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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Platnick, Steven E.↗
DOE OSTI2023

Simulation of African Easterly Waves in a Global Climate Model

Abstract African easterly waves (AEWs) exert significant influence on local and downstream high-impact weather including tropical cyclone (TC) genesis over the Atlantic. Accurate representation of AEWs in climate and weather prediction models therefore is necessary for skillful predictions. In this study, we examine simulated AEWs, including their evolution, vertical structure, and linkage to tropical cyclone genesis, in the NASA Goddard Earth Observing System Model, version 5 (GEOS-5) atmospheric global climate model. Identified by the leading empirical orthogonal function mode of time-filtered precipitation, the observed westward propagating AEWs along the southern track over the Atlantic are largely captured in GEOS-5, but with a slower phase speed and significantly weaker amplitude downstream off the West Africa coast. The weak downstream development of AEWs in GEOS-5 is accompanied by much reduced TC genesis over the main development region. Further analyses suggest that the slow westward propagation and weaker AEW amplitude downstream can be ascribed to a weak African easterly jet, while overestimated negative (positive) meridional potential vorticity (PV) gradients appear to the north (south) of 10°N in GEOS-5. The greatly overestimated positive meridional PV gradient to the south of 10°N is expected to generate strong horizontal stretching in the AEW wave pattern in the model, which hinders organization of convection and its feedback to sustain the AEW development. Persistent and vigorous AEW precipitation in the Guinea Highlands of the West Africa coast could also be responsible for reduced westward propagation of AEWs in the model.

Meteorology & Atmospheric Sciences↗
NASA NTRS2017

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Global Circulation Models (GCMs)↗
DOE OSTI2024

Physical inconsistencies in the representation of the ocean heat-carbon nexus in simple climate models

The Ocean Heat-Carbon Nexus, linking ocean heat and carbon uptake, is crucial for understanding climate responses to cumulative carbon dioxide (CO 2 ) emissions and to net zero CO 2 emissions. It results from a suite of processes involving the exchange of heat and carbon across the sea-air interface as well as their storage below the mixed layer and redistribution by the ocean large-scale circulation. The Ocean Heat and Carbon Nexus is assumed to be consistently represented across two modelling platforms used in the latest IPCC assessments: the Earth System Models (ESMs) and the Simple Climate Models (SCMs). However, our research shows significant deficiencies in state-of-the-art SCMs in replicating the ocean heat-carbon nexus of ESMs due to a crude treatment of the ocean thermal and carbon cycle coupling. With one SCM, we show that a more realistic heat-to-carbon uptake ratio exacerbates the projected warming by 0.1 °C in low overshoot scenarios and up to 0.2 °C in high overshoot scenarios. It is therefore critical to explore how SCMs’ physical inconsistencies, such as the representation of the ocean heat-carbon nexus, can affect future warming projections used in climate assessments, not just by SCMs in Working Group 3 but also by ESMs in Working Group 1 via SCM-driven emission-to-concentration translation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

A permafrost implementation in the simple carbon-climate model Hector v.2.3.pf

Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

Dawn L. Woodard↗
NASA NTRS2024

Hector V3.2.0: Functionality and Performance of a Reduced-Complexity Climate Model

Hector is an open-source reduced complexity climate-carbon cycle model that models critical Earth system processes on a global and annual basis. Here we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3) and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO2 concentrations and global mean surface temperature, and its future temperature projections are consistent with more complex Earth System Model output data from the Sixth Coupled Model Intercomparison Project. We show that Hector V3 is a fully open source, flexible, performant, and robust simulator of global climate changes, note its limitations, and discuss future areas of improvement and research with respect to the model’s scientific, stakeholder, and educational priorities.

Kayln Dorheim↗
DOE OSTI2021

A permafrost implementation in the simple carbon–climate model Hector v.2.3pf

Abstract. Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating Climate Models with the CLIVAR 2020 ENSO Metrics Package

El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Fall and Rise of the Global Climate Model

Abstract Global models are an essential tool for climate projections, but conventional coarse‐resolution atmospheric general circulation models suffer from errors both in their parameterized cloud physics and in their representation of climatically important circulation features. A notable recent study by Terai et al. (2020, https://doi.org/10.1029/2020ms002274) documents a global model capable of reproducing the regime‐based effect of aerosols on cloud liquid water path expected from observational evidence. This may represent a significant advance in cloud process fidelity in global models. Such models can be expected to give a better estimate of the effective radiative forcing of the climate. If this advance in cloud process representation can be matched by advances in the representation of circulation features such as monsoons, then such models may also be able to navigate the complex tangle between spatially heterogeneous aerosol–cloud interactions and regional circulation patterns. This tight link between aerosol and circulation results in anthropogenic perturbations of climate variables of societal importance, such as regional rainfall distributions. Upcoming global models with km‐scale resolution may improve the regional circulation and be able to take advantage of the Terai et al. (2020, https://doi.org/10.1029/2020ms002274) improvement in cloud physics. If so, an era of significantly improved regional climate projection capabilities may soon dawn. If not, then the improvement in cloud physics might spur intensified efforts on problems in model dynamics. Either way, based on the rapid changes in aerosol emissions in the near future, learning to make reliable projections based on biased models is a skill that will not go out of style.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hector V3.2.0: functionality and performance of a reduced-complexity climate model

Abstract. Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Statistically bias-corrected and downscaled climate models underestimate the adverse effects of extreme heat on U.S. maize yields

Abstract Efforts to understand and quantify how a changing climate can impact agriculture often rely on bias-corrected and downscaled climate information, making it important to quantify potential biases of this approach. Here, we use a multi-model ensemble of statistically bias-corrected and downscaled climate models, as well as the corresponding parent models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), to drive a statistical panel model of U.S. maize yields that incorporates season-wide measures of temperature and precipitation. We analyze uncertainty in annual yield hindcasts, finding that the CMIP5 models considerably overestimate historical yield variability while the bias-corrected and downscaled versions underestimate the largest weather-induced yield declines. We also find large differences in projected yields and other decision-relevant metrics throughout this century, leaving stakeholders with modeling choices that require navigating trade-offs in resolution, historical accuracy, and projection confidence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Generalized Aerosol/Chemistry Interface (GIANT): A Community Effort to Advance Collaborative Science across Weather and Climate Models

Atmospheric aerosol and chemistry modules are key elements in Earth system models (ESMs), as they predict air pollutant concentrations and properties that can impact human health, weather, and climate. The current uncertainty in climate projections is partly due to the inaccurate representation of aerosol direct and indirect forcing. Aerosol/chemistry parameterizations used within ESMs and other atmospheric models span large structural and parameter uncertainties that are difficult to assess independently of their host models. Moreover, there is a strong need for a standardized interface between aerosol/chemistry modules and the host model to facilitate portability of aerosol/chemistry parameterizations from one model to another, allowing not only a comparison between different parameterizations within the same modeling framework, but also quantifying the impact of different model frameworks on aerosol/chemistry predictions. To address this need, we have initiated a new community effort to coordinate the construction of a Generalized Aerosol/Chemistry Interface (GIANT) for use across weather and climate models. We aim to organize a series of community workshops and hackathons to design and build GIANT, which will serve as the interface between a range of aerosol/chemistry modules and the physics and dynamics components of atmospheric host models. GIANT will leverage ongoing efforts at the U.S. modeling centers focused on building next-generation ESMs and the international AeroCom initiative to implement this common aerosol/chemistry interface. GIANT will create transformative opportunities for scientists and students to conduct innovative research to better characterize structural and parametric uncertainties in aerosol/chemistry modules, and to develop a common set of aerosol/chemistry parameterizations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

The effect of nonlinear diffusive heat transport in a simple climate model

The effects of nonlinear diffusive heat transport in North's (1975) model is reexamined. By inserting the nonlinearity into the original energy balance equation rather than the spectrally transformed linear algebraic equations, and including one more mode in the spectral expansion, it is found that nonlinear diffusion does give a significantly different sensitivity for states near the current climate. For linear diffusion, an increase of 0.1% of the solar constant from the present value is sufficient to melt all the ice on the earth, whereas an increase of about five times as large is required for nonlinear diffusion. This difference in sensitivity shows the importance of dynamical modeling in simple climate models.

Lin, C. A.↗
NASA NTRS1984

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Phillips, T. J.↗
NASA NTRS1984

Design for and efficient dynamic climate model with realistic geography

The long term climate sensitivity which include realistic atmospheric dynamics are severely restricted by the expense of integrating atmospheric general circulation models are discussed. Taking as an example models used at GSFC for this dynamic model is an alternative which is of much lower horizontal or vertical resolution. The model of Heid and Suarez uses only two levels in the vertical and, although it has conventional grid resolution in the meridional direction, horizontal resolution is reduced by keeping only a few degrees of freedom in the zonal wavenumber spectrum. Without zonally asymmetric forcing this model simulates a day in roughly 1/2 second on a CRAY. The model under discussion is a fully finite differenced, zonally asymmetric version of the Heid-Suarez model. It is anticipated that speeds can be obtained a few seconds a day roughly 50 times faster than moderate resolution, multilayer GCM's.

Suarez, M. J.↗
DOE OSTI2020

Accelerated Climate Model for Energy (ACME): Ocean and Sea-Ice Processes

The primary goal of this project was to understand the role of the ocean and sea-ice components in the evolution of the climate in both a high-resolution fully-coupled 1850 preindustrial control and present day transient climate simulations run using the Energy Exascale Earth System Model (E3SM), formerly known as the Accelerated Climate Model for Energy (ACME). Two distinct approaches to the initialization of the present day transients were tested: in the first, an ensemble of three transients used atmospheric reanalysis forced 0.1-degree ocean/sea-ice states, while a fourth transient was branched off the preindustrial control. Biases from the control were inherited by its successor transient, in particular, sea surface temperatures (SSTs) at high latitudes were too warm and too much northward meridional heat transport occurred in the North Atlantic Ocean. SSTs in the Northern Hemisphere and Atlantic meridional heat transport increased in the transients initialized from the ocean/sea-ice simulation over a 40-50 year period to largely resemble the transient branched off the control simulation. Excessive absorbed solar radiation (ASR) is considered to be responsible for the SST biases as well as the formation of mode waters in lighter density classes than in reality both in the Southern Ocean and the North Atlantic Ocean subtropical gyre. These mode waters ventilate the thermocline waters to the north of their formation sites explaining the excessive Atlantic meridional heat transport and some of the warming in the high-latitude North Atlantic Ocean after multiple decades.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.

Frei, Allan↗