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At least 829 records · Page 46

Mapping Post-Climate Change Biogeographical Regions with Deep Latent Variable Models

Forecasting future changes to biodiversity due to shifts in climate is challenging due to nonlinear interactions between species as recorded in their presence/absence data. This work proposes using variational autoencoders with environmental covariates to identify low-dimensional structure in species’ joint co-occurrence patterns and leveraging this simplified representation to provide multivariate predictions of their habitat extent under future climate scenarios. We pursue a latent space clustering approach to map biogeographical regions of frequently co-occurring species and apply this methodology to a dataset from northern Belgium, generating predictive maps illustrating how these regions may expand or contract with changing temperature under a future climate scenario.

Krapu, Chris↗

Preparing the Power Sector to Navigate Climate and Water Risks

As the climate changes, so will water availability and other ambient conditions, threatening the reliability of today's power system and tomorrow's clean energy grid. That's why researchers at the National Renewable Energy Laboratory (NREL) - along with those at Sandia National Laboratories, Oak Ridge National Laboratory, the City University of New York, the Electric Power Research Institute, and the National Energy Technology Laboratory - are studying both regional and national climate and hydrologic changes to provide a comprehensive assessment of climate and water impacts and risks to the U.S. power grid.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

The National Climate Database (NCDB): An Unbiased 100-Year Dataset for PV Modeling

In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.

bias correction↗

Impact of climate change on water availability and its propagation through the Western U.S. power grid

Climate impact assessment for power systems has tended to focus on the effects of water availability on generation without explicitly considering how these impacts propagate through the interconnected grid to affect generation in other locations. We investigate the impact of projected water availability on the operations of the contemporary Western U.S. power grid, focusing specifically on regional interdependencies. Hydrologic simulations derived from three GCMs (CCSM4, INMCM4 and GFDL-CM3) and two radiative scenarios (RCP4.5 and RCP8.5) are used to force a large-scale, distributed water management model (MOSART-WM), which translates water availability into power generation constraints at hydropower plants and water-dependent thermo-electric plants. Power system dynamics are evaluated using the production cost model PLEXOS. We find that the inter-regional connections across the Western U.S. electricity infrastructure are key in managing drastic variations in regional water availability. Net generation in the Northwest and Northern California is substantially sensitive to local water availability. Generation from the Desert Southwest emerges as a critical resource to compensate for variations in water availability in those regions. Climate change impacts on Northwestern water availability therefore drive future changes in other regions’ generation and regional power flows. The large inter-annual hydrological variability of Northern California exacerbates grid stress arising from long-term changes in water availability in the Northwest. While the regional power flow directions seem insensitive to long-term variations in water availability, the analysis highlights the need to consider other compounding regional factors such as changes in Southern California net load or changes in regional fuel prices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An assessment of Earth's climate sensitivity using multiple lines of evidence

In this work, we assess evidence relevant to Earth's equilibrium climate sensitivity per doubling of atmospheric CO 2 , characterized by an effective sensitivity S . This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density (PDF) for S given all the evidence, including tests of robustness to difficult-to-quantify uncertainties and different priors. The 66% range is 2.6-3.9 K for our Baseline calculation, and remains within 2.3-4.5 K under the robustness tests; corresponding 5-95% ranges are 2.3-4.7 K, bounded by 2.0-5.7 K (although such high-confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent, and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S , in particular using comprehensive models and process understanding to address limitations in the traditional forcing-feedback paradigm for interpreting past changes.

54 ENVIRONMENTAL SCIENCES↗

Seasonal Dependent Impact of Ice Cloud Longwave Scattering on the Polar Climate

Most climate models neglect cloud longwave (LW) scattering because scattering is considered negligible compared to strong LW absorption by clouds and greenhouse gases. While this rationale is valid for simulating extrapolar regions, it is questionable for the polar regions, where the atmosphere is dry and hence has weak absorption, and ice clouds that have strong scattering capability frequently occur. Using the slab-ocean Community Earth System Model, we show that ice cloud LW scattering can warm winter surface air temperature by 0.8–1.8 K in the Arctic and 1.3–1.9 K in the Antarctic, while this warming becomes much weaker in polar summer. Such scattering effect cannot be correctly assessed when sea surface temperature and sea ice are prescribed as this effect is manifested through a surface-atmosphere coupling. Furthermore, cloud LW scattering is a necessity for the correct simulation of polar climate and surface radiation budget, especially in the winter.

54 ENVIRONMENTAL SCIENCES↗

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗

Trends of Sediment Resuspension and Budget in Southern Lake Michigan Under Changing Wave Climate and Hydrodynamic Environment

Sediment suspension and transport driven by waves and currents play a significant role in both the ecological and physical environments of large lakes. Lake Michigan has faced a rapidly increasing water level associated with intensified wind waves in the past decade. To investigate the spatiotemporal characteristics of suspended sediment concentration (SSC) and associated coastal sediment budgets in southern Lake Michigan, a 30-year (1991–2020) hindcast was performed using a coupled wave-current-sediment model (SWAN-FVCOM-CSTMS). We found that in southern Lake Michigan, the basin-wide mean SSC increased, and the coastal sediment loss accelerated dramatically, corresponding with intensified waves, currents and lake water level rises over the past decade. The basin-wide mean SSC, coastal sediment loss, wave height, wind speed, current speed, and water level in southern Lake Michigan are highly correlated. Spatially, the results reveal decreases in coastal SSC and sediment loss in the western portion of the southern basin, while the eastern sectors show an increase in both metrics. This reflects a clear shift in the wave climate and hydrodynamic environment. The alterations in long-term coastal sediment budgets imply that considerable shoreline transformations are being influenced by modifications in the wave climate. Understanding the spatiotemporal characteristics of SSC and coastal sediment budgets is crucial for strategic water resource management and coastal infrastructure planning.

54 ENVIRONMENTAL SCIENCES↗

The GFDL‐CM4X Climate Model Hierarchy, Part II: Case Studies

This paper is Part II of a two‐part paper that documents the Climate Model version 4X (CM4X) hierarchy of coupled climate models developed at the Geophysical Fluid Dynamics Laboratory. Part I of this paper is presented in Griffies et al. (2025a, https://doi.org/10.1029/2024MS004861 ). Here we present a suite of case studies that examine ocean and sea ice features that are targeted for further research, which include sea level, eastern boundary upwelling, Arctic and Southern Ocean sea ice, Southern Ocean circulation, and North Atlantic circulation. The case studies are based on experiments that follow the protocol of version 6 from the Coupled Model Intercomparison Project. The analysis reveals a systematic improvement in the simulation fidelity of CM4X relative to its CM4.0 predecessor, as well as an improvement when refining the ocean/sea ice horizontal grid spacing from the 0.25° of CM4X‐p25 to the 0.125° of CM4X‐p125. Even so, there remain many outstanding biases, thus pointing to the need for further grid refinements, enhancements to numerical methods, and/or advances in parameterizations, each of which target long‐standing model biases and limitations.

54 ENVIRONMENTAL SCIENCES↗

Taking stock of national climate policies to evaluate implementation of the Paris Agreement

Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO 2 eq by 2030 with the optimal pathways to implement the well below 2 °C and 1.5 °C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2 °C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossilfuel- dependent countries.

54 ENVIRONMENTAL SCIENCES↗

Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation

Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of “seasonally variable regimes becoming more variable”. Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation.

54 ENVIRONMENTAL SCIENCES↗

Quantifying uncertainty in aggregated climate change risk assessments

High-level assessments of climate change impacts aggregate multiple perils into a common framework. This requires incorporating multiple dimensions of uncertainty. Here we propose a methodology to transparently assess these uncertainties within the ‘Reasons for Concern’ framework, using extreme heat as a case study. We quantitatively discriminate multiple dimensions of uncertainty, including future vulnerability and exposure to changing climate hazards. High risks from extreme heat materialise after 1.5–2 °C and very high risks between 2–3.5 °C of warming. Risks emerge earlier if global assessments were based on national risk thresholds, underscoring the need for stringent mitigation to limit future extreme heat risks.

54 ENVIRONMENTAL SCIENCES↗

Climate and hydraulic traits interact to set thresholds for liana viability

Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.

54 ENVIRONMENTAL SCIENCES↗

Hidden delays of climate mitigation benefits in the race for electric vehicle deployment

Although battery electric vehicles (BEVs) are climate-friendly alternatives to internal combustion engine vehicles (ICEVs), an important but often ignored fact is that the climate mitigation benefits of BEVs are usually delayed. The manufacture of BEVs is more carbon-intensive than that of ICEVs, leaving a greenhouse gas (GHG) debt to be paid back in the future use phase. Here we analyze millions of vehicle data from the Chinese market and show that the GHG break-even time (GBET) of China’s BEVs ranges from zero (i.e., the production year) to over 11 years, with an average of 4.5 years. 8% of China’s BEVs produced and sold between 2016 and 2018 cannot pay back their GHG debt within the eight-year battery warranty. We suggest enhancing the share of BEVs reaching the GBET by promoting the effective substitution of BEVs for ICEVs instead of the single-minded pursuit of speeding up the BEV deployment race.

33 ADVANCED PROPULSION SYSTEMS↗

The path to 1.5 °C requires ratcheting of climate pledges

Using model simulations of high-ambition emissions pathways, we show that ratcheting—or increasing—climate ambition through 2030 will be crucial to limiting global peak temperature changes this century. Although updated pledges offered in advance of the Glasgow climate conference in 2021 meaningfully strengthened global ambition in 2030 compared to the 2015 Paris pledges, here, our study underscores the importance of countries ratcheting their 2030 pledges further to reduce the magnitude of temperature overshoot and consequently reduce the risks of irreversible and adverse consequences to natural and human systems.

54 ENVIRONMENTAL SCIENCES↗

Irrigation-induced land water depletion aggravated by climate change

Agricultural irrigation has experienced rapid expansion, and its growing freshwater consumption is potentially exacerbating water scarcity issues. Previous studies predominantly relied on observations or land-only simulations, often neglecting land–atmosphere interactions or failing to capture long-term evolution. We therefore analyse the effects of historical irrigation expansion on water fluxes and resources using seven Earth system models. Here we show that irrigation expansion in many regions substantially decreases the net water influx from the atmosphere to land, further aggravating the existing drying trends caused by climate change. For example, irrigation expansion changed the trend of this net influx from −0.664 ( ± 0.283) to −1.461 ( ± 0.261) mm yr −2 in South Asia after 1960. Consequently, the local terrestrial water storage depletion rate is substantially enlarged by irrigation expansion (for example, from −2.559 ( ± 0.094) to −16.008 ( ± 0.557) mm yr −1 ). Our results attribute the land water loss to irrigation expansion and climate change, calling for immediate solutions to tackle the negative trends.

irrigation↗

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗

From carbon to climate action: harnessing basalt for geological carbon dioxide (CO 2 ) storage onshore and offshore

Abating emissions and reducing atmospheric concentrations of carbon dioxide (CO 2 ) are crucial in avoiding catastrophic climate change. Basalt reservoirs offer suitable CO 2 storage sites and are present onshore and offshore. This study compares the geological, economic and social aspects of CO 2 storage in both domains using two basalt formations from the Republic of Ireland: the Limerick Igneous Suite and the Druid Formation. Offshore reservoirs offer larger storage resources but are more expensive to develop. Nevertheless, both offer gigatonne-scale theoretical CO 2 storage. Reviewing public perception studies on wind energy demonstrates that the commonly held belief that offshore projects face less opposition owing to their distance from communities has been dispelled, while similar studies on carbon capture and removal show no preference for onshore or offshore development. Instead, a general scepticism towards carbon removal is observed, with concerns that it hinders broader decarbonization efforts. The desire of all stakeholders to be involved throughout project development is consistently observed. Lessons from offshore natural gas projects highlight the consequences of failing to engage with local communities. The Republic of Ireland has significant potential to deploy geological CO 2 storage in basalt reservoirs, but policy hurdles such as legal limits on storage volumes must be overcome to reconcile climate ambition and legislative capacity.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗