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

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.

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.

scholarly journals Annual and semiannual cycles of midlatitude surface temperature and baroclinicity: reanalysis data and AOGCMs simulations

2016 ◽  
Author(s):  
Valerio Lembo ◽  
Isabella Bordi ◽  
Antonio Speranza
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Relative Phase ◽  
North Pacific Ocean ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Bivariate Analysis ◽  
Seasonal Forecasts ◽  
Frequency Model ◽  
Annual Frequency

Abstract. Seasonal variability of surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere-ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically: (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres; (ii) at the annual frequency, estimates of the relative phase between surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1 month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3 but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterize the cyclic response of current global atmosphere-ocean models to the external (solar) forcing that is of interest for seasonal forecasts.

scholarly journals Extreme Drought Events over the Amazon Basin: The Perspective from the Reconstruction of South American Hydroclimate

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1594 ◽  
Author(s):  
Beatriz Garcia ◽  
Renata Libonati ◽  
Ana Nunes
Keyword(s):  
Surface Temperature ◽  
Extreme Events ◽  
General Circulation ◽  
Amazon Basin ◽  
General Circulation Models ◽  
Extreme Drought ◽  
Severe Drought ◽  
South American ◽  
Spatial And Temporal Patterns ◽  
Near Surface

The Amazon basin has experienced severe drought events for centuries, mainly associated with climate variability connected to tropical North Atlantic and Pacific sea surface temperature anomalous warming. Recently, these events are becoming more frequent, more intense and widespread. Because of the Amazon droughts environmental and socioeconomic impacts, there is an increased demand for understanding the characteristics of such extreme events in the region. In that regard, regional models instead of the general circulation models provide a promising strategy to generate more detailed climate information of extreme events, seeking better representation of physical processes. Due to uneven spatial distribution and gaps found in station data in tropical South America, and the need of more refined climate assessment in those regions, satellite-enhanced regional downscaling for applied studies (SRDAS) is used in the reconstruction of South American hydroclimate, with hourly to monthly outputs from January 1998. Accordingly, this research focuses on the analyses of recent extreme drought events in the years of 2005 and 2010 in the Amazon Basin, using the SRDAS monthly means of near-surface temperature and relative humidity, precipitation and vertically integrated soil moisture fields. Results from this analysis corroborate spatial and temporal patterns found in previous studies on extreme drought events in the region, displaying the distinctive features of the 2005 and 2010 drought events.

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>

scholarly journals Importance of the advection scheme for the simulation of water isotopes over Antarctica by general circulation models: a case study with LMDZ-iso (LMDZ5a revision 1750)

2017 ◽  
Author(s):  
Alexandre Cauquoin ◽  
Camille Risi
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Temperature Relationship ◽  
Water Isotopes ◽  
Good Representation ◽  
Advection Scheme ◽  
Atmospheric General Circulation ◽  
Atmospheric General Circulation Models ◽  
Polar Water

Abstract. Atmospheric general circulation models (AGCMs) are known to have a warm and isotopically enriched bias over Antarctica. We test here the hypothesis that these biases are consequences of a too diffusive advection. Using the LMDZ-iso model, we show that a good representation of the advection, especially on the horizontal, is very important to reduce the bias in the isotopic contents of precipitation above this area and to improve the modelled water isotopes – temperature relationship. A good advection scheme is thus essential when using GCMs for paleoclimate applications based on polar water isotopes.

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