Convective Parameterization in a Model for the Prediction of Heavy Rain in Southern Thailand

Abstract

Numerical weather predictions of three heavy rainfall events in the northeast monsoon causing floods and damage in southern Thailand are reported in this paper. The Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model (MM5) was used with the Betts-Miller (BM), Grell (GR), and new Kain-Fritsch (KF2) convective parameterization (CP) schemes at 5 km resolution, and also with an unparameterized or explicit (EX) scheme, to look for a promising method for precipitation forecasting. The accumulated precipitation amounts predicted by the model were evaluated qualitatively by comparison with the Tropical Rainfall Measuring Mission (TRMM) maps, and quantitatively by calculating statistical score indices for di¤erent rainfall thresholds. The simulations were evaluated by comparing the synoptic near surface fields with the NCEP FNL objective analysis fields and also with the vertical profiles of wind speed, temperature and mixing ratio at Songkhla station.The simulations gave generally satisfactory predictions of the synoptic fields, except for an overprediction of the relative humidity. The heavy rainfall was associated in each case with a small vortex where the northeasterly wind interacted with a warm humid southerly wind. The model underestimated the heavy rainfall amounts, and widely di¤erent rainfall patterns were produced by the di¤erent schemes used. The KF2 and EX schemes generally gave better results than the BM and GR schemes.

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“…This might be due to the dependency on a single stable humidity profile and disregard of cloud dynamics in the Betts-Miller convective adjustment scheme (Kerkhoven et al 2006) from which BMJ was derived. However, the KF (EXP2) performed slightly better, as found in a previous study for simulations at 5 km resolution (Yavinchan et al 2011). The KF CPS is a mass-flux parameterization modified from the previous KF scheme (Kain & Fritsch 1993).…”

“…These CPSs include Kain-Fritsch (KF) (Kain 2004), Betts-Miller-Janjic (BMJ) (Janjic 1994), multi-scale Kain-Fritsch (MKF) (Zheng et al 2016), new simplified Arakawa-Schubert (NS) (Han & Pan 2011), and the new Tiedtke scheme (NT). The KF, BMJ, and Arakawa-Schubert schemes are widely used in tropical weather prediction (Ardie et al 2012;Kumar et al 2008;Salimun et al 2010;Yavinchan et al 2011). The combinations of these CPSs in all three different domains are denoted as Experiments 1 to 10 (EXP 1 to 10, Table 1).…”

“…For better prediction skill, a model must be able to properly represent moist convection at smaller scales. In Juneng et al (2007), Salimun et al (2010), and Yavinchan et al (2011), overestimation of heavy rainfall was a common issue. For NWP model forecast skill improvement, holistic understanding of errors and their growth is needed (Zhang et al 2006) and this aspect has yet to be researched adequately over this region.…”

“…Despite the urgent and crucial needs for skilful forecasts, research and developmental works to improve numerical weather prediction (NWP) over this region appear limited Salimun et al 2010;Yavinchan et al 2011). These earlier studies focused merely on assessing the performance of certain parameterization schemes, and process understanding.…”

Uji Sensitivitas Skema Parameterisasi Cumulus untuk Prediksi Hujan di Wilayah Jawa Timur

“…Beberapa penelitian untuk menguji skema parameterisasi pada model WRF-ARW telah dilakukan baik di dunia ataupun di Indonesia, diantaranya oleh: Gilliland [8]; Mercader [9]; serta Yavichan [10] yang menguji ketiga skema parameterisasi tersebut di Nebraska, Catalonia, dan South Thailand dengan memperoleh hasil bahwa skema Kain-Fritch paling baik digunakan untuk simulasi pada daerah tersebut. Sedangkan di Indonesia telah dilakukan pengujian ketiga skema tersebut, juga dilakukan untuk melihat sensitivitas parameterisasi antara lain dilakukan oleh Santriyani [2] yang menghasilkan bahwa skema Grell-Devenyi merupakan skema terbaik dalam analisa hujan ekstrim di Jakarta, pengujian skema dilakukan juga oleh Ginting [7] dengan hasil skema BMJ merupakan skema terbaik dalam kejadian angin kencang di Makassar, dan penelitian oleh Kurniawan, [11] yang meneliti wilayah Surabaya (Juanda) dan Jakarta (Cengkareng) dengan hasil bahwa skema BMJ merupakan skema terbaik digunakan dalam prakiraan hujan di Surabaya, serta GD dan KF baik untuk digunakan di Jakarta [11].…”