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Duda, David P.

Publications and source records attributed to Duda, David P..

Construction of a Matched Global Cloud and Radiance Product from LEO/GEO and EPIC Observations to Estimate Daytime Earth Radiation Budget from DSCOVR

With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can be computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and details of how data from the multi-satellite measurements are selected.

Duda, David P.

Properties of Linear Contrails Detected in 2012 Northern Hemisphere MODIS Imagery

Observation of linear contrail cirrus coverage and retrieval of their optical properties are valuable data for validating atmospheric climate models that represent contrail formation explicitly. These data can reduce our uncertainty of the regional effects of contrail-generated cirrus on global radiative forcing, and thus improve our estimation of the impact of commercial aviation on climate change. We use an automated contrail detection algorithm (CDA) to determine the coverage of linear persistent contrails over the Northern Hemisphere during 2012. The contrail detection algorithm is a modified form of the Mannstein et al. (1999) method, and uses several channels from thermal infrared MODIS data to reduce the occurrence of false positive detections. A set of contrail masks of varying sensitivity is produced to define the potential range of uncertainty in contrail coverage estimated by the CDA. Global aircraft emissions waypoint data provided by FAA allow comparison of detected contrails with commercial aircraft flight tracks. A pixel-level product based on the advected flight tracks defined by the waypoint data and U-V wind component profiles from the NASA GMAO GEOS-4 reanalysis has been developed to assign a confidence of contrail detection for the contrail mask. To account for possible contrail cirrus missed by the CDA, a post-processing method based on the assumption that pixels adjacent to detected linear contrails will have radiative signatures similar to those of the detected contrails is applied to the Northern Hemisphere data. Results from several months of MODIS observations during 2012 will be presented, representing a near-global climatology of contrail coverage. Linear contrail coverage will be compared with coverage estimates determined previously from 2006 MODIS data.

Duda, David P.

Estimating Contrail Climate Effects from Satellite Data

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Minnis, Patrick

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Duda, David P.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

Duda, David P.

The Continuous Monitoring of Desert Dust using an Infrared-based Dust Detection and Retrieval Method

Airborne dust and sand are significant aerosol sources that can impact the atmospheric and surface radiation budgets. Because airborne dust affects visibility and air quality, it is desirable to monitor the location and concentrations of this aerosol for transportation and public health. Although aerosol retrievals have been derived for many years using visible and near-infrared reflectance measurements from satellites, the detection and quantification of dust from these channels is problematic over bright surfaces, or when dust concentrations are large. In addition, aerosol retrievals from polar orbiting satellites lack the ability to monitor the progression and sources of dust storms. As a complement to current aerosol dust retrieval algorithms, multi-spectral thermal infrared (8-12 micron) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI) are used in the development of a prototype dust detection method and dust property retrieval that can monitor the progress of Saharan dust fields continuously, both night and day. The dust detection method is incorporated into the processing of CERES (Clouds and the Earth s Radiant Energy System) aerosol retrievals to produce dust property retrievals. Both MODIS (from Terra and Aqua) and SEVERI data are used to develop the method.

Duda, David P.

Contrail Tracking and ARM Data Product Development

A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.

Duda, David P.

Relating Satellite-Based Contrail Detection to NWA Output

Contrail-induced cloud cover has been shown to be a significant factor in regional climate change over the United States of America. As air traffic increases, the potential for globally significant impacts also rises. To better understand and predict these potential climatic effects, it is necessary to develop models that can accurately represent contrail properties based on ambient atmospheric variables including temperature, relative humidity and winds. Several high-resolution numerical weather analyses (NWA) including the 20-km Rapid Update Cycle (RUC) and the University of Oklahoma Center for Analysis and Prediction of Storms Advanced Regional Prediction System (ARPS) can provide the temperature, humidity and wind information necessary to diagnose contrail formation. One outstanding problem that must be addressed to achieve a realistic simulation of contrails is the large uncertainties in upper tropospheric relative humidity (UTH) in numerical weather analyses. Current numerical weather analyses tend to underestimate UTH due to large dry biases in the balloon soundings used to construct the analyses. To evaluate each of the models, we match several months of contrail properties derived from satellite and surface observations to the NWA-derived humidity, vertical velocity, wind shear and atmospheric stability. The relationships between several contrail properties (including optical depth and areal contrail coverage) and the NWA-derived statistics will be analyzed to determine under which atmospheric conditions widespread contrail outbreaks are favored.

Duda, David P.

Contrail Coverage Over the USA Derived from NOAA and EOS Satellite Data

Contrails, like natural cirrus clouds, can cause a warming of the Earth-atmospheric system by absorbing longwave radiation from the surface and lower troposphere and radiating additional radiation back to the surface. They can also produce some cooling of the surface during the daytime by reflecting some sunlight back to space. Recently, Minnis et al. (2004) determined from surface observations of cirrus cloud cover that the overall impact appears to be a warming that is consistent with theoretical calculations, at least over the United States of America (USA) and surrounding areas. This finding highlights the need to better understand the formation and persistence of contrails and their radiative properties. To better assess the climatic impact of contrails, it is essential to determine the variability of the contrail microphysical properties, their impact on the atmospheric radiation budget, and their relationship to the atmospheric state. To that end, this paper continues the analyses of Advanced Very High Resolution Radiometer (AVHRR) data from the NOAA-15 (N15), NOAA-16 (N16), and NOAA-17 (N17) satellites, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites. The combination of these satellites provides a relatively comprehensive coverage of the daily cycle of air traffic. Thus, it should be possible to use these data to help understand the impact of air traffic on the upper tropospheric humidity during the day as well as determine the local-time variability of contrail coverage. The results will be valuable for developing models of contrail effects and methods for mitigating the impact of aviation on climate.

Palikonda, Rabindra

Observations of Aircraft Dissipation Trails from GOES

Two cases of distrails (aircraft dissipation trails) with associated fall streak clouds were analyzed using multispectral geostationary satellite data. One distrail was observed on 23 July 2000 in a single cloud layer over southeastern Virginia and the Chesapeake Bay. Another set of trails developed on 6 January 2000 at the top of multilayer clouds off the coasts of Georgia and South Carolina. The distrails on both days formed in optically thin, midlevel stratified clouds with cloud-top heights between 7.6 and 9.1 km. The distrail features remained intact and easily visible from satellite images for 1-2 h in spite of winds near 50 km at cloud level. The width of the distrails spread as far as 20 km within 90 min or less. Differences between the optical properties of the clouds surrounding the trails and those of the fall streak particles inside the distrails allowed for easy identification of the fall streak clouds in either the 3.9-micrometer brightness temperature imagery, or the 10.7-micrometer - 12.0-micrometer brightness temperature difference. Although the three-channel infrared retrieval was better at retrieving cloud properties in the multilayer cloud case, two independent remote sensing retrievals of both distrail cases showed that the fall streaks had larger particle sizes than the clouds outside of the trails.

Duda, David P.

Atmospheric Multiple Scattering Effects on GLAS Altimetry: Analysis of Expected Errors in Antarctic Altitude Measurements - Part 2

The altimetry bias in GLAS (Geoscience Laser Altimeter System) or other laser altimeters resulting from atmospheric multiple scattering is studied in relationship to current knowledge of cloud properties over the Antarctic Plateau. Estimates of seasonal and interannual changes in the bias are presented. Results show the bias in altitude from multiple scattering in clouds would be a significant error source without correction. The selective use of low optical depth clouds or cloudfree observations, as well as improved analysis of the return pulse such as by the Gaussian method used here, are necessary to minimize the surface altitude errors. The magnitude of the bias is affected by variations in cloud height, cloud effective particle size and optical depth. Interannual variations in these properties as well as in cloud cover fraction could lead to significant year-to-year variations in the altitude bias. Although cloud-free observations reduce biases in surface elevation measurements from space, over Antarctica these may often include near-surface blowing snow, also a source of scattering-induced delay. With careful selection and analysis of data, laser altimetry specifications can be met.

Mahesh, Ashwin

Atmospheric Multiple Scattering Effects on GLAS Altimetry: Calculations of Single Pulse Bias - Part 1

Estimates of the effect of pulse stretching on satellite laser altimetry in particular the Geoscience Laser Altimeter System (GLAS), by cloud multiple scattering were made from an analytical method and from Monte Carlo calculations. The path delay of the return pulse was found to be largest for low-level clouds with particle radii (3-20 microns). The magnitude of the path delay was affected by several factors including cloud height, cloud optical depth, cloud particle size, particle shape, and receiver field of view. Polar aerosol and Rayleigh scattering usually added less than 1 cm to the overall path delay. Path delay estimates for all cloud conditions would be less if a simple Gaussian fit of the return pulse peak were used to measure the pulse's centroid. However, care must be taken in determining the centroid as factors such as pulse width, surface slope and the fitting method used will affect the estimate. A planned application for laser altimetry is high precision monitoring of the height change of polar ice sheets. In the absence of a correction algorithm, the required GLAS altimetry accuracies will not be achieved unless atmospheric channel information is used to remove profiles that are likely to be heavily contaminated by multiple scattering.

Duda, David P.

Calculations of multiple scattering-induced errors in the GLAS mission

The Geoscience Lidar Altimeter System (GLAS) is a laser altimeter designed to measure temporal changes in the topography and mass balance of the Earth's ice sheets. GLAS is scheduled to be launched as part of the Earth Observing System (EOS) in 2001. Due to the large pulse width of GLAS and the slope (and roughness) of the ice sheets, the mean elevation of the laser's surface spot will be estimated from the centroid of the return pulse. While the accuracy of individual altimetry measurements is expected to be 15 cm, a cross-over technique that averages the elevation differences at selected points on the ice sheets will allow GLAS to detect mean ice elevation changes as small as 2 cm per year. One factor that may degrade the proposed accuracy of the altimeter measurements is the effect of multiple scattering by thin clouds and aerosols over the ice sheets. In the return pulse, some photons from the lidar are slightly deflected by cloud particles but still return to the instrument detector. Since these photons travel a longer path than photons that pass directly to and from the surface, the mean travel time of the pulse is lengthened and the centroid of the return pulse is shifted toward a later time . This study intends to determine the importance of this source of altimetry error in the GLAS measurements. Two methods will be used to estimate path delays in the GLAS lidar for a range of cloud conditions. An analytic expression of a doubly scattered return signal (Eloranta, 1972) will be compared to Monte Carlo simulations that estimate path delays by cloud, aerosol and molecular scattering. The results from both methods will be discussed in relationship to current knowledge of Arctic cloud climatology, and the impact of multiple scattering on GLAS altimeter measurements will be evaluated.

Duda, David P.

The radiation budget of stratocumulus clouds measured by tethered balloon instrumentation: Variability of flux measurements

Measurements of longwave and shortwave radiation were made using an instrument package on the NASA tethered balloon during the FIRE Marine Stratocumulus experiment. Radiation data from two pairs of pyranometers were used to obtain vertical profiles of the near-infrared and total solar fluxes through the boundary layer, while a pair of pyrgeometers supplied measurements of the longwave fluxes in the cloud layer. The radiation observations were analyzed to determine heating rates and to measure the radiative energy budget inside the stratocumulus clouds during several tethered balloon flights. The radiation fields in the cloud layer were also simulated by a two-stream radiative transfer model, which used cloud optical properties derived from microphysical measurements and Mie scattering theory.

Duda, David P.

Analysis of tethered balloon data from San Nicolas Island on 8 July 1987

Analysis of the 8 July 1987 (Julian Day 189) tethered balloon flight from San Nicolas Island is summarized. The flight commenced at about 14:30 UTC (7:30 Pacific Daylight Time) and lasted six and one-half hours. The position of the Colorado State University (CSU) instrument package as a function of time is shown. For the purpose of presentation of results, researchers divided the flight into 13 legs. These legs consist of 20 minute constant level runs, with the exception of leg 1, which is a sounding from the surface to just above 930 mb. The laser ceilometer record of cloud base is also shown. The cloud base averaged around 970 mb during much of the flight but was more variable near the end. Before the tethered balloon flight commenced, a Communications Link Analysis and Simulation System (CLASS) sounding was released at 12:11 UTC (5:11 PDT). Temperature and moisture data below 927 mb for this sounding is shown. The sounding indicates a cloud top around 955 mb at this time.

Cox, Stephen K.