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At least 91 records · Page 5

10 Yr Spatial and Temporal Trends of PM2.5 Concentrations in the Southeastern US Estimated Using High-resolution Satellite Data

Long-term PM2.5 exposure has been reported to be associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of the true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of spatiotemporally continuous distribution of PM2.5 concentrations are essential. Satellite-retrieved aerosol optical depth (AOD) has been widely used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, an inherent disadvantage of current AOD products is their coarse spatial resolutions. For instance, the spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) are 10 km and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5-AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US, centered at the Atlanta Metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted for each year individually, and we obtained model fitting R2 ranging from 0.71 to 0.85, MPE from 1.73 to 2.50 g m3, and RMSPE from 2.75 to 4.10 g m3. In addition, we found cross validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 g m3, and RMSPE from 3.12 to 5.00 g m3, indicating a good agreement between the estimated and observed values. Spatial trends show that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. A time series analysis was conducted to examine temporal trends of PM2.5 concentrations in the study area from 2001 to 2010. The results showed that the PM2.5 levels in the study area followed a generally declining trend from 2001 to 2010 and decreased about 20 during the period. However, there was an exception of an increase in year 2005, which is attributed to elevated sulfate concentrations in the study area in warm months of 2005. An investigation of the impact of wild and prescribed fires on PM2.5 levels in 2007 suggests a positive relationship between them.

particulate matter (PM2.5)↗

Using Supra-Arcade Downflows as Probes of Electron Acceleration During Solar Flares

Extracting information from coronal features above flares has become more reliable with the availability of increasingly higher spatial and temporal-resolution data in recent decades. We are now able to sufficiently probe the region high above long-duration flaring active regions where reconnection is expected to be continually occurring. Flows in the supra-arcade region, first observed with Yohkoh/SXT, have been theorized to be associated with newly-reconnected outflowing loops. High resolution data appears to confirm these assertions. Assuming that these flows are indeed reconnection outflows, then the detection of those directed toward the solar surface (i.e. downflowing) should be associated with particle acceleration between the current sheet and the loop footpoints rooted in the chromosphere. RHESSI observations of highly energetic particles with respect to downflow detections could potentially constrain electron acceleration models. I will discuss measurements of these supra-arcade downflows (SADs) in relation to reconnection model parameters and present preliminary findings comparing the downflow timings with high-energy RHESSI lightcurves.

Savage, Sabrina L.↗

Using Supra-Arcade Downflows as Probes of Particle Acceleration in Solar Flares

Extracting information from coronal features above flares has become more reliable with the availability of increasingly higher spatial- and temporal-resolution data in recent decades. We are now able to sufficiently probe the region high above long-duration flaring active regions where reconnection is expected to be continually occurring. Flows in the supra-arcade region, first observed with Yohkoh/SXT, have been theorized to be associated with newly-reconnected outflowing loops. High resolution data appears to confirm these assertions. Assuming that these flows are indeed reconnection outflows, then the detection of those directed toward the solar surface (i.e. downflowing) should be associated with particle acceleration between the current sheet and the loop footpoints rooted in the chromosphere. RHESSI observations of highly energetic particles with respect to downflow detections could potentially constrain electron acceleration models. We provide measurements of these supra-arcade downflows (SADs) in relation to reconnection model parameters and present preliminary findings comparing the downflow timings with high-energy RHESSI lightcurves.

Savage, Sabrina↗

Performance of two texture-based classifiers of cloud fields using spatially averaged Landsat data

Using the gray-level difference vector approach, classification accuracies with 1/8-km spatial-resolution data are similar to those obtained using the full spatial-resolution features. Hence no advantage is to be gained in cloud classification accuracies by using even higher spatial resolutions obtained from Landsat TM or SPOT imagery. The optimum spatial resolution is 1/4 km. However, significant improvement in cloud-classification accuracy compared to that available from the 1-km resolution of AVHRR and GOES imagery is obtained using 1/2-km-resolution data. Cirrus-classification accuracy is especially compromised as spatial resolution is degraded. However, texture measures defined at the combination of pixel separations d = 1,4 improve classification accuracies by several percent, even for 1-km spatial-resolution data. Cirrus-classification accuracy is significantly improved by the use of multiple distance features.

Sengupta, S. K.↗

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.

Menzel, W. Paul↗

Summary of results and conclusions based on analysis of volume imaging and high spectral resolution lidar data acquired during FIRE phase 1, part 1

The collection of long term global statistics on cloud cover may be most easily accomplished with satellite based observations; however, measurements derived from passive satellite retrieval methods must be calibrated and verified by in situ or ground based remote sensor observations. Verification is not straight forward, however, because the highly variable nature of cloud altitude, morphology, and optical characteristics complicates the scaling of point measurements to satellite footprint sized areas. This is particularly evident for cirrus clouds which may be organized on horizontal scales of 10's of meters to 8 km or more, and have optical depths ranging from less than .003 to greater than 3. Cirrus clouds can strongly influence earths' radiative balance, but, because they are often transmissive, cirrus clouds are difficult to detect and characterize from satellite measurements. Because of its precise ranging capabilities, spatial resolution and sensitivity, lidar observations have played an important role in the detection, depiction, and characterization of cirrus clouds. Some of the characteristics of cirrus clouds are summarized which observed the High Spectral Resolution and Volume Imaging Lidars during the phase 1 IFO and ETO periods.

Grund, Christian J.↗

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

Sadowski, F. E.↗

Residual Strahls in Solar Wind Electron Dropouts: Signatures of Magnetic Connection to the Sun, Disconnection, or Interchange Reconnection?

A recent assessment of suprathermal electron heat flux dropouts (HFDs) in the solar wind eliminated 90% as possible signatures of field lines disconnected from the Sun at both ends (Pagel et al., 2005b). The primary reason for elimination was the presence of a residual field-aligned strahl presumably signaling field lines connected to the Sun. Using high-time-resolution data from the Wind spacecraft, this paper tests whether the residual strahls were an artifact of averaging over pitch angle distributions (PADs) with and without strahls. An automated search for PADs without strahls (flat PADs) yields an occurrence rate of only 14% within HFDs, but a detailed case study shows that these flat PADs are imbedded within intervals of nearly flat PADs, that is, PADS with residual strahls that cannot be artifacts of averaging. An attractive alternative is that the residual strahls result from intermixing of originally back-scattered fluxes (haloes) of unequal intensities on field lines that have either disconnected or interchange reconnected at the Sun. A reevaluation of reported streaming of higher-energy electrons in HFDs suggests a similar cause. While the high-time-resolution data show high variability of PAD profiles within HFDs, this paper reopens the possibility that a substantial fraction signal disconnection or interchange reconnection. Estimated occurrence rates of fields having undergone these processes based upon published HFD rates are of the same order of magnitude as the surprisingly low values of 1-5% recently predicted by a model of a balanced heliospheric flux budget (Owens and Crooker, 2007).

Crooker, N. U.↗

Earth Observations to Assess Impact of Hurricane Katrina on John C. Stennis Space Center

The peril from hurricanes to Space Operations Centers is real and is forecast to continue; Katrina, Rita, and Wilma of 2005 and Charley, Frances, Ivan, and Jeanne of 2004 are sufficient motivation for NASA to develop a multi-Center plan for preparedness and response. As was demonstrated at SSC (Stennis Space Center) in response to Hurricane Katrina, NASA Centers are efficiently activated as local command centers, playing host to Federal and State agencies and first responders to coordinate and provide evacuation, relocation, response, and recovery activities. Remote sensing decision support provides critical insight for managing NASA infrastructure and for assisting Center decision makers. Managers require geospatial information to manage the federal city. Immediately following Katrina, SSC s power and network connections were disabled, hardware was inoperative, technical staff was displaced and/or out of contact, and graphical decision support tools were non-existent or less than fully effective. Despite this circumstance, SSC EOC (Emergency Operations Center) implemented response operations to assess damage and to activate recovery plans. To assist Center Managers, the NASA ASP (Applied Sciences Program) made its archive of high-resolution data over the site available. In the weeks and months after the immediate crisis, NASA supplemented this data with high-resolution, post-Katrina imagery over SSC and much of the affected coastal areas. Much of the high-resolution imagery was made available through the Department of Defense Clear View contract and was distributed through U.S. Geological Survey Center for Earth Resources Observation and Science "Hurricane Katrina Disaster Response" Web site. By integrating multiple image data types with other information sources, ASP applied an all-source solutions approach to develop decision support tools that enabled managers to respond to critical issues, such as expedient access to infrastructure and deployment of resources, provision of temporary shelter, logistical control of critical supplies, and the mobilization and coordination of assets from ground crews to aircraft/airspace management. Furthermore, ASP developed information products that illustrate risks to SSC's infrastructure from surge, inundation, and flood. Current plans include developing wind-risk prototype products for refinement and adoption into EOC plans.

Graham, William D.↗

Analysis of high resolution satellite data for cosmic gamma ray bursts

Cosmic gamma ray bursts detected a germanium spectrometer on the low altitude satellite 1972-076B were surveyed. Several bursts with durations ranging from approximately 0.032 to 15 seconds were found and are tabulated. The frequency of occurrence/intensity distribution of these events was compared with the S to the -3/2 power curve of confirmed events. The longer duration events fall above the S to the -3/2 power curve of confirmed events, suggesting they are perhaps not all true cosmic gamma-ray bursts. The narrow duration events fall closely on the S to the -3/2 power curve. The survey also revealed several counting rate spikes, with durations comparable to confirmed gamma-ray bursts, which were shown to be of magnetospheric origin. Confirmation that energetic electrons were responsible for these bursts was achieved from analysis of all data from the complete payload of gamma-ray and energetic particle detectors on board the satellite. The analyses also revealed that the narrowness of the spikes was primarily spatial rather than temporal in character.

Imhof, W. L.↗

The use of high-resolution terrain data in gravity field prediction

Different types of gravity prediction methods for local and regional gravity evaluation are developed, tested, and compared. Four different test areas were particularly selected in view of different prediction requirements. Also different parts of the spectrum of the gravity field were considered.

Groten, E.↗

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.↗

Automated cloud base height determination from high resolution Landsat data - A Hough transform approach

A direct method for determining the cloud base height derived from the displacement of the shadow from the cloud, and the solar azimuth and zenith angle is presented. Cumulus cloud scenes over land from Landsat MSS imagery are considered. The clouds are first matched with the corresponding shadows; the pixel distance of a reference point in the cloud is computed from the corresponding reference point in the shadow; and then the solar zenith angle is used to compute the cloud base height. Observations indicate that the cloud base height appears to be size-dependent with larger clouds generally associated with higher cloud bases and that clouds within the same size range and within the same scene region are approximately of the same height.

Sengupta, S. K.↗