Results for “Retrieval Algorithm” — Page 29

NASA NTRS2016

A Ten-Year Global Record of Absorbing Aerosols Above Clouds from OMI's Near-UV Observations

Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes associated with the aerosol-cloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regional of the world. Contrary to the cloud-free scenario over dark surface, for which aerosols are known to produce a net cooling effect (negative radiative forcing) on climate, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud depends directly on the aerosol loading, microphysical-optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of optical depth of absorbing aerosols above clouds retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA's Aura platform. The presence of absorbing aerosols above cloud reduces the upwelling radiation reflected by cloud and produces a strong 'color ratio' effect in the near-UV region, which can be unambiguously detected in the OMI measurements. Physically based on this effect, the OMACA algorithm retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. The algorithm architecture and results from a ten-year global record including global climatology of frequency of occurrence and above-cloud aerosol optical depth, and a discussion on related future field campaigns are presented.

Ozone Monitoring Instrument↗

NASA NTRS1982

Retrieval of ocean surface and atmospheric parameters from multichannel microwave radiometric measurements

Methods for the retrieval of ocean surface temperature, surface wind speed, rain rate, cloud height, and the amounts of water vapor and nonprecipitated liquid water over the ocean from Scanning Multichannel Microwave Radiometer (SMMR) data are presented. The sensitivity of retrieval algorithms for wind speed and sea surface temperature, in the absence of rain, to the undetected presence of rain, is discussed along with the accuracy of a more general method for the retrieval of rain rate in conjunction with other meteorological parameters. It is concluded that the inability to retrieve the average rain rate accurately at small rain angles is due to the inability of SMMR to distinguish between small raindrops and nonprecipitating droplets.

Chang, A. T. C.↗

NASA NTRS1993

Effects of vertical distribution of water vapor and temperature on total column water vapor retrieval error

Results are presented of a test of the physically based total column water vapor retrieval algorithm of Wentz (1992) for sensitivity to realistic vertical distributions of temperature and water vapor. The ECMWF monthly averaged temperature and humidity fields are used to simulate the spatial pattern of systematic retrieval error of total column water vapor due to this sensitivity. The estimated systematic error is within 0.1 g/sq cm over about 70 percent of the global ocean area; systematic errors greater than 0.3 g/sq cm are expected to exist only over a few well-defined regions, about 3 percent of the global oceans, assuming that the global mean value is unbiased.

Sun, Jielun↗

NASA NTRS2014

Inter-Comparison of SMOS and Aquarius Sea Surface Salinity: Effects of the Dielectric Constant and Vicarious Calibration

Two spaceborne instruments share the scientific objective of mapping the global Sea Surface Salinity (SSS). ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometry to retrieve SSS. We find that SSS retrieved by SMOS is generally lower than SSS retrieved by Aquarius, except for very cold waters where SMOS SSS is higher overall. The spatial distribution of the differences in SSS is similar to the distribution of sea surface temperature. There are several differences in the retrieval algorithm that could explain the observed SSS differences. We assess the impact of the dielectric constant model and the ancillary sea surface salinity used by both missions for calibrating the radiometers and retrieving SSS. The differences in dielectric constant model produce differences in SSS of the order of 0.3 psu and exhibit a dependence on latitude and temperature. We use comparisons with the Argo in situ data to assess the performances of the model in various regions of the globe. Finally, the differences in the ancillary sea surface salinity products used to perform the vicarious calibration of both instruments are relatively small (0.1 psu), but not negligible considering the requirements for spaceborne remote sensing of SSS.

radiometry↗

NASA NTRS2017

Soil Moisture Retrieval with Airborne PALS Instrument over Agricultural Areas in SMAPVEX16

NASA's SMAP (Soil Moisture Active Passive) calibration and validation program revealed that the soil moisture products are experiencing difficulties in meeting the mission requirements in certain agricultural areas. Therefore, the mission organized airborne field experiments at two core validation sites to investigate these anomalies. The SMAP Validation Experiment 2016 included airborne observations with the PALS (Passive Active L-band Sensor) instrument and intensive ground sampling. The goal of the PALS measurements are to investigate the soil moisture retrieval algorithm formulation and parameterization under the varying (spatially and temporally) conditions of the agricultural domains and to obtain high resolution soil moisture maps within the SMAP pixels. In this paper the soil moisture retrieval using the PALS brightness temperature observations in SMAPVEX16 is presented.

SMAPVEX15↗

DOE OSTI2020

Metrology of Time-Domain Soft X-Ray Attosecond Pulses and Reevaluation of Pulse Durations of Three Recent Experiments

Attosecond pulses in the soft x-ray (SXR) to water-window energy region offer the tools for creating and studying target-specific localized inner-shell electrons or holes in materials, enabling monitoring or controlling charge and energy flows in a dynamic system on attosecond timescales. Recently, a number of laboratories have reported generation of continuum harmonics in the hundred-electron-volt to kilovolt region with few-cycle long-wavelength mid-infrared lasers. These harmonics have the bandwidth to support pulses with durations of a few to a few-ten attoseconds. But harmonics generated in a gas medium have attochirps that cannot be fully compensated by materials over a broad spectral range; thus, realistically what are the typical shortest attosecond pulses that one can generate? To answer this question, it is essential that the temporal attosecond pulses be accurately characterized. By reanalyzing the soft x-ray attosecond metrology reported in three recent experiments using a newly developed broadband phase retrieval algorithm, we demonstrate here that the generated attosecond pulses in the first two papers have durations of about 60 as, longer than what they have reported. Similarly, the duration from the third experiment is retrieved to be about half of the 322-as upper limit cited in that work. We also introduce the autocorrelation (AC) of the streaking spectrogram. By comparing the ACs from the experiments and from the retrieved SXR pulses, the accuracy of the retrieved results can be directly visualized. Our retrieval method is fast and accurate, and it shall provide a powerful tool for the metrology of the emerging few-ten-attosecond pulses.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1999

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

Mishchenko, Michael I.↗

NASA NTRS2008

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Petersen, Walter A.↗

NASA NTRS2014

Seasonal Parameterizations of the Tau-Omega Model Using the ComRAD Ground-Based SMAP Simulator

NASA's Soil Moisture Active Passive (SMAP) mission is scheduled for launch in November 2014. In the prelaunch time frame, the SMAP team has focused on improving retrieval algorithms for the various SMAP baseline data products. The SMAP passive-only soil moisture product depends on accurate parameterization of the tau-omega model to achieve the required accuracy in soil moisture retrieval. During a field experiment (APEX12) conducted in the summer of 2012 under dry conditions in Maryland, the Combined Radar/Radiometer (ComRAD) truck-based SMAP simulator collected active/passive microwave time series data at the SMAP incident angle of 40 degrees over corn and soybeans throughout the crop growth cycle. A similar experiment was conducted only over corn in 2002 under normal moist conditions. Data from these two experiments will be analyzed and compared to evaluate how changes in vegetation conditions throughout the growing season in both a drought and normal year can affect parameterizations in the tau-omega model for more accurate soil moisture retrieval.

SMAP↗

NASA NTRS2016

Second SNPP Cal/Val Campaign: Environmental Data Retrieval Analysis

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.

Zhou, Daniel K.↗

NASA NTRSDate not supplied

SWIPE: Spectral Water Inversion Processor and Emulator

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will be discussing the progress made developing SWIPE: Spectral Water Inversion Processor and Emulator. SWIPE is a platform for advanced modeling of coastal and inland aquatic habitats. The goal is create a comprehensive and cohesive system to leverage recent advancements in computation and machine learning to develop a synthetic training ground for sensitivity studies and algorithm development. The four principal facets of SWIPE include: 1. Advanced two-layer coated sphere bio-optical modeling and GPU radiative transfer modeling, 2. Big Data involving massive synthetic spectral libraries of optical properties of various global aquatic particles, surface reflectance, and top-of-atmosphere reflectance, all at hyperspectral resolution leveraging high-end computing systems at NASA Ames Research Center, 3. Deep Learning for algorithm development for water quality inversion of concentrations of common biogeophysical variables as well as optics, full uncertainty characterization by water type, and forward emulation, and lastly, 4. Image Processing for application of developed retrieval algorithms for both hyperspectral and multispectral sensors with experimental corrections for global adjacency, noise, sunglint, and benthic reflectance. This presentation will demonstrate the Equivalent Algal Populations (EAP) two-layer coated sphere scattering model which has been used develop spectral libraries of hyperspectral inherent optical properties of roughly 80 species of phytoplankton, covering 15 different classes and nine taxonomic functional types. The EAP model was also used to derive spectral properties of 10 different non-algal particle functional types. Examples of how the SMART-G (Speed-up Monte-carlo Advanced Radiative Transfer using GPU) radiative transfer code is used to model optically complex aquatic signals will be presented and discussed in the context of creating a massive synthetic database which can leverage the full power of next generation machine learning techniques and high end computing for water quality inversion. We will discuss our active investigation in things like appropriate model architectures, dimensionality reduction techniques such as PCA and autoencoders, uncertainty quantification and abstaining, and which variables actually benefit most from hyperspectral information versus multispectral resolution. We are also curious about questions relating to cost/benefit analysis in terms of computation resources, neural network complexity, and data volumes. Answers to these questions will hopefully elaborate on cost efficiency for potential future sensor design considerations.

SWIPE↗

DOE OSTI2023

Field Validation of Cloud Properties Sensor (SAIL Field Campaign Report)

The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Field Validation of Cloud Properties Sensor – SAIL Field Campaign Report

The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1999

Towards a Strategy of Remote Sensing of Aerosol Direct and Indirect Radiative Forcing

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. Much effort has gone into the development of new satellite sensors specifically designed to retrieve aerosol loading and some information about the sizes of the aerosols. These next generation remote sensing instruments (EOS-MODIS, EOS-MISR, POLDER, ATSR) will provide unprecedented accuracy in the retrieval of aerosol loading. Although the new generation of sensors has excellent accuracy compared to the heritage instruments of the past, they still have measurement limitations. In clean, pristine regions the absolute magnitude of the uncertainty in the aerosol retrieval becomes comparable in magnitude to the signal itself. If much of the aerosol forcing is occurring at very low magnitudes of aerosol concentrations, satellite remote sensing will miss it. This study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals. This study is not an intercomparison of global transport models. It is not an estimation of global aerosol forcing. This study is an exercise to determine whether satellite remote sensing can live up to our high expectations. The results show that while remote sensing will be able to measure a majority of the direct forcing, it will miss roughly half of the indirect forcing.

Remer, L. A.↗

NASA NTRS1999

Satellite Remote Sensing of Aerosol Forcing

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. While satellite measurements of direct aerosol forcing appear to be straightforward, satellite measurements of aerosol indirect forcing will be more complicated. Pioneering studies identified indirect aerosol forcing using AVHRR data in the biomass burning regions of Brazil. We have expanded this analysis with AVHRR to include an additional year of data and assimilated water vapor fields. The results show similar latitudinal dependence as reported by Kaufman and Fraser, but by using water vapor observations we conclude that latitude is not a proxy for water vapor and the strength of the indirect effect is not correlated to water vapor amounts. In addition to the AVHRR study we have identified indirect aerosol forcing in Brazil at much smaller spatial scales using the MODIS Airborne Simulator. The strength of the indirect effect appears to be related to cloud type and cloud dynamics. There is a suggestion that some of the cloud dynamics may be influenced by smoke destabilization of the atmospheric column. Finally, this study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals.

Remer, Lorraine↗

NASA NTRS2000

Uncertainties in Remote Sensing of Aerosol Radiative Forcing

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. Much effort has gone into the development of new satellite sensors specifically designed to retrieve aerosol loading and some information about the sizes of the aerosols. These next generation remote sensing instruments (EOS-MODIS, EOS-MISR, POLDER, ATSR) will provide unprecedented accuracy in the retrieval of aerosol loading. Although the new generation of sensors has excellent accuracy compared to the heritage instruments of the past, they still have measurement limitations. In clean, pristine regions the absolute magnitude of the uncertainty in the aerosol retrieval becomes comparable in magnitude to the signal itself. If much of the aerosol forcing is occurring at very low magnitudes of aerosol concentrations, satellite remote sensing will miss it. This study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals. This study is not an intercomparison of global transport models. It is not an estimation of global aerosol forcing. This study is an exercise to determine whether satellite remote sensing can live up to our high expectations.

Remer, L.↗

NASA NTRS1993

Estimation of solar backscatter ultraviolet albedo using ground-based Umkehr measurements

A retrieval method was developed to estimate the solar backscatter ultraviolet (SBUV) satellite albedo for the ozone profiler wavelengths using ground-based ultraviolet measurements. For the present investigation the Umkehr was used as the ground-based ultraviolet measurement. Simulated SBUV data and Umkehr data theoretically computed from a priori ozone profiles observed by the SAGE II satellite were used to develop the retrieval algorithm and to test its capability. The test indicated that albedos for the SBUV ozone profiler wavelengths should allow estimates to a precision of +/- 5 percent or better, depending on the accuracy of the ultraviolet measurement. Retrievals using actual Umkehr observations were also performed to provide a preliminary look at the magnitude and annual variation of retrieved albedos. A case study was performed, comparing retrieved albedos with SBUV-measured albedos. The SBUV albedo change was seen to be approximately twice as large as the albedo changes estimated by the Umkehr method. Results of the investigation suggest that the method of estimation may be useful for determining the drift rate of the SBUV calibration.

Deluisi, John J.↗

NASA NTRS1996

U.S. Participation in the GOME and SCIAMACHY Projects

This report summarizes research done under NASA Grant NAGW-2541 from April 1, 1996 through March 31, 1997. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, and development of infrared line-by-line atmospheric modeling and retrieval capability for SCIAMACHY. SAO also continues to participate in GOME validation studies, to the limit that can be accomplished at the present level of funding. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY is currently in instrument characterization. The first two European ozone monitoring instruments (OMI), to fly on the Metop series of operational meteorological satellites being planned by Eumetsat, have been selected to be GOME-type instruments (the first, in fact, will be the refurbished GOME flight spare). K. Chance is the U.S. member of the OMI Users Advisory Group.

Chance, K. V.↗