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At least 271 records · Page 15

CATS Near Real Time Data Products: Applications for Assimilation Into the NASA GEOS-5 AGCM

From February 2015 through October 2017, the NASA Cloud-Aerosol Transport System (CATS) backscatter lidar operated on the International Space Station (ISS) as a technology demonstration for future Earth Science Missions, providing vertical measurements of cloud and aerosols properties. Owing to its location on the ISS, a cornerstone technology demonstration of CATS was the capability to acquire, process, and disseminate near-real time (NRT) data within 6 hours of observation time. CATS NRT data has several applications, including providing notification of hazardous events for air traffic control and air quality advisories, field campaign flight planning, as well as for constraining cloud and aerosol distributions in via data assimilation in aerosol transport models. Â Recent developments in aerosol data assimilation techniques have permitted the assimilation of aerosol optical thickness (AOT), a 2-dimensional column integrated quantity that is reflective of the simulated aerosol loading in aerosol transport models. While this capability has greatly improved simulated AOT forecasts, the vertical position, a key control on aerosol transport, is often not impacted when 2-D AOT is assimilated. Here, we present preliminary efforts to assimilate CATS aerosol observations into the NASA Goddard Earth Observing System version 5 (GEOS-5) atmospheric general circulation model and assimilation system using a 1-D Variational (1-D VAR) ensemble approach, demonstrating the utility of CATS for future Earth Science Missions.

Hlavka, D. L.↗

AIRS Level 2 Data Products

The Atmospheric InfraRed Sounder (AIRS) Standard Retrieval Product consists of retrieved cloud and surface properties; profiles of retrieved temperature, water vapor, and ozone; and a flag indicating the presence of cloud ice or water. They contain quality assessment flags in addition to retrieved quantities and are generated for all locations where atmospheric soundings are taken. An AIRS granule consists of 6 minutes of data. This corresponds to approximately 1/15 of an orbit but exactly 45 scan lines of AMSU-A data or 135 scan lines of AIRS and HSB data.

Vicente, Gilberto↗

Comparison of simulated and actual wind shear radar data products

Prior to the development of the NASA experimental wind shear radar system, extensive computer simulations were conducted to determine the performance of the radar in combined weather and ground clutter environments. The simulation of the radar used analytical microburst models to determine weather returns and synthetic aperture radar (SAR) maps to determine ground clutter returns. These simulations were used to guide the development of hazard detection algorithms and to predict their performance. The structure of the radar simulation is reviewed. Actual flight data results from the Orlando and Denver tests are compared with simulated results. Areas of agreement and disagreement of actual and simulated results are shown.

Britt, Charles L.↗

Image masks of global ship tracks for NASA MODIS data products

Ship tracks, long thin artificial cloud features formed from the pollutants in ship exhaust, are satellite-observable examples of aerosol-cloud interactions (ACI) that can lead to increased cloud albedo and thus increased solar reflectivity, phenomena of interest in solar radiation management. In addition to ship tracks being of interest to meteorologists and policy makers, their observed cloud perturbations provide benchmark evidence of ACI that remain poorly captured by climate models. To broadly analyze the effects of ship tracks, high-resolution satellite imagery data highlighting their presence are required. To support this, we provide a hand labelled dataset to serve as a benchmark for a variety of subsequent analyses. Established from a previous dataset that identified ship track presence using NASA’s MODIS Aqua satellite imager, our first-of-its-kind dataset is comprised of image masks: capturing full ship track regions, including their contours, emission points and dispersive patterns. In total, 300 images, or around 2,500 masked ship tracks, observed under varying conditions are provided, and may facilitate training of machine learning algorithms to automate extraction.

Atmospheric dynamics↗

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Kato, Seiji↗

AMSR-2 Daily Snow Depth Data Product Using a Neural Network Algorithm Trained by Collocated ICESat-2 Measurements

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu 1 et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu 2 et al. (2022,2024) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, a neural network (NN) algorithm, employing several channels from AMSR-2 and the humidity vertical profiles GMAO GEOS-IT, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained NN snow-depth was applied to 2014-2020 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. This paper used AMSR-2 data, a passive microwave instrument to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗

NASA’s NextGen Remote Sensing Instruments Have Arrived: Data Products For Studying Disease Vectors

Remote sensing can be used to measure, evaluate or estimate both the environment (state functions) and interfaces (processfunctions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equationsto significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remotesensing instruments which have become recently operational will provide a significant enhancement in our ability to studydisease vector’s life cycles and habitats. These instruments are on the International Space Station (ISS) and includeECOSTRESS, DESIS, and GEDI. ECOSTRESS is a 5 channel, thermal IR instrument with 70 m resolution and approximately1-5 day repeat cycle of day/night pairs. DESIS jointly developed by German Aerospace Center and Teledyne Brown Engineeringis a hyperspectral sensor system of 235 channels and 30 m resolution. DESIS data is only being acquired on demand. GEDI is ahigh-resolution laser ranger used for observing Earth’s forests and topography. NASA’s current ISS instrument configuration provides measurements of the critical environmental measures of environmentalstate functions important to vector & disease life cycles. Remote sensing data provide a spatial context and time series oflandscape scale process functions represented by land use mapping and measurements of ecological functions. Global publichealth is entering a new information age through the use of spatial models of disease vector/host ecologies driven by the use ofremotely sensed data to measure environmental and structural factors critical in determining disease vector habitats. In 2018, NASA initiated a new study for the Surface Biology and Geology (SBG) Designated Observable, identified in the 2018National Academies’ Decadal Survey entitled, “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observationfrom Space.” (https://www.nap.edu/catalog/24938/thriving-on-our-changing-planet-a-decadal-strategy-for-earth) . The SBG isplanned to collect global remote sensing measurements using a hyperspectral spectrometer and multispectral thermal data. Thesedata sets will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats globally. The 3sensors on the ISS provide precursor data to prepare the community for the application of future SBG data toward diseasestudies.

Disease Vectors↗

Improving Ocean Color Data Products using a Purely Empirical Approach: Reducing the Requirement for Radiometric Calibration Accuracy

Radiometric calibration is the foundation upon which ocean color remote sensing is built. Quality derived geophysical products, such as chlorophyll, are assumed to be critically dependent upon the quality of the radiometric calibration. Unfortunately, the goals of radiometric calibration are not typically met in global and large-scale regional analyses, and are especially deficient in coastal regions. The consequences of the uncertainty in calibration are very large in terms of global and regional ocean chlorophyll estimates. In fact, stability in global chlorophyll requires calibration uncertainty much greater than the goals, and outside of modern capabilities. Using a purely empirical approach, we show that stable and consistent global chlorophyll values can be achieved over very wide ranges of uncertainty. Furthermore, the approach yields statistically improved comparisons with in situ data, suggesting improved quality. The results suggest that accuracy requirements for radiometric calibration cab be reduced if alternative empirical approaches are used.

Gregg, Watson↗

Oceanographic and meteorological research based on the data products of SEASAT

De-aliased SEASAT SASS vector winds obtained during the GOASEX (Gulf of Alaska SEASAT Experiment) program were processed to obtain superobservations centered on a one degree by one degree grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. Each grid point of the synoptic field provides the mean synoptic east-west and north-south wind components plus estimates of the standard deviations of these means. These superobservations winds are then processed further to obtain synoptic scale vector winds stress fiels, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations for each grid point value. The resulting fields appear to be consistant over large distances and to agree with, for example, geostationary cloud images obtained concurrently. Their quality is far superior to that of analyses based on conventional data.

Pierson, W. J.↗

Planetary and Stellar Data Products Expected From The Kepler Mission

The Kepler Mission is a Discovery-class mission scheduled to be launched in the 2006-2007 time frame. It is a wide field of view photometer with a 95 m aperture designed to attain a photometric precision of 2 parts in 10^5 for the 12th magnitude stars. It will continually observe 100,000 main-sequence stars from 9th to 14th magnitude for a period of four years with a cadence of 4/hour. This database should be unique in its photometric precision, cadence, and duration of observations. Several hundred terrestrial-size planets will be detected if they are common around solar-like stars. Based on the current results of Doppler-velocity searches, over a thousand giant planets will also be found. A guest investigator program is planned that would provide the opportunity to observe thousands of other objects in the 105 square degree FOV. Such objects could include stars with micro-variability, other intrinsic variables, cataclysmic variables, eclipsing binaries (including x-ray binaries), and possibly AGN. A ground-based program to classify all 225,000 stars in the FOV and to do a detailed examination of a subset of the stars that show planetary companions is planned. Doppler-velocity observations will be made to find the presence of giant planets not seen in transit. The data will be rapidly released to the community for follow up observations and for changes to the guest investigator program.

Borucki, W. J.↗

Advanced Precipitation and Boundary Layer Data Products Derived from ARM Radar Wind Profilers

This research project was successful in delivering on four main objectives. First, software was developed to accurately calculate 915-MHz radar wind profiler (RWP) spectrum moments from the recorded Doppler velocity power spectra. Second, software was developed to calibrate the RWP reflectivity factor using collocated surface disdrometer observations. Third, the Python processing code was documented and given to the ARM Infrastructure to produce ARM ‘b level’ calibrated RWP products. Fourth, calibrated RWP products were uploaded to the ARM Archive as PI Products for 10 years of SGP RWP observations and for GoAmazon and TRACER field campaign RWP observations. In addition to working with RWP observations, this research project also worked with KAZR observations to distinguish insects from boundary layer clouds to help improve the ARSCL cloud mask product. The PI worked with senior and early career ARM funded scientists at BNL exploring how to include calibrated RWP moments into future versions of the ARSCL product.

54 ENVIRONMENTAL SCIENCES↗

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗

TRMM-based Merged Data Products Compared to Global Precipitation Climatology Project (GPCP) Analyses

This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) (launched in November 1997) information as the key calibration tool; in a merged analysis on a 1 degree x l degree latitude/longitude monthly scale based on multiple satellite sources and raingauge analyses. The TRMM-based product will be compared with the community-based Global Precipitation Climatology Project (GPCP) results. The long-term GPCP analysis is compared to the new TRMM-based analysis which uses the most accurate TRMM information to calibrate the estimates from the Special Sensor Microwave/Imager (SSM/I) and geosynchronous IR observations and merges those estimates together with the TRMM and gauge information to produce accurate rainfall estimates with the increased sampling provided by the combined satellite information. The comparison with TRMM results on a month-to-month basis should clarify the strengths and weaknesses of the long-term GPCP product in the tropics and point to how to improve the monitoring analysis. Preliminary results from the TRMM merged satellite analysis indicates close agreement with the GPCP estimates. By the time of the meeting over a year of TRMM products will be available for comparison. Global tropical and regional values will be compared. Seasonal variations, and variations associated with the 1998 El Nino/Southern Oscillation ENSO event will be examined and compared between the two analyses. These variations will be examined carefully and validated where possible from surface-based radar and gauge observations. The role of TRMM observations in the refinement of the long-term monitoring product will be outlined.

Adler, Robert F.↗

Coherent Doppler Lidar Data Products from Space-Based Platforms

Coherent Doppler lidar is a promising technique for the global measurements of winds using a space-based platform. Doppler lidar produces estimates of the radial component of the velocity vector averaged over the resolution volume of the measurement. Profiles of the horizontal vector winds are produced by scanning the lidar beam or stepping the lidar beam through a sequence of different angles (step-stare). The first design for space-based measurements proposed a conical scan which requires a high power laser to produce acceptable signal levels for every laser pulse. Performance is improved by fixing the laser beam and accumulating the signal from many lidar pulses for each range-gate. This also improves the spatial averaging of the wind estimates and reduces the threshold signal energy required for a good estimate. Coherent Doppler lidar performance for space-based operation is determined using computer simulations and including the wind variability over the measurement volume as well as the variations of the atmospheric aerosol backscatter.

Frehlich, Rod↗

Validation of Ocean Color Satellite Data Products in Under Sampled Marine Areas

The planktonic marine cyanobacterium, Trichodesmium sp., is broadly distributed throughout the oligotrophic marine tropical and sub-tropical oceans. Trichodesmium, which typically occurs in macroscopic bundles or colonies, is noteworthy for its ability to form large surface aggregations and to fix dinitrogen gas. The latter is important because primary production supported by N2 fixation can result in a net export of carbon from the surface waters to deep ocean and may therefore play a significant role in the global carbon cycle. However, information on the distribution and density of Trichodesmium from shipboard measurements through the oligotrophic oceans is very sparse. Such estimates are required to quantitatively estimate total global rates of N2 fixation. As a result current global rate estimates are highly uncertain. Thus in order to understand the broader biogeochemical importance of Trichodesmium and N2 fixation in the oceans, we need better methods to estimate the global temporal and spatial variability of this organism. One approach that holds great promise is satellite remote sensing. Satellite ocean color sensors are ideal instruments for estimating global phytoplankton biomass, especially that due to episodic blooms, because they provide relatively high frequency synoptic information over large areas. Trichodesmium has a combination of specific ultrastructural and biochemical features that lend themselves to identification of this organism by remote sensing. Specifically, these features are high backscatter due to the presence of gas vesicles, and absorption and fluorescence of phycoerythrin. The resulting optical signature is relatively unique and should be detectable with satellite ocean color sensors such as the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS).

Subramaniam, Ajit↗

Evaluation of NASA Data Products for RPO Applications

This presentation summarizes preliminary investigations at SSC by NASA's ASD in Air Quality including decision support tools, partner plans, working groups, and committees. An overview of follow-on short-term and long-term objectives is also provided. A table of potential NASA sensors for use with air quality applications is included, along with specifications for MODIS 04 and 06 products. This presentation was originally given by Rich Piorot of the Vermont Department of Environmental Conservation - Air Quality as part of a round-table discussion during "Exploring Collaborative Opportunities in Air Quality Monitoring, Modelling and Communication Workshop" in Boulder, CO, on March 21-22, 2005; verbal consent for this presentation to be provided to Mr. Piorot was given by the NASA SSC ASD Air Quality Program Manager on March 14, 2005.

Frisbie, Troy↗