Abstract

An Earth Observing System global snow cover extent data products record at moderate spatial resolution (375–500 m) began in February 2000 with the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra satellite. The record continued with the Aqua MODIS in July 2002, the Suomi-National Polar Platform (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) in January 2012 and continues with the Joint Polar Satellite System-1 (JPSS-1) VIIRS, launched in November of 2017. The objective of this work is to develop a snow cover extent Earth Science Data Record (ESDR) using different satellites, sensors and algorithms. There are many issues to understand when data from different algorithms and sensors are used over a decade-scale time period to create a continuous dataset. Issues may also arise with sensor degradation and even differences in sensor band locations. In this paper we describe development of an ESDR derived from existing MODIS and VIIRS data products and demonstrate continuity among the products. The MODIS and VIIRS snow cover detection algorithms produce very similar daily snow cover maps, with 90–97% agreement in snow cover extent (SCE) in different landscapes. Differences in SCE between products ranged from 2–15% and are attributable to convolved factors of viewing geometry, pixel spread across a scan and time of observation. Compared at a common grid size of 1 km, there is a mean of 95% agreement in SCE and a difference range of 1–10% between the MODIS and VIIRS SCE maps. Mapping sensor observations to a coarser resolution grid reduces the effect of the factors convolved in the 500 m tile to tile comparisons. We conclude that the MODIS and VIIRS SCE data products are reliable constituents of a moderate-resolution ESDR.

Highlights

  • Snow cover extent (SCE) has been cited as an Essential Climate Variable in the Global Climate Observing System because of its tremendous importance in the Earth’s energy balance and as a source of freshwater for more than 1 billion people worldwide [1]

  • Products derived from the Normalized Difference Vegetation Index (NDVI) and other indices were cross compared at a climate modeling grid (CMG) scale of ~5 km spatial resolution to minimize effects that factors such as sensor characteristics and viewing geometry can have on cross comparisons of observations at sensor pixel resolution

  • Large areas of cloud cover are similar among the three products on a given day but small areas of cloud and cloud cover at the periphery of snow cover extent (SCE) areas differ due to differences in the cloud mask algorithms for Moderate-resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS), time of acquisition and other convolved factors

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Summary

Introduction

Snow cover extent (SCE) has been cited as an Essential Climate Variable in the Global Climate Observing System because of its tremendous importance in the Earth’s energy balance and as a source of freshwater for more than 1 billion people worldwide [1]. Snow is important globally for recreation and for municipal water-supply needs. Snow can cover up to 50% of the Northern Hemisphere land surface in winter, covering 1.9 to 45 million km2 [2]. In the Northern Hemisphere SCE is highly variable from year to year, decade-scale trends may be difficult to identify until a sufficient length of record is available. Duration and melt date of snow cover is critical to understand interannual and longer-term changes at regional to hemisphere scales. Changes in regional SCE are both an indicator and a result of climate change

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