An Evaluation of Temperature and Precipitation Surface-Based and Reanalysis Datasets for the Canadian Arctic, 1950–2010

Abstract

The spatial and temporal consistency of seasonal air temperature and precipitation in eight widely used gridded observation-based climate datasets (CANGRD, CRU-TS3.1, CRUTEM4.1, GISTEMP, GPCC, GPCP, HadCRUT3, and UDEL) and eight reanalyses (20CR, CFSR, ERA-40, ERA-Interim, JRA25, MERRA, NARR, and NCEP2) was evaluated over the Canadian Arctic for the 1950-2010 period. The evaluation used the CANGRD dataset, which is based on homogenized temperature and adjusted precipitation from climate stations, as a reference. Dataset agreement and bias were observed to exhibit important spatial, seasonal, and temporal variability over the Canadian Arctic with the largest spread occurring between datasets over mountain and coastal regions and over the Canadian Arctic Archipelago. Reanalysis datasets were typically warmer and wetter than surface observation-based datasets, with CFSR and 20CR exhibiting biases in total annual precipitation on the order of 300 mm. Warm bias in 20CR exceeded 12°C in winter over the western Arctic. Analysis of the temporal consistency of datasets over the 1950-2010 period showed evidence of discontinuities in several datasets as well as a noticeable increase in dataset spread in the period after approximately 2000. Declining station networks, increased automation, and the inclusion of new satellite data streams in reanalyses are potential contributing factors to this phenomenon. Evaluation of trends over the 1950-2010 period showed a relatively consistent picture of warming and increased precipitation over the Canadian Arctic from all datasets, with CANGRD giving moistening trends two times larger than the multi-dataset average related to the adjustment of the station precipitation data. The study results indicate that considerable care is needed when using gridded climate datasets in local or regional scale applications in the Canadian Arctic.

Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas

“…All reanalyses displayed an overall warm bias in agreement with previous studies (e.g. Rapaić et al 2015) with a median bias of +3.4 °C for REM. Contrary to reanalyses, RCMs had a cold bias in TNn with MEM bias of approximately −2.8 °C.…”

“…Trace precipitation amounts for solid precipitation were assigned values from 0.03 to 0.07 mm that varied inversely with latitude following Mekis and Vincent (2011). CFSR, MERRA and ERA-Interim monthly mean temperature and precipitation data were previously evaluated over the Canadian Arctic by Rapaić et al (2015) and over the entire Arctic by Lindsay et al (2014). Both papers indicate that MERRA and ERA-Interim have relatively small warm and wet biases compared to other reanalyses, while CFSR was found to have particularly large positive precipitation biases.…”

“…The only exception was the annual coldest temperature (TNn; Fig. 3k), which is influenced by local scale factors such as proximity to open water and topography that influence inversion layer formation (Rapaić et al 2015). For precipitation indices, the entire domain is characterised by relatively small amounts of precipitation, with most stations having mean annual precipitation rates of less than 1.0 mm/day (Fig.…”

Canadian Snow and Sea Ice: Trends (1981–2015) and Projections (2020–2050)

“…In light of documented differences in gridded temperature datasets over Canada (Rapaic et al, 2015), surface temperature trends were derived from a blend of six reanalysis products: the European Centre for Mid-Range Weather Forecasting…”

Recent changes to the hydrological cycle of an Arctic basin at the tundra–taiga transition

“…4); however, the change point analysis showed an important decrease in the year 1972 from 369 to 321 mm yr −1 for the mean annual precipitation (Table 3). Vincent et al (2015) investigated long-term trends in precipitation records over Canada for the period between 1948 and 2012 using the gridded and spatially interpolated CANGRD dataset (Rapaic et al, 2015). For the region around Havikpak Creek Vincent et al (2015) showed significant spatial variability with a small increase of less than 10 % in annual precipitation.…”