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At least 415 records · Page 23

The New NASA Ames Infrared Optical Constant Facility. Determinations for Titan Aerosol-, and Exoplanet and Brown Dwarf Cloud Particle Analogs

Here we present a new optical constant facility developed at NASA Ames that will allow the determination of optical constants in the infrared of various materials, analogs of hazes and cloud particles in (exo)planet atmospheres and brown dwarfs. Our facility is composed of a Fourier Transform Infrared (FTIR) spectrometer continuously covering the Near-IR, mid-IR and Far-IR range (from 0.74 to 200 µm), coupled to variable angle transmittance and reflectance accessories that allow the characterization of the scattering properties of nonhomogeneous samples (laboratory planetary aerosol analogs, films, slabs of material, crystals, powders...) over a wide incidence and emittance angle range (0-90 degrees). This permits the angular light distribution in both transmission and reflection measurements to be characterized, enabling the determination of the complex indices of refraction, n and k, over the full NIR-FIR range via modeling of the laboratory observations. The resulting refractive indices are critical input parameters in radiative transfer models, exoplanet and brown dwarf cloud models, protoplanetary disk simulations and other models used for the interpretation of observational data from past, current and future (exo)planetary NASA missions. We will present preliminary data obtained on Titan aerosol analogs produced in the Titan Haze Simulation (THS) experiment on COSmIC, a unique experimental platform developed at NASA Ames that allows the simulation of Titan's complex atmospheric chemistry at Titan-like temperature (200 K). We will also introduce a new study of the optical properties of ammonium-bearing phosphates, potential cloud particles forming in temperate exoplanets and brown dwarfs.

Planetary Science↗

COMMIT in 7-SEAS/BASELInE: Operation of and Observations from a Novel, Mobile Laboratory for Measuring In-Situ Properties of Aerosols and Gases

Trace gases and aerosols (particularly biomass-burning aerosols) have important implications for air quality and climate studies in Southeast Asia (SEA). This paper describes the purpose, operation, and datasets collected from NASA Goddard Space Flight Center's (NASA/GSFC) Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) laboratory, a mobile platform designed to measure trace gases and optical/microphysical properties of naturally occurring and anthropogenic aerosols. More importantly, the laboratory houses a specialized humidification system to characterize hygroscopic growth/enhancement, a behavior that affects aerosol properties and cloud-aerosol interactions and is generally underrepresented in the current literature. A summary of the trace gas and optical/microphysical measurements is provided, along with additional detail and analysis of data collected from the hygroscopic system during the 2015 Seven South-East Asian Studies (7-SEAS) field campaign. The results suggest that data from the platform are reliable and will complement future studies of aerosols and air quality in SEA and other regions of interest.

aerosols↗

Temporal and Spatial Distribution of Liquid Water and Ice Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODE) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and the Aqua spacecraft on April 26,2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the globe.

King, Michael D.↗

The Radiative Effect on Cloud Microphysics from the Arctic to the Tropics

Cloud representation is one of the largest uncertainties in the current weather and climate models. In this article, the observations and modeling of the radiative effect on (cloud) microphysics (REM) from the Arctic to the Tropics are overviewed, providing a new direction to meet the challenge of cloud representation. REM deals with the radiation-induced temperature difference between cloud particles and air. It leads to two common phenomena observed at the surface—dew and frost—and impacts clouds aloft significantly, which is noticed via the wide occurrence of horizontally oriented ice crystals (HOICs). However, REM has been overlooked by all of the operational weather and climate models. Based on the bin model of REM and the global distribution of radiative cooling/warming, the observations of REM from several platforms (e.g., aircrafts, field campaigns, and satellites) are coordinated in this article, yielding a global picture on REM. As a result, the picture is compatible with the global distribution of HOICs and other ice crystal characteristics obtained from various clouds on the globe, such as diamond dust (or clear-sky precipitation) in the Arctic, sub-visual cirrus clouds in the tropical tropopause layer, and other cirrus clouds from the low to high latitudes. In addition, ice crystals possess relatively strong REM compared to liquid drops because their aspect ratio is usually not one. The global picture on REM can be used by the weather and climate modelers to diagnose their cloud representation biases. It can also be used to improve the atmospheric ice retrieval algorithm from satellite observations.

cloud microphysics↗

Effects of meteoroids and space debris on the particulate environment for space station

A large orbiting platform such as Space Station will be subjected to numerous impacts by meteoroids and space debris fragments. These hypervelocity impacts will produce clouds of ejected structural material in the vicinity of the Station. The development of a preliminary model for impact-generated ejecta production which combines the fluxes of meteoroids and space debris fragments with a description of the number of ejecta particles produced by hypervelocity impacts is reported. Modeling results give mean ejecta densities from 30 to 100 percent of the present particulate background limitation of 1 particle 5 microns and larger per orbit per 1 x 10(-5) sr field-of-view as seen by a 1-m-diameter aperture telescope in the 1990's time frame. Projected increases in the space debris flux raise this density to 300 percent of this limitation after 2010. The model is also applied to estimate the vulnerability of metallic claddings on composite structural members to penetration by hypervelocity projectiles, thereby exposing the substrate to atomic oxygen. The estimated annual number of penetrations is from 4 to 8 per square meter of cross-sectional area in the mid 1990's, increasing to more than 40 penetrations per square meter after 2010.

Seebaugh, W. R.↗

Surface Radiation Budget (SRB) Release 2 Shortwave Daily Data in Native Format (SRB_REL2_SW_DAILY)

This data set contains upward and downward fluxes, photosynthetically active radiative flux, aerosol and cloud optical depth, cloud fraction, and solar zenith angle measured at three hourly intervals for each day for the entire globe between 07/01/1983 and 10/31/1995. These SW surface radiative parameters were derived with the Shortwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1998-07-26] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=daily; Temporal_Resolution_Range=daily].

ALL SKY SW SURFACE UPWARD FLUX↗

Customizing NASA's Earth Science Research Products for addressing MENA Water Challenges

As projected by IPCC 2007 report, by the end of this century the Middle East North Mrica (MENA) region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. In late 2011, the World Bank, USAID and NASA have joined hands to establishing integrated, modem, up to date NASA developed capabilities for various countries in the MENA region for addressing water resource issues and adapting to climate change impacts for improved decision making for societal benefits. The main focus of this undertaking is to address the most pressing societal issues which can be modeled and solved by utilizing NASA Earth Science remote sensing data products and hydrological models. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. NASA has over fifteen satellites and thirty instruments operating on these space borne platforms and generating over 2000 different science products on a daily basis. Some of these products are soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gasses, ice and snow measurements, and many more. All of the data products, models and research results are distributed via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, drought assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Training is an important component under this activity and adequate level of training will be offered to build basic capacity to work with NASA provided data products, models for their future use. This paper provides a comprehensive introduction to NASA's Earth Science mission for understanding the behavior of our home Planet, projecting its health for future generations and applying research results solving societal issues.

Habib, Shahid↗

9+ Years of CALIPSO PSC Observations: An Evolving Climatology

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than nine-year data record from 2006- 2015.

Pitts, Michael C.↗

CALIPSO Polar Stratospheric Cloud Observations from 2006-2015

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than nine-year data record from 2006- 2015.

Pitts, Michael C.↗

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015- 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Reid W Sawtell↗

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015- 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Reid W Sawtell↗

TPSAS-NF1676L-20076-DND

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than eight-year data record.

Michael C Pitts↗

A Synopsis of the 8+ Year CALIOP Polar Stratospheric Cloud Data Record

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than eight-year data record.

Michael C Pitts↗

Technology for active laser remote sensing from space

The requirements for the experiments to be performed on the laser atmospheric sounder and altimeter facility of the polar orbiting platform are considered. The proposed instruments for the Lidar In-Space Technology Experiment designed to calibrate and verify the radiative transfer equation for laser energies at wavelengths of 1060, 532, and 355 nm, and to measure the vertical distribution of aerosols, the optical thickness of high altitude clouds, and the top of clouds are described. Research in the area of tunable laser materials and Lidar transmitters, in particular Ti:Al2O3 materials and Lidar transmitters, aimed at increasing wavelength tunability, efficiency, and the lifetime of solid-state lasers for utilization on Space Station polar orbiting platforms is discussed.

Sokoloski, M. M.↗

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗

Neighborhood Keeper Program Review

Dragos provided INL access to their Neighborhood Keeper platform, which contains simulated data, sample reports given to utilities, and access to anonymized program data that is sent from utilities to the cloud. Dragos has specifically asked INL to review the available data and respond to the following questions: 1) What detections or combinations of detections are most useful? 2) What additional analysis would benefit the electricity subsector? 3) How could Neighborhood Keeper reporting be modified to benefit the electricity subsector? 4) What lessons learned from the Cybersecurity for the Operational Technology Environment (CyOTE) program could be provided? 5) Based on INL’s experience with utilities, are there lessons learned about data sharing that could be provided? 6) Are there recommendations that could benefit the electricity subsector?

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗

New Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

King, Michael D.↗