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At least 343 records · Page 19

Investigation of CATS Aerosol Products and Application Toward Global Diurnal Variation of Aerosols

We present a comparison of 1064 nm aerosol optical depth (AOD) and aerosol extinction profiles from the Cloud-Aerosol Transport System (CATS) level 2 aerosol product with collocated Aerosol Robotic Network (AERONET) AOD, Moderate Imaging Spectroradiometer (MODIS) Aqua and Terra Dark Target AOD and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD and extinction data for the period of March 2015–October 2017. Upon quality-assurance checks of CATS data, reasonable agreement is found between aerosol data from CATS and other sensors. Using quality-assured CATS aerosol data, for the first time, variations in AODs and aerosol extinction profiles are evaluated at 00:00, 06:00, 12:00 and 18:00 UTC (and/or 00:00, 06:00, 12:00 and 18:00 local time or LT) on both regional and global scales. This study suggests that marginal variations are found in AOD from a global mean perspective, with the minimum aerosol extinction values found at 18:00 LT near the surface layer for global oceans, for both the June–November and December–May seasons. Over land, below 500 m, the daily minimum and maximum aerosol extinction values are found at 12:00 and 00:00/06:00 LT, respectively. Strong diurnal variations are also found over north Africa, the Middle East and India for the December–May season, and over north Africa, south Africa, the Middle East and India for the June–November season.

Logan Lee↗

NASA’s Atmosphere Observing System (AOS), From A Precipitation Perspective

NASA is developing the Atmosphere Observing System (AOS) mission as part of its Earth System Observatory (ESO) in response to priorities identified in the 2017 Earth Science Decadal Survey. AOS addresses the Decadal Survey’s call for missions measuring the targeted observables “clouds, convection, and precipitation”; “aerosol and cloud radiative properties”, and “aerosol vertical profiles”. AOS is currently in Phase A, the concept and technology development phase, with plans for satellite launches in the late 2020’s and early 2030’s, and suborbital measurements to include field campaigns after those satellite launches. Key precipitation-related instrumentation includes Doppler radars capable of measuring clouds and precipitation, and passive microwave radiometers with channels between 89-700 GHz. Other instrumentation includes dual-wavelength backscatter lidars, a multi-wavelength and multi-angle polarimeter, a far infrared imaging radiometer, and aerosol and moisture limb sounders that will contribute to studies of coupled aerosol-cloud-precipitation processes. From the perspective of precipitation science, a Ku-band Doppler radar in a 55° inclined orbit provided by JAXA will continue the heritage of precipitation radar measurements made by the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM), while adding information about Doppler-derived particle vertical motions. With assumptions about particle terminal velocities, the Doppler measurements will enable estimates of the vertical air motion in storms. A higher frequency (W and/or Ka band) radar on a satellite in a polar sun-synchronous orbit will add similar information with greater sensitivity to clouds and to light precipitation. Passive microwave radiometers for AOS will be less capable than those from TRMM and GPM from a precipitation-measurement perspective, but more capable of adding information about cloud processes. Synergies among these and other instruments are expected to advance process-level understanding of aerosols, clouds, and precipitation.

Daniel J Cecil↗

Application of the Man-computer Interactive Data Access System (McIDAS) to aerospace meteorology

The Man-computer Interactive Data Access System (McIDAS) considered in this paper has been in use at Marshall Space Flight Center (MSFC) since 1981. The MSFC McIDAS system is primarily employed as a research tool, taking into account rainfall estimates as deduced from Scanning Multichannel Microwave Radiometer (SMMR) data, remote sensing sensor development (MAMS), Doppler-lidar derived winds, cloud tracked winds, and analysis of lightning ground strike data. With respect to the SMMR data analysis, passive microwave satellite data are displayed on McIDAS as images. Two major research efforts are concerned with the determination of mesoscale winds. These efforts are based on a utilization of a Doppler-lidar system, and GOES multispectral imagery. It is pointed out that future plans include increased usage of the McIDAS system.

Meyer, P. J.↗

Mapping Aerosol Lidar Ratios Over Ocean for CALIPSO Using Modis AOD-Constrained Retrievals and A Global Aerosol Model

The CALIPSO aerosol algorithms currently assign one lidar ratio value for each of the seven tropospheric aerosol types. In a future data products release, the CALIPSO project aims to improve these algorithms by developing regional and seasonal lidar ratio climatologies. In this study, aerosol lidar ratios are inferred through Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscatter profiles constrained by collocated aerosol optical depth from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) datasets. The analysis is subsampled for only those profiles that are cloud-free and contain one aerosol type (based on CALIOP feature classification). In addition, the CALIOP profiles are collocated with aerosol volume fractions simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. In this talk, the twelve-year (2006-2017) mean spatial distributions of inferred aerosol lidar ratios for CALIOP-classified marine aerosols and the corresponding modeled sea salt volume fractions (SSVF) will be shown. Model-assisted climatological lidar ratio maps on a seasonal scale will also be presented, developed from the empirical relationship found between the modeled SSVF and lidar ratios. A comparison with past studies will be provided as well as results of a sensitivity study regarding the variability of retrieved lidar ratios as a function of horizontal averaging resolution. While the majority of this talk will focus on lidar ratios for CALIOP-classified marine aerosols, preliminary results will be shown for other aerosol types over ocean, such as dust and elevated smoke.

Travis Toth↗

Raw_data_Batch_I: Argonne to Shorewood via I-55

Date of collection: May 12, 2023 Location: Interstate 55, DuPage County, IL This data set contains lidar and vision data collected along a round trip between I-55 Exit 273A and Exit 253. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![argonne shorewood image](argone-shorewood.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal Infrared Dust Optical Depth and Coarse-Mode Effective Diameter Over Oceans Retrieved From Collocated MODIS and CALIOP Observations

In this study, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations and dust vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10μm) and the coarse-mode dust effective diameter (Deff) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume particle size distribution (PSD) corresponding to retrieved Deff with the in-situ measured dust PSDs from the AER-D, SAMUM-2 and SALTRACE field campaigns through case studies. The new DAOD10μm retrievals were evaluated first through comparisons with the collocated DAOD10.6μm retrieved from the combined Imaging Infrared Radiometer (IIR) and CALIOP observations from our previous study (Zheng et al. 2022). The pixel-to-pixel comparison of the two DAOD retrievals indicates a good agreement (R~0.7) and a significant reduction of (~50%) retrieval uncertainties largely thanks to the better constraint on dust size. In a climatological comparison, the seasonal and regional (5°×2°) mean DAOD10um retrievals based on our combined MODIS and CALIOP method are in good agreement with the two independent Infrared Atmospheric Sounding Interferometer (IASI) products over three dust transport regions (i.e., North Atlantic (NA; R = 0.9), Indian Ocean (IO; R = 0.8) and North Pacific (NP; R = 0.7)). Using the new retrievals from 2013 to 2017, we performed a climatological analysis of coarse mode dust Deff over global oceans. We found that dust Deff over IO and NP are up to 20% smaller than that over NA. Over NA in summer, we found a ~50% reduction of the number of retrievals with Deff > 5 μm from 15°W to 35°W and a stable trend of Deff average at 4.4 μm from 35°W throughout the Caribbean Sea (90°W). Over NP in spring, only ~5% of retrieved pixels with Deff > 5 μm are found from 150°E to 180°, while the mean Deff remains stable at 4.0 μm throughout eastern NP. To our best knowledge, this study is the first to retrieve both DAOD and coarse-mode dust particle size over global oceans for multiple years. This retrieval dataset provides insightful information for evaluating dust long-wave radiative effects and coarse mode dust particle size in models.

dust optical depth↗

Future NASA Earth Science Missions

Following on the successful launch of Aura in July 2004, NASA will continue to add to the A-train with the spring 2006 launch of the CALIPSO and Cloudsat missions, followed by the fall 2008 launch of the Orbiting Carbon Observatory (OCO). The CALIPSO mission has three nadir-viewing instruments: a cloud-aerosol lidar for measuring aerosol and cloud height and properties, a 3-channel thermal infrared imaging radiometer, and a wide field cloud camera. The Cloudsat mission has a 94 GHz cloud profiling radar, returning cloud structure vs. height profiles. Orbiting Carbon Observatory (OCO) is a mission focused on precision measurements of total column CO2 using reflected sunlight. These missions and how they relate to the other parts of the A-train will be presented. A brief report from a NASA workshop on future atmospheric science missions will also be presented.

Gleason, James↗

Fisher's Peak Ecological Forecasting: Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation.

DEVELOP Tech Paper↗

Marin County Wildland Fires: Examining Fuel Load and Land Cover Change to Inform Fire Prevention and Suppression Decisions in Marin County, CA

Heightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wild fire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry, a Marin-based fire service work force development program, to develop new models to assist with fire management. Using data from Sentinel-2A, Planet Scope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), the team developed several input data layers to three models evaluating wild fire severity. One model performed a suitability analysis with weights based on scientific literature, another utilized machine learning based on past fires in Marin and neighboring Sonoma County to predict the difference normalized burn ratio, and the third inputted data layers into the Flam Map tool, which outputs risk categories. The team compared model outputs and, using the best-fit model, performed fuzzy logic analysis to identify specific locations where a fire break could be constructed to interrupt the progress of an active fire. These tools were proven useful and will assist partners in preparing for and managing an active wildfire event.

Suhani Dalal↗

Marin County Wildland Fires: Examining Fuel Load and Land Cover Change to Inform Fire Prevention and Suppression Decisions in Marin County, CA

Heightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wildfire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry (a Marin-based fire service workforce development program) and the Marin County Fire Department to develop models to assist with fire management. Using data from Sentinel-2A, PlanetScope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), our team developed a number of input data layers for three different models to evaluate wildfire severity. One model performed a suitability analysis with weights based on scientific literature; another model utilized a U-Net Convolutional Neural Network trained on previous fires in Marin and neighboring Sonoma County to predict the difference normalized burn severity; and the third inputted data layers into the FlamMap tool that outputs risk categories. We compared model outputs and performed a weighted overlay analysis to identify specific locations where a fireline could be constructed to interrupt the progress of an active fire. These tools will assist partners in preparing for and managing active wildfire situations.

Remote sensing↗

Atmospheric Depolarization Lidar Experimental Receiver: A Space Shuttle Hitchhiker Payload

Development work is underway at the Goddard Space Flight Center to construct a depolarization measuring atmospheric lidar receiver. The Atmospheric Lidar (AL) is tentatively scheduled to fly on the Space Shuttle in a late-1999 time frame. The AL will fly in conjunction with the Shuttle Laser Altimeter (SLA) and the Infrared Spectral Imaging Radiometer (ISIR) to provide a comprehensive package of atmospheric aerosol and cloud information. The AL operates in conjunction with the SLA laser transmitter and measures profiles of atmospheric backscatter at 532 nm. The receiver system discriminates between the parallel and perpendicular polarizations of the backscattered signal, thus providing depolarization ratios for scattering from clouds. The lidar receiver also provides cloud height and thickness measurements to complement the brightness temperature measurements generated by the ISIR thermal imager. The function of the AL is twofold. The primary function is to provide range-resolved measurements of atmospheric aerosol backscatter and depolarization ratio at 532 nm with 75 m vertical resolution. The scientific purpose of these measurements is to determine composition of clouds based on the depolarization ratio (i.e cloud content is water or ice), to determine cloud height and thickness, and to gain further understanding of the global distribution of aerosols. This information, when coupled with the cloud brightness measured by the ISIR thermal imager will provide a significant amount of information on cloud composition and radiative effects, particularly for cirrus and sub-visual cirrus clouds. A secondary function of the AL is to serve as an in-space test bed for lidar technology advancements, including a fully fiber-coupled receiver and photon counting from space. In addition, the data obtained by the AL will be used to develop software for the Geoscience Laser Altimeter System (GLAS) flight mission.

McGill, Matthew J.↗

WHYMSIE-SGP Field Campaign Report

Through a partnership between the U.S. National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA), this field campaign demonstrated first-of-its-kind hyperspectral microwave airborne measurements (Conical Scanning Millimeter-wave Imaging Radiometer [CoSMIR-H]). It was complemented by other passive (infrared, visible) and active (lidar) sensors onboard the NASA ER-2 aircraft. Serving as a future NASA planetary boundary-layer (PBL) mission prototype, the Westcoast and Heartland Hyperspectral Microwave Intensive Experiment (WH 2 yMSIE, formerly WHyMSIE) aimed to capture a wide variety of thermodynamic, moisture, and PBL regimes across a variety of surface types. The intensive operating period of the campaign spanned from October 22, 2024, through November 15, 2024, and included a large network of collaborators.

54 ENVIRONMENTAL SCIENCES↗

An ultra-sensitive coherent detector capable of single photon detection for lidar applications

The properties of Ultra-Sensitive Coherent Detectors (USCD's) are nearly that of an ideal detector for lidar applications. Recent progress in the development of USCD's is briefly reviewed, and its imaging capability is demonstrated. These new detectors possess properties with significant improvements over conventional technology. These improvements include a high quantum efficiency of 0.95, gain in excess of 10 exp 13, a narrow bandwidth of 180-300 MHz at 1 micron, imaging capability, and phase conjugation ability. We have constructed a USCD using two Nd:YAG laser amplifiers and a four-wave Brillouin mirror (FWBM) using SnCl4 as the Brillouin medium. Using a 10 Hz repetitively-pulsed single frequency laser, we have shown that the Brillouin medium is free from thermal blooming and from optical breakdown.

Amimoto, Sherwin↗

Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4: Potential for Enhancing Nocturnal Ice Cloud Retrievals

Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared

Minnis, Patrick↗

Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4- Potential for Enhancing Nocturnal Ice Cloud Retrievals

Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared

CRS and CPL↗

Space-Based Lasers for Remote Sensing Applications

There are currently three operational lidar systems orbiting the Earth, the Moon and the planet Mercury gathering scientific data and images to form a better understanding of our Earth and solar system. In this paper we will present an overview of the spacebome laser programs and offer insights into future spacebome lasers for remote sensing applications.

Yu, Anthony W.↗

Fisher's Peak Ecological Forecasting - Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation

Lauren Lad↗

June 2023 Canadian Wildfire Effects on Hampton Roads VA using ASDC Data

In June of 2023 thousands of acres of wildfires spread across northwestern Canada. This event emitted huge amounts of smoke, and pollutants that travelled east across the North America, the Atlantic ocean and eventually all the way to Continental Europe. This smoke created a dangerous air quality event throughout the Atlantic Coast. As climate change increases the prevalence of wildfires more cities and states will be affected by the dangerous smoke and pollutants produced by these events. In this poster we documented and investigated the June 06th Air Quality Event over Hampton Roads, VA. To perform a comparative analysis, we utilized two data sources: NASA’s Atmospheric Science Data Center we used the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the Deep Space Climate ObserVatoRy (DSCOVR) Enhanced Polychromatic Imaging Camera (EPIC), data product, and the EPA’s ground-based Air Quality System (AQS).

Air Quality↗