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Synoptic analysis and mesoscale numerical modelling of heavy precipitation: a case study of flash flood event in Kota Kinabalu, Malaysia

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Abstract

A case of severe flash flood event affecting Kota Kinabalu (KK) on 17 Jul 2005 is analyzed by means of synoptic analysis using ERA-Interim Reanalysis and NCEP-FNL Data sets. In the synoptic scale, significant amount of precipitation was recorded in Sabah on 16 Jul and 17 Jul 2005. The heavy rainfall was associated to the upper-level ridge and lower-level cyclone observed over the South China Sea. Several low-pressure centers were also noticed over the Philippines Sea which were believed to intensify the heavy rainfall in Sabah. The vertical cross section for divergence along 116°E at Kota Kinabalu also revealed that a significant convergence was observed near the surface and accompanied by a strong updraft of divergence at upper-level. In the mesoscale, the ability of the convection-permitting WRF model to reproduce the convective cells associated with the heavy rainfall event is examined. A triply nested WRF model with the highest resolution of 5-km horizontal grid spacing was integrated with conventional analysis data. The simulation results were validated against observation from TRMM, CHIRPS, and PERSIANN-CDR. The modelled results agree moderately to the observation and fairly well simulated the initiation, intensification, and deceleration of heavy rainfall at nearly the right time except for some mismatch in terms of spatial distribution. The corresponding precipitation amount was also reasonably reproduced in its distribution but slightly overestimated. We also found that the cause of this severe flash flood is rooted to the prolonged heavy rainfall in the KK region induced by Typhoon Haitang.

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References

  • Ardie WA, Sow KS, Tangang FT et al (2012) The performance of different cumulus parameterization schemes in simulating the 2006/2007 southern peninsular Malaysia heavy rainfall episodes. J Earth Syst Sci 121:317–327

    Article  Google Scholar 

  • Ashouri H, Gehne M, National Center for Atmospheric Research Staff (eds) (2018) Last modified 10 Dec 2018. The Climate Data Guide: PERSIANN-CDR: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Climate Data Record. https://climatedataguide.ucar.edu/climate-data/persiann-cdr-precipitation-estimation-remotely-sensed-information-using-artificial.

  • Berrisford P, Dee D, Poli P, Brugge R, Fielding K, Fuentes M et al (2011) The ERA-Interim archive, version 2.0

  • Bruintjes RT, Clark TL, Hall WD (1994) Interactions between topographic airflow and cloud/precipitation development during the passage of a winter storm in Arizona. J Atmos Sci 51:48–67

    Article  Google Scholar 

  • Carbone RE, Tuttle JD, Ahijevych DA, Trier SB (2002) Inferences of predictability associated with warm season precipitation episodes. J Atmos Sci 59:2033–2056

    Article  Google Scholar 

  • Cardoso RM, Soares PMM, Miranda PMA, Belo-Pereira M (2013) WRF high resolution simulation of Iberian mean and extreme precipitation climate. Int J Climatol 33:2591–2608. https://doi.org/10.1002/joc.3616

    Article  Google Scholar 

  • Chawla I, Osuri KK, Mujumdar PP, Niyogi D (2018) Assessment of the weather research and forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin. Hydrol Earth Syst Sci 22(2):5

    Article  Google Scholar 

  • Colle BA, Mass CF (1996) An observational and modeling study of the interaction of low-level southwesterly flow with the olympic mountains during COAST IOP 4. Mon Weather Rev 124:2152–2175. https://doi.org/10.1175/1520-0493(1996)124%3c2152:AOAMSO%3e2.0.CO;2

    Article  Google Scholar 

  • Colle BA, Mass CF, Westrick KJ (2000) MM5 precipitation verification over the Pacific Northwest during the 1997–99 cool seasons. Weather Forecast 15:730–744. https://doi.org/10.1175/1520-0434(2000)015%3c0730:MPVOTP%3e2.0.CO;2

    Article  Google Scholar 

  • Davis BAS, Brewer S, Stevenson AC, Guiot J (2003) The temperature of Europe during the Holocene reconstructed from pollen data. Q Sci Rev 22:1701–1716. https://doi.org/10.1016/S0277-3791(03)00173-2

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597

    Article  Google Scholar 

  • Deng L, McCabe MF, Stenchikov G, Evans JP, Kucera PA (2015) Simulation of flash-flood-producing storm events in Saudi Arabia using the weather research and forecasting model. J Hydrometeorol 16(2):615–630

    Article  Google Scholar 

  • Dudhia J (1989) Numerical Study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107. https://doi.org/10.1175/1520-0469(1989)046%3c3077:NSOCOD%3e2.0.CO;2

    Article  Google Scholar 

  • Efstathiou GA, Zoumakis NM, Melas D et al (2013) Sensitivity of WRF to boundary layer parameterizations in simulating a heavy rainfall event using different microphysical schemes: effect on large-scale processes. Atmos Res 132–133:125–143. https://doi.org/10.1016/j.atmosres.2013.05.004

    Article  Google Scholar 

  • Fiori E, Comellas A, Molini L, Rebora N, Siccardi F, Gochis DJ, Tanelli S, Parodi A (2014) Analysis and hindcast simulations of an extreme rainfall event in the Mediterranean area: the Genoa 2011 case. Atmos Res 138:13–29

    Article  Google Scholar 

  • Flesch TK, Reuter GW (2012) WRF model simulation of two Alberta flooding events and the impact of topography. J Hydrometeorol 13:695–708. https://doi.org/10.1175/JHM-D-11-035.1

    Article  Google Scholar 

  • Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison L, Hoell A, Michaelsen J (2015) The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci Data 2:150066

    Article  Google Scholar 

  • Gallus WAJ, Correia JJ, Jankov I (2005) The 4 June 1999 Derecho event: a particularly difficult challenge for numerical weather prediction. Weather Forecast 20:705–728. https://doi.org/10.1175/WAF883.1

    Article  Google Scholar 

  • Gaudet B, Cotton WR (1998) Statistical characteristics of a real-time precipitation forecasting model. Weather Forecast 13:966–982. https://doi.org/10.1175/1520-0434(1998)013%3c0966:SCOART%3e2.0.CO;2

    Article  Google Scholar 

  • Givati A, Lynn B, Liu Y, Rimmer A (2011) Using the WRF model in an operational streamflow forecast system for the Jordan River. J Appl Meteorol Climatol 51(2):285–299

    Article  Google Scholar 

  • Haghroosta T, Ismail WR, Ghafarian P, Barekati SM (2014) The efficiency of the Weather Research and Forecasting ( WRF ) model for simulating typhoons. Nat Hazards Earth Syst Sci 14:2179–2187. https://doi.org/10.5194/nhess-14-2179-2014

    Article  Google Scholar 

  • Hahn DC (2007) Evaluation of WRF performance for depicting orographically-induced gravity waves in the stratosphere. In: Proceedings of the 8th WRF user’s workshop

  • Hong SY, Lee JW (2009) Assessment of the WRF model in reproducing a flash-flood heavy rainfall event over Korea. Atmos Res 93:818–831. https://doi.org/10.1016/j.atmosres.2009.03.015

    Article  Google Scholar 

  • Hong S, Lim J (2006) The WRF single-moment 6-class microphysics scheme (WSM6). J Korean Meteorol Soc 42:129–151

    Google Scholar 

  • Hong S-Y, Dudhia J, Chen S-H (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–120. https://doi.org/10.1175/1520-0493(2004)132%3c0103:ARATIM%3e2.0.CO;2

    Article  Google Scholar 

  • Hong S-Y, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341. https://doi.org/10.1175/MWR3199.1

    Article  Google Scholar 

  • Hong SY, Moon NK, Lim KS, Kim JW (2010) Future climate change scenarios over Korea using a multi-nested downscaling system: a pilot study. Asia Pac J Atmos Sci 46(4):425–435

    Article  Google Scholar 

  • Hsu KL, Gao X, Sorooshian S, Gupta HV (1997) Precipitation estimation from remotely sensed information using artificial neural networks. J App Meteor 36(9):1176–1190

    Article  Google Scholar 

  • Huffman GJ (1997) Estimates of root-mean-square random error for finite samples of estimated precipitation. J Appl Meteorol 36(9):1191–1201

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Nelkin EJ (2010) The TRMM Multi-Satellite Precipitation Analysis (TMPA). Satellite rainfall applications for surface hydrology. Springer, Netherlands, Dordrecht, pp 3–22

    Chapter  Google Scholar 

  • Jee JB, Kim S (2017) Sensitivity study on high-resolution WRF precipitation forecast for a heavy rainfall event. Atmosphere 8(6):96

    Article  Google Scholar 

  • Kain JS (2004) The Kain–Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181. https://doi.org/10.1175/1520-0450(2004)043%3c0170:TKCPAU%3e2.0.CO;2

    Article  Google Scholar 

  • Lee KO, Uyeda H, Lee DI (2014) Microphysical structures associated with enhancement of convective cells over Mt. Halla, Jeju Island, Korea on 6 Jul 2007. Atmos Res 135:76–90

    Article  Google Scholar 

  • Mass CF, Ovens D, Westrick K, Colle BA (2002) Does increasing horizontal resolution produce more skillful forecasts? Am Meteorol Soc 1:407–430. https://doi.org/10.1175/1520-0477(2002)083

    Article  Google Scholar 

  • Maussion F, Scherer D, Finkelnburg R, Richters J, Yang W, Yao T (2011) WRF simulation of a precipitation event over the Tibetan Plateau, China—an assessment using remote sensing and ground observations. Hydrol Earth Syst Sci 15(6):5

    Article  Google Scholar 

  • Mlawer EJ, Taubman SJ, Brown PD et al (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res Atmos 102:16663–16682. https://doi.org/10.1029/97JD00237

    Article  Google Scholar 

  • Molg T, Chiang JCH, Gohm A, Cullen NJ (2009) Temporal precipitation variability versus altitude on a tropical high mountain: observations and mesoscale atmospheric modelling. Q J R Meteorol Soc 135:1439–1455

    Article  Google Scholar 

  • Oozeer MY, Chan A, Ooi MCG, Zarzur AM, Salinas SV, Chew BN, Morris KI, Choong WK (2016) Numerical study of the transport and convective mechanisms of biomass burning haze in South-Southeast Asia. Aerosol Air Qual Res 16:2950–2963

    Article  Google Scholar 

  • Parrish DF, Derber JC (1992) The National Meteorological Center's spectral statistical-interpolation analysis system. Mon Weather Rev 120(8):1747–1763

    Article  Google Scholar 

  • Rahmawati N, Lubcznski MW (2018) Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia. Theor Appl Climatol 134:513–532

    Article  Google Scholar 

  • Raju PVS, Potty J, Mohanty UC (2011) Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model. Meteorol Atmos Phys 113:125–137. https://doi.org/10.1007/s00703-011-0151-y

    Article  Google Scholar 

  • Rogelis MC, Werner M (2018) Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas. Hydrol Earth Syst Sci 22(1):853–870

    Article  Google Scholar 

  • Santos-Alamillos FJ, Pozo-Vázquez D, Ruiz-Arias JA, Lara-Fanego V, Tovar-Pescador J (2013) Analysis of WRF model wind estimate sensitivity to physics parameterization choice and terrain representation in Andalusia (Southern Spain). J Appl Meteorol Climatol 52(7):1592–1609

    Article  Google Scholar 

  • Singh J, Yeo K, Liu X et al (2015) Evaluation of WRF model seasonal forecasts for tropical region of Singapore. Adv Sci Res 12:69–72. https://doi.org/10.5194/asr-12-69-2015

    Article  Google Scholar 

  • Sorooshian S, Hsu K, Braithwaite D, Ashouri H (2014) NOAA climate data record (CDR) of precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN-CDR), Version 1, Revision 1. https://gis.ncdc.noaa.gov/geoportal/catalog/search/resource/details.page

  • Weisman ML, Davis C, Wang W et al (2008) Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Weather Forecast 23:407–437. https://doi.org/10.1175/2007WAF2007005.1

    Article  Google Scholar 

  • Wilson JW, Roberts RD (2006) Summary of convective storm initiation and evolution during IHOP: observational and modeling perspective. Mon Weather Rev 134:23–47. https://doi.org/10.1175/MWR3069.1

    Article  Google Scholar 

  • Xue M, Martin WJ (2006) A high-resolution modeling study of the 24 May 2002 dryline case during IHOP. Part I: Numerical simulation and general evolution of the dryline and convection. Mon Weather Rev 134:149–171. https://doi.org/10.1175/MWR3071.1

    Article  Google Scholar 

  • Zhang D-L, Gao K, Parsons DB (1988) Numerical Simulation of an Intense Squall Line during 10–11 June 1985 PRE-STORM. Part I: model verification. Mon Weather Rev 117:960–994

    Article  Google Scholar 

  • Zhou J, Zhang H, Zhang J et al (2017) WRF model for precipitation simulation and its application in real-time flood forecasting in the Jinshajiang River Basin, China. Meteorol Atmos Phys 1:1–13. https://doi.org/10.1007/s00703-017-0542-9

    Article  Google Scholar 

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Acknowledgements

This research was supported by the Malaysian Ministry of Education under the research Grant number SBK0352-2017 and was greatly acknowledged.

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Correspondence to Jackson Hian-Wui Chang.

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Chang, J.HW., Kong, S.S.K., Sentian, J. et al. Synoptic analysis and mesoscale numerical modelling of heavy precipitation: a case study of flash flood event in Kota Kinabalu, Malaysia. Meteorol Atmos Phys 132, 181–201 (2020). https://doi.org/10.1007/s00703-019-00682-9

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