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Ingo Richter and Takeshi Doi

Abstract

The influence of sea surface temperature (SST) on interannual surface wind variability in the tropical Atlantic and Pacific is estimated using sensitivity experiments with the SINTEX-F GCM and the ensemble spread in a nine-member control simulation. Two additional estimates are derived for both SINTEX-F and the ERA-Interim reanalysis using regression analysis and singular value decomposition. All methods yield quite consistent estimates of the fraction of surface wind variability that is determined by SST and therefore potentially predictable. In the equatorial Atlantic, analysis suggests that for the period 1982–2014 approximately 2/3 of surface zonal wind variability in boreal spring and early summer is potentially predictable, while 1/3 is due to noise. Of the predictable component, up to about 35% may be driven from outside the tropical Atlantic, suggesting an important role for remote forcing and a diminished one for local feedbacks. In the northern tropical Atlantic, only 30% of boreal winter variability is predictable, most of which is forced from the Pacific. This suggests a minor role for local coupled air–sea feedbacks. For the equatorial Pacific, the results suggest high predictability throughout the year, most of which is due to local SST, with the tropical Atlantic only playing a minor role in boreal summer. In the tropical Atlantic, atmospheric internal variability is strongly dependent on the presence of deep convection, which, in turn, is related to mean SST. A similar, but weaker, state dependence of internal variability is evident in the tropical Pacific.

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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, Tomoki Tozuka, and Toshio Yamagata

Abstract

Using an ocean–atmosphere coupled general circulation model, air–sea interaction processes associated with the Atlantic meridional mode are investigated from a new viewpoint of its link with the Guinea Dome in the northern tropical Atlantic. The subsurface thermal oceanic dome develops off Dakar from late spring to late fall owing to wind-induced Ekman upwelling. Its seasonal evolution is due to surface wind variations associated with the northward migration of the intertropical convergence zone (ITCZ). Since the upwelling cools the mixed layer in the Guinea Dome region during summer, it is very important to reproduce its variability in order to simulate the sea surface temperature (SST) there.

During the preconditioning phase of the positive (negative) Atlantic meridional mode, the dome is anomalously weak (strong) and the mixed layer is anomalously deep (shallow) there in late fall. This condition reduces (enhances) the sensitivity of the mixed layer temperature to the climatological atmospheric cooling. As a result, the positive (negative) SST anomaly appears there in early winter. Then, it develops in the following spring through the wind–evaporation–SST (WES) positive feedback associated with the anomalous northward (southward) migration of the ITCZ. This, in turn, leads to the stronger (weaker) Ekman upwelling and colder (warmer) subsurface temperature in the dome region during summer. It plays an important role on the decay of the warm (cold) SST anomaly through entrainment as a negative feedback. Therefore, simulating this interesting air–sea interaction in the Guinea Dome region is critical in improving prediction skill for the Atlantic meridional mode.

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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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Takeshi Doi, Tomoki Tozuka, Hideharu Sasaki, Yukio Masumoto, and Toshio Yamagata

Abstract

Using outputs from a high-resolution OGCM, seasonal and interannual variations of the Angola Dome (AD) are revisited. Although the AD was previously considered to be one large cold tongue extending from the West African coast, it is shown that two cold domes exist. These two domes have remarkably different mechanisms for their seasonal variation. The weak dome, whose center is located at 6°S, 1°E, develops from May to September owing to the divergence of heat transport associated with upwelling. The strong dome, on the other hand, extends from the west coast of Africa between 20° and 15°S, and develops from April to August by the surface heat flux. The interannual variation of the weak dome is strongly influenced by the Atlantic Niño. An unusual relaxation of easterly wind stress in the central equatorial Atlantic Ocean associated with the Atlantic Niño triggers second baroclinic downwelling equatorial Kelvin waves, which propagate eastward along the equator and poleward along the coast after reaching the African coast as coastal Kelvin waves. Then, downwelling Rossby waves radiate away from the coast and cause significant warming in the weak dome region. The interannual variation of the South Equatorial Undercurrent may be associated with that of the AD; its transport decreases by 0.6 Sv, and its core shifts equatorward by 0.2° when the AD is anomalously weak.

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J. V. Ratnam, Takeshi Doi, Yushi Morioka, Pascal Oettli, Masami Nonaka, and Swadhin K. Behera

Abstract

The selective ensemble mean (SEM) technique is applied to the late spring and summer months (May–August) surface air temperature anomaly predictions of the Scale Interaction Experiment–Frontier Research Center for Global Change, version 2 (SINTEX-F2), coupled general circulation model over Japan. Using the Köppen–Geiger climatic classification we chose four regions over Japan for applying the SEM technique. The SINTEX-F2 ensemble members for the SEM are chosen based on the anomaly correlation coefficients (ACC) of the SINTEX-F2 predicted and observed surface air temperature anomalies. The SEM technique is applied to generate the forecasts of the surface air temperature anomalies for the period 1983–2018 using the selected members. Analysis shows the ACC skill score of the SEM prediction to be higher compared to the ACC skill score of predictions obtained by averaging all the 24 members of the SINTEX-F2 (ENSMEAN). The SEM predicted surface air temperature anomalies also have higher hit rate and lower false alarm rate compared to the ENSMEAN predicted anomalies over a range of temperature anomalies. The results indicate the SEM technique to be a simple and easy to apply method to improve the SINTEX-F2 predictions of surface air temperature anomalies over Japan. The better performance of the SEM in generating the surface air temperature anomalies can be partly attributed to realistic prediction of 850-hPa geopotential height anomalies over Japan.

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J. V. Ratnam, Swadhin K. Behera, Takeshi Doi, Satyban B. Ratna, and Willem A. Landman

Abstract

In an attempt to improve the forecast skill of the austral summer precipitation over South Africa, an ensemble of 1-month-lead seasonal hindcasts generated by the Scale Interaction Experiment–Frontier Research Center for Global Change (SINTEX-F2v) coupled global circulation model is downscaled using the Weather Research and Forecasting (WRF) Model. The WRF Model with two-way interacting domains at horizontal resolutions of 27 and 9 km is used in the study. Evaluation of the deterministic skill score using the anomaly correlation coefficients shows that SINTEX-F2v has significant skill in precipitation forecasts confined to western regions of South Africa. Dynamical downscaling of SINTEX-F2v forecasts using the WRF Model is found to further improve the skill scores over South Africa. However, larger improvements in the skill scores are achieved when the WRF Model is forced by a form of bias-corrected SINTEX-F2v forecasts. The systematic biases in the original fields of the SITNEX-F2v forecasts are removed by superimposing the SINTEX-F2v 6-hourly anomalies over the ERA-Interim 6-hourly climatological fields. The WRF Model forced by the bias-corrected SINTEX-F2v shows significant skill in the forecast anomalies of precipitation over most parts of South Africa. Interestingly, the WRF Model runs with the bias correction did not help to improve the SINTEX-F2v forecast of 2-m air temperatures. Perhaps this is because of the large biases in the precipitation forecast by the WRF Model driven by the bias-corrected SINTEX-F2v. These results are important for potentially improving seasonal forecasts over South Africa.

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Takeshi Doi, Gabriel A. Vecchi, Anthony J. Rosati, and Thomas L. Delworth

Abstract

Using two fully coupled ocean–atmosphere models—Climate Model version 2.1 (CM2.1), developed at the Geophysical Fluid Dynamics Laboratory, and Climate Model version 2.5 (CM2.5), a new high-resolution climate model based on CM2.1—the characteristics and sources of SST and precipitation biases associated with the Atlantic ITCZ have been investigated.

CM2.5 has an improved simulation of the annual mean and the annual cycle of the rainfall over the Sahel and northern South America, while CM2.1 shows excessive Sahel rainfall and lack of northern South America rainfall in boreal summer. This marked improvement in CM2.5 is due to not only high-resolved orography but also a significant reduction of biases in the seasonal meridional migration of the ITCZ. In particular, the seasonal northward migration of the ITCZ in boreal summer is coupled to the seasonal variation of SST and a subsurface doming of the thermocline in the northeastern tropical Atlantic, known as the Guinea Dome. Improvements in the ITCZ allow for better representation of the coupled processes that are important for an abrupt seasonally phase-locked decay of the interannual SST anomaly in the northern tropical Atlantic.

Nevertheless, the differences between CM2.5 and CM2.1 were not sufficient to reduce the warm SST biases in the eastern equatorial region and Angola–Benguela area. The weak bias of southerly winds along the southwestern African coast associated with the excessive southward migration bias of the ITCZ may be a key to improve the warm SST biases there.

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J. V. Ratnam, Takeshi Doi, Willem A. Landman, and Swadhin K. Behera

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In this study, we attempted to forecast the onset of summer rains over South Africa using seasonal precipitation forecasts generated by the Scale Interaction Experiment–Frontier Research Center for Global Change, version 2 (SINTEX-F2), seasonal forecasting system. The precipitation forecasts of the 12-member SINTEX-F2 system, initialized on 1 August and covering the period 1998–2015, were used for the study. The SINTEX-F2 forecast precipitation was also downscaled using dynamical and statistical techniques to improve the spatial and temporal representation of the forecasts. The Weather Research and Forecasting (WRF) Model with two cumulus parameterization schemes was used to dynamically downscale the SINTEX-F2 forecasts. The WRF and SINTEX-F2 precipitation forecasts were corrected for biases using a linear scaling method with a 31-day moving window. The results indicate the onset dates derived from the raw and bias-corrected model precipitation forecasts to have realistic spatial distribution over South Africa. However, the forecast onset dates have root-mean-square errors of more than 30 days over most parts of South Africa except over the northeastern province of Limpopo and over the Highveld region of Mpumalanga province, where the root-mean-square errors are about 10–15 days. The WRF Model with Kain–Fritsch cumulus scheme (bias-corrected SINTEX-F2) has better performance in forecasting the onset dates over Limpopo (the Highveld region) compared to other models, thereby indicating the forecast of onset dates over different regions of South Africa to be model dependent. The results of this study are important for improving the forecast of onset dates over South Africa.

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