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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change

Abstract The future trajectory of atmospheric CO 2 concentration depends on the development of the terrestrial carbon sink, which in turn is influenced by forest dynamics under changing environmental conditions. An in‐depth understanding of model sensitivities and uncertainties in non‐steady‐state conditions is necessary for reliable and robust projections of forest development and under scenarios of global warming and CO 2 enrichment. Here, we systematically assessed if a biogeochemical process‐based model (3D‐CMCC‐CNR), which embeds similarities with many other vegetation models, applied in simulating net primary productivity (NPP) and standing woody biomass (SWB), maintained a consistent sensitivity to its 55 input parameters through time, during forest ageing and structuring as well as under climate change scenarios. Overall, the model applied at three contrasting European forests showed low sensitivity to the majority of its parameters. Interestingly, model sensitivity to parameters varied through the course of >100 yr of simulations. In particular, the model showed a large responsiveness to the allometric parameters used for initialize forest carbon and nitrogen pools early in forest simulation (i.e., for NPP up to ~37%, 256 g C·m −2 ·yr −1 and for SWB up to ~90%, 65 Mg C/ha, when compared to standard simulation), with this sensitivity decreasing sharply during forest development. At medium to longer time scales, and under climate change scenarios, the model became increasingly more sensitive to additional and/or different parameters controlling biomass accumulation and autotrophic respiration (i.e., for NPP up to ~30%, 167 g C·m −2 ·yr −1 and for SWB up to ~24%, 64 Mg C/ha, when compared to standard simulation). Interestingly, model outputs were shown to be more sensitive to parameters and processes controlling stand development rather than to climate change (i.e., warming and changes in atmospheric CO 2 concentration) itself although model sensitivities were generally higher under climate change scenarios. Our results suggest the need for sensitivity and uncertainty analyses that cover multiple temporal scales along forest developmental stages to better assess the potential of future forests to act as a global terrestrial carbon sink.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate warming threatens the persistence of a community of disturbance-adapted native annual plants

With ongoing climate change, populations are expected to exhibit shifts in demographic performance that will alter where a species can persist. This presents unique challenges for managing plant populations and may require ongoing interventions, including in situ management or introduction into new locations. However, few studies have examined how climate change may affect plant demographic performance for a suite of species, or how effective management actions could be in mitigating climate change effects. Over the course of two experiments spanning 6 yr and four sites across a latitudinal gradient in the Pacific Northwest, United States, here we manipulated temperature, precipitation, and disturbance intensity, and quantified effects on the demography of eight native annual prairie species. Each year we planted seeds and monitored germination, survival, and reproduction. We found that disturbance strongly influenced demographic performance and that seven of the eight species had increasingly poor performance with warmer conditions. Across species and sites, we observed 11% recruitment (the proportion of seeds planted that survived to reproduction) following high disturbance, but just 3.9% and 2.3% under intermediate and low disturbance, respectively. Moreover, mean seed production following high disturbance was often more than tenfold greater than under intermediate and low disturbance. Importantly, most species exhibited precipitous declines in their population growth rates (λ) under warmer-than-ambient experimental conditions and may require more frequent disturbance intervention to sustain populations. Aristida oligantha, a C4 grass, was the only species to have λ increase with warmer conditions. These results suggest that rising temperatures may cause many native annual plant species to decline, highlighting the urgency for adaptive management practices that facilitate their restoration or introduction to newly suitable locations. Frequent and intense disturbances are critical to reduce competitors and promote native annuals’ persistence, but even such efforts may prove futile under future climate regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Investigating added value of regional climate modeling in North American winter storm track simulations

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This work describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981–2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCMdriven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonalmean characteristics, a caveat is raised on the RCM ability to handle storm temporal ‘seriality’, as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Global biomass supply modeling for long-run management of the climate system

Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.

09 BIOMASS FUELS↗
DOE OSTI2023

Discussion on “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach”

Abstract We thank the authors for this interesting paper that highlights important ideas and concepts for the future of climate model ensembles and their storage, as well as future uses of stochastic emulators. Stochastic emulators are particularly relevant because of the statistical nature of climate model ensembles, as discussed in previous work of the authors (Castruccio et al. in J Clim 32:8511–8522, 2019; Hu and Castruccio in J Clim 34:8409–8418, 2021). We thank the authors for sharing of some of their data with us in order to illustrate this discussion. In the following, in Sect. 1 we discuss alternative techniques currently used and studied, namely lossy compression and ideas emerging from the climate modeling community, that could feed the discussion on ensemble and storage. In that section, we also present numerical results of compression performed on the data shared by the authors. In Sect. 2, we discuss the current statistical model proposed by the authors and its context. We discuss other potential uses of stochastic emulators in climate and Earth modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Chapter 9.12 - Weather, Climatic and Ecological Impacts of Onshore Wind Farms

Wind power is an environmentally sustainable technology that is likely to be part of the solution to the climate change, air pollution, and energy security problems. Despite many positive benefits, the rapid development of wind power has raised concerns about some potential adverse environmental impacts. While converting wind?s kinetic energy into electricity, wind turbines (WTs) modify properties of the atmospheric boundary layer (ABL) including the vertical profiles and surface-atmosphere exchanges of energy, momentum, mass, moisture, and trace gases. Given the current installed capacity and the projected installation worldwide, wind farms (WFs) are likely becoming a major driver of manmade land use change on Earth. Hence, understanding WT-atmosphere-surface interactions and assessing potential environmental impacts of WFs are of significant scientific, societal and economic importance. Here we review our progress in assessing potential impacts of onshore wind power on weather, climate and vegetation activity. A consensus is emerging based on observations and modeling studies that WFs cause a local to regional warming effect, particularly at nighttime, while the impacts on precipitation, wind patterns, crop yields and vegetation activity are uncertain. The warming effect results simply from vertical heat redistribution within the ABL due to turbine-enhanced vertical turbulent mixing in the wakes. At the global scale, with a substantial installation of WFs, mesoscale and climate models predicted large regional changes but small global impacts on temperature, while the impacts on precipitation, clouds, wind patterns and large-scale circulation have large uncertainties and are region specific and scale dependent. Despite increasing number of research efforts, our assessment of potential WF impacts is still very limited. Although the WF impacts are mostly local and limited to the near-surface ABL, this is the layer where we live and plants grow. Hence, more studies are needed to improve our understanding of WT-atmosphere-surface interactions and our capability to model and project the weather, climatic and ecological impacts of large WFs.

atmospheric boundary layer↗
DOE OSTI2016

Biophysical and hydrological effects of future climate change including trends in CO 2 , in the St. Joseph River watershed, Eastern Corn Belt

Future climate change has the potential to significantly impact crop growth, both directly due to CO 2 enhancement and indirectly, through temperature and moisture impacts. Here, this work investigates the biophysical and hydrological effects of future climate change, including trends in CO 2 , in the St. Joseph River watershed, Eastern Corn Belt. In this study, the Soil and Water Assessment Tool (SWAT) was first modified to take dynamic CO 2 concentration as input. A regional crop leaf development curve from Landsat TM imagery was also used to adjust model performance in corn leaf area development for the historical period. A multi-objective calibration strategy was employed to ensure acceptable simulation of streamflow, seasonal crop growth and interannual crop yield simultaneously. The model was then driven by future climate change and CO 2 data from three Atmosphere-Ocean General Circulation Models (AOGCMs), which are GFDL-CM2.1.1, NCAR-PCM1.3, and UKMO-HADCM3.1, under three Special Report on Emissions Scenarios (SRES), including B1, A1 B and A2 to investigate crop and streamflow response in two future periods: the near future (2021–2050) and the far future (2061–2090). The St. Joseph River watershed is expected to experience more winter and spring precipitation, but slightly decreasing summer precipitation. Due to increasing temperature and decreasing summer moisture, more drought stress is predicted. Both annual total aeration and drought stress are projected to be more variable in both future periods. Although future CO 2 enhancement will benefit the crop growth and final yield by improving radiation use efficiency (RUE) and reducing drought stresses, simulated corn yield still decreased by 6% in the near future period, and 16% in the far future period due to the combined effect of both climate change and CO 2 enhancement. Streamflow redistribution is also predicted in the future. Stream discharge is projected to increase for the whole flow range in the near future period. For the far future period, high flows are expected to decrease, while low flows are expected to increase, indicating more hydrologic drought and flood events in the St. Joseph River watershed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The impact of climate on solvent-based direct air capture systems

Direct air capture (DAC) is increasingly seen as a critical technology to reach mid-century net-zero targets and limit climate change to well below 2 °C. While the commercialization of DAC technologies is being pursued by numerous companies, there remains remarkably little information on their performance under “real-world” conditions. In this paper, for the first time, we investigate the influence of temperature and relative humidity of air on the CO 2 capture rate at the air contactor, overall energy requirement, CO 2 capture efficiency, and levelized cost of liquid-solvent based DAC systems. We observe that the overall energy demand decreases from 11.1 to 8.3 GJ/tCO 2 as the CO 2 capture rate increases from 40 to 85 % and that high capture rates can only be achieved in hot and humid climate conditions. We observe that a CO 2 capture rate of 75 % is only possible above 17 °C and 90 % relative humidity, and this drops dramatically at lower temperatures. It is also observed that water evaporation in the air contactor is highest at dry and low relative humidity, as expected. The sensitivity analysis showed that CO 2 capture efficiency is relatively insensitive to climate conditions for the liquid-solvent based DAC plant. Lastly, the levelized cost of natural gas standalone scenario varies from $240/tCO 2 to $409/tCO 2 , and this is more sensitive to temperature than relative humidity. The levelized cost of the natural gas stand-alone case is between 7 % and 10 % lower than that of an electric grid-connected case across all climate conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Multi-stage heat pump with two-phase injection for cold climate applications implementing natural refrigerants

Heat pump adoption in cold climates is limited by various technical challenges, including heat capacity degradation, compressor deterioration, and frost accumulation on the outdoor heat exchanger. Furthermore, wide-spread adoption of heat pumps with high global warming potential presents a possible environmental concern. Thus, we present a heat pump concept termed the “saturation cycle,” which uses numerous compression stages to improve energy efficiency and injects two-phase refrigerant between compression stages to dramatically reduce compressor discharge temperatures. Given the growing interest in heat pumps, there is a need for a straightforward framework for parametric evaluation of natural refrigerants in high-efficiency heat pump cycle architectures, like the saturation cycle, in adverse climates. This work develops a thermodynamic modeling framework and focuses on the application of natural refrigerants to explore the performance trends at extremely cold climates down to −25 °C. This study shows that a two-stage saturation cycle and four-stage saturation cycle can reduce the compressor discharge superheating by up to 51–57 % or 73–80 %, respectively, depending on the refrigerant. Furthermore, at −25 °C, a two-stage R-290 saturation cycle heat pump theoretically can use 25 % less power than a single-stage heat pump or can provide up to 59 % more heating capacity when using the same compressor power as the baseline single-stage heat pump. The exergetic parametric analyses show that two-phase refrigerant injection fundamentally improves the thermodynamic performance of the heat pump, reducing overall exergy destruction by 10 % compared to a vapor-injection heat pump, compared at −25 °C. Thus, the saturation cycle is a promising heat pump cycle architecture for cold climate applications due to its superior energy savings (or capacity improvement) and substantial de-superheating capabilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Spatio-temporal multivariate cluster evolution analysis for detecting and tracking climate impacts

Recent years have seen a growing concern about climate change and its impacts. While Earth System Models (ESMs) can be invaluable tools for studying the impacts of climate change, the complex coupling processes encoded in ESMs and the large amounts of data produced by these models, together with the high internal variability of the Earth system, can obscure important source-to-impact relationships. Here, this paper presents a novel and efficient unsupervised data-driven approach for detecting statistically-significant impacts and tracing spatio-temporal source-impact pathways in the climate through a unique combination of ideas from anomaly detection, clustering and Natural Language Processing (NLP). Using as an exemplar the 1991 eruption of Mount Pinatubo in the Philippines, we demonstrate that the proposed approach is capable of detecting known post-eruption impacts/events. We additionally describe a methodology for extracting meaningful sequences of post-eruption impacts/events by using NLP to efficiently mine frequent multivariate cluster evolutions, which can be used to confirm or discover the chain of physical processes between a climate source and its impact(s).

Anomaly detection↗
DOE OSTI2023

Further understanding “severe” climate risk

What makes one climate risk more “severe” or “dangerous” than others? Acknowledging that the notion of dangerousness can substantially vary from one sociocultural context to another, this Perspective paper builds on recent literature to explore three notions that are estimated to be foundational to climate risk severity: the physical, ecological and social thresholds leading to transformational and possibly abrupt changes; the irreversibility of these changes; and the cascading effects within and across the systems affected. While not necessarily the most determining dimensions of risk, they deserve more attention and integration into frameworks to assess “severe” climate risk, such frameworks remaining under-developed. The paper also takes stock of issues related to the spatial scale(s) of and the evidence base for severe climate risks. It lands on four intertwined research directions across geographies, sectors and populations, that are hypothesized to play a critical role in the coming decade, from feeding the next IPCC cycle to more broadly supporting the development of anticipatory adaptation policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impact of soiling on Si and CdTe PV modules: Case study in different Brazil climate zones

Soiling, particulate accumulation on photovoltaic (PV) module surfaces, reduces the available solar resource and the resulting generated device power. This case-study summarizes initial results of 5-year research on the contrasting soiling conditions in the tropical, subtropical, and semi-arid climates in Brazil. A major objective is to present a case study of the effects of soiling on PV module performance in different Brazil climate zones that represent the primary areas for the current and expanding Brazil solar installations. For this, the paper presents methodologies to quantify the soiling ratio (SRatio) and soiling rate (SRate) for two representative commercial technologies, polycrystalline or multicrystalline silicon (mc-Si) and thin-film cadmium telluride (CdTe) modules, through soiling monitoring stations deployed in the selected climate regions. An aim is to add to the growing soiling-research knowledge base through addressing these key factors and their relationships to critical electrical, solar resource, thermal, and local meteorological and environmental parameters. This paper presents, evaluates, and compares soiling rates and losses in Belo Horizonte, Minas Gerais (Equatorial Tropical: 19.92° S, 43.99° W), Porto Alegre, Rio Grande do Sul (Humid-Subtropical: 30.05° S, 51.17° W), and Brotas de Macaúbas, Bahia (Semi-Arid: 12.00° S, 42.63° W). The results show that soiling is moderate in all 3-regions, for example with 0.1%/day < SRate < 0.2%/day for Belo Horizonte. Precipitation dominates the cleaning of the modules in the summertime in this climate zone, while it is the major factor year-round in Rio Grande do Sul. Wind is the major issue mitigating the soiling accumulation for the Bahia installation. The methodology incorporates several key refinements, including the normalization and adjustment for the meteorological parameters (temperature, irradiance, wind, precipitation). The evaluations include the region-specific differing effects of non-uniform soiling, natural cleaning, and ambient temperatures.

14 SOLAR ENERGY↗
DOE OSTI2025

Enhancing building resilience in cold climates: Integrating heat pump technologies with renewable energy

As electrification advances and Cold Climate Heat Pump technology progresses, ensuring grid stability becomes increasingly critical for effective heating in cold climates. However, natural disasters, especially during winter, pose significant threats to grid stability, impacting the reliability of air-source heat pumps. Despite these challenges, the integration of renewable energy sources and storage solutions in heating systems has not been extensively studied within the context of resilience. Here, this paper delves into the literature on renewable-powered heat pumps to assess their potential in enhancing building resilience in U.S. cold climate zones, which are particularly susceptible to extreme weather and grid disruptions. By leveraging renewable sources—solar, geothermal, and water—in conjunction with heat pump technology and supported by thermal or battery storage, this approach aims to provide a dependable solution for maintaining indoor heating during grid failures. Our analysis begins with a review of various renewable energy sources suitable for heat pumps, followed by an exploration of their application in cold climate regions across the U.S., and discussions on potential integration strategies with heat pump systems. This study highlights the advantages and suitability of solar irradiance and geothermal resources, emphasizing the importance of tailored, site-specific assessments to maximize energy efficiency and resilience. Additionally, it outlines the economic and environmental considerations necessary for implementing such systems and identifies potential challenges and areas for future research to facilitate the broader integration of renewable energy in heating solutions for enhanced resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Climatic factors and human population changes in Eurasia between the Last Glacial Maximum and the early Holocene

Archaeological records document a significant expansion of populations from the Last Glacial Maximum (LGM, ~23–19 ka) to the early Holocene (EH, ~9 ka) in Eurasia, which is often attributed to the influence of orbital-scale climate changes. Yet, information remains limited concerning the climatic factor(s) which were responsible for conditioning demographic patterns. Here, in this work, we present results from an improved Minimalist Terrestrial Resource Model (MTRM), forced by a transient climate simulation from the LGM to the EH. Simulated potential hunter-gatherer population densities and spatial distributions across Eurasia are supported by observed archaeological sites in Europe and China. In the low latitudes, potential population size change was predominantly controlled by precipitation and its strong influence on plant and animal resources. In the middle-high latitudes, temperature was the dominant driver in influencing potential population size change and animal resource availability. Different regional responses of potential populations to climate change across Eurasia - owing to variations in available food resources between the LGM and EH - provide a better understanding of human dispersal during the Late Pleistocene.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Market expectations of a warming climate

In this paper, we compare prices of financial derivatives whose payouts are based on future weather outcomes to CMIP5 climate model predictions as well as observed weather station data across eight cities in the US from 2001 through 2020. Derivative prices respond both to short-term weather forecasts for the next two weeks and longer-term warming trends. We show that the long-term trends in derivative prices are comparable to station-level data and climate model output. The one exception is February in the northeastern US, where financial markets price in a polar vortex-induced cooling effect, a recent scientific finding that was not present in the older CMIP5 climate output. When looking at the spatial and temporal heterogeneity in trends, futures prices are more aligned with climate model output than observed weather station trends, suggesting that market participants closely align their expectations with scientific projections rather than recent observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impacts of climate change on future hurricane induced rainfall and flooding in a coastal watershed: A case study on Hurricane Harvey

The warming climate is likely to increase hurricane-associated extreme rainfall and lead to sea-level rise (SLR). Thus, how the floods induced by intense hurricanes respond to these potential changes is of great concern. This study investigates the future warmer climate impacts on hurricane-induced extreme rainfall, and—more importantly—the subsequent compound flooding at the watershed scale (from an event-based analysis perspective). To this goal, a modeling framework is designed based on the Distributed Hydrology Soil Vegetation Model (DHSVM), the Two-Dimensional fvand the Regional Community Earth System Model (R-CESM). The framework was applied to Hurricane Harvey (2017) at the Clear Creek watershed (a coastal watershed in the southern Houston) as a case study. The results show that the projected maximum rainfall totals over the watershed would be exacerbated by 17.7 % and 49.7 % in the 2050s and 2090s (respectively) under Representative Concentration Pathway 8.5 (RCP 8.5). This means a 16.1 % increase in Harvey rainfall over the watershed per degree Celsius increase in Mean Surface Temperature over the Gulf of Mexico region (18°~31° N, 77°~98° W). Meanwhile, the increases in maximum inundation extent would be 11.0 % (2050s) and 19.5 % (2090s). Furthermore, considerable increases in maximum inundation depth and duration in regions along the middle and downstream of Clear Creek (and also those around Clear Lake) are expected. The projected SLR will have little effect on the maximum inundation depth and extent if storm surge changes are not taken into account; meanwhile, it will influence the inundation duration at downstream locations. In conclusion, this modeling framework can be also applied at other coastal watersheds to evaluate the projected climate change impacts on the compound flooding induced by extreme climate events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗