cloud screening method particularly feasible for snow ... · cloud shadows currently not considered...

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Cloud screening method particularly feasible for snow cover mapping Sari Metsämäki Finnish Environment Institute (SYKE) LPVE Workshop ESA, Esrin 28-30 Jan 2014

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Page 1: Cloud screening method particularly feasible for snow ... · Cloud shadows currently not considered in SCDA2.0 1-2 pixels buffering does not completely solve this problem In situ

Cloud screening method particularly feasible for snow cover mapping

Sari Metsämäki

Finnish Environment Institute (SYKE)

LPVE Workshop

ESA, Esrin

28-30 Jan 2014

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Motivation

Need for cloud screening algorithm in ESA DUE-GlobSnow project (2009 - )

Project team could not identify a suitable method for Envisat/AATSR, particularly for fractional snow mapping purposes

Undetected clouds usually lead to false snow identification

Very conservative cloud mask may reduce the area for snow mapping

Problems over snow-covered boreal forests and at the edges of snow-covered terrain or at thin snow cover

Official AATSR cloud mask (provided in level 1b) presents severe false cloud commissions over land areas

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Framework for method development

No need to identify all (small/semi-transparent) clouds in confident snow-free areas

Cloud screening is targeted, not cloud classification binary information, no classes, no propabilities

Must be relatively simple and computationally fast

Must be applicable for Northern Hemisphere, no regional/local tuning

Must not confuse between fractional snow and clouds (it’s the fractional snow we want to see!)

Should work particularly over seasonally snow-covered areas and throughout the potential snow season

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Major features of SCDA2.0

Simple Cloud Detection Algorithm

Designed to work with only a few spectral bands

common for Terra/MODIS, Envisat/AATSR, ERS-

2/ATSR-2, NPP Suomi/VIIRS R550, R1.6, BT3.7,

BT11, BT12

Based on empirically determined thresholds for

single bands and their ratios

Driven by BT11-BT3.7

Ratio NDSI / R550 important in avoiding false cloud

commissions

Several other test for BT12, R550 and NDSI

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Page 6: Cloud screening method particularly feasible for snow ... · Cloud shadows currently not considered in SCDA2.0 1-2 pixels buffering does not completely solve this problem In situ

Cloud masks for GlobSnow-2 SE-product from NPP Suomi/VIIRS

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30 Jan, 2003

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Snow

Snow

Cloud

Cloud

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AATSR cloud (operational)

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Snow

Snow

Cloud

Cloud

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GlobSnow-2 cloudSCDA v2.0

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MODIS cloud(from MOD10_L2)

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Improvement from GlobSnow-1 cloud mask :

GlobSnow-1

Edges of snow-covered area falsely interpreted as snow

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Improvement from GlobSnow-1 cloud mask :

GlobSnow-2

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28 Feb, 2003

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Cloud

Snow-covered forest and tundra

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AATSR cloud (operational)

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MODIS cloud(from MOD10_L2)

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GlobSnow-2 cloudSCDA v2.0

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Cloud

Snow-covered forest and tundra

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GlobSnow-2 cloudSCDA v2.0

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07 Mar, 2003

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Cloud

Cloud

Snow-covered terrain

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AATSR cloud (operational)

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MODIS cloud(from MOD10_L2)

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GlobSnow-2 cloudSCDA v2.0

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GlobSnow-2 cloudSCDA v2.0

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12 Apr, 2005

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cloud

Thin/fractional snow

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MODIS cloud(from MOD10_L2)

False cloud commissions, as reported by Hall et Riggs, 2007

Hall, D. K., & Riggs, G. A. (2007). Accuracy assessment of the MODIS snow products. Hydrological Processes, 21(12), 1534–1547.

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GlobSnow-2 cloudSCDA v2.0

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False cloud commissions for Mongolia still a concern (1)

Fractional snow at the edge of snow-covered areas are easily misclassified as cloud (yellow here)

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GS-2 SE, Feb 20, 2009 NASA MOD10_L2, Feb 20, 2009

Edge of snow-covered area

False cloud commissions for Mongolia still a concern (2)

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Occasional cloud omissions in summer months for some cloud types

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Way forward

Improvements are allways welcome! Issue with clouds is not solved…

On-going work: better detection of summertime clouds Reference image approach is investigated (based on SCAmod

FSC retrieval method)

Expansion of teaching data set for decision rules

Cloud shadows currently not considered in SCDA2.0 1-2 pixels buffering does not completely solve this problem

In situ observations on cloudiness could help the method development and validation: e.g. sky-cameras

Need of proper cloud screening method for snow mapping purposes from Sentinel-3 SLSTR SCDA2.0 is a good basis for that

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Thank you for your attention!

Acknowledgement to

• Finnish Meteorological Institute (FMI) • Gamma Remote Sensing AGfor GlobSnow-processings