Probabilistic multimodel ensemble prediction of decadal variability of East Asian surface air temperature based on IPCC-AR5 near-term climate simulations

2013 ◽  
Vol 30 (4) ◽  
pp. 1129-1142 ◽  
Author(s):  
Jia Wang ◽  
Xiefei Zhi ◽  
Yuwen Chen
Keyword(s):  
Air Temperature ◽  
Decadal Variability ◽  
East Asian ◽  
Surface Air Temperature ◽  
Ensemble Prediction ◽  
Multimodel Ensemble ◽  
Climate Simulations ◽  
Near Term

scholarly journals Air Temperature and Anthropogenic Forcing: Insights from the Solid Earth

2011 ◽  
Vol 24 (2) ◽  
pp. 569-574 ◽  
Author(s):  
Jean O. Dickey ◽  
Steven L. Marcus ◽  
Olivier de Viron
Keyword(s):  
Air Temperature ◽  
Decadal Variability ◽  
Surface Air Temperature ◽  
Radiation Budget ◽  
Cloud Formation ◽  
Length Of Day ◽  
Anthropogenic Forcing ◽  
The Core ◽  
Earth’S Radiation Budget ◽  
Gas Effect

Abstract Earth’s rotation rate [i.e., length of day (LOD)], the angular momentum of the core (CAM), and surface air temperature (SAT) all have decadal variability. Previous investigators have found that the LOD fluctuations are largely attributed to core–mantle interactions and that the SAT is strongly anticorrelated with the decadal LOD. It is shown here that 1) the correlation among these three quantities exists until 1930, at which time anthropogenic forcing becomes highly significant; 2) correcting for anthropogenic effects, the correlation is present for the full span with a broadband variability centered at 78 yr; and 3) this result underscores the reality of anthropogenic temperature change, its size, and its temporal growth. The cause of this common variability needs to be further investigated and studied. Since temperature cannot affect the CAM or LOD to a sufficient extent, the results favor either a direct effect of Earth’s core-generated magnetic field (e.g., through the modulation of charged-particle fluxes, which may impact cloud formation) or a more indirect effect of some other core process on the climate—or yet another process that affects both. In all three cases, their signals would be much smaller than the anthropogenic greenhouse gas effect on Earth’s radiation budget during the coming century.

scholarly journals Quantifying the contribution of anthropogenic influence to the East Asian winter monsoon in 1960–2012

2019 ◽  
Vol 19 (15) ◽  
pp. 9903-9911
Author(s):  
Xin Hao ◽  
Shengping He ◽  
Huijun Wang ◽  
Tingting Han
Keyword(s):  
Air Temperature ◽  
General Circulation ◽  
East Asian Winter Monsoon ◽  
East Asian ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Winter Monsoon ◽  
Anthropogenic Influence ◽  
Anthropogenic Forcing ◽  
Asian Winter Monsoon

Abstract. The East Asian winter monsoon (EAWM) is greatly influenced by many factors that can be classified as anthropogenic forcing and natural forcing. Here we explore the contribution of anthropogenic influence to the change in the EAWM over the past decades. Under all forcings observed during 1960–2013 (All-Hist run), the atmospheric general circulation model is able to reproduce the climatology and variability of the EAWM-related surface air temperature and 500 hPa geopotential height and shows a statistically significant decreasing EAWM intensity with a trend coefficient of ∼-0.04 yr−1, which is close to the observed trend. By contrast, the simulation, which is driven by the same forcing as the All-Hist run but with the anthropogenic contribution to them removed, shows no decreasing trend in the EAWM intensity. By comparing the simulations under two different forcing scenarios, we further reveal that the responses of the EAWM to the anthropogenic forcing include a rise of 0.6∘ in surface air temperature over East Asia as well as weakening of the East Asian trough, which may result from the poleward expansion and intensification of the East Asian jet forced by the change in temperature gradient in the troposphere. Additionally, compared with the simulation without anthropogenic forcing, the frequency of strong (weak) EAWM occurrence is reduced (increased) by 45 % (from 0 to 10/7). These results indicate that the weakening of the EAWM during 1960–2013 may be mainly attributed to the anthropogenic influence.

scholarly journals Quantifying the contribution of anthropogenic influence to the East Asian winter monsoon in 1960–2012

2019 ◽  
Author(s):  
Xin Hao ◽  
Shengping He ◽  
Huijun Wang ◽  
Tingting Han
Keyword(s):  
East Asia ◽  
Air Temperature ◽  
General Circulation ◽  
East Asian Winter Monsoon ◽  
East Asian ◽  
Surface Air Temperature ◽  
Winter Monsoon ◽  
Anthropogenic Influence ◽  
Anthropogenic Forcing ◽  
Asian Winter Monsoon

Abstract. The East Asian winter monsoon (EAWM) can be greatly influenced by many factors that can be classified as anthropogenic forcing and natural forcing. Here we explore the contribution of anthropogenic influence to the change in the EAWM over the past decades. Under all forcings observed during 1960–2013 (All-Hist run), the atmospheric general circulation model is able to reproduce the climatology and variability of the EAWM-related surface air temperature and 500 hPa geopotential height, and shows a statistically significant decreasing EAWM intensity with a trend coefficient of ∼−0.04 yr−1 which is close to the observed trend. By contrast, the simulation, which is driven by the same forcing as All-Hist run but with the anthropogenic contribution to them removed, shows no decreasing trend in the EAWM intensity. By comparing the simulations under two different forcing scenarios, we further reveal that the responses of the EAWM to the anthropogenic forcing include a rise of 0.6 ° in surface air temperature over the East Asia as well as weakening of the East Asia trough, which may result from the poleward expansion and intensification of the East Asian jet forced by the change of temperature gradient in the troposphere. Additionally, compared with the simulation without anthropogenic forcing, the frequency of strong (weak) EAWM occurrence is reduced (increased) by 45 % (from 0 to 10/7). These results indicate that the weakening of the EAWM during 1960–2013 may be mainly attributed to the anthropogenic influence.

scholarly journals Seasonal Prediction of Surface Air Temperature across Vietnam Using the Regional Climate Model Version 4.2 (RegCM4.2)

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Tan Phan Van ◽  
Hiep Van Nguyen ◽  
Long Trinh Tuan ◽  
Trung Nguyen Quang ◽  
Thanh Ngo-Duc ◽  
...  
Keyword(s):  
Air Temperature ◽  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Seasonal Prediction ◽  
Ensemble Prediction ◽  
Model Bias ◽  
Skill Scores ◽  
Model Predictions

To investigate the ability of dynamical seasonal climate predictions for Vietnam, the RegCM4.2 is employed to perform seasonal prediction of 2 m mean (T2m), maximum (Tx), and minimum (Tn) air temperature for the period from January 2012 to November 2013 by downscaling the NCEP Climate Forecast System (CFS) data. For model bias correction, the model and observed climatology is constructed using the CFS reanalysis and observed temperatures over Vietnam for the period 1980–2010, respectively. The RegCM4.2 forecast is run four times per month from the current month up to the next six months. A model ensemble prediction initialized from the current month is computed from the mean of the four runs within the month. The results showed that, without any bias correction (CTL), the RegCM4.2 forecast has very little or no skill in both tercile and value predictions. With bias correction (BAS), model predictions show improved skill. The experiment in which the results from the BAS experiment are further successively adjusted (SUC) with model bias at one-month lead time of the previous run showed further improvement compared to CTL and BAS. Skill scores of the tercile probability forecasts were found to exceed 0.3 for most of the target months.

scholarly journals The Effects of Gridding Algorithms on the Statistical Moments and Their Trends of Daily Surface Air Temperature*

2015 ◽  
Vol 28 (23) ◽  
pp. 9188-9205 ◽  
Author(s):  
Nicholas R. Cavanaugh ◽  
Samuel S. P. Shen
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climate Models ◽  
Decadal Variability ◽  
Surface Air Temperature ◽  
Higher Order ◽  
Statistical Moments ◽  
Weighted Sums ◽  
Higher Order Moments ◽  
Station Data

Abstract This paper explores the effects from averaging weather station data onto a grid on the first four statistical moments of daily minimum and maximum surface air temperature (SAT) anomalies over the entire globe. The Global Historical Climatology Network–Daily (GHCND) and the Met Office Hadley Centre GHCND (HadGHCND) datasets from 1950 to 2010 are examined. The GHCND station data exhibit large spatial patterns for each moment and statistically significant moment trends from 1950 to 2010, indicating that SAT probability density functions are non-Gaussian and have undergone characteristic changes in shape due to decadal variability and/or climate change. Comparisons with station data show that gridded averages always underestimate observed variability, particularly in the extremes, and have altered moment trends that are in some cases opposite in sign over large geographic areas. A statistical closure approach based on the quasi-normal approximation is taken to explore SAT’s higher-order moments and point correlation structure. This study focuses specifically on relating variability calculated from station data to that from gridded data through the moment equations for weighted sums of random variables. The higher-order and nonlinear spatial correlations up to the fourth order demonstrate that higher-order moments at grid scale can be determined approximately by functions of station pair correlations that tend to follow the usual Kolmogorov scaling relation. These results can aid in the development of constraints to reduce uncertainties in climate models and have implications for studies of atmospheric variability, extremes, and climate change using gridded observations.

scholarly journals Influence of the NAO on Wintertime Surface Air Temperature over East Asia: Multidecadal Variability and Decadal Prediction

2021 ◽  
Author(s):  
Jianping Li ◽  
Tiejun Xie ◽  
Xinxin Tang ◽  
Hao Wang ◽  
Cheng Sun ◽  
...  
Keyword(s):  
East Asia ◽  
Air Temperature ◽  
East Asian ◽  
Surface Air Temperature ◽  
Atlantic Multidecadal Oscillation ◽  
Warming Trend ◽  
Decadal Prediction ◽  
Delayed Effect ◽  
Multidecadal Variability ◽  
Cold Events

AbstractIn this paper, we investigate the influence of the winter NAO on the multidecadal variability of winter East Asian surface air temperature (EASAT) and EASAT decadal prediction. The observational analysis shows that the winter EASAT and East Asian minimum SAT (EAmSAT) display strong in-phase fluctuations and a significant 60–80-year multidecadal variability, apart from a long-term warming trend. The winter EASAT experienced a decreasing trend in the last two decades, which is consistent with the occurrence of extremely cold events in East Asia winters in recent years. The winter NAO leads the detrended winter EASAT by 12–18 years with the greatest significant positive correlation at the lead time of 15 years. Further analysis shows that ENSO may affect winter EASAT interannual variability, but does not affect the robust lead relationship between the winter NAO and EASAT. We present the coupled oceanic-atmospheric bridge (COAB) mechanism of the NAO influences on winter EASAT multidecadal variability through its accumulated delayed effect of ∼15 years on the Atlantic Multidecadal Oscillation (AMO) and Africa-Asia multidecadal teleconnection (AAMT) pattern. An NAO-based linear model for predicting winter decadal EASAT is constructed on the principle of the COAB mechanism, with good hindcast performance. The winter EASAT for 2020–34 is predicted to keep on fluctuating downward until ∼2025, implying a high probability of occurrence of extremely cold events in coming winters in East Asia, followed by a sudden turn towards sharp warming. The predicted 2020/21 winter EASAT is almost the same as the 2019/20 winter.

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