Coupled C-N-P QUINCY terrestrial biosphere enhanced for high latitude simulations over 1960-2018 for the high-Arctic region

General

We performed simulations over sites with the global terrestrial model state-of-the-art QUINCY for sites covering the high-Arctic. These simulations server to improve quantifications of impacts caused by nitrogen mobilized following the thaw of permafrost, both for vegetation growth and soil processes. In a model version that was extended for a better representation of high latitudes, we performed sets of simulations to seperate effects that arise from increased nutrient release from thawing of permafrost soil, changes in the physical climate, as well as atmospheric CO₂ fertilization. In addition to this, we constructed GPP estimates from eddy-covariance towers, as well as seasonalities of thaw depths using soil temperature data.

Methods

Modelled data was simulated with the fully coupled QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) model (see model code: quincy_model_code.zip, QUINCY gitlab commit 1868232970ea4f8dbfd75c12f918ca32d43ea3ae). We extended the model with important high-latitude processes (soil freezing, snow, dynamic rooting depths). We used University of East Anglia Climatic Research Unit Japanese Reanalysis (CRU-JRA; Harris, 2019) atmospheric forcing to drive the model for 1901 to 2018, using only the 1960-2018 time frame for our analysis. We conducted three sets of simulations. climate+withoutpermafrostCNP considers changes in climate, but initialising carbon and nutrients contents to exponentially decrease with depth, as in the standard model. By doing this, C, N and P contents at depth are close to zero, thus excluding any potential fertilization effect linked to a deepening active layer. The second set of simulations was again driven by changing climate (climate), but this time also considering the release of carbon and nutrient pools from previously permanently-frozen layers, i.e. release from the permafrost. The third set of simulations additionally considered the impact of increasing atmospheric CO₂ levels on vegetation dynamics and carbon cycle processes (climate+CO₂). 

Annual timeseries are found in annual_data_1960_2018.zip, weekly climatologies are found in seasonal_data_1998_2018.zip, eddy-covariance-derived seasonalities are given in eddyfluxcovariance_data.zip. Individidual file descriptions and units are given in README.txt.

The data described here is used in the publication Lacroix et al. Mismatch of N release from the permafrost and vegetative uptake opens pathways of increasing nitrous oxide emissions in the high Arctic. Accepted for publication in Global Change Biology.

Harris, I.C. (2019): CRU JRA v1.1: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2017. Centre for Environmental Data Analysis, 25 February 2019. doi:10.5285/13f3635174794bb98cf8ac4b0ee8f4ed.