Abstract

In this study, daily maps of snow cover distribution and sea ice extent produced by NOAA’s interactive multisensor snow and ice mapping system (IMS) were validated using in situ snow depth data from observing stations obtained from NOAA’s National Climatic Data Center (NCDC) for calendar years 2006 to 2010. IMS provides daily maps of snow and sea ice extent within the Northern Hemisphere using data from combination of geostationary and polar orbiting satellites in visible, infrared and microwave spectrums. Statistical correspondence between the IMS and in situ point measurements has been evaluated assuming that ground measurements are discrete and continuously distributed over a 4 km IMS snow cover maps. Advanced Very High Resolution Radiometer (AVHRR) land and snow classification data are supplemental datasets used in the further analysis of correspondence between the IMS product and in situ measurements. The comparison of IMS maps with in situ snow observations conducted over a period of four years has demonstrated a good correspondence of the data sets. The daily rate of agreement between the products mostly ranges between 80% and 90% during the Northern Hemisphere through the winter seasons when about a quarter to one third of the territory of continental US is covered with snow. Further, better agreement was observed for stations recording higher snow depth. The uncertainties in validation of IMS snow product with stationed NCDC data were discussed.

Highlights

  • Snow cover plays a critical role in regional to global scale hydrological modeling [1,2].Rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods

  • The analysis of a correlation time series between the ice mapping system (IMS) product and the National Climatic Data Center (NCDC) stations involves a heavier focus on the winter months than the summer months

  • This is because the likelihood of a mismatch between an IMS pixel and NCDC station reading is higher during the winter season

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Summary

Introduction

Snow cover plays a critical role in regional to global scale hydrological modeling [1,2].Rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Remote sensing measurements in the visible and near infrared part of spectrum have shown great potential in providing information on the snow cover extent. Satellite sensors such as the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA satellites, Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System (EOS). The bright surface features or boundaries between water bodies and land can increase erroneous snow detection. These errors are eliminated using interactive techniques where multiple images were used along with microwave data [6]

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