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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 523 records · Page 29
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NASA NTRS1993

The role of large-scale eddies in the climate equilibrium. Part 2: Variable static stability

Lorenz's two-level model on a sphere is used to investigate how the results of Part 1 are modified when the interaction of the vertical eddy heat flux and static stability is included. In general, the climate state does not depend very much on whether or not this interaction is included, because the poleward eddy heat transport dominates the eddy forcing of mean temperature and wind fields. However, the climatic sensitivity is significantly affected. Compared to two-level model results with fixed static stability, the poleward eddy heat flux is less sensitive to the meridional temperature gradient and the gradient is more sensitive to the forcing. For example, the logarithmic derivative of the eddy flux with respect to the gradient has a slope that is reduced from approximately 15 on a beta-plane with fixed static stability and approximately 6 on a sphere with fixed static stability, to approximately 3 to 4 in the present model. This last result is more in line with analyses from observations. The present model also has a stronger baroclinic adjustment than that in Part 1, more like that in two-level beta-plane models with fixed static stability, that is, the midlatitude isentropic slope is very insensitive to the forcing, the diabatic heating, and the friction, unless the forcing is very weak.

Zhou, Shuntai↗
NASA NTRS2022

Exploring the Relationship Between Temperature Forecast Errors and Earth System Variables

Accurate subseasonal weather forecasts, from two weeks up to a season, can help reduce costs and impacts related to weather and corresponding extremes. The quality of weather forecasts has improved considerably in recent decades as models represent more details of physical processes, and they benefit from assimilating comprehensive Earth observation data as well as increasing computing power. However, with ever–growing model complexity, it becomes increasingly difficult to pinpoint weaknesses in the forecast models’ process representations which is key to improving forecast accuracy. In this study, we use a comprehensive set of observation–based ecological, hydrological and meteorological variables to study their potential for explaining temperature forecast errors at the weekly time scale. For this purpose, we compute Spearman correlations between each considered variable and the forecast error obtained from the ECMWF subseasonal–to–seasonal (S2S) reforecasts at lead times of 1–6 weeks. This is done across the globe for the time period 2001–2017. The results show that temperature forecast errors globally are most strongly related with climate–related variables such as surface solar radiation and precipitation, which highlights the model’s difficulties in accurately capturing the evolution of the climate–related variables during the forecasting period. At the same time, we find particular regions in which other variables are more strongly related to forecast errors. For instance, in central Europe, eastern North America and southeastern Asia, vegetation greenness and soil moisture are relevant, while in western South America and central North America, circulation–related variables such as surface pressure relate more strongly with forecast errors. Overall, the identified relationships between forecast errors and independent Earth observations reveal promising variables on which future forecasting system development could focus by specifically considering related process representations and data assimilation.

Temperature↗
NASA NTRS1999

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Fox-Rabinovitz, Michael S.↗
NASA NTRS2008

Climate Quality Broadband and Narrowband Solar Reflected Radiance Calibration Between Sensors in Orbit

vAs the potential impacts of global climate change become more clear [1], the need to determine the accuracy of climate prediction over decade-to-century time scales has become an urgent and critical challenge. The most critical tests of climate model predictions will occur using observations of decadal changes in climate forcing, response, and feedback variables. Many of these key climate variables are observed by remotely sensing the global distribution of reflected solar spectral and broadband radiance. These "reflected solar" variables include aerosols, clouds, radiative fluxes, snow, ice, vegetation, ocean color, and land cover. Achieving sufficient satellite instrument accuracy, stability, and overlap to rigorously observe decadal change signals has proven very difficult in most cases and has not yet been achieved in others [2]. One of the earliest efforts to make climate quality observations was for Earth Radiation Budget: Nimbus 6/7 in the late 1970s, ERBE in the 1980s/90s, and CERES in 2000s are examples of the most complete global records. The recent CERES data products have carried out the most extensive intercomparisons because if the need to merge data from up to 11 instruments (CERES, MODIS, geostationary imagers) on 7 spacecraft (Terra, Aqua, and 5 geostationary) for any given month. In order to achieve climate calibration for cloud feedbacks, the radiative effect of clear-sky, all-sky, and cloud radiative effect must all be made with very high stability and accuracy. For shortwave solar reflected flux, even the 1% CERES broadband absolute accuracy (1-sigma confidence bound) is not sufficient to allow gaps in the radiation record for decadal climate change. Typical absolute accuracy for the best narrowband sensors like SeaWiFS, MISR, and MODIS range from 2 to 4% (1-sigma). IPCC greenhouse gas radiative forcing is approx. 0.6 W/sq m per decade or 0.6% of the global mean shortwave reflected flux, so that a 50% cloud feedback would change the global reflected flux by approx. 0.3 W/sq m or 0.3% per decade in broadband SW calibration change. Recent results comparing CERES reflected flux changes with MODIS, MISR, and SeaWiFS narrowband changes concluded that only SeaWiFS and CERES were approaching sufficient stability in calibration for decadal climate change [3]. Results using deep convective clouds in the optically thick limit as a stability target may prove very effective for improving past data sets like ISCCP. Results for intercalibration of geostationary imagers to CERES using an entire month of regional nearly coincident data demonstrates new approaches to constraining the calibration of current geostationary imagers. The new Decadal Survey Mission CLARREO is examining future approaches to a "NIST-in-Orbit" approach of very high absolute accuracy reference radiometers that cover the full solar and infrared spectrum at high spectral resolution but at low spatial resolution. Sampling studies have shown that a precessing CLARREO mission could calibrate other geo and leo reflected solar radiation and thermal infrared sensors.

Wielicki, Bruce A.↗
NASA NTRS2013

On the Lack of Stratospheric Dynamical Variability in Low-top Versions of the CMIP5 Models

We describe the main differences in simulations of stratospheric climate and variability by models within the fifth Coupled Model Intercomparison Project (CMIP5) that have a model top above the stratopause and relatively fine stratospheric vertical resolution (high-top), and those that have a model top below the stratopause (low-top). Although the simulation of mean stratospheric climate by the two model ensembles is similar, the low-top model ensemble has very weak stratospheric variability on daily and interannual time scales. The frequency of major sudden stratospheric warming events is strongly underestimated by the low-top models with less than half the frequency of events observed in the reanalysis data and high-top models. The lack of stratospheric variability in the low-top models affects their stratosphere-troposphere coupling, resulting in short-lived anomalies in the Northern Annular Mode, which do not produce long-lasting tropospheric impacts, as seen in observations. The lack of stratospheric variability, however, does not appear to have any impact on the ability of the low-top models to reproduce past stratospheric temperature trends. We find little improvement in the simulation of decadal variability for the high-top models compared to the low-top, which is likely related to the fact that neither ensemble produces a realistic dynamical response to volcanic eruptions.

troposphere↗
NASA NTRS2013

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

The variability of Atlantic tropical cyclones (TCs) associated with El Nino-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions in the TC activities during eastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region as in observations. The difference between the models and observations is likely due to the bias of vertical wind shear in response to the shift of tropical heating associated with CP El Nino, as well as the model bias in the mean circulation.

Tropical Cyclones↗
NASA NTRS2005

Orbiting Carbon Observatory

Human impact on the environment has produced measurable changes in the geological record since the late 1700s. Anthropogenic emissions of CO2 today may cause the global climate to depart for its natural behavior for many millenia. CO2 is the primary anthropogenic driver of climate change. The Orbiting Carbon Observatory goals are to help collect measurements of atmospheric CO2, answering questions such as why the atmospheric CO2 buildup varies annually, the roles of the oceans and land ecosystems in absorbing CO2, the roles of North American and Eurasian sinks and how these carbon sinks respond to climate change. The present carbon cycle, CO2 variability, and climate uncertainties due atmospheric CO2 uncertainties are highlighted in this presentation.

orbiting carbon observatory (OCO)↗
NASA NTRS2021

Climate Drivers of Arctic Tundra Variability and Change Using an Indicators Framework

This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.

Uma S. Bhatt↗
NASA NTRS2017

Effects of Variable Eccentricity on the Climate of an Earth-Like World

The Kepler era of exoplanetary discovery has presented the Astronomical community with a cornucopia of planetary systems very different from the one which we inhabit. It has long been known that Jupiter plays a major role in the orbital parameters of Mars and its climate, but there is also a long-standing belief that Jupiter would play a similar role for Earth if not for its large moon. Using a three dimensional general circulation model (3-D GCM) with a fully-coupled ocean we simulate what would happen to the climate of an Earth-like world if Mars did not exist, but a Jupiter-like planet was much closer to Earths orbit. We investigate two scenarios that involve evolution of the Earth-like planets orbital eccentricity from 0 to 0.066 on a time scale of 4500 years, and from 0 to 0.283 over 6500 years. We discover that during most of the 6500 year scenario the planet would experience a moist greenhouse effect when near periastron. This could have implications for the ability of such a world to retain an ocean on time scales of 109 years. More Earth-like planets in multi-planet systems will be discovered as we continue to survey the skies and the results herein show that the proximity of large gas giant planets may play an important role in the habitabilty of these worlds. These are the first such 3-D GCM simulations using a fully-coupled ocean with a planetary orbit that evolves over time due to the presence of a giant planet.

Stability↗
NASA NTRS2021

Future Climate Change Significantly Alters Interannual Wheat Yield Variability Over Half of Harvested Areas

Climate change affects the spatial and temporal distribution of crop yields, which can critically impair food security across scales. A number of previous studies have assessed the impact of climate change on mean crop yield and future food availability, but much less is known about potential future changes in interannual yield variability. Here, we evaluate future changes in relative interannual global wheat yield variability (the coefficient of variation (CV)) at 0.25° spatial resolution for two representative concentration pathways (RCP4.5 and RCP8.5). A multi-model ensemble of crop model emulators based on global process-based models is used to evaluate responses to changes in temperature, precipitation, and CO2. The results indicate that over 60% of harvested areas could experience significant changes in interannual yield variability under a high-emission scenario by the end of the 21st century (2066–2095). About 31% and 44% of harvested areas are projected to undergo significant reductions of relative yield variability under RCP4.5 and RCP8.5, respectively. In turn, wheat yield is projected to become more unstable across 23% (RCP4.5) and 18% (RCP8.5) of global harvested areas—mostly in hot or low fertilizer input regions, including some of the major breadbasket countries. The major driver of increasing yield CV change is the increase in yield standard deviation, whereas declining yield CV is mostly caused by stronger increases in mean yield than in the standard deviation. Changes in temperature are the dominant cause of change in wheat yield CVs, having a greater influence than changes in precipitation in 53% and 72% of global harvested areas by the end of the century under RCP4.5 and RCP8.5, respectively. This research highlights the potential challenges posed by increased yield variability and the need for tailored regional adaptation strategies.

Climate change↗
NASA NTRS2016

The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB V1.0) Contribution to CMIP6

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decisionmakers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs (observational datasets) and indicated user needs for the gridding and processing of model output.

Vulnerability↗
NASA NTRS2011

Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition

Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.

Lau, William K. M.↗
NASA NTRS1998

A common-sense climate index: is climate changing noticeably?

We propose an index of climate change based on practical climate indicators such as heating degree days and the frequency of intense precipitation. We find that in most regions the index is positive, the sense predicted to accompany global warming. In a few regions, especially in Asia and western North America, the index indicates that climate change should be apparent already, but in most places climate trends are too small to stand out above year-to-year variability. The climate index is strongly correlated with global surface temperature, which has increased as rapidly as projected by climate models in the 1980s. We argue that the global area with obvious climate change will increase notably in the next few years. But we show that the growth rate of greenhouse gas climate forcing has declined in recent years, and thus there is an opportunity to keep climate change in the 21st century less than "business-as-usual" scenarios.

Time↗
NASA NTRS2004

Discoveries about Tropical Ozone from Satellite and SHADOZ (Southern Hemisphere ADditional Ozonesondes)

We have been producing near-real tropical tropospheric ozone ("TTO") data from TOMS since 1997 with Prof. Hudson and students at the University of Maryland. Maps for 1996-2000 for the operational Earth-Probe instrument reside at: . The tropics is a region strongly influenced by natural variability and anthropogenic activity and the satellite data have been used to track biomass burning pollution and to detect interannual variability and climate signals in ozone. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical variability. Thus, in 1998, NASA's Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ provides a public archive of ozonesonde data from twelve tropical and subtropical stations at http://croc.gsfc.nasa.gov/shadoz. Highlights from the first 4-5 years of SHADOZ data (presently > 2000 sondes) will be shown.

Thompson, Anne M.↗
NASA NTRS2015

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Simulation↗
NASA NTRSDate not supplied

Multi-source Estimates of Land / Ocean Moisture Transport Variability over the Satellite Era

It is widely appreciated that atmospheric transport of water from the world’s oceans is a process key to planetary energy balance as well as Earth's habitability. What is not yet clear is the extent of variability in moisture transports, the relative importance of interdecadal variability versus climate change signals, and importantly, our ability to quantify these changes. This work assesses variations in moisture transport variability during the satellite era (~1980 to present) by comparing several different estimates. (i) The most direct estimate is the vertically integrated flux convergence of moisture from reanalyses which use observed wind and moisture information. (ii) One alternative estimate comes from P-ET over land taken from global hydrologic models constrained with precipitation and near-surface meteorology. Here we use an ensemble of six models. An adjunct to this method is to employ satellite derive ET (e.g., GLEAM or DOLCE). (iii) Complementary to this is E-P over the global oceans derived from satellite estimates of P such as TRMM, GPM and GPCP and SeaFlux V3 or J-OFURO3 estimates of E, all relying heavily upon microwave measurements. Transport between land and oceans must essentially balance at monthly scales, i.e., vanish globally. (iv) a fourth perspective comes from estimate of terrestrial RO + storage rate, delta S. G-RUN Ensemble which uses observed streamflow and P measurements to calibrate a statistical model provides the former while GRACE, GRACE-FO provide total water storage anomalies used to calculate storage rate changes. GRACE REC uses GRACE data to train a precipitation-driven statistical model to extend storage estimates before the GRACE era. (All of these alternatives to reanalysis estimates also consider the small atmospheric column water vapor contribution.) We examine the transport changes from these three different methodologies, their relative accuracies and discuss the origin of their differences. Regional trends in moisture flux divergence and their role in multi-decadal trends are considered. Interannual variability arising in connection with ENSO variability is a dominant signal, driven largely by P changes. Trends since 1980 include reductions in moisture delivery to the western U.S., eastern Brazil, and central Africa with recovery of moisture convergence to the Sahel and parts of eastern North America.

Franklin Robertson↗