A physical model for the global mean surface air temperature anomalies over the past century

1997 ◽  
Vol 42 (8) ◽  
pp. 658-662 ◽  
Author(s):  
Guangyu Shi ◽  
Jiandong Guo ◽  
Xiaobiao Fan ◽  
Lingxia Wang
Keyword(s):  
Physical Model ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Past Century ◽  
Temperature Anomalies ◽  
The Past ◽  
Air Temperature Anomalies ◽  
Global Mean

CMIP5 model simulations of warm Arctic-cold Eurasia pattern in winter surface air temperature anomalies

2020 ◽  
Vol 54 (11-12) ◽  
pp. 4499-4513
Author(s):  
Sai Wang ◽  
Debashis Nath ◽  
Wen Chen ◽  
Tianjiao Ma
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Cmip5 Model ◽  
Model Simulations ◽  
Temperature Anomalies ◽  
Air Temperature Anomalies

40-years of Saharan dust events in the Carpathian Basin: background, frequency, intensity, changing patterns

2020 ◽  
Author(s):  
György Varga ◽  
Nadia Gammoudi ◽  
János Kovács
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Flow Patterns ◽  
Carpathian Basin ◽  
Saharan Dust ◽  
Dust Deposition ◽  
Temperature Anomalies ◽  
Modis Aod ◽  
Dust Events ◽  
Air Temperature Anomalies

<p>Saharan dust events were investigated in the Carpathian Basin (Central Europe) for the period between 1979 and 2018 by using various satellite (TOMS and OMI Aerosol Index; MODIS AOD) and numerical forecast (Barcelona Supercomputing Centre’s DREAM, NMMB/BSC-Dust-model and SKIRON) products and modelled deposition of NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2. The identified 218 episodes were classified into three characteristic clusters based on synoptic background. 700 hPa geopotential height, wind vectors and meridional flow patterns, as well as backward trajectories of the episodes determined the classification.</p><p>Interannual variability of dust activity was remarkable, while seasonal frequencies of the episodes revealed clear spatiotemporal patterns with spring (40.2%) and summer (31.6%) maxima of the events. Mean values of dust deposition showed springtime maxima (44.1%) and dominance of wet deposition (77-93%), while amount of deposited dust material in the other seasons were quite similar, indicating the governing role of local weather conditions (e.g., precipitation patterns). Average warm advection of the episodes was 3.5°C (with spring minima, due to the more rain), but the decadal surface air temperature anomalies showed a general increasing trend.</p><p>Recently, a few more intense wintertime dust deposition events indicated changes in the deterministic atmospheric flow system. Seasonal and decadal zonal mean surface air temperature anomalies of dusty days showed clearly the increased warming of high latitudes during the last few winter episodes. The enhanced meridionality of (dust transporting) winds was also observable in the number of days with 15< m/s meridional wind component (at 700 hPa). Warmer Arctic region and more meandering air flow patterns could be responsible for these unusual dust episodes in the recent years.</p><p>Support of the National Research, Development and Innovation Office NKFIH KH130337 and NKFIH K120213 are gratefully acknowledged.</p>

Improving predictions of surface air temperature anomalies over Japan by Selective Ensemble Mean technique

2020 ◽  
Author(s):  
J. V. Ratnam ◽  
Takeshi Doi ◽  
Yushi Morioka ◽  
Pascal Oettli ◽  
Masami Nonaka ◽  
...  
Keyword(s):  
Air Temperature ◽  
General Circulation ◽  
Surface Air Temperature ◽  
Correlation Coefficients ◽  
Circulation Model ◽  
Skill Score ◽  
Temperature Anomalies ◽  
Selective Ensemble ◽  
Ensemble Mean ◽  
Air Temperature Anomalies

AbstractSelective ensemble mean (SEM) technique is applied to the late spring and summer months (May to August) surface air temperature anomaly predictions of the Scale Interaction Experiment-Frontier Research Center for Global Change Version 2 (SINTEX-F2) coupled general circulation model over Japan. Using the Köppen-Geiger climatic classification we chose four regions over Japan for applying the SEM technique. The SINTEX-F2 ensemble members for the SEM are chosen based on the anomaly correlation coefficients (ACC) of the SINTEX-F2 predicted and observed surface air temperature anomalies. The SEM technique is applied to generate the forecasts of the surface air temperature anomalies for the period 1983 to 2018 using the selected members. Analysis shows the ACC skill score of the SEM prediction to be higher compared to the ACC skill score of predictions obtained by averaging all the 24 members of the SINTEX-F2 (ENSMEAN). The SEM predicted surface air temperature anomalies also have higher hit rate and lower false alarm rate compared to the ENSMEAN predicted anomalies over a range of temperature anomalies. The results indicate the SEM technique to be a simple and easy to apply method to improve the SINTEX-F2 predictions of surface air temperature anomalies over Japan. The better performance of the SEM in generating the surface air temperature anomalies can be partly attributed to realistic prediction of 850hPa geopotential height anomalies over Japan.

Land surface air temperature variations over Eurasia and possible causes in the past century

2017 ◽  
Vol 38 (4) ◽  
pp. 1925-1937 ◽  
Author(s):  
Zhiyan Zuo ◽  
Song Yang ◽  
Kang Xu ◽  
Renhe Zhang ◽  
Qiong He ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Past Century ◽  
Temperature Variations ◽  
The Past ◽  
Air Temperature Variations

scholarly journals On the interchangeability of sea-surface and near-surface air temperature anomalies in climatologies

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Angelo Rubino ◽  
Davide Zanchettin ◽  
Francesco De Rovere ◽  
Michael J. McPhaden
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Sea Surface ◽  
Near Surface ◽  
Temperature Anomalies ◽  
Air Temperature Anomalies

scholarly journals On the scaling effect in global surface air temperature anomalies

2013 ◽  
Vol 13 (10) ◽  
pp. 5243-5253 ◽  
Author(s):  
C. A. Varotsos ◽  
M. N. Efstathiou ◽  
A. P. Cracknell
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Sea Surface ◽  
Scaling Exponents ◽  
Mean Values ◽  
Temperature Anomalies ◽  
Air Temperature Anomalies

Abstract. The annual and the monthly mean values of the land-surface air temperature anomalies from 1880–2011, over both hemispheres, are used to investigate the existence of long-range correlations in their temporal evolution. The analytical tool employed is the detrended fluctuation analysis, which eliminates the noise of the non-stationarities that characterize the land-surface air temperature anomalies in both hemispheres. The reliability of the results obtained from this tool (e.g., power-law scaling) is investigated, especially for large scales, by using error bounds statistics, the autocorrelation function (e.g., rejection of its exponential decay) and the method of local slopes (e.g., their constancy in a sufficient range). The main finding is that deviations of one sign of the land-surface air temperature anomalies in both hemispheres are generally followed by deviations with the same sign at different time intervals. In other words, the land-surface air temperature anomalies exhibit persistent behaviour, i.e., deviations tend to keep the same sign. Taking into account our earlier study, according to which the land and sea surface temperature anomalies exhibit scaling behaviour in the Northern and Southern Hemisphere, we conclude that the difference between the scaling exponents mainly stems from the sea surface temperature, which exhibits a stronger memory in the Southern than in the Northern Hemisphere. Moreover, the variability of the scaling exponents of the annual mean values of the land-surface air temperature anomalies versus latitude shows an increasing trend from the low latitudes to polar regions, starting from the classical random walk (white noise) over the tropics. There is a gradual increase of the scaling exponent from low to high latitudes (which is stronger over the Southern Hemisphere).

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