Snow/Cloud Discrimination with Multispectral Satellite Measurements

Allen, R. C.; Durkee, Philip A.; Wash, Carlyle H.

doi:10.1175/1520-0450(1990)029<0994:sdwmsm>2.0.co;2

Cited by 111 publications

(75 citation statements)

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“…The ability of multispectral satellite observations to distinguish snow cover from bare land and clouds during the daytime has led to important advances in the capacity of snow field monitoring [16][17][18][19][20][21]. However, challenges exist at night.…”

Section: Mid-latitude Snow Fieldsmentioning

confidence: 99%

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Miller

Straka

Mills³

et al. 2013

Remote Sensing

282

194

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Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many OPEN ACCESSRemote Sens. 2013, 5 6718 important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available-expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.

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Section: Mid-latitude Snow Fieldsmentioning

confidence: 99%

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Miller

Straka

Mills³

et al. 2013

Remote Sensing

282

194

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“…To estimate ρ TOA (3.7,µ 0 ,µ,φ) from BT (3.7 µm), we invert the Planck function in order to find the temperature corresponding to the radiance measurement at 3.7 µm and extract the reflectance part of it. This method used by Allen et al (1990), Trepte et al (1999), Spangenberg et al (2001)…”

Section: Theoretical Basis Of Aerosol Optical Thickness Retrieval In mentioning

confidence: 99%

Remote sensing of aerosols over snow using infrared AATSR observations

et al. 2011

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Abstract. Infrared (IR) retrievals of aerosol optical thickness (AOT) are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT) simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from the significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA) reflectance in the visible spectral range. In the current work, a new method to retrieve AOT of the coarse and accumulation mode particles over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR) on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 µm and utilizes its dual-viewing observation technique, implying the forward view with an observation zenith angle of around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT) at 3.7 µm, and interpolation of look-up tables (LUTs) for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 µm using a fixed Angström parameter.Correspondence to: L. G. Istomina (lora@iup.physik.uni-bremen.de)The presented method has been validated against groundbased Aerosol Robotic Network (AERONET) data for 4 high Arctic stations and shows good agreement.A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust event. The retrieved AOT maps of the region show a clear increase of AOT in the Kangerlussuaq area. The area of increased AOT was detected on 5 July on the ice sheet east of Kangelussuaq, opposite to the observed north easterly wind at ground level. This position can be explained by a small scale atmospheric circulation transporting the mobilized mineral dust upslope, after its intrusion into the upper branch of the circulation.The performed study of atmospheric reflectance at 3.7 µm also shows possibilities for the detection and retrievals of cloud properties over snow surfaces.

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“…The ''reflectivity product'' is obtained by using the T 4 value to solve for the emitted Planck radiance at 3.9 mm [e.g., Allen et al, 1990], which is then removed from the total 3.9 mm radiance, resulting in reflectance. With no thermal component, there is usually a significant difference in reflectivity between volcanic ash and other features that results in improved detection of the ash, with the maximum difference observed during daylight hours.…”

Section: Product Generation and Displaymentioning

confidence: 99%

Improved detection of airborne volcanic ash using multispectral infrared satellite data

2003

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[1] A technique for improved detection of airborne volcanic ash has been developed that uses three infrared (IR) bands from meteorological satellites. The three IR bands are centered near 3.9, 10.7, and 12.0 mm wavelength. The technique is based on the sum of two brightness temperature differences (BTDs), scaled to maximize the brightness and contrast of volcanic ash in the output image. The physical effects attributed to the observed BTDs that help distinguish the volcanic ash from various meteorological cloud types are (1) differential absorption by volcanic ash or sulfur dioxide at 3.9 mm, 10.7 mm, and 12.0 mm and (2) strong solar reflectance by ash at 3.9 mm, which varies diurnally. On the basis of two examples using data from the Geostationary Operational Environmental Satellite (GOES) the three-band IR technique is shown to provide better discrimination of volcanic ash from meteorological clouds than is possible using existing two-band methods. This conclusion is supported by comparisons of brightness count profiles and estimation of false ash detection rate statistics. The best results from the three-band IR technique are obtained during daylight hours over any surface, and at night when the ash cloud is over the ocean or other large body of water. The three-band IR technique is one of the tools currently being employed operationally at the Washington Volcanic Ash Advisory Center.

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Snow/Cloud Discrimination with Multispectral Satellite Measurements

Cited by 111 publications

References 0 publications

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Remote sensing of aerosols over snow using infrared AATSR observations

Improved detection of airborne volcanic ash using multispectral infrared satellite data

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