scholarly journals Seasonal Rainfall Prediction Skill over South Africa: One- versus Two-Tiered Forecasting Systems

2012 ◽  
Vol 27 (2) ◽  
pp. 489-501 ◽  
Author(s):  
Willem A. Landman ◽  
David DeWitt ◽  
Dong-Eun Lee ◽  
Asmerom Beraki ◽  
Daleen Lötter
Keyword(s):  
South Africa ◽  
General Circulation ◽  
Atmospheric Model ◽  
Forecast Skill ◽  
Coupled Systems ◽  
Seasonal Rainfall ◽  
Coupled Models ◽  
Skill Levels ◽  
Forecast Performance ◽  
Sst Anomalies

Abstract Forecast performance by coupled ocean–atmosphere or one-tiered models predicting seasonal rainfall totals over South Africa is compared with forecasts produced by computationally less demanding two-tiered systems where prescribed sea surface temperature (SST) anomalies are used to force the atmospheric general circulation model. Two coupled models and one two-tiered model are considered here, and they are, respectively, the ECHAM4.5–version 3 of the Modular Ocean Model (MOM3-DC2), the ECHAM4.5-GML–NCEP Coupled Forecast System (CFSSST), and the ECHAM4.5 atmospheric model that is forced with SST anomalies predicted by a statistical model. The 850-hPa geopotential height fields of the three models are statistically downscaled to South African Weather Service district rainfall data by retroactively predicting 3-month seasonal rainfall totals over the 14-yr period from 1995/96 to 2008/09. Retroactive forecasts are produced for lead times of up to 4 months, and probabilistic forecast performance is evaluated for three categories with the outer two categories, respectively, defined by the 25th and 75th percentile values of the climatological record. The resulting forecast skill levels are also compared with skill levels obtained by downscaling forecasts produced by forcing the atmospheric model with simultaneously observed SST in order to produce a reference forecast set. Downscaled forecasts from the coupled systems generally outperform the downscaled forecasts from the two-tiered system, but neither of the two systems outscores the reference forecasts, suggesting that further improvement in operational seasonal rainfall forecast skill for South Africa is still achievable.

scholarly journals Different Ways of Framing Event Attribution Questions: The Example of Warm and Wet Winters in the United Kingdom Similar to 2015/16

2018 ◽  
Vol 31 (12) ◽  
pp. 4827-4845 ◽  
Author(s):  
Nikolaos Christidis ◽  
Andrew Ciavarella ◽  
Peter A. Stott
Keyword(s):  
United Kingdom ◽  
Atmospheric Model ◽  
Human Influence ◽  
Coupled Models ◽  
Modes Of Variability ◽  
The United Kingdom ◽  
Event Attribution ◽  
Key Characteristics ◽  
Reference Event ◽  
Sst Anomalies

Attribution analyses of extreme events estimate changes in the likelihood of their occurrence due to human climatic influences by comparing simulations with and without anthropogenic forcings. Classes of events are commonly considered that only share one or more key characteristics with the observed event. Here we test the sensitivity of attribution assessments to such event definition differences, using the warm and wet winter of 2015/16 in the United Kingdom as a case study. A large number of simulations from coupled models and an atmospheric model are employed. In the most basic case, warm and wet events are defined relative to climatological temperature and rainfall thresholds. Several other classes of events are investigated that, in addition to threshold exceedance, also account for the effect of observed sea surface temperature (SST) anomalies, the circulation flow, or modes of variability present during the reference event. Human influence is estimated to increase the likelihood of warm winters in the United Kingdom by a factor of 3 or more for events occurring under any atmospheric and oceanic conditions, but also for events with a similar circulation or oceanic state to 2015/16. The likelihood of wet winters is found to increase by at least a factor of 1.5 in the general case, but results from the atmospheric model, conditioned on observed SST anomalies, are more uncertain, indicating that decreases in the likelihood are also possible. The robustness of attribution assessments based on atmospheric models is highly dependent on the representation of SSTs without the effect of human influence.

scholarly journals Impact of Ocean–Atmosphere Current Feedback on Ocean Mesoscale Activity: Regional Variations and Sensitivity to Model Resolution

2020 ◽  
Vol 33 (7) ◽  
pp. 2585-2602 ◽  
Author(s):  
Swen Jullien ◽  
Sébastien Masson ◽  
Véra Oerder ◽  
Guillaume Samson ◽  
François Colas ◽  
...  
Keyword(s):  
General Circulation ◽  
Surface Wind ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Ocean Model ◽  
Model Resolution ◽  
Coupled Models ◽  
Current Feedback ◽  
Regional Variations ◽  
Ocean Atmosphere

AbstractOcean mesoscale eddies are characterized by rotating-like and meandering currents that imprint the low-level atmosphere. Such a current feedback (CFB) has been shown to induce a sink of energy from the ocean to the atmosphere, and consequently to damp the eddy kinetic energy (EKE), with an apparent regional disparity. In a context of increasing model resolution, the importance of this feedback and its dependence on oceanic and atmospheric model resolution arise. Using a hierarchy of quasi-global coupled models with spatial resolutions varying from 1/4° to 1/12°, the present study shows that the CFB induces a negative wind work at scales ranging from 100 to 1000 km, and a subsequent damping of the mesoscale activity by ~30% on average, independently of the model resolution. Regional variations of this damping range from ~20% in very rich eddying regions to ~40% in poor eddying regions. This regional modulation is associated with a different balance between the sink of energy by eddy wind work and the source of EKE by ocean intrinsic instabilities. The efficiency of the CFB is also shown to be a function of the surface wind magnitude: the larger the wind, the larger the sink of energy. The CFB impact is thus related to both wind and EKE. Its correct representation requires both an ocean model that resolves the mesoscale field adequately and an atmospheric model resolution that matches the ocean effective resolution and allows a realistic representation of wind patterns. These results are crucial for including adequately mesoscale ocean–atmosphere interactions in coupled general circulation models and have strong implications in climate research.

scholarly journals A Technique for Dynamically Downscaling Daily-Averaged GCM Datasets Using the Conformal Cubic Atmospheric Model

2011 ◽  
Vol 139 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Marcus Thatcher ◽  
John L. McGregor
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Coupled Model ◽  
Circulation Model ◽  
Interpolation Formula ◽  
Atmospheric Model ◽  
Order Estimate ◽  
Climate Projections ◽  
Coupled Models ◽  
Selective Filter

Abstract In this paper the authors dynamically downscale daily-averaged general circulation model (GCM) datasets over Australia using the Conformal Cubic Atmospheric Model (CCAM). The technique can take advantage of the wider range of Coupled Model Intercomparison Project phase 3 (CMIP3) daily-averaged GCM datasets than is available using 3-hourly datasets. The daily-averaged host GCM atmospheric data are fitted to a time interpolation formula and then differentiated in time to produce a first-order estimate of the atmosphere at 0000 UTC on each simulation day. The processed GCM data are forced into CCAM using a scale-selective filter with an 18° radius. Since this procedure is unable to account for the diurnal cycle, the forcing data are only applied to winds and air temperatures once per day between 800 and 100 hPa. Lateral boundary conditions are not required since CCAM employs a variable-resolution global grid. The technique is evaluated by downscaling daily-averaged 2.5° NCEP reanalyses over Australia at 60-km resolution from 1971 to 2000 and comparing the results to downscaling the 6-hourly reanalyses and to simulating with sea surface temperature (SST)-only forcing. The results show that the daily-averaged downscaling technique can simulate average seasonal maximum and minimum screen temperatures and rainfall similar to those obtained downscaling 6-hourly reanalyses. Some implications for regional climate projections are considered by downscaling four daily-averaged GCM datasets from the twentieth-century climate in coupled models (20C3M) experiment over Australia.

scholarly journals Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state

2020 ◽  
Vol 13 (11) ◽  
pp. 5191-5209
Author(s):  
Yingxia Gao ◽  
Nicholas P. Klingaman ◽  
Charlotte A. DeMott ◽  
Pang-Chi Hsu
Keyword(s):  
General Circulation ◽  
Intraseasonal Oscillation ◽  
Phase Relationship ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Boreal Summer ◽  
Coupled Models ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Taylor Diagram ◽  
Mean State

Abstract. The effect of air–sea coupling on simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere–ocean-mixed-layer coupled (SPCAM3-KPP, referred to as SPK throughout) and uncoupled configurations of the superparameterized (SP) Community Atmospheric Model, version 3 (SPCAM3, referred to as SPA throughout). The coupled configuration is constrained to either observed ocean mean state or the mean state from the SP coupled configuration with a dynamic ocean (SPCCSM3), to understand the effect of mean-state biases on the BSISO. All configurations overestimate summer mean subtropical rainfall and its intraseasonal variance. All configurations simulate realistic BSISO northward propagation over the Indian Ocean and western Pacific, in common with other SP configurations. Prescribing the 31 d smoothed sea surface temperature (SST) from the SPK simulation in SPA worsens the overestimated BSISO variance. In both coupled models, the phase relationship between intraseasonal rainfall and SST is well captured. This suggests that air–sea coupling improves the amplitude of simulated BSISO and contributes to the propagation of convection. Constraining SPK to the SPCCSM3 mean state also reduces the overestimated BSISO variability but weakens BSISO propagation. Using the SPCCSM3 mean state also introduces a 1-month delay to the BSISO seasonal cycle compared to SPK with the observed ocean mean state, which matches well with observation. Based on a Taylor diagram, both air–sea coupling and SPCCSM3 mean-state SST biases generally lead to higher simulated BSISO fidelity, largely due to their abilities to suppress the overestimated subtropical BSISO variance.

scholarly journals Role of the Indo-Pacific Interbasin Coupling in Predicting Asymmetric ENSO Transition and Duration

2012 ◽  
Vol 25 (9) ◽  
pp. 3321-3335 ◽  
Author(s):  
Masamichi Ohba ◽  
Masahiro Watanabe
Keyword(s):  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
La Nina ◽  
The Pacific ◽  
Enso Asymmetry ◽  
Sst Anomalies

Warm and cold phases of El Niño–Southern Oscillation (ENSO) exhibit a significant asymmetry in their transition/duration such that El Niño tends to shift rapidly to La Niña after the mature phase, whereas La Niña tends to persist for up to 2 yr. The possible role of sea surface temperature (SST) anomalies in the Indian Ocean (IO) in this ENSO asymmetry is investigated using a coupled general circulation model (CGCM). Decoupled-IO experiments are conducted to assess asymmetric IO feedbacks to the ongoing ENSO evolution in the Pacific. Identical-twin forecast experiments show that a coupling of the IO extends the skillful prediction of the ENSO warm phase by about one year, which was about 8 months in the absence of the IO coupling, in which a significant drop of the prediction skill around the boreal spring (known as the spring prediction barrier) is found. The effect of IO coupling on the predictability of the Pacific SST is significantly weaker in the decay phase of La Niña. Warm IO SST anomalies associated with El Niño enhance surface easterlies over the equatorial western Pacific and hence facilitate the El Niño decay. However, this mechanism cannot be applied to cold IO SST anomalies during La Niña. The result of these CGCM experiments estimates that approximately one-half of the ENSO asymmetry arises from the phase-dependent nature of the Indo-Pacific interbasin coupling.

Diagnosing Sources of U.S. Seasonal Forecast Skill

2006 ◽  
Vol 19 (13) ◽  
pp. 3279-3293 ◽  
Author(s):  
X. Quan ◽  
M. Hoerling ◽  
J. Whitaker ◽  
G. Bates ◽  
T. Xu
Keyword(s):  
Air Temperature ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Diagnostic Methods ◽  
Sea Surface ◽  
Empirical Methods ◽  
Spatial Coverage ◽  
Sst Anomalies

Abstract In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ensemble simulations with four atmospheric general circulation models (AGCMs) forced by observed monthly global SSTs from 1950 to 1999, and ensemble AGCM experiments forced by idealized SST anomalies. The empirical methods involve a suite of reductions of the AGCM simulations. These include uni- and multivariate regression models that encapsulate the simultaneous and one-season lag linear connections between seasonal mean tropical SST anomalies and U.S. precipitation and surface air temperature. Nearly all of the AGCM skill in U.S. precipitation and surface air temperature, arising from global SST influences, can be explained by a single degree of freedom in the tropical SST field—that associated with the linear atmospheric signal of El Niño–Southern Oscillation (ENSO). The results support previous findings regarding the preeminence of ENSO as a U.S. skill source. The diagnostic methods used here exposed another skill source that appeared to be of non-ENSO origins. In late autumn, when the AGCM simulation skill of U.S. temperatures peaked in absolute value and in spatial coverage, the majority of that originated from SST variability in the subtropical west Pacific Ocean and the South China Sea. Hindcast experiments were performed for 1950–99 that revealed most of the simulation skill of the U.S. seasonal climate to be recoverable at one-season lag. The skill attributable to the AGCMs was shown to achieve parity with that attributable to empirical models derived purely from observational data. The diagnostics promote the interpretation that only limited advances in U.S. seasonal prediction skill should be expected from methods seeking to capitalize on sea surface predictors alone, and that advances that may occur in future decades could be readily masked by inherent multidecadal fluctuations in skill of coupled ocean–atmosphere systems.

scholarly journals Climatological Increased Precipitation from July to August in the Western North Pacific Region Simulated by CMIP6 Models

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 664
Author(s):  
Xiao Dong ◽  
Renping Lin
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Vertical Motion ◽  
Atmospheric Model ◽  
Coupled Models ◽  
Model Simulations ◽  
Observational Analysis ◽  
Budget Analysis ◽  
Circulation Change ◽  
Precipitation Increase

In this study, the climatological precipitation increase from July to August over the western North Pacific (WNP) region was investigated through observations and simulations in the Coupled Model Intercomparison Project Phase 6 (CMIP6), atmospheric model simulations and historical experiments. Firstly, observational analysis showed that the precipitation increase is associated with a decrease in the local sea surface temperature (SST), indicating that the precipitation increase is not driven by the change in SST. In addition, the pattern of precipitation increase is similar to the vertical motion change at 500-hPa, suggesting that the precipitation increase is related to the circulation change. Moisture budget analysis further confirmed this relation. In addition to the observational analysis, the outputs from 26 CMIP6 models were further evaluated. Compared with atmospheric model simulations, air–sea coupled models largely improve the simulation of the climatological precipitation increase from July to August. Furthermore, model simulations confirmed that the bias in the precipitation increase is intimately associated with the circulation change bias. Thus, two factors are responsible for the bias of the precipitation increase from July to August in climate models: air–sea coupling processes and the performance in vertical motion change.

scholarly journals Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

2017 ◽  
Vol 21 (9) ◽  
pp. 4841-4859 ◽  
Author(s):  
Sean W. D. Turner ◽  
James C. Bennett ◽  
David E. Robertson ◽  
Stefano Galelli
Keyword(s):  
System Performance ◽  
Research Effort ◽  
Forecast Accuracy ◽  
Strong Relationship ◽  
Forecast Skill ◽  
Severe Drought ◽  
Forecast Performance ◽  
Performance Improvements ◽  
Sensitivity Assessment ◽  
Seasonal Streamflow

Abstract. Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

scholarly journals Indo-Western Pacific Climate Variability: ENSO Forcing and Internal Dynamics in a Tropical Pacific Pacemaker Simulation

2018 ◽  
Vol 31 (24) ◽  
pp. 10123-10139 ◽  
Author(s):  
Chuan-Yang Wang ◽  
Shang-Ping Xie ◽  
Yu Kosaka
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Southern Oscillation ◽  
Internal Variability ◽  
Tropical Pacific ◽  
Western Pacific ◽  
Ocean Atmosphere ◽  
Sst Anomalies

El Niño–Southern Oscillation (ENSO) peaks in boreal winter but its impact on Indo-western Pacific climate persists for another two seasons. Key ocean–atmosphere interaction processes for the ENSO effect are investigated using the Pacific Ocean–Global Atmosphere (POGA) experiment with a coupled general circulation model, where tropical Pacific sea surface temperature (SST) anomalies are restored to follow observations while the atmosphere and oceans are fully coupled elsewhere. The POGA shows skills in simulating the ENSO-forced warming of the tropical Indian Ocean and an anomalous anticyclonic circulation pattern over the northwestern tropical Pacific in the post–El Niño spring and summer. The 10-member POGA ensemble allows decomposing Indo-western Pacific variability into the ENSO forced and ENSO-unrelated (internal) components. Internal variability is comparable to the ENSO forcing in magnitude and independent of ENSO amplitude and phase. Random internal variability causes apparent decadal modulations of ENSO correlations over the Indo-western Pacific, which are high during epochs of high ENSO variance. This is broadly consistent with instrumental observations over the past 130 years as documented in recent studies. Internal variability features a sea level pressure pattern that extends into the north Indian Ocean and is associated with coherent SST anomalies from the Arabian Sea to the western Pacific, suggestive of ocean–atmosphere coupling.

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