Validation of NOAA Interactive Snow Maps in the North American region with National Climatic Data Center Ground-based Data

• Main Author: Chen, Christine
• Format: Thesis
• Language: English
• Published: CUNY Academic Works 2011
• Subjects: Snow; Remote Sensing; Ims; Civil and Environmental Engineering; Civil Engineering; Engineering; Sea ice; taiga
• Online Access: https://academicworks.cuny.edu/cc_etds_theses/29; https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1028&context=cc_etds_theses

"Both the areal coverage of snow and the volume of water in its subsequent melt are of concern for the creation and maintenance of both hydroelectric power and local water supply. The interactive multisensor snow and ice mapping system (IMS) is a geographic interactive system that allows for both the viewing of various sensor data and the mapping daily both snow and sea ice extent by an analyst on one platform. This thesis investigates the agreement between the National Oceanic and Atmospheric Administration’s (NOAA) interactive multisensor snow and ice mapping system (IMS) and snow depth values obtained from the National Climatic Data Center’s (NCDC) observing stations in the North American region between 30 – 60° North latitude and 60 – 140° West longitude throughout January 2006 – February 2010. A comparative analysis is made on the basis of land cover, snow type, and snow depth. The first comparison is the most basic comparison. It is a general comparison station-by station between the two datasets. The second, third, and fourth comparisons are all attempts to further the analysis between the interactive multisensor snow and ice mapping system and National Climatic Data Center observing stations. The motivation behind these comparisons is to shed light on the strengths and weaknesses of the NOAA interactive multisensor snow and ice mapping system at different conditions. This knowledge may then be used for future IMS product development. The second and third comparisons involve supplemental datasets. These supplemental datasets are used to examine the role and effects of land classes and snow classes. A 0.5 km AVHRR land classification dataset is used in the second comparison. A 1 km snow classification dataset ii is used in the third comparison. The fourth comparison is an investigation into the effects of snow depth. In this case, the agreement between the NOAA interactive multisensor snow and ice mapping system (IMS) and snow depth values obtained from the National Climatic Data Center’s (NCDC) observing stations is determined upon the placement of the stations into prescribed snow depth intervals. The results from the first comparison show a good agreement between the National Oceanic and Atmospheric Administration’s (NOAA) interactive multisensor snow and ice mapping system (IMS) and snow depth values obtained from the National Climatic Data Center’s (NCDC) observing stations. The agreement ranges from 79% - 100% throughout the study period. The results from the second comparison suggest that the correlation (%) between the snow extent of the Interactive Multisensor Snow and Ice Mapping system and the National Climatic Data Center snow depth values are higher for woodland and wooded grassland than the grassland and cropland. More insight as to the relation in the correlation (%) ranges for the select land classes may be determined through further investigation. This may include investigations based on location or snow depth. The results from the third comparison suggest that the agreement between the two datasets is stronger for the ephemeral snow class and weaker for the maritime, warm taiga, and prairie snow classes. The higher values of correlation (%) for the ephemeral snow class is likely due to a larger number of match situations in which the NCDC observing station records 0 cm (no snow) and the IMS result is land (no snow). The results from the fourth comparison suggest that the agreement between the IMS and NCDC observing stations increases with increasing snow depth."