| Abstract |
Understanding the changes in Greenland's temperature is important for assessing and predicting the mass of the Greenland ice sheet, which plays an important role in sea level rise. In this study, we analyzed the annual and seasonal coastal Greenland's temperatures during the period 1952–2017 (focusing on the period 2013–2017) based on a dataset obtained from the Danish Meteorological Institute (DMI). Overall, the annual coastal Greenland's temperature increased during 1952–2017 at a rate of 0.23 °C decade⁻¹, especially in the southeastern (0.70 °C decade⁻¹) and northern (0.42 °C decade⁻¹) regions of the island. From the changes in the seasonal coastal Greenland's composite temperature (CT), winter exhibited the largest change rate (0.28 °C decade⁻¹), and the summer CT increased by 0.25 °C decade⁻¹, while the spring CT increased by 0.17 °C decade⁻¹ with less variation. The temperature increase accelerated during 2013–2017 according to Mann-Kendall (M-K) tests, especially in the northeastern and northern regions of the island. The seasonal temperature change of the whole island decreased in the following order: annual > autumn > summer > winter > spring. We also analyzed the annual inland temperature change during the period 1997–2017 based on a dataset obtained from the Greenland Climate Network; the results indicated that the inland temperature increased by 0.13 °C decade⁻¹. Pearson correlation analysis was used to determine the teleconnection relationship between the coastal temperatures and large-scale atmosphere-ocean climate indexes, and we found that the Greenland Blocking Index (GBI), Atlantic Multidecadal Oscillation (AMO), Tropical Northern Atlantic Index (TNA), North Tropical Atlantic Index (NTA), Caribbean Index (CAR), Atlantic Meridional Mode (AMM), East Atlantic (EA) and Western Hemisphere warm pool (WHWP) have significant positive correlations with the coastal temperature in most months, except in February and May. However, the North Atlantic Oscillation (NAO), Arctic Oscillation (AO) and Eastern Asia/Western Russia (EAWR) show significant negative correlations with temperature. Overall, there exists a time lag effect between the climate indexes (except for the GBI, AO and NAO) and temperature. From the application of the random forest model, we found that the GBI, NAO, CO₂, AMO, N₂O, SF₆, CH₄, and Northern Oscillation Index (NOI) are the most important variables that influenced the CT changes during 1979–2017. Finally, we calculated the contribution rates of the most important variables to temperature change during the period 1979–2017 and showed that the contribution rates of the GBI, CO₂ and NOI to temperature change were 47.30%, 35.68%, and 17.02%, respectively.
|
