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Desmond Manatsa and Swadhin K. Behera

Abstract

Variability of the equatorial East Africa “short rains” (EASR) has intensified significantly since the turn of the twentieth century. This increase toward more extreme rainfall events has not been gradual but is strongly characterized by epochs. The rain gauge–based Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset for the period 1901–2009 is used to demonstrate that the epochal changes were dictated by shifts in the Indian Ocean dipole (IOD) mode. These shifts occurred during 1961 and 1997. In the pre-1961 period, there was virtually no significant linear link between the IOD and the EASR. But a relatively strong coupling between the two occurred abruptly in 1961 and was generally maintained at that level until 1997, when another sudden shift to even a greater level occurred. The first principal component (PC1) extracted from the EASR spatial domain initially merely explained about 50% of the rainfall variability before 1961, and then catapulted to about 73% for the period from 1961 to 1997, before eventually shifting to exceed 82% after 1997. The PC1 for each successive epoch also displayed loadings with notably improved spatial coherence. This systematic pattern of increase was accompanied by both a sharp increase in the frequency of rainfall extremes and spatial coherence of the rainfall events over the region. Therefore, it is most likely that the 1961 and 1997 IOD shifts are responsible for the epochal modulation of the EASR in both the spatial and temporal domain.

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Yushi Morioka, Francois Engelbrecht, and Swadhin K. Behera

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Potential sources of decadal climate variability over southern Africa are examined by conducting in-depth analysis of available datasets and coupled general circulation model (CGCM) experiments. The observational data in recent decades show a bidecadal variability noticeable in the southern African rainfall with its positive phase of peak during 1999/2000. It is found that the rainfall variability is related to anomalous moisture advection from the southwestern Indian Ocean, where the anomalous sea level pressure (SLP) develops. The SLP anomaly is accompanied by anomalous sea surface temperature (SST). Both SLP and SST anomalies slowly propagate eastward from the South Atlantic to the southwestern Indian Ocean. The analysis of mixed layer temperature tendency reveals that the SST anomaly in the southwestern Indian Ocean is mainly due to eastward advection of the SST anomaly by the Antarctic Circumpolar Current. The eastward propagation of SLP and SST anomalies are also confirmed in the 270-yr outputs of the CGCM control experiment. However, in a sensitivity experiment where the SST anomalies in the South Atlantic are suppressed by the model climatology, the eastward propagation of the SLP anomaly from the South Atlantic disappears. These results suggest that the local air–sea coupling in the South Atlantic may be important for the eastward propagation of the SLP anomaly from the South Atlantic to the southwestern Indian Ocean. Although remote influences from the tropical Pacific and Antarctica were widely discussed, this study provides new evidence for the potential role of local air–sea coupling in the South Atlantic for the decadal climate variability over southern Africa.

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Takeshi Doi, Swadhin K. Behera, and Toshio Yamagata

Abstract

This paper explores merits of 100-ensemble simulations from a single dynamical seasonal prediction system by evaluating differences in skill scores between ensembles predictions with few (~10) and many (~100) ensemble members. A 100-ensemble retrospective seasonal forecast experiment for 1983–2015 is beyond current operational capability. Prediction of extremely strong ENSO and the Indian Ocean dipole (IOD) events is significantly improved in the larger ensemble. It indicates that the ensemble size of 10 members, used in some operational systems, is not adequate for the occurrence of 15% tails of extreme climate events, because only about 1 or 2 members (approximately 15% of 12) will agree with the observations. We also showed an ensemble size of about 50 members may be adequate for the extreme El Niño and positive IOD predictions at least in the present prediction system. Even if running a large-ensemble prediction system is quite costly, improved prediction of disastrous extreme events is useful for minimizing risks of possible human and economic losses.

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Takeshi Doi, Chaoxia Yuan, Swadhin K. Behera, and Toshio Yamagata

Abstract

Predictability of a recently discovered regional coupled climate mode called the California Niño (Niña) off Baja California and California is explored using a seasonal prediction system based on the Scale Interaction Experiment-Frontier, version 1 (SINTEX-F1) coupled ocean–atmosphere general circulation model. Because of the skillful prediction of basin-scale El Niño (La Niña), the California Niño (Niña) that co-occurs with El Niño (La Niña) with a peak in boreal winter is found to be predictable at least a couple of seasons ahead. On the other hand, the regional coupled phenomenon peaking in boreal summer without co-occurrence with El Niño (La Niña) is difficult to predict. The difficulty in predicting such an intrinsic regional climate phenomenon may be due to model deficiency in resolving the regional air–sea–land positive feedback processes. The model may also underestimate coastal Kelvin waves with a small offshore scale, which may play an important role in the generation of the California Niño/Niña. It may be improved by increasing horizontal resolution of the ocean component of the coupled model. The present study may provide a guideline to improve seasonal prediction of regional climate modes for important industrial as well as social applications.

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J. V. Ratnam, Takeshi Doi, and Swadhin K. Behera

Abstract

An ensemble of 1-month-lead seasonal retrospective forecasts generated by the Scale Interaction Experiment (SINTEX)–Frontier Research Center for Global Change (FRCGC), version 2 tuned for performance on a vector supercomputer (SINTEX-F2v), coupled global circulation model (CGCM) were downscaled using the Weather Research and Forecasting (WRF) Model to improve the forecast of the austral summer precipitation and 2-m air temperatures over Australia. A set of four experiments was carried out with the WRF Model to improve the forecasts. The first was to drive the WRF Model with the SINTEX-F2v output, and the second was to bias correct the mean component of the SINTEX-F2v forecast and drive the WRF Model with the corrected fields. The other experiments were to use the SINTEX-F2v forecasts and the mean bias-corrected SINTEX-F2v forecasts to drive the WRF Model coupled to a simple mixed layer ocean model. Evaluation of the forecasts revealed the WRF Model driven by bias-corrected SINTEX-F2v forecasts to have a better spatial and temporal representation of forecast precipitation and 2-m air temperature, compared to SINTEX-F2v forecasts. Using a regional coupled model with the bias-corrected SINTEX-F2v forecast as the driver further improved the skill of the precipitation forecasts. The improvement in the WRF Model forecasts is due to better representation of the variables in the bias-corrected SINTEX-F2v forecasts driving the WRF Model. The study brings out the importance of including air–sea interactions and correcting the global forecasts for systematic biases before downscaling them for societal applications over Australia. These results are important for potentially improving austral summer seasonal forecasts over Australia.

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J. V. Ratnam, Swadhin K. Behera, and Toshio Yamagata

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Periods of low convective activity over southern Africa during the peak rainy season from December to February are known to be due to the northeastward displacement of the tropical temperate trough (TTT) systems from the landmass. In this study, using Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) data, the authors show that the displacement of the TTT systems during long periods of low convective activity has origins in the Northern Hemisphere. Using standardized area-averaged outgoing longwave radiation (OLR) daily anomalies over southern Africa, long periods of low convective activity are defined as periods of positive OLR anomalies lasting consecutively for 5 or more days with a standard deviation of 1 or more. An eddy streamfunction anomaly composite of the periods of low convective activity shows an upper-level anomalous wave originating in the Northern Hemisphere and extending to southern Africa from the eastern Pacific and displacing the tropical–extratropical cloud bands from the southern African landmass into the southwestern Indian Ocean. The wave train is also seen to generate an anticyclonic anomaly over southern Africa, resulting in suppressed convective activity. Understanding the causes of the long periods of low convective activity will help in improving their predictability and also the predictability of seasonal rainfall over southern Africa.

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Jing-Jia Luo, Swadhin K. Behera, Yukio Masumoto, and Toshio Yamagata

Abstract

Surface air temperature (SAT) over the globe, particularly the Northern Hemisphere continents, has rapidly risen over the last 2–3 decades, leading to an abrupt shift toward a warmer climate state after 1997/98. Whether the terrestrial warming might be caused by local response to increasing greenhouse gas (GHG) concentrations or by sea surface temperature (SST) rise is recently in dispute. The SST warming itself may be driven by both the increasing GHG forcing and slowly varying natural processes. Besides, whether the recent global warming might affect seasonal-to-interannual climate predictability is an important issue to be explored. Based on the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) climate prediction system in which only observed SSTs are assimilated for coupled model initialization, the present study shows that the historical SST rise plays a key role in driving the intensified terrestrial warming over the globe. The SST warming trend, while negligible for short lead predictions, has substantial impact on the climate predictability at long lead times (>1 yr) particularly in the extratropics. The tropical climate predictability, however, is little influenced by global warming. Given a perfect warming trend and/or a perfect model, global SAT and precipitation could be predicted beyond two years in advance with an anomaly correlation skill above ∼0.6.

Without assimilating ocean subsurface observations, model initial conditions show a strong spurious cooling drift of subsurface temperature; this is caused by large negative surface heat flux damping arising from the SST-nudging initialization. The spurious subsurface cooling drift acts to weaken the initial SST warming trend during model forecasts, leading to even negative trends of global SAT and precipitation at long lead times and hence deteriorating the global climate predictability. Concerning the important influence of the subsurface temperature on the global SAT trend, future efforts are required to develop a good scheme for assimilating subsurface information particularly in the extratropical oceans.

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Jing-Jia Luo, Sebastien Masson, Swadhin K. Behera, and Toshio Yamagata

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Using a fully coupled global ocean–atmosphere general circulation model assimilating only sea surface temperature, the authors found for the first time that several El Niño–Southern Oscillation (ENSO) events over the past two decades can be predicted at lead times of up to 2 yr. The El Niño condition in the 1997/98 winter can be predicted to some extent up to about a 1½-yr lead but with a weak intensity and large phase delay in the prediction of the onset of this exceptionally strong event. This is attributed to the influence of active and intensive stochastic westerly wind bursts during late 1996 to mid-1997, which are generally unpredictable at seasonal time scales. The cold signals in the 1984/85 and 1999/2000 winters during the peak phases of the past two long-lasting La Niña events are predicted well up to a 2-yr lead. Amazingly, the mild El Niño–like event of 2002/03 is also predicted well up to a 2-yr lead, suggesting a link between the prolonged El Niño and the tropical Pacific decadal variability. Seasonal climate anomalies over vast parts of the globe during specific ENSO years are also realistically predicted up to a 2-yr lead for the first time.

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Yushi Morioka, Koutarou Takaya, Swadhin K. Behera, and Yukio Masumoto

Abstract

The interannual variations in the summertime Mascarene high have great impacts on the southern African climate as well as the sea surface temperature (SST) in the southern Indian Ocean. A set of coupled general circulation model (CGCM) experiments are performed to examine a role of the interannual SST variability in the southern Indian Ocean on the summertime Mascarene high variability. The dominant interannual variability in the summertime Mascarene high shows the strengthening (weakening) in its southern part throughout the austral summer (December–February). However, in the experiment where the interannual SST variability in the southern Indian Ocean is suppressed, the strengthening (weakening) of the Mascarene high in its southern part does not persist until February. Also, the Mascarene high variability and its associated SST anomalies in December and January are found to increase (decrease) the southern African rainfall via more (less) moisture supply from the southern Indian Ocean. The Mascarene high variability is actually associated with a meridional dipole of positive and negative SST anomalies, which in turn produces that of the meridional SST gradient anomaly. This causes a southward (northward) shift of the storm tracks and hence the westerly jet, favoring the strengthening (weakening) of the Mascarene high in its southern part. This local ocean–atmosphere feedback effectively operates in February, when the meridional dipole of the SST anomalies reaches the maximum. These results provide new insight into the important role of the local SST variability in the summertime Mascarene high variability and hence the southern African climate.

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Swadhin K. Behera, Jing-Jia Luo, Sebastien Masson, Pascale Delecluse, Silvio Gualdi, Antonio Navarra, and Toshio Yamagata

Abstract

The variability in the East African short rains is investigated using 41-yr data from the observation and 200-yr data from a coupled general circulation model known as the Scale Interaction Experiment-Frontier Research Center for Global Change, version 1 (SINTEX-F1). The model-simulated data provide a scope to understand the climate variability in the region with a better statistical confidence. Most of the variability in the model short rains is linked to the basinwide large-scale coupled mode, that is, the Indian Ocean dipole (IOD) in the tropical Indian Ocean. The analysis of observed data and model results reveals that the influence of the IOD on short rains is overwhelming as compared to that of the El Niño–Southern Oscillation (ENSO); the correlation between ENSO and short rains is insignificant when the IOD influence is excluded. The IOD–short rains relationship does not change significantly in a model experiment in which the ENSO influence is removed by decoupling the ocean and atmosphere in the tropical Pacific. The partial correlation analysis of the model data demonstrates that a secondary influence comes from a regional mode located near the African coast.

Inconsistent with the observational findings, the model results show a steady evolution of IOD prior to extreme events of short rains. Dynamically consistent evolution of correlations is found in anomalies of the surface winds, currents, sea surface height, and sea surface temperature. Anomalous changes of the Walker circulation provide a necessary driving mechanism for anomalous moisture transport and convection over the coastal East Africa. The model results nicely augment the observational findings and provide us with a physical basis to consider IOD as a predictor for variations of the short rains. This is demonstrated in detail using the statistical analysis method. The prediction skill of the dipole mode SST index in July and August is 92% for the observation, which scales slightly higher for the model index (96%) in August. As observed in data, the model results show decadal weakening in the relationship between IOD and short rains owing to weakening in the IOD activity.

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