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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 NTRS2012

Derived Land Surface Emissivity From Suomi NPP CrIS

Presented here is the land surface IR spectral emissivity retrieved from the Cross-track Infrared Sounder (CrIS) measurements. The CrIS is aboard the Suomi National Polar-orbiting Partnership (NPP) satellite launched on October 28, 2011. We describe the retrieval algorithm, demonstrate the surface emissivity retrieved with CrIS measurements, and inter-comparison with the Infrared Atmospheric Sounding Interferometer (IASI) emissivity. We also demonstrate that surface emissivity from satellite measurements can be used in assistance of monitoring global surface climate change, as a long-term measurement of IASI and CrIS will be provided by the series of EUMETSAT MetOp and US Joint Polar Satellite System (JPSS) satellites. Monthly mean surface properties are produced using last 5-year IASI measurements. A temporal variation indicates seasonal diversity and El Nino/La Nina effects not only shown on the water but also on the land. Surface spectral emissivity and skin temperature from current and future operational satellites can be utilized as a means of long-term monitoring of the Earth's environment. CrIS spectral emissivity are retrieved and compared with IASI. The difference is small and could be within expected retrieval error; however it is under investigation.

Zhou, Daniel K.↗
NASA NTRS2012

Bridging Informatics and Earth Science: a Look at Gregory Leptoukh's Contributions

With the tragic passing this year of Gregory Leptoukh, the Earth and Space Sciences community lost a tireless participant in--and advocate for--science informatics. Throughout his career at NASA, Dr. Leptoukh established a theme of bridging the gulf between the informatics and science communities. Nowhere is this more evident than his leadership in the development of Giovanni (GES DISC Interactive Online Visualization ANd aNalysis Infrastructure). Giovanni is an online tool that serves to hide the often-complex technical details of data format and structure, making science data easier to explore and use by Earth scientists. To date Giovanni has been acknowledged as a contributor in 500-odd scientific articles. In recent years, Leptoukh concentrated his efforts on multi-sensor data inter-comparison, merging and fusion. This work exposed several challenges at the intersection of data and science. One of these was the ease with which a naive user might generate spurious comparisons, a potential hazard that was the genesis of the Multi-sensor Data Synergy Advisor (MDSA). The MDSA uses semantic ontologies and inference rules to organize knowledge about dataset quality and other salient characteristics in order to advise users on potential caveats for comparing or merging two datasets. Recently, Leptoukh also led the development of AeroStat, an online Giovanni instance to investigate aerosols via statistics from station and satellite comparisons and merged maps of data from more than one instrument. Aerostat offers a neural net based bias adjustment to harmonize the data by removing systematic offsets between datasets before merging. These examples exhibit Leptoukh's talent for adopting advanced computer technologies in the service of making science data more accessible to researchers. In this, he set an example that is at once both vital and challenging for the ESSI community to emulate.

Source record↗
NASA NTRS2013

Pre- and Post-perihelion Observations of C/2009 P1 (Garradd): Evidence for an Oxygen-rich Heritage?

We conducted pre- and post-perihelion observations of Comet C/2009 P1 (Garradd) on UT 2011 October 13 and 2012 January 8, at heliocentric distances of 1.83 and 1.57 AU, respectively, using the high-resolution infrared spectrometer (NIRSPEC) at the Keck II 10-m telescope on Mauna Kea, HI. Pre-perihelion, we obtained production rates for nine primary volatiles (native ices): H2O, CO, CH3OH, CH4, C2H6, HCN, C2H2, H2CO, and NH3. Post-perihelion, we obtained production rates for three of these (H2O, CH4, and HCN) and sensitive upper limits for three others (C2H2, H2CO, and NH3). CO was enriched and C2H2 was depleted, yet C2H6 and CH3OH were close to their currentmean values asmeasured in a dominant group of Oort cloud comets. This may indicate processing of its pre-cometary ices in a relatively oxygen-rich environment. Our measurements indicate consistent pre- and post-perihelion abundance ratios relative to H2O, suggesting we were measuring compositional homogeneity among measured species to the depths in the nucleus sampled. However, the overall gas production was lower post-perihelion despite its smaller heliocentric distance on January 8. This is qualitatively consistent with other studies of C/2009 P1, perhaps due to seasonal differences in the heating of one or more active regions on the nucleus. On October 13, the water profile showed a pronounced excess towards the Sun-facing hemisphere that was not seen in other molecules, including H2O on January 8, nor in the dust continuum. Inter-comparison of profiles from October 13 permitted us to quantify contributions due to release of H2O from the nucleus, and fromits release in the coma. This resulted in the latter source contributing 25-30% of the total observed water within our slit, which covered roughly +/-300 km by +/-4500 km from the nucleus. We attribute this excess H2O, which peaked at a mean projected distance of 1300-1500 km from the nucleus, to release from water-rich, relatively pure icy grains

Volatile composition↗
NASA NTRS2012

Improvement in Simulation of Eurasian Winter Climate Variability with a Realistic Arctic Sea Ice Condition in an Atmospheric GCM

The present study investigates how much a realistic Arctic sea ice condition can contribute to improve simulation of the winter climate variation over the Eurasia region. Model experiments are set up using different sea ice boundary conditions over the past 24 years (i.e., 1988-2011). One is an atmospheric model inter-comparison (AMIP) type of run forced with observed sea-surface temperature (SST), sea ice, and greenhouse gases (referred to as Exp RSI), and the other is the same as Exp RSI except for the sea ice forcing, which is a repeating climatological annual cycle (referred to as Exp CSI). Results show that Exp RSI produces the observed dominant pattern of Eurasian winter temperatures and their interannual variation better than Exp CSI (correlation difference up to approx. 0.3). Exp RSI captures the observed strong relationship between the sea ice concentration near the Barents and Kara seas and the temperature anomaly across Eurasia, including northeastern Asia, which is not well captured in Exp CSI. Lagged atmospheric responses to sea ice retreat are examined using observations to understand atmospheric processes for the Eurasian cooling response including the Arctic temperature increase, sea-level pressure increase, upper-level jet weakening and cold air outbreak toward the mid-latitude. The reproducibility of these lagged responses by Exp RSI is also evaluated.

sea-ice↗
NASA NTRS2014

Probing for Exoplanets Hiding in Dusty Debris Disks: Disk Imaging, Characterization, and Exploration with HST-STIS Multi-roll Coronagraphy

Spatially resolved scattered-light images of circumstellar debris in exoplanetary systems constrain the physical properties and orbits of the dust particles in these systems. They also inform on co-orbiting (but unseen) planets, the systemic architectures, and forces perturbing the starlight-scattering circumstellar material. Using HST/STIS broadband optical coronagraphy, we have completed the observational phase of a program to study the spatial distribution of dust in a sample of ten circumstellar debris systems, and one "mature" protoplanetrary disk all with HST pedigree, using PSF-subtracted multi-roll coronagraphy. These observations probe stellocentric distances greater than or equal to 5 AU for the nearest systems, and simultaneously resolve disk substructures well beyond corresponding to the giant planet and Kuiper belt regions within our own Solar System. They also disclose diffuse very low-surface brightness dust at larger stellocentric distances. Herein we present new results inclusive of fainter disks such as HD92945 (F (sub disk) /F (sub star) = 5x10 (sup -5) confirming, and better revealing, the existence of a narrow inner debris ring within a larger diffuse dust disk. Other disks with ring-like sub-structures and significant asymmetries and complex morphologies include: HD181327 for which we posit a spray of ejecta from a recent massive collision in an exo-Kuiper belt; HD61005 suggested to be interacting with the local ISM; HD15115 and HD32297, discussed also in the context of putative environmental interactions. These disks, and HD15745, suggest that debris system evolution cannot be treated in isolation. For AU Mic's edge-on disk we find out-of-plane surface brightness asymmetries at greater than or equal to 5 AU that may implicate the existence of one or more planetary perturbers. Time resolved images of the MP Mus proto-planetary disk provide spatially resolved temporal variability in the disk illumination. These and other new images from our HST/STIS GO/12228 program enable direct inter-comparison of the architectures of these exoplanetary debris systems in the context of our own Solar System.

stellocentric distances↗
NASA NTRS2014

Assessment of Satellite Radiometry in the Visible Domain

Marine reflectance and chlorophyll-a concentration are listed among the Essential Climate Variables by the Global Climate Observing System. To contribute to climate research, the satellite ocean color data records resulting from successive missions need to be consistent and well characterized in terms of uncertainties. This chapter reviews various approaches that can be used for the assessment of satellite ocean color data. Good practices for validating satellite products with in situ data and the current status of validation results are illustrated. Model-based approaches and inter-comparison techniques can also contribute to characterize some components of the uncertainty budget, while time series analysis can detect issues with the instrument radiometric characterization and calibration. Satellite data from different missions should also provide a consistent picture in scales of variability, including seasonal and interannual signals. Eventually, the various assessment approaches should be combined to create a fully characterized climate data record from satellite ocean color.

ocean color↗
NASA NTRS2014

Infrared Spectral Radiance Intercomparisons With Satellite and Aircraft Sensors

Measurement system validation is critical for advanced satellite sounders to reach their full potential of improving observations of the Earth's atmosphere, clouds, and surface for enabling enhancements in weather prediction, climate monitoring capability, and environmental change detection. Experimental field campaigns, focusing on satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft, are an essential part of the validation task. Airborne FTS systems can enable an independent, SI-traceable measurement system validation by directly measuring the same level-1 parameters spatially and temporally coincident with the satellite sensor of interest. Continuation of aircraft under-flights for multiple satellites during multiple field campaigns enables long-term monitoring of system performance and inter-satellite cross-validation. The NASA / NPOESS Airborne Sounder Testbed - Interferometer (NAST-I) has been a significant contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This presentation gives an overview of benefits achieved using airborne sensors such as NAST-I utilizing examples from recent field campaigns. The methodology implemented is not only beneficial to new sensors such as the Cross-track Infrared Sounder (CrIS) flying aboard the Suomi NPP and future JPSS satellites but also of significant benefit to sensors of longer flight heritage such as the Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) on the AQUA and METOP-A platforms, respectively, to ensure data quality continuity important for climate and other applications. Infrared spectral radiance inter-comparisons are discussed with a particular focus on usage of NAST-I data for enabling inter-platform cross-validation.

Larar, Allen M.↗
NASA NTRS2014

The Giant Planet Satellite Exospheres

Exospheres are relatively common in the outer solar system among the moons of the gas giant planets. They span the range from very tenuous, surface-bounded exospheres (e.g., Rhea, Dione) to quite robust exospheres with exobase above the surface (e.g., lo, Triton), and include many intermediate cases (e.g., Europa, Ganymede, Enceladus). The exospheres of these moons exhibit an interesting variety of sources, from surface sputtering, to frost sublimation, to active plumes, and also well illustrate another common characteristic of the outer planet satellite exospheres, namely, that the primary species often exists both as a gas in atmosphere, and a condensate (frost or ice) on the surface. As described by Yelle et al. (1995) for Triton, "The interchange of matter between gas and solid phases on these bodies has profound effects on the physical state of the surface and the structure of the atmosphere." A brief overview of the exospheres of the outer planet satellites will be presented, including an inter-comparison of these satellites exospheres with each other, and with the exospheres of the Moon and Mercury.

McGrath, Melissa A.↗
NASA NTRS2014

Evaluation of the Sensor Data Record from the Nadir Instruments of the Ozone Mapping Profiler Suite (OMPS)

This paper evaluates the first 15 months of the Ozone Mapping and Profiler Suite (OMPS) Sensor Data Record (SDR) acquired by the nadir sensors and processed by the National Oceanic and Atmospheric Administration Interface Data Processing Segment. The evaluation consists of an inter-comparison with a similar satellite instrument, an analysis using a radiative transfer model, and an assessment of product stability. This is in addition to the evaluation of sensor calibration and the Environment Data Record product that are also reported in this Special Issue. All these are parts of synergetic effort to provide comprehensive assessment at every level of the products to ensure its quality. It is found that the OMPS nadir SDR quality is satisfactory for the current Provisional maturity. Methods used in the evaluation are being further refined, developed, and expanded, in collaboration with international community through the Global Space-based Inter-Calibration System, to support the upcoming long-term monitoring.

validation↗
NASA NTRS2015

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

On board of the NASA's Global Hawk (AV1) aircraft there are two microwave, namely: the passive microwave Hurricane Imaging Radiometer (HIRAD), and the active microwave High-altitude Imaging Wind and Rain Airborne Profiler (HIWRAP). This paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when the Global Hawk aircraft flew over an intense tropical squall-line that was simultaneously observed, by the Tampa NEXRAD meteorological radar. During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. NEXRAD 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. In this paper, results are presented of the three-way inter-comparison of HIRAD Tb, HIWRAP dbZ and NEXRAD rain rate imagery.

HIRAD↗
NASA NTRS2015

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

NASA's Global Hawk aircraft (AV1)has two microwave sensors: the passive Hurricane Imaging Radiometer (HIRAD), and the active High-altitude Imaging Wind and Rain Airborne Profiler(HIWRAP). Results are presented for a rain measurement validation opportunity that occurred in 2013, when the AV1 flew over a tropical squall-line that was simultaneously observed by the Tampa NEXRAD radar. During this experiment, Global Hawk made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD performed volume scans every 5 minutes. In this poster, the three-way inter-comparison of HIRAD Tb (base temperature), HIWRAP dbZ (decibels relative to equivalent reflectivity) and NEXRAD rain rate imagery are presented. Also, observed HIRAD Tbs are compared with theoretical radiative transfer model results using HIWRAP Rain Rates.

Retrieval↗
NASA NTRS2015

Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

Climate change↗
NASA NTRS2015

Explore GPM IMERG and Other Global Precipitation Products with GES DISC GIOVANNI

New features and capabilities in the newly released GIOVANNI allow exploring GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) Early, Late and Final Run global half-hourly and monthly precipitation products as well as other precipitation products distributed by the GES DISC such as TRMM Multi-Satellite Precipitation Analysis (TMPA), MERRA (Modern Era Retrospective-Analysis for Research and Applications), NLDAS (North American Land Data Assimilation Systems), GLDAS (Global Land Data Assimilation Systems), etc. GIOVANNI is a web-based tool developed by the GES DISC (Goddard Earth Sciences and Data Information Services Center) to visualize and analyze Earth science data without having to download data and software. The new interface in GIOVANNI allows searching and filtering precipitation products from different NASA missions and projects and expands the capabilities to inter-compare different precipitation products in one interface. Knowing differences in precipitation products is important to identify issues in retrieval algorithms, biases, uncertainties, etc. Due to different formats, data structures, units and so on, it is not easy to inter-compare precipitation products. Newly added features and capabilities (unit conversion, regridding, etc.) in GIOVANNI make inter-comparisons possible. In this presentation, we will describe these new features and capabilities along with examples.

Giovanni↗
NASA NTRS2015

Interannual to Decadal Variability of Ocean Evaporation as Viewed from Climate Reanalyses

Questions we'll address: Given the uncoupled framework of "AMIP" (Atmosphere Model Inter-comparison Project) experiments, what can they tell us regarding evaporation variability? Do Reduced Observations Reanalyses (RedObs) using Surface Fluxes and Clouds (SFC) pressure (and wind) provide a more realistic picture of evaporation variability? What signals of interannual variability (e.g. El Nino/Southern Oscillation (ENSO)) and decadal variability (Interdecadal Pacific Oscillation (IPO)) are detectable with this hierarchy of evaporation estimates?

Climate Variability↗
NASA NTRS2015

SPARC's Stratospheric Sulfur and its Role in Climate Activity (SSiRC)

The stratospheric aerosol layer is a key component in the climate system. It affects the radiative balance of the atmosphere directly through interactions with solar and terrestrial radiation, and indirectly through its effect on stratospheric ozone. Because the stratospheric aerosol layer is prescribed in many climate models and Chemistry-Climate Models (CCMs), model simulations of future atmospheric conditions and climate generally do not account for the interaction between the aerosol-sulfur cycle and changes in the climate system. The present understanding of how the stratospheric aerosol layer may be affected by future climate change and how the stratospheric aerosol layer may drive climate change is, therefore, very limited. The purposes of SSiRC (Stratospheric Sulfur and its Role in Climate) include: (i) providing a coordinating structure for the various individual activities already underway in different research centers; (ii) encouraging and supporting new instrumentation and measurements of sulfur containing compounds, such as COS, DMS, and non-volcanic SO2 in the UT/LS globally; and (iii) initiating new model/data inter-comparisons. SSiRC is developing collaborations with a number of other SPARC activities including CCMI and ACAM. This presentation will highlight the scientific goals of this project and on-going activities and propose potential interactions between SSiRC and ACAM.

Thomason, Larry↗
NASA NTRS2015

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Stackhouse, Paul W., Jr.↗
NASA NTRS2016

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗
NASA NTRS2013

Hadoop for High-Performance Climate Analytics: Use Cases and Lessons Learned

Scientific data services are a critical aspect of the NASA Center for Climate Simulations mission (NCCS). Hadoop, via MapReduce, provides an approach to high-performance analytics that is proving to be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. The NCCS is particularly interested in the potential of Hadoop to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we prototyped a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. The initial focus was on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. After preliminary results suggested that this approach improves efficiencies within data intensive analytic workflows, we invested in building a cyber infrastructure resource for developing a new generation of climate data analysis capabilities using Hadoop. This resource is focused on reducing the time spent in the preparation of reanalysis data used in data-model inter-comparison, a long sought goal of the climate community. This paper summarizes the related use cases and lessons learned.

analytics↗