Kathleen I. Strabala

Bio: Kathleen I. Strabala is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Cirrus & Cloud top. The author has an hindex of 13, co-authored 22 publications receiving 2330 citations. Previous affiliations of Kathleen I. Strabala include Cooperative Institute for Meteorological Satellite Studies.

Discriminating clear sky from clouds with MODIS

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.

Four years of global cirrus cloud statistics using HIRS

Abstract: Trends in global upper-tropospheric transmissive cirrus cloud cover are beginning to emerge from a four-year cloud climatology using NOAA polar-orbiting High-Resolution Infrared Radiation Sounder (HIRS) multispectral data. Cloud occurrence, height, and effective emissivity are determined with the CO2 slicing technique on the four years of data (June 1989-May 1993). There is a global preponderance of transmissive high clouds, 42% on the average; about three-fourths of these are above 500 hPa and presumed to be cirrus. In the Inter-tropical Convergence Zone (ITCZ), a high frequency of cirrus (greater than 50%) is found at all times; a modest seasonal movement tracks the sun. Large seasonal changes in cloud cover occur over the oceans in the storm belts at midlatitudes; the concentrations of these clouds migrate north and south with the seasons following the progressions of the subtropical highs (anticyclones). More cirrus is found in the summer than in the winter in each hemisphere. A significant change in cirrus cloud cover occurs in 1991, the third year of the study. Cirrus observations increase from 35% to 43% of the data, a change of eight percentage points. Other cloud forms, opaque to terrestrial radiation, decerase by nearly the same amount. Most of the increase is thinner cirrus with infrared optical depths below 0.7. The increase in cirrus happens at the same time as the 1991-92 El Nino/Southern Oscillation (ENSO) and the eruption of Mt. Pinatubo. The cirrus changes occur at the start of the ENSO and persist into 1993 in contrast to other climatic indicators that return to near pre-ENSO and volcanic levels in 1993.

Cloud Properties inferred from 812-µm Data

Abstract: A trispectral combination of observations at 8-, 11-, and 12-µm bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-µm brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 µm than between 8 and 11 µm, while for ice, the reverse is true. Cloud phase is determined by a scatter diagram of 8-minus-11-µm versus 11-minus-12-µm brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud leer than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-µm bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-µm bandwidth for future satellites can...

Remote sensing of cloud properties using MODIS airborne simulator imagery during SUCCESS: 2. Cloud thermodynamic phase

Abstract: Methods to infer cloud thermodynamic phase (ice or water) are investigated using multispectral imagery An infrared (IR) trispectral algorithm using the 852-, 11-, and 12-gm bands (Ackerman et al, 1990; Strabala et al, 1994) forms the basis of this work and will be applied to data from the Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument Since the algorithm uses IR bands, it can be applied to either daytime or nighttime data and is not sensitive to the presence of cloud shadows A case study analysis is performed with a MODIS airborne simulator (MAS) scene collected during the Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS) on April 21, 1996, at 2000 UTC The scene under scrutiny is quite complex, containing low-level broken water clouds, cirrus cells, cloud shadows, subvisual cirrus, and contrails The IR trispectral algorithm is found to be less accurate in (1) regions where more than one cloud phase type occurs and (2) regions of thin cirrus overlying a lower-level cloud layer To improve the phase retrieval accuracy in these areas of difficulty, additional bands located at 065, 163, and 190 gm are incorporated Radiative transfer (RT) calculations are performed to simulate the MAS bands using the cirrus and water cloud models detailed by Baum et al (this issue) The RT calculations are performed for single- layer cirrus- and water-phase clouds as well as for the case of thin cirrus overlying a lower-level water droplet cloud Both modeled results and application of the theory to a case study suggest that the cloud thermodynamic phase retrieval accuracy can be improved by inclusion of the visible and near infrared bands

Seasonal and Diurnal Changes in Cirrus Clouds as Seen in Four Years of Observations with the VAS

Abstract: GOES VAS multispectral observations in the carbon dioxide absorption band at 15 μm have been used to compile cloud-cover statistics over the continental United States for the past 4 years. The CO2 technique calculates both cloud-top pressures and effective emissivities and reliably distinguishes semitransparent cirrus from opaque clouds. The frequency of semitransparent cirrus clouds exhibits small seasonal variation; they are generally present 25%–30% of the time in all seasons. Diurnal variations of semitransparent cirrus are found only in the summer months and correspond to diurnal variations in convection in the Rocky Mountains and southeastern United States, increases of 20% in cirrus are noted subsequent to the convective cloud activity. In the winter months, no diurnal change in semitransparent cirrus is detected. Attempts to correlate cirrus with some common atmospheric features reveal that a majority of cirrus occurred where dynamic parameters indicate rising vertical motion but that con...

The MODIS Aerosol Algorithm, Products and Validation

Abstract: The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA’s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41–15 m). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 m. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of 0.03 0.05 over ocean and 0.05 0.15 over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within reff 0.11 m. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.

Advances in understanding clouds from ISCCP

Abstract: This progress report on the International Satellite Cloud Climatology Project (ISCCP) describes changes made to produce new cloud data products (D data), examines the evidence that these changes are improvements over the previous version (C data), summarizes some results, and discusses plans for the ISCCP through 2005. By late 1999 all datasets will be available for the period from July 1983 through December 1997. The most significant changes in the new D-series cloud datasets are 1) revised radiance calibrations to remove spurious changes in the long-term record, 2) increased cirrus detection sensitivity over land, 3) increased low-level cloud detection sensitivity in polar regions, 4) reduced biases in cirrus cloud properties using an ice crystal microphysics model in place of a liquid droplet microphysics model, and 5) increased detail about the variations of cloud properties. The ISCCP calibrations are now the most complete and self-consistent set of calibrations available for all the weather...

The MODIS cloud products: algorithms and examples from Terra

Abstract: The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System (EOS) platform launched in December 1999. After achieving final orbit, MODIS began Earth observations in late February 2000 and has been acquiring data since that time. The instrument is also being flown on the Aqua spacecraft, launched in May 2002. A comprehensive set of remote sensing algorithms for cloud detection and the retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various algorithms being used for the remote sensing of cloud properties from MODIS data with an emphasis on the pixel-level retrievals (referred to as Level-2 products), with 1-km or 5-km spatial resolution at nadir. An example of each Level-2 cloud product from a common data granule (5 min of data) off the coast of South America will be discussed. Future efforts will also be mentioned. Relevant points related to the global gridded statistics products (Level-3) are highlighted though additional details are given in an accompanying paper in this issue.

The Collection 6 MODIS aerosol products over land and ocean

Abstract: . The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.