-derived estimates. The new product leverages two well-established concentration algorithms, known as the NASA Team and Bootstrap, both developed at and produced by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC). The sea ice estimates compare well with similar GSFC products while also fulfilling all NOAA CDR initial operation capability (IOC) requirements, including (1) self describing file format, (2) ISO 19115-2 compliant collection-level metadata,(3) Climate and Forecast (CF) compliant file-level metadata, (4) grid-cell level metadata (data quality fields), (5) fully automated and reproducible processing and (6) open online access to full documentation with version control, including source code and an algorithm theoretical basic document. The primary limitations of the GSFC products are lack of metadata and use of untracked manual corrections to the output fields. Smaller differences occur from minor variations in processing methods by the National Snow and Ice Data Center (for the CDR fields) and NASA (for the GSFC fields). The CDR concentrations do have some differences from the constituent GSFC concentrations, but trends and variability are not substantially different.

Passive Microwave↗