Investigating the effect of snow-ice formation on snow depth and density over Arctic sea ice

Kuvaus

We investigated the effect of snow-ice formation on snow depth and density over Arctic sea ice. We coupled SnowModel-LG, a snow modeling system adapted for snow depth and density reconstruction over sea ice, with HIGHTSI, a 1-D sea ice thermodynamic model, to simulate snow-ice growth. Pan-Arctic model simulations were performed over the period 1 August 1980 through 31 July 2022. The model outputs were gridded to the 25x25 km Equal-Area Scalable Earth Grid (EASE-Grid), provided by the National Snow and Ice Data Center (NSIDC) (361 x 361 pixels). We compared snow depth and density from the coupled product (SnowModel-LG_HS) to outputs from the SnowModel-LG. The data set includes daily, pan-Arctic information of snow depth, snow density, snow-ice thickness and thermodynamically grown sea ice thickness from 1.8.1980 until 31.7.2022, based on SnowModel-LG_HS. Specifically, it includes the following (4) netcdf files: 1. snod_hs.nc: Pan-Arctic snow depth based on SnowModel-LG_HS 2. sden_hs.nc: Pan-Arctic snow density based on SnowModel-LG_HS 3. sice.nc: Pan-Arctic snow-ice thickness based on SnowModel-LG_HS 4. tice.nc: Pan-Arctic thermodynamically grown sea ice thickness based on SnowModel-LG_HS
Näytä enemmän

Julkaisuvuosi

2023

Aineiston tyyppi

Tekijät

Colorado State University

Liston, Glen - Tekijä

Ilmatieteen laitos - Julkaisija

Jutila, Arttu - Tekijä

Merkouriadi, Ioanna - Tekijä

Projekti

Muut tiedot

Tieteenalat

Geotieteet

Kieli

englanti

Saatavuus

Avoin

Lisenssi

Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)

Avainsanat

INSPIRE theme: climatologyMeteorologyAtmosphere, snow depth, snow density, snow-ice, Arctic Ocean

Asiasanat

Ajallinen kattavuus

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