The application of a single-model ensemble system to the seasonal prediction of winter temperatures for Islamabad and Lahore using coupled general circulation models

Weather ◽  
2017 ◽  
Vol 73 (5) ◽  
pp. 159-164
Author(s):  
Bushra Khalid ◽  
Cholaw Bueh ◽  
Shumaila Javeed ◽  
Shaukat Ali ◽  
Qaiser Sultana ◽  
...  
Keyword(s):  
General Circulation ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Model Ensemble ◽  
Single Model ◽  
Winter Temperatures ◽  
Coupled General Circulation Models

The Last Interglaciation in Northeast Siberia

1995 ◽  
Vol 43 (2) ◽  
pp. 147-158 ◽  
Author(s):  
Anatoly V. Lozhkin ◽  
Patricia M. Anderson
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
The Arctic ◽  
The North ◽  
River Terraces ◽  
Atmospheric General Circulation ◽  
Winter Temperatures ◽  
Atmospheric General Circulation Models ◽  
Arctic Coast ◽  
Organic Deposits

AbstractAlluvial, fluvial, and organic deposits of the last interglaciation are exposed along numerous river terraces in northeast Siberia. Although chronological control is often poor, the paleobotanical data suggest range extensions of up to 1000 km for the primary tree species. These data also indicate that boreal communities of the last interglaciation were similar to modern ones in composition, but their distributions were displaced significantly to the north-northwest. Inferences about climate of this period suggest that mean July temperatures were warmer by 4 to 8°C, and seasonal precipitation was slightly greater. Mean January temperatures may have been severely cooler than today (up to 12°C) along the Arctic coast, but similar or slightly warmer than present in other areas. The direction and magnitude of change in July temperatures agree with Atmospheric General Circulation Models, but the 126,000-year-B.P. model results also suggest trends opposite to the paleobotanical data, with simulated cooler winter temperatures and drier conditions than present during the climatic optimum.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

Why is the AMOC Monostable in Coupled General Circulation Models?

2014 ◽  
Vol 27 (6) ◽  
pp. 2427-2443 ◽  
Author(s):  
Wei Liu ◽  
Zhengyu Liu ◽  
Esther C. Brady
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Meridional Overturning Circulation ◽  
Surface Salinity ◽  
Sensitivity Experiment ◽  
Climate System Model ◽  
Control Simulation ◽  
Coupled General Circulation Models ◽  
The Stability ◽  
Flux Adjustment

Abstract This paper is concerned with the question: why do coupled general circulation models (CGCM) seem to be biased toward a monostable Atlantic meridional overturning circulation (AMOC)? In particular, the authors investigate whether the monostable behavior of the CGCMs is caused by a bias of model surface climatology. First observational literature is reviewed, and it is suggested that the AMOC is likely to be bistable in the real world in the past and present. Then the stability of the AMOC in the NCAR Community Climate System Model, version 3 (CCSM3) is studied by comparing the present-day control simulation (without flux adjustment) with a sensitivity experiment with flux adjustment. It is found that the monostable AMOC in the control simulation is altered to a bistable AMOC in the flux-adjustment experiment because a reduction of the surface salinity biases in the tropical and northern North Atlantic leads to a reduction of the bias of freshwater transport in the Atlantic. In particular, the tropical bias associated with the double ITCZ reduces salinity in the upper South Atlantic Ocean and, in turn, the AMOC freshwater export, which tends to overstabilize the AMOC and therefore biases the AMOC from bistable toward monostable state. This conclusion is consistent with a further analysis of the stability indicator of two groups of IPCC Fourth Assessment Report (AR4) CGCMs: one without and the other with flux adjustment. Because the tropical bias is a common feature among all CGCMs without flux adjustment, the authors propose that the surface climate bias, notably the tropical bias in the Atlantic, may contribute significantly to the monostability of AMOC behavior in current CGCMs.

Status and Improvements of Coupled General Circulation Models

Science ◽  
2000 ◽  
Vol 288 (5473) ◽  
pp. 1991-1997 ◽  
Author(s):  
H. Grassl
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Coupled General Circulation Models

Forecast skill of autumn snow for European winter climate during the 20th century: A multi member seasonal prediction experiment

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann
Keyword(s):  
Snow Cover ◽  
General Circulation ◽  
Initial Conditions ◽  
Internal Variability ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Winter Climate ◽  
European Continent ◽  
Near Surface

<p>As the leading climate mode to explain wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Northern Hemispheric cryosphere as possible predictor for the wintertime NAO (Cohen et al. 2014). Although several studies could find seasonal prediction skill in reanalysis data (Orsolini et al. 2016, Duville et al. 2017,Han & Sun 2018), experiments with ocean-atmosphere general circulation models (AOGCMs) still show conflicting results (Furtado et al. 2015, Handorf et al. 2015, Francis 2017, Gastineau et al. 2017). </p><p>Here we use two kinds ECMWF seasonal prediction ensembles starting with November initial conditions taken from the long-term reanalysis ERA-20C and forecasting the following three winter months. Besides the 110-year ensemble of 50 members representing internal variability of the atmosphere, we investigate a second ensemble of 20 members where initial conditions are split between low and high snow cover years for the Northern Hemisphere. We compare two recently used Eurasian snow cover indices for their skill in predicting winter climate for the European continent. Analyzing the two forecast experiments, we found that prediction runs starting with high snow index values in November result in significantly more negative NAO states in the following winter (DJF), which in turn modulates near surface temperatures. We track the atmospheric anomalies triggered by the high snow index through the tropo- and stratosphere as well as for the individual winter months to provide a physical explanation for the formation of this particular climate state.</p><p> </p>

The Double-ITCZ Syndrome in Coupled General Circulation Models: The Role of Large-Scale Vertical Circulation Regimes

2010 ◽  
Vol 23 (5) ◽  
pp. 1127-1145 ◽  
Author(s):  
A. Bellucci ◽  
S. Gualdi ◽  
A. Navarra
Keyword(s):  
Surface Temperature ◽  
Systematic Error ◽  
General Circulation ◽  
Large Scale ◽  
Deep Convection ◽  
General Circulation Models ◽  
Intertropical Convergence Zone ◽  
Convergence Zone ◽  
Vertical Circulation ◽  
Coupled General Circulation Models

Abstract The double–intertropical convergence zone (DI) systematic error, affecting state-of-the-art coupled general circulation models (CGCMs), is examined in the multimodel Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) ensemble of simulations of the twentieth-century climate. The aim of this study is to quantify the DI error on precipitation in the tropical Pacific, with a specific focus on the relationship between the DI error and the representation of large-scale vertical circulation regimes in climate models. The DI rainfall signal is analyzed using a regime-sorting approach for the vertical circulation regimes. Through the use of this compositing technique, precipitation events are regime sorted based on the large-scale vertical motions, as represented by the midtropospheric Lagrangian pressure tendency ω500 dynamical proxy. This methodology allows partition of the precipitation signal into deep and shallow convective components. Following the regime-sorting diagnosis, the total DI bias is split into an error affecting the magnitude of precipitation associated with individual convective events and an error affecting the frequency of occurrence of single convective regimes. It is shown that, despite the existing large intramodel differences, CGCMs can be ultimately grouped into a few homogenous clusters, each featuring a well-defined rainfall–vertical circulation relationship in the DI region. Three major behavioral clusters are identified within the AR4 models ensemble: two unimodal distributions, featuring maximum precipitation under subsidence and deep convection regimes, respectively, and one bimodal distribution, displaying both components. Extending this analysis to both coupled and uncoupled (atmosphere only) AR4 simulations reveals that the DI bias in CGCMs is mainly due to the overly frequent occurrence of deep convection regimes, whereas the error on rainfall magnitude associated with individual convective events is overall consistent with errors already present in the corresponding atmosphere stand-alone simulations. A critical parameter controlling the strength of the DI systematic error is identified in the model-dependent sea surface temperature (SST) threshold leading to the onset of deep convection (THR), combined with the average SST in the southeastern Pacific. The models featuring a THR that is systematically colder (warmer) than their mean surface temperature are more (less) prone to exhibit a spurious southern intertropical convergence zone.

scholarly journals Ocean mixed layer processes in the Pacific Decadal Oscillation in coupled general circulation models

2012 ◽  
Vol 41 (5-6) ◽  
pp. 1407-1417 ◽  
Author(s):  
Bo Young Yim ◽  
Yign Noh ◽  
Sang-Wook Yeh ◽  
Jong-Seong Kug ◽  
Hong Sik Min ◽  
...  
Keyword(s):  
Mixed Layer ◽  
Pacific Decadal Oscillation ◽  
General Circulation ◽  
General Circulation Models ◽  
Ocean Mixed Layer ◽  
The Pacific ◽  
Coupled General Circulation Models

Investigating quasi-resonant Rossby waves with an idealized general circulation model

2020 ◽  
Author(s):  
Todd Mooring ◽  
Marianna Linz
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Rossby Waves ◽  
Circulation Model ◽  
General Circulation Models ◽  
Weather Extremes ◽  
Dynamical Mechanism ◽  
Atmospheric Physics ◽  
Coupled General Circulation Models ◽  
Mean State

<p>Petoukhov et al.’s (2013, PNAS) hypothesis of quasi-resonant Rossby waves as a mechanism for destructive weather extremes—both heat- and rain-related, observed and projected—has received a great deal of attention in recent years.  Most notably, it has been used for diagnostic studies of reanalysis products and full-physics atmospheric or coupled general circulation models. However, studies of this sort essentially assume (rather than test) the validity of the underlying theory.</p><p>Since the quasi-resonance theoretical arguments do not explicitly involve the full complexity of atmospheric physics, it ought to be possible to test them within the much simpler framework of an idealized general circulation model. By carefully constructing the forcing fields for such a model, we will achieve control of its zonal mean state and thus the waveguide properties of the zonal jet. We will explore the properties of the quasi-stationary Rossby waves in such simulations to test whether they have the properties predicted by Petoukhov et al. By testing this dynamical mechanism in a simplified model, we can better understand its applicability and limitations for investigations of future climate.</p>

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