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NASA NTRSDate not supplied

Exploring the Elevated Water Vapor Signal Associated With the Free Tropospheric Biomass Burning Plume Over the Southeast Atlantic Ocean

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol–cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume–vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ∼5–6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (∼6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

Kristina Pistone↗
NASA NTRSDate not supplied

Biomass Burning Smoke and Coincident Water Vapor Over the Southeast Atlantic Stratocumulus Region: Results from Observations and Models

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the Southeast Atlantic (SEA) Ocean. We present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA. Using multiple airborne datasets, we observe a strongly linear correlation between biomass burning indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. This relationship was particularly strong in the 2016 observations, but was also present in the 2017 and 2018 deployments. Using ECMWF and MERRA-2 reanalyses and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper-tropospheric air and then is subjected to conditions of strong westward advection, namely the South African Easterly Jet (AEJ-S). Our analysis indicates that airmasses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ~5-6km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. The smoky, humid mixed air is then subjected to strong zonal winds and advected over the SEA following largely isentropic trajectories. HYSPLIT back trajectories support this interpretation. With better understanding of this relationship, and its spatial and temporal variations, we are working towards accurately quantifying the radiative and dynamical effects of both aerosol and water vapor over this region.

Kristina Pistone↗
NASA NTRS2021

Columnar Aerosol Types and Compositions Over Peninsular Southeast Asia Based on Long-Term AERONET Data

Aerosol chemical components such as black carbon (BC) and brown carbon (BrC) regulate aerosol optical properties, which in turn drive the atmospheric radiative forcing estimations due to aerosols. In this study, we used the long-term measurements from AERONET (Aerosol Robotic Network) to better understand the aerosol types and composition with respect to their seasonal and spatial variabilities in peninsular Southeast Asia (PSEA, here defined as Vietnam, Cambodia, Thailand, Laos, and Myanmar). Two methods (i.e., aerosol type cluster and aerosol component retrieval) were applied to determine the aerosol type and chemical composition during the biomass-burning (BB) season. AERONET sites in northern PSEA showed a higher AOD (aerosol optical depth) compared to that of southern PSEA. Differences in land use pattern, geographic location, and weather regime caused much of the aerosol variability over PSEA. Lower single-scattering albedo (SSA) and higher fine-mode fraction (FMF) values were observed in February and March, suggesting the predominance of BB type aerosols with finer and stronger absorbing particles during the dry season. However, we also found that the peak BB month (i.e., March) in northern PSEA may not coincide with the lowest SSA once dust particles have mixed with the other aerosols. Furthermore, we investigated two severe BB events in March of 2014 and 2015, revealing a significant BrC fraction during BB event days. On high AOD days, although the BC fraction was high, the BrC fraction remained low due to lack of aerosol aging. This study highlights the dominance of carbonaceous aerosols in the PSEA atmosphere during the BB season, while also revealing that transported dust particles and BrC aerosol aging may introduce uncertainties into the aerosol radiative forcing calculation.

Sheng-Hsiang Wang↗
NASA NTRSDate not supplied

Aerosol Above Cloud Optical Depth in the Southeast Atlantic and Its Use in Continuity NASA Products

When aerosol overlie bright clouds, their radiative impact on the incident light can be either positive or negative. This difference in radiative impact promotes difficulties in remote sensing aerosol properties, which have shown biases in aerosol optical depth (AOD) retrievals when clouds are underneath. To better constrain this quantity, we have measured aerosols above clouds over the course of 3 years in the southeast Atlantic as part of the ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES). These directly measured AOD above clouds are used to build and improve upon the current Near-Real-Time MODACAERO algorithm for above cloud AOD from MODIS, into a continuity product for NASA EOS/SNPP/JPSS. Here we present a summary of the above cloud aerosol optical depth measured during ORACLES, and that will be used for porting the MODACAERO algorithm to the continuity product. We use aerosol optical depth measured directly from sunlight attenuation using the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) and compare it to the active remote sensing, High Spectral Resolution Lidar-2 (HSRL-2). We present a combination of all 3 years of measurements during peak biomass burning season. We have observed average above cloud aerosol optical depth at 500 nm ranging from 0.28 to 0.37, with the maximum in August 2017. We emphasize the use of improved aerosol absorption and scattering models based on airborne measurements during ORACLES.

aerosol optical depth (AOD)↗
NASA NTRSDate not supplied

Excessive Subsidence of the Southeast Atlantic Biomass Burning Aerosol Plume in the NASA Goddard Earth Observing System (GEOS) Model

Global models struggle to accurately represent the meteorological environment over the Southeast Atlantic Ocean, as evidenced by the poor representation of persistent marine stratocumulus decks off the west coast of southern Africa. This complex regime also experiences significant seasonal biomass burning aerosol plumes that are transported from southern Africa over the Atlantic Ocean, which gradually descend via large scale subsidence and interact radiatively and microphysically with the cloudy environment of the region. In comparisons to space borne lidar and aircraft observations we find that the NASA Goddard Earth Observing System (GEOS) model’s MERRA-2 aerosol and meteorology reanalysis shows that the aerosol plume descends too rapidly due to exaggerated large-scale downward vertical motion. This complicates the evaluation of aerosol properties utilizing aircraft observations collected throughout the ORACLES campaign as well as the model’s representation of the heating rate profiles due to the aerosol itself and its radiative interaction with the semi-permanent cloud deck typically located lower in altitude than the smoke. Two types of modeling experiments using GEOS will be presented to diagnose deficiencies in the model related to the excessive subsidence. Ensembles of free-running model simulations with and without radiatively active biomass burning aerosol will be used to quantify the impact of smoke on the atmospheric circulation. It will be demonstrated that heating within the aerosol layer results in self lofting through a reduction of the subsidence but did not alter the vertical placement or speed of the African Easterly jet. The amount of aerosol absorption required to eliminate the bias in the height of the aerosol plume through self-lofting will then be quantified. Finally, a second type of modeling experiment will be discussed in which the meteorology is constrained to observations. This will allow for biases in the height of the aerosol plume due to the general circulation model to be distinguished from biases that may be induced through the data assimilation process.

Allison Collow↗
NASA NTRSDate not supplied

The Seasonal Evolution of Atmospheric Vertical Structure of Smoke and Humidity Over the Southeast Atlantic Biomass Burning Region

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region; this correlation is persistent through the biomass burning season, although varying through the course of the season. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. We use the ORACLES observations to assess this smoke-vapor relationship. First, we discuss the good agreement between the airborne ORACLES dataset and the ECMWF ERA5 and CAMS reanalyses, as well as results from NASA’s MERRA-2, as seen over the three deployment years. We then use the reanalyses to develop a framework in which to understand more broadly the radiative and dynamical interactions between the elevated smoke and water vapor over the SEA through the biomass burning season, beyond the three ORACLES observation periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalyses, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. The radiative heating of both aerosol and water vapor has potential to influence the cloud-top entrainment and atmospheric turbulence, thus modifying the underlying stratocumulus cloud properties. We next discuss how these smoke-humidity variations influence both the low-cloud fraction (as observed by MODIS and VIIRS, and output by ERA5) and the boundary layer height in the region. This classification will ultimately allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗
NASA NTRSDate not supplied

Impacts of Aerosol and Cloud Variability on Satellite-Derived All-skies Direct Aerosol Radiative Effects (DARE) over the North and Southeast Atlantic

The Top-of-Atmosphere (TOA) Shortwave (SW) Direct Aerosol Radiative Effect (DARE) in all-sky conditions (i.e., aerosols in clear skies and aerosols above and below all types of clouds) is the global change in upwelling radiative flux due to aerosols. It is one of the strongest indicators of global climate change due to aerosols. SW DARE at TOA depends on the Earth’s surface albedo, cloud fraction, cloud optical properties, and aerosol optical properties, which are all challenging to accurately characterize from space. The overarching goals of our project are to provide state-of-the-art observational all-sky TOA SW DARE, along with guidance on which aerosol and/or cloud properties are the most important to measure, and at which spatio-temporal scales, for accurate DARE observations. We compute all-sky DARE based on state-of-the-art cloud and aerosol retrieval algorithms from CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) and MODIS (Moderate Resolution Imaging spectroradiometer) satellite sensors, as well as aerosol intensive properties from MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) simulations over three specific regions of the Atlantic Ocean from 2012 to 2016. In this symposium, we present a characterization of the cloud and aerosol optical and physical properties and the observational TOA SW DARE along three individual satellite tracks in the Southeast Atlantic region -- on September 18 and 20, 2016 and August 13, 2017. We then quantify the impact of assuming homogeneous cloud or aerosol fields in space-based TOA SW DARE calculations. And, finally, the resulting space-based all-skies aerosol vertical distribution and DARE calculations are evaluated using remote sensing observations from coincident suborbital flights from the NASA ORACLES (the ObseRvations of Aerosols above CLouds and their intEractionS, ORACLES field campaign) field campaign. The NASA Atmospheric Observing System (AOS) mission addresses the NASA Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables and proposes, as one of its aerosol objectives, to reduce uncertainties in estimates of global mean all-sky SW DARE at TOA. Well characterizing clouds, aerosol vertical distributions, aerosol types and associated all-skies DARE over the Atlantic Ocean will inform the AOS community on where, when, how, and how often the satellite retrievals should be performed to estimate DARE and reduce all-skies DARE uncertainties most accurately. These comprehensive characterizations will also identify the key regions and times when the AOS (or other ACCP-related) suborbital missions should be conducted to evaluate and improve the AOS space-based observations and retrievals.

aerosol↗
NASA NTRS2024

Land Cover Change Analysis and Spatial Variations in Southeast Asian Nations: Insights on Spatial Scale Dynamics

Land cover type is a fundamental aspect of studies using remote sensing for environmental analysis such as monitoring deforestation, quantifying wildland fire emissions, and more. There are many land cover products available for varying time periods and spatial resolutions, each with different land cover class definitions and number of land cover classes. These differences yield inherent variation in land cover estimates. In this study, we explore the spatial and areal variation between two major datasets for their commonly available time of 2018 to 2022 (MODIS 500m Land Cover and Esri Sentinel-2 10m land cover) in the continental Southeast Asia countries of Cambodia, Laos, Myanmar, Thailand, and Vietnam. To enable comparison, we resampled the datasets and reclassified the land cover classes to a common scheme. Major disagreement was detected between Esri and MODIS, especially for the wetlands/flooded vegetation class in which only 3.6% of pixels were in agreement. In addition to quantifying variation between the datasets, we quantify land cover change at the decadal scale of 2001, 2011, and 2021 for each country and identified province-level hotspots of land cover change. Cambodia experienced the highest rate of land cover change with 67.8% of total land area changed, followed by Vietnam (58.6%), Laos (50.2%), Myanmar (46.9%), and Thailand (46.3%). The highest rate of land cover change was detected in Odtar Mean Chey, Cambodia, which had large swaths of forest area cleared for agricultural production, river damming, and more. Ultimately, many areas in the region experienced forest clearing for crop production (i.e. rice) which appeared to be classified as wetland in the MODIS product, and crop in the Esri product. Myanmar was the only country which did not experience net decline in forest area over the 2001 to 2021 time period.

Land Cover Change↗
NASA NTRS2024

Vertical Structure of a Springtime Smoky and Humid Troposphere Over the Southeast Atlantic From Aircraft and Reanalysis

The springtime atmosphere over the southeast Atlantic Ocean (SEA) is subjected to a consistent layer of biomass burning (BB) smoke from widespread fires on the African continent. An elevated humidity signal is coincident with this layer, consistently proportional to the amount of smoke present. The combined humidity and BB aerosol has potentially significant radiative and dynamic impacts. Here, we use aircraft-based observations from the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) deployments in conjunction with reanalyses to characterize covariations in humidity and BB smoke across the SEA. The observed plume–vapor relationship, and its agreement with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, persists across all observations, although the magnitude of the relationship varies as the season progresses. Water vapor is well represented by the reanalyses, while CAMS tends to underestimate carbon monoxide especially under high BB. While CAMS aerosol optical depth (AOD) is generally overestimated relative to ORACLES AOD, the observations show a consistent relationship between carbon monoxide (CO) and aerosol extinction, demonstrating the utility of the CO tracer to understanding vertical aerosol distribution. We next use k-means clustering of the reanalyses to examine multi-year seasonal patterns and distributions. We identify canonical profile types of humidity and of CO, allowing us to characterize changes in vapor and BB atmospheric structures, and their impacts as they covary. While the humidity profiles show a range in both total water vapor concentration and in vertical structure, the CO profiles primarily vary in terms of maximum concentration, with similar vertical structures in each. The distribution of profile types varies spatiotemporally across the SEA region and through the season, ranging from largely one type in the northeast and southwest to more evenly distributed between multiple types where air masses meet in the middle of the SEA. These distributions follow patterns of transport from the humid, smoky source region (greatest influence in the northeast of the SEA) and the seasonal changes in both humidity and smoke (increasing and decreasing through the season, respectively). With this work, we establish a framework for a more complete analysis of the broader radiative and dynamical effects of humid aerosols over the SEA.

Kristina Pistone↗
NASA NTRS2024

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗
DOE OSTI2023

Grid Interconnection and Renewables Deployment Related Air Quality and Human Health Benefits in Southeast Asia

The Association of Southeast Asian Nations (ASEAN) has increasingly focused on multilateral electricity trade, improved grid resiliency and modernization. These opportunities in the power sector have been studied through the ASEAN Interconnection Masterplan Studies, the most recent of which is the ASEAN Interconnection Masterplan Study III (AIMS III). AIMS III assessed four different scenarios of power system in the ASEAN countries that include a base scenario and three additional scenarios (called optimum RE, ASEAN RE, and High RE) considering different levels of deployment of renewable energy (RE) and cross-border generation and trade of electricity for three years (2025, 2030, 2040). In this work, we quantify the potential air quality and public health co-benefits of AIMS III scenarios. For a rapidly expanding, energy hungry region like SE Asia generation is power generation is expected to increase significantly. The AIMS III scenarios' capacity expansion modeling suggest that: 1) Generation nearly doubles from 2025 to 2040 in all four AIMS III scenarios; 2) Most of the increased generation is met by coal in all four AIMS III scenarios; 3) While renewables generation increases in all four AIMS III scenarios, the fraction of total generation (its share) generally decreases because of the much greater increase in non-renewable sources, mostly coal. Only in the High RE Target scenario do renewables represent a higher share in 2040 than in 2025, though even here it is at the expense of natural gas rather than coal; 4) As a result, emissions of gaseous and aerosol pollutants increase significantly in all scenarios. Because emissions increase in 2040 compared to 2025 for all four AIMS III scenarios, so do PM2.5 concentrations. Even for the High RE Target scenario (the scenario with highest share of renewable energy), compared to the Base scenario in 2025, in 2040 PM2.5 concentrations are higher. Compared to the Base scenario in the same years, the Optimum RE and ASEAN RE Target scenarios do not differ very much from the Base in terms of PM2.5 concentration. The High RE Target scenario, on the other hand, yields noticeably lower PM2.5 concentration. For example, in 2040 the population-weighted decrease in annual average PM2.5 concentration in the High RE Target scenario relative to the Base scenario is 0.5 ug m-3. Compared to the Base scenario in 2040, each of the alternative AIMS III scenarios is estimated to result in net reductions in power-sector air quality-related excess mortality in the ASEAN region. Yet there are a few countries for which the Optimum RE and ASEAN RE Target result in increases in PM2.5-related excess mortality (Thailand and Vietnam for the ASEAN RE Target scenario and Thailand for the Optimum RE scenario). However, for the High RE Target scenario, all countries benefit and find reductions in excess mortality resulting from the power sector scenarios modeled in AIMS III with regionwide mortality decreasing by 16,000 compared to the Base scenario in 2040. In summary, our analysis finds that changing power generation emissions is a crucial lever for improving public health in ASEAN member countries and provides a pathway for policymakers to make decision backed by a realistic power sector expansion and air quality analyses.

air quality↗
DOE OSTI2023

Pollen and Bio-Soiling in the Southeast U.S.

Typical PV soiling models presume that soiling follows a sawtooth pattern: linear soiling during dry periods followed by abrupt recovery or cleaning during rainfall events. Due to frequency of rainfall in the in the eastern U.S. sawtooth soiling models report near zero soiling losses in this region. Alternatively, through work with system owner/operators per NREL's PVfleet project it has become clear that there are systems in the Southeast that have soiled as high as 10% which are not recovering with regular rainfall. The current hypothesis is that sticky soiling due to pollen or other biological sources is persistent to rainfall removal. Field data and the latest progress towards de-risking bio-soiling will be presented.

photovoltaic↗
DOE OSTI2024

Factors Influencing Grid-connected Heat Pump Water Heater Performance in the Southeast U.S.

Grid-connected heat pump water heaters (HPWH) can shift electrical load while minimizing impacts to hot water availability for occupants. This capability provides a flexible grid resource to utilities seeking to manage peak loads Such load control also can feasibly improve renewable utilization within the utility electric production mix, for instance using off-peak generation during periods with high renewable energy generation. It also offers lower electric bills to customers through increased energy efficiency of HPWH and cuts greenhouse gas emissions. In particular, the Southeast U.S. due to its high penetration of electric water heating presents a promising opportunity for grid-connected HPWHs. This paper builds upon the results of an extensive HPWH load shifting field study conducted in 51 occupied homes in Florida using EcoPort technology (Butzbaugh et al, 2022). In 2022, only an initial evaluation was available. Here, long term load results are available as well as examination of various control strategies and influences. Analysis is conducted for HPWH energy use and load shifting performance based on home occupancy (i.e., low and high) and water heater location (i.e., conditioned and unconditioned) across different temperature profiles. An unexpected outcome of this analysis was the poor performance of HPWHs located in conditioned spaces, possibly because of inadequate air volume from improper installation. We did find higher demand reductions from 2-hour load ups and slightly improved for critical peak signals in the afternoon control periods. As expected, higher occupancy households showed great load reductions.

Fenaughty, Karen↗
DOE OSTI2020

COVID-19 and the Power Sector in Southeast Asia: Impacts and Opportunities

The COVID-19 pandemic is unique among the range of threats encountered over the last century, and its specific impacts do not necessarily resemble those of other disasters. In the near term, the pandemic is causing demand shocks, workforce impacts, supply chain complications, and a global, economic contraction with long-term consequences as yet unknown. In contrast, with natural disasters the principal impacts are more acute. These include infrastructure destruction, displaced populations, and often localized economic impact; however, the long-term response to both of these threats–pandemics and destructive forces of nature–requires similar approaches to building short-term and long-term resilience that prepare power sectors for safe and reliable operation during times of disruption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Southern Company Services: Project 2: Tall Tower Wind Technical Potential for the Southeast (Modifications 4, 5), Project 4: Offshore Wind Potential for Southern Company Services (Modifications 7, 8)

Project 2: The National Laboratory of the Rockies (NLR) and Southern Company Services (SCS) seek to establish an agreement to assess the technical potential for wind energy in the Southeastern U.S. SCS has requested that NLR conduct a detailed assessment of system performance, available capacity, transmission distance, and levelized cost of electricity (LCOE) at turbine hub heights of 100m to 160m within the SCS service territory. NLR will also provide an assessment of utility photovoltaic (PV) technical potential within the SCS service territory. NLR has unique modeling capabilities to assist SCS with high spatial and temporal resolution assessment of wind and PV technical potential, considering geospatial constraints. Project 4: NLR and SCS seek to develop a spatially explicit techno-economic assessment for offshore wind energy in the Southeastern U.S. The analysis aims to characterize the regional sensitivities of offshore wind plant costs and performance, underwater cabling, potential siting constraints, and landfall spur transmission costs.

17 WIND ENERGY↗