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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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NASA NTRS2017

The Contribution of Solar Brightening to the US Maize Yield Trend

Predictions of crop yield under future climate change are predicated on historical yield trends1,2,3, hence it is important to identify the contributors to historical yield gains and their potential for continued increase. The large gains in maize yield in the US Corn Belt have been attributed to agricultural technologies4, ignoring the potential contribution of solar brightening (decadal-scale increases in incident solar radiation) reported for much of the globe since the mid-1980s. In this study, using a novel biophysical/empirical approach, we show that solar brightening contributed approximately 27% of the US Corn Belt yield trend from 1984 to 2013. Accumulated solar brightening during the post-flowering phase of development of maize increased during the past three decades, causing the yield increase that previously had been attributed to agricultural technology. Several factors are believed to cause solar brightening, but their relative importance and future outlook are unknown, making prediction of continued solar brightening and its future contribution to yield gain uncertain. Consequently, results of this study call into question the implicit use of historical yield trends in predicting yields under future climate change scenarios.

Matthijs Tollenaar↗

NASA NTRS1997

Oceanic Observations

For many years, merchant ships and the naval fleets of various countries have been the major source of data over and in the open ocean. Oceanographic research experiments and process studies in the field have also contributed to the climatological data bases for the global ocean, but, for the most part, these have been limited in duration and extent. However, over the last 10 years under the auspices of the World Climate Research Program and the International Geosphere Biosphere Program the role of the oceans in global and climate change has taken on increased significance. This has created a need for a considerably improved understanding of the seasonal, interannual, decadal and longer time-scale variability of the physical and biogeochemical attributes of the global ocean. As a result, over the past 10 years several major international field programs have been implemented and have had a tremendous impact on the number of in situ observations obtained for the global ocean. The Tropical Ocean Global Atmosphere (TOGA) program, the World Ocean Circulation Experiment (WOCE), and the Joint Global Ocean Flux Study (JGOFS) were designed with observational, modelling, and process study components aimed at analyzing different aspects of the ocean's role in the coupled climate system. In parallel with the field programs, continuous space-based observations of sea surface temperature, sea surface topography, and sea surface winds spanning nearly a decade or longer have become a reality. During this same time period, numerical ocean models and computational power have advanced to the point where the oceanographic observations, both in situ and remotely sensed, can be assimilated into numerical ocean models in order to provide a four-dimensional (x-y-z-t) depiction of the evolving state of the global ocean.

Busalacchi, Antonio J.↗

DOE OSTI2012

Practical Application of Parallel Coordinates for Climate Model Analysis

The determination of relationships between climate variables and the identification of the most significant associations between them in various geographic regions is an important aspect of climate model evaluation. The EDEN visual analytics toolkit has been developed to aid such analysis by facilitating the assessment of multiple variables with respect to the amount of variability that can be attributed to specific other variables. EDEN harnesses the parallel coordinates visualization technique and is augmented with graphical indicators of key descriptive statistics. A case study is presented in which the focus on the Harvard Forest site (42.5378N Lat, 72.1715W Lon) and the Community Land Model Version 4 (CLM4) is evaluated. It is shown that model variables such as land water runoff are more sensitive to a particular set of environmental variables than a suite of other inputs in the 88 variable analysis conducted. The approach presented here allows climate-domain scientists to focus on the most important variables in the model evaluations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A weather pattern responsible for increasing wildfires in the western United States

Abstract The western United States (U.S.) has been experiencing more severe wildfires, in part due to climate change, but the underlying synoptic patterns and their modulation in driving fire weather is unclear. Here we investigated the relationship between weather regimes (WRs) and fire weather indices, specifically vapor pressure deficit (VPD) and the Canadian Forest Fire Weather Index. By identifying five singular WRs using k-means clustering, we found that a particular regime (WR-2), one characterized by a distinct tripolar wave train pattern over the continental U.S., has exhibited an increased frequency since 1980. The ascribed WR-2 regime was found to be mainly responsible for rising trends in the fire weather indices, especially VPD. Further, the average fire indices of the WR-2 regime played a more important role than the frequency in shaping the rising trends in the fire weather indices. The increased frequency of the WR-2 WR was mainly attributed to anthropogenic forcing and, the year-to-year variation of the frequency was associated with sea surface temperature anomalies over the subtropical eastern Pacific. Human-induced climate change might have furthered the exacerbation of wildfire danger in the western U.S. by modulating the behaviors of WRs and fire weather indices.

Zhang, Wei (ORCID:0000000221698749)↗

DOE OSTI2018

Natural Variability Has Slowed the Decline in Western U.S. Snowpack Since the 1980s

Spring snowpack in the mountains of the western United States has not declined substantially since the 1980s, despite significant global and regional warming. Here in this paper we show that this apparent insensitivity of snowpack to warming is a result of changes in the atmospheric circulation over the western United States, which have reduced snowpack losses due to warming. Climate model simulations indicate that the observed circulation changes have been driven in part by a shift in Pacific sea surface temperatures that is attributable to natural variability, and not part of the simulated response to anthropogenic forcing. Removing the influence of natural variability reveals a robust anthropogenic decline in western U.S. snowpack since the 1980s, particularly during the early months of the accumulation season (October–November). These results suggest that the recent stability of western U.S. snowpack will be followed by a period of accelerated decline once the current mode of natural variability subsides.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully--coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110km grid spacing), ocean and sea ice (60km in the mid-latitudes and 30km at the equator and poles), and river transport (55km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima (CMIP6 DECK) simulations consisting of a long pre-industrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO 2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between pre-industrial (1850) and present-day, the trajectory of the warming diverges from observations in the second half of the 20th century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERF ari+aci = -1.65 W m -2 ) and high equilibrium climate sensitivity (ECS = 5.3 K).

58 GEOSCIENCES↗

DOE OSTI2024

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Observed Increase in Tropical Cyclone‐Induced Sea Surface Cooling Near the U.S. Southeast Coast

Abstract Tropical cyclones (TCs) induce substantial upper‐ocean mixing and upwelling, leading to sea surface cooling. In this study, we explore changes in TC‐induced cold wakes along the United States (U.S.) Southeast and Gulf Coasts during 1982–2020. Our study shows a significant increase in TC‐induced sea surface temperature (SST) cooling of about 0.20°C near the U.S. Southeast Coast over this period. However, for the U.S. Gulf Coast, trends in TC‐induced SST cooling are insignificant. Analysis of the large‐scale oceanic environments indicate that the increasing TC‐induced cold wakes near the Southeast coast have been predominantly caused by the cooling of subsurface waters in that region. This upper‐ocean change is attributed to the enhancement of surface pressure gradient across land‐sea boundary and the associated increase in alongshore winds over there. Further analysis with climate models reveals the important role of anthropogenic forcings in driving these changes in the atmospheric circulation response along the U.S. Southeast Coast.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Back-to-back high category atmospheric river landfalls occur more often on the west coast of the United States

Abstract The catastrophic December 2022-January 2023 nine atmospheric rivers in California underscore the urgent need to better understand such high-risk weather extremes. Here we applied a machine learning clustering tool to understand the activity of atmospheric river clusters. Reanalysis results show that clusters with high density, that is the time fraction under atmospheric river conditions within a cluster, exhibit more frequent high-category atmospheric rivers, alongside an increased likelihood for extreme precipitation and severe land surface responses. The key circulation patterns of atmospheric river clusters are primarily attributed to subseasonal variability. Furthermore, the occurrence and density of atmospheric river clusters are modulated by the daily variability of the geopotential height field. Climate model projections suggest that atmospheric river clusters with higher density and higher categories will be more frequent as warming level increases. Our findings emphasize the important role of atmospheric river clusters in the development of climate adaptation and resilience strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Surface wind energy trends near Taiwan in winter since 1871

The tropical surface wind speed in boreal winter reaches a maximum near Taiwan. This stable wind resource may be used for future clean energy development. How this surface wind energy source has changed in past 141 years is investigated using the 20 th century reanalysis dataset and CMIP5 models. Our observational analysis shows that the surface wind speed experienced a weakening trend in the past 141 years (1871 - 2010). The average decreasing rate is around -1.4 m s -1 per century. The decrease is primarily attributed to the relative sea surface temperature (SST) cooling in the subtropical North Pacific, which forces a large-scale low-level anti-cyclonic circulation anomaly in situ and is thus responsible for the southerly trend near Taiwan. The relative SST trend pattern is attributed mainly to the greenhouse gas effect associated with anthropogenic activities. The southerly trend near Taiwan is more pronounced in the boreal winter than in summer. Such seasonal difference is attributed to the reversed seasonal mean wind, which promotes more efficient positive feedback in the boreal winter. The CMIP5 historical run analysis reveals that climate models capture less SST warming and large-scale anti-cyclonic circulation in the subtropical North Pacific, but the simulated weakening trend of the surface wind speed near Taiwan is too small.

17 WIND ENERGY↗

DOE OSTI2019

Arboreal Epiphytes in the Soil-Atmosphere Interface: How Often Are the Biggest “Buckets” in the Canopy Empty?

Arboreal epiphytes (plants residing in forest canopies) are present across all major climate zones and play important roles in forest biogeochemistry. The substantial water storage capacity per unit area of the epiphyte “bucket” is a key attribute underlying their capability to influence forest hydrological processes and their related mass and energy flows. It is commonly assumed that the epiphyte bucket remains saturated, or near-saturated, most of the time; thus, epiphytes (particularly vascular epiphytes) can store little precipitation, limiting their impact on the forest canopy water budget. We present evidence that contradicts this common assumption from (i) an examination of past research; (ii) new datasets on vascular epiphyte and epi-soil water relations at a tropical montane cloud forest (Monteverde, Costa Rica); and (iii) a global evaluation of non-vascular epiphyte saturation state using a process-based vegetation model, LiBry. All analyses found that the external and internal water storage capacity of epiphyte communities is highly dynamic and frequently available to intercept precipitation. Globally, non-vascular epiphytes spend <20% of their time near saturation and regionally, including the humid tropics, model results found that non-vascular epiphytes spend ~1/3 of their time in the dry state (0–10% of water storage capacity). Even data from Costa Rican cloud forest sites found the epiphyte community was saturated only 1/3 of the time and that internal leaf water storage was temporally dynamic enough to aid in precipitation interception. Analysis of the epi-soils associated with epiphytes further revealed the extent to which the epiphyte bucket emptied—as even the canopy soils were often <50% saturated (29–53% of all days observed). Results clearly show that the epiphyte bucket is more dynamic than currently assumed, meriting further research on epiphyte roles in precipitation interception, redistribution to the surface and chemical composition of “net” precipitation waters reaching the surface.

Hargis, Hailey↗

NASA NTRS2013

SMAP Radar Processing and Calibration

The Soil Moisture Active Passive (SMAP) mission is part of the NASA space-based Earth observation program, and consists of an L-band radar and radiometer scheduled for launch into sun synchronous orbit in late 2014. A joint effort of the Jet Propulsion Laboratory (JPL) and the Goddard Space Flight Center (GSFC), the SMAP mission draws heavily on the design and risk reduction heritage of the Hydrosphere State (Hydros) mission [1], [2]. The SMAP science and applications objectives are to: 1) understand processes that link the terrestrial water, energy and carbon cycles, 2) estimate global water and energy fluxes at the land surface, 3) quantify net carbon flux in boreal landscapes, 4) enhance weather and climate forecast skill, and 5) develop improved flood prediction and drought monitoring capability. To meet these science objectives, SMAP ground processing will combine the attributes of the radar and radiometer observations (in terms of their spatial resolution and sensitivity to soil moisture, surface roughness, and vegetation) to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Model sensitivities translate the soil moisture accuracy to a radar backscatter accuracy of 1 dB (1 sigma) at 3 km resolution and a brightness temperature accuracy of 1.3 K at 40 km resolution. This paper will describe the level 1 radar processing and calibration challenges and the choices made so far for the algorithms and software implementation.

Synthetic Aperture Radar (SAR),↗

DOE OSTI2022

Surface warming in global cities is substantially more rapid than in rural background areas

Warming trends in cities are influenced both by large-scale climate processes and by local-scale urbanization. However, little is known about how surface warming trends of global cities differ from those characterized by weather observations in the rural background. Here, through statistical analyses of satellite land surface temperatures (2002 to 2021), we find that the mean surface warming trend is 0.50 ± 0.20 K·decade –1 (mean ± one S.D.) in the urban core of 2000-plus city clusters worldwide, and is 29% greater than the trend for the rural background. On average, background climate change is the largest contributor explaining 0.30 ± 0.11 K·decade –1 of the urban surface warming. In city clusters in China and India, however, more than 0.23 K·decade –1 of the mean trend is attributed to urban expansion. We also find evidence of urban greening in European cities, which offsets 0.13 ± 0.034 K·decade –1 of background surface warming.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Xarray Climate Data Analysis Tools

xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an "open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.

Vo, Tom↗

NASA NTRSDate not supplied

Simulated Disruptions of the Quasi-Biennial Oscillation

The Quasi-Biennial Oscillation has exhibited remarkable stability over the observational record—until a well-documented 2015/16 disruption and an emerging disruption in 2020/21. The possibility that disruptions are more frequent in a changing climate is important to consider, as the QBO affects predictability, stratospheric composition, and surface weather. However, this possibility is challenging to assess for a variety of reasons. For instance, the 2015/16 disruption has been attributed to anomalous easterly momentum flux from extratropical waves. By comparison, the 2020/21 disruption involves anomalous westerly forcing, less likely to originate from the same mechanism. We present a rich variety of QBO disruptions that spontaneously arise in integrations of the hightop NASA GISS Model E2.2. The disruptions loosely fall into several categories, some of which are analogous to the 2015/16 disruption and the 2020 disruption, as well as a previously undocumented possible disruption in 1988. Several factors appear to influence QBO disruptions in the model: natural variability, climate change, tropical SSTs, volcanic eruptions, and model physics/tuning. Although QBO representation is an ongoing challenge for models, the results point to a model-independent framework for assessment of disruptions.

Quasi-Biennial Oscillation↗

DOE OSTI2016

Improvements in Global Climate Model Microphysics Using a Consistent Representation of Ice Particle Properties

This paper describes a new approach for representing ice microphysics in climate models. In contrast with most previous schemes, this approach does not include separate categories for cloud and precipitating ice and instead uses a single two-moment category to represent all solid hydrometeors. Thus, there is no need for an ice “autoconversion” size threshold parameter, which has a critical impact on simulated climate in the Community Atmosphere Model (CAM5) yet is poorly constrained by theory or observations. Further, in the new treatment, all ice microphysical processes and parameters, including ice effective radius and mean fall speed, are formulated self-consistently and flexibly based on empirical ice particle mass–size and projected area–size relationships. This means that the scheme can represent the physical coupling between bulk particle density, mean fall speed, and effective radius, which is not possible in current schemes. Two different methods for specifying these relationships based on observations are proposed. The new scheme is tested in global simulations using CAM5. Differences in simulations using the two methods for specifying the mass– and projected area–size relationships, particularly the cloud radiative forcing, are attributable mainly to the effects on mean ice particle fall speed, impacting sedimentation and ice water path. With some tuning of parameters involved in calculating homogeneous freezing it produces a similar climate compared to the simulations using the original CAM5 microphysics. Thus, it can produce a comparable climate while improving the physical basis and self-consistency of ice particle properties and parameters.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

Role of Updraft Velocity in Temporal Variability of Global Cloud Hydrometeor Number

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

cloud condensation nuclei↗

DOE OSTI2022

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century

Rising ambient temperatures due to climate change will increase urban populations’ exposures to extreme heat. During hot hours, a key protective adaptation is increased air conditioning and associated consumption of electricity for cooling. But during cold hours, milder temperatures have the offsetting effect of reducing consumption of electricity and other fuels for heating. We elucidate the net consequences of these opposing effects in 36 cities in different world regions. We couple reduced-form statistical models of cities’ hourly responses of electric load to temperature with temporally downscaled projections of temperatures simulated by 21 global climate models (GCMs), projecting the effects of warming on the demand for electricity circa 2050. Cities' responses, temperature exposures and impacts are heterogeneous, with changes in total annual consumption ranging from –2.7 to 5.7%, and peak power demand increasing by as much as 9.5% at the multi-GCM median. The largest increases are concentrated in more economically developed mid-latitude cities, with less developed urban areas in the tropics exhibiting relatively small changes. The results highlight the important role of the structure of electricity demand: large temperature increases in tropical cities are offset by their inelastic responses, which can be attributed to lower air-conditioning penetration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗