Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Climate projections”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 829 records · Page 46

Projected regional changes in mean and extreme precipitation over Africa in CMIP6 models

Precipitation plays a crucial role in Africa's agriculture, water resources, and economic stability, and assessing its potential changes under future warming is important. In this study, we demonstrate that the latest generation of coupled climate models (CMIP6) robustly project substantial wetting over western, central, and eastern Africa. In contrast, southern Africa and Madagascar tend toward future drying. Under shared socioeconomic pathways (defined by Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5), our results suggest that most parts of Africa, except for southern Africa and Madagascar, will experience very wet years five times more often in 2050–2100, according to the multi-model median. Conversely, southern Africa and Madagascar will experience very dry years twice as often by the end of the 21st century. Furthermore, we find that the increasing risk of extreme annual rainfall is accompanied by a shift toward days with heavier rainfall. Our findings provide important insights into inter-hemispheric changes in precipitation characteristics under future warming and underscore the need for serious mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

58 GEOSCIENCES↗

Non-stationary historical trends in wave energy climate for coastal waters of the United States

The thirty-year non-stationary historical trends in the wave energy climate for United States coastal waters between 1980 and 2009 are investigated using spectral partitioned wave data generated from a WaveWatch III® (version 5.05) hindcast. In addition to historical trends in the omni-directional wave power, frequency and directionally resolved wave power, frequency and directional spreading, and seasonal variability, are examined for the first time, including their geographical distribution. These historical wave energy climate trends are linked to changes to the dominant wave systems and commensurate trends in the historical wind climate. Total wave power trends are consistent with other studies, but the present study identifies regions, and specific frequency and direction bands, where significant wave energy climate changes have occurred. For some regions, changes to wave climate parameters exceeded one-percent annually, more than thirty-percent over the study period. In conclusion, non-stationary trends of this magnitude have significant implications for ocean and coastal engineering projects designed assuming wave climates are stationary and warran

16 TIDAL AND WAVE POWER↗

Bhutan Water Resources III: Analyzing Forest Disturbances and Climate Data in Bhutan to Create a Tool for Assisting the Himalayan Environment Rhythm Observation and Evaluation Systems (HEROES) Project

Forest disturbances from bark beetle outbreaks are a major concern in Bhutan, known to cause extensive tree mortality to pine and spruce forests. The NASA DEVELOP team partnered with the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER), the Bhutan Foundation, and the Karuna Foundation to assess forest changes for the districts of Bumthang and Haa from 2000 to 2018. The project used preprocessed meteorological data from the Climate Hazards Center Infrared Precipitation with Station (CHIRPS) and Famine Early Warning System Network Land Data Assimilation System (FLDAS), along with Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) to assess apparent forest disturbance occurrences and observed climate trends. Shuttle Radar Topography Mission (SRTM) was used to resolve variations in elevation and slope for mountainous regions. Using the Google Earth Engine LandTrendr (LT) code algorithm, along with Landsat data, the team developed an app called Forest Disturbances Detection Toolbox (FDDT) to assess forest changes in Bhutan. The app includes climate variables for the focus districts, along with LT variables, which allows the end users to further examine the cause of disturbances. The team compared geocoordinates for known disturbances with LT disturbance detection products. Although additional work is needed in the future to validate the project end products from the FDDT, the tool will be provided to the project partners to aid forest management efforts in Bhutan.

Tashi Choden↗

Increasing precipitation whiplash in climate change hotspots

Abstract Throughout the world, the hydrologic cycle is projected to become more variable due to climate change, posing challenges in semi-arid regions with high water resource vulnerability. Precipitation whiplash results from hydrologic variability, and refers to interannual shifts between wet (⩾80th historical percentile) and dry (⩽20th historical percentile) years. Using five model large ensembles, we show that whiplash is projected to increase in frequency (25%–60%) and intensity (30%–100%) by 2100 across several semi-arid regions of the globe, including Western North America and the Mediterranean. These changes can be driven by increases in the frequency of wet years or dry years, or both, depending on the region. Moisture budget calculations in these regions illuminate the physical mechanisms behind increased whiplash. Thermodynamic changes generally dominate, with modulations by dynamics, evaporation, and eddies on regional or global scales. These findings highlight increasingly volatile hydrology in semi-arid regions as the 21st Century progresses.

54 ENVIRONMENTAL SCIENCES↗

Seamless Projections of Global Storm Surge and Ocean Waves Under a Warming Climate

For coastal adaptation purposes, it is important to estimate the climate related changes in extreme sea levels due to storm surges and ocean waves, in addition to mean sea level rise. In this study, we provide the first consistent and continuous estimation of projected changes in global storm surges and ocean waves from the past to the warmer future, based on an extremely high resolution global climate model. The spatial pattern in the trend of annual maximum sea surface heights and wave heights is predominantly driven by changes in tropical cyclone (TC) frequency. In the western North Pacific, future TC frequencies are projected to decrease, and the annual maximum sea surface heights and wave heights show decreasing trends (-20 cm/century and -200 cm/century). Although highly intense tropical cyclones are enhanced in the warmer climate, highly extreme storm surges and wave heights do not necessarily increase due to the large natural variability.

54 ENVIRONMENTAL SCIENCES↗

The SPARC-Reanalysis Intercomparison Project: Summary of Phase 1 and Plans for Phase 2 (S-RIP2): Chemical Reanalyses & Air Quality, Tropospheric Circulation, Extreme Events, and More

Reanalysis datasets are widely used to understand numerous atmospheric processes. Different reanalyses may give very different results for the same diagnostics. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP, https://s-rip.github.io/) is a coordinated activity to compare key diagnostics among available reanalyses, identify differences among reanalyses and their underlying causes, provide guidance on appropriate usage of reanalyses in scientific studies, and contribute to future improvements in the reanalysis products via collaborations with reanalysis centers and data users. S-RIP Phase 1 (completed in early 2022) focused primarily on the upper troposphere through the middle atmosphere and processes linking these regions to the troposphere and surface. We look forward to broadening our efforts in Phase 2 (S-RIP2), with new foci including studies of tropospheric circulation, extreme weather events, and their links to the stratosphere, and focusing on evaluation of chemical reanalyses, both those with a stratosphere / upper troposphere focus and those that focus on air quality applications. This presentation will provide a summary of Phase 1 results and discussion of future directions for S-RIP2, emphasizing applications to composition and chemistry studies as well as fostering capacity building for Early Career Scientists.

Jonathan S Wright↗

Projected changes in African easterly wave activity due to climate change

African easterly waves significantly influence regional hydroclimate, making it crucial to understand how global warming will impact their activity. Here, we investigate future changes in wave activity and assess the underlying mechanisms using an ensemble of Earth system models. We find a robust increase in wave activity over the Sahel–Sahara region by the end of the 21st century under two emission scenarios. This intensification is linked to increased baroclinicity associated with a strengthening of the meridional temperature gradient between the Guinea Coast and the Sahara. Our results also indicate that low-level warming enhances the waves by reinforcing monsoon flow, leading to increased convergence and vertical motion along the intertropical discontinuity. These energetic alterations significantly modify the conditions that currently produce these waves. Overall, our findings suggest that changes in wave activity could impact the transport of Saharan dust and mesoscale convective activity over the Sahel.

54 ENVIRONMENTAL SCIENCES↗

A USCLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

The USCLI VAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCM5), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models.

Schubert, Siegfried↗

Modelling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects.

Except for frozen water in ice and glaciers, groundwater is the world's largest distributed store of freshwater and has strategic importance to global food and water security. In this paper, the most recent advances quantifying groundwater depletion (GWD) are comprehensively reviewed. This paper critically evaluates the recently advanced modeling approaches estimating GWD at regional and global scales, and the evidence of feedbacks to the Earth system including sea-level rise associated with GWD. Finally, critical challenges and opportunities in the use of groundwater are identified for the adaption to growing food demand and uncertain climate.

Groundwater Depletion (GWD)↗

Disentangling climate and policy uncertainties for the Colorado River post-2026 operations

Abstract Lakes Mead and Powell in the Colorado River Basin underpin water and hydropower supply for the western United States. While the policies currently regulating the basin will expire by 2026, planning remains challenging due to intertwined climate variability and policy uncertainties. Based on streamflow projections from 10 dynamically downscaled CMIP6 global climate models and unique methods that add and remove internal variability, we evaluate future conditions at Powell and Mead under existing and alternative policies. Due to projected streamflow declines, under existing policy, both reservoirs will face substantial risks (>80% likelihood) of reaching dead pool before 2060. Adopting recently proposed alternative policies reduces but doesn’t eliminate such risks. All policies also exhibit tipping points where reservoir levels can change rapidly with a slight change in streamflow. A sustainable policy may require larger reductions to further reduce the reservoirs’ dead pool risks and provide better buffers from sudden changes.

Science & Technology - Other Topics↗

A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

Kusmec, Aaron (ORCID:000000032295385X)↗

Urban Expansion and Climate Change: Investigating the Impact of Future Scenarios on Child Health

Cities in the poorest countries of the world are rapidly urbanizing. In fact, some of the fastest growing cities on the planet are found in sub-Saharan Africa. Many people benefit from economic, educational, and health opportunities that exist in cities and, as a result, city-dwellers often face less risk of poverty and disease in the context of climate change than their rural-dwelling counterparts. However, rapid urbanization, resulting from a large and constant influx of migrants from rural areas, can put pressure on existing social, economic, and health systems. For poor cities, they face a challenge to support existing residents while also expanding to support the needs of migrants, many of whom are deeply impoverished. Additionally, in a climate change, linked to heat waves, floods, droughts, and other related events, can add stress to complex urban food, health, hygiene, and housing systems. In this project we investigate urban expansion, climate change, and health in four major African cities – Ouagadougou, Addis Ababa, Nairobi, and Kigali. We consider different scenarios of urban expansion using historic and contemporary maps of urban extent, combined with climate (temperature, rainfall, and vegetation) and land cover combined with spatially referenced health information from the Demographic and Health Surveys (DHS) to investigate the relationships between urban dwelling, climate change and health. Temperature and rainfall scenarios are developed under different urban land use futures (expanding agricultural areas versus reducing agricultural areas) to examine the ways that individual health outcomes related to malnutrition vary under different potential future conditions. Preliminary results of the research highlight the importance of temperature for health, in particular, and suggest that while urban conditions related to urban infrastructure (e.g., educational attainment, electricity access, and improved hygiene) cannot reduce health risks to counter the impacts of high temperatures and reduced agricultural land. As cities in poor countries urbanize, city-dwellers face unique risks when droughts, heat waves, and other extreme weather events occur. In this project we explore urban land use conditions, climate conditions and health using future scenarios. Specifically we evaluate health outcomes in the future while considering different land use practices, urban expansion, temperature, and rainfall conditions to identify individual-level risk and protective factors. We compare results across four major cities in sub Saharan Africa.

Public Health↗

Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM)

Traditionally, watershed-scale hydrology is simulated by distributed hydrological models with offline meteorological forcing data, or by regional regional climate models that link atmospheric and land hydrology interactions. Global climate models (GCMs) are rarely used to study watershed-scale hydrology due to the relatively coarse grid resolution, computationally expensive downscaling, and simplified physical processes. Recently, however, watershed-scale hydrology analysis has become possible in GCMs due to the development of variable-resolution GCMs that dynamically couple the hydrological processes between atmosphere and land systems at fine resolutions in selected regions and coarse resolution elsewhere. In this study, we used the variable-resolution Community Earth System Model (VR-CESM) with refined-resolution (14 km) in the western U.S. and eastern China to evaluate watershed-scale hydrology. Furthermore, we compared the historical VR-CESM outputs with gauge measurements and other hydrological models (e.g., National Water Model in the U.S.) and calibrated the subsurface runoff capacities in four mountainous watersheds. An RCP8.5 projection from 2007 to 2050 is used to estimate the impact of changing precipitation and snow climatology on watershed hydrology. We also analyzed the long-term runoff variability and the possibility of extreme runoff events as simulated by the VR-CESM. Although calibration is not possible in larger-scale watersheds, VR-CESM simulates the long-term annual variability of watersheds and provides insights on climate change impacts on hydrology. We conclude that refined-resolution VR-CESM can be used for watershed-scale hydrology analysis to understand water resources and water balance, in addition to traditional watershed-scale hydrological models. It enables hydrological analysis at multiple watersheds in one simulation and can help understand the two-way dynamics between land surface hydrology and atmospheric processes, and is especially practical for projecting climate change impacts. However, it is challenging to apply VR-CESM for hydrologic analysis in regulated watersheds as human factors (e.g., pumping, irrigation, water diversion) have not been fully addressed in VR-CESM.

54 ENVIRONMENTAL SCIENCES↗

Importance of Internal Variability for Climate Model Assessment

Benchmarking climate model simulations against observations of the climate is core to the process of building realistic climate models and developing accurate future projections. However, in many cases, models do not match historical observations, particularly on regional scales. If there is a mismatch between modeled and observed climate features, should we necessarily conclude that our models are deficient? Using several illustrative examples, we emphasize that internal variability can easily lead to marked differences between the basic features of the model and observed climate, even when decades of model and observed data are available. This can appear as an apparent failure of models to capture regional trends or changes in global teleconnections, or simulation of extreme events. Despite a large body of literature on the impact of internal variability on climate, this acknowledgment has not yet penetrated many model evaluation activities, particularly for regional climate. We emphasize that using a single or small ensemble of simulations to conclude that a climate model is in error can lead to premature conclusions on model fidelity. A large ensemble of multidecadal simulations is therefore needed to properly sample internal climate variability in order to robustly identify model deficiencies and convincingly demonstrate progress between generations of climate models.

Climate and Earth system modelling↗

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↗

ARC3.2 Summary for City Leaders Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network

ARC3.2 presents a broad synthesis of the latest scientific research on climate change and cities. Mitigation and adaptation climate actions of 100 cities are documented throughout the 16 chapters, as well as online through the ARC3.2 Case Study Docking Station. Pathways to Urban Transformation, Major Findings, and Key Messages are highlighted here in the ARC3.2 Summary for City Leaders. These sections lay out what cities need to do achieve their potential as leaders of climate change solutions. UCCRN Regional Hubs in Europe, Latin America, Africa, Australia and Asia will share ARC3.2 findings with local city leaders and researchers. The ARC3.2 Summary for City Leaders synthesizes Major Findings and Key Messages on urban climate science, disasters and risks, urban planning and design, mitigation and adaptation, equity and environmental justice, economics and finance, the private sector, urban ecosystems, urban coastal zones, public health, housing and informal settlements, energy, water, transportation, solid waste, and governance. These were based on climate trends and future projections for 100 cities around the world.

Ecosystems↗

Internal Climate Variability Obscures Future Freezing Rain Changes Despite Global Warming Trend

Abstract Although numerous studies have projected changes in freezing rain under future climate conditions, the internal variability of freezing rain remains poorly quantified. Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. By employing multivariate quantile mapping, we decompose the projected freezing rain trend into contributions from changes in temperature, relative humidity, and precipitation, which helps separate the forced response from internal climate variability. Our finding reveals a notable decrease in freezing rain occurrence in most areas. Despite a substantial temperature increase, internal variability overshadows climate forcing across a large portion of the eastern United States until about 2050. This insight has implications for practitioners, suggesting that the observed freezing rain frequency climatology continues to provide a relevant baseline for decision‐making in the near term. However, longer‐term design and adaptation plans should consider the projected changes in these regions.

Zhuang, Haoyu (Richard) [Department of Atmospheric↗