The accuracy of climate variability and trends across Arctic Fennoscandia in four reanalyses

• Published in: International Journal of Climatology
• Main Authors: Marshall, Gareth J., Kivinen, Sonja, Jylha, Kirsti, Vignols, Rebecca M., Rees, W.G.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Royal Meteorological Society 2018
• Subjects: Arctic; Merra; Climate change; Fennoscandia
• Online Access: http://nora.nerc.ac.uk/id/eprint/518735/; https://nora.nerc.ac.uk/id/eprint/518735/1/Marshall_et_al-2018-International_Journal_of_Climatology.pdf; https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.5541

Arctic Fennoscandia has undergone significant climate change over recent decades. Reanalysis data sets allow us to understand the atmospheric processes driving such changes. Here we evaluate four reanalyses against observations of near‐surface air temperature (SAT) and precipitation (PPN) from 35 meteorological stations across the region for the 35‐year period from 1979 to 2013. The reanalyses compared are the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), the European Centre for Medium‐Range Weather Forecast (ECMWF) Interim reanalysis (ERA‐Interim), the Japanese Meteorological Agency (JMA) 55‐year reanalysis (JRA‐55) and National Aeronautics and Space Administration (NASA)’s Modern‐Era Retrospective Analysis for Research and Applications (MERRA). All four reanalyses have an overall small cool bias across Arctic Fennoscandia, with MERRA typically ~1 °C cooler than the others. They generally reproduce the broad spatial patterns of mean SAT across the region, although less well in areas of complex orography. Observations reveal a statistically significant warming across Arctic Fennoscandia, with the majority of trends significant at p < .01. Three reanalyses show similar regional warming but of smaller magnitude while CFSR is anomalous, even having a slight cooling in some areas. In general, the other reanalyses are sufficiently accurate to reproduce the varying significance of observed seasonal trends. There are much greater differences between the reanalyses when comparing PPN to observations. MERRA‐Land, which merges a gauge‐based data set, is clearly the best: CFSR is the least successful, with a significant wet bias. The smoothed reanalysis orography means that the high PPN associated with the western side of the Scandinavian Mountains extends too far inland. Spatial patterns of PPN trends across the region differ markedly between the reanalyses, which have varying success at matching observations and generally fail to replicate sites with significant ...