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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 1,765 records · Page 98

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NASA NTRS1979

An energy-balance model with multiply-periodic and quasi-chaotic free oscillations

A slightly modified version of the one-dimensional time-dependent energy-balance climate model of Ghil and Bhattacharya (1978) is presented. The albedo-temperature parameterization has been reformulated and the smoothing of the temperature distribution in the tropics has been eliminated. The model albedo depends on time-lagged temperature in order to account for finite growth and decay time of continental ice sheets. Two distinct regimes of oscillatory behavior which depend on the value of the albedo-temperature time lag are considered.

Bhattacharya, K.↗

NASA NTRS1991

Simulation of the Pinatubo aerosol cloud in general circulation model

The global transport and dispersion of the Pinatubo aerosol cloud are simulated by means of a high-resolution stratospheric version of the NCAR Community Climate Model (CCM2) with an annual cycle. A passive tracer was injected into the model stratosphere over the Philippine Islands on June 15, and the transport was simulated for 180 d using an accurate semi-Lagrangian advection scheme. The simulated volcanic aerosol cloud initially drifted westward and expanded in longitude and latitude. The bulk of the aerosol cloud dispersed zonally to form a continuous belt in longitude, and remained confined to the tropics, centered near the 20-mb level for the entire 180-d model run, although a small amount was transported episodically into the upper troposphere in association with convective disturbances. Aerosol transported to the troposphere was dispersed within a few weeks into the Northern Hemisphere extratropics. In the Southern Hemisphere, the aerosol was mixed into the region equatorward of the core of the polar night jet during the first 50 d, but penetration into southern polar latitudes was delayed until the final warming in November.

Boville, Byron A.↗

NASA NTRS2013

Co-variation of Temperature and Precipitation in CMIP5 Models and Satellite Observations

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled (CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates.There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5)simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 % K for simulations and 3-4 % K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Nio Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (greater than or equal to 75 precipitation percentile), the precipitation response is 13-15%K for GPCP and 5%K for models while trends in P are 2.4% decade for GPCP, 0.6% decade for CMIP5 and 0.9decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

surface temperature↗

DOE OSTI2022

Will Anthropogenic Warming Increase Evapotranspiration? Examining Irrigation Water Demand Implications of Climate Change in California

Abstract Climate modeling studies and observations do not fully agree on the implications of anthropogenic warming for evapotranspiration (ET), a major component of the water cycle and driver of irrigation water demand. Here, we use California as a testbed to assess the ET impacts of changing atmospheric conditions induced by climate change on irrigated systems. Our analysis of irrigated agricultural and urban regions shows that warmer atmospheric temperatures have minimal implications for ET rates and irrigation water demands—about one percent change per degree Celsius warming (∼1% °C −1 ). By explicitly modeling irrigation, we control for the confounding effect of climate‐driven soil moisture changes and directly estimate water demand implications. Our attribution analysis of the drivers of ET response to global anthropogenic warming shows that as the atmospheric temperature and vapor pressure deficit depart from the ideal conditions for transpiration, regulation of stomata resistance by stressed vegetation almost completely offsets the expected increase in ET rates that would otherwise result from abiotic processes alone. We further show that anthropogenic warming of the atmosphere has minimal implications for mean relative humidity (<1.7% °C −1 ) and the surface available energy (<0.2% °C −1 ), which are critical drivers of ET. This study corroborates the growing evidence that plant physiological changes moderate the degree to which changes in potential ET are realized as actual ET.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Development of a two-dimensional zonally averaged statistical-dynamical model. II - The role of eddy momentum fluxes in the general circulation and their parameterization

The role of eddy momentum fluxes in the general circulation was investigated using a two-dimensional zonally averaged statistical-dynamical model described by Yao and Stone (1987), which is almost two orders of magnitude faster than the three-dimensional climate model of Hansen et al. (1983). Results show that the vertical structure of the meridional eddy flux has relatively little impact on the general circulation, presumably because the vertical structure is strongly constrained by the thermal wind relation and surface friction. On the other hand, it was found that, in order to simulate accurately the general circulation and its response to climate changes, parameterization of the vertically integrated meridional eddy flux of angular momentum is necessary. A new parameterization of this eddy momentum transport was carried out, which is intended to represent the transport due to large-scale transient eddies arising from baroclinic instability.

Stone, Peter H.↗

NASA NTRS2005

A Model Assessment of Satellite Observed Trends in Polar Sea Ice Extents

For more than three decades now, satellite passive microwave observations have been used to monitor polar sea ice. Here we utilize sea ice extent trends determined from primarily satellite data for both the Northern and Southern Hemispheres for the period 1972(73)-2004 and compare them with results from simulations by eleven climate models. In the Northern Hemisphere, observations show a statistically significant decrease of sea ice extent and an acceleration of sea ice retreat during the past three decades. However, from the modeled natural variability of sea ice extents in control simulations, we conclude that the acceleration is not statistically significant and should not be extrapolated into the future. Observations and model simulations show that the time scale of climate variability in sea ice extent in the Southern Hemisphere is much larger than in the Northern Hemisphere and that the Southern Hemisphere sea ice extent trends are not statistically significant.

Vinnikov, Konstantin Y.↗

DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Trade-Offs of Simplified Versus Comprehensive Representation of Mineralogy When Studying Dust Impacts on Earth’s Climate Systems

The intensity and direction of dust impacts on Earth’s climate systems depend on mineral composition. For example, the presence or absence of a few percent of iron oxides in dust will determine if dust is warming or cooling the atmosphere. Similarly, feldspar will enhance ice cloud formation, while acid gases in the atmosphere will react on the surface of dust calcite limiting acid rain. Still, most climate models use a simplified representation of dust mineralogy. They assume a fixed composition at emission which stays invariant during transport and removal. Such simplification assumes spatially and temporally constant physical and chemical properties of dust, and appears to provide satisfactory results when comparing some properties with observations. The trade-off is their lack of spatial gradients, which will fail to induce circulation, cloud and precipitation changes. The two reasons to omit mineral variations are the uncertainty of current atlases of soil mineral composition in arid regions, and, more practically, an improved runtime efficiency. The former reason is losing ground with the recent launch (July 2022) of a dedicated mission (NASA/JPL EMIT) to retrieve global soil mineralogy of dust sources at high spatial resolution. While the EMIT science team is finalizing a satisfactory global map of mineral composition of dust sources, we analyzed the interaction of dust mineralogy on radiation and its impact on the fast temperature response using different representations of mineral composition from detailed and spatially varying to simplified and globally uniform, assuming different hematite contents and methods to calculate optical properties. Our results show that resolving dust mineralogy reduces dust absorption, and results in improved agreement with observation-based single scattering albedo (SSA), radiative fluxes from CERES (the Clouds and the Earth’s Radiant Energy System), and land surface temperature from CRU (Climatic Research Unit), compared to the baseline bulk dust model version. It also results in distinct radiative impacts on Earth’s climate over North Africa. From our 19-year simulation, we will show that it leads to a reduction of over 50% in net downward radiation at top of atmosphere (TOA) across the Sahara and an approximately 20% reduction over the Sahel. We will explain how the surface temperature response affects the monsoon flow from the Gulf of Guinea. Interestingly, we find similar results by simply fixing the hematite content of dust to a globally uniform value of 0.9% by volume. We will discuss the underlying reasons for such results and show that they may be unrelated to the distribution of soil mineralogy. Still, an accurate representation of soil mineralogy is necessary to better understand dust impacts on the Earth’s climate systems.

dust impacts↗

NASA NTRSDate not supplied

Projecting the Lasting Fate of the Hunga Tonga-Hunga Ha’apai Eruption on the Stratosphere through Connecting Measurements to Models

On 15th Jan. 2022 the submarine volcano Hunga Tonga-Hunga Ha’apai (HTHH) injected approximately 0.5 Tg of sulfur dioxide into the stratosphere, but more significantly added 150-170 Tg of water vapor to the stratospheric background (over a 10% perturbation) in a matter of several hours. The sulfur dioxide rapidly converted to sulfate aerosol and along with water vapor, was transported around the Southern Hemisphere sub-tropics into midlatitudes with some transport into the Northern Hemisphere. With a much longer lifetime than sulfate aerosol, measurable water vapor anomalies are likely to persist for the remainder of the decade. Satellite measurements from limb and nadir viewing observing instruments provide the information needed to reasonably initialize the HTHH eruption in the Goddard Earth Observing System (GEOS) model using the “replay” framework coupled to the Global Modeling Initiative (GMI) stratosphere-troposphere chemical mechanism for the recent past and continue the simulations into the future with the free running chemistry climate model (CCM). Using a number of model ensemble members together with the satellite observations, we are beginning to quantify how the HTHH eruption is perturbing stratospheric composition and climate and projecting the influences to come as the enhanced water vapor continues to spread globally with only very slow removal mechanisms. We will also discuss some of the future measurement needs to understand how the atmosphere is responding to events like the HTHH eruption, large wildfires, and a changing climate.

volcano↗

DOE OSTI2024

Floods of Egypt’s Nile in the 21st century

Extreme precipitation and flooding events are rising globally, necessitating a thorough understanding and sustainable management of water resources. One such setting is the Nile River’s source areas, where high precipitation has led to the filling of Lake Nasser (LN) twice (1998–2003; 2019–2022) in the last two decades and the diversion of overflow to depressions west of the Nile, where it is lost mainly to evaporation. Using temporal satellite-based data, climate models, and continuous rainfall-runoff models, we identified the primary contributor to increased runoff that reached LN in the past two decades and assessed the impact of climate change on the LN’s runoff throughout the twenty-first century. Findings include: (1) the Blue Nile subbasin (BNS) is the primary contributor to increased downstream runoff, (2) the BNS runoff was simulated in the twenty-first century using a calibrated (1965–1992) rainfall-runoff model with global circulation models (GCMs), CCSM4, HadGEM3, and GFDL-CM4.0, projections as model inputs, (3) the extreme value analysis for projected runoff driven by GCMs’ output indicates extreme floods are more severe in the twenty-first century, (4) one adaptation for the projected twenty-first century increase in precipitation (25–39%) and flood (2%-20%) extremes is to recharge Egypt’s fossil aquifers during high flood years.

Climate change↗

DOE OSTI2022

Multi-Variable Parametric Analysis of Prototype Building Energy Performance Using Current and Future Weather Scenarios For Data-Driven Market Transformation Support

This project aimed to develop a public building simulation data set that may be used to inform building code development and guidelines for building innovation. The data set consists of several common building types and many representative locations across the United States. A parametric design of building properties was developed to create a range of building energy models that represent common building design decisions with a particular focus on fenestration options. The US Department of Energy prototype building energy models were altered according to a parametric building design and simulated using both current weather data and future weather estimates derived from global climate models. The resulting data set allows for pertinent exploration of building design parameters, including fenestration, within different environments across the United States in the broader context of climate change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Challenges and perspectives for large-scale temperature reconstructions of the past two millennia

Knowledge of the temperature variability during the last one to two millennia is important for providing a perspective to present-day climate excursions, for assessing the sensitivity of the climate to different forcings, and for providing a test bed for climate models. Since systematic instrumental temperature records only extend back to the nineteenth century, such knowledge mainly relies on climate-sensitive proxy data. Here we critically assess some of the many challenges related to large-scale multiproxy temperature reconstructions. We begin with a review of available large-scale temperature reconstructions, focusing on the differences in low-frequency variability and the response to natural forcings such as major volcanic eruptions and changes in total solar irradiance. Then, we discuss different proxy selection strategies, review previously used reconstruction methods, and discuss their ability to reconstruct the amplitude of the low-frequency variability. To shed additional light on the challenges of large-scale reconstructions, we investigate the spatial and temporal correlation structures in the observed temperature field and discuss the implications of these correlation structures regarding the required number and positions of proxies. We demonstrate how the unavoidable uncertainty related to noisy proxies will show up as bias and variance in the reconstruction and that the partition between these forms of errors depends on the reconstruction method. Pseudo-proxy experiments are conducted to further discuss the influence of noise and the requirements regarding the geographical location and number of proxies necessary for reliably reconstructing the low-frequency variability. Finally, we conclude with recommendations for future large-scale temperature reconstructions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Improving Low‐Cloud Fraction Prediction Through Machine Learning

Abstract In this study, we evaluated the performance of machine learning (ML) models (XGBoost) in predicting low‐cloud fraction (LCF), compared to two generations of the community atmospheric model (CAM5 and CAM6) and ERA5 reanalysis data, each having a different cloud scheme. ML models show a substantial enhancement in predicting LCF regarding root mean squared errors and correlation coefficients. The good performance is consistent across the full spectrums of atmospheric stability and large‐scale vertical velocity. Employing an explainable ML approach, we revealed the importance of including the amount of available moisture in ML models for representing spatiotemporal variations in LCF in the midlatitudes. Also, ML models demonstrated marked improvement in capturing the LCF variations during the stratocumulus‐to‐cumulus transition (SCT). This study suggests ML models' great potential to address the longstanding issues of “too few” low clouds and “too rapid” SCT in global climate models.

Geology↗

DOE OSTI2021

A novel approach to characterize the full spectrum and radiative properties of aerosols

Organic aerosols play a significant role in the absorption and radiative budget of the atmosphere, but current modeling approaches do not adequately capture the photo-chemical and oxidative bleaching that occurs during their lifetimes. Most climate models inaccurately assume constant optical properties of these particles, therefore leading to errors in their predictions. In this study we present an approach to better parameterize the optical properties of atmospheric aerosols, including brown carbon (BrC). Using thin-film spectrometry, the full spectrum of reflectivity and emissivity was used to calculate the complex refractive index for multiple species of organic aerosols. This is in contrast to previous techniques which only probe single wavelengths. Since BrC is a complex molecular mixture, we initially focused on single species absorption using four molecular surrogates. Dye-doped polyacrylic-acid thin-films were prepared on glass slides and compared to an aerosolized collection method. Verification of the collection method will open the door to characterizing the complex refractive index of smoke and ambient aerosol.

58 GEOSCIENCES↗

DOE OSTI2022

Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation (Final Report)

This project is based on new multi-frequency radar observations collected during the AWARE field campaign in 2016 at McMurdo Station by the ARM Mobile facility. Three scientific goals have been achieved. We have developed ice and mixed-phase cloud microphysics retrievals from multi-wavelength radar observations and ancillary observations, generally applicable at ARM sites. These technique generally better characterize the size of the ice crystals, their equivalent water content and the degree of riming better than using single wavelength techniques. We have characterized ice microphysical properties and ice processes via multi-frequency signatures. We have identified a unique mode in the McMurdo dataset appearing at quite cold temperature that we have attributed to riming processes. Triple frequency radar measurements unfortunately were available only for a short period but our work lays the foundation for building climatological and testing their replicability in models. Simultaneously case studies from the AWARE campaign have been exploited to evaluate and improve the NASA GISS ModelE3 climate model, including selection of case studies for combined goals of (i) running side-by-side using large-eddy simulation (LES) and ModelE3 in single-column model (SCM) mode and (ii) fingerprinting cloud processes in multi-wavelength radar observations. The different components of this work have contributed to 15 published papers with two currently under review.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Mesoscale convective systems in the third pole region: Characteristics, mechanisms and impact on precipitation

The climate system of the Third Pole region, including the (TP) and its surroundings, is highly sensitive to global warming. Mesoscale convective systems (MCSs) are understood to be a vital component of this climate system. Driven by the monsoon circulation, surface heating, and large-scale and local moisture supply, they frequently occur during summer and mostly over the central and eastern TP as well as in the downstream regions. Further, MCSs have been highlighted as important contributors to total precipitation as they are efficient rain producers affecting water availability (seasonal precipitation) and potential flood risk (extreme precipitation) in the densely populated downstream regions. The availability of multi-decadal satellite observations and high-resolution climate model datasets has made it possible to study the role of MCSs in the under-observed TP water balance. However, the usage of different methods for MCS identification and the different focuses on specific subregions currently hamper a systematic and consistent assessment of the role played by MCSs and their impact on precipitation over the TP headwaters and its downstream regions. Here, we review observational and model studies of MCSs in the TP region within a common framework to elucidate their main characteristics, underlying mechanisms, and impact on seasonal and extreme precipitation. We also identify major knowledge gaps and provide suggestions on how these can be addressed using recently published high-resolution model datasets. Three important identified knowledge gaps are 1) the feedback of MCSs to other components of the TP climate system, 2) the impact of the changing climate on future MCS characteristics, and 3) the basin-scale assessment of flood and drought risks associated with changes in MCS frequency and intensity. A particularly promising tool to address these knowledge gaps are convection-permitting climate simulations. Therefore, the systematic evaluation of existing historical convection-permitting climate simulations over the TP is an urgent requirement for reliable future climate change assessments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

Subpixel Snow-Covered-Area and Snow Grain Size From Mixture Analysis with AVIRIS Data

Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made. Snow grain size, SWE and snow impurities determine the spectral albedo of snow, which controls the net solar flux at the snowpack surface. Snow albedo is of the utmost importance in snowmelt modeling, yet the difficulty with which grain size, SWE, and impurities are mapped has left the spatial distribution of snow albedo in alpine catchments poorly understood. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been used to estimate sub-pixel snow-covered-area and snow grain size independently. In this paper we present a technique which improves estimates of both snow parameters by treating their mapping simultaneously.

Green Robert O.↗

NASA NTRS2002

Evaluation of Cirrus Cloud Simulations using ARM Data-Development of Case Study Data Set

Cloud-resolving models (CRMs) are being increasingly used to develop parametric treatments of clouds and related processes for use in global climate models (GCMs). CRMs represent the integrated knowledge of the physical processes acting to determine cloud system lifecycle and are well matched to typical observational data in terms of physical parameters/measurables and scale-resolved physical processes. Thus, they are suitable for direct comparison to field observations for model validation and improvement. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. The objective is to compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. Progress is assessing cloud and other environmental conditions will be described. Results of preliminary simulations using a regional cloud system model (MM5) and a CRM will be discussed. Focal science questions for the model comparison are strongly based on results of the idealized GCSS WG2 cirrus cloud model comparison projects (Idealized Cirrus Cloud Model Comparison Project and Cirrus Parcel Model Comparison Project), which will also be briefly summarized.

Starr, David OC.↗