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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 NTRS2015

AgMIP Climate Data and Scenarios for Integrated Assessment

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

agriculture↗
NASA NTRS2010

Future Flight Opportunities and Calibration Protocols for CERES: Continuation of Observations in Support of the Long-Term Earth Radiation Budget Climate Data Record

The goal of the Clouds and the Earth s Radiant Energy System (CERES) project is to provide a long-term record of radiation budget at the top-of-atmosphere (TOA), within the atmosphere, and at the surface with consistent cloud and aerosol properties at climate accuracy. CERES consists of an integrated instrument-algorithm validation science team that provides development of higher-level products (Levels 1-3) and investigations. It involves a high level of data fusion, merging inputs from 25 unique input data sources to produce 18 CERES data products. Over 90% of the CERES data product volume involves two or more instruments. Continuation of the Earth Radiation Budget (ERB) Climate Data Record (CDR) has been identified as critical in the 2007 NRC Decadal Survey, the Global Climate Observing System WCRP report, and in an assessment titled Impacts of NPOESS Nunn-McCurdy Certification on Joint NASA-NOAA Climate Goals . Five CERES instruments have flown on three different spacecraft: TRMM, EOS-Terra and EOS-Aqua. In response, NASA, NOAA and NPOESS have agreed to fly the existing CERES Flight Model (FM-5) on the NPP spacecraft in 2011 and to procure an additional CERES Sensor with modest upgrades for flight on the JPSS C1 spacecraft in 2014, followed by a CERES follow-on sensor for flight in 2018. CERES is a scanning broadband radiometer that measures filtered radiance in the SW (0.3-5 m), total (TOT) (0.3-200 m) and WN (8-12 m) regions. Pre-launch calibration is performed on each Flight Model to meet accuracy requirements of 1% for SW and 0.5% for outgoing LW observations. Ground to flight or in-flight changes are monitored using protocols employing onboard and vicarious calibration sources. Studies of flight data show that SW response can change dramatically due to optical contamination. with greatest impact in blue-to UV radiance, where tungsten lamps are largely devoid of output. While science goals remain unchanged for ERB Climate Data Record, it is now understood that achieving these goals is more difficult for two reasons. The first is an increased understanding of the dynamics of the Earth/atmosphere system which demonstrates that separation of natural variability from anthropogenic change on decadal time scales requires observations with higher accuracy and stabilit

Priestley, Kory J.↗
NASA NTRSDate not supplied

Deriving a Suite of Climate Data Records from 21-years of Sounder Observations

Two retrieval algorithms, a Single Field-of-view Sounder Atmospheric Product (SiFSAP) Level 2 algorithm and a Climate Fingerprinting Sounder Product (ClimFiSP) Level 3 algorithm, have been developed at NASA Langley Research Center. In this presentation, we will demonstrate the radiance closure build into these two algorithms. This is possible due to the use of a principal-component-based radiative transfer model (PCRTM). The PCRTM enables the inclusion of all available spectral information from hyperspectral IR sounders. It also has fast and accurate capability of modeling observed cloudy radiance spectra directly. The SiFSAP, which fits sounder radiance spectra using PCRTM as forward model and an optimal estimation as inverse model, has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. With great support from NASA sounder SIPS, the SiFSAP algorithm has been delivered to NASA GES DISC for L2 and L3 data generation and releasing. The ClimFiSP uses a spectral fingerprinting method to directly generate L3 data products from spatiotemporally averaged L1 data. The goal of ClimFiSP is to generate high-quality climate data records (CDRs) from multiple IR sounders (e.g. Aqua AIRS, SNPP CrIS, NOAA-20 and NOAA-21 CrIS) using a consistent retrieval methodology. Using CHIRP L1 data, we have generated 20-years of CDRs for atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties. The algorithm will be transitioned to Sounder SIPS soon and eventually to NASA GES DISC.

Xu Liu↗
NASA NTRS2015

Evaluating a New Homogeneous Total Ozone Climate Data Record from GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A

The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality ozone data products generated from different satellite sensors. For total ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the total ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI total ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Système D′Analyse par Observations Zénithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 total ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI total ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 plus or minus 1 percent level for all three sensors while the near-zero decadal stability of the total ozone columns (TOCs) provided by the three European instruments falls well within the 1-3 percent requirement of the European Space Agency's Ozone Climate Change Initiative project.

Satellite sensors↗
NASA NTRS2012

Sustained Satellite Missions for Climate Data Records

Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

climate data records↗
NASA NTRSDate not supplied

On the use of DSCOVR EPIC to monitor the visible calibration stability of polar orbiting imagers to improve the next edition of the CERES climate data record.

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES instruments are onboard the Terra, Aqua, NPP, and NOAA-20 spacecraft. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert CERES footprint radiance observations into fluxes using empirically derived angular directional models obtained during early CERES record. CERES utilizes geostationary sensors to infer the regional diurnal fluxes in between Terra and Aqua CERES observations. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The Aqua-MODIS, SNPP-VIIRS, and NOAA-20 VIIRS afternoon imagers will also need to be radiometrically scaled to the same common calibration reference. Although all three imagers employ onboard solar diffusers, the calibration is not consistent over time due to instrument anomalies and ageing of the onboard calibrators. The CERES imager and GEO calibration group (IGCG) has been tasked to remove the imager channel calibration drifts for the next CERES reprocessing effort. The team will rely primarily on deep convective clouds, desert, and polar ice invariant targets to monitor the imager channel stability. The team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to Aqua-MODIS. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC instrument onboard DSCOVR employs a CCD array to image the Earth approximately every 2-hours. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. This is likely due to the DSCOVR satellite being located about a 1.5M km from the Earth, where very little Earth reflected solar radiation degrades the optics. The excellent radiometric stability of EPIC allows the CERES IGCG to utilize the EPIC observations as a stable reference for monitoring the calibration stability of the three afternoon imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗
NASA NTRS2009

Uncertainty Management in Remote Sensing of Climate Data. Summary of A Workshop

Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis (NRC, 2007). Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data, including statistical methods used to calibrate and validate satellite instruments, lack an overall mathematically based framework.

Remote sensing↗
NASA NTRS2017

How Long Do Satellites Need to Overlap? Evaluation of Climate Data Stability from Overlapping Satellite Records

Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 %/yr uncertainty (0.00008 W/sq m/nm/yr), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.

climate data records↗
NASA NTRSDate not supplied

A New, Efficient, and Consistent Method for Generating Climate Data Record from Operational Hyperspectral Sounder Instruments on AQUA, S-NPP and NOAA 20

Operational IR sounders such AIRS on NASA Aqua, CrIS on S-NPP and on NOAA 20 satellites provide high quality hyperspectral measurements for weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It can provide fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

Xu Liu↗
NASA NTRS2018

Comparison of MERRA-2 and ECCO-V4 Ocean Surface Heat Fluxes: Consequences of Different Forcing Feedbacks on Ocean Circulation and Implications for Climate Data Assimilation

Forcing ocean models with reanalysis data is a common practice in ocean modeling. As part of this practice, prescribed atmospheric state variables and interactive ocean SST (Sea Surface Temperature) are used to calculate fluxes between the ocean and the atmosphere. When forcing an ocean model with reanalysis fields, errors in the reanalysis data, errors in the ocean model and errors in the forcing formulation will generate a different solution compared to other ocean reanalysis solutions (which also have their own errors). As a first step towards a consistent coupled ocean-atmosphere reanalysis, we compare surface heat fluxes from a state-of-the-art atmospheric reanalysis, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), to heat fluxes from a state-of-the-art oceanic reanalysis, the Estimating the Circulation and Climate of the Ocean Version 4, Release 2 (ECCO-v4). Then, we investigate the errors associated with the MITgcm (Massachusetts Institute of Technology general circulation model) ocean model in its ECCO-v4 ocean reanalysis configuration (1992-2011) when it is forced with MERRA- 2 atmospheric reanalysis fields instead of with the ECCO-v4 adjoint optimized ERA-interim state variables. This is done by forcing ECCO-v4 ocean with and without feedbacks from MERRA-2 related to turbulent fluxes of heat and moisture and the outgoing long wave radiation. In addition, we introduce an intermediate forcing method that includes only the feedback from the interactive outgoing long wave radiation. The resulting ocean circulation is compared with ECCO-v4 reanalysis and in-situ observations. We show that, without feedbacks, imbalances in the energy and the hydrological cycles of MERRA-2 (which are directly related to the fact it was created without interactive ocean) result in considerable SST drifts and a large reduction in sea level. The bulk formulae and interactive outgoing long wave radiation, although providing air-sea feedbacks and reducing model-data misfit, strongly relax the ocean to observed SST and may result in unwanted features such as large change in the water budget. These features have implications in a desired forcing recipe to be used. The results strongly and unambiguously argue for next generation data assimilation climate studies to involve fully coupled systems.

MERRA-2↗