SEARCH · Search NASA

Results for “validation dataset”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

NASA NTRS2015

CFD Validation Experiment of a Mach 2.5 Axisymmetric Shock-Wave Boundary-Layer Interaction

Preliminary results of an experimental investigation of a Mach 2.5 two-dimensional axisymmetric shock-wave/boundary-layer interaction (SWBLI) are presented. The purpose of the investigation is to create a SWBLI dataset specifically for CFD validation purposes. Presented herein are the details of the facility and preliminary measurements characterizing the facility and interaction region. The results will serve to define the region of interest where more detailed mean and turbulence measurements will be made.

Superonic Flow↗

NASA NTRS2015

CFD Validation Experiment of a Mach 2.5 Axisymmetric Shock-Wave/Boundary-Layer Interaction

Preliminary results of an experimental investigation of a Mach 2.5 two-dimensional axisymmetric shock-wave/ boundary-layer interaction (SWBLI) are presented. The purpose of the investigation is to create a SWBLI dataset specifically for CFD validation purposes. Presented herein are the details of the facility and preliminary measurements characterizing the facility and interaction region. These results will serve to define the region of interest where more detailed mean and turbulence measurements will be made.

Shock-Wave/Boundary Layer Interaction↗

NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗

NASA NTRS1997

Pre-Launch Tasks Proposed in our Contract of December 1991

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Running, Steven W.↗

NASA NTRS1998

Pre-Launch Tasks Proposed in our Contract of December 1991

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Source record↗

NASA NTRSDate not supplied

Understanding the Uncertainty and Variability of Earth’s Radiation Budget Components Over the Past 3 Decades from the NASA’s GEWEX Surface Radiation Budget Release 4 Integrated Product

The NASA/GEWEX Surface Radiation Budget (SRB) project produced a 30+ year time series of 3-hourly Top-of-Atmosphere (TOA) and surface radiative flux components at a 1x1 degree resolution. This SRB Release 4 Integrated Productare derived using imager data products from the cross-calibrated from ISCCP (International Satellite Cloud Climatology Project) “HSeries” radiance, cloud and surface property data products. The ISCCP HXS product replaces ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use and discuss radiative flux sensitivities to in this presentation. Total solar irradiance is now variable consistent with SORCE measurements. Sea surface (SeaFlux v2.0) and land surface products (LandFlux) are utilized to achieve an radiative flux estimatesintegrated with global data sets from these GEWEX projects. The variable aerosol composition are specified using a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC) also used for background aerosol in the ISCCP HX. Numerous other improvements were made to the SW and LW algorithms including improved cloud optical property treatments and specification of surface spectral albedo and emissivity for various surface conditions. Here we analyze the new SWand LWSRB datasets, comparing them to the previous Release 3, BSRN, GEBA and PMEL surface measurements, and ERBE and CERES satellite datasets. For surface flux validation besides ensemble comparisons, we show the variability of SRB vs surface measurements from BSRN beginning in 1992 and GEBA SW from 1983. We assess the variability of the surface flux anomalies, particularly the net fluxes and the cloud radiative effects, over the entire time period including the period containing CERES overlap. For the TOA fluxes, the anomalies of the fluxes in the early period are compared to the MEaSURES ERBE and the latter period to CERES EBAF/SYN1Deg datasets for a benchmark. Long-term changes in the surface radiation budget components and cloud radiative effects are shown and discussed relative to CERES and surface measurements. This includes a change point analysis that helps associate various changes in the ISCCP GEO/LEO configurations and other inputs to variations in the radiative budget components.

Earth Radiation Budget↗

NASA NTRS2004

Simulating Virtual Terminal Area Weather Data Bases for Use in the Wake Vortex Avoidance System (Wake VAS) Prediction Algorithm

During the research project, sounding datasets were generated for the region surrounding 9 major airports, including Dallas, TX, Boston, MA, New York, NY, Chicago, IL, St. Louis, MO, Atlanta, GA, Miami, FL, San Francico, CA, and Los Angeles, CA. The numerical simulation of winter and summer environments during which no instrument flight rule impact was occurring at these 9 terminals was performed using the most contemporary version of the Terminal Area PBL Prediction System (TAPPS) model nested from 36 km to 6 km to 1 km horizontal resolution and very detailed vertical resolution in the planetary boundary layer. The soundings from the 1 km model were archived at 30 minute time intervals for a 24 hour period and the vertical dependent variables as well as derived quantities, i.e., 3-dimensional wind components, temperatures, pressures, mixing ratios, turbulence kinetic energy and eddy dissipation rates were then interpolated to 5 m vertical resolution up to 1000 m elevation above ground level. After partial validation against field experiment datasets for Dallas as well as larger scale and much coarser resolution observations at the other 8 airports, these sounding datasets were sent to NASA for use in the Virtual Air Space and Modeling program. The application of these datasets being to determine representative airport weather environments to diagnose the response of simulated wake vortices to realistic atmospheric environments. These virtual datasets are based on large scale observed atmospheric initial conditions that are dynamically interpolated in space and time. The 1 km nested-grid simulated datasets providing a very coarse and highly smoothed representation of airport environment meteorological conditions. Details concerning the airport surface forcing are virtually absent from these simulated datasets although the observed background atmospheric processes have been compared to the simulated fields and the fields were found to accurately replicate the flows surrounding the airport where coarse verification data were available as well as where airport scale datasets were available.

Kaplan, Michael L.↗

NASA NTRS2006

Measurements of Unsteady Wake Interference Between Tandem Cylinders

A multi-phase, experimental study in the Basic Aerodynamics Research Tunnel at the NASA Langley Research Center has provided new insight into the unsteady flow interaction around cylinders in tandem arrangement. Phase 1 of the study characterized the mean and unsteady near-field flow around two cylinders of equal diameter using 2-D Particle Image Velocimetry (PIV) and hot-wire anemometry. These measurements were performed at a Reynolds number of 1.66 x 10(exp 5), based on cylinder diameter, and spacing-to-diameter ratios, L/D, of 1.435 and 3.7. The current phase, Phase 2, augments this dataset by characterizing the surface flow on the same configurations using steady and unsteady pressure measurements and surface flow visualization. Transition strips were applied to the front cylinder during both phases to produce a turbulent boundary layer upstream of the flow separation. For these flow conditions and L/D ratios, surface pressures on both the front and rear cylinders show the effects of L/D on flow symmetry, pressure recovery, and the location of flow separation and attachment. Mean streamlines and instantaneous vorticity obtained from the PIV data are used to explain the flow structure in the gap and near-wake regions and its relationship to the unsteady surface pressures. The combination of off-body and surface measurements provides a comprehensive dataset to develop and validate computational techniques for predicting the unsteady flow field at higher Reynolds numbers.

Jenkins, Luther N.↗

NASA NTRS2013

The HyMeX Special Observation Period in Central Italy: Precipitation Measurements, Retrieval Techniques and Preliminary Results

The Mediterranean area concentrates the major natural risks related to the water cycle, including heavy precipitation and flash-flooding during the fall season. The capability to predict such high-impact events remains weak because of the contribution of very fine-scale processes and their non-linear interactions with the larger scale processes. These societal and science issues motivate the HyMeX (Hydrological cycle in the Mediterranean Experiment, http://www.hymex.orgl) experimental programme. HyMeX aims at a better quantification and understanding of the water cycle in the Mediterranean with emphasis on intense events. The observation strategy of HyMEX is organized in a long-term (4 years) Enhanced Observation Periods (EOP) and short-term (2 months) Special Observation Periods (SOP). HyMEX has identified 3 main Mediterranean target areas: North-West (NW), Adriatic (A) and South-East (SE). Within each target area several hydrometeorological sites for heavy rainfall and flash flooding have been set up. The hydrometeorological sire in Central Italy (CI) is interested by both western and eastern fronts coming from the Atlantic Ocean and Siberia, respectively. Orographic precipitations play an important role due to the central Apennine range, which reaches nearly 3000 m (Gran Sasso peak). Moreover, convective systems commonly develop in CI during late summer and beginning of autumn, often causing localized hailstorms with cluster organized cells. Western fronts may heavily hit the Tiber basin crossing large urban areas (Rome), whereas eastern fronts can cause flash floods along the Adriatic coastline. Two major basins are involved within Cl region: Tiber basin (1000 km long) and its tributary Aniene and the Aterno-Pescara basin (300 km long). The first HyMeX SOP1.1 was carried out from Sept. till Nov. 2012 in the NW target area The Italian SOP1.1 was coordinated by the Centre of Excellence CETEMPS, University of L'Aquila, a city located in the CI heart. The CI area was covered by a uniquely dense meteorological instrumentation thanks to a synergy between Italian institutions and NASA-GSFC. The following RADARs were operated: a Doppler single-polarization C-band radar located at Mt Midia; the Polar 55C Doppler dual-polarization C-band radar located in Rome; a Doppler C-hand polarimetric radar located at Il Monte (Abnazo); a polarimetric X-band mini-radar in L' Aquila; a polarimetric X-hand portable mini-radar in Rome; a single-polarization X-band mini-radar in Rome. DISDROMETERs were also deployed: 4 Parsivel optical disdrometers in Rome (at Sapienza, CNR-ISAC and CNR-INSEAN); 1 2D-video disdrometer in Rome; 3 Parsivels optical disdrometer respectively in L'Aquila (Abnazo), Avezzano (Abruzzo) and Pescara (Abnazo). Other INSTRUMENTS were available: 1 K-band vertically-pointing micro rain-radar (MRR), 2 Pludix X-band disdrometers, 1 VLF lightning sensor, 1 microwave radiometer at 23-31 GHz in Rome (at Sapienza); the raingauge network with more than 200 stations in Central Italy. Three overpasses in CI were also performed by the Falcon 20 aircraft equipped with the 950Hz cloud radar RASTA Analysis of the SOP1.1 main events in CI will be described by focusing on the raindrop size distribution statistics and its geographical variability. Intercomparison of rainfall estimates from disdrometers, raingauges and radars will be illustrated with the aim to provide a quality-controlled and physically consistent rainfall dataset for meteorological modeling validation and assimilation purposes.

Gatlin, Patrick↗

NASA NTRS2014

The Benefits of Sample Return: Connecting Apollo Soils and Diviner Lunar Radiometer Remote Sensing Data

The Diviner Lunar Radiometer, onboard NASA's Lunar Reconnaissance Orbiter, has produced the first global, high resolution, thermal infrared observations of an airless body. The Moon, which is the most accessible member of this most abundant class of solar system objects, is also the only body for which we have extraterrestrial samples with known spatial context. Here we present the results of a comprehensive study to reproduce an accurate simulated lunar environment, evaluate the most appropriate sample and measurement conditions, collect thermal infrared spectra of a representative suite of Apollo soils, and correlate them with Diviner observations of the lunar surface. We find that analyses of Diviner observations of individual sampling stations and SLE measurements of returned Apollo soils show good agreement, while comparisons to thermal infrared reflectance under terrestrial conditions do not agree well, which underscores the need for SLE measurements and validates the Diviner compositional dataset. Future work includes measurement of additional soils in SLE and cross comparisons with measurements in JPL Simulated Airless Body Emission Laboratory (SABEL).

Greenhagen, B. T.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-29044-DND

In Langley NASA, Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. The capability of viewing C3M product on browsers will be available on CERES ordering tool web site in the future, https://ceres.larc.nasa.gov

David R Doelling↗

NASA NTRS2020

Alaska Transportation & Infrastructure - Identifying Permafrost Subsidence Using NASA Earth Observations to Pinpoint Road & Infrastructure Vulnerability in Fairbanks, Alaska

A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. UAVSAR and Sentinel-1 seasonal deformation returns produced consistent spatial deformation patterns with residual root mean squared errors of 13 and 21 millimeters, respectively. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution.In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.

Patrick Saylor↗

NASA NTRS2020

Alaska Transportation & Infrastructure Identifying Permafrost Subsidence Using NASA Earth Observations to Pinpoint Road and Infrastructure Vulnerability in Fairbanks, Alaska

A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. The strongest relationship in spatial deformation is observed between Sentinel-1 and UAVSAR with a residual root mean square error of 20 mm. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution. In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.

DEVELOP Tech Paper↗

NASA NTRS2023

Fan Noise Predictions of the NASA Source Diagnostic Test Using Unsteady Simulations with LAVA Part I: Near-Field Aerodynamics and Turbulence

A sliding mesh technique within the Launch, Ascent, and Vehicle Aerodynamics (LAVA) computational framework is validated using the experimental dataset collected as part of the NASA Source Diagnostic Test (SDT) campaign. Two modeling approaches are explored: the unsteady Reynolds-Averaged Navier Stokes (URANS) with Spalart-Allmaras (SA) turbulence model closure, and a hybrid Reynolds-Averaged Navier Stokes/Large Eddy Simulation (RANS/LES) paradigm employing a Zonal Detached Eddy Simulation (ZDES) closure with enhanced shielding protection. Fan stage performance metrics, aerodynamic quantities and turbulent flow structures are analyzed in this work. Initial studies focusing on grid and time-step sensitivity are presented. Sensitivity to different variants of the SA turbulence model is analyzed, supporting the use of the baseline SA model in the production runs. Two conditions are analyzed in detail using URANS and hybrid RANS/LES (HRLES). Mean flow quantities are well-captured by both methods in the low-speed (approach) regime. While URANS misses all the upstream-propagating noise in the inlet due to the rotor-locked tones being evanescent in nature at subsonic fan tip speeds, HRLES captures this broadband component in its pressure field. At the high-speed (sideline) condition, URANS shows better agreement with the SDT data than HRLES in the interstage flow-field. In this regime, URANS captures the tonal content propagating through the inlet, since the tones are now cut-on. Both methods are suitable to capture fan stage performance metrics and mean flow quantities, but only HRLES is able to resolve the fine turbulent structures responsible for broadband noise. The results support the use of the sliding mesh technique implemented in this work for future turbomachinery applications within the LAVA solver framework.

AATT↗

NASA NTRS2023

Fan Noise Predictions of the NASA Source Diagnostic Test Using Unsteady Simulations with LAVA Part I: Near-Field Aerodynamics and Turbulence

AATT↗

NASA NTRS2023

Validation of Universal Cryogenic Flow Boiling Correlations in Thermal Desktop for Liquid Helium

Understanding two-phase cryogenic propellant behavior is key to enabling technologies for future spaceflight missions. Developing accurate models of two-phase flow phenomena, particularly flow boiling in the heating configuration is relevant to the propellant transfer process both in microgravity and on other planetary surfaces. Currently there is a need for more accurate, direct cryogenic data anchored models for various boiling phenomena. Recently, universal correlations for cryogens flowing in heated tubes have been developed for a wide variety of fluids, thermodynamic conditions, and various regimes across the boiling curve, and have been patched to provide a smooth, continuous predictive curve. This paper demonstrates how these correlations have been ported into Thermal Desktop to improve predictive performance. To test the validity of the new correlations, Thermal Desktop is validated against a historical dataset of flow boiling experiments in the heating configuration using liquid helium. Based on results, the new correlations show a substantial improvement over the original built-in flow boiling correlations in Thermal Desktop in predicting the wall temperature as a function of preponderant parameters for this quantum fluid.

cryogenic propellant transfer↗

NASA NTRSDate not supplied

Validation of Universal Cryogenic Flow Boiling Correlations in Thermal Desktop for Liquid Helium

Understanding two-phase cryogenic propellant behavior is key to enabling technologies for future spaceflight missions. Developing accurate models of two-phase flow phenomena, particularly in the current work, flow boiling in the heating configuration, is relevant to the propellant transfer process both in 1-g and microgravity. Currently there is a need for more accurate, direct cryogenic data anchored models for various boiling phenomena. Recently, universal correlations for cryogens flowing in heated tubes have been developed for a wide variety of fluids, thermodynamic conditions, and various regimes across the boiling curve, and have been patched to provide a smooth, continuous predictive curve. This paper describes implementation and validation of these correlations into Thermal Desktop to improve predictive performance, with a focus on liquid helium. Results from Thermal Desktop using both the built-in and new correlations are validated against a historical dataset of flow boiling experiments in the heating configuration using liquid helium. Based on results, the new correlations show a substantial improvement over the original built-in flow boiling correlations in Thermal Desktop in predicting the wall temperature as a function of preponderant parameters for this quantum fluid at temperatures greater than the lambda temperature, T λ = 2.17K.

cryogenic propellant transfer↗

NASA NTRSDate not supplied

Developing Satellite-Assisted Particulate Matter (SAPM) Estimates over India for the MIRA Working Group

The Models, In Situ, and Remote Sensing of Aerosols (MIRA) Working Group is an international collective that encourages collaboration among researchers from these three atmospheric aerosol communities. MIRA currently comprises five interdisciplinary and independently funded Topic Groups, each with specific goals, and involves requests for additional scientific datasets. The Satellite-Assisted Particulate Matter (SAPM) Topic Group, as part of MIRA, focuses on studying particulate matter smaller than 2.5 microns in diameter (PM2.5) due to its significant contribution to air pollution and its harmful effects on human health. While the annual mean PM2.5 levels are typically low (~5-15 μg/m³) across most of the contiguous United States (CONUS), other countries experience much higher concentrations (e.g., India). SAPM aims to compare different methods and techniques for obtaining surface PM2.5 proxies using spaceborne passive and active remote sensors, aerosol models, and in situ measurements. Ultimately, SAPM aims to provide more extensive coverage of PM2.5 concentrations than what is currently available from in situ ground stations, which are limited in some parts of the CONUS and large regions worldwide. Current SAPM members are exploring PM2.5 estimation techniques using active sensors. This presentation offers an overview of these techniques and highlights the strengths and limitations of each approach. These techniques include 1) spaceborne lidar (CALIOP: Cloud-Aerosol Lidar with Orthogonal Polarization) alone, and 2) a combination of spaceborne lidar (CATS: Cloud Aerosol Transport System) and a global aerosol transport model (GEOS: Goddard Earth Observing System). Additionally, we present a case study featuring our SAPM research in India, a country with high levels of PM2.5 concentrations (i.e., state-level annual means of ~100-200 μg/m³). Consistent spatial patterns in PM2.5 over India are found from the in situ data, CALIOP-based, and CATS/model-based methods, with the highest concentrations found in northern India near New Delhi. The gridded PM2.5 analysis yields high R values between in situ and CATS/model (~0.7) and between in situ and CALIOP nighttime (~0.9), as well as good agreement between CATS/model and CALIOP nighttime PM2.5 estimates (R = ~0.8 and slope = ~0.9). For current and future efforts, the SAPM Topic Group is actively seeking new collaborators, especially those working with in situ aerosol measurements, and is interested in acquiring additional aerosol datasets to improve and validate the PM2.5 proxies.

Travis D Toth↗