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At least 199 records · Page 11

Improvements to the Simplified Loads Methodology in IEC 61400-2: November 22, 2021 - November 21, 2022

The "Simplified Loads Model" (SLM) of IEC 61400-2 provides a simple methodology to assess the structural integrity of a small wind turbine (SWT). The SLM is unique to the small wind turbine standard. It was included to allow SWT manufacturers with limited resources to undertake integrity checks at a reasonable cost in time and resources and avoid the expense of detailed aeroelastic simulations. Unfortunately, the SLM has gained the reputation of being overly conservative and this has reduced its value to the SWT community and its use in SWT design and certification. Conservatism in design standards is needed but excessive conservatism is not. The aim of this report is to address the principal areas of excess conservatism and recommend changes to the SLM that preserve its simplicity but reduce the excess. The changes for the ultimate loads are consistent with their treatment in aeroelastic modelling for certification and with related codes for wind loading on structures. The recommendations for a new fatigue design load case are also based on aeroelastic simulations, in this case of five SWTs of varying configurations with rated power from 2.4 to 50 kW. It is also pointed out the design load case for yawed operation omits an important term. The recommended inclusion of this term would make the SLM slightly more conservative for this case.

17 WIND ENERGY↗

Energy Assets Transformation Web Mapping Application

This submission contains the link and geospatial materials used in the Energy Assets Transformation Web Mapping Application. The zip file contains 19 geospatial layers in a file geodatabase called EAT.gdb to be grouped in the following categories. 1. Industrial Assets: Coal Generation Units Retirements 2012-2040 (EIA); Examples of Repurposing Projects (32 projects in total); Abandoned Coal Mines (CORD, SkyTruth); Abandoned or Orphaned Wells (for ten states only). 2. Energy Transition Communities: 48C (e) Tax Credits - Designated Energy Communities (IRA); Index of Deep Disadvantage; Local Energy Action Program (LEAP); EJ Index for Proximity to Hazardous Waste (EPA). 3. Regional Landscape: State-Level Funding Programs (relevant to repurposing projects, for 2022 and 2023 only); Coal Flows from Mine to Plant 2021 (EIA), Variable Renewable Energy Shares (Wind and Solar, 2021, EIA). 4. Supporting Infrastructure: Railroads (HIFLD), Electric Power Transmission Lines (HIFLD), Major Highways (NHPN, DOT), Major Ports (National Atlas of the U.S.); Independent System Operators (HIFLD), NERC Regions and Subregions (HIFLD).

abandoned coal mines↗

Grid Value Proposition of Marine Energy

Marine energy technologies convert the energy of ocean waves, and tidal, river, and ocean currents into electricity and other forms of usable energy. The marine energy resource potential in the United States is significant and geographically diverse, with a study commissioned by the U.S. Department of Energy estimating that the nation’s annual marine energy potential is approximately 2,300 TWh/year across the 50 states, or greater than 57 percent of U.S. electricity generation in 2019. However, the marine energy industry still faces hurdles to commercialization. While high costs relative to wind and solar remain a key challenge, other hurdles relate to marine energy’s value streams not being well characterized and not captured by traditional energy comparison metrics like the levelized cost of energy. To address this challenge, this project undertakes several types of analyses to identify and illustrate value propositions for marine energy resources. It provides a fresh framework for considering electric system benefits based on unique marine energy attributes, and provides analyses illustrating and quantifying those benefits. The authors find many opportunities for the deployment of marine energy technologies both in the near term and within typical utility planning timeframes (i.e. up to 20 years). From a resource and technology perspective, marine energy resources can deliver distinct and valuable benefits to different configurations of the grid, whether the bulk system, isolated distribution systems, or remote communities, islands, and microgrids. Marine energy resources can be valuable in increasing technology diversity in a generation portfolio, providing energy where it is otherwise difficult to come by, supporting local resiliency, complementing and being complemented by other resources including solar, wind, and energy storage, and avoiding land constraints.

16 TIDAL AND WAVE POWER↗

Public perceptions of wave energy development on the west coast of North America: Risks, benefits, and coastal attachment

While solar and wind energy continue to grow as significant sources of renewable energy, a global energy transition away from fossil fuels will require an expanding portfolio of generating resources. Marine renewable energy has the potential to contribute greatly in the coming decades, as the more predictable nature of wave energy can support the resiliency of the power grid and complement solar and inland wind generation. Yet, the broad deployment of marine energy technologies like wave energy will depend on public support, making it critical to identify the relevant factors associated with public attitudes and risk/benefit perceptions. This paper draws on social representations theory to specifically examine perceptions of wave energy on the west coast of North America, a site chosen because of the high suitability for wave energy generation and the fact that one of only three wave energy test sites in the world is under development off the coast of Oregon. Using an online survey in June 2020, we recruited a sample of 2000 respondents from California, Oregon, Washington, and British Columbia. We found a majority of respondents held positive attitudes to wave energy, but respondents also had low familiarity – with a quarter of respondents lacking sufficient information to form an opinion. We used logistic regression to identify factors correlated with wave energy attitudes, finding that respondents who were more supportive of wind and solar energy, more optimistic about new technology, and reported more familiarity with wave energy were significantly more likely to have a positive impression of wave energy. Respondents with higher levels of place attachment to coastal areas were more split, as they perceived higher benefits of wave energy – but also higher risks. Our results indicate broad appeal of wave energy on the west coast, but we caution policymakers and developers to not take initial siting processes for granted. As experience has shown for offshore wind, broad appeal does not guarantee a smooth siting process in a local context. Furthermore, the role of place attachment to coastal areas must be taken seriously or risk alienating local communities.

16 TIDAL AND WAVE POWER↗

Aircraft Observations of Turbulence in Cloudy and Cloud-Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development

This study examines boundary layer turbulence derived from high temporal resolution meteorological measurements from 40 research flights over the western North Atlantic Ocean during the 2020 deployments of ACTIVATE. Frequency distributions of various turbulent quantities reveal stronger turbulence during the winter deployment than in summer and for cloud‐topped than in cloud‐free boundary layers during the summer deployment. Maximum turbulence kinetic energy (TKE) is most often within cloud from observations in winter and summer, whereas it is mostly below cloud in both seasons by a global model turbulence parameterization. Further, bivariate frequency distributions are consistent with the bivariate Gaussian probability distribution functions assumed for the closure of higher‐order turbulence/shallow convection parameterizations used by some global models. Turbulence simulated by the Community Atmosphere Model version 6 and the Energy Exascale Earth System Model Atmosphere Model version 2 using such parameterizations is not as strong as observed, with more TKE going into vertical wind perturbations rather than into zonal wind perturbations as observed, suggesting that the treatment of turbulence in Earth system models still needs to be further improved.

54 ENVIRONMENTAL SCIENCES↗

ARM FY2021 Radar Plan

The fundamental objective of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) radar facility is to provide high-quality radar observations to the scientific user community with an overarching goal of improving the treatment of clouds and precipitation in climate models. ARM has a complement of 32 scanning and zenith pointing radars, not including the radar wind profilers. This large number of radars and deployment locales require an enormous commitment of effort to keep operational. It has been the experience in ARM that all these radars cannot be always operated at a high level, and priorities need to be developed to properly manage operations every fiscal year. This document provides an overview of the FY20 activities and documents the priorities for FY21.

54 ENVIRONMENTAL SCIENCES↗

Coal Power Plant Reinvestment Visualization Tool

This tool, available at https://energycommunities.gov/coal-power-plant-reinvestment-visualization-tool/, serves as a public database and map for the purposes of enabling state and local economic development officials, project developers, and power plant owners to identify and pursue opportunities for plant and community reinvestment. The Coal Power Plant Reinvestment Visualization Tool focuses on coal power plants that have been closed or set-to-retire, alongside key infrastructure characteristics that are relevant for potential redevelopment reinvestment opportunities, including the opportunity to query these data based off pre-defined or user-set queries to identify opportunities for coal power facility reinvestment to support solar, wind, manufacturing, and nuclear. These Data for visualization and query include, but are not limited to: • Electric Transmission Lines • EPA Brownfield Sites (assessed with Federal funding) • Petroleum Terminals • Ports • Railroads • Others The tool will be updated periodically to provide relevant information to enable state and local economic development officials, project developers, and power plant owners to identify and pursue opportunities for economic revitalization and community reinvestment. Within this application data are focused on U.S. power plants with coal generation, where at least one on-site generator utilizes or utilized coal as a fuel source, including planned retirements through 2058 (EIA, 2024). Additional information on energy communities and revitalization opportunities can be accessed on the Interagency Working Group on Coal & Power Plant Communities & Economic Revitalization Energy Communities website (https://energycommunities.gov).

Closures↗

Evaluating Variable‐Resolution CESM Over China and Western United States for Use in Water‐Energy Nexus and Impacts Modeling

Abstract Climate models are critical tools to study earth system processes and are often further downscaled to provide refined‐resolution data sets for regional water‐energy impact analyses. In this study, the Variable‐Resolution Community Earth System Model (VR‐CESM), a new dynamical downscaling method, is employed to generate 1/8° simulations for China and the western United States over 1970–2006. Precipitation, temperature, snowpack, radiation, and wind speed are compared with two 1° global climate models, regional climate model ensemble, and reference data sets to evaluate their fidelity. Simulated precipitation skill is dependent upon the reference data sets used, a slight (<+10%) and spatially consistent wet bias in China during summer and the western United States during winter. Precipitation bias in VR‐CESM is the smallest among models and demonstrates the added value provided by resolution refinement. However, temperature biases are generally greater than precipitation due to more complicated interactions among processes. VR‐CESM simulates +2°C warm bias in the low‐elevation regions in China but −2°C cold bias in mountains. However, DJF cold bias (−2.23°C to−3.37°C) and JJA warm bias (+1.13°C to +1.87°C) exist in the western United States. The modeling skills of precipitation and temperature at various topographies are similar in the two evaluated regions. The cold bias was likely affected by downward shortwave radiation deficit (−15%) and slow bias of surface wind speeds (−16% to −29%). Despite the wet and cold bias, snow water equivalent and snow cover are underestimated in mountains. We conclude that VR‐CESM outperforms other models evaluated and provides the best estimation of downscaled climate model data for water‐energy studies.

54 ENVIRONMENTAL SCIENCES↗

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

17 WIND ENERGY↗

Activating Opportunity Zones for Rapid Solar+Storage Deployment in Low Income Communities (Final Report)

Millions of Texans choose their own power provider, giving them the option to have low-cost and even renewable energy delivered through their retail electric plan. However, Texans with less disposable income often pay more for electricity and have limited access to green energy and emergency backup power even though the costs of solar and wind power are at record lows and continue to decline. The Powered for Good initiative aimed to help deliver clean, affordable, 100% renewable electricity to low-income households in Texas’s Competitive Retail Areas, where households can choose their electricity provider. Objectives: The primary goal of this project was to develop and validate one or more affordable solar+storage products (i.e., priced less than of $0.14/kWh) that Retail Electricity Providers (REP) can offer to LI households. The team achieved three objectives: 1. Investigate how to best reduce electricity costs and increase availability of emergency power for LI customers; 2. Build momentum for, and facilitate an approach to, a Texas-based pilot deployment of such solar+storage products, with a goal of greatly expanding this approach to a large segment of the LI population in Texas; 3. Provide the structural framework, finance model, and roadmap to potentially increase investment of solar+storage projects in LI communities across U.S. states when modified to meet their state-specific laws and regulations. The team evaluated the market of viable solutions for low-income Texans through interviews and focus groups with professionals and residents with lived experience. The team then piloted a low-cost retail electric product. Following the pilot, the team developed educational materials, including fact sheets, a Go Green Save Green interactive guide, and an Electricity Bill Analysis Tool. The team is now working to increase power resilience and reduce energy insecurity with micro solar and storage in partnership with local entities in the Harris County area. Key Findings: Informed by Powered for Good research, including the experiences on Texas residents and electricity system experts, the Powered for Good team developed a pilot that was implemented by Energy Well Texas, a new company formed in late 2020. The pilot featured a combination of a 100% clean residential energy offering delivered through the electrical grid plus a selection of batteries, lights and a solar panel that provided participants with varying levels of backup power. For the 8 customers who submitted previous bills, the Energy Well Texas pilot reduced energy bills by about 30%. In Houston, residents earning less than 30% of Area median Income (AMI) spend an average 13% of their income on energy or about $1,555 per year. Repeating the pilot results for these residents could yield $466 in savings per customer or about 4% of their income. While this will not end energy poverty, it is a big step toward that goal. The Powered for Good and Energy Well Texas teams are currently planning their post-pilot phase of service offerings.

14 SOLAR ENERGY↗

Subseasonal Variability of U.S. Coastal Sea Level from MJO and ENSO Teleconnection Interference

Abstract Climate variability affects sea levels as certain climate modes can accelerate or decelerate the rising sea level trend, but subseasonal variability of coastal sea levels is underexplored. This study is the first to investigate how remote tropical forcing from the MJO and ENSO impact subseasonal U.S. coastal sea level variability. Here, composite analyses using tide gauge data from six coastal regions along the U.S. East and West Coasts reveal influences on sea level anomalies from both the MJO and ENSO. Tropical MJO deep convection forces a signal that results in U.S. coastal sea level anomalies that vary based on MJO phase. Further, ENSO is shown to modulate both the MJO sea level response and background state of the teleconnections. The sea level anomalies can be significantly enhanced or weakened by the MJO-associated anomaly along the East Coast due to constructive or destructive interference with the ENSO-associated anomaly, respectively. The West Coast anomaly is found to be dominated by ENSO. We examine physical mechanisms by which MJO and ENSO teleconnections impact coastal sea levels and find consistent relationships between low-level winds and sea level pressure that are spatially varying drivers of the variability. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts. Significance Statement Coastal flooding due to sea level rise is increasingly threatening communities, but natural fluctuations of coastal sea levels can exacerbate the human-caused sea level rise trend. This study assesses the role of tropical influences on coastal subseasonal (2 weeks–3 months) sea level heights. Further, we explore the mechanisms responsible, particularly for constructive interference of signals contributing to coastal flooding events. Subseasonal signals amplify or suppress the lower-frequency signals, resulting in higher or lower sea level heights than those expected from known climate modes (e.g., ENSO). Low-level onshore winds and reduced sea level pressure connected to the tropical phenomena are shown to be indicators of increased U.S. coastal sea levels, and vice versa. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts.

Meteorology & Atmospheric Sciences↗

Renewable energy analysis in indigenous communities using bottom-up demand prediction

This paper provides a methodology for the holistic analysis of hybrid renewable energy systems in rural communities. Electric demand is an important component for modeling and analysis of renewable energy systems. Typically, electric demand data is not available due to the internal privacy policies of utility providers. Therefore, this study proposes the use of bottom-up approaches for the development of the electric demand profile, considering the general homogeneity of residential and commercial buildings in rural communities. As a test case, this study develops the electric demand profile and investigates the technical and environmental feasibility of a hybrid renewable energy system for the New Town community on the Fort Berthold Indian Reservation (FBIR) in North Dakota. This study conducts the hybrid renewable energy system’s analysis by developing scripts in the LK scripting language and integrating System Advisor Model software’s open-source modules for modeling of renewable energy systems. Here, the results for the validation testbed of this study show that hybrid renewable resources have higher ratios of energy used for self-consumption to the total energy generated compared to stand-alone wind and PV farms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The influence of recent and future climate change on spring Arctic cyclones

In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global climate reconstructions and projections to examine how recent and future climatic changes alter cyclone behavior. Results suggest that recent climate change has not yet had an appreciable effect on Arctic cyclone characteristics. However, future sea ice loss and increasing surface temperatures drive large increases in the near-surface temperature gradient, sensible and latent heat fluxes, and convection during cyclones. The future climate can alter cyclone trajectories and increase and prolong intensity with greatly augmented wind speeds, temperatures, and precipitation. Such changes in cyclone characteristics could exacerbate sea ice loss and Arctic warming through positive feedbacks. The increasing extreme nature of these weather events has implications for local ecosystems, communities, and socio-economic activities.

54 ENVIRONMENTAL SCIENCES↗

Hydropower Flexibility and Environmental Tradeoffs Analysis

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordinating multiple tools, including water resources, ecological, and technical and economic power grid modeling, informs dam water releases. The case study, the Columbia River Basin multipurpose reservoir project, is operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. We integrated a production cost model, a water resource model, and decades of tribal knowledge to analyze the fish-friendly way of operating Columbia hydropower scheduling and grid impacts. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

Columbia River↗

Assessment and Improvement of the SST-Gamma Transition Model in Nalu-Wind

We conduct laminar–turbulent boundary-layer transition simulations using a local correlation-based transition model for two-dimensional incompressible flow and present enhancements to improve the accuracy of transition predictions. Menter’s Galilean-invariant 𝛾 transition model is implemented in the incompressible, unstructured-grid flow solver Nalu-Wind and is validated against experimental data and results from NASA’s flow solvers. The test cases of the AIAA Transition Prediction and Modeling Workshop are investigated, namely, the T3A/T3B flat plates and the NLF(1)-0416 and S809 airfoils. Based on the results, best practices for transition simulations, particularly for an unstructured-grid flow solver, are identified. Additional airfoil simulations are conducted for two wind turbine airfoils, S822 at Reynolds numbers of 𝑂⁡(10 5 ) and DU00-W-212 at Reynolds numbers of 𝑂⁡(10 7 ), to assess the model at low and high Reynolds numbers. Furthermore, through this work, we propose several approaches to enhance transition simulations, including 1) enforcing positivity of the implicit operator for the source terms of the transition model, 2) employing a constant turbulence intensity in stationary external flow simulations, and 3) recommending meshing for unstructured-grid flow solvers. Finally, we provide detailed documentation of the validation and data for the canonical cases to the transition modeling community.

17 WIND ENERGY↗

Long-Term Photovoltaic System Performance in Cold, Snowy Climates

As countries around the world transition towards renewable energy, there is increasing interest in using photovoltaic (PV) technologies to help decarbonize northern and alpine communities due to their scalability and affordability. However, a barrier to large-scale adoption of PV in cold climates is long-term performance uncertainty under snowfall, freeze-thaw cycles, low temperatures, and high winds. In this work, we provide a comprehensive review of published silicon degradation rates in cold Koppen-Geiger climate classifications of Dfb (humid continental), Dfc (subarctic), and ET (tundra). We first analyze the system degradation rates of three subarctic ground-mounted photovoltaic sites in North America using the RdTools year-on-year method: an Al-BSF double-axis tracking site in Fairbanks, Alaska (65degrees N); a PERC and silicon heterojunction bifacial vertical and south-tilted site in Fairbanks, Alaska; and a PERC south-facing fixed-tilt site in Fort Simpson, Northwest Territories (62degrees N). Degradation rates of these newly analyzed sites vary between -0.4%/year and -1.5%/year. Combining these data with previously reported cold climate degradation rates, we show that the distribution of cold climate degradation peaks at -0.1%/year to -0.2%/year but has a large tail with rates above -0.5%/year. The average reported cold climate degradation rate is -0.45%/year, whereas the median value is -0.33%/year. These results suggest that despite frequent freeze-thaw cycles and potential exposure to high wind and snow loads, PV systems in cold climates tend to degrade slower than PV systems in warmer climates. The limited sample size of reported degradation rates in cold climates (27) motivates the need for further data acquisition and monitoring efforts as new technologies are deployed.

14 SOLAR ENERGY↗

Fast Response of East Asian Precipitation in June 2020 to Local and Remote Aerosol Emission Reductions during COVID-19

Here, in this study, the fast response of East Asian summer precipitation to COVID-19–induced aerosol emission reductions is examined using the Community Earth System Model, version 2.2 (CESM2.2). The emission reductions decreased aerosol optical depth and cloud cover over northern China in June 2020. The troposphere became warmer, strengthening the land–sea thermal contrast and anomalous southerly winds. The subtropical westerly jet accelerated and shifted southward, favoring low-level convergence, upward air motions, and subsequent condensational heating over the Yangtze River basin (YRB). The feedback of condensational heating in return strengthened the convergence and ascent. The western North Pacific subtropical high was intensified, which further enhanced the moisture advection and convergence over the YRB. Both the enhanced moisture convergence and ascent increased precipitation over the YRB during June 2020. Furthermore, local and remote emission reductions show different impacts on convection and moisture transport over the YRB. The emission reductions over China caused stronger convective precipitation (1.15 vs 0.63 mm day −1 ) but weaker larger-scale precipitation (1.17 vs 2.24 mm day −1 ) than the emission reductions outside China. In addition to the emission reductions, the sea surface temperature (SST) anomalies in 2020 also play an important role in increasing precipitation over the YRB, contributing about 42.8%. The relative contribution of SST anomalies also increases under the COVID-19–induced emission scenario.

54 ENVIRONMENTAL SCIENCES↗