scholarly journals Seasonal Variation of Surface Temperature Change during the Last Several Decades

2011 ◽  
Vol 24 (15) ◽  
pp. 3817-3821 ◽  
Author(s):  
Syukuro Manabe ◽  
Jeffrey Ploshay ◽  
Ngar-Cheung Lau

Abstract Using the historical surface temperature dataset compiled by Climatic Research Unit of the University of East Anglia and the Hadley Centre of the United Kingdom, this study examines the seasonal and latitudinal profile of the surface temperature change observed during the last several decades. It reveals that the recent change in zonal-mean surface air temperature is positive at practically all latitudes. In the Northern Hemisphere, the warming increases with increasing latitude and is large in the Arctic Ocean during much of the year except in summer, when it is small. At the Antarctic coast and in the northern part of the circumpolar ocean (near 55°S), where limited data are available, the changes appear to be small during most seasons, though the warming is notable at the coast in winter. However, this warming is much less than the warming over the Arctic Ocean. The seasonal variation of the surface temperature change appears to be broadly consistent with the result from a global warming experiment that was conducted some time ago using a coupled atmosphere–ocean–land model.

2016 ◽  
Vol 70 (1) ◽  
pp. 19-27
Author(s):  
M Ogi ◽  
S Rysgaard ◽  
DG Barber ◽  
T Nakamura ◽  
B Taguchi

1995 ◽  
Vol 21 ◽  
pp. 91-95 ◽  
Author(s):  
James R. Miller ◽  
Gary L. Russell

A global coupled atmosphere–ocean model is used to examine the hydrologic cycle of the Arctic Ocean. The model has a horizontal resolution of 4° × 5°, nine vertical layers in the atmosphere and 13 in the ocean. River discharge into the Arctic Ocean is included by allowing runoff from each continental grid box to flow downstream according to a specified direction file and a speed that depends on topography. A 74 year control simulation of the present climate is used to examine variability of the hydrologic cycle, including precipitation, sea ice, glacial ice and river discharge. A 74 year transient simulation in which atmospheric CO2increases each year at a compound rate оf 1% is then used to examine potential changes in the hydrologic cycle. Among these changes are a 4°C increase in mean annual surface air temperature in the Arctic Ocean, a decrease in ice cover which begins after 35 years, and increases in river discharge and cloud cover. There is little change in the net difference between precipitation and evaporation. Also in the transient simulation, glacial ice on Greenland decreases relative to the control.


2020 ◽  
Author(s):  
Hongyuan Zheng ◽  
Yuan Gao ◽  
Yinyue Xia ◽  
Haizhen Yang ◽  
Minghong Cai

2021 ◽  
Author(s):  
Marie Sicard ◽  
Masa Kageyama ◽  
Sylvie Charbit ◽  
Pascale Braconnot ◽  
Jean-Baptiste Madeleine

Abstract. The Last Interglacial period (129–116 ka BP) is characterized by a strong orbital forcing which leads to a different seasonal and latitudinal distribution of insolation compared to the pre-industrial period. In particular, these changes amplify the seasonality of the insolation in the high latitudes of the northern hemisphere. Here, we investigate the Arctic climate response to this forcing by comparing the CMIP6 lig127k and pi-Control simulations performed with the IPSL-CM6A-LR model. Using an energy budget framework, we analyse the interactions between the atmosphere, ocean, sea ice and continents. In summer, the insolation anomaly reaches its maximum and causes a near-surface air temperature rise of 3.2 °C over the Arctic region. This warming is primarily due to a strong positive surface downwelling shortwave radiation anomaly over continental surfaces, followed by large heat transfers from the continents back to the atmosphere. The surface layers of the Arctic Ocean also receives more energy, but in smaller quantity than the continents due to a cloud negative feedback. Furthermore, while heat exchanges from the continental surfaces towards the atmosphere are strengthened, the ocean absorbs and stores the heat excess due to a decline in sea ice cover. However, the maximum near-surface air temperature anomaly does not peak in summer like insolation, but occurs in autumn with a temperature increase of 4.0 °C relative to the pre-industrial period. This strong warming is driven by a positive anomaly of longwave radiations over the Arctic ocean enhanced by a positive cloud feedback. It is also favoured by the summer and autumn Arctic sea ice retreat (−1.9 × 106 and −3.4 × 106 km2 respectively), which exposes the warm oceanic surface and allows heat stored by the ocean in summer and water vapour to be released. This study highlights the crucial role of the sea ice cover variations, the Arctic ocean, as well as changes in polar clouds optical properties on the Last Interglacial Arctic warming.


2008 ◽  
Vol 47 (2) ◽  
pp. 411-424 ◽  
Author(s):  
Young-Kwon Lim ◽  
Ming Cai ◽  
Eugenia Kalnay ◽  
Liming Zhou

Abstract The impact of different surface vegetations on long-term surface temperature change is estimated by subtracting reanalysis trends in monthly surface temperature anomalies from observation trends over the last four decades. This is done using two reanalyses, namely, the 40-yr ECMWF (ERA-40) and NCEP–NCAR I (NNR), and two observation datasets, namely, Climatic Research Unit (CRU) and Global Historical Climate Network (GHCN). The basis of the observation minus reanalysis (OMR) approach is that the NNR reanalysis surface fields, and to a lesser extent the ERA-40, are insensitive to surface processes associated with different vegetation types and their changes because the NNR does not use surface observations over land, whereas ERA-40 only uses surface temperature observations indirectly, in order to initialize soil temperature and moisture. As a result, the OMR trends can provide an estimate of surface effects on the observed temperature trends missing in the reanalyses. The OMR trends obtained from observation minus NNR show a strong and coherent sensitivity to the independently estimated surface vegetation from normalized difference vegetation index (NDVI). The correlation between the OMR trend and the NDVI indicates that the OMR trend decreases with surface vegetation, with a correlation < −0.5, indicating that there is a stronger surface response to global warming in arid regions, whereas the OMR response is reduced in highly vegetated areas. The OMR trend averaged over the desert areas (0 < NDVI < 0.1) shows a much larger increase of temperature (∼0.4°C decade−1) than over tropical forest areas (NDVI > 0.4) where the OMR trend is nearly zero. Areas of intermediate vegetation (0.1 < NDVI < 0.4), which are mostly found over midlatitudes, reveal moderate OMR trends (approximately 0.1°–0.3°C decade−1). The OMR trends are also very sensitive to the seasonal vegetation change. While the OMR trends have little seasonal dependence over deserts and tropical forests, whose vegetation state remains rather constant throughout the year, the OMR trends over the midlatitudes, in particular Europe and North America, exhibit strong seasonal variation in response to the NDVI fluctuations associated with deciduous vegetation. The OMR trend rises up approximately to 0.2°–0.3°C decade−1 in winter and early spring when the vegetation cover is low, and is only 0.1°C decade−1 in summer and early autumn with high vegetation. However, the Asian inlands (Russia, northern China with Tibet, and Mongolia) do not show this strong OMR variation despite their midlatitude location, because of the relatively permanent aridity of these regions.


2020 ◽  
Vol 125 (4) ◽  
Author(s):  
Zoé Koenig ◽  
Ilker Fer ◽  
Eivind Kolås ◽  
Trygve O. Fossum ◽  
Petter Norgren ◽  
...  

2014 ◽  
Vol 152 ◽  
pp. 99-108 ◽  
Author(s):  
Daehyun Kang ◽  
Jungho Im ◽  
Myong-In Lee ◽  
Lindi J. Quackenbush

2010 ◽  
Vol 23 (15) ◽  
pp. 4216-4232 ◽  
Author(s):  
Ryan Eastman ◽  
Stephen G. Warren

Abstract Sea ice extent and thickness may be affected by cloud changes, and sea ice changes may in turn impart changes to cloud cover. Different types of clouds have different effects on sea ice. Visual cloud reports from land and ocean regions of the Arctic are analyzed here for interannual variations of total cloud cover and nine cloud types, and their relation to sea ice. Over the high Arctic, cloud cover shows a distinct seasonal cycle dominated by low stratiform clouds, which are much more common in summer than winter. Interannual variations of cloud amounts over the Arctic Ocean show significant correlations with surface air temperature, total sea ice extent, and the Arctic Oscillation. Low ice extent in September is generally preceded by a summer with decreased middle and precipitating clouds. Following a low-ice September there is enhanced low cloud cover in autumn. Total cloud cover appears to be greater throughout the year during low-ice years. Multidecadal trends from surface observations over the Arctic Ocean show increasing cloud cover, which may promote ice loss by longwave radiative forcing. Trends are positive in all seasons, but are most significant during spring and autumn, when cloud cover is positively correlated with surface air temperature. The coverage of summertime precipitating clouds has been decreasing over the Arctic Ocean, which may promote ice loss.


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