EVALUATION OF THE CORDEX-SEA MODELS PERFORMANCE IN SIMULATING CHARACTERISTICS OF WET SEASON IN INDONESIA

Authors

  • Rini Hidayati Departemen Geofisika dan Meteorologi, FMIPA, IPB University
  • Supari Supari Pusat Informasi Perubahan Iklim, Badan Meteorologi Klimatologi dan Geofisika
  • Alif Akbar Syafrianno Departemen Geofisika dan Meteorologi, FMIPA, IPB University Pusat Informasi Perubahan Iklim, Badan Meteorologi Klimatologi dan Geofisika
  • Akhmad Faqih Institut Pertanian Bogor (IPB)

DOI:

https://doi.org/10.31172/jmg.v24i1.965

Keywords:

CORDEX-SEA, model evaluation, wet season

Abstract

Indonesia's climate is known to be challenging to adequately simulate by climate models because of the complexity of the weather system and sea-land distribution. Model evaluation is essential to measure confidence in the model results. This study evaluates the performance of the CORDEX-SEA model in simulating monthly rainfall patterns and the characteristics of seasonal rainfall, i.e., pattern, timing, length, and intensity, in Indonesia during 1986-2005. The performance of weighted (WMME) and unweighted ensemble methods are also calculated. Corrected CHIRPS data with similar seasonal patterns with point observation data is used as reference data to evaluate models. Percentage of the agreement of seasonal patterns between models and observation, FAR, and POD values were used to assess the model's ability to simulate seasonal patterns. WMME has the best seasonal patterns agreement with observation, 67% of all grids. The best model performance is shown by monsoonal patterns, with a POD value of 83% by WMME. Otherwise, all models could not describe an anti-monsoonal pattern, with a small POD (0-33%) and a high FAR (60-100%). In simulating the wet season on climatological, annual, and annual mean scales, both MMEs have similar performance and are better than individual models, with WMME performing best. However, on an annual scale, the yearly wet season produced by all models tends to approach its climatology value, making it less reliable in extreme years. Most models have higher daily and monthly rainfall than observation. In conclusion, the weighted ensemble method describes Indonesia's rainy season well, thus providing a reasonable basis for further research in climate projection analysis.

Author Biography

Akhmad Faqih, Institut Pertanian Bogor (IPB)

h-index Google Scholar: 6

References

LQ Avia, “Change in rainfall per-decades over Java Island, Indonesia,” IOP Conf. Ser. Earth Environment. sci. , vol. 374, no. 1, p. 012037, Nov. 2019, doi: 10.1088/1755-1315/374/1/012037.

N. Herlina and A. Prasetyorini, "Effect of Climate Change on Planting Season and Productivity of Maize (Zea mays L.) in Malang Regency," J. Agricultural Science. Indonesia. , vol. 25, no. 1, pp. 118–128, Jan. 2020, doi: 10.18343/jipi.25.1.118.

AB Sekaranom, E. Nurjani, and F. Nucifera, “Agricultural Climate Change Adaptation in Kebumen, Central Java, Indonesia,” Sustainability , vol. 13, no. 13, p. 7069, Jun. 2021, doi: 10.3390/su13137069.

RL Naylor, DS Battisti, DJ Vimont, WP Falcon, and MB Burke, “Assessing risks of climate variability and climate change for Indonesian rice agriculture,” Proc. Christmas. Acad. sci. , vol. 104, no. 19, pp. 7752–7757, May 2007, doi: 10.1073/pnas.0701825104.

F. Tangang et al. , “Projected future changes in rainfall in Southeast Asia based on CORDEX–SEA multi-model simulations,” Clim. Dyn. , vol. 55, no. 5–6, pp. 1247–1267, Sept. 2020, doi: 10.1007/s00382-020-05322-2.

J. -I. Hamada, MD Yamanaka, J. Matsumoto, S. Fukao, PA Winarso, and T. Sribimawati, “Spatial and Temporal Variations of the Rainy Season over Indonesia and their Link to ENSO.,” J. Meteorol . Soc. jpn. Ser II , vol. 80, no. 2, pp. 285–310, 2002, doi: 10.2151/jmsj.80.285.

E. Aldrian and R. Dwi Susanto, "Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature," Int. J. Climatol. , vol. 23, no. 12, p. 1435–1452, Oct. 2003, doi: 10.1002/joc.950.

B. Liebmann et al. , “Seasonality of African Precipitation from 1996 to 2009,” J. Clim. , vol. 25, no. 12, p. 4304–4322, Jun. 2012, doi: 10.1175/JCLI-D-11-00157.1.

CM Dunning, ECL Black, and RP Allan, “The onset and cessation of seasonal rainfall over Africa,” J. Geophys. Res. Atmospheres , vol. 121, no. 19, Oct. 2016, doi: 10.1002/2016JD025428.

CM Dunning, E. Black, and RP Allan, “Later Wet Seasons with More Intense Rainfall over Africa under Future Climate Change,” J. Clim. , vol. 31, no. 23, pp. 9719–9738, Dec. 2018, doi: 10.1175/JCLI-D-18-0102.1.

B. Wang et al. , “Monsoons Climate Change Assessment,” Bull. Am. meteorol. Soc. , vol. 102, no. 1, pp. E1–E19, Jan. 2021, doi: 10.1175/BAMS-D-19-0335.1.

G. Nikulin et al. , “The effects of 1.5 and 2 degrees of global warming on Africa in the CORDEX ensemble,” Environ. Res. Lett. , vol. 13, no. 6, p. 065003, May 2018, doi: 10.1088/1748-9326/aab1b1.

F. Ge et al. , “Risks of precipitation extremes over Southeast Asia: does 1.5 °C or 2 °C global warming make a difference?,” Environ. Res. Lett. , vol. 14, no. 4, p. 044015, Apr. 2019, doi: 10.1088/1748-9326/aaff7e.

Supari et al. , “Multi-model projections of precipitation extremes in Southeast Asia based on CORDEX-Southeast Asia simulations,” Environ. Res. , vol. 184, p. 109350, May 2020, doi: 10.1016/j.envres.2020.109350.

M. Herrmann, T. Nguyen-Duy, T. Ngo-Duc, and F. Tangang, “Climate change impact on sea surface winds in Southeast Asia,” Int. J. Climatol. , vol. 42, no. 7, pp. 3571–3595, 2022, doi: https://doi.org/10.1002/joc.7433.

SI Seneviratne et al. , “Changes in Climate Extremes and their Impacts on the Natural Physical Environment,” in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change , CB Field, Q. Dahe, TF Stocker , and V. Barros, Eds. Cambridge: Cambridge University Press, 2012, pp. 109–230. doi: 10.1017/CBO9781139177245.006.

E. -S. Im, Y. -W. Choi, and J. -B. Ahn, "Robust intensification of hydroclimatic intensity over East Asia from multi-model ensemble regional projections," Theor. appl. climatol. , vol. 129, no. 3–4, pp. 1241–1254, Aug. 2017, doi: 10.1007/s00704-016-1846-2.

N. Herger, G. Abramowitz, R. Knutti, O. Angélil, K. Lehmann, and BM Sanderson, “Selecting a climate model subset to optimize key ensemble properties,” Earth Syst. Dyn. , vol. 9, no. 1, pp. 135–151, Feb. 2018, doi: 10.5194/esd-9-135-2018.

C. Miao, Q. Duan, Q. Sun, and J. Li, “Evaluation and application of Bayesian multi-model estimation in temperature simulations,” Prog. Phys. geogr. Earth Environment. , vol. 37, no. 6, pp. 727–744, Dec. 2013, doi: 10.1177/0309133313494961.

D. Nohara, A. Kitoh, M. Hosaka, and T. Oki, “Impact of Climate Change on River Discharge Projected by Multimodel Ensemble,” J. Hydrometeorol. , vol. 7, no. 5, pp. 1076–1089, Oct. 2006, doi: 10.1175/JHM531.1.

WS Hariadi et al. , “Evaluation of onset, cessation and seasonal precipitation of the Southeast Asia rainy season in CMIP5 regional climate models and HIGHRESMIP global climate models,” Int. J. Climatol. , vol. 42, no. 5, pp. 3007–3024, Apr. 2022, doi: 10.1002/joc.7404.

M. Collins et al. , “Long-term climate change: Projections, commitments and irreversibility,” in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change , TF Stocker, D. Qin, G.-K. Plattner, M. Tignor, SK Allen, J. Doschung, A. Nauels, Y. Xia, V. Bex, and PM Midgley, Eds. Cambridge, UK: Cambridge University Press, 2013, pp. 1029–1136. doi: 10.1017/CBO9781107415324.024.

C. Funk et al. , “The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes,” Sci. Data , vol. 2, no. 1, p. 150066, Dec. 2015, doi: 10.1038/sdata.2015.66.

Supari, F. Tangang, L. Juneng, and E. Aldrian, “Observed changes in extreme temperature and precipitation over Indonesia: EXTREME TEMPERATURE AND PRECIPITATION OVER INDONESIA,” Int. J. Climatol. , vol. 37, no. 4, pp. 1979–1997, Mar. 2017, doi: 10.1002/joc.4829.

F. Giorgi et al. , “RegCM4: model description and preliminary tests over multiple CORDEX domains,” Clim. Res. , vol. 52, pp. 7–29, Mar. 2012, doi: 10.3354/cr01018.

J. Michalakes et al. , “THE WEATHER RESEARCH AND FORECAST MODEL: SOFTWARE ARCHITECTURE AND PERFORMANCE,” in Use of High Performance Computing in Meteorology , Reading, UK, Sep. 2005, pp. 156–168. doi: 10.1142/9789812701831_0012.

G. Strandberg et al. , “CORDEX scenarios for Europe from the Rossby Center regional climate model RCA4,” SMHI , vol. 116, 2014.

DV Sein et al. , “Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation,” J. Adv. Model. Earth System. , vol. 7, no. 1, pp. 268–304, Mar. 2015, doi: 10.1002/2014MS000357.

KE Taylor, “Summarizing multiple aspects of model performance in a single diagram,” J. Geophys. Res. Atmospheres , vol. 106, no. D7, pp. 7183–7192, Apr. 2001, doi: 10.1029/2000JD900719.

X. Yang et al. , “The Optimal Multimodel Ensemble of Bias-Corrected CMIP5 Climate Models over China,” J. Hydrometeorol. , vol. 21, no. 4, pp. 845–863, Apr. 2020, doi: 10.1175/JHM-D-19-0141.1.

RPD Walsh and DM Lawler, “RAINFALL SEASONALITY: DESCRIPTION, SPATIAL PATTERNS AND CHANGE THROUGH TIME,” Weather , vol. 36, no. 7, pp. 201–208, Jul. 1981, doi: 10.1002/j.1477-8696.1981.tb05400.x.

T. Peterson, “Climate change indices,” WMO Bull. , vol. 54, no. 2, pp. 83–86, 2005.

Y. Darmawan, H.-H. Hsu, and J. -Y. Yu, “Characteristics of Large-Scale Circulation Affecting the Inter-Annual Precipitation Variability in Northern Sumatra Island during Boreal Summer,” Atmosphere , vol. 12, no. 2, 2021, doi: 10.3390/atmos12020136.

R. Knutti, R. Furrer, C. Tebaldi, J. Cermak, and GA Meehl, “Challenges in Combining Projections from Multiple Climate Models,” J. Clim. , vol. 23, no. 10, p. 2739–2758, 2010, doi: 10.1175/2009JCLI3361.1.

L. Juneng et al. , “Sensitivity of Southeast Asia rainfall simulations to cumulus and air-sea flux parameterizations in RegCM4,” Clim. Res. , vol. 69, no. 1, pp. 59–77, Jun. 2016, doi: 10.3354/cr01386.

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Published

2023-08-28 — Updated on 2024-02-02

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Hidayati, R., Supari, S., Syafrianno, A. A., & Faqih, A. (2024). EVALUATION OF THE CORDEX-SEA MODELS PERFORMANCE IN SIMULATING CHARACTERISTICS OF WET SEASON IN INDONESIA. Jurnal Meteorologi Dan Geofisika, 24(1), 39–51. https://doi.org/10.31172/jmg.v24i1.965 (Original work published August 28, 2023)

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Vol. 24 No. 1 (2023)

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Copyright (c) 2023 Rini Hidayati, Supari Supari, Alif Akbar Syafrianno, Akhmad Faqih

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