Leading interannual variability modes of East Asian winter precipitation in CMIP5 general circulation models

2018 ◽  
Vol 76 (2) ◽  
pp. 177-189
Author(s):  
C Jin ◽  
Y Yang ◽  
W Guo
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
East Asian ◽  
General Circulation Models ◽  
Winter Precipitation

The Climatology and Interannual Variability of East Asian Summer Monsoon in CMIP5 Coupled Models: Does Air–Sea Coupling Improve the Simulations?

2014 ◽  
Vol 27 (23) ◽  
pp. 8761-8777 ◽  
Author(s):  
Fengfei Song ◽  
Tianjun Zhou
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
East Asian Summer Monsoon ◽  
General Circulation ◽  
Asian Summer Monsoon ◽  
East Asian ◽  
General Circulation Models ◽  
Surface Evaporation ◽  
Asian Summer ◽  
High Skill

Abstract The climatology and interannual variability of the East Asian summer monsoon (EASM) simulated by 34 coupled general circulation models (CGCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated. To estimate the role of air–sea coupling, 17 CGCMs are compared to their corresponding atmospheric general circulation models (AGCMs). The climatological low-level monsoon circulation and mei-yu/changma/baiu rainfall band are improved in CGCMs from AGCMs. The improvement is at the cost of the local cold sea surface temperature (SST) biases in CGCMs, since they decrease the surface evaporation and enhance the circulation. The interannual EASM pattern is evaluated by a skill formula and the highest/lowest eight models are selected to investigate the skill origins. The observed Indian Ocean (IO) warming, tropical eastern Indian Ocean (TEIO) rainfall anomalies, and Kelvin wave response are captured well in high-skill models, while these features are not present in low-skill models. Further, the differences in the IO warming between high-skill and low-skill models are rooted in the preceding ENSO simulation. Hence, the IO–western Pacific anticyclone (WPAC) teleconnection is important for CGCMs, similar to AGCMs. However, compared to AGCMs, the TEIO SST anomaly is warmer in CGCMs, since the easterly wind anomalies in the southern flank of the WPAC reduce the climatological monsoon westerlies and decrease the surface evaporation. The warmer TEIO induces the stronger precipitation anomaly and intensifies the teleconnection. Hence, the interannual EASM pattern is better simulated in CGCMs than that in AGCMs.

scholarly journals Contributors to linkage between Arctic warming and East Asian winter climate

2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Wave Train ◽  
East Asian ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
The Arctic ◽  
Winter Climate ◽  
Arctic Warming

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.

scholarly journals An Assessment of GCM Skill in Simulating Persistence across Multiple Time Scales

2011 ◽  
Vol 24 (14) ◽  
pp. 3609-3623 ◽  
Author(s):  
Fiona Johnson ◽  
Seth Westra ◽  
Ashish Sharma ◽  
Andrew J. Pitman
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Large Scale ◽  
Low Frequency ◽  
General Circulation Models ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Max Planck ◽  
Reservoir Storage ◽  
Low Frequency Variability

Abstract Climate change impact studies for water resource applications, such as the development of projections of reservoir yields or the assessment of likely frequency and amplitude of drought under a future climate, require that the year-to-year persistence in a range of hydrological variables such as catchment average rainfall be properly represented. This persistence is often attributable to low-frequency variability in the global sea surface temperature (SST) field and other large-scale climate variables through a complex sequence of teleconnections. To evaluate the capacity of general circulation models (GCMs) to accurately represent this low-frequency variability, a set of wavelet-based skill measures has been developed to compare GCM performance in representing interannual variability with the observed global SST data, as well as to assess the extent to which this variability is imparted in precipitation and surface pressure anomaly fields. A validation of the derived skill measures is performed using GCM precipitation as an input in a reservoir storage context, with the accuracy of reservoir storage estimates shown to be improved by using GCM outputs that correctly represent the observed low-frequency variability. Significant differences in the performance of different GCMs is demonstrated, suggesting that judicious selection of models is required if the climate impact assessment is sensitive to low-frequency variability. The two GCMs that were found to exhibit the most appropriate representation of global low-frequency variability for individual variables assessed were the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ECHAM4 and L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4); when considering all three variables, the Max Planck Institute (MPI) ECHAM5 performed well. Importantly, models that represented interannual variability well for SST also performed well for the other two variables, while models that performed poorly for SST also had consistently low skill across the remaining variables.

scholarly journals Seasonal Forecasts of Canadian Winter Precipitation by Postprocessing GCM Integrations

2008 ◽  
Vol 136 (3) ◽  
pp. 769-783 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet ◽  
Jacques Derome
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Winter Precipitation ◽  
Second Phase ◽  
Seasonal Forecasts ◽  
Large Area ◽  
Ensemble Forecasts ◽  
The North ◽  
Ensemble Mean

Abstract In the second phase of the Canadian Historical Forecasting Project (HFP2), four global atmospheric general circulation models (GCMs) were used to perform seasonal forecasts over the period of 1969–2003. Little predictive skill was found from the uncalibrated GCM ensemble seasonal predictions for the Canadian winter precipitation. This study is an effort to improve the precipitation forecasts through a postprocessing approach. Canadian winter precipitation is significantly influenced by two of the most important atmospheric large-scale patterns: the Pacific–North American pattern (PNA) and the North Atlantic Oscillation (NAO). The time variations of these two patterns were found to be significantly correlated with those of the leading singular value decomposition (SVD) modes that relate the ensemble mean forecast 500-mb geopotential height over the Northern Hemisphere and the tropical Pacific SST in the previous month (November). A statistical approach to correct the ensemble forecasts was formulated based on the regression of the model’s leading forced SVD patterns and the observed seasonal mean precipitation. The performance of the corrected forecasts was assessed by comparing its cross-validated skill with that of the original GCM ensemble mean forecasts. The results show that the corrected forecasts predict the Canadian winter precipitation with statistically significant skill over the southern prairies and a large area of Québec–Ontario.

Improving the Prediction of Winter Precipitation and Temperature over the Continental United States: Role of the ENSO State in Developing Multimodel Combinations

2010 ◽  
Vol 138 (6) ◽  
pp. 2447-2468 ◽  
Author(s):  
Naresh Devineni ◽  
A. Sankarasubramanian
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Winter Precipitation ◽  
Skill Levels ◽  
Higher Weights ◽  
Atmospheric General Circulation Models ◽  
Multimodel Ensembles ◽  
Precipitation And Temperature

Abstract Recent research into seasonal climate prediction has focused on combining multiple atmospheric general circulation models (GCMs) to develop multimodel ensembles. A new approach to combining multiple GCMs is proposed by analyzing the skill levels of candidate models contingent on the relevant predictor(s) state. To demonstrate this approach, historical simulations of winter (December–February, DJF) precipitation and temperature from seven GCMs were combined by evaluating their skill—represented by mean square error (MSE)—over similar predictor (DJF Niño-3.4) conditions. The MSE estimates are converted into weights for each GCM for developing multimodel tercile probabilities. A total of six multimodel schemes are considered that include combinations based on pooling of ensembles as well as on the long-term skill of the models. To ensure the improved skill exhibited by the multimodel scheme is statistically significant, rigorous hypothesis tests were performed comparing the skill of multimodels with each individual model’s skill. The multimodel combination contingent on Niño-3.4 shows improved skill particularly for regions whose winter precipitation and temperature exhibit significant correlation with Niño-3.4. Analyses of these weights also show that the proposed multimodel combination methodology assigns higher weights for GCMs and lesser weights for climatology during El Niño and La Niña conditions. On the other hand, because of the limited skill of GCMs during neutral Niño-3.4 conditions, the methodology assigns higher weights for climatology resulting in improved skill from the multimodel combinations. Thus, analyzing GCMs’ skill contingent on the relevant predictor state provides an alternate approach for multimodel combinations such that years with limited skill could be replaced with climatology.

Modeling Climate Limits of Plants Found in Sonoran Desert Packrat Middens

2002 ◽  
Vol 58 (2) ◽  
pp. 112-121 ◽  
Author(s):  
Samantha Thompson Arundel
Keyword(s):  
Sonoran Desert ◽  
General Circulation ◽  
Monsoon Rainfall ◽  
Climatic Factors ◽  
Meteorological Data ◽  
Warm Season ◽  
General Circulation Models ◽  
Winter Precipitation ◽  
Simultaneous Increase ◽  
Cool Season

AbstractGeostatistical analyses of 35 plant species from 213 packrat middens with combined records spanning the last 40,000 yr indicate that many presumed winter precipitation-dependent taxa that existed in the Sonoran Desert during the last glaciation were expelled by increasing monsoon precipitation instead of waning cool-season moisture. The statistical influence of excessive monsoon rainfall on the distributions of many species probably reflects the simultaneous increase in the magnitude and occurrence of fire. During the early Holocene, results indicate a dramatic decrease in cool-season precipitation and an increase in monsoon rainfall. Levels of temperature and precipitation continued to change linearly until they reached modern values. These conclusions are drawn from a newly developed computer model that determines which climatic factors impede species movement into an unoccupied region. Climatic “limiters,” derived from digital versions of modern plant distributions, elevation, and meteorological data, formed the basis of the reconstructions. Particularly important distribution limiters for the Sonoran Desert include maximum warm-season precipitation and low winter temperatures. The model allows for quantitative estimates of past climatic changes with relatively detailed temporal and spatial resolutions. These results can be used to refine paleoclimatic interpretations based on coarser resolution General Circulation Models.

scholarly journals Application of Dynamical and Statistical Downscaling to East Asian Summer Precipitation for Finely Resolved Datasets

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yoo-Bin Yhang ◽  
Soo-Jin Sohn ◽  
Il-Won Jung
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Dynamical Downscaling ◽  
Asian Summer Monsoon ◽  
East Asian ◽  
Value Added ◽  
Summer Precipitation ◽  
General Circulation Models ◽  
Coarse Spatial Resolution ◽  
Asian Summer

Various downscaling approaches have been developed to overcome the limitation of the coarse spatial resolution of general circulation models (GCMs). Such techniques can be grouped into two approaches of dynamical and statistical downscaling. In this study, we investigated the performances of different downscaling methods, focusing on East Asian summer monsoon precipitation to obtain more finely resolved and value added datasets. The dynamical downscaling was conducted by the Regional Model Program (RMP) of the Global/Regional Integrated Model system (GRIMs), while the statistical downscaling was performed through coupled pattern-based simple linear regression. The dynamical downscaling resulted in a better representation of the spatial distribution and long-term trend than the GCM produced; however, it tended to overestimate precipitation over East Asia. In contrast, the application of the statistical downscaling resulted in a bias in the amount of precipitation, due to low variance that is inherent in regression-based downscaling. A combination of dynamical and statistical downscaling produced the best results in time and space. This study provides a guideline for determining the most effective and robust downscaling method in the hydrometeorological applications, which are quite sensitive to the accuracy of downscaled precipitation.

scholarly journals A Comparative Analysis of Change in the First and Second Moment of the PDF of Seasonal Mean 200-mb Heights with ENSO SSTs

2009 ◽  
Vol 22 (6) ◽  
pp. 1412-1423 ◽  
Author(s):  
Bhaskar Jha ◽  
Arun Kumar
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
General Circulation Models ◽  
Seasonal Forecast ◽  
Seasonal Predictability ◽  
Second Moment ◽  
Sst Variability ◽  
Atmospheric General Circulation Models ◽  
The Mean ◽  
Probability Density Function Pdf

Abstract Based on simulations from nine different atmospheric general circulation models (AGCMs), a comparative assessment of the influence of ENSO SST variability on the first and second moment of the probability density function (PDF) of 200-mb seasonal mean height is made. This comparison is quantified by regressing the interannual variability in the mean and the spread of the seasonal means against the Niño-3.4 SSTs. Based on the analysis of simulations from multiple AGCMs, it is concluded that the relative impact of interannual variability of SSTs is larger, and more systematic, on the mean of the PDF of 200-mb heights than on its spread. This result implies that seasonal predictability due to SSTs is predominantly a function of its influence on the seasonal mean. Further, for the practice of seasonal predictions, it might be pragmatic to assume that spread of seasonal means stays constant and that the seasonal forecast information resides entirely in the shift of the seasonal mean PDF.

scholarly journals Statistical–Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation

2005 ◽  
Vol 18 (11) ◽  
pp. 1831-1843 ◽  
Author(s):  
Michael K. Tippett ◽  
Lisa Goddard ◽  
Anthony G. Barnston
Keyword(s):  
General Circulation ◽  
Forecast Error ◽  
General Circulation Models ◽  
Winter Precipitation ◽  
Precipitation Variability ◽  
Severe Drought ◽  
Seasonal Forecasts ◽  
Dynamical Method ◽  
Sst Forcing ◽  
Atmospheric General Circulation Models

Abstract Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region’s interannual precipitation variability. The statistical–dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo–west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical–dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December–March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical–dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03. May Kabul be without gold, but not without snow. —Traditional Afghan proverb

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