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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Remote sounding of the tropical cirrus cloud temperature and optical depth using 6.5 and 10.5-micron radiometers during STEP

A dual-channel retrieval technique involving the water vapor band at 6.5 microns and the window region at 10.5 microns has been developed to infer the temperature and emissivity of tropical anvils. This technique has been applied to data obtained from the ER-2 narrow field-of-view radiometers during two flights in the field observation of the Stratosphere-Troposphere Exchange Project near Darwin, Australia, January-February 1987. The retrieved cloud temperatures are between 190 and 240 K, while the cloud emissivities derived from the retrieval algorithm range from about 0.2 to 1. Moreover, the visible optical depths have been obtained from the cloud emissivity through a theoretical parameterization with values of 0.5-10. A significant portion of tropical cirrus clouds are found to have optical depths greater than about 6. Because of the parameterization, the present technique is unable to precisely determine the optical depth values for optically thick cirrus clouds.

Liou, K. N.↗
NASA NTRS2007

Cloud Optical Depth Retrievals from Solar Background "signal" of Micropulse Lidars

Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10-15% for overcast stratus and broken clouds. In fact, for broken cloud situations one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

Chiu, J. Christine↗
NASA NTRS1989

Diurnal variations in optical depth at Mars

Viking lander camera images of the Sun were used to compute atmospheric optical depth at two sites over a period of 1 to 1/3 martian years. The complete set of 1044 optical depth determinations is presented in graphical and tabular form. Error estimates are presented in detail. Otpical depths in the morning (AM) are generally larger than in the afternoon (PM). The AM-PM differences are ascribed to condensation of water vapor into atmospheric ice aerosols at night and their evaporation in midday. A smoothed time series of these differences shows several seasonal peaks. These are simulated using a one-dimensional radiative convective model which predicts martial atmospheric temperature profiles. A calculation combinig these profiles with water vapor measurements from the Mars Atmospheric Water Detector is used to predict when the diurnal variations of water condensation should occur. The model reproduces a majority of the observed peaks and shows the factors influencing the process. Diurnal variation of condensation is shown to peak when the latitude and season combine to warm the atmosphere to the optimum temperature, cool enough to condense vapor at night and warm enough to cause evaporation at midday.

Colburn, D. S.↗
NASA NTRS2022

Quantifying and Reducing Uncertainty in Microwave Vegetation Optical Depth and Soil Moisture Retrievals

Soil moisture and vegetation optical depth (VOD; related to vegetation water content) retrieved from SMAP and SMOS satellites are widely used for a range of hydrosphere and biosphere applications. However, while soil moisture has been globally well-validated, VOD validation has been sparse. Furthermore, simultaneously retrieval of these parameters results in uncertainties both individually in soil moisture and VOD retrievals as well as in compensation between the parameters. Here, we show global locations where soil moisture and VOD retrievals will have lower uncertainty, based on complementary brightness temperature information content and signal-to-noise ratio metrics. In these same locations, we show that error still propagates more into VOD. However, using VOD regularization algorithms, this error is greatly reduced, especially at sub-weekly timescales where algorithmic error can be most apparent. Despite these regularization approaches that reduce errors, there are yet vast differences in available global regularized retrievals originating from different algorithmic choices.

Passive microwave radiometry↗
NASA NTRS2016

Aerosol Optical Depth Distribution in Extratropical Cyclones over the Northern Hemisphere Oceans

Using Moderate Resolution Imaging Spectroradiometer and an extratropical cyclone database,the climatological distribution of aerosol optical depth (AOD) in extratropical cyclones is explored based solely on observations. Cyclone-centered composites of aerosol optical depth are constructed for the Northern Hemisphere mid-latitude ocean regions, and their seasonal variations are examined. These composites are found to be qualitatively stable when the impact of clouds and surface insolation or brightness is tested. The larger AODs occur in spring and summer and are preferentially found in the warm frontal and in the post-cold frontal regions in all seasons. The fine mode aerosols dominate the cold sector AODs, but the coarse mode aerosols display large AODs in the warm sector. These differences between the aerosol modes are related to the varying source regions of the aerosols and could potentially have different impacts on cloud and precipitation within the cyclones.

MODIS↗
NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗
NASA NTRS1999

Global and Seasonal Aerosol Optical Depths Derived From Ultraviolet Observations by Satellites (TOMS)

It has been shown that absorbing aerosols (dust, smoke, volcanic ash) can be detected in the ultraviolet wavelengths (331 nm to 380 nm) from satellite observations (TOMS, Total Ozone Mapping Spectrometer) over both land and water. The theoretical basis for these observations and their conversions to optical depths is discussed in terms of an aerosol index AI or N-value residue (assigned positive for absorbing aerosols). The theoretical considerations show that negative values of the AI frequently represent the presence of non-absorbing aerosols (NA) in the troposphere (mostly pollution in the form of sulfates, hydrocarbons, etc., and some natural sulfate aerosols) with particle sizes near 0.1 to 0.2 microns or less. The detection of small-particle non-absorbing aerosols from the measured backscattered radiances is based on the observed wavelength dependence from Mie scattering after the background Rayleigh scattering is subtracted. The Mie scattering from larger particles, 1 micron or more (e.g., cloud water droplets) has too small a wavelength dependence to be detected by this method. In regions that are mostly cloud free, aerosols of all sizes can be seen in the single channel 380 nm or 360 nm radiance data. The most prominent Al feature observed is the strong asymmetry in aerosol amount between the Northern and Southern Hemispheres, with the large majority of NA occurring above 20degN latitude. The maximum values of non-absorbing aerosols are observed over the eastern U.S. and most of western Europe corresponding to the areas of highest industrial pollution. Annual cycles in the amount of NA are observed over Europe and North America with maxima occurring in the summer corresponding to times of minimum wind transport. Similarly, the maxima in the winter over the Atlantic Ocean occurs because of wind borne transport from the land. Most regions of the world have the maximum amount of non-absorbing aerosol in the December to January period except for the eastern North America and Europe. Comparisons of the estimated TOMS aerosol optical depths show good agreement in magnitude and seasonal dependence with sun-photometer optical depths obtained at Goddard Space Flight Center (39degN 76.88degW) in the U.S. and in Lille (50.63degN 3.07degE) in France. The study of these aerosols is important for detecting the sources of industrial pollution and its redistribution by winds on a global basis, as well as its effect on reducing the UV irradiance at the Earth's surface.

Herman, J. R.↗
NASA NTRS2022

Developing Data-Driven Artificial Neural Network for A High Throughput Retrieval of Aerosol Optical Depth and Surface Temperature of Mars

In this work, we aim to developartificial neural network(ANN)techniquesto reproduce the retrieval results ofphysical quantities from spacecraft observations of solar system bodiesusing radiative transfer methods. The particular application here is the retrieval of dust optical depth, water-ice optical depth, and surface temperatureonMarsusingdaytime observationsobtained by the Thermal Emission Spectrometer (TES) onboard the Mars Global Surveyor.Compared against the results obtained from traditional radiative transfer retrieval techniques, our ANN successfully recoveredthe three quantitiesusingdaytime observations. The principal advantage of thesemachine learning(ML) algorithms istheir complete automation and highthroughput. Therefore, the algorithms presented here would be useful for very large datasets andwould make practical the sampling of many different approximations or boundary conditions related to a given observation dataset and retrieval problem.

Rafael Moreno↗
NASA NTRS2020

Assimilation of Vegetation Optical Depth Retrievals from Passive Microwave Radiometry

Vegetation optical depth (VOD) retrievals from passive microwave sensors provide analog estimates of above-ground canopy biomass. This study presents the development and analysis of assimilating VOD retrievals from X-, C-, and L-band passive microwave instruments within the Noah-MP land surface model over the Continental U.S. The results from this study demonstrate that the assimilation of VOD retrievals have a significant beneficial impact on the simulation of evapotranspiration and GPP, particularly over the agricultural areas of the U.S. The improvements in the water and carbon fluxes from the assimilation of VOD from X- and C-band sensors are found to be comparable to those obtained from the assimilation of vegetation indices from optical sensors.The study also quantifies the relative and joint impact of assimilating surface soil moisture and VOD from the Soil Moisture Active Passive (SMAP) mission. The utility of soil moisture assimilation for improving ET is more significant over water-limited regions, whereas VOD DA is more impactful over areas where soil moisture is not the primary controlling factor on ET. The results also indicate that the information on moisture and vegetation states from SMAP can be simultaneously exploited through the joint assimilation of surface soil moisture and VOD. Since passive microwave-based VOD retrievals are available in nearly all weather conditions, their use within data assimilation systems offers the ability to extend and improve the utility obtained from the use of optical/infrared based vegetation retrievals

Sujay V Kumar↗
NASA NTRS2010

Contrails of Small and Very Large Optical Depth

This work deals with two kinds of contrails. The first comprises a large number of optically thin contrails near the tropopause. They are mapped geographically using a lidar to obtain their height and a camera to obtain azimuth and elevation. These high-resolution maps provide the local contrail geometry and the amount of optically clear atmosphere. The second kind is a single trail of unprecedentedly large optical thickness that occurs at a lower height. The latter was observed fortuitously when an aircraft moving along the wind direction passed over the lidar, thus providing measurements for more than 3 h and an equivalent distance of 620 km. It was also observed by Geostationary Operational Environmental Satellite (GOES) sensors. The lidar measured an optical depth of 2.3. The corresponding extinction coefficient of 0.023 per kilometer and ice water content of 0.063 grams per cubic meter are close to the maximum values found for midlatitude cirrus. The associated large radar reflectivity compares to that measured by ultrasensitive radar, thus providing support for the reality of the large optical depth.

Atlas, David↗
NASA NTRS1999

Regional Aerosol Optical Depth Characteristics from Satellite Observations: ACE-1, TARFOX and ACE-2 Results

Analysis of the aerosol properties during 3 recent international field campaigns ACE-1, TARFOX and ACE-2 are described using satellite retrievals from NOAA AVHRR data. Validation of the satellite retrieval procedure is performed with airborne, shipboard, and land-based sunphotometry during ACE-2. The intercomparison between satellite and surface optical depths has a correlation coefficient of 0.93 for 630 nm wavelength and 0.92 for 860 nm wavelength, The standard error of estimate is 0.025 for 630 nm wavelength and 0.023 for 860 nm wavelength. Regional aerosol properties are examined in composite analysis of aerosol optical properties from the ACE-1, TARFOX and ACE-2 regions. ACE-1 and ACE-2 regions have strong modes in the distribution of optical depth around 0.1, but the ACE-2 tails toward higher values yielding an average of 0.16 consistent with pollution and dust aerosol intrusions. The TARFOX region has a noticeable mode of 0.2, but has significant spread of aerosol optical depth values consistent with the varied continental aerosol constituents off the eastern North American Coast.

Durkee, P. A.↗
NASA NTRS2013

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 μm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

cirrus correction↗
NASA NTRS2001

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Owe, Manfred↗
NASA NTRS2018

Correcting for Trace Gas Absorption When Retrieving Aerosol Optical Depth from Satellite Observations of Reflected Shortwave Radiation

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard Suomi-NPP) sensors, use wavelength bands in "window" regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper we use High-resolution TRANsmission (HITRAN) database and Line-by-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are "similar", they are different enough that applying MODIS specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.

Satellite Remote Sensing↗
NASA NTRS2024

Retrievals of Aerosol Optical Depth Over the Western North Atlantic Ocean During ACTIVATE

Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near the surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidars and polarimeters for future airborne and satellite missions.

Aerosol optical depth↗
NASA NTRS2003

Optical Depth Retrievals from HRSC Stereo Images

Mars Express is due to arrive in orbit around Mars during the last days of 2003. A primary task of its mission is to map Mars in stereo with the High Resolution Stereo Camera (HRSC) at a spatial resolution of up to 12 m. The Martian atmosphere contains large amounts of dust and other aerosols that scatter light and influence the images. Therefore, image analysis requires careful consideration of these atmospheric effects. An essential parameter to consider is the optical depth. It will be possible to map the optical depth of the Martian atmosphere from HRSC stereo images by analyzing contrast differences. Software to this purpose has been developed at the Max-Planck Institute for Aeronomy in Lindau Germany. We present examples of optical depth-retrievals from airborne HRSC-A images of a region in the French Alps.

N M Hoekzema↗
NASA NTRS2012

Retrieval of Aerosol Optical Depth Above Clouds from OMI Observations: Sensitivity Analysis, Case Studies

A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originated in arid and semi-arid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth atmosphere system is especially important. The generally negative (cooling) top of the atmosphere direct effect of absorbing aerosols, may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. In this paper we discuss the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol-cloud separation. The technique was applied to above-cloud aerosol events over the Southern Atlantic Ocean yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value.

Torres, O.↗