Numerical Simulations of Myanmar Cyclone Nargis and the Associated Storm Surge Part I: Forecast Experiment with a Nonhydrostatic Model and Simulation of Storm Surge

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Numerical Simulations of Myanmar Cyclone Nargis and the Associated Storm Surge Part I: Forecast Experiment with a Nonhydrostatic Model and Simulation of Storm Surge Journal of the Meteorological Society of Japan, Vol. 88, No. 3, pp. 521--545, 2010. 521 DOI:10.2151/jmsj.2010-315 Numerical Simulations of Myanmar Cyclone Nargis and the Associated Storm Surge Part I: Forecast Experiment with a Nonhydrostatic Model and Simulation of Storm Surge Tohru KURODA, Kazuo SAITO, Masaru KUNII Meteorological Research Institute, Tsukuba, Japan and Nadao KOHNO Japan Meteorological Agency, Tokyo, Japan (Manuscript received 27 May 2009, in final form 25 February 2010) Abstract Numerical simulations of the 2008 Myanmar cyclone Nargis and the associated storm surge were conducted using the Japan Meteorological Agency (JMA) Nonhydrostatic Model (NHM) and the Princeton Ocean Model (POM). Although the JMA operational global analysis (GA) and the global spectral model (GSM) forecast underestimated Nargis’ intensity, downscale experiments by NHM with a horizontal resolution of 10 km using GA and GSM forecast data reproduced the development of Nargis more properly. Sensitivity experiments to study the e¤ects of ice phase, sea surface temperature (SST), and horizontal resolu- tions to Nargis’ rapid development were conducted. In a warm rain experiment, Nargis developed earlier and the eye radius became larger. It was shown that a high SST anomaly preexistent in the Bay of Bengal led to the rapid intensification of the cyclone, and that SST at least warmer than 29C was necessary for the development seen in the experiment. In a simulation with a horizontal resolution of 5 km, the cyclone exhibited more distinct develop- ment and attained a center pressure of 968 hPa. Numerical experiments on the storm surge were performed with POM whose horizontal resolution is 3.5 km. An experiment with POM using GSM forecast data could not reproduce the storm surge, while a simulation us- ing NHM forecast data predicted a rise in the sea surface level by over 3 m. A southerly sub-surface current driven by strong surface winds of the cyclone caused a storm surge in the river mouths in southern Myanmar fac- ing the Andaman Sea. Our results demonstrate that the storm surge produced by Nargis was predictable two days before landfall by a downscale forecast with a mesoscale model using accessible operational numerical weather prediction (NWP) data and application of an ocean model. 1. Introduction tion is important for preventing and mitigating me- teorological disasters. In the areas around the Bay Severe meteorological phenomena such as tropi- of Bengal, historically, there have been several cal cyclones (TCs) sometimes cause catastrophic cases in which storm surges induced by TCs gave damage to human society; therefore, their predic- rise to severe floods (Obashi 1994). In cases such as the 1970 Bohla cyclone (Frank and Husain 1971) Corresponding author: Tohru Kuroda, Meteorological and the 1991 Bangladesh cyclone (Katsura et al. Research Institute, 1-1, Nagamine Tsukuba, Ibaraki 1992; Bern et al. 1993), cyclones generated in the 305-0052, Japan. E-mail: [email protected] central area of the bay moved northward and 6 2010, Meteorological Society of Japan made landfall in Bangladesh, and the associated 522 Journal of the Meteorological Society of Japan Vol. 88, No. 3 storm surges destroyed the lowlands of that coun- experiments, in which the JMA global spectral try. In 2007, cyclone Sidr struck the same area and model (GSM) forecast data are used as the lateral caused considerable destruction (MFDM Bangla- boundary conditions are conducted. Also, the re- desh 2008; Hasegawa et al. 2008). sults are compared with a reproduction experiment, In contrast with the above cases, cyclone Nargis in which global analyses (GA) are used as the lat- that was generated at the end of April 2008, moved eral boundary conditions instead of the GSM fore- eastward. On May 2, it made landfall in southern cast in order to observe the impact of the accuracy Myanmar during its strongest period and caused a of the lateral boundary value. destructive storm surge over the Irrawaddy Delta 2) To investigate the impact of the sea surface and other low-lying areas that claimed more than temperature (SST) and the physical process on the one hundred thousand lives (Webster 2008). For di- rapid development of Nargis: saster prediction in the areas mentioned above, SST is an important factor controlling the devel- forecasts of TCs and the associated storm surges opment of tropical cyclones. McPhaden et al. (2009) based on numerical weather prediction (NWP) are pointed out that there was a preexisting warm particularly important. anomaly of SST in the Bay of Bengal in late April Since 2007, a research project called ‘‘Interna- 2008 and inferred that this had contributed to the tional Research for Prevention and Mitigation of rapid intensification of Nargis. Lin et al. (2009) Meteorological Disasters in Southeast Asia’’ has determined that there were warm anomalies not been conducted by the Kyoto University, the Mete- only in the SST but also in the temperatures of orological Research Institute (MRI), and other in- the subsurface layer, and showed that this situation stitutes in Southeast Asian countries (Yoden et al. reduced the cyclone-induced ocean cooling by 2008; Koh and Teo 2009). The goals of this project using numerical experiments with a one-dimensional are to demonstrate the applicability of downscale ocean mixed layer model. However, neither Mc- NWP in Southeast Asia and to propose a decision Phaden et al. (2009) nor Lin et al. (2009) have con- support tool for preventing and mitigating meteo- ducted numerical simulation of Nargis using a full- rological disasters. From this point of view, we se- scale atmospheric model. In this paper, we examine lected the devastating disasters caused by Nargis as the impact of SST on Nargis’ development through one of the most important targets that we should sensitivity experiments using di¤erent SST datasets. study in this project. We assumed a minimum lead The impact of ice phase on Nargis’ development is time of two days before the landfall in order to ef- also examined, and the results are compared with fectively mitigate Nargis’ storm surge damage and the study by Sawada and Iwasaki (2007), in which set the initial time of our simulation as 12 UTC on simplified conditions including a horizontally uni- April 30, 2008, the time when Nargis started its form background were used. The impact of hori- eastward movement and one day before its rapid zontal resolution is also examined. These sensitivity development. Considering the project’s purpose experiments are not necessarily comprehensive, but and the real-time accessibility to data required for they give us information that help us to understand downscale NWP, the Japan Meteorological Agency the magnitude of the influence of the model un- (JMA) nonhydrostatic model (NHM) and the certainty with respect to the influence of the initial JMA’s operational global data are used as the fore- and boundary conditions on Nargis’ rapid develop- cast model and for obtaining the initial and/or ment. boundary conditions, respectively; the model and 3) To examine the predictability of storm surges the data are available and accessible to registered using downscale NWP and an ocean model: users in Southeast Asia. As for storm surges on the Bay of Bengal, In this paper, we conduct numerical simulation Flather (1994) studied storm surges associated with of Nargis and the associated storm surge for the the 1970 Bohla cyclone (Frank and Husain 1971) following purposes and scientific interests: and the 1991 Bangladesh cyclone using a numerical 1) To examine the predictability of Nargis two ocean model. However, this was a two-dimensional days before its landfall by downscale NWP using open sea model, with surface winds and pressures NHM and data available to Southeast Asian re- derived from a semi-analytical cyclone model using searchers: the best track data supplied by the US Navy Joint Considering the practical availability of the ex- Typhoon Warning Center (JTWC). periment in the case of real-time operation, forecast Recently, Kim et al. (2006) conducted numerical June 2010 T. KURODA et al. 523 simulation of the storm surge of Hurricane Ka- proached southern Myanmar. The minimum center trina, which damaged the city of New Orleans pressure estimated by JTWC was 937 hPa, while in the United States of America in 2005. The RSMC estimated its intensity as 962 hPa. The rain- simulation results obtained using a sophisticated fall rate observed by the Tropical Rainfall Measur- atmosphere-wave-ocean coupled model were in ing Mission’s Microwave Imager (TRMM/TMI) at agreement with the actual observations. However, 0137 UTC on May 2 is indicated in Fig. 2, which for achieving a practical disaster prevention, sim- depicts the typical structure of a developed cyclone pler surge predictions using a downscale mesoscale with a compact central dense overcast (CDO) and NWP and a one-way nested ocean model may be distinct spiral rainbands. After landfall at around more desirable, with application to the Bay of 09–12 UTC on May 2, the cyclone moved inland Bengal as an urgent subject (Dube et al. 2009). to the northeast, passing over southern Myanmar In this study, we conduct a numerical simulation and rapidly decayed. of the storm surge of Nargis, applying the Prince- 2.2 Storm surge of Nargis ton Ocean Model (POM) to the Bay of Bengal. The destructive damage in southern Myanmar The advantages of the NHM-simulated surface during the passage of Nargis was primarily caused winds and pressures over the GSM forecast will be by the storm surge, though the estimated maximum shown. wind speed exceeded 40 m/s. Since the river deltas This paper is organized as follows: Section 2 re- in southern Myanmar are low-lying, the storm views the characteristic features of Nargis and its surge reached inland several tens of kilometers associated storm surge.
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