scholarly journals Some peculiarities of the near-surface air temperature change in the Antarctic Peninsula region

2014 ◽  
pp. 110-123 ◽  
Author(s):  
V.E. Tymofeyev ◽  
Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 360
Author(s):  
Michael Matějka ◽  
Kamil Láska ◽  
Klára Jeklová ◽  
Jiří Hošek

The Antarctic Peninsula belongs to the regions of the Earth that have seen the highest increase in air temperature in the past few decades. The warming is reflected in degradation of the cryospheric system. The impact of climate variability and interactions between the atmosphere and the cryosphere can be studied using numerical atmospheric models. In this study, the standard version of the Weather Research and Forecasting (WRF) model was validated on James Ross Island in the northern part of the Antarctic Peninsula. The aim of this study was to verify the WRF model output at 700 m horizontal resolution using air temperature, wind speed and wind direction observations from automatic weather stations on the Ulu Peninsula, the northernmost part of James Ross Island. Validation was carried out for two contrasting periods (summer and winter) in 2019/2020 to assess possible seasonal effects on model accuracy. Simulated air temperatures were in very good agreement with measurements (mean bias −1.7 °C to 1.4 °C). The exception was a strong air temperature inversion during two of the winter days when a significant positive bias occurred at the coastal and lower-altitude locations on the Ulu Peninsula. Further analysis of the WRF estimates showed a good skill in simulating near-surface wind speed with higher correlation coefficients in winter (0.81–0.93) than in summer (0.41–0.59). However, bias and RMSE for wind speed tended to be better in summer. The performance of three WRF boundary layer schemes (MYJ, MYNN, QNSE) was further evaluated. The QNSE scheme was generally more accurate than MYNN and MYJ, but the differences were quite small and varied with time and place. The MYNN and QNSE schemes tended to achieve better wind speed simulation quality than the MYJ scheme. The model successfully captured wind direction, showing only slight differences to the observed values. It was shown that at lower altitudes the performance of the model can vary greatly with time. The model results were more accurate during high wind speed southwestern flow, while the accuracy decreased under weak synoptic-scale forcing, accompanied by an occurrence of mesoscale atmospheric processes.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Min Xu ◽  
Lejiang Yu ◽  
Kaixin Liang ◽  
Timo Vihma ◽  
Deniz Bozkurt ◽  
...  

AbstractNear-surface air temperature at the Argentinian research base Esperanza on the northern tip of the Antarctic Peninsula reached 18.3 °C on 6 February 2020, which is the highest temperature ever recorded on the entire Antarctic continent. Here we use weather observations since 1973 together with the ERA5 reanalysis to investigate the circulation that shaped the 2020 event, and its context over the past decades. We find that, during the 2020 event, a high-pressure ridge over the 40°-100°W sector and a blocking high on the Drake Passage led to an anticyclonic circulation that brought warm and moist air from the Pacific Ocean to the Antarctic Peninsula. Vertical air flows in a foehn warming event dominated by sensible heat and radiation made the largest contribution to the abrupt warming. A further analysis with 196 extreme warm events in austral summer between 1973 and 2020 suggests that the mechanisms behind the 2020 event form one of the two most common clusters of the events, exhibiting that most of the extreme warm events at Esperanza station are linked to air masses originating over the Pacific Ocean.


2004 ◽  
Vol 50 (169) ◽  
pp. 257-267 ◽  
Author(s):  
Elizabeth M. Morris ◽  
Robert Mulvaney

AbstractOver the period 1972–98 the height of the snow surface at eight Antarctic sites in Palmer Land and on Alexander Island has been measured with respect to fixed points on local nunataks. From these data an empirical relation between height changes over a given period and three key variables has been derived. These variables are (i) the local mean annual surface air temperature, (ii) a regional estimate of energy available for melt over the period (derived from the nearby Rothera air-temperature record) and (iii) a regional estimate of accumulation over the period (derived from the nearby Gomez Nunatak ice-core accumulation record). Using this relation, the contribution of the Antarctic Peninsula to sea-level rise for warming from climatic conditions (averaged over the last 30 years) is estimated to be −0.006 ± 0.002 mm a−1 K−1. If recent warm conditions persist, however, and meltwater can run off to the sea, the contribution to sea-level rise from ablation is calculated to be 0.07 ± 0.02 mm a−1 K−1.


2014 ◽  
Vol 27 (3) ◽  
pp. 1143-1167 ◽  
Author(s):  
Zengyun Hu ◽  
Chi Zhang ◽  
Qi Hu ◽  
Hanqin Tian

Abstract The arid and semiarid region in central Asia is sensitive and vulnerable to climate variations. However, the sparse and highly unevenly distributed meteorological stations in the region provide limited data for understanding of the region’s climate variations. In this study, the near-surface air temperature change in central Asia from 1979 to 2011 was examined using observations from 81 meteorological stations, three local observation validated reanalysis datasets of relatively high spatial resolutions, and the Climate Research Unit (CRU) dataset. Major results suggested that the three reanalysis datasets match well with most of the local climate records, especially in the low-lying plain areas. The consensus of the multiple datasets showed significant regional surface air temperature increases of 0.36°–0.42°C decade−1 in the past 33 years. No significant contributions from declining irrigation and urbanization to temperature change were found. The rate is larger in recent years than in the early years in the study period. Additionally, unlike in many regions in the world, the temperature in winter showed no increase in central Asia in the last three decades, a noticeable departure from the global trend in the twentieth century. The largest increase in surface temperature was occurring in the spring season. Analyses further showed a warming center in the middle of the central Asian states and weakened temperature variability along the northwest–southeast temperature gradient from the northern Kazakhstan to southern Xinjiang. The reanalysis datasets also showed significant negative correlations between temperature increase rate and elevation in this complex terrain region.


Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 217
Author(s):  
Jiangping Zhu ◽  
Aihong Xie ◽  
Xiang Qin ◽  
Yetang Wang ◽  
Bing Xu ◽  
...  

The European Center for Medium-Range Weather Forecasts (ECMWF) released its latest reanalysis dataset named ERA5 in 2017. To assess the performance of ERA5 in Antarctica, we compare the near-surface temperature data from ERA5 and ERA-Interim with the measured data from 41 weather stations. ERA5 has a strong linear relationship with monthly observations, and the statistical significant correlation coefficients (p < 0.05) are higher than 0.95 at all stations selected. The performance of ERA5 shows regional differences, and the correlations are high in West Antarctica and low in East Antarctica. Compared with ERA5, ERA-Interim has a slightly higher linear relationship with observations in the Antarctic Peninsula. ERA5 agrees well with the temperature observations in austral spring, with significant correlation coefficients higher than 0.90 and bias lower than 0.70 °C. The temperature trend from ERA5 is consistent with that from observations, in which a cooling trend dominates East Antarctica and West Antarctica, while a warming trend exists in the Antarctic Peninsula except during austral summer. Generally, ERA5 can effectively represent the temperature changes in Antarctica and its three subregions. Although ERA5 has bias, ERA5 can play an important role as a powerful tool to explore the climate change in Antarctica with sparse in situ observations.


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