GTMIP meteorological driving dataset for the GRENE-TEA observation sites (20-year detrended)

The modeling group (GTM) in the terrestrial ecosystem research project of the GRENE Arctic Climate Change Research Project (GRENE-TEA) aims to a) feed to the coupled global climate model (CGCM) research project for the possible improvement of the physical and ecological processes for the Arctic terrestrial modeling (excl. glaciers and ice sheets) in the extant terrestrial schemes in the CGCMs, and b) lay the foundations of the future-generation Arctic terrestrial model development. To achieve these goals GTM conducts a model intercomparison project (GTMIP) among the openly participating models. The GTMIP is designated to 1) enhance communications and understanding of the "mind and hands" between the modeling researchers and field scientists, 2) assess the uncertainty and variations stemmed from the extant model implementation/designation, and the variability due to climatic and historical conditions among the Arctic sites, and 3) feed such information and evaluations to the future-generation Arctic terrestrial model development. The GTMIP comprised of two stages: the first using observation data at the GRENE-TEA sites (stage 1) and the second using CGCM outputs for circumpolar regions (stage 2) to drive and validate the models. The meteorological variables provided for model forcing are total precipitation (Pr), air temperature at reference height (Tair), surface pressure (Psurf), wind speed at reference height (Wind), surface incident shortwave radiation (SWdown), surface incident long wave radiation (LWdown), and specific humidity at reference height (Qair). The stage 1 provides two levels of the half-hourly datasets for the GTMIP sites, namely the level 0 (L0) and level 1 (L1) for Fairbanks (Poker Flat Research Range), Alaska, USA; Kevo (Kevo Research Station), Finland; Tiksi, Sakha Republic, Russian Federation; Yakutsk (Spasskaya Pad), Sakha Republic, Russian Federation. This 20-year detrended meteorological dataset provides driving data for spin up, especially for biogeochemical models to set up initial soil carbon conditions, without being affected by warming trend and/or ENSO (El Nino Southern Oscillation). This dataset is based on L1 data for the period of 1980-1999.