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At least 217 records · Page 12

Historical and future trends in South Asian monsoon low pressure systems in a high-resolution model ensemble

Historical trends in monsoon low pressure systems (LPS), the dominant rain-bearing weather system of South Asia, have been difficult to assess due to changes in the observing network. Future projections have also remained uncertain because prior studies concluded that many coarse-resolution climate models do not accurately simulate LPS. Here, we examine changes in South Asian monsoon LPS simulated by an ensemble of global models, including some with high spatial resolution, that we show skillfully represent LPS. In the ensemble mean, the number of strong LPS (monsoon depressions) decreased over the last 65 years (1950–2014) by about 15% while no trend was detected for weaker LPS (monsoon lows). The reduction in depression counts then moderated, yielding no trend in the periods 1980–2050 or 2015–2050. The ensemble mean projects a shift in genesis from ocean to land and an increase in LPS precipitation of at least 7% K −1 , which together contribute to a projected increase in seasonal mean and extreme precipitation over central India.

54 ENVIRONMENTAL SCIENCES↗

The increasing threat of Rift Valley fever virus globalization: strategic guidance for protection and preparation

Rift Valley fever virus (RVFV) (Bunyavirales: Phlebovirus) is a prominent vector-borne zoonotic disease threat to global agriculture and public health. Risks of introduction into nonendemic regions are tied to changing climate regimes and other dynamic environmental factors that are becoming more prevalent, as well as virus evolutionary factors and human/animal movement. Endemic to the African continent, RVFV has caused large epizootics at the decadal scale since the early 20th century but has spread to the Arabian Peninsula and shows increasing patterns of interepizootic transmission on the annual scale. This virus can be transmitted by mosquitoes as well as through direct contact with infected tissues and can cause sporadic to widespread morbidity and mortality in domestic ungulate livestock as well as humans. High viremias in infected livestock moved for legal and illegal trade as well as in infected mosquitoes or human travelers can spread this virus worldwide. With increasing global commerce, it is likely RVFV will be introduced to new areas with suitable hosts, mosquito vector species, and environments. However, the strong mosquito component of RVFV epidemiology combined with advancements in vaccines, diagnostics, and virus evolutionary factors create opportunities for strategies to leverage models of connectivity among potential source and emerging regions to target surveillance and mitigation activities to reduce the risk of RVFV introduction, or contain the virus should it be introduced, into new regions.

60 APPLIED LIFE SCIENCES↗

Projected evolution of droughts and human exposure in the contiguous United States under SSP5-8.5: a regional downscaling perspective

The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.

CMIP6↗

FACETS Dynamical Downscaling Simulations over North America by the CAM-MPAS Variable-Resolution Model

Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through development of metrics and their demonstration on a hierarchy of downscaled climate datasets to quantify aspects of climate change projections that are credible, particularly for supporting decisions related to the energy-water-land nexus. As a part of this effort, we have produced a regional climate dataset using the Model for Prediction Across Scales coupled to the Community Atmosphere Model (CAM-MPAS). This global modeling framework is configured with variable-resolution meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The variable-resolution configurations allow fine-scale features to be better resolved inside the refinement and interact with global-scale circulations. The dataset includes multiple uniform- (240km and 120km) and variable-resolution (200-50km, 100-25km, and 46-12km) simulations that are designed to be compatible with other regional climate simulations that contribute to the hierarchy of downscaled climate datasets of the project. Furthermore, the dataset consists of simulations for both the present-day (1989-2010) and future (2079-2100) climate and post-processing of the model output has been coordinated across the project for consistency to facilitate common analysis across the hierarchy of datasets. Altogether, this CAM-MPAS model dataset provides a unique opportunity to assess the influence of resolutions and modeling framework on model credibility and climate change projection.

Sakaguchi, Koichi↗

ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models

We report that this study examines historical simulations of ENSO in the E3SM-1-0, CESM2, and GFDL-CM4 climate models, provided by three leading U.S. modeling centers as part of the Coupled Model Intercomparison Project phase 6 (CMIP6). These new models have made substantial progress in simulating ENSO’s key features, including: amplitude; timescale; spatial patterns; phase-locking; spring persistence barrier; and recharge oscillator dynamics. However, some important features of ENSO are still a challenge to simulate. In the central and eastern equatorial Pacific, the models’ weaker-than-observed subsurface zonal current anomalies and zonal temperature gradient anomalies serve to weaken the nonlinear zonal advection of subsurface temperatures, leading to insufficient warm/cold asymmetry of ENSO’s sea surface temperature anomalies (SSTA). In the western equatorial Pacific, the models’ excessive simulated zonal SST gradients amplify their zonal temperature advection, causing their SSTA to extend farther west than observed. The models underestimate both ENSO’s positive dynamic feedbacks (due to insufficient zonal wind stress responses to SSTA) and its thermodynamic damping (due to insufficient convective cloud shading of eastern Pacific SSTA during warm events); compensation between these biases leads to realistic linear growth rates for ENSO, but for somewhat unrealistic reasons. The models also exhibit stronger-than-observed feedbacks onto eastern equatorial Pacific SSTAs from thermocline depth anomalies, which accelerates the transitions between events and shortens the simulated ENSO period relative to observations. Implications for diagnosing and simulating ENSO in climate models are discussed.

54 ENVIRONMENTAL SCIENCES↗

Drought shrinks terrestrial upland resilience to climate change

Abstract Aim Drought has been shown to alter terrestrial ecosystem carbon (C) and nitrogen (N) dynamics, and thus feedback to future climate. However, drought‐induced changes in terrestrial upland C and N pools and the drought response of soil carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) fluxes are yet to be quantified. Location Global upland ecosystems. Time period 2000–2018. Major taxa studied Terrestrial C and N fluxes. Methods A meta‐analysis was conducted that compiled 1,344 measurements from 128 manipulative studies worldwide to obtain a general picture of terrestrial C and N cycling responses to soil drought stress and identify the primary driving factors. Results We showed that drought significantly decreased plant C pools, with stronger negative responses of aboveground than belowground C components. Drought significantly decreased soil respiration ( R S ) and N 2 O fluxes by 19% and 29%, respectively. There were non‐significant changes in soil organic C and N pools in response to drought; in contrast to a considerable decrease in soil dissolved organic C (−22%), there was a robust increase in soil nitrate‐N (26%) following short‐term drought impact. By relating net ecosystem productivity (NEP) to the difference between net primary production (NPP) and soil heterotrophic respiration ( R H ), drought was found to drive a decrease up to −37% in NEP, being equivalent to a reduction in terrestrial net C uptake of 2.91 t C/ha. Main conclusions Our study provides insights into soil release of CO 2 and N 2 O with a linkage to the changes in terrestrial C and N pools in response to drought across upland biomes. Our findings highlight that, despite the lowered soil C release rate, the capacity of upland biomes as a C sink to slow climate change would still be weakened due to a robust decline of plant‐derived C input to soil in a future drier climate.

Zheng, Yajing↗

Dynamic metrics of natural ventilation cooling effectiveness for interactive modeling

The evaluation of natural ventilation potential for cooling indoor spaces during the early design phases is of great interest to researchers and practitioners. Among various definitions and usages for natural ventilation potential (NVP) in early design evaluation, this paper reviews and identifies the key performance indicators, and proposes two new dynamic metrics—natural ventilation cooling effectiveness (NVCE) and climate potential utilization ratio (CPUR). The metrics are dynamically responsive to various design options, in both steady and transient states, allowing consideration of thermal mass. Assisting in design development processes, the metrics quantify how well indoor spaces make use of natural ventilation’s cooling capacity. Case studies are presented to demonstrate how NVCE and CPUR enable designers to evaluate the predicted performance and how to apply the information to improve building design. Finally, the results of the design iterations showed that the relationship among various design parameters should be dynamically understood in order to evaluate the performance of natural ventilation, confirming that “the more the airflow, the greater the potential,” and “the heavier the thermal mass, the greater the energy saving” were not always true.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Seasonal Controls on Microbial Depolymerization and Oxidation of Organic Matter in Floodplain Soils

Floodplain soils are vast reservoirs of organic carbon often attributed to anaerobic conditions that impose metabolic constraints on organic matter degradation. What remains elusive is how such metabolic constraints respond to dynamic flooding and drainage cycles characteristic of floodplain soils. Here, in this work, we show that microbial depolymerization and respiration of organic compounds, two rate-limiting steps in decomposition, vary spatially and temporally with seasonal flooding of mountainous floodplain soils (Gothic, Colorado, USA). Combining metabolomics and -proteomics, we found a lower abundance of oxidative enzymes during flooding coincided with the accumulation of aromatic, high-molecular weight compounds, particularly in surface soils. In subsurface soils, we found that a lower oxidation state of carbon coincided with a greater abundance of chemically reduced, energetically less favorable low-molecular weight metabolites, irrespective of flooding condition. Our results suggest that seasonal flooding temporarily constrains oxidative depolymerization of larger, potentially plant-derived compounds in surface soils; in contrast, energetic constraints on microbial respiration persist in more reducing subsurface soils regardless of flooding. Our work underscores that the potential vulnerability of these distinct anaerobic carbon storage mechanisms to changing flooding dynamics should be considered, particularly as climate change shifts both the frequency and extent of flooding in floodplains globally.

54 ENVIRONMENTAL SCIENCES↗

Winter precipitation changes in California under global warming: Contributions of CO2, uniform SST warming, and SST change patterns

Climate models project a wetting winter over California, distinct from the drying in all other Mediterranean climate regions under warming. Dynamic effect via an eastward extension of the westerly jet stream over the North Pacific is the root cause for the wetting California. Utilizing four sets of prescribed-SST (sea surface temperature) simulations, the relative effects of direct CO2 radiative forcing, uniform SST warming, and SST change pattern are investigated. The wetting winter is dominated by uniform SST warming mainly through its effect on the jet extension. As a fundamental response to the enhanced upper-tropospheric warming in the tropics, the jet extension in coupled simulations is well reproduced under uniform SST warming and robust among models. An El Niño-like SST warming pattern has a secondary contribution to the jet extension via atmospheric teleconnection, but with large inter-model spread. Relative to the SST forcing, the direct CO2 radiative effect is negligible.

Dong, Lu↗

Likely accelerated weakening of Atlantic overturning circulation emerges in optimal salinity fingerprint

The long-term response of the Atlantic meridional overturning circulation (AMOC) to anthropogenic forcing has been difficult to detect from the short direct measurements available due to strong interdecadal variability. Here, we present observational and modeling evidence for a likely accelerated weakening of the AMOC since the 1980s under the combined forcing of anthropogenic greenhouse gases and aerosols. This likely accelerated AMOC weakening signal can be detected in the AMOC fingerprint of salinity pileup remotely in the South Atlantic, but not in the classic warming hole fingerprint locally in the North Atlantic, because the latter is contaminated by the “noise” of interdecadal variability. Our optimal salinity fingerprint retains much of the signal of the long-term AMOC trend response to anthropogenic forcing, while dynamically filtering out shorter climate variability. Given the ongoing anthropogenic forcing, our study indicates a potential further acceleration of AMOC weakening with associated climate impacts in the coming decades.

54 ENVIRONMENTAL SCIENCES↗

Developing Renewable Energy Applications for Water Treatment Technologies and Transmission

The need for smaller treatment facilities for more isolated or rural municipal entities and industrial water treatment facilities continues to grow. From environmental justice and energy needs in remote communities that have never been serviced by larger scale utilities to smaller onsite treatment requirements to meet discharge regulations, energy efficient treatment systems that can leverage renewable energy sources can be an important asset to owners. Climate change and population dynamics have changed the needs for distributed water treatment systems and the manner in which they function. New treatment technologies that can operate under dynamic conditions and leverage variable energy sources (e.g., renewable energy, RE) can provide substantial efficiencies and cost savings. The National Renewable Energy Laboratory (NREL) is embarking on research projects that will perform multi-scale studies to investigate treatment technologies on varying source water quality that can operate under unsteady state flow conditions (timing) in response to energy availability, supply, and demand. A pilot-scale system will be built to assess modularity and scaling of treatment system operating conditions and performance. Modeling will also be used to determine feasibility and integration into grid emulation platforms to understand the use and value of operation with RE. Optimization will be completed for the treatment and distribution systems to document strengths and weaknesses of using RE power sources. Results of this effort will advance dynamic water treatment understanding under variable conditions and integration of RE sources to power these systems. This will lead to further decarbonization of municipal and private treatment facilities while supporting a paradigm shift in water treatment process operation and system design to achieve net-zero goals and move toward energy-sensitive resilient water treatment systems.

ENERGY PLANNING, POLICY, AND ECONOMY↗

The Effect of an Equatorial Continent on the Tropical Rain Belt. Part 1: Annual Mean Changes in the ITCZ

The TRACMIP (Tropical Rain Belts with an Annual Cycle and Continent Model Intercomparison Project) ensemble includes slab-ocean aquaplanet controls and experiments with a highly idealized tropical continent, characterized by modified aquaplanet grid cells with increased evaporative resistance, increased albedo, reduced heat capacity, and no ocean heat transport (zero Q-flux). In the annual mean, an equatorial cold tongue develops west of the continent and induces dry anomalies and a split in the oceanic intertropical convergence zone (ITCZ). Ocean cooling is initiated by advection of cold, dry air from the winter portion of the continent; warm, humid anomalies in the summer portion are restricted to the continent by anomalous surface convergence. The surface energy budget suggests that ocean cooling persists and intensifies because of a positive feedback between a colder surface, drier and colder air, reduced downwelling longwave (LW) flux, and enhanced net surface LW cooling (LW feedback). A feedback between wind, evaporation, and SST (so-called WES feedback) also contributes to the establishment and maintenance of the cold tongue. Simulations with a gray-radiation model and simulations that diverge from protocol (with negligible winter cooling) confirm the importance of moist-radiative feedbacks and of rectification effects on the seasonal cycle. This mechanism coupling the continental and oceanic climate might be relevant to the double ITCZ bias. The key role of the LW feedback suggests that the study of interactions between monsoons and oceanic ITCZs requires full-physics models and a hierarchy of land models that considers evaporative processes alongside heat capacity as a defining characteristic of land.

54 ENVIRONMENTAL SCIENCES↗

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Use-Inspired, Process-Oriented GCM Selection: Prioritizing Models for Regional Dynamical Downscaling

Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).

54 ENVIRONMENTAL SCIENCES↗

Dominant controls of cold-season precipitation variability over the high mountains of Asia

A robust understanding of the sub-seasonal cold season (November–March) precipitation variability over the High Mountains of Asia (HMA) is lacking. Here, we identify dynamic and thermodynamic pathways through which natural modes of climate variability establish their teleconnections over the HMA. First, we identify evaporative sources that contribute to the cold season precipitation over the HMA and surrounding areas. The predominant moisture contribution comes from the mid-latitude regions, including the Mediterranean/Caspian Seas and Mediterranean land. Second, we establish that several tropical and extratropical forcings display a sub-seasonally fluctuating influence on precipitation distribution over the region during the cold season. Many of them varyingly interact, so their impacts cannot be explained independently or at seasonal timescales. Lastly, a single set of evaporative sources is not identifiable as the key determinant in propagating a remote teleconnection because the sources of moisture anomalies depend on the pattern of sub-seasonally varying dynamical forcing in the atmosphere.

59 BASIC BIOLOGICAL SCIENCES↗

Urbanization exacerbates continental- to regional-scale warming

Urbanization is usually ignored when estimating past changes in large-scale climate and for future climate projections since cities historically covered a small fraction of the Earth’s surface. Here, by combining global land surface temperature observations with historical estimates of urban area, we demonstrate that the urban contribution to continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions and countries in Asia. Consequently, expected urban expansion over the next century suggests further increased urban influence on large-scale surface climate in the future (approximately 0.16 K for North America and Europe for high-emission scenario in 2100). Based on these results, also seen for air temperature, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in climate change assessments. This requires incorporation of dynamic urban extent and biophysics in current-generation Earth system models to quantify potential urban feedback on the climate system across scales.

Chakraborty, TC↗

The Leading Modes of Asian Summer Monsoon Variability as Pulses of Atmospheric Energy Flow

Monsoon rainfall anomalies are often organized into dynamical modes that are more predictable than rainfall at specific locations. Here a linear response function (LRF) is constructed to extract the neutral modes (NM) of the dynamical atmospheric system and their optimal forcing that govern precipitation variability, providing a dynamical underpinning for the empirically derived, recurrent rainfall patterns. The leading mode (NM1) features a shift in the Atlantic ITCZ, a drying over the Indian Ocean and Indian subcontinent, and a “South-Flood-North Drought (SFND)” pattern over eastern China, a pattern inferable from changes in the atmospheric energy flow forced by the corresponding optimal forcing and further enhanced by the water vapor and cloud feedbacks. Moreover, the slow evolving component of the NM1 in response to CO2 forcing can be skillfully predicted by running the ocean heat uptake through the LRF, implicating a deterministic ocean dynamic source for the NM1-like trend under climate warming.

monsoon mode of variability, EBM, climate change, ↗

CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US

This dataset presents a suite of downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled dynamically using Regional Climate Model version 4 (RegCM4). Each ensemble member covers the 1980-2019 baseline and 2020-2059 near-future periods under the high-end (SSP585) emission scenario. This dataset is formulated to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details on this dataset, please refer to Kao et al. (2022) and Rastogi et al. (2022).

13 HYDRO ENERGY↗