Journal ArticleDOI
Discriminating clear sky from clouds with MODIS
Steven A. Ackerman,Kathleen I. Strabala,W. Paul Menzel,Richard A. Frey,Christopher C. Moeller,Liam E. Gumley +5 more
Reads0
Chats0
TLDR
The MODIS cloud mask algorithm as discussed by the authors uses several cloud detection tests to indicate a level of confidence that the MEDIS is observing clear skies, which is ancillary input to MEDIS land, ocean, and atmosphere science algorithms to suggest processing options.Abstract:
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.read more
Citations
More filters
Journal ArticleDOI
A Principal Component Based Haze Masking Method for Visible Images
TL;DR: A principal component (PC)-based haze masking (PCHM) method is developed for the masking of haze in visible remote sensing images covering land surfaces at middle latitudes and the quantitative assessments verify the superiority of the proposed method over the haze optimized transformation method for the production of binary haze masks.
Journal ArticleDOI
1.5 years of TROPOMI CO measurements: Comparisons to MOPITT and ATom
Sara Martínez-Alonso,Merritt N. Deeter,Helen M. Worden,Tobias Borsdorff,Ilse Aben,Roisin Commane,Bruce C. Daube,Gene Francis,Maya George,Jochen Landgraf,D. Mao,Kathryn McKain,Kathryn McKain,Steven C. Wofsy +13 more
TL;DR: The authors analyzed TROPOspheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data acquired between November 2017 and March 2019 with respect to other satellite (MOPITT, Measurement Of Pollution In The Troposphere) and airborne (ATom, Atmospheric Tomography mission) datasets.
Journal ArticleDOI
On the response of MODIS cloud coverage to global mean surface air temperature
TL;DR: In this article, the ΔTs-mediated cloud cover response for different cloud types by linearly regressing the monthly anomaly of cloud cover (ΔC) with the monthly anomalies of global Ts is analyzed.
Journal ArticleDOI
The influence of local oil exploration and regional wildfires on summer 2015 aerosol over the North Slope of Alaska
Jessie M. Creamean,Maximilian Maahn,Gijs de Boer,Allison McComiskey,Arthur J. Sedlacek,Yan Feng +5 more
TL;DR: In this article, the authors report on airborne observations from the US Department of Energy Atmospheric Radiation Measurement (ARM) program's Fifth Airborne Carbon Measurements (ACME-V) field campaign along the North Slope of Alaska during the summer of 2015.
References
More filters
Journal ArticleDOI
Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data
TL;DR: The SNOMAP algorithm as discussed by the authors was developed to map global snow cover using Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning at launch in 1998.
Journal ArticleDOI
Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS)
TL;DR: The authors describe the status ofMODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning spectrometer with 32 uniformly spaced channels between 0.410 and 0.875 mu m, used for determining the total precipitable water vapor and atmospheric stability.
Journal ArticleDOI
An improved method for detecting clear sky and cloudy radiances from AVHRR data
R. W. Saunders,K. T. Kriebel +1 more
TL;DR: In this article, the authors proposed a scheme to identify cloud-free and cloud-filled pixels (i.e. fields of view) from satellite radiance data, which consists of five daytime or five night-time tests applied to each individual pixel to determine whether that pixel is cloud free, partly cloudy or cloud filled.
Journal ArticleDOI
GEMI: a non-linear index to monitor global vegetation from satellites
TL;DR: A new vegetation index is proposed which has been designed specifically to reduce the relative effects of these undesirable atmospheric perturbations, while maintaining the information about the vegetation cover.
Journal ArticleDOI
Cloud Detection Using Satellite Measurements of Infrared and Visible Radiances for ISCCP
TL;DR: In this article, the cloud detection part of the International Satellite Cloud Climatology Project (ISCCP) analysis is described, and the detection algorithm is supported by global, multiyear surveys of the statistical behavior of satellite-measured infrared and visible radiances to determine those characteristics that differentiate cloudy and clear scenes and how these characteristics vary among climate regimes.