Jurnal Sains Dirgantara
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PROYEKSI DEBIT ALIRAN PERMUKAAN DAS CITARUM BERBASIS LUARAN MODEL ATMOSFER
Full text link Rainfall variability has an impact on the amount of water balance in each watershed (catchment) scale of space and time, so that rainfall variability has an important role to discharge runoff. As the main input is not only rainfall, but the level of land cover and soil physical properties with various concepts was an important input in maintaining the equilibrium amount of water in a watershed, resulting in an equilibrium water balance, and surface flow is considered as a likely output for the sector needs. The data used is the GCM model outputs Geophysical Fluid Dynamics Laboratory (GFDL) in units of rainfall (mm) are reduced from global to local scale. Besides the rainfall data (mm) taken from the Tropical Rainfall Measuring Mission (TRMM, 3B43) satellite with a resolution of 0.25 degrees (equivalent to 27.5 km2), temperature (0C) from the Moderate Resolution Imaging Spectroradiometer (MODIS) level with a resolution of 0.045 degrees (equivalent to 5 km2). Similarly, observational data of rainfall, surface temperature and flow rate (mm3/sec) from 2001 to 2009 are used to validate satellite data and atmospheric models. The correlation between rainfall observations, satellite and atmospheric model outputs are 0.76 and 0.65, respectively. By using the method of Hydrological Simulation Model (HYSIM) can be determined projections of future surface flow atmospheric model based on the DAS Citarum, West Java. Based on the flow rates calculation and observations from 2001 to 2009, have suitability with correlation coefficient of 0.8. The results of calibration flow rate projections from 2011 to 2019 is following the pattern of previous years with a correlation of 0.6. Flow rate is affected by rainfall in the region. Based on the rainfall projections, it is known that rainfall increases with increasing rainfall, the availability of water even more, so that the flow at the surface of the Citarum river basin is expected to increase. Keywords:DAS Citarum, HYSIM, Climate, Satellite, and Atmospheric mode
PENENTUAN ONSET MONSUN DI WILAYAH INDO-AUSTRALIA BERDASARKAN LOMPATAN ITCZ
Full text linkInter-Tropical Convergence Zone (ITCZ) is one of the factors affecting weather and climate in the Indonesia Maritime-Continent Region together with El-Niño Southern Oscillation (ENSO), Indian Ocean Dipole Mode (IODM), Madden Julian Oscillation (MJO), Tropical Cyclone (TC), and Monsoon. ITCZ influence weather and climate in the Indonesia region. Therefore, monitoring and understanding ITCZ behaviour become important as an alternative method to predict variability, anomaly, and extreme atmospheric conditions in Indonesia region. Research has been conducted to study the behaviour of ITCZ in the Indonesia maritime-continent region using Multi-Functional Transport Satellite (MTSAT) data from year 2006 to 2009. Identification of ITCZ and its movement was carried out based on minimum cloud top temperature observed by MTSAT satellite. Meridional movement of ITCZ were then compared to the Indo-Australia Monsoon Indices and rainfall from Tropical Rainfall Measuring Mission (TRMM) satellite. The results showed that ITCZ positions tend to exist at certain locations and experienced jumps to mid-latitude during seasonal change to dry and wet seasons. The results can be used to predict monsoon onset in the Indo-Australia region based on ITCZ jumps, and also to verify rainfall prediction models which in turn can be applied to hydrological models, environtmental models, and rainfall-related disaster early warning systems. Keywords: ITCZ, Monsoon, Onset, Satellite, Indonesi
HOLT-WINTERS DALAM PREDIKSI ANOMALI OLR
Full text linkOne of the pivotal study when analyzing the impact of the Madden-Julian Oscillation (MJO) phenomenon on rainfall anomalies in the Western part of Indonesia region is knowing the characteristics and the prediction of Outgoing Longwave Radiation (OLR) as the main parameter. This paper, focused to develop a predictive model OLR using the Box-Jenkins (ARIMA) method, which compared by the Holt-Winters method. This analysis focused on the average five days (pentad) OLR data in the Western part of Indonesia region, precisely at the position of 120oE for period of January 2007 to December 2009. Based on the comparison of the MSE (Mean Squares of Errors), and the MAPE (Mean Absolute Percentage Error) obtained from the Box-Jenkins (ARIMA) and Holt-Winters methods can be concluded that appropriate to predict the value of pentad OLR data on the position 120oE is the Box-Jenkins (ARIMA) method, because it has smaller value of MSE and MAPE comparing with the Holt-Winters method. Box-Jenkins model is the model ARIMA (1.0.1)(0.1.1)9 according to the results of significance analysis, autocorrelation in the residuals (white noise), also normality of residuals, where the process is repeated until model is really suitable and best meet the assumptions of model selection. The models can be assessed by the signal tracking value at each forecasting model. This assessment showed two of models in accepted boundary value, i.e ±5. This shows forecasting model can still be used to predict the 4 periods of the OLR pentad anomaly. Keywords: Box-Jenkins (ARIMA), Holt-Winters, OLR, and Prediction Model ABSTRAK Salah satu kajian penting ketika menganalisis dampak dari fenomena Madden
PRAKIRAAN CUACA DENGAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGENEURAL NETWORK, DAN ADAPTIVE SPLINES THRESHOLD AUTOREGRESSION DI STASIUN JUANDA SURABAYA
Full text linkThe need of weather forecasting is primary to support activities in various sectors, so the efforts of development for forecast methods to improve the precision and the accuracy of the weather information are very important. Various weather forecasting models by engineering or stochastic model approach have been developed, although each method has both weaknesses and strengths, the efforts for developing techniques or methods to get the best model have to be done. What is elaborated in this article represent the result of testing in three statistical methods to obtain the best weather forecasting models. Three methods as mentioned before are: the Autoregressive Integrated Moving Average (ARIMA), Neural Network (NN), and Adaptive Splines Threshold Autoregression (ASTAR) to forecast the temperature, humidity, and daily rainfall. The performance of these three methods are evaluated by correlation values and Root Mean Square Error (RMSE). The good performance characterized by a high correlation between actual and forecast values, and also has a small RMSE. The results of this research indicate that ASTAR method produces better signed by a higher correlation, lower RMSE values and the constant forecasting from the first day until the thirtieth. The correlation in ASTAR method for Tmax and RHmin respectively are 0,70 and 0,75, for ARIMA method are 0,31 and 0,47, for NN method are 0,02 and -0,06. The three methods have poor performance for Tmin, RHmax and RRR. Keywords: Weather forecast, ARIMA, ASTAR, Neural Networ
ANALISIS PERILAKU ANGIN DI LAPISAN 850 hPa HASIL OBSERVASI DATA WPR DIKAITKAN DENGAN PERILAKU DATA INDEKS MONSUN GLOBAL DI INDONESIA
Full text linkThis study analyzed the behavior of winds in the lower layers of the troposphere, or rather at "approximately" 850 hPa layer, which is equivalent to an altitude of "about" 1.5 km above the sea level (asl) and observed the data at Wind Profiling Radar (WPR) in Pontianak, Biak, Manado, Serpong and Kototabang, particularly in the wet months (BB) and dry months (BK) for a few months. The results show that the WPR data used to identify the Monsoon on the Indonesian Maritime Continent region (BMI) is quite refresentative. The results further show that the cities which are located relatively close to the equatorial line, such as Pontianak and Biak are relatively strongly influenced by wind zonal (East-West). While the city which is relatively far from the equatorial line (like Manado), is relatively strongly affected by the meridional wind (North-South). There is further analysis of why this is happening. However, this is allegedly due to the influence of Coriolis force (Coriolis Force), particularly at the lower layers of the troposphere in the region that is located relatively far from the equatorial than in the precise area at the equatorial considering that the Coriolis force itself is close to zero (very small) for the equatorial region. Another interesting point is that the zonal winds are stronger influence on the data AUSMI (Australian Monsoon Index), while the meridional winds are the stronger influence on the data WNPMI (Western North Pacific Monsoon Index) with correlation values respectively around 0.76 and 0.45. Keywords: Monsoon Signal, WPR, and Global Monsoon Inde
KARAKTERISTIK CO2 PERMUKAAN DI BANDUNG TAHUN 2008-2009 (PENGUKURAN TETAP DI WILAYAH PASTEUR)
Full text linkA fixed instrument for CO2 measurement (LPN SATKLIM-1B) has been built and installed at LAPAN Bandung, started by using a direct recorder system on the computer then it is completed with data connection to the CO2 monitoring web server. The CO2 sensor used by NDIR technology has been corrected by the temperature and pressure compensation. The sensor was installed on 15 m above ground level, acquired and also recorded its data by monitoring the software developed by using the Microsoft Visual Basic 6.0. From the recording result of measurement data in Bandung from 2008 until 2009, with one minute interval data, it was obtained that the data characteristic compared to the measurement data from Global Atmospheric Watch (GAW) station in Kototabang (using spectroscopy technology) and Mauna Loa, all of them have the same pattern. From one year analysis (2008 – 2009) it was also obtained that by the increase of motor vehicle in Bndung for about 226,500 vehicle a year, 76% land building, and just 8.7% green open spaces, the CO2 has increased 1.5 ppm and the temperature from AWS data 2008-2009 (a year) data has increased 4.3ºC. In another side, the CO2 multiplication effect has occurred at 06.30-08.00 AM according to surface and vertical profile measuremens, due to stable atmosphere and calm wind. Key words: Surface fixed system, CO2 concentration, Convectio
ANALISIS STRUKTUR VERTIKAL MJO TERKAIT DENGAN AKTIVITAS SUPER CLOUD CLUSTERS (SCCs) DI KAWASAN BARAT INDONESIA
Full text linkOne important aspect when its Coupling Processes Equatorial Atmosphere (CPEA) Campaign 2004 in Kototabang which lasted for approximately one month of observation (April 10 to May 10, 2004) was an analysis of the vertical structure of the phenomenon of the Madden-Julian Oscillation (MJO) related to the activity of the Super Cloud Clusters (SCCs) as one of the main parameters in assessing the behavior of rainfall occurred in the western region of Indonesia. The data used are data of Equatorial Atmosphere Radar (EAR), Boundary Layer Radar (BLR), Mini Automatic Weather Station (MAWS), and Optical Rain Gauge (ORG) at Kototabang, LAPAN Ground Station. While the supporting data used are long-wave radiation anomaly data (Outgoing Longwave Radiation, OLR) and surface rainfall data. The analysis using spectral techniques, particularly the Fast Fourier Transform (FFT) on data anomalies daily average five (pentad) OLR oscillation 2001-2005 period shows that the dominant than the data is approximately 30 daily. These oscillations typically occurred in the lower troposphere layer with the direction of propagation toward the east. Besides that, the existence of convergence and divergence processes in the layer 3 and 10 km above mean sea level (msl) is also found, particularly on the date April 23, 2004 of EAR data analysis. Finally, we try to link these events by analyzing the relationship between OLR with the rainfall in Kototabang and the surrounding region, particularly ORG measurement results with the correlation coefficient of about 0.71. Keywords : CPEA Campaign, MJO, OLR, EAR, and OR
RANCANG BANGUN ALAT PENGUKUR DAN SISTEM JARINGAN DATA CO2 DI INDONESIA BERBASIS WEB
Full text linkA web-based CO2 measurement device and a data network system in Indonesia which consist of the CO2 measurement device, the local data processor system, and the central data processor system has been built. The CO2 measurement device consist of the GMM220 CO2 sensor module from Vaisala and the data logger system. The data logger output consists of location, time, date, CO2 concentration, and input voltage, which packed all up in one data form with RGPGHG as the data header. The data logger system store the data into SD Card memory and ends it to the local data processor system. The CO2 Monitor Software in the local data processor system processes the data and display the graphical data which shows the maximum, minimum and average values of the data, and also sends the data to the central data processor system. The central data processor system displays data from several local data processor systems in the form of real time web-based graphical data and text, so the internet users can access and download its data. The development result device has been applicated in Kototabang, and the CO2 measurement device has been connected as well to the central data processor system in Bandung via the internet network to perform the web-based CO2 data network system in Indonesia. According to the data stored by the central data processor system for the periode of 1 - 26 March 2010, it shows that the CO2 concentration in Kototabang have an average of 403,5 ppm, with the maximum of 476,9 ppm and the minimum of 364,7 ppm. While the CO2 concentration in Bandung have an average of 397,2 ppm, with the maximum of 502,5 ppm and the minimum of 325,3 ppm. Key words: Data logger, CO2 sensor, Web-based interfac