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Publication Additional Information Download
Publication Type
Journal Article
Authorship
Menard, C., Essery, R., Krinner, G., Arduini, G., Bartlett, P., Boone, A., Brutel-Vuilmet, C., Burke, E., Cuntz, M., Dai, Y., Decharme, B., Dutra, E., Fang, L., Fierz, C., Gusev, Y., Hagemann, S., Haverd, V., Kim, H., Lafaysse, M., Marke, T., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Schaedler, G., Semenov, V., Smirnova, T., Strasser, U., Swenson, S., Turkov, D., Wever, N., Yuan, H.
Title
Scientific and human errors in a snow model intercomparison
Year
2021
Publication Outlet
BAMS, Bulletin of the American Meteorological Society, 102(1), E61-E79
DOI
https://doi.org/10.1175/BAMS-D-19-0329.1
Citation
Menard, C., Essery, R., Krinner, G., Arduini, G., Bartlett, P., Boone, A., Brutel-Vuilmet, C., Burke, E., Cuntz, M., Dai, Y., Decharme, B., Dutra, E., Fang, L., Fierz, C., Gusev, Y., Hagemann, S., Haverd, V., Kim, H., Lafaysse, M., Marke, T., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Schaedler, G., Semenov, V., Smirnova, T., Strasser, U., Swenson, S., Turkov, D., Wever, N., Yuan, H. (2021): Scientific and human errors in a snow model intercomparison, BAMS, https://doi.org/10.1175/BAMS-D-19-0329.1 .
Abstract
Twenty-seven models participated in the Earth System Model–Snow Model Inter-comparison Project (ESM-SnowMIP), the most data-rich MIP dedicated to snow modeling. Our findings do not support the hypothesis advanced by previous snow MIPs: evaluating models against more variables and providing evaluation datasets extended temporally and spatially does not facilitate identification of key new processes requiring improvement to model snow mass and energy budgets, even at point scales. In fact, the same modeling issues identified by previous snow MIPs arose: albedo is a major source of uncertainty, surface exchange parameterizations are problematic, and individual model performance is inconsistent. This lack of progress is at-tributed partly to the large number of human errors that led to anomalous model behavior and to numerous resubmissions. It is unclear how widespread such errors are in our field and others; dedicated time and resources will be needed to tackle this issue to prevent highly sophisticated models and their research outputs from being vulnerable because of avoidable human mistakes. The design of and the data available to successive snow MIPs were also questioned. Evaluation of models against bulk snow properties was found to be sufficient for some but inappropriate for more complex snow models whose skills at simulating internal snow properties remained untested. Discussions between the authors of this paper on the purpose of MIPs revealed varied, and sometimes contradictory, motivations behind their participation. These findings started a collaborative effort to adapt future snow MIPs to respond to the diverse needs of the community.
Program Affiliations
GWF: Global Water Futures
INARCH: International Network of Alpine Research Catchment Hydrology
Project Affiliations
GWF-IMPC: Integrated Modelling Program for Canada
INARCH2/COPE: International Network of Alpine Research Catchment Hydrology (Phase 2)/Common Observation Period Experiment
Publication Stage
Published
Additional Information
IMPC, INARCH
Download Links
https://doi.org/10.1175/BAMS-D-19-0329.1
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