Assessment of spring snow cover duration variability over northern Canada from satellite datasets

Abstract

Variability in northern hemisphere (NH) spring and summer snow extent is strongly influenced by snow cover duration (SCD) across the Canadian Arctic. In order to assess the accuracy with which satellite-derived snow extent datasets capture the dynamic melt period (1 April–31 July), SCD datasets derived from the weekly NOAA snow chart record (1979–2004), daily IMS product (2000–2004), passive microwave (PMW) brightness temperatures (1979–2004), and Ku-band QuikSCAT scatterometer data (2000–2004) were assessed against in situ measurements across the Canadian Arctic (north of 60°). The higher resolution IMS and QSCAT datasets showed the best ability to capture spatial variability in spring SCD over the Canadian Arctic, followed by the NOAA and PMW datasets. The poorer performance of the PMW was anticipated because of documented difficulties monitoring snow cover over forested and mountainous terrain. Both the IMS and the NOAA datasets exhibited positive biases of ∼ 22–26 days which can be related to elevation effects and frequent cloud cover. The NOAA dataset was unable to capture interannual variability in spring snow cover over the central Canadian Arctic tundra region (66–74° N, 80–120° W) while the PMW was able to capture a significant fraction of the observed variability. This fact, combined with anomalous snow-cover temperature responses in the NOAA data further reinforces the conclusions of Wang et al. [Wang, L., Sharp, M., Brown, R., Derksen, C., & Rivard, B., (2005a). Evaluation of spring snow covered area depletion in the Canadian Arctic from NOAA snow charts. Remote Sensing of Environment, 95, 453–463] that considerable care be taken when using NOAA data during the summer months (June–August) where NH snow cover variability is controlled by relatively small regions with frequent cloud cover. QuikSCAT data were able to provide comparable results to IMS over the 2000–2004 period, indicating that Ku-band scatterometer measurements can make an important contribution to monitoring terrestrial snow extent during spring melt.