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NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗

NASA NTRSDate not supplied

Formation of Tropopause Cirrus clouds by Typhoon-induced gravity waves during the Asian Summer Monsoon: A Case Study from the BATAL 2017 Campaign

Cirrus clouds in the Tropical Tropopause Layer (TTL) have a net warming impact on Earth’s climate and they regulate the amount of water vapor entering the lower stratosphere through dehydration process near the cold-point tropopause. During the Boreal summer, Asian Summer Monsoon (ASM) is an important source of cirrus clouds and humidity in the TTL owing to frequent deep convection. However, better representation of convection and TTL cirrus clouds in global climate models is needed for accurate assessment of their response to changing climate. In this study, we investigate the mechanisms involved in the formation of a tropopause cirrus cloud layer observed during the Balloon measurement campaigns of the Asian Tropopause Aerosol Layer (BATAL) over Hyderabad (17.47 °N, 78.58 °E), India on 23 August 2017. A subvisible cirrus cloud layer (optical thickness ~0.025) was detected by a backscatter sonde (COBALD) onboard a balloon near the cold-point tropopause (CPT, temperature~ -86.4 ° C, altitude~17.9 km) which was later confirmed by the CATS lidar on the ISS. Simultaneous measurements from an optical particle counter (Boulder Counter) revealed the presence of ice crystals smaller than 50 microns in this layer. The formation mechanism responsible for this tropopause cirrus is investigated using a technique combining three-dimensional back-trajectories, satellite observations, and ERA5 reanalysis data. Satellite observations revealed that the overshooting convection associated with a category-3 typhoon Hato, which hit Macau and Hong Kong on 23 August 2017 injected ice into the lower stratosphere. This caused a hydration patch that followed the ASM anticyclone subsequently moving towards Hyderabad. The presence of tropopause cirrus cloud layers in the cold temperature anomalies and updrafts along the back-trajectories indicated towards the role of typhoon-induced gravity waves in their formation. This case study highlights the role of typhoons in influencing the formation of tropopause cirrus clouds through stratospheric hydration and gravity waves in the ASM anticyclone.

Amit Kumar Pandit↗

NASA NTRSDate not supplied

Tropical Convection Through the Lens of the INCUS Mission

The overarching goal of the recently selected NASA INvestigation of Convective UpdraftS (INCUS) mission is to enhance our understanding of why, when and where tropical convective storms form, and why only some of these storms produce extreme weather. Convective storms provide an important pathway for the transport of air and water between Earth’s surface and the upper troposphere. This vertical transport of air and water, often referred to as convective mass flux (CMF), plays a critical role in Earth’s weather and climate system through its impacts on microphysical and precipitation rates, detrainment and upper tropospheric moistening, high cloud feedbacks, and the large-scale circulation. Potential changes to the CMF as a function of the local environment or with changing climates may also have significant implications for severe weather such as flood-producing rainfall, damaging hail and lightning. In spite of the critical role of this vertical transport of water and air, representation of CMF remains a major source of error in weather and climate models, thereby limiting our ability to accurately predict convective storms and their impacts. The tropics-wide observations from INCUS will enhance our understanding of tropical convective storm processes and will provide guidance for representing these processes in numerical models across scales. INCUS is comprised of three SmallSat platforms each carrying a RainCube-heritage Ka-band 7-beam scanning radar. The satellite platforms will be 30 and 90 seconds apart, thus providing three time intervals (30, 90 and 120 seconds) over which observations will be made. INCUS will investigate CMF using a novel time-differenced radar reflectivity profile approach. In addition to the Ka-band radar, a single TEMPEST-D-heritage cross-track-scanning passive microwave radiometer will be housed on the middle SmallSat. The radiometer will provide extensive storm context for the radar observations, as well as observations of the convective anvils. The combination of the radars and radiometer on INCUS will deliver unprecedented three-dimensional views of tropical convective storms. INCUS is the first systematic investigation of the rapidly evolving CMF within tropical convective storms, the observations of which are expected to significantly enhance both our understanding and prediction of storm structure, their dynamics and microphysical processes, and the ways in which these evolve over storm lifetimes. This presentation will highlight the observational capabilities and scientific approach of the INCUS mission.

Susan C. van den Heever↗

NASA NTRS2023

StratoFIRE: Modeling Wildfire Smoke in the Stratosphere

The most extreme manifestation of a fire–weather interaction is the formation of pyrocumulonimbus (pyroCb) thunderstorms, triggered by super-heated updrafts, which can eject smoke at altitudes exceeding 20 Km. In this study, we investigated climate-related impacts from the most intensive pyroCb-triggered injection of smoke in the stratosphere: the Australian New Year wildfires in 2019/2020. We first provide a general overview of the vision and objectives of the StratoFIRE project. With the aid of the global chemistry-climate model EMAC, we then simulate radiative and chemical perturbations in the stratosphere in relation to 0.9 Tg smoke in the stratosphere assuming different injection heights, from 13 to 16 Km. The simulation of stratospheric optical depth perturbations were found to be sensitive to the assumed injection height, with a maximum height at 16 Km showing the best agreement with the GLOSSAC and SAGE-ISS aerosol extinction observations.

PyroCb↗

NASA NTRS2023

Overview and Statistical Analysis of Boundary Layer Clouds and Precipitation Over the Western North Atlantic Ocean

Due to their fast evolution and large natural variability in macro- and microphysical properties, the accurate representation of boundary layer clouds in current climate models remains a challenge. One of the regions with large intermodel spread in the Coupled Model Intercomparison Project Phase 6 ensemble is the western North Atlantic Ocean. Here, statistically representative in situ measurements can help to develop and constrain the parameterization of clouds in global models. To this end, we performed comprehensive measurements of boundary layer clouds, aerosol, trace gases, and radiation in the western North Atlantic Ocean during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. In total, 174 research flights with 574 flight hours for cloud and precipitation measurements were performed with the HU-25 Falcon during three winter (February–March 2020, January–April 2021, and November 2021–March 2022) and three summer seasons (August–September 2020, May–June 2021, and May–June 2022). Here we present a statistical evaluation of 16 140 individual cloud events probed by the fast cloud droplet probe and the two-dimensional stereo cloud probe during 155 research flights in a representative and repetitive flight strategy allowing for robust statistical data analyses. We show that the vertical profiles of distributions of the liquid water content and the cloud droplet effective diameter (ED) increase with altitude in the marine boundary layer. Due to higher updraft speeds, higher cloud droplet number concentrations (N liquid ) were measured in winter compared to summer despite lower cloud condensation nucleus abundance. Flight cloud cover derived from statistical analysis of in situ data is reduced in summer and shows large variability. This seasonal contrast in cloud coverage is consistent with a dominance of a synoptic pattern in winter that favors conditions for the formation of stratiform clouds at the western edge of cyclones (post-cyclonic). In contrast, a dominant summer anticyclone is concomitant with the occurrence of shallow cumulus clouds and lower cloud coverage. The evaluation of boundary layer clouds and precipitation in the N liquid ED phase space sheds light on liquid, mixed-phase, and ice cloud properties and helps to categorize the cloud data. Ice and liquid precipitation, often masked in cloud statistics by a high abundance of liquid clouds, is often observed throughout the cloud. The ACTIVATE in situ cloud measurements provide a wealth of cloud information useful for assessing airborne and satellite remote-sensing products, for global climate and weather model evaluations, and for dedicated process studies that address precipitation and aerosol–cloud interactions.

Aerosol↗

NASA NTRSDate not supplied

Climatology of Global Precipitation Measurement Mission Precipitation Regimes and Implications for Global Estimates of Vertical Winds

The Global Precipitation Measurement (GPM) mission Validation Network (VN) framework leverages over 118 ground-based polarimetric Doppler radars to validate a large subset of precipitation measurements and retrievals from the GPM Dual-frequency Precipitation Radar (DPR). Recently, GPM DPR reflectivity profiles within the VN have been classified according to their convective regime using unsupervised machine learning techniques. The archetypal regimes are stratiform, convective, mixed stratiform-convective (e.g., transition regions), and “other” (e.g., peripheral regions of light precipitation). Subcategories within these four primary regimes vary according to the characteristic depth of included reflectivity profiles, resulting in 12 main GPM DPR precipitation profile categories. Polarimetry of ground-based Doppler radars in the VN offers additional insights into the types of precipitation, while pairs of radars positioned near each other enable retrieval of vertical winds via dual-Doppler analysis. Geometrically matched to the DPR reflectivity profiles in the GPM VN, these ground-based data and retrievals contribute more detailed characterization of the distinct kinematic and microphysical structures associated with each of the 12 DPR precipitation regimes. DPR reflectivity profiles linked with wind in the VN are restricted to GPM overpasses of proximal radar pairs that allow dual-Doppler analysis. Although a limited subset of DPR profiles in the VN are matched with vertical motion, agreement between the reflectivity structures paired with wind data and those of the greater DPR dataset in the VN suggest that estimates of vertical motion may be inferred in regions without ground-based measurements. We present a climatology of the 12 convective regimes identified within the DPR VN dataset as well as early efforts to estimate the kinematic and microphysical structures of precipitation profiles within the greater GPM DPR dataset by applying machine learning techniques. Precipitation data paired with global estimates of vertical winds from these efforts offer early insight to and support upcoming missions to retrieve convective mass flux, including the Investigation of Convective Updrafts (INCUS) in the Tropics and the global Atmosphere Observing System (AOS).

Precipitation↗

NASA NTRSDate not supplied

Exploring Lightning and Convective Processes Using the Ground-Radar Multiplatform Precipitation Feature Database

The Multiplatform Precipitation Feature (MPF) database synthesizes coincident spaceborne and ground-based lightning and radar data in a framework of storm-based features, fusing broader spaceborne detection capabilities with process-based, storm-level analysis practices. The MPF database was designed to extend the scale and scope of investigations into the complex connections between precipitation, updrafts, and lightning. The NASA International Space Station Lightning Imaging Sensor (ISS LIS) serves as the source of lightning information for the database. The first iteration of the MPF database leveraged the NASA Global Precipitation Measurement (GPM) mission spaceborne Dual-frequency Precipitation Radar (DPR) to define features, along with contributions of microphysics data and vertical wind retrievals from the GPM Validation Network (VN) of ground-based radar data. The dependency on coincident ISS and GPM satellite overpasses of radars in a dual-Doppler configuration significantly limited the size of the initial database of features, referred to as VNMPFs, but established the database infrastructure and feasibility. We present here a second iteration of the MPF database that omits the GPM DPR and VN, instead incorporating data directly from selected proximal installations of the operational Next Generation Radar (NEXRAD) network that facilitate vertical wind retrievals via dual-Doppler analysis. These features based exclusively on ground-based polarimetric Doppler radar are hereafter referred to as Ground-Radar MPFs (GRMPFs). Removing the restriction of a coincident GPM overpass appreciably increases the size of the GRMPF database while incorporating more detailed information from higher-resolution radar data and retrievals. This expansion allows for unprecedented broad, robust statistical analyses of the electrical, kinematic, and microphysical characteristics of deep convective processes. These results highlight the potential for advancements in lightning meteorology made possible by combining multiple perspectives from global lightning measurements and ground-based radar data.

Lightning↗

NASA NTRSDate not supplied

Precipitation Science at NASA MSFC

The Precipitation Research Group in NASA MSFC’s Earth Science Branch (ST-11) focuses on observations of precipitation (rain, snow, and hail) from a variety of perspectives: ground-based radars, surface gauge networks, airborne instruments, and spaceborne measurements from onboard satellites. Current work includes identifying signatures of hail and strong thunderstorms from spaceborne measurements and assessing those signatures against multiple satellite datasets and ground-based radar observations. The Precipitation Team is also involved in the development and maintenance of NASA’s global-gridded multi-satellite precipitation product (IMERG) and operating and maintaining the GPM Validation Network (VN): a software package that geometrically matches the reference ground-based weather radar observations with GPM satellite observations in 3D. The team is also responsible for the Advanced Microwave Precipitation Radiometer (AMPR) used in airborne field campaign research, which recently was used to collect data on thunderstorms that produce terrestrial gamma-ray flashes (TGFs) in the Airborne Lightning Observatory for FEGS and TGFs (ALOFT) field campaign. While the Precipitation Group largely supports NASA’s Global Precipitation Measurement (GPM) mission and Precipitation Science Team, the team also looks to the future Precipitation Measurement Mission (PMM) and Investigation of Convective Updrafts (INCUS) missions.

Sarah D Bang↗

NASA NTRSDate not supplied

Relating Lightning Flash Characteristics to Convective Structure in Tropical Cyclones

For decades, lightning has been used with some success as an indicator of tropical cyclone (TC) intensity change. An increase in inner-core lightning is usually associated with TC intensification, but this is not always the case. Significant lightning outbreaks have been observed in weakening storms, and hurricanes can rapidly intensify in the total absence of inner-core lightning. These conflicting results arise because lightning production depends on convective and microphysical characteristics that can arise during both intensification and weakening phases in TCs. Recent work using flash size and energy metrics provided by the Geostationary Lightning Mapper (GLM) aboard the GOES-R series of satellites shows some promise in distinguishing between lightning outbreaks that correspond to intensification and those that correspond to weakening. If a hurricane is rapidly intensifying in the presence of inner-core lightning, the size and optical energy of the flashes generally increases as intensification proceeds. It is hypothesized that this relationship is governed by changes in the TC-scale circulation that produce enhanced upper-level outflow and large, strongly helical convective updrafts in the inner core. These changes increase the quantity and spatial extent of charged upper-level ice, which allows large intracloud flashes to occur when electric field breakdown occurs. This presentation will present objective diagnostics of convective asymmetry using azimuthal wavenumber decomposition of GOES-R Advanced Baseline Imager brightness temperatures. The degree of symmetry will be related to GLM flash characteristics to better understand how changes in the symmetry of TC inner-core convection relates to flash rate, size, and energy. It will also show how the evolution of inner-core asymmetries relates to the spatial distribution and characteristics of lightning flashes in the inner core.

Patrick Duran↗

NASA NTRSDate not supplied

Diurnal Cycles of Intense Thunderstorms As Seen By Satellites

Spaceborne sensors cannot directly measure aspects of severe weather occurring at ground-level. Tools from Geostationary Earth Orbit (GEO) and Low Earth Orbit (LEO) can be related to storm intensity and likelihood of severe weather. Visible and Infrared (GEO and LEO) measure cloud-top properties and horizontal structure. Some properties have empirical correlations with severe weather occurrence. Precipitation Radar (LEO) measures vertical profile of reflectivity related to particle size and concentration, but attenuates (2.2-cm and shorter wavelengths) well above the surface in intense thunderstorms. Lightning mappers (GEO and LEO) measure lightning flash rates and flash properties, which relate to updraft properties including size and vigor. SAR and optical sensors can detect damage paths on the surface after a storm has passed. (Depends on the vegetation type and maturity.)

Daniel J Cecil↗

NASA NTRSDate not supplied

A Long-Term GOES Satellite Overshooting Cloud Top and Anvil Cloud Climatology Over South America

The modern-era GOES satellite series began in 1994 with the GOES-8 satellite, and was augmented in 2018 with higher spatial resolution and more frequent imaging when GOES-16 became operational. GOES imagery has provided forecasters and researchers new perspectives into cloud top patterns associated with severe convection, and the ability to better forecast convection in regions without adequate ground-based weather radar coverage. While much attention has been given to convection over North America, convection over South America can be equally, if not more, intense and frequent. Recent studies have demonstrated that overshooting cloud tops (OT) and surrounding anvil clouds can be detected within infrared satellite imagery. Relative storm updraft intensity metrics such as the tropopause-relative infrared brightness temperature, the prominence of an OT relative to its surrounding anvil, and cloud top height can also be derived using automated methods combined with reanalysis data. These automated OT detection and intensity estimation methods have recently been applied to all GOES images collected over South America, in combination with the MERRA-2 reanalysis, from 1995 to 2022 at NASA Langley within a project supported by the NASA Applied Sciences Disasters program. Innovative aggregation methods have merged these products into daily, monthly, annual, and multi-annual composites, with hourly time bins, at ~4 km pixel spacing to enable researchers a new opportunity to study South American convective processes throughout the diurnal cycle. These products have recently become publicly available from NASA. This presentation will overview this new dataset, and novel insights into South American convection depicted by the data.

Kristopher Bedka↗

NASA NTRSDate not supplied

Robust Path-following Controller for Multirotor Vehicles in Uncertain Wind Conditions

This paper presents simulations of L1 adaptive controller on a multirotor vehicle for compensation of convective winds. There are increasing efforts to utilize unmanned vehicles for fighting wildfires, but such vehicles need to be able to compensate for convective updrafts and other uncertainties (e.g., wind shear and turbulence) caused by the wildfire. Other application domains, such as urban air mobility, also must account for convective or uncertain winds present in urban microclimates. Geometric controllers have great tracking performance properties in environments without uncertainties, but the tracking performance degrades when wind disturbances and external loads are present in the environment. Introducing L1 adaptive control into the controller architecture compensates for these wind disturbances and reduces the tracking error caused by such disturbances. The controller architecture is implemented on a small quadrotor. The simulations demonstrate the advantages of the L1 adaptive augmentation for a sample figure-eight trajectory while encountering unknown variable wind conditions with an external load.

John L Bullock↗

NASA NTRSDate not supplied

Ground Validation Activities for the INCUS Satellite Mission

Over the next decade, there will be several satellite-based radar missions designed to estimate vertical motions and mass flux within deep convection. One of these is the upcoming Investigation of Cumulus Updrafts (INCUS) mission. INCUS will do this using a low-Earth orbit train of three small satellites carrying Ka-band radars to observe the 3-D evolution of radar reflectivity within deep convective cells at time intervals of 30-, 90-, and 120-sec. One approach to validating this novel time-difference (delta-t) approach would include a pair of Doppler radars flown on two different high-altitude aircraft (i.e., satellite simulator), but that solution is not practical within the scope of a cost-capped Earth Venture mission like INCUS. Instead, the ground-based validation (GV) approach for INCUS will consist of using vertical profiling radars, including analysis of existing convective cases, and multiple polarimetric, Doppler radars performing coordinated rapid sampling of the same convective cell. These new observations will be collected in the coming years through local deployments of existing research radar facilities at 1 - 3 sites over multiple seasons to capture a statistically significant sample of storm types (both pre- and post-launch) or as a single post-launch field campaign in a region where convection is very predictable. This presentation will include an overview of INCUS GV, both pre- and post-launch activities, as well as some of our collaborations with the radar community to address some of the challenges in sampling the vertical evolution of convective cells on 120-sec or less time scales.

remote sensing↗

NASA NTRSDate not supplied

Quantifying Tropopause-Overshooting Volume from Satellite and Radar Observations During the DCOTSS 2021 and 2022 Campaigns

Tropopause-overshooting cloud locations, their volume, and the percentage of anvil cloud occupied by overshooting were quantified from state-of-the-art merged NEXRAD radar and GOES-16/17 satellite products during the 2021 and 2022 Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) study periods. A novel method for defining and tracking large individual storms or storm outbreak objects in space and time was presented, which enabled improved understanding of the complex feature-specific biases among GOES- and GridRad-derived overshooting metrics. GOES overshooting cloud top height was estimated using a stratospheric lapse rate approach informed by GOES visible and IR measurements of shadows from OTs and calibrated based on previously observed maximum GridRad overshooting distribution. Total overshooting volumes derived over CONUS are higher for GOES than GridRad for both years, especially during 2021. Over all storm outbreak objects with observed overshooting, GOES observed higher overshooting percentages while GridRad observed relatively higher overshooting magnitudes. The greater spatial coverage of GOES overshooting, especially noticeable during the mature and dissipation stages of outbreaks due to inherent limitations of infrared satellite data which make it difficult to differentiate cold, high-altitude outflow from true updraft cores, outweighed differences in magnitude to yield higher GOES volume. Individual events, however, revealed that the higher overshooting magnitudes observed by GridRad produce higher overshooting volumes at times. Four-dimensional trajectories of tropopause-overshooting air parcels were compared 5 days after overshooting occurred to depict the envelope of convectively impacted air in the stratosphere. The generally good agreement in parcel plume area initiated from GOES and GridRad overshooting detections suggests that geostationary satellite data can be used to estimate where and how often overshooting impacts stratospheric composition in regions without a ground-based weather radar network to estimate climate impacts of overshooting convection.

Kristopher Bedka↗

NASA NTRSDate not supplied

Robust Path-following Controller for Multirotor Vehicles in Uncertain Wind Conditions

John Bullock↗

NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗

DOE OSTI2022

Simulation-Based Model for Facility-Scale Eagle Presence Mapping

This talk presents the recent progress in building a predictive movement model for predicting conflict between soaring raptors and wind turbines. In particular, it details the recently developed numerical tool called Stochastic Soaring Raptor Simulator for simulating updraft-subsidized paths for soaring raptors through variety of wind conditions and the associated directional intent.

agent-based model↗

DOE OSTI2022

Progress Towards a Predictive Eagle Behavior and Risk Modeling Framework: Overview and Recent Validation Efforts

This presentation summarizes progress to date of the U.S. Department of Energy project, "Development of a computational framework for modeling golden eagles (Aquila chrysaetos) near wind farms," which focuses on stochastic behavioral modeling of soaring raptors across landscape, facility, and turbine spatiotemporal scales. This publicly available, open-source modeling framework includes behavioral models based on three different underlying principles: energy minimization at landscape scale, behavioral heuristics at landscape-facility scale, and data-driven behaviors at the facility-micro-scale. We will briefly overview the key advancements in the behavioral modeling state of the art, which leverages multiple high-resolution telemetry data sources combined with high-fidelity atmospheric flow modeling insights. We then present preliminary results from a validation study in Altamont, California. This new study involves a novel application of the Stochastic Soaring Raptor Simulator (SSRS), in a new geographic locale, to understand facility scale eagle movement patterns over time scales representative of a wind project's lifetime. For this desktop analysis (that does not depend on any high-performance computing resources), SSRS simultaneously considers a variety of wind conditions and eagle approach vectors toward a project site of interest. This work demonstrates the integration of publicly available landscape-scale atmospheric datasets, our recently improved engineering updraft models (see presentation from Thedin et al.), and our energy minimization behavioral models within the SSRS framework. While we only present results from a single behavioral model, the integration of these three modeling components forms the foundation for our more sophisticated behavioral models (see presentations from Brandes et al., Sandhu et al.) that are under active development. Results are presented in the form of presence maps, which may be applied to estimate risk to wildlife, augment ground survey data, inform wind-plant operations, or incorporated into wind-plant designs.

agent-based modeling↗