Andrew K. Heidinger

A Naive Bayesian Cloud-Detection Scheme Derived from CALIPSO and Applied within PATMOS-x

AbstractThe naive Bayesian methodology has been applied to the challenging problem of cloud detection with NOAA’s Advanced Very High Resolution Radiometer (AVHRR). An analysis of collocated NOAA-18/AVHRR and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations was used to automatically and globally derive the Bayesian classifiers. The resulting algorithm used six Bayesian classifiers computed separately for seven surface types. Relative to CALIPSO, the final results show a probability of correct detection of roughly 90% over water, deserts, and snow-free land; 82% over the Arctic; and below 80% over the Antarctic. This technique is applied within the NOAA Pathfinder Atmosphere’s Extended (PATMOS-x) climate dataset and the Clouds from AVHRR Extended (CLAVR-x) real-time product generation system. Comparisons of the PATMOS-x results with those from International Satellite Cloud Climatology Project (ISCCP) and Moder...

Deriving an inter-sensor consistent calibration for the AVHRR solar reflectance data record

A new set of reflectance calibration coefficients has been derived for channel 1 (0.63 μm) and channel 2 (0.86 μm) of the Advanced Very High Resolution Radiometer (AVHRR) flown on the National Oceanic and Atmospheric Administration (NOAA) and European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar orbiting meteorological satellites. This paper uses several approaches that are radiometrically tied to the observations from National Aeronautics and Space Administrations (NASAs) Moderate Resolution Imaging Spectroradiometer (MODIS) imager to make the first consistent set of AVHRR reflectance calibration coefficients for every AVHRR that has ever flown. Our results indicate that the calibration coefficients presented here provide an accuracy of approximately 2% for channel 1 and 3% for channel 2 relative to that from the MODIS sensor.

Gazing at Cirrus Clouds for 25 Years through a Split Window. Part I: Methodology

Abstract This paper demonstrates that the split-window approach for estimating cloud properties can improve upon the methods commonly used for generating cloud temperature and emissivity climatologies from satellite imagers. Because the split-window method provides cloud properties that are consistent for day and night, it is ideally suited for the generation of a cloud climatology from the Advanced Very High Resolution Radiometer (AVHRR), which provides sampling roughly four times per day. While the split-window approach is applicable to all clouds, this paper focuses on its application to cirrus (high semitransparent ice clouds), where this approach is most powerful. An optimal estimation framework is used to extract estimates of cloud temperature, cloud emissivity, and cloud microphysics from the AVHRR split-window observations. The performance of the split-window approach is illustrated through the diagnostic quantities generated by the optimal estimation approach. An objective assessment of the perfo...

Daytime cloud overlap detection from AVHRR and VIIRS

Abstract Two algorithms for detecting multilayered cloud systems with satellite data are presented. The first algorithm utilizes data in the 0.65-, 11-, and 12-μm regions of the spectrum that are available on the Advanced Very High Resolution Radiometer (AVHRR). The second algorithm incorporates two different techniques to detect cloud overlap: the same technique used in the first algorithm and an additional series of spectral tests that now include data from the 1.38- and 1.65-μm near-infrared regions that are available on the Moderate Resolution Imaging Spectroradiometer (MODIS) and will be available on the Visible/Infrared Imager/Radiometer Suite (VIIRS). VIIRS is the imager that will replace the AVHRR on the next generation of polar-orbiting satellites. Both algorithms were derived assuming that a scene with cloud overlap consists of a semitransparent ice cloud that overlaps a cloud composed of liquid water droplets. Each algorithm was tested on three different MODIS scenes. In all three cases, the se...

Daytime Global Cloud Typing from AVHRR and VIIRS: Algorithm Description, Validation, and Comparisons

Abstract Three multispectral algorithms for determining the cloud type of previously identified cloudy pixels during the daytime, using satellite imager data, are presented. Two algorithms were developed for use with 0.65-, 1.6-/3.75-, 10.8-, and 12.0-μm data from the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) operational polar-orbiting satellites. The AVHRR algorithms are identical except for the near-infrared data that are used. One algorithm uses AVHRR channel 3a (1.6 μm) reflectances, and the other uses AVHRR channel 3b (3.75 μm) reflectance estimates. Both of these algorithms are necessary because the AVHRRs on NOAA-15 through NOAA-17 have the capability to transmit either channel 3a or 3b data during the day, whereas all of the other AVHRRs on NOAA-7 through NOAA-14 can only transmit channel 3b data. The two AVHRR cloud-typing schemes are used operationally in NOAA’s extended Clouds from AVHRR (CLAVR)-x processing system. The ...

Molecular Line Absorption in a Scattering Atmosphere. Part II: Application to Remote Sensing in the O2 A band

This paper explores the feasibility of using O 2 A-band reflectance spectra in the retrieval of cloud optical and physical properties. Analyses demonstrate that these reflection spectra are sensitive to optical properties of clouds such as optical depth t c and phase function, vertical profile information including cloud-top pressure, pressure thickness, and the surface albedo. An estimation method is developed to demonstrate how well this information might be retrieved from synthetic spectra calculated by a line-by-line spectral multiple scattering model assuming realistic instrument parameters (spectral resolution, calibration accuracy, and signal-to-noise properties). The quality of the retrievals is expressed in terms of two indices, one relating to total error and another that quantifies the extent of reliance of the retrieval on the measurement, or conversely on other a priori information. Sources of total error include instrument-related errors, forward model errors including phase function errors, and errors in a priori data. The retrievals presented show the following: (i) The optical depth, surface albedo, cloud-top pressure, and cloud layer pressure thickness can be retrieved with an accuracy of approximately 5% for most cases of low cloud except when these clouds are optically thin and over bright surfaces. The spectra also contain information about the pressure thickness of the low-level cloud and this information also can be retrieved with an expected accuracy of less than 10% and with little reliance on any a priori data. (ii) Significantly larger errors result for retrievals for high clouds when no attempt is made to constrain the uncertainties associated with the unknown character of the scattering phase function. (iii) Retrieval of a limited amount of information about the phase function is possible under certain circumstances. It is possible to retrieve the asymmetry parameter sufficiently well to improve the accuracy of the forward model. This results in a shrinking of the errors in t c to less than 10% for t c . 0.1. (iv) The pressure information about scattering layers inherent in the A-band spectra is shown to provide a limited amount of vertical profiling capability (four to five layers of information at the most) provided the measurements are obtained with a spectral resolution of about 0.5 cm21 and obtained with an accuracy of 2% or better. A specific example demonstrates the capability of not only detecting the presence of thin high cloud above lower brighter cloud but also the capability of estimating the optical depths of both clouds. (v) The advantage of additional information such as provided by active profilers (radar and lidar) is explored. The advantages of this additional profile information are quantitatively shown to improve not only the retrieval of vertical profiles of extinction but also the optical properties of individual cloud layers.

The Successive-Order-of-Interaction Radiative Transfer Model. Part I: Model Development

Abstract This study, the first part of a two-part series, develops the method of “successive orders of interaction” (SOI) for a computationally efficient and accurate solution for radiative transfer in the microwave spectral region. The SOI method is an iterative approximation to the traditional adding and doubling method for radiative transfer. Results indicate that the approximations made in the SOI method are accurate for atmospheric layers with scattering properties typical of those in the infrared and microwave regions. In addition, an acceleration technique is demonstrated that extends the applicability of the SOI approach to atmospheres with greater amounts of scattering. A comparison of the SOI model with a full Monte Carlo model using the atmospheric profiles given by Smith et al. was used to determine the optimal parameters for the simulation of microwave top-of-atmosphere radiances. This analysis indicated that a four-stream model with a maximum initial-layer optical thickness of approximately ...

Implementation of the Daytime Cloud Optical and Microphysical Properties Algorithm (DCOMP) in PATMOS-x

AbstractThis paper describes the daytime cloud optical and microphysical properties (DCOMP) retrieval for the Pathfinder Atmosphere’s Extended (PATMOS-x) climate dataset. Within PATMOS-x, DCOMP is applied to observations from the Advanced Very High Resolution Radiometer and employs the standard bispectral approach to estimate cloud optical depth and particle size. The retrievals are performed within the optimal estimation framework. Atmospheric-correction and forward-model parameters, such as surface albedo and gaseous absorber amounts, are obtained from numerical weather prediction reanalysis data and other climate datasets. DCOMP is set up to run on sensors with similar channel settings and has been successfully exercised on most current meteorological imagers. This quality makes DCOMP particularly valuable for climate research. Comparisons with the Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 dataset are used to estimate the performance of DCOMP.

Molecular Line Absorption in a Scattering Atmosphere. Part I: Theory

This paper revisits the classical problem of particle scattering‐gaseous absorption and considers the extent to which the growth of absorption lines of a known gas can be used to obtain information about the scattering particles. The focus of the study is directed toward interpretation of the reflection spectrum of the O 2 A band located in the spectral region between 0.759 and 0.771 mm and the results provide a theoretical foundation for the retrieval of particle information described in a related study. This study demonstrates that there are six main properties that affect the absorption and reflection spectra: the optical depth of the cloud or aerosol, the pressure level of the top of this layer, the (pressure) thickness of the layer, the scattering phase function, the particle single-scatter albedo, and the surface albedo. Measured quantities, such as the spectral radiance or the ratio of in-absorption to continuum radiances are shown to be sensitive to these parameters in a manner that varies according to the O 2 optical depth. This variation sensitivity offers a way of separating the dependence of the measurements on these parameters, thereby providing some basis for their retrieval with suitable spectral measurements that resolve a sufficient range of O2 optical depth. Specifically, it is shown that radiances reflected from thin layers are sensitive to optical depth and phase function whereas the radiance ratio is sensitive to layer height. For thick layers, the sensitivity to optical depth diminishes leaving primarily a sensitivity to bulk information about the scattering phase function. By measuring radiances as a function of changing O 2 absorption, it is possible to distinguish optically thin layers above brighter lower reflecting surfaces, providing an ability to distinguish high-level thin cloud over brighter lower-level clouds or reflecting surfaces. The effects of 3D geometry on the spectral radiances is also considered in the context of photon path. It is shown how the spectral radiances provide some insight on 3D effects and the probable importance of these 3D effects on the retrievals. The equivalence theorem is illustrated and is used to provide line-by-line simulations of the reflection spectrum from hypothetical 3D clouds. A method to identify the nature of the 3D bias on retrievals of optical depth is discussed.

The Advanced Very High Resolution Radiometer Pathfinder Atmosphere (PATMOS) Climate Dataset: A Resource for Climate Research

As part of the joint National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) Pathfinder program, the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) has created a research-quality global atmospheric dataset through the reprocessing of Advanced Very High Resolution Radiometer (AVHRR) observations since 1981. The AVHRR is an imaging radiometer that flies on NOAA polar-orbiting operational environmental satellites (POES) measuring radiation reflected and emitted by the earth in five spectral channels. Raw AVHRR observations were recalibrated using a vicarious calibration technique for the reflectance channels and an appropriate treatment of the nonlinearity of the infrared channels. The observations are analyzed in the Pathfinder Atmosphere (PATMOS) project to obtain statistics of channel radiances, cloud amount, top of the atmosphere radiation budget, and aerosol optical thickness over ocean. The radiances and radiation bu...