Abstract
The snow water equivalent (SWE) products from passive microwave remote sensing are useful in global climate change studies due to the long-time and all-weather imaging capabilities of passive microwave radiometry at the hemisphere scale. Northern Hemisphere SWE products, including products from the National Snow and Ice Data Center (NSIDC) and GlobSnow from the European Space Agency (ESA), have been providing long-time series information since 1979. However, the different algorithms used to produce the NSIDC and GlobSnow products lead to discrepancies in the data. To determine which product might be superior, this paper assesses their hemisphere-scale quality for the time period 1979−2010. By comparing the data with historical snow depth measurements obtained from 7388 meteorological stations in the Northern Hemisphere, the accuracies of the different SWE products are analyzed for the period and for different snow types. The results show that for SWEs above 30 mm but below 200 mm, GlobSnow estimates maintain a better linear relation with the ground measurements. NSIDC products are more influenced by microwave “saturation,” producing obvious underestimations for SWEs over 120 mm. However, for shallow snow (SWE less than 30 mm), the slight overestimate produced by GlobSnow is more obvious than that of the other NSIDC products.
Highlights
The snowpack is important both as a boundary condition on the atmosphere and as storage for fresh water
We describe the comparison between a large set of snow depth measurements from meteorological stations and three passive microwave radiometry (PMR) products, such as GlobSnow and the two National Snow and Ice Data Center (NSIDC) snow water equivalent (SWE) products
Liu et al.: Hemispheric-scale comparison of monthly passive microwave snow water equivalent products highest SWE contain dissimilarities at the hemisphere scale (Fig. 2). Both NSIDC products extend to lower latitude regions, especially over Eurasia, whereas the GlobSnow products cover a smaller area
Summary
The snowpack is important both as a boundary condition on the atmosphere and as storage for fresh water. Some advanced studies have attempted to introduce microwave radiation models into the retrieval process with the aim of better predicting the microwave radiation from the snowpack based on physical mechanisms.[22,23,24,25,26] These methods often have higher precision but are too complex for direct retrieval of snow variables under varying snow conditions at the hemisphere scale Among these methods, the HUT model (developed at Helsinki University of Technology) is an adequate simple model that has proven feasible in global SWE retrieval. A Bayesian inversion method for the HUT emission model[27,28,29] has proven to be more accurate, with a lower root-mean-square error (RMSE) and bias than those of other algorithms[30] (including the NSIDC operational algorithm[20] and the AMSR-E standard SWE product21) when applied over Eurasia, Canada, and northern Finland. Because the PMRs’ brightness temperature is influenced by the properties of the snow (i.e., the amount of snow, snow grain size, snow density, and the presence of liquid water), it is necessary to make comparisons for similar snow classes, which are defined according to the properties of the snow
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
