Impacts of convectively coupled equatorial waves on rainfall extremes in Java, Indonesia

2020 ◽  
Author(s):  
Sandro W. Lubis ◽  
Muhamad R. Respati
Keyword(s):  
Equatorial Waves ◽  
Convectively Coupled Equatorial Waves ◽  
Rainfall Extremes

Impacts of convectively coupled equatorial waves on rainfall extremes in Java, Indonesia

2021 ◽  
Author(s):  
Muhamad Reyhan Respati ◽  
Sandro W. Lubis
Keyword(s):  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Moisture Flux ◽  
Kelvin Waves ◽  
Equatorial Waves ◽  
Multiple Wave ◽  
Extreme Rainfall Events ◽  
Convectively Coupled Equatorial Waves ◽  
Rainfall Extremes

<p>Rainfall extremes cause significant socioeconomic impacts in Indonesia, as they are often followed by disastrous events, such as floods and landslides. Of particular interest is Java Island, the most populated region in Indonesia, which is prone to damaging flooding as a result of heavy rainfall. The prediction of rainfall extremes in this region has mainly been focused on the effects of seasonal and intraseasonal variability, such as monsoons and the Madden–Julian Oscillation. Here, using an extensive station database from 1987 to 2017 and the gridded Asian Precipitation‐Highly Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE) product from 1980 to 2007, we show that severe weather conditions associated with rainfall extremes in Java during the rainy season (November to April) can also be attributed to convectively coupled equatorial waves (CCEWs) that occur on a shorter time scale.</p><p>Evidence is presented that CCEWs, including Kelvin, equatorial Rossby (ER), and mixed Rossby‐gravity (MRG) waves, significantly modulate daily rainfall extremes over Java Island. Of these three types, the Kelvin waves have the greatest influence on heavy rainfall over Java Island. The convectively active (suppressed) phases of Kelvin waves increase (decrease) the probability of extreme rain events over land regions by up to 60% (50%) of the baseline probability. On the other hand, the convectively active phases of ER (MRG) waves increase the probability by up to 45% (40%), while the suppressed phases decrease this by up to 40% (30%). In terms of the mechanism of rainfall extremes, CCEWs modulate moisture flux convergence, leading to the enhancement of local convection over the region. In addition, the analysis of multiple wave events indicates that positive (negative) interferences of the CCEWs lead to an amplification (suppression) of extreme rainfall probability. Overall, the results suggest that equatorial waves provide an important source of the predictability for daily extreme rainfall events over Java Island.</p><p><strong><span>Reference:</span></strong></p><p><span>Lubis, SW</span>, <span>Respati, MR</span>. <span>Impacts of convectively coupled equatorial waves on rainfall extremes in Java, Indonesia</span>. <em>Int J Climatol</em>. <span>2020</span>; <span>1</span>– <span>23</span>. </p><p> </p>

The influence of observations propagated by convectively coupled equatorial waves

2011 ◽  
Vol 137 (656) ◽  
pp. 641-655 ◽  
Author(s):  
Qoosaku Moteki ◽  
Kunio Yoneyama ◽  
Ryuichi Shirooka ◽  
Hisayuki Kubota ◽  
Kazuaki Yasunaga ◽  
...  
Keyword(s):  
Equatorial Waves ◽  
Convectively Coupled Equatorial Waves

scholarly journals Convectively Coupled Equatorial Waves. Part I: Horizontal and Vertical Structures

2007 ◽  
Vol 64 (10) ◽  
pp. 3406-3423 ◽  
Author(s):  
Gui-Ying Yang ◽  
Brian Hoskins ◽  
Julia Slingo
Keyword(s):  
Composite Structures ◽  
Wave Structure ◽  
Wave Theory ◽  
Western Hemisphere ◽  
Equatorial Waves ◽  
Kelvin Wave ◽  
Ambient Flow ◽  
Convectively Coupled Equatorial Waves ◽  
Eastern Hemisphere ◽  
Equatorial Wave

Abstract Multilevel 15-yr ECMWF Re-Analysis (ERA-15) and satellite-observed brightness temperature (Tb) data for the period May–October 1992 are used to examine the horizontal and vertical structures of convectively coupled equatorial waves. Dynamical waves are isolated using a methodology developed previously. Composite structures of convectively coupled equatorial waves are obtained using linear regression/correlation between convection (Tb) and dynamical structures. It is found that the relationship depends on the ambient flow and the nature of the convective coupling, and varies between off-equatorial- and equatorial-centered convection, different hemispheres, and seasons. The Kelvin wave structure in the Western Hemisphere is generally consistent with classic equatorial wave theory and has its convection located in the region of low-level convergence. In the Eastern Hemisphere the Kelvin wave tends to have convection in the region of enhanced lower-tropospheric westerlies and a tilted vertical structure. The Kelvin wave also tends to have a third peak in zonal wind amplitude at 500 hPa and exhibits upward propagation into the lower stratosphere. Lower-tropospheric westward-moving mixed Rossby–gravity (WMRG) and n = 1 Rossby (R1) wave structures and their relationship with convection are consistent with classic equatorial wave theory and the implied lower-tropospheric convergences. In the Eastern Hemisphere the WMRG and R1 waves have first baroclinic mode structures in the vertical. However, in the Western Hemisphere, the R1 wave has a barotropic structure. In the Eastern Hemisphere the R1 wave, like the Kelvin wave, tends to have equatorial convection in the region of enhanced lower-level westerlies, suggesting that enhanced surface energy fluxes associated with these waves may play an important organizing role for equatorial convection in this warm-water hemisphere. In the upper troposphere, eastward-moving Rossby–gravity (EMRG) and n = 1 gravity waves are found in the Eastern Hemisphere, and eastward-moving WMRG and R1 waves are found in the Western Hemisphere, suggestive of Doppler shifting of waves by the ambient flow.

scholarly journals Forecast Skill of the Madden–Julian Oscillation in Two Canadian Atmospheric Models

2008 ◽  
Vol 136 (11) ◽  
pp. 4130-4149 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet ◽  
Jacques Derome
Keyword(s):  
General Circulation ◽  
Initial Conditions ◽  
Circulation Model ◽  
Skill Score ◽  
Forecast Skill ◽  
Second Phase ◽  
Equatorial Waves ◽  
Madden Julian Oscillation ◽  
Atmospheric Models ◽  
Convectively Coupled Equatorial Waves

Abstract The output of two global atmospheric models participating in the second phase of the Canadian Historical Forecasting Project (HFP2) is utilized to assess the forecast skill of the Madden–Julian oscillation (MJO). The two models are the third generation of the general circulation model (GCM3) of the Canadian Centre for Climate Modeling and Analysis (CCCma) and the Global Environmental Multiscale (GEM) model of Recherche en Prévision Numérique (RPN). Space–time spectral analysis of the daily precipitation in near-equilibrium integrations reveals that GEM has a better representation of the convectively coupled equatorial waves including the MJO, Kelvin, equatorial Rossby (ER), and mixed Rossby–gravity (MRG) waves. An objective of this study is to examine how the MJO forecast skill is influenced by the model’s ability in representing the convectively coupled equatorial waves. The observed MJO signal is measured by a bivariate index that is obtained by projecting the combined fields of the 15°S–15°N meridionally averaged precipitation rate and the zonal winds at 850 and 200 hPa onto the two leading empirical orthogonal function (EOF) structures as derived using the same meridionally averaged variables following a similar approach used recently by Wheeler and Hendon. The forecast MJO index, on the other hand, is calculated by projecting the forecast variables onto the same two EOFs. With the HFP2 hindcast output spanning 35 yr, for the first time the MJO forecast skill of dynamical models is assessed over such a long time period with a significant and robust result. The result shows that the GEM model produces a significantly better level of forecast skill for the MJO in the first 2 weeks. The difference is larger in Northern Hemisphere winter than in summer, when the correlation skill score drops below 0.50 at a lead time of 10 days for GEM whereas it is at 6 days for GCM3. At lead times longer than about 15 days, GCM3 performs slightly better. There are some features that are common for the two models. The forecast skill is better in winter than in summer. Forecasts initialized with a large amplitude for the MJO are found to be more skillful than those with a weak MJO signal in the initial conditions. The forecast skill is dependent on the phase of the MJO at the initial conditions. Forecasts initialized with an MJO that has an active convection in tropical Africa and the Indian Ocean sector have a better level of forecast skill than those initialized with a different phase of the MJO.

Sign in / Sign up

Export Citation Format

Share Document