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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Climate Impact and GIS Education Using Realistic Applications of Data.gov Thematic Datasets in a Structured Lesson-Based Workbook

This project created a workbook which teaches Earth Science to undergraduate and graduate students through guided in-class activities and take-home assignments organized around climate topics which use GIS to teach key geospatial analysis techniques and cartography skills. The workbook is structured to the White House's Data.gov climate change themes, which include Coastal Flooding, Ecosystem Vulnerability, Energy Infrastructure, Arctic, Food Resilience, Human Health, Transportation, Tribal Nations, and Water. Each theme provides access to framing questions, associated data, interactive tools, and further reading (e.g. The US Climate Resilience Toolkit and National Climate Assessment). Lessons make use of the respective theme's available resources. The structured thematic approach is designed to encourage independent exploration. The goal is to teach climate concepts and concerns, GIS techniques and approaches, and effective cartographic representation and communication results; and foster a greater awareness of publicly available resources and datasets. To reach more audiences more effectively, a two level approach was used. Level 1 serves as an introductory study and relies on only freely available interactive tools to reach audiences with fewer resources and less familiarity. Level 2 presents a more advanced case study, and focuses on supporting common commercially available tool use and real-world analysis techniques.

Satellite Imagery↗
NASA NTRS2017

Impact of Climate Change on Heat-Related Mortality in Jiangsu Province, China

A warming climate is anticipated to increase the future heat-related total mortality in urban areas. However, little evidence has been reported for cause-specific mortality or nonurban areas. Here we assessed the impact of climate change on heat-related total and cause-specific mortality in both urban and rural counties of Jiangsu Province, China, in the next five decades. To address the potential uncertainty in projecting future heat-related mortality, we applied localized urban- and nonurban-specific exposure response functions, six population projections including a no population change scenario and five Shared Socioeconomic Pathways (SSPs), and 42 temperature projections from 21 global-scale general circulation models and two Representative Concentration Pathways (RCPs). Results showed that projected warmer temperatures in 2016-2040 and 2041-2065 will lead to higher heat-related mortality for total non-accidental, cardiovascular, respiratory, stroke, ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes occurring annually during May to September in Jiangsu Province, China. Nonurban residents in Jiangsu will suffer from more excess heat-related cause-specific mortality in 2016-2065 than urban residents. Variations across climate models and RCPs dominated the uncertainty of heat-related mortality estimation whereas population size change only had limited influence. Our findings suggest that targeted climate change mitigation and adaptation measures should be taken in both urban and nonurban areas of Jiangsu Province. Specific public health interventions should be focused on the leading causes of death (stroke, IHD, and COPD), whose health burden will be amplified by a warming climate.

projection↗
NASA NTRS2017

Applications of VIC for Climate Land Cover Change Imapacts

Study focuses on the Lower Mekong Basin (LMB), the LMB is an economically and ecologically important region: (1) One of the largest exporters of rice and fish products, (2) Within top three most biodiverse river basins in the world. Natural climate variability plays an important role in water supply within the region: (1) Short-term climate variability (ENSO, MJO), (2) Long-term climate variability (climate change). Projections of climate change show there will be a decrease in water availability world wide which has implications for food security and ecology. Additional studies show there may be socioeconomic turmoil due to water wars and food security in developing regions such as the Mekong Basin. Southeast Asia has experienced major changes in land use and land cover from 1980 – 2000. Major economic reforms resulting in shift from subsistence farming to market-based agricultural production. Changes in land cover continue to occur which have an important role within the land surface aspect of hydrology.

remote sensing↗
NASA NTRS2017

The Future of Planetary Climate Modeling and Weather Prediction

Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

Del Genio, A. D.↗
NASA NTRS2018

Projecting Climate and Land Use Change Impacts on Actual Evapotranspiration for the Narmada River Basin in Central India in the Future

Assessment of actual evapotranspiration (ET) is essential as it controls the exchange of water and heat energy between the atmosphere and land surface. ET also influences the available water resources and assists in the crop water assessment in agricultural areas. This study involves the assessment of spatial distribution of seasonal and annual ET using Surface Energy Balance Algorithm for Land (SEBAL) and provides an estimation of future changes in ET due to land use and climate change for a portion of the Narmada river basin in Central India. Climate change effects on future ET are assessed using the ACCESS1-0 model of CMIP5. A Markov Chain model estimated future land use based on the probability of changes in the past. The ET analysis is carried out for the years 2009-2011. The results indicate variation in the seasonal ET with the changed land use. High ET is observed over forest areas and crop lands, but ET decreases over crop lands after harvest. The overall annual ET is high over water bodies and forest areas. ET is high in the premonsoon season over the water bodies and decreases in the winter. Future ET in the 2020s, 2030s, 2040s, and 2050s is shown with respect to land use and climate changes that project a gradual decrease due to the constant removal of the forest areas. The lowest ET is projected in 2050. Individual impact of land use change projects decreases in ET from 1990 to 2050, while climate change effect projects increases in ET in the future due to rises in temperature. However, the combined impacts of land use and climate changes indicate a decrease in ET in the future.

Kundu, Sananda↗
NASA NTRS2018

System and Method for Providing a Climate Data Analytic Services Application Programming Interface

A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface. The system includes a programming library that enables client device software to invoke the capabilities of a climate data analytics system through requests to various services supported by the climate data analytics system, and also includes a client-side communications interface that enables the programming library's methods to interact with a climate data analytics system's server interface to obtain access to the capabilities of the system. In one implementation, the programming library is implemented in the Python programming language. The programming library can include basic utilities that call a single, server-side method implemented by one of the various services supported by the climate data analytics system, and extended utilities that call a series of basic utilities and/or other extended utilities that have been placed under programmatic control in order to create client-side convenience methods and workflows.

Schnase, John L.↗
NASA NTRS2017

Multi-Model Impacts of Climate Change on Pollution Transport from Global Emission Source Regions

The impacts of climate change on tropospheric transport, diagnosed from a carbon monoxide (CO)-like tracer species emitted from global CO sources, are evaluated from an ensemble of four chemistry-climate model (CCMs) contributing to the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Model time-slice simulations for present-day and end of the 21st century conditions were performed under the Representative Concentrations Pathways (RCP) climate scenario RCP 8.5. All simulations reveal a strong seasonality in transport, especially over the tropics. The highest CO-tracer mixing ratios aloft occur during boreal winter when strong vertical transport is co-located with biomass burning emission source regions. A consistent and robust decrease in future CO-tracer mixing ratios throughout most of the troposphere, especially in the tropics, and an increase around the tropopause is found across the four CCMs in both winter and summer. Decreases in CO-tracer mixing ratios in the tropical troposphere are associated with reduced convective mass fluxes in this region, which in turn may reflect a weaker Hadley Cell circulation in the future climate. Increases in CO-tracer mixing ratios near the tropopause are largely attributable to a rise in tropopause height, although a poleward shift in the midlatitude jets may also play an important role in the extra-tropical upper troposphere. An increase in CO-tracer mixing ratios also occurs near the Equator, centred over EquatorialCentral Africa, extending from the surface to the mid troposphere which is most likely related to localised decreases in convection in the vicinity of the Intertropical Convergence Zone, resulting in larger CO-tracer mixing ratios over biomass burning regions and smaller mixing ratios downwind.

Tropospheric Transport↗
NASA NTRS2019

Water Vapour Adjustments and Responses Differ Between Climate Drivers

Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by 7% per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.4±0.9%K(exp -1) for sulfate to 9.8±2%K(exp -1) for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.2±0.5 to 9.9±0.7d between 1986-2005 and 2081-2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.

Hodnebrog, Øivind↗
NASA NTRS2019

Efficacy of Climate Forcings in PDRMIP Models

Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multimodel analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near‐surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multimodel mean efficacies based on ERF are close to one for global perturbations of methane, sulfate, black carbon, and insolation, but there is notable intermodel spread. We do not find robust evidence that the geographic location of sulfate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy‐induced bias of ±0.4 K in equilibrium climate sensitivity to CO2 doubling when estimated using the historical GSAT trend.

T B Richardson↗
NASA NTRS2018

Explicit Cloud Representation in the Atmos 1D Climate Model for Earth and Rocky Planet Applications

1D climate models are less sophisticated than 3D global circulation models (GCMs), however their computational time is much less expensive, allowing a large number of runs in a short period of time to explore a wide parameter space. Exploring parameter space is particularly important for predicting the observable properties of exoplanets, for which few parameters are known with certainty. Therefore, 1D climate models are still very useful tools for planetary studies. In most of these 1D models, clouds are not physically represented in the atmosphere, despite having a well-known, significant impact on a planetary radiative budget. This impact is simulated by artificially raising surface albedo, in order to reproduce the observed-averaged surface temperature (i.e. 288 K for modern Earth) and a radiative balance at the top of the atmosphere. This non-physical representation of clouds, causes atmospheric long wave and shortwaves fluxes to not match observational data. Additionally, this technique represents a parameter that is highly-tuned to modern Earth’s climate, and may not be appropriate for planets that deviate from modern Earth’s climate conditions. In this paper, we present an update to the climate model within the Atmos 1­D atmospheric modeling package with a physical representation of clouds. We show that this physical representation of clouds in the atmosphere allows both long wave and shortwave fluxes to match observational data. This improvement will allow us to study the energy fluxes for a variety of cloudy rocky planets, and increase our confidence in future simulations of temperature profile and net energy balance.

Thomas Fauchez↗
NASA NTRSDate not supplied

Evaluating Retrieval Algorithm Climate Stability: Estimating 3D Optical Thickness Bias Distributions by Cloud Type

Detecting climate trends on large spatiotemporal scales requires accurate, stable measurements and stable retrieval algorithms. We strive to estimate how time-variant retrieval algorithm biases may impact trend detection. Here we focus on the 3D cloud optical thickness (τc) bias, which is among the largest in passive cloud retrieval algorithms. If this bias is time dependent, a possibility with potential decadal changes in cloud morphology, it may obscure genuine trends in τc. Although previous studies have evaluated the cloud- and sun-view geometry-dependent 3D τc bias on small spatial scales, before our current study none have evaluated the stability of this well-known bias on climate-relevant large spatiotemporal scales. These studies must estimate large scale distributions of the 3D τc bias by cloud type and estimate how cloud type amount may change between two climate states. We employ a novel approach to estimate large scale distributions of 3D τc using a proxy of the bias that quantifies the departure of clouds from satisfying the 1D radiative transfer assumption used in passive τc retrievals. This existing globally-distributed proxy is an angular consistency metric that was developed using fused Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) measurements. Calculating the 3D τc bias and the proxy, for known cloud fields enables us to establish statistical relationships between these two quantities, which can be used to calculate large-scale distributions of the 3D τc bias. This approach limits the number of 3D radiative transfer simulations required to only those needed to estimate a statistical relationship between the 3D τc bias for known cloud fields and a proxy of the bias. It is likely that future studies will be needed to evaluate retrieval algorithm bias stability for other geophysical variables as the community develops climate data records from satellite observations and their retrievals. This must be done in addition to monitoring and correcting measurement errors and uncertainties and understanding their impact on retrieved essential climate variables.

Yolanda Shea↗
NASA NTRS2020

Global Carbon Cycle and Climate Feedbacks in the NASA GISS ModelE2.1

We present results from the NASA GISS ModelE2.1‐G‐CC Earth System Model with coupled climate‐carbon cycle simulations that were submitted to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) Coupled Climate‐Carbon Cycle MIP (C4MIP). Atmospheric CO2 concentration and carbon budgets for the land and ocean in the historical simulations were generally consistent with observations. Low simulated atmospheric CO2 concentrations during 1850‐1950 were due to excess uptake from prescribed land cover change, which erroneously replaced arid shrublands with higher biomass crops, and assumed high 2004 LAI values in vegetated lands throughout the historical simulation. At the end of the historical period, slightly higher simulated CO2 than observed resulted from the land being an insufficient net carbon sink, despite the net effect of CO2 fertilization and warming‐induced increases to leaf photosynthetic capacity. The global ocean carbon uptake agreed well with the observations with the largest discrepancies in the low latitudes. Future climate projection at 2091‐2100 agreed with CMIP5 models in the northward shift, of temperate deciduous forest climate and expansion across Eurasia along 60 °N latitude, and dramatic regional biome shifts from drying and warming in continental Europe. Carbon feedback parameters were largely similar to the CMIP5 model ensemble. For our model, the variation of land feedback parameters within the uncertainty arises from the fertilization feedback being less sensitive due to lack of increased vegetation growth, and the comparably more negative ocean carbon‐climate feedback is due to the large slowdown of the Atlantic overturning circulation.

Carbon cycle↗
NASA NTRS2020

Irrigation Water Demand Sensitivity to Climate Variability across the Contiguous United States

Climate variability is an important driver of irrigation water use in many regions. Efforts to anticipate climate change impacts on future water availability can benefit from understanding how irrigation water demand has responded to these drivers to date. Here we apply satellite derived data, meteorological reanalysis, an advanced land surface model, and available state level reports to quantify irrigation demand sensitivities to temperature and precipitation across the Contiguous United States, for the period of 2002-2017. As expected, strong negative correlations are found between precipitation and irrigation withdrawals, both simulated and reported. Temperature sensitivities, however, vary by region and season, as do the interactive effects of temperature and precipitation on irrigation. Climate-induced irrigation variability is largest in transitional climate zones. These transitional zones are generally separate from the regions where rates of irrigation withdrawals are greatest, such that climate-induced variability in irrigation demand represents a water resource consideration that is distinct from chronic over pumping.

Wanshu Nie↗
NASA NTRSDate not supplied

Modeled Impacts of LULC and Climate Change Predictions on Water Quality in Belize

Land use and land cover (LULC) change can have detrimental effects on water quality. In Belize, agricultural expansion creates the risk of increased sediment load and excess nutrients in runoff water, while deforestation removes potential infiltration sites for this outflow. Climate change and evolving precipitation rates can intensify the quantity of runoff, further enabling the flow of sediments and excess nutrients out to the lagoon surrounding the Belize Barrier Reef Reserve System (BBRRS). This study estimated future water quality in Belize by projecting LULC change through 2090 across Belize’s major watersheds based on observed trends from 2008-2018. Those LULC projections were subsequently combined with soil type data, elevation, and precipitation rates into a hydrologic model to produce runoff estimates as a proxy for water quality. The two Coupled Model Intercomparison Project phase 6 (CMIP-6) scenarios employed in the study represented bookend climate change scenarios, and both predicted lower precipitation rates in Belize over the next century due to climate change. When holding LULC change constant, these climate scenarios projected a decrease in runoff, suggesting a positive relationship between precipitation and runoff. The southern watersheds in particular are projected to experience greater decreases in annual rainfall and runoff by 2090. When holding climate constant, runoff increased by approximately 2.8% in the Conservation-focused LULC scenario by 2090, which was 28% lower than the Business as Usual scenario and 42% lower than the Development scenario.

water resources↗
NASA NTRSDate not supplied

Evaluating and Exploring Extreme Precipitation in CHIRPS3, CHIMES, and the Climate Hazards Station Database

Between 2015 and 2019, the impacts and losses associated with droughts, floods, and hurricanes surged through the interaction of increasing exposure and more extreme weather and climate (Funk 2021). In 2020, the Aon-Benfield Reinsurance Company reported that cyclones, floods, and droughts resulted in $165 billion (USD) in losses. For 2020, EM-DAT lists 363 flood, landslide, storm, and drought events impacting some 98 million people. As hazards mount, models indicate more variable precipitation, and observations indicate increasing extremes in humid regions, yet the small number of available gauge observations is declining. In this talk we briefly introduce two new resources: version 3 of the 1981-near present Climate Hazards center Infrared Precipitation with Stations (CHIRPS3) archive, and the 2000-near present Climate Hazards IMErg with Stations archive (CHIMES). The satellite-only CHIRP3 and CHIME components are based, respectively, on geostationary thermal infrared Cold Cloud Duration (CCD) values and the NASA GPM IMERGlate product. These archives benefit from thousands of station observations. In addition to standard global sources, the Climate Hazards station database includes about 5,000 additional stations in humid tropical and sub-tropical areas associated with likely increases in extreme rainfall. While effectively monitoring extreme precipitation is important to humanitarian agencies like FEWS NET, and to hydrologic modeling applications (a, b), evaluations of the widely used CHIRPS2 product indicate a propensity to underestimate extremes. Here, we explain the source of this problem. Then, focusing on pentad totals in 12 well-gauged regions, we use the high-quality gauge-based REGEN dataset to show that CHIRP3 and CHIME perform substantially better than CHIRP2. We examine trends in extremes in these validation regions, comparing REGEN results with values from the satellite-only CHIRP2, CHIRP3, CHIME and the gauge-enhanced CHIRP2, CHIRP3, CHIME. Trends in dry and humid regions are contrasted and compared. We conclude with global evaluations of the pentad CHIRP3, CHIRPS3, CHIME, CHIMES, and Climate Hazards station database products. How does the performance of the shorter period of record CHIME compare with CHIRP3? We anticipate that the sophisticated microwave-based IMERGlate inputs into CHIME will perform better. Where do we see the largest increases in extremes in these products? How well might CHIRPS3 and CHIMES perform in the context of humanitarian assistance efforts?

C Funk↗
NASA NTRS2022

Linkages Between GRACE Water Storage, Hydrologic Extremes, and Climate Teleconnections in Major African Aquifers

Water resources management is a critical issue in Africa where many regions are subjected to sequential droughts and floods. The objective of our work was to assess spatiotemporal variability in water storage and related controls (climate, human intervention) in major African aquifers and consider approaches toward more sustainable development. Different approaches were used to track water storage, including GRACE/GRACE Follow On satellites for Total Water Storage (TWS); satellite altimetry for reservoir storage, MODIS satellites for vegetation indices, and limited ground-based monitoring. Results show that declining trends in TWS (60–73 km3 over the 18 yr GRACE record) were restricted to aquifers in northern Africa, controlled primarily by irrigation water use in the Nubian and NW Saharan aquifers. Rising TWS trends were found in aquifers in western Africa (23–49 km3), attributed to increased recharge from land use change and cropland expansion. Interannual variability dominated TWS variability in eastern and southern Africa, controlled primarily by climate extremes. Climate teleconnections, particularly El Nino Southern Oscillation and Indian Ocean Dipole, strongly controlled droughts and floods in eastern and southern Africa. Huge aquifer storage in northern Africa suggests that the recent decadal storage declines should not impact the regional aquifers but may affect local conditions. Increasing groundwater levels in western Africa will need to be managed because of locally rising groundwater flooding. More climate resilient water management can be accomplished in eastern and southern Africa by storing water from wet to dry climate cycles. Accessing the natural water storage provided by aquifers in Africa is the obvious way to manage the variability between droughts and floods.

Africa water storage↗
NASA NTRS2021

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗
NASA NTRS2022

Volcanic Climate Warming through Radiative and Dynamical Feedbacks of SO2 Emissions

Volcanic flood basalt eruptions have been linked to or are contemporaneous with major climate disruptions, ocean anoxic events, and mass extinctions throughout at least the last 400M years of Earth’s history. Previous studies and recent history have shown that volcanically-driven climate cooling can occur through reflection of sunlight by H2SO4 aerosols, while longer-term climate warming can occur via CO2 emissions. We use the Goddard Earth Observing System Chemistry- Climate Model to simulate a four-year duration volcanic SO2 emission of the scale of the Wapshilla Ridge member of the Columbia River Basalt eruption. Brief cooling from H2SO4 aerosols is outweighed by dynamically and radiatively driven warming of the climate through a three orders of magnitude increase in stratospheric H2O vapor.

Scott D Guzewich↗