Verification of Weather Predictions Using Voluntary Weather Observations Via WhatsApp and Google Forms During the Dry Season 2021

Giarno Giarno(1*), Munawar Munawar(2), Ervan Ferdiansyah(3), Fendy Arifianto(4), Asri Pratiwi(5), Silvia Yulianti(6)

(1) State College of Meteorology Climatology and Geophysics
(2) State College of Meteorology Climatology and Geophysics
(3) State College of Meteorology Climatology and Geophysics (STMKG)
(4) State College of Meteorology Climatology and Geophysics (STMKG)
(5) State College of Meteorology Climatology and Geophysics (STMKG)
(6) State College of Meteorology Climatology and Geophysics (STMKG)
(*) Corresponding Author

Abstract

The weather data that can be obtained through government institutions is very limited, whereas in order to increase the accuracy of weather predictions a homogeneous and dense distribution of data is needed. Therfore it is necessary to increase the data and the purpose of this research is to create a simple and effective way to encourage the number of weather observations in Indonesia through the STMKG Weather Care program. Forms that are made as easy as for respondents to understand, simple, and don't take the time. Developed using Google Form and distributed via the most popular social media today, namely WhatsApp. The test results showed that social media has the potential to be used to support voluntary weather data. The form made is sufficient so that the respondents make relatively few mistakes in terms of the main content of the form. Moreover, the mistakes that are often made by respondents include filling in ID, and typing sub-districts that require manual correction. Based on the results of voluntary observations spread in almost all provinces of Indonesia with the most incoming data coming from the provinces of Central Java and East Java. Based on the evaluation results of 4 months of testing, weather variations and their predictions can be identified with an accurate distribution, with an average accuracy of 0.79. Differences in methods used in verification may affect accuracy.

Full Text:

PDF

References

As-syakur, A.R. (2010) Pola spasial pengaruh kejadian la nina terhadap curah hujan di indonesia tahun 1998/1999; observasi menggunakan data TRMM multisatellite precipitation analysis (TMPA) 3B43. Prosiding Pertemuan Ilmiah Tahunan MAPIN XVII Bandung.

Awadallah, A.G. (2012) Selecting Optimum Locations of Rainfall Stations Using Kriging and Entropy. International Journal of Civil & Environmental Engineering, 12(1), 36-41.

Balsamo, G., Agusti-Panareda, A., Albergel, C., Arduini, G., Beljaars, A., Bidlot, J., Blyth, E., Bousserez, N., Boussetta, S., Brown, A., Buizza, R., Buontempo, C., Chevallier, F., Choulga, M., Cloke, H., Cronin, M.F., Dahoui, M., De Rosnay, P., Dirmeyer, P.A., Drusch, M., Dutra, E., Ek, M.B., Gentine, P., Hewitt, H., Keeley, S.P.E., Kerr, Y., Kumar, S., Lupu, C., Mahfouf, J.-F., McNorton, J., Mecklenburg, S., Mogensen, K., Muñoz-Sabater, J., Orth, R., Rabier, F., Reichle, R., Ruston, B., Pappenberger, F., Sandu, I., Seneviratne, S.I., Tietsche, S., Trigo, I.F., Uijlenhoet, R., Wedi, N., Woolway, R.I. and Zeng, X. (2018) Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. Remote Sens. 10(2038). https://doi.org/10.3390/rs10122038.

Barhoumi, C. (2015) The Effectiveness of WhatsApp Mobile LearningActivities Guided by Activity Theory on Students' Knowledge Management. Contemporary Educational Technology, 6(3), 221-238.

Bayong, T.H.K. (2004) Klimatologi. Bandung, Penerbit ITB.

Centurioni, L.R., Turton, J., Lumpkin, R., Braasch, L., Brassington, G., Chao, Y., Charpentier, E., Chen, Z., Corlett, G., Dohan, K., Donlon, C., Gallage, C., Hormann, V., Ignatov, A., Ingleby, B., Jensen, R., Kelly-Gerreyn, B.A., Koszalka, I.M., Lin, X., Lindstrom, E., Maximenko, N., Merchant, C.J., Minnett, P., O’Carroll, A., Paluszkiewicz, T., Poli, P., Poulain, P.M., Reverdin, G., Sun, X., Swail, V., Thurston, S., Wu, L., Yu, L., Wang, B. and Zhang, D. (2019) Global in situ Observations of Essential Climate and Ocean Variables at the Air–Sea Interface. Front. Mar. Sci. 6(419) doi: 10.3389/fmars.2019.00419.

Cocorahs (2021) CoCoRaHS's 20th Anniversary. Available Online at: https://cocorahs.org/Content.aspx?page=20years [October 12, 2021].

Didiharyono and Giarno (2021) Application of the Simple Verification Method to Estimate the Weather at Makassar Maritime Station, Indonesia. Walailak Journal of Science and Technology (WJST), 18(18), https://doi.org/10.48048/wjst.2021.9542.

D'Arrigo, R. and Wilson, R. (2008) El Ni˜no and Indian Ocean influences on Indonesian drought: implications for forecasting rainfall and crop productivity. International Journal of Climatology. 28, 611-616.

Fattah, S. F. E. A. (2015) The Effectiveness of Using WhatsApp Messenger as One of Mobile Learning Techniques to Develop Students' Writing Skills. Journal of Education and Practice. 6(32), 115-127.

Giarno, Zadrach L. D., and Mustofa, M. A. (2012) Kajian awal musim hujan and awal musim kemarau di Indonesia. Jurnal Meteorologi and Geofisika. 1, 1–8.

Giarno, Hadi, M. P., Suprayogi, S., and Murti, S. H. (2018), Distribution of accuracy of TRMM daily rainfall in Makassar Strait. Forum Geografi, 32(1), 38-52.

Giarno, Hadi, M. P., Suprayogi, S., and Murti, S. H. (2019) Daily quantitative precipitation estimates use weather radar reflectivity in South Sulawesi. IOP Conf. Ser. Earth Environ. Sci. 256, 012042. doi:10.1088/1755-1315/256/1/012042.

Giarno, Hadi, M. P., Suprayogi, S., and Murti, S. H. (2020) Impact of rainfall intensity, monsoon and MJO to rainfall merging in the Indonesian maritime continent. J. Earth. Syst. Sci/ 129(164) https://doi.org/10.1007/s12040-020-01427-8.

Hidayat, R., and Kizu, S. (2010) Influence of the Madden–Julian Oscillation on Indonesian rainfall variability in austral summer. International Journal of Climatology. 30, 1816-1825.

Jisha, K. and Jebakumar (2014) Whatsapp: A trend setter in mobile communication among Chennai youth. IOSR Journal of Humanities and Social Science (IOSR-JHSS). 19(9), 1-6.

Kiki and Alam, F. (2019) Verifikasi parameter presipitasi akumulasi 24 jam pada model cuaca numerik tahun 2017. Buletin BBMKG Wilayah II. 9(2), 1-5.

Kompas (2019) Data Bencana BNPB pada 2019, 1.538 Kejadian dan 325 Korban Meninggal. Kompas, Available Online at: https://nasional.kompas.com/read/2019/04/30/19322341/data-bencana-bnpb-pada-2019-1538-kejadian-dan-325-korban-meninggal [October 12, 2021].

Lee, H. S. (2015) General Rainfall Patterns in Indonesia and the Potential Impacts of Lokal Seas on Rainfall Intensity. Water. 7, 1750-1768.

Martono, M. and Wardoyo, T. (2017) Impacts of El Niño 2015 and the Indian Ocean Dipole 2016 on Rainfall in the Pameungpeuk and Cilacap Regions. Forum Geografi. 31(2), 184–195.

Mbukusa, N. R. (2018) Perceptions of students on the use of WhatsApp in Teaching Methods of English as Second Language at the University of Namibia. Journal of Curriculum and Teaching. 7(2), 112-119.

Murdiyanto and Gutomo, T. (2015) Bencana Alam Banjir dan Tanah Longsor dan Upaya Masyarakat dalam Penanggulangan. Jurnal PKS, 14(4), 437-452.

Neale, R. and Sligo, J. (2003) The Maritime Continent and Its Role in the Global Climate: A GCM Study, Journal of Climate. 16, 834-848.

NOAA (2021) United States Voluntary Observing Ship Program. Available Online at: https://www.vos.noaa.gov/ [October 12, 2021].

Nur’utami, M. N. and Hidayat, R. (2016) Influences of IOD and ENSO to Indonesian Rainfall Variability: Role of Atmosphere-ocean Interaction in the Indo-pacific Sector. In: Procedia Environmental Sciences. 196–203.

Orbelo (2021) Most Popular Social Media Platforms in 2021, Orbelo, Available Online at: https://id.oberlo.com/statistics/most-popular-social-media-platforms. [October 12, 2021].

Spaccio, J., DeGaetano, A. and Doesken, N. (2021) COVID-19 stay-at-home orders result in a decrease in the number of missing daily precipitation observations. Bulletin of the American Meteorological Society. 102, 207–209.

The Maritime Executive (2020) COVID-19 Impacting Weather Forecasts. Available Online at: https://www.maritime-executive.com/article/covid-19-impacting-weather-forecasts [October 12, 2021].

WMO (1994) Guide to hydrological practice : Data acquisition and processing analysis and forecasting and other applications. Geneva, WMO-No.168.

WMO (2015) Guidelines on Multi-hazard Impact-based Forecast and Warning Services, Geneva, World Meteorological Organization.

DOI: 10.23917/forgeo.v36i1.16333

Article Metrics

Abstract view(s): 630 time(s)
PDF: 295 time(s)

Refbacks

  • There are currently no refbacks.


Bookmark and Share