Koreksi Bias Data Hujan Luaran GCM ECHAM5 Untuk Prediksi Curah Hujan Bulanan dan Musiman Pulau Lombok: Bias Correction for GCM ECHAM5 Model Rainfall Data Output in Estimating Monthly and Seasonally Rainfall for Lombok Island

Humairo Saidah; Agustono  Setiawan; Lilik  Hanifah; Eko  Pradjoko; Agus  Suroso

doi:10.29303/jstl.v7i2.289

Authors

Humairo Saidah Mataram University
Agustono Setiawan Jurusan Teknik Sipil Fakultas Teknik, Universitas Mataram
Lilik Hanifah Jurusan Teknik Sipil Fakultas Teknik, Universitas Mataram
Eko Pradjoko Jurusan Teknik Sipil Fakultas Teknik, Universitas Mataram
Agus Suroso Jurusan Teknik Sipil Fakultas Teknik, Universitas Mataram

DOI:

https://doi.org/10.29303/jstl.v7i2.289

Keywords:

koreksi, bias, model iklim global, ECHAM5

Abstract

This study aims to evaluate the ability of the ECHAM5 GCM model output data in estimating monthly rainfall on the island of Lombok. The data used in this study are ECHAM5 monthly rainfall data and automatic rainfall recorder (ARR) measurement rain data for 2000-2018 obtained from ARR Gunung Sari. Correction of bias is conducted by using the mean ratio method and the regression method. The method that produces the best approach is then used to obtain rain data projections and a simple regression method. Evaluation and validation used the Pearson correlation coefficient (r), Root Mean Square Error (RMSE) and Nash-Sutcliffe Efficiency (NSE) values. The results obtained are that the daily and monthly rainfall data from the ECHAM5 model cannot be directly used to replace the rain measurement data because of its very low accuracy. The downscaling technique performed on daily and monthly rainfall data using the average ratio method does not show satisfactory performance where the efficiency figures produced are still low even gave a slight increasing number. However, the ECHAM5 model data can be used to obtain rainfall projections on a monthly and seasonal scale with a good and satisfactory correlation. Key words: mean ratio method; global climate model; ECHAM5; monthly rainfall.

Author Biography

Humairo Saidah, Mataram University

Civil engineering

References

Abdulhalim, D.F., Tanudjaja, L., Sumarauw, J.S., 2018. Analisis Debit Banjir Dan Tinggi Muka Air Sungai Talawaan Di Titik 250 M Sebelah Hulu Bendung Talawaan. Jurnal Sipil Statik 6.

Aprilestari, N., Setiawan, A., Saidah, H., 2021. Analisis Keseimbangan Air Daerah Irigasi Gebong, Kecamatan Narmada Lombok Barat.

Araya-Osses, D., Casanueva, A., Román-Figueroa, C., Uribe, J.M., Paneque, M., 2020. Climate change projections of temperature and precipitation in Chile based on statistical downscaling. Climate Dynamics 54, 4309–4330.

Asyeifa, V.R., 2017. Pemodelan Statistical Downscaling Dengan Projection Pursuit Regression Untuk Meramalkan Curah Hujan Bulanan Di Sentra Produksi Padi Jawa Timur. ITS.

Azhar, K.J., Gunawan, T.A., 2021. Analisis Debit Andalan Untuk Probabilitas Terpenuhi Kebutuhan Air Irigasi Dalam Pengairan Lahan Pertanian Di Desa Paldas Kecamatan Rantau Bayur Kabupaten Banyuasin.

Budiyono, B., Faisol, A., 2021. Evaluasi Data Climate Hazards Group Infrared Precipitation With Station (Chirps) Dengan Data Pembanding Automatic Weather Stations (Aws) Dalam Mengestimasi Curah Hujan Harian Di Provinsi Papua BaratT. Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) 10, 64–72. https://doi.org/10.23960/jtep-l.v10i1.64-72

Bunganaen, W., Karbeka, N.S., Hangge, E.E., 2020. Analisis Ketersediaan Air Terhadap Pola Tanam dan Luas Areal Irigasi Daerah Irigasi Siafu. Jurnal Teknik Sipil 9, 15–26.

Chaniago, D., 2021. Kajian Kekeringan Meteorologis dengan Metode Standardized Precipitation Index (SPI) di Bagian Selatan Provinsi Daerah Istimewa Yogykarta (DIY).

Derrick, T.R., Thomas, J.M., 2004. Time series analysis: the cross-correlation function.

Eden, J.M., Widmann, M., 2014. Downscaling of GCM-Simulated Precipitation Using Model Output Statistics. Journal of Climate 27, 312–324. https://doi.org/10.1175/JCLI-D-13-00063.1

Faqih, A., 2017. A Statistical Bias Correction Tool for Generating Climate Change Scenarios in Indonesia based on CMIP5 Datasets. IOP Conf. Ser.: Earth Environ. Sci. 58, 012051. https://doi.org/10.1088/1755-1315/58/1/012051

Ginting, J.M., Sujono, J., Jayadi, R., 2019. Analisis Hubungan Data Hujan Satelit dengan Hujan Terukur ARR Kalibawang, in: Pros. Konf. Pascasarj. Tek. Sipil, No. November. pp. 89–102.

Hutama, W., Mursalin, M., Wulansari, S., 2021. Analisis Kebutuhan Dan Ketersediaan Air Di Desa Pulau Pandan Kecamatan Bukit Karman Kabupaten Kerinci.

Jain, S.K., Sudheer, K., 2008. Fitting of hydrologic models: a close look at the Nash–Sutcliffe index. Journal of hydrologic engineering 13, 981–986.

Maraun, D., Widmann, M., Gutiérrez, J.M., 2019. Statistical downscaling skill under present climate conditions: A synthesis of the VALUE perfect predictor experiment. International Journal of Climatology 39, 3692–3703.

Nam, C.C., Quaas, J., 2012. Evaluation of clouds and precipitation in the ECHAM5 general circulation model using CALIPSO and CloudSat satellite data. Journal of Climate 25, 4975–4992.

Negara, I.D.G.J., BUDIANTO, M.B., SUPRIYADI, A., SAIDAH, H., 2020. Analisis kebutuhan air tanaman dengan metode caoli pada tanaman tomat dengan irigasi tetes di lahan kering lombok utara. Ganec Swara 14, 419–425.

Nggarang, Y.E.P., Pattiraja, A.H., Henong, S.B., 2020. Analisa Perbandingan Penentuan Debit Rencana Menggunakan Metode Nakayasu dan Simulasi Aplikasi HEC-HMS di Das Lowo Rea. Eternitas: Jurnal Teknik Sipil 1, 23–33.

Novita, F., Harisuseno, D., Suhartanto, E., 2021. Studi Kekeringan Meteorologi dengan Menggunakan Metode Standardized Precipitation Index (SPI) dan China Z Index (CZI) di DAS Lekso Kabupaten Blitar. Jurnal Teknologi dan Rekayasa Sumber Daya Air 1, 648–660.

Osly, P.J., Dwiyandi, F., Ihsani, I., Ririhena, R.E., 2019. Analisis Kebutuhan Dan Ketersediaan Air Kabupaten Manokwari dengan Model Mock. Jurnal Infrastruktur 5, 59–67.

Pariartha, I.P.G.S., Arimbawa, I.K.D., Yekti, M.I., 2021. Analisis Debit Rencana Tukad Unda Bagian Hilir Menggunakan HEC-HMS. Jurnal Teknik Pengairan: Journal of Water Resources Engineering 12, 36–46.

Perdana, D.A., Zakaria, A., Sumiharni, S., 2015. Studi Pemodelan Curah hujan sintetik dari beberapa stasiun di wilayah Pringsewu. Jurnal Rekayasa Sipil dan Desain 3, 45–56.

RAZIN, M.A., 2021. Prediksi Data Hujan Terukur terhadap Data Hujan Satelit Tropical Rainfall Measuring Mission (TRMM) di Jawa Bagian Barat (PhD Thesis). Universitas Jenderal Soedirman.

Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., Tompkins, A., 2003. The atmospheric general circulation model ECHAM 5. PART I: Model description. https://doi.org/10.17617/2.995269

Sachindra, D., Ahmed, K., Rashid, M.M., Shahid, S., Perera, B., 2018. Statistical downscaling of precipitation using machine learning techniques. Atmospheric research 212, 240–258.

Saidah, H., Budianto, M.B., Hanifah, L., 2017. Analisa indeks dan sebaran kekeringan menggunakan metode standardized precipitation index (SPI) dan geographical information system (GIS) Untuk Pulau Lombok. Jurnal Spektran 5, 173–179.

Saidah, H., Pracoyo, A., Khairudin, K., 2020. Perbandingan Beberapa Metode Perhitungan Debit Puncak Banjir Rancangan. GANEC SWARA 14, 526–536.

Sudinda, T.W., 2020. Penentuan Debit Andalan dengan Metoda FJ MOCK di Daerah Aliran Sungai Cisadane. Jurnal Air Indonesia 11.

Sutanto, N.T., 2020. Analisis Banjir Kelurahan Tanjung Duren Selatan.

Tahmasebi, P., Sahimi, M., 2013. Cross-correlation function for accurate reconstruction of heterogeneous media. Physical review letters 110, 078002.

Talumepa, M.Y., Tanudjaja, L., Sumarauw, J.S., 2017. Analisis Debit Banjir dan Tinggi Muka Air Sungai Sangkub Kabupaten Bolaang Mongondow Utara. Jurnal Sipil Statik 5.

Tselioudis, G., Douvis, C., Zerefos, C., 2012. Does dynamical downscaling introduce novel information in climate model simulations of precipitation change over a complex topography region? Int. J. Climatol. 32, 1572–1578. https://doi.org/10.1002/joc.2360

Utami, N.A., Sujiono, E.H., Palloan, P., 2021. Analisis Tingkat Kekeringan Meteorologis Di Wilayah Sulawesi Selatan Menggunakan Metode Indeks Presipitasi Terstandarisasi (SPI). Presented at the Prosiding Seminar Nasional Fisika PPs Universitas Negeri Makassar, pp. 114–117.

Wang, W., Lu, Y., 2018. Analysis of the mean absolute error (MAE) and the root mean square error (RMSE) in assessing rounding model. Presented at the IOP conference series: materials science and engineering, IOP Publishing, p. 012049.

World Meteorological Organization, 2010. Commission for Instruments and Methods of Observation, WMO-No. 1064. World Meteorological Organization (WMO), Switzerland.