# Seasonal Prediction of Boreal Winter Rainfall over the Western Maritime Continent during ENSO

• Since the beginning of the Association of Southeast Asian Nations Climate Outlook Forum (ASEANCOF) in 2013, the most difficult challenge has been the rainfall forecast in boreal winter. This is the Maritime Continent monsoon season during which rainfall reaches maximum in the annual cycle. This forecast difficulty arises in spite of the general notion that seasonal predictability of the Maritime Continent rainfall may be higher than most places because of the strong and robust influences of ENSO. The lower predictability is consistent with the lower correlation between ENSO and western Maritime Continent rainfall that reaches minimum during the boreal winter monsoon. Various theories have been proposed to explain this low correlation. In this paper, we review the research on ENSO–Maritime Continent rainfall relationship and show that the main cause of the forecast difficulty is the wind–terrain interaction involving the Sumatran and Malay Peninsula mountains, rather than the effect of sea surface temperature (SST). The wind–terrain interaction due to the low-level regional scale anomalous horizontal circulation offsets the anomalous Walker circulation during both El Niño and La Niña. The net result of these two opposing responses to ENSO is a lower local predictability. We propose to call this low-predictability region the WIMP (Western Indonesia–Malay Peninsula) region both for its geographical location and its special characteristic of causing difficulties for forecasters to make a confident forecast for the boreal winter. Our result suggests that climate models lack skills in forecasting rainfall in this region because their predictability depends strongly on SST.
• Fig. 1.  The ASEAN Climate Outlook Forum consensus rainfall forecasts for (a) December–February (DJF) 2013/14 (from ASEANCOF-1, 2013), (b) DJF 2014/15 (from ASEANCO-3, 2014), and (c) DJF 2015/16 (from ASEANCOF-5, 2015) over Southeast Asia in terms of tercile probabilities.

Fig. 2.  (a) ASEAN Climate Outlook Forum (ASEANCOF) consensus rainfall forecasts for December–February (DJF) 2016/17 over Southeast Asia (from ASEANCOF-7, 2016). (b) Anomaly of outgoing longwave radiation (OLR; W m–2) for DJF 2016/17 from Asia–Pacific Climate Center (APCC) 2017 (at http://www.apcc21.org).

Fig. 3.  (a) ASEAN Climate Outlook Forum (ASEANCOF) consensus rainfall forecasts for December–February (DJF) 2017/18 over Southeast Asia in terms of tercile probabilities (from ASEANCOF-9, 2017). (b) Verification by the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) for DJF 2017/18 over Southeast Asia in terms of tercile (shading; from ASEANCOF-10, 2018).

Fig. 4.  As in Fig. 3, but for DJF 2018/19

Fig. 5.  (a) Coefficients of correlation between NCEP Climate Forecast System (CFSv2)-predicted and observed rainfall during wet season (black lines) and dry season (red lines) in the Sumatra–Malay–Borneo region (SMB; solid lines) and the eastern Maritime Continent (EMC; dashed lines) of different lead time (month). (b) As in (a), but for the correlation between the NCEP CFSv2-predicted rainfall and negative Niño-3.4. The horizontal dotted lines denote the 95% confidence level (from Zhang et al., 2016a).

Fig. 6.  Correlations of 1979–2002 CMAP rainfall with Niño3 SST. Areas above the 5% significance level are shaded. The rainfall index regions enclosed by blue solid lines are Sumatra–Malay Peninsula (SMP); southwest oceanic area to southwest of Sumatra (SWO); and Central Maritime Continent (CMC) (from Chang et al., 2004b). The SMP region is over western Indonesia–Malay Peninsula and will be renamed the WIMP region.

Fig. 7.  Correlations of 1979–2002 CMAP rainfall with the (a) SMP (Sumatra–Malay Peninsula) rainfall index and (b) SWO (Southwest Oceanic region) rainfall index. The rainfall index regions are enclosed by blue solid lines in Fig. 6. Areas above the 5% significance level are shaded (from Chang et al., 2004b).

Fig. 8.  (a) Composite of Niño3 SST “cold minus warm” 850-hPa wind V850 (m s−1; heavy arrows indicate differences with at least a 95% confidence level in either the zonal or the meridional component) and vorticity (shading; 10−6 s−1; only differences at 95% or higher confidence level are plotted) during 1979–2002; (b) as in (a), but for “wet minus dry” in the WIMP rainfall index; and (c) long-term seasonal (DJF) mean 850-hPa wind (from Chang et al., 2004b).

Fig. 9.  Normalized area-averaged 850-hPa vertical p-velocity $\omega _{850}$ evolution (black solid line) and SSTA evolution in the western Maritime Continent region (black dotted line; 4°S–5°N, 100°–112°E) and in a broader equatorial Maritime Continent region defined by Hendon (2003) (black dashed line; 0–10°S, 95°–135°E) during El Niño year from July (0) to February (1) (from Jiang and Li, 2018).

Fig. 10.  Schematic diagram of the low-level anomalous circulation over the WIMP area during (a) La Niña and (b) El Niño development phases. For La Niña, the circulation centered near Philippines is cyclonic and the equatorial anomalous westerlies are part of the lower branch of the planetary-scale Walker circulation that produces low-level convergence in the broad Maritime Continent area. However, the westerlies in the eastern Indian Ocean encounters the Sumatra mountains and produce dry descent in the WIMP region, resulting in decreased rainfall. For El Niño, the equatorial anomalous easterlies are part of the lower branch of the Walker circulation that produces low-level divergence over in the broad Maritime Continent area, while the easterlies associated with the Philippine Sea anticyclone encounters the Sumatra mountains from the west, producing moist ascent and increased rainfall in the WIMP region. The shading represents the topography (m).

###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## Seasonal Prediction of Boreal Winter Rainfall over the Western Maritime Continent during ENSO

###### Corresponding author: Chih-Pei CHANG, cpchang@nps.edu;
• 1. Department of Meteorology, Naval Postgraduate School, Monterey, CA 93943, USA
• 2. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environmental Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China
• 3. Department of Atmospheric Sciences, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822, USA
• 4. School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China

Abstract: Since the beginning of the Association of Southeast Asian Nations Climate Outlook Forum (ASEANCOF) in 2013, the most difficult challenge has been the rainfall forecast in boreal winter. This is the Maritime Continent monsoon season during which rainfall reaches maximum in the annual cycle. This forecast difficulty arises in spite of the general notion that seasonal predictability of the Maritime Continent rainfall may be higher than most places because of the strong and robust influences of ENSO. The lower predictability is consistent with the lower correlation between ENSO and western Maritime Continent rainfall that reaches minimum during the boreal winter monsoon. Various theories have been proposed to explain this low correlation. In this paper, we review the research on ENSO–Maritime Continent rainfall relationship and show that the main cause of the forecast difficulty is the wind–terrain interaction involving the Sumatran and Malay Peninsula mountains, rather than the effect of sea surface temperature (SST). The wind–terrain interaction due to the low-level regional scale anomalous horizontal circulation offsets the anomalous Walker circulation during both El Niño and La Niña. The net result of these two opposing responses to ENSO is a lower local predictability. We propose to call this low-predictability region the WIMP (Western Indonesia–Malay Peninsula) region both for its geographical location and its special characteristic of causing difficulties for forecasters to make a confident forecast for the boreal winter. Our result suggests that climate models lack skills in forecasting rainfall in this region because their predictability depends strongly on SST.

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