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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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At least 451 records · Page 25
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NASA NTRS2015

Investigation of North American Vegetation Variability under Recent Climate: A Study Using the SSiB4/TRIFFID Biophysical/Dynamic Vegetation Model

Recent studies have shown that current dynamic vegetation models have serious weaknesses in reproducing the observed vegetation dynamics and contribute to bias in climate simulations. This study intends to identify the major factors that underlie the connections between vegetation dynamics and climate variability and investigates vegetation spatial distribution and temporal variability at seasonal to decadal scales over North America (NA) to assess a 2-D biophysical model/dynamic vegetation model's (Simplified Simple Biosphere Model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID)) ability to simulate these characteristics for the past 60 years (1948 through 2008). Satellite data are employed as constraints for the study and to compare the relationships between vegetation and climate from the observational and the simulation data sets. Trends in NA vegetation over this period are examined. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation, which describes the population dynamics of species competing for some common resource, have been identified as having major impacts on vegetation spatial distribution and obtaining proper initial vegetation conditions in SSiB4/TRIFFID. The finding that vegetation competition coefficients significantly affect vegetation distribution suggests the importance of including biotic effects in dynamical vegetation modeling. The improved SSiB4/TRIFFID can reproduce the main features of the NA distributions of dominant vegetation types, the vegetation fraction, and leaf area index (LAI), including its seasonal, interannual, and decadal variabilities. The simulated NA LAI also shows a general increasing trend after the 1970s in responding to warming. Both simulation and satellite observations reveal that LAI increased substantially in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with differentmodels and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

climate variability↗
NASA NTRSDate not supplied

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗
NASA NTRS1980

Atmospheric aerosols and climate

The impact of terrestrial aerosols on the earth's climate and solar and infrared radiation budget are considered. Attention is given to the optical properties of aerosols, that is, optical depth, the single scattering albedo, and the asymmetry parameter, and to the relation between the optical depth and surface temperature for tropospheric and stratospheric aerosols. Also considered are experimental projects to determine the single scattering albedo, as well as the optical properties of natural aerosols such as sea salt, soil, and sulfates, and their variability. In addition, the impact of volcanic activity and the question of whether aerosols cause climatic warming or cooling are discussed, and the available observational evidence linking aerosols and climate is reviewed.

Toon, O. B.↗
NASA NTRSDate not supplied

Mission Overview and Status IGARSS Conference

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is a strategic climate continuity mission that was defined in the 2010 document Responding to the Challenge of Climate and Environmental Change: NASA’s Plan for Climate-Centric Architecture for Earth Observations and Applications from Space (referred to as the “Climate Initiative”). Scheduled for launch in January 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records [1]. PACE will extend the high quality ocean ecological, ocean biogeochemical, cloud, and aerosol particle data records begun by NASA in the 1990s, building on the exceptional heritages of the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), and the Visible Infrared Imaging Radiometer Suite (VIIRS). The PACE project office at NASA’s GSFC is responsible for the satellite development, launch and operations. The NASA Headquarters PACE Program Science office is responsible for supporting the science data processing system and assembling competed community science teams, which will include field-based vicarious calibration and data product validation efforts to support the PACE Project Science team. The mission is planned for launch into a Sun synchronous polar orbit at 676.5 km with an inclination of 98 degrees and a 1 pm local ascending node crossing time. The PACE observatory is comprised of three instruments, an Ocean Color Instrument (OCI) and two polarimeters, the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone). The OCI is the primary instrument on the observatory and is being developed at Goddard Space Flight Center (GSFC). The OCI is a hyperspectral scanning radiometer designed to measure spectral radiances from the ultraviolet to shortwave infrared (SWIR) to enable advanced ocean color and heritage cloud and atmospheric aerosol science [2]. The HARP2 and SPEXone are complimentary instruments on the PACE observatory, acquired outside of GSFC. The HARP2 is multi-spectral, wide swath (supporting atmospheric correction of OCI), and hyper-angular, with capabilities for cloud science that exceed what is capable from OCI alone. The SPEXone is narrow swath, multi-angular, and hyperspectral, with capabilities for atmospheric aerosol science that exceed what can be accomplished with OCI. NASA Headquarters directed the mission development to be guided by a Design-to-Cost (DTC) process. All elements of the mission, other than the cost, are in the DTC trade space. At the heart of the DTC process are the mission studies, performed across all the mission elements. The mission studies were used to define appropriate approaches within and across elements while maximizing science capabilities at a high cost confidence. Mission baseline requirements development is also embedded within the DTC process, as these requirements were not established at the onset of the mission concept development. Baseline mission requirements are a product of the mission studies and are defined by the project office as part of the DTC process. At the time of this writing, OCI, HARP2 and SPEXone are integrated onto the PACE spacecraft, creating the PACE observatory. The instruments and spacecraft subsystems are undergoing combined functional performance testing in preparation for observatory-level environmental testing prior to shipment to the launch site. Here, we will provide an update on science capabilities and observatory readiness for its early 2024 launch.

remote sensing↗
NASA NTRS1999

Ocean-Atmosphere Interaction in Climate Changes

The diagram, which attests the El Nino teleconnection observed by the NASA Scatterometer (NSCAT) in 1997, is an example of the results of our research in air-sea interaction - the core component of our three-part contribution to the Climate Variability Program. We have established an interplay among scientific research, which turns spacebased data into knowledge, a push in instrument technology, which improves observations of climate variability, and an information system, which produces and disseminates new data to support our scientific research. Timothy Liu led the proposal for advanced technology, in response to the NASA Post-2002 Request for Information. The sensor was identified as a possible mission for continuous ocean surface wind measurement at higher spatial resolution, and with the unique capability to measure ocean surface salinity. He is participating in the Instrument Incubator Program to improve the antenna technology, and is initiating a study to integrate the concept on Japanese missions. He and his collaborators have set up a system to produce and disseminate high level (gridded) ocean surface wind/stress data from NSCAT and European missions. The data system is being expanded to produce real-time gridded ocean surface winds from Quikscat, and precipitation and evaporation from the Tropical Rain Measuring Mission. It will form the basis for a spacebased data analysis system which will include momentum, heat and water fluxes. The study on 1997 El Nino teleconnection illustrates our interdisciplinary and multisensor approach to study climate variability. The diagram shows that the collapse of trade wind and the westerly wind anomalies in the central equatorial Pacific led to the equatorial ocean warming. The equatorial wind anomalies are connected to the anomalous cyclonic wind pattern in the northeast Pacific. The anomalous warming along the west coast of the United States is the result of the movement of the pre-existing warm sea surface temperature anomalies with the cyclonic wind anomalies toward the coast. The results led to a new study which identifies decadal ocean variations in the Northeast Pacific. Three studies of oceanic responses to wind forcing caused by the seasonal change of monsoons, the passage of a typhoon, and the 1997 El Nino, were successfully conducted. Besides wind forcing, we continue to examine new techniques for estimating thermal and hydrologic fluxes, through the inverse ocean mixed-layer model, through divergence of atmospheric water transport, and by direct retrieval from radiances observed by microwave radiometers. Greenhouse warming has been linked to water vapor measured by two spaceborne sensors in two studies. In the first study, strong baroclinicity and deep convection were found to transport water vapor to the upper atmosphere and increase greenhouse trapping over the storm tracks of the North Pacific and Atlantic. In another study, the annual cycle of greenhouse warming were related to sea surface temperature (SST) and integrated water vapor, and the latitudinal dependence of the magnitudes and phases of the annual cycles were compared.

Liu, W. Timothy↗
NASA NTRS2014

Using Ensemble Short-Term Initialized Coupled NASA GEOS5 Climate Model Integrations to Study Convective Bias Growth

The representation of convective processes, particularly deep convection in the tropics, remains a persistent problem in climate models. In fact structural biases in the distribution of tropical rainfall in the CMIP5 models is hardly different than that of the CMIP3 versions. Given that regional climate change at higher latitudes is sensitive to the configuration of tropical forcing, this persistent bias is a major issue for the credibility of climate change projections. In this study we use model output from integrations of the NASA Global Earth Observing System Five (GEOS5) climate modeling system to study the evolution of biases in the location and intensity of convective processes. We take advantage of a series of hindcast experiments done in support of the US North American Multi-Model Ensemble (NMME) initiative. For these experiments a nine-month forecast using a coupled model configuration is made approximately every five days over the past 30 years. Each forecast is started with an updated analysis of the ocean, atmosphere and land states. For a given calendar month we have approximately 180 forecasts with daily means of various quantities. These forecasts can be averaged to essentially remove "weather scales" and highlight systematic errors as they evolve. Our primary question is to ask how the spatial structure of daily mean precipitation over the tropics evolves from the initial state and what physical processes are involved. Errors in parameterized convection, various water and energy fluxes and the divergent circulation are found to set up on fast time scales (order five days) compared to errors in the ocean, although SST changes can be non-negligible over that time. For the month of June the difference between forecast day five versus day zero precipitation looks quite similar to the difference between the June precipitation climatology and that from the Global Precipitation Climatology Project (GPCP). We focus much of our analysis on the influence of SST gradients, associated PBL baroclinicity enabled by turbulent mixing, the ensuing PBL moisture convergence, and how changes in these processes relate to convective precipitation bias growth over this short period.

Cohen, Charlie↗
NASA NTRS2015

Climate Model Diagnostic Analyzer

The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

cloud computing↗
NASA NTRS2003

Satellites as Sentinels for Climate and Health

Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring, risk mapping, and surveillance of parameters useful to such problems as vector- borne and infectious diseases, air and water quality,. harmful algal blooms, W radiation, contaminant and pathogen transport in air and water, and thermal stress. Remote sensing, geographic information systems (GIs), global positioning systems (GPS), improved computation capabilities, and interdisciplinary research between the Earth and health science communities, together with local knowledge, are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global climate and health issues. These collaborative efforts are enabling increased understanding of the relationships among changes in temperature, rainfall, wind, soil moisture, solar radiation, vegetation, and the patterns of extreme weather events and health issues. This increased understanding and improved information and data sharing, in turn, empowers local health and environmental decision-makers to better predict climate-related health problems, decrease vulnerability, take preventive measures, and improve response actions. This paper provides a number of recent examples of how satellites - from their unique vantage point in space - can serve as sentinels for climate and health.

Maynard, Nancy G.↗
NASA NTRS2011

The Impact of Warm Pool El Nino Events on Antarctic Ozone

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific in austral spring and summer. Previous work found an enhancement in planetary wave activity in the South Pacific in austral spring, and a warming of 3-5 K in the Antarctic lower stratosphere during austral summer, in WPEN events as compared with ENSO neutral. In this presentation, we show that weakening of the Antarctic vortex during WPEN affects the structure and magnitude of high-latitude total ozone. We use total ozone data from TOMS and OMI, as well as station data from Argentina and Antarctica, to identify shifts in the longitudinal location of the springtime ozone minimum from its climatological position. In addition, we examine the sensitivity of the WPEN-related ozone response to the phase of the quasi-biennial oscillation (QBO). We then compare the observed response to WPEN events with Goddard Earth Observing System chemistry-climate model, version 2 (GEOS V2 CCM) simulations. Two, 50-year time-slice simulations are forced by annually repeating SST and sea ice climatologies, one set representing observed WPEN events and the second set representing neutral ENSO events, in a present-day climate. By comparing the two simulations, we isolate the impact of WPEN events on lower stratospheric ozone, and furthermore, examine the sensitivity of the WPEN ozone response to the phase of the QBO.

Hurwitz, Margaret M.↗
NASA NTRS1994

The global climate of December 1992-February 1993. Part 2: Large-scale variability across the tropical western Pacific during TOGA COARE

Recently, scientists from more than a dozen countries carried out the field phase of a project called the Coupled-Atmosphere Response Experiment (COARE), devoted to describing the ocean-atmosphere system of the western Pacific near-equatorial warm pool. The project was conceived, organized, and funded under the auspices of the International Tropical Ocean Global Atmosphere (TOGA) Program. Although COARE consisted of several field phases, including a year-long atmospheric enhanced monitoring period (1 July 1992 -- 30 June 1993), the heart of COARE was its four-month Intensive Observation Period (IOP) extending from 1 Nov. 1992 through 28 Feb. 1993. An overview of large-scale variability during COARE is presented. The weather and climate observed in the IOP is placed into context with regard to large-scale, low-frequency fluctuations of the ocean-atmosphere system. Aspects of tropical variability beginning in Aug. 1992 and extending through Mar. 1993, with some sounding data for Apr. 1993 are considered. Variability over the large-scale sounding array (LSA) and the intensive flux array (IFA) is emphasized.

Gutzler, D. S.↗
NASA NTRS2002

Geodetic Application of ROCSAT-3/COSMIC: Climate-Induced Time-Variable Gravity

The ROCSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) mission consists of a constellation of 6 low-earth orbiting satellites. In conducting the atmospheric limb sounding using the GPS radio occultation technique (which is the main objective of the mission), the satellite orbits are precisely determined at any given moment by GPS "high-low" satellite-to-satellite tracking. These precise orbit determination (POD) data contain useful information about the Earth's gravitational field and its time variations, for both geophysical and climate-related research. Our previous simulations showed that the use of these orbit data can yield an order of magnitude improvement over the state-of-the-art global gravity model EGM96 out to degree and order 20 (spatial resolution of 1000 km), depending on the mission design and orbit adjustment scenario. In this paper, the temporal variation signals of low-degree harmonics are the subject matter. These signals can be obtained from POD at the 800 km operational altitude (where the non-gravitational forces is weaker and can be better modeled and removed) during the lifetime of the mission. The time-varying gravity is becoming an important data source for studying climate-related global changes, especially in anticipating the use of the time-variable gravity data from the GRACE mission which was recently launched into orbit. Although not as precise as what GRACE promises to achieve, with much denser spatial and temporal coverages provided by 6 satellites and hence greatly reduced aliasing errors COSMIC represents independent and complementary observations for the new time-variable gravity research. We will present simulation results based on the present mission scenario.

Chao, Benjamin F.↗