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Constraining Reanalysis Snowfall Over the Arctic Ocean Using CloudSat Observations
Author(s) -
Cabaj A.,
Kushner P. J.,
Fletcher C. G.,
Howell S.,
Petty A. A.
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2019gl086426
Subject(s) - snow , environmental science , arctic , climatology , sea ice , arctic ice pack , range (aeronautics) , meteorology , geology , oceanography , geography , materials science , composite material
In the absence of widespread snowfall observations over the Arctic Ocean, reanalysis products provide a wide range of estimates of time‐evolving snowfall rates over Arctic sea ice, and it can be difficult to determine which product is most representative. In this work, Arctic snowfall rates retrieved from 2006 to 2016 CloudSat observations and snowfall products from three reanalyses are assessed. The products can be brought into encouraging agreement over the region on interannual time scales once differences in spatial representativeness and temporal sampling are accounted for. This motivates the use of CloudSat's snowfall product to calibrate reanalysis snowfall. The calibration is carried out for four Arctic quadrants and combined to produce regionally resolved and consistent estimates of interannually varying snowfall. Calibrated reanalysis snowfall inputs are then used to drive the NASA Eulerian Snow On Sea Ice Model, reducing the interproduct spread in the resulting simulated snow depths across the Arctic.