Liam E. Gumley

Discriminating clear sky from clouds with MODIS

The MODIS cloud mask uses several cloud detection tests to indicate a level of confidence that the MEDIS is observing clear skies. It will be produced globally at single-pixel resolution; the algorithm uses as many as 14 of the MEDIS 36 spectral bands to maximize reliable cloud detection and to mitigate past difficulties experienced by sensors with coarser spatial resolution or fewer spectral bands. The MEDIS cloud mask is ancillary input to MEDIS land, ocean, and atmosphere science algorithms to suggest processing options. The MEDIS cloud mask algorithm will operate in near real time in a limited computer processing and storage facility with simple easy-to-follow algorithm paths. The MEDIS cloud mask algorithm identifies several conceptual domains according to surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. Once a pixel has been assigned to a particular domain (defining an algorithm path), a series of threshold tests attempts to detect the presence of clouds in the instrument field of view. Each cloud detection test returns a confidence level that the pixel is clear ranging in value from 1 (high) to zero (low). There are several types of tests, where detection of different cloud conditions relies on different tests. Tests capable of detecting similar cloud conditions are grouped together. While these groups are arranged so that independence between them is maximized, few, if any, spectral tests are completely independent. The minimum confidence from all tests within a group is taken to be representative of that group. These confidences indicate absence of particular cloud types. The product of all the group confidences is used to determine the confidence of finding clear-sky conditions. This paper outlines the MEDIS cloud masking algorithm. While no present sensor has all of the spectral bands necessary for testing the complete MEDIS cloud mask, initial validation of some of the individual cloud tests is presented using existing remote sensing data sets.

IMPROVING NATIONAL AIR QUALITY FORECASTS WITH SATELLITE AEROSOL OBSERVATIONS

Accurate air quality forecasts can allow for mitigation of the health risks associated with high levels of air pollution. During September 2003, a team of NASA, NOAA, and EPA researchers demonstrated a prototype tool for improving fine particulate matter (PM2.5) air quality forecasts using satellite aerosol observations. Daily forecast products were generated from a near-real-time fusion of multiple input data products, including aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS)/Earth Observing System (EOS) instrument on the NASA Terra satellite, PM2.5 concentration from over 300 state/local/national surface monitoring stations, meteorological fields from the NOAA/NCEP Eta Model, and fire locations from the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) product. The products were disseminated via a Web interface to a small g...

Airborne Scanning Spectrometer for Remote Sensing of Cloud, Aerosol, Water Vapor, and Surface Properties

An airborne scanning spectrometer was developed for measuring reflected solar and emitted thermal radiation in 50 narrowband channels between 0.55 and 14.2mm. The instrument provides multispectral images of outgoing radiation for purposes of developing and validating algorithms for the remote sensing of cloud, aerosol, water vapor, and surface properties from space. The spectrometer scans a swath width of 37 km, perpendicular to the aircraft flight track, with a 2.5-mrad instantaneous field of view. Images are thereby produced with a spatial resolution of 50 m at nadir from a nominal aircraft altitude of 20 km. Nineteen of the spectral bands correspond closely to comparable bands on the Moderate Resolution Imaging Spectroradiometer ( MODIS ) , a facility in- strument being developed for the Earth Observing System to be launched in the late 1990s. This paper describes the optical, mechanical, electrical, and data acquisition system design of the MODIS Airborne Simulator and presents some early results obtained from measurements acquired aboard the National Aeronautics and Space Administration ER-2 aircraft that illustrate the performance and quality of the data produced by this instrument.

MODIS Global Cloud-Top Pressure and Amount Estimation: Algorithm Description and Results

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua platforms provides unique measurements for deriving global and regional cloud properties. MODIS has spectral coverage combined with spatial resolution in key atmospheric bands, which is not available on previous imagers and sounders. This increased spectral coverage/spatial resolution, along with improved onboard calibration, enhances the capability for global cloud property retrievals. MODIS operational cloud products are derived globally at spatial resolutions of 5 km (referred to as level-2 products) and are aggregated to a 1° equal-angle grid (referred to as level-3 product), available for daily, 8-day, and monthly time periods. The MODIS cloud algorithm produces cloud-top pressures that are found to be within 50 hPa of lidar determinations in single-layer cloud situations. In multilayer clouds, where the upper-layer cloud is semitransparent, the MODIS cloud pressure is representa...

Simultaneous retrieval of atmospheric profiles, land-surface temperature, and surface emissivity from Moderate-Resolution Imaging Spectroradiometer thermal infrared data: extension of a two-step physical algorithm

An extension to the two-step physical retrieval algorithm was developed. Combined clear-sky multitemporal and multispectral observations were used to retrieve the atmospheric temperature-humidity profile, land-surface temperature, and surface emissivities in the midwave (3-5 microns) and long-wave (8-14.5 microns) regions. The extended algorithm was tested with both simulated and real data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator. A sensitivity study and error analysis demonstrate that retrieval performance is improved by the extended algorithm. The extended algorithm is relatively insensitive to the uncertainties simulated for the real observations. The extended algorithm was also applied to real MODIS daytime and nighttime observations and showed that it is capable of retrieving medium-scale atmospheric temperature water vapor and retrieving surface temperature emissivity with retrieval accuracy similar to that achieved by the Geostationary Operational Environmental Satellite (GOES) but at a spatial resolution higher than that of GOES.

Remote Sensing of Flooding in the U.S. Upper Midwest during the Summer of 1993

Abstract The U.S. upper Midwest was subjected to severe flooding during the summer of 1993. Heavy rainfall in the Mississippi River basin from April through July caused flooding of many Midwest rivers, including the Mississippi, Illinois, Missouri, and Kansas Rivers. The flood crest of 15.1 m at St. Louis, Missouri on 1 August 1993 was the highest ever measured, surpassing the previous record of 13.2 m set on 28 April 1973. Damage estimates include at least 47 flood-related deaths and a total damage cost of

Blackbody emissivity considerations for radiometric calibration of the MODIS Airborne Simulator (MAS) thermal channels

12 billion. Remotely sensed imagery of severe flooding in the U.S. Midwest was obtained under cloud-free skies on 29 July 1993 by the MODIS (Moderate Resolution Imaging Spectroradiometer) Airborne Simulator (MAS). The MAS is newly developed scanning spectrometer with 50 spectral bands in the wavelength range 0.55–14.3 μm. By combining spectral bands centered at 2.14, 0.94, and 0.66 μm in red, green, and blue display channels, respectively, false color images were created from the MAS data obtained on ...

Analysis of air quality variability in Shanghai using AOD and API data in the recent decade

The impact of non-unit calibration blackbody emissivity on MODIS airborne simulator (MAS) absolute thermal calibration accuracy is investigated. Estimates of blackbody effective emissivity were produced for MAS infrared channels using laboratory observations of a thermally controlled external source in a stable ambient environment. Results are consistent for spectrally close atmospheric window channels. SWIR channels show an effective emissivity of about 0.98; LWIR channels show an effective emissivity of about 0.94. Using non-unit blackbody effective emissivity reduces MAS warm scene brightness temperatures by about 1 degree Celsius and increases cold scene brightness temperatures by more than 5 degrees Celsius as compared to those inferred from assuming a unit emissivity blackbody. To test the MAS non- unit effective emissivity calibration, MAS and high- resolution interferometer sounder (HIS) LWIR data from a January 1995 ER-2 flight over the Gulf of Mexico were compared. Results show that including MAS blackbody effective emissivity decreases LWIR absolute calibration biases between the instruments to less than 0.5 degrees Celsius for all scene temperatures, and removes scene temperature dependence from the bias.

Introducing HYDRA: A Multispectral Data Analysis Toolkit

We use the aerosol optical depth (AOD) measured by the moderate resolution imaging spectrometer (MODIS) onboard the Terra satellite, air pollution index (API) daily data measured by the Shanghai Environmental Monitoring Center (SEMC), and the ensemble empirical mode decomposition (EEMD) method to analyze the air quality variability in Shanghai in the recent decade. The results indicate that a trend with amplitude of 1.0 is a dominant component for the AOD variability in the recent decade. During the World Expo 2010, the average AOD level reduced 30% in comparison to the long-term trend. Two dominant annual components decreased 80% and 100%. This implies that the air quality in Shanghai was remarkably improved, and environmental initiatives and comprehensive actions for reducing air pollution are effective. AOD and API variability analysis results indicate that semi-annual and annual signals are dominant components implying that the monsoon weather is a dominant factor in modulating the AOD and API variability. The variability of AOD and API in selected districts located in both downtown and suburban areas shows similar trends; i.e., in 2000 the AOD began a monotonic increase, reached the maxima around 2006, then monotonically decreased to 2011 and from around 2006 the API started to decrease till 2011. This indicates that the air quality in the entire Shanghai area, whether urban or suburban areas, has remarkably been improved. The AOD improved degrees (IDS) in all the selected districts are (8.6±1.9)%, and API IDS are (9.2±7.1)%, ranging from a minimum value of 1.5% for Putuo District to a maximum value of 22% for Xuhui District.

Status and calibration of the MODIS airborne simulator for earth remote sensing applications

A freeware-based multispectral data analysis tool kit for satellite data has been developed to assist research and development of remote-sensing applications as well as education and training of remote-sensing scientists; it is called HYDRA—HYper-spectral data viewer for Development of Research Applications. HYDRA provides a fast and flexible interface that allows users to explore and visualize relationships between radiances (or reflectances and brightness temperatures) and wavelength (or wavenumber) using spectra diagrams, cross sections, scatter plots, multichannel combinations, and color enhancements on a pixel-by-pixel basis with full access to the underlying metadata of location and time. HYDRA enables interrogation of multispectral (and hyperspectral) fields of data so that a) pixel location and spectral measurement values can be easily displayed; b) spectral channels can be combined in linear functions and the resulting images displayed; c) false color images can be constructed from multiple chann...