scholarly journals Skillful Climate Forecasts of the Tropical Indo-Pacific Ocean Using Model-Analogs

2018 ◽  
Vol 31 (14) ◽  
pp. 5437-5459 ◽  
Author(s):  
Hui Ding ◽  
Matthew Newman ◽  
Michael A. Alexander ◽  
Andrew T. Wittenberg
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Coarse Grained ◽  
Seasonal Forecasts ◽  
Multimodel Ensemble ◽  
Initial State ◽  
The North ◽  
Eastern Equatorial Pacific ◽  
Spread Model ◽  
The Individual

Seasonal forecasts made by coupled atmosphere–ocean general circulation models (CGCMs) undergo strong climate drift and initialization shock, driving the model state away from its long-term attractor. Here we explore initializing directly on a model’s own attractor, using an analog approach in which model states close to the observed initial state are drawn from a “library” obtained from prior uninitialized CGCM simulations. The subsequent evolution of those “model-analogs” yields a forecast ensemble, without additional model integration. This technique is applied to four of the eight CGCMs comprising the North American Multimodel Ensemble (NMME) by selecting from prior long control runs those model states whose monthly tropical Indo-Pacific SST and SSH anomalies best resemble the observations at initialization time. Hindcasts are then made for leads of 1–12 months during 1982–2015. Deterministic and probabilistic skill measures of these model-analog hindcast ensembles are comparable to those of the initialized NMME hindcast ensembles, for both the individual models and the multimodel ensemble. In the eastern equatorial Pacific, model-analog hindcast skill exceeds that of the NMME. Despite initializing with a relatively large ensemble spread, model-analogs also reproduce each CGCM’s perfect-model skill, consistent with a coarse-grained view of tropical Indo-Pacific predictability. This study suggests that with little additional effort, sufficiently realistic and long CGCM simulations provide the basis for skillful seasonal forecasts of tropical Indo-Pacific SST anomalies, even without sophisticated data assimilation or additional ensemble forecast integrations. The model-analog method could provide a baseline for forecast skill when developing future models and forecast systems.

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.

scholarly journals Systematic Estimates of Initial-Value Decadal Predictability for Six AOGCMs

2012 ◽  
Vol 25 (6) ◽  
pp. 1827-1846 ◽  
Author(s):  
Grant Branstator ◽  
Haiyan Teng ◽  
Gerald A. Meehl ◽  
Masahide Kimoto ◽  
Jeff R. Knight ◽  
...  
Keyword(s):  
North Atlantic ◽  
General Circulation ◽  
General Circulation Models ◽  
Initial Value ◽  
Initial State ◽  
The North ◽  
Key Factor ◽  
External Conditions ◽  
The Mean ◽  
Time Invariant

Abstract Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control integrations with time invariant external conditions. Through the application of analog and multivariate linear regression methodologies, average predictability properties are estimated for forecasts initiated from every state on the control trajectories. For basinwide measures of predictability, the influence of the initial state tends to last for roughly a decade in both basins, but this limit varies widely among the models, especially in the North Atlantic. Within each basin, predictability varies regionally by as much as a factor of 10 for a given model, and the locations of highest predictability are different for each model. Model-to-model variations in predictability are also seen in the behavior of prominent intrinsic basin modes. Predictability is primarily determined by the mean of forecast distributions rather than the spread about the mean. Horizontal propagation plays a large role in the evolution of these signals and is therefore a key factor in differentiating the predictability of the various 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.

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 Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations

2021 ◽  
Vol 13 (21) ◽  
pp. 4464
Author(s):  
Jiawen Xu ◽  
Xiaotong Zhang ◽  
Chunjie Feng ◽  
Shuyue Yang ◽  
Shikang Guan ◽  
...  
Keyword(s):  
General Circulation ◽  
Bayesian Model Averaging ◽  
Mean Squared Error ◽  
Radiant Energy ◽  
Coupled Model ◽  
Model Averaging ◽  
Longwave Radiation ◽  
Energy System ◽  
General Circulation Models ◽  
The Individual

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).

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

&lt;p&gt;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.&lt;/p&gt;

scholarly journals North Atlantic 20th century multidecadal variability in coupled climate models: sea surface temperature and ocean overturning circulation

Ocean Science ◽  
2011 ◽  
Vol 7 (3) ◽  
pp. 389-404 ◽  
Author(s):  
I. Medhaug ◽  
T. Furevik
Keyword(s):  
Surface Temperature ◽  
20Th Century ◽  
North Atlantic ◽  
General Circulation ◽  
General Circulation Models ◽  
Meridional Overturning Circulation ◽  
Overturning Circulation ◽  
Atlantic Sector ◽  
The North ◽  
The North Atlantic

Abstract. Output from a total of 24 state-of-the-art Atmosphere-Ocean General Circulation Models is analyzed. The models were integrated with observed forcing for the period 1850–2000 as part of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. All models show enhanced variability at multi-decadal time scales in the North Atlantic sector similar to the observations, but with a large intermodel spread in amplitudes and frequencies for both the Atlantic Multidecadal Oscillation (AMO) and the Atlantic Meridional Overturning Circulation (AMOC). The models, in general, are able to reproduce the observed geographical patterns of warm and cold episodes, but not the phasing such as the early warming (1930s–1950s) and the following colder period (1960s–1980s). This indicates that the observed 20th century extreme in temperatures are due to primarily a fortuitous phasing of intrinsic climate variability and not dominated by external forcing. Most models show a realistic structure in the overturning circulation, where more than half of the available models have a mean overturning transport within the observed estimated range of 13–24 Sverdrup. Associated with a stronger than normal AMOC, the surface temperature is increased and the sea ice extent slightly reduced in the North Atlantic. Individual models show potential for decadal prediction based on the relationship between the AMO and AMOC, but the models strongly disagree both in phasing and strength of the covariability. This makes it difficult to identify common mechanisms and to assess the applicability for predictions.

scholarly journals Predictable and Unpredictable Aspects of U.S. West Coast Rainfall and El Niño: Understanding the 2015/16 Event

2019 ◽  
Vol 32 (10) ◽  
pp. 2843-2868 ◽  
Author(s):  
Benjamin A. Cash ◽  
Natalie J. Burls
Keyword(s):  
Pacific Northwest ◽  
West Coast ◽  
El Niño ◽  
El Nino ◽  
Rainfall Variability ◽  
Winter Season ◽  
Seasonal Forecasts ◽  
The North ◽  
Dry Conditions ◽  
The Individual

AbstractCalifornia experienced record-setting drought from 2012 to 2017. Based on both seasonal forecast models and historical associations, there was widespread expectation that the major El Niño event of 2015/16 would result in increased winter-season precipitation and break the drought. However, the 2015/16 winter rainy season ultimately resulted in slightly below-average precipitation and the drought continued. In this work we analyze data from both observations and seasonal forecasts made as part of the North American Multi-Model Ensemble (NMME) to better understand the general relationship between El Niño and U.S. West Coast rainfall, focusing on Southern California (SOCAL) rainfall, Pacific Northwest (PNW) rainfall, and the 2015/16 event. We find that while there is a statistically significant positive correlation between El Niño events and the SOCAL and PNW rainfall anomalies, this relationship explains at most one-third of the observed variance. Examination of hindcasts from the NMME demonstrates that the models are capable of accurately reproducing this observed correlation between tropical Pacific sea surface temperatures and California rainfall when information from the individual ensemble members is retained. However, focusing on the multimodel ensemble mean, which deliberately reduces the influence of unpredicted variability, drastically overestimates the strength of this relationship. Our analysis demonstrates that much of the winter rainfall variability along the U.S. West Coast is dominated by unpredicted variations in the 200-hPa height field and that this same unpredicted variability was largely responsible for the unexpectedly dry conditions in 2015/16.

scholarly journals A double ITCZ phenomenology of wind errors in the equatorial Atlantic in seasonal forecasts with ECMWF models

2019 ◽  
Vol 19 (17) ◽  
pp. 11383-11399
Author(s):  
Jonathan K. P. Shonk ◽  
Teferi D. Demissie ◽  
Thomas Toniazzo
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Equatorial Atlantic ◽  
Seasonal Forecasts ◽  
Coupled Models ◽  
Trade Winds ◽  
Double Itcz ◽  
Rapid Transition

Abstract. Modern coupled general circulation models produce systematic biases in the tropical Atlantic that hamper the reliability of long-range predictions. This study focuses on a common springtime westerly wind bias in the equatorial Atlantic in seasonal hindcasts from two coupled models – ECMWF System 4 and EC-Earth v2.3 – and in hindcasts also based on System 4, but with prescribed sea-surface temperatures. The development of the equatorial westerly bias in early April is marked by a rapid transition from a wintertime easterly, cold tongue bias to a springtime westerly bias regime that displays a marked double intertropical convergence zone (ITCZ). The transition is a seasonal feature of the model climatology (independent of initialisation date) and is associated with a seasonal increase in rainfall where a second branch of the ITCZ is produced south of the Equator. Excess off-equatorial convergence redirects the trade winds away from the Equator. Based on arguments of temporal coincidence, the results of our analysis contrast with those from previous work, and alleged causes hereto identified as the likely cause of the equatorial westerly bias in other models must be discarded. Quite in general, we find no evidence of remote influences on the development of the springtime equatorial bias in the Atlantic in the IFS-based models. Limited evidence however is presented that supports the hypothesis of an incorrect representation of the meridional equatorward flow in the marine boundary layer of the southern Atlantic as a contributing factor. Erroneous dynamical constraints on the flow upstream of the Equator may generate convergence and associated rainfall south of the Equator. This directs attention to the representation of the properties of the subtropical boundary layer as a potential source for the double ITCZ bias.

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