Fithriya Yulisiasih Rohmawati
Department Of Geophysics And Meteorology, Faculty Of Mathematics And Natural Sciences, IPB University, Dramaga Campus, Bogor, Indonesia 16680

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Journal : Agromet

Prediksi Awal Musim Hujan di Jawa Menggunakan Data Luaran Regional Climate Model Version 3.1 (RegCM3) Fithriya Yulisiasih Rohmawati; Rizaldi Boer; Akhmad Faqih
Agromet Vol. 28 No. 1 (2014)
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.875 KB) | DOI: 10.29244/j.agromet.28.1.17-22

Abstract

Monsoon onset information plays an important role in setting up planting strategy for achieving optimum yield. This study aimed to develop forecasting model for the monsoon onset in main rice growing area of Java used Regional Climate Model Version 3.1 (RegCM3). The forecasting models of the monsoon onset and September-Oktober-November (SON) rainfall data were developed using regression model that have the highest coefficient determination and the models were tested using likelihood ratio test. It was found that the forecasting models of the monsoon onset and September-Oktober-November rainfall data were polynomial orde 2 or cuadratic that have coefficient determination 69%, 74%, 80% and 86%. Likelihood ratio test found that RegCM3 rainfall data was not significantly different with observation rainfall data (α = 0.05). Onset in Java between 25th until 34th of 10-days period (early September until early December).
The Effect of Car Free Day (CFD) on Pollutant Emissions at Alternative Roads (Case Study: RE Martadinata Street, Bogor City) Rachmawati Aida; Fithriya Yulisiasih Rohmawati; Ana Turyanti
Agromet Vol. 33 No. 1 (2019): JUNE 2019
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (707.115 KB) | DOI: 10.29244/j.agromet.33.1.8-19

Abstract

Car Free Day (CFD) is a social campaign aimed to reduce the dependence of people on vehicle uses, which occurs once per week in Bogor. The idea intends to decrease the vehicle emissions. However, CFD is often to cause a new problem like the congestions, which are found on the nearby alternative roads, as happened in RE Martadinata Street, Bogor City. This study aims to compare the emission load and the concentrations of pollutants in ambient air during CFD (06.00-09.00 am) and non-CFD days in alternative road. We measured the following pollutants: CO, HC, NOx, PM10 and SO2. This research first applied Fixed-Box Model to estimate concentration of pollutants, then we used the Finite Length Line Source (FLLS) to estimate dispersion of pollutants. The results showed that there was no substantial difference in pollutant emissions between CFD and non-CFD days. But if we separate between weekdays and weekend, our analysis revealed that emissions during the weekend are bigger than that of weekdays. This was consistent with an increase of number of vehicles during the weekends by 17.2%. Based on our analysis, motorcycle contributes to an increased of CO, HC, PM10 pollutants, whereas SO2 and NOx pollutants were generated by cars. Our findings suggest that a short time of CFD does not contribute a lot to reduce the emissions.
Season Onset Prediction Based on Statistical Model for Malang Regency, East Java Fithriya Y Rohmawati; Urfana Istiqomah; Rahmat Hidayat
Agromet Vol. 36 No. 1 (2022): JUNE 2022
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.36.1.21-30

Abstract

Prediction of season onset is important for many sectors, particularly on agricultural practices, as its usage for reducing climate risk and planning activities. Current knowledge on season onset prediction mainly focused on large area, which remains research challenge for local level. This research developed model prediction of season onset for Malang Regency, East Java based on global climate data. The research specifically aimed to: (i) determine the onset date of rainy and dry season, (ii) generate equation for onset date prediction using principal component regression (PCR) approach, and (iii) evaluate the model performance. We depend on statistical model based on a combine of domain time and principal component analysis (PCA) for atmospheric variables, namely sea level pressure, outgoing longwave radiation, and zonal wind. We used the Tropical Rainfall Measuring Mission (TRMM) data for model evaluation, especially for determination of onset date. Based on cumulative anomalies rainfall, the onset date for dry season occurred in the early May, whereas for rainy season it was in early November. The results showed that regression models of the principal components had a good skill to predict onset date for both seasons. It has been confirmed by a low error and a high correlation. Visually, the dynamic of onset dates from model was mostly identical to the observation. The predictive model for rainy season had higher performance compared to the model for dry season. This finding was confirmed by insignificant difference resulted from the independent t-test between model and observed onset dates. The best model for dry season was conducted by domain time of February, whereas for rainy season was domain time of August. This research can be used to complement previous studies regarding season onset prediction in Indonesia.