Climatological Stations Research Articles

PERAMALAN CURAH HUJAN EKSTREM DI KOTA MEDAN DENGAN MODEL SPATIAL EXTREME VALUE DENGAN PENDEKATAN MAX STABLE PROCESS

This research includes extreme spatial values. Application of the method with the Max-Stable (MSP) process. The approach will be used for the analysis of extreme rainfall in Medan City and Deli Serdang Regency. The extreme value sample selected by the Block Maxima Method, will be estimated to the spatial extreme value form by including location factors. The Max Stable Process (MSP) is an extension of the Multivariate distribution of extreme values into an infinite dimension of the theoretical extreme values. After selecting the best model, extreme rainfall data in Medan City and Deli Serdang Regency were obtained, then calculating predictions of extreme rainfall with certain time periods. Predictions are calculated using the rate of return, predictions of extreme rainfall using the return period for the next two years, in the city of Medan Belawan Maritime Station will reach 122.98 mm, BMKG Region 1 Station will reach a value of 139.13 mm. And the rain monitor in Deli Serdang Regency, the Deli Serdang Geophysics Station is predicted to be a maximum of 218.09 mm, the Kualanamu Meteorological Station is predicted to reach 91.87 mm, the North Sumatra Climatology Station will reach a maximum value of 174.18 mm. Predicted maximum Precipitation extremes can also be calculated for t (time) in future periods

Flood Sedimentology for Future Floods Mitigation in North Luwu, Sulawesi, Indonesia

A sedimentological study after the flash floods that hit North Luwu on July 13, 2020, has been carried out on three affected rivers, namely the Masamba River, the Radda River, and the Binuang River. The study aims to determine the sedimentological impact of the 2020 flash flood disaster, including sedimentation rate, annual bedload sediment volume, and total sediments, which will be used as a reference for future mitigation consideration. The study is based on fieldwork for data collection and laboratory analysis. The results of field measurements and laboratory analysis are then processed by calculating the sedimentation rate at the annual discharge, the bedload sediment volume, and the total estimated sediment accumulated by the flash flood. Sedimentation rate analysis was performed using the Ackers-White formula, and flood delineation was processed using HEC-RAS software. The climatological data from the climatology station at Andi Djemma Airport were used to calculate the river discharge. It is estimated that the volume of bedload sediment in the Binuang River is 16,194,168 m3/year, that of the Masamba River is 7,852,061 m3/year, and that of the Radda River is 4,003,011 m3/year. The volume of sediment brought by flash flood sedimentation in the Radda River is 9,141,608.39 m3, while that in the Masamba River is 55,131,761.29 m3, and that in the Binuang River is 136,838,603.61 m3. The total estimated sedimentation generated by the flash flood on the three rivers on July 13, 2020, is 222,476,966 m3. Based on the study, zonation for vulnerability levels is designed for a future mitigation scheme. The zonation can be classified into three zones: 1) the highly affected zone; 2) the moderately affected zone; and 3) the least affected zone, with special purposes in each zone. It is strongly recommended that future disaster settlement and infrastructure reconstruction policies be based on this zone to reduce disaster risk. Doi: 10.28991/CEJ-2023-09-04-011 Full Text: PDF

ANALISIS NERACA AIR LAHAN UNTUK PENGEMBANGAN KEDELE DI KECAMATAN RANOMEETO BARAT KABUPATEN KONAWE SELATAN

In order to develop soybean plants, the availability of water in the form of soil moisture is one of the factors that give a very important message. Water supply is usually obtained from rainwater, so the arrangement of cropping pattern often follows the pattern of rainfall distribution that occurs. Preparation of water balance is intended to increase the productivity of dry land through the determination of pattern and planting schedule in accordance with groundwater availability. The water balance analysis using climate data series includes monthly rainfall and air temperature. Climate data obtained from Climatology Station Wolter Monginsidi Kendari Southeast Sulawesi. The opportunity for rainfall is exceeded and the water balance is analyzed using statistical methods. The results show that the soil moisture conditions are available for the crops for 8 months, ie from December 10 daily 2 to July 10 daily 2. while the water deficit in August to November (during dry season). Thus the cultivation can be done for 8 months ie when a surplus of water.

Empirical model for the estimation of global solar radiation in the Aceh Besar Regency, Aceh

Solar energy plays an important role in the temperature distribution on the Earth's surface and essential energy that sustains life for human. In the calculation of solar energy, the limitation of solar radiation data is a major obstacle. Solar radiation data is very limited at some observation stations due to the costly procurement of measuring instruments and complicated techniques. Estimation of global solar radiation using empirical models is one way to overcome the limitations of global solar radiation data at various locations. This study built the Angstrom-Prescott model to estimate global solar radiation based on the sunshine duration’s parameter in Aceh Besar Regency. Two years (2019-2020) global solar radiation and sunshine duration data from Aceh Climatological Station were used to estimate global solar radiation in 2021. Data for 2021 was using to evaluated the equation H/H0=0.28+0.22 (n/N), the results showed good model accuracy with an RMSE value of 0.052 and a MAPE of 11% (good forecasting). The model equation has been reliable to calculate solar radiation in four locations in Aceh Besar Regency.

Verification of the Weather Research and Forecasting Model (WRF) for the Domain of Silesian Voivodeship and Upper Silesia Metropolitan Region

Abstract The paper presents the analysis of the statistical errors of the meteorological parameters predicted by the WRF (Weather Research and Forecasting) model. The model is used for forecasting air pollution in the Silesian Voivodeship with an accuracy of about 70-80%. Thus, the main idea of the research was assessing to what extent the error in the forecast of meteorological parameters affects the error of the air quality forecast, which can be evaluated using the system InfoSMOG – MED for the inhabitants of the Silesian Voivodeship at www.slaskiesmogstop. It was also investigated how the reduction of the mesh size of the forecast of meteorological parameters affects the error of the forecast of these parameters, which was necessary for the next project SMART. The research was carried out for 3 computational domains: Poland, Silesian Voivodeship and Upper Silesia Metropolitan Region, each with a different grid resolution. The predicted temperature and wind speed data were compared with the measured data from the Polish synoptic stations and the stations of the METAR airports meteorological shield located in the respective domains. In addition, the error of the predicted parameters was investigated in the grid where the climatological station is located in the Śląskie Planetarium in Chorzów.

A study on the possibility of using cloud accumulation variable for calculating the total quantity of solar radiation falling on the Yemeni terrain

In the limitation of gathering actual data of the total amount of solar radiation in the presence of clouds from the climatological stations in Yemen, other indirect methods were used to calculate them. A systematic method suggested by two researchers in the literature, viz., Liberlyand T. G., and Sarukinoi, L. I. were applied to give the possibility of calculating the solar radiation by using the actual cloud quantity “ns” available at the stations. This requires only the monthly data of the percentage of the cloud quantity that can be taken from the network stations (coordinates) without referring to the actual values of the cloud quantity of the specified climatological stations "n1".
 The results show that the percentage degree of deviation from the total quantity of solar radiation “QRns” when the clouds accumulate "ns" that were calculated using the method introduced by Liberlyand and Sarukinoi from the actual quantity of solar radiation “Qf” taken directly from the climatological stations for Aden, Riyan, Perim Island, Kamaran Island and Sana'a was , , , and respectively. 
 These percentages are within the allowable ranges for the theoretical calculations in the thermal energy. Consequently, the results give evidence of the possibility for using the total quantity of solar radiation calculated from the cloud accumulation variable “ns" with the use of the theoretical total solar radiation “QRn1” in any station in Yemen instead of “Qf” if its value cannot be obtained or due to the limitation of getting the value of the actual cloud accumulation “n1” in the climatological stations.

Mapping the representativeness of precipitation measurements in Mainland China

Meteorological observations provide essential data for weather forecasting and climate change studies. Whether the measured data can accurately support such applications closely relates to the representativeness of the data collected, which depends on both the scale of observation and the density of the measurement network. Precipitation presents in the form of events and is discontinuous both in time and space. Gauge observations of precipitation could provide fundamental data but have difficulty quantitatively assessing precipitation system scale. Therefore, assessments on the representativeness of precipitation at synoptic and climatological scales remain needed. Here, we show the first high-resolution map of the representativeness of precipitation over Mainland China based on the latest satellite data. Our results show that the daily precipitation spatial consistency is the highest in eastern China and lowest on the Tibetan Plateau. However, the pattern of the monthly spatial consistency is different and is the highest over Northeast China Plain, the Loess Plateau, and the Middle–Lower Yangtze Plain. Compared to the density of rain gauges, we find that the current national station network with ∼2400 stations still has difficulty supporting synoptic studies in western China. However, for climate change studies based on monthly data, the density of the national reference climatological station network is sufficient, except in the western Tibetan Plateau and deserts with no available stations. For climatological studies, the quality of precipitation gauge observations is more important than its spatial density. Our results could provide great practical significance for considering the layout of rain gauges.

Gradual changes in temperature, humidity, rainfall, and solar irradiation as indicators of city climate change and increasing hydrometeorological disaster: a case study in Yogyakarta, Indonesia

Climate change began in the 1980s when global warming became a global concern, and it has continued in several cities in Indonesia. This paper measures climate change in Yogyakarta, Indonesia based on gradual changes in the air temperature, air humidity, rainfall depth, and duration of the sun's irradiation. The data were obtained for a period of 43 years (1976-2018) from the meteorological recording data at the climatology station in Yogyakarta. Data processing is done using the average statistical method, as outlined in the relationship graph between the years and the parameters studied. The results show that climate change in Yogyakarta has been clearly occurring. It is indicated by the increase of the average air temperature, the decrease of the average air humidity, the rising rainfall in the rainy season, and the changing of the sun's irradiation duration in the rainy season and in the dry season.

Characteristics and tendencies of the Gumanti Valley rainfall pattern towards erosivity as a mitigation effort in facing the threat of climate hazards

Rainfall is one of the most important climatic parameters in the agricultural sector. Each raindrop contains kinetic energy that can destroy soil particles and carry them away to lower places. Nutrients located in the top layer of soil are susceptible to erosion, which decreases soil productivity. Rainfall patterns are formed due to global, regional, and local factors that influence them. Changes in rainfall patterns will affect erosivity. The rainfall data used in this study came from the cooperation rain post of the West Sumatra Climatology Station located in Lembah Gumanti. Linear regression was used to assess the rainfall trend and Bols erosivity to calculate the effect of rainfall on erosion. The trend of rainfall in the Lembah Gumanti from 2014–2022 showed a value of +0.195, and the largest erosivity value occurred in 2020 as a result of the La Nina climate phenomenon. This research shows that an increase in rainfall will be followed by an increase in erosivity. High erosivity is feared to threaten the availability of soil nutrients, so mitigation efforts need to be made in anticipation of the threat of climate hazards for agricultural areas located in the highlands, such as the Lembah Gumanti region.

Frequency analysis of absolute maximum air temperatures in Serbia

This paper describes the frequency analysis of absolute maximum air temperatures, using annual maximum series (AMS) in the period 1961-2010 from 40 climatological stations in Serbia with maximum likelihood estimation of distribution parameters. For the goodness of fit testing of General Extreme Value (GEV), Normal, Log-Normal, Pearson 3 (three parameters), and Log-Pearson 3 distribution, three different tests were used (Kolmogorov-Smirnov, Anderson-Darling, chi-square). Based on the results of these tests (best average rank of certain distribution), the appropriate distribution is selected. GEV distribution proved to be the most appropriate one in most cases. The probability of exceedance of absolute maximum air temperatures on 1%, 0.5%, 0.2%, and 0.1% levels are calculated. A spatial analysis of the observed and modeled values of absolute maximum air temperatures in Serbia is given. The absolute maximum air temperature of 44.9?C was recorded at Smederevska Palanka station, and the lowest value of maximum air temperature 35.8?C was recorded at Zlatibor station, one of the stations with the highest altitude. The modeled absolute maximum air temperatures are the highest at Zajecar station with 44.5?C, 45.6?C, 47.0?C, and 48.0?C and the lowest values are calculated for Sjenica station with 35.5?C, 35.8?C, 36.1?C, and 36.2?C for the return periods of 100, 200, 500, and 1000 years, respectively. Our findings indicate the possible occurrence of much higher absolute maximum air temperatures in the future than the ones recorded on almost all of the analyzed stations.

Rainless Day Management using Geographic Information System and Wireless Sensor Networks on Climatology Station Banjarbaru

Information obtained at the Banjarbaru Climatology Station includes seasonal forecasts, rainfall analysis, rainfall properties analysis, rainy day analysis, and monitoring of rainless days in the South Kalimantan region. Monitoring of Rainless Day is a form of data on rainless days that occur in South Kalimantan in sequence. The data is sent by observers to the Banjarbaru Climatology Station office using SMS, WhatsApp, and even by calling the staff of the Banjarbaru Climatology Station so that employees must check every media both SMS, WhatsApp, and telephone to find out the data sent by observers. Related to these problems, a web-based rainless day monitoring application was made. By using the Research and Development (R&D) method to facilitate the management of rainless day data, a geographic information system management system using Google Maps API and MySQL database is built which is integrated with Internet of Things (IoT) technology based on Wireless Sensor Networks (WSN) for data collection in real-time. The system built will provide notifications in the management of areas affected by rainless days in order to deal with drought.

The Effect of El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on Rainfall and Its Correlation with Consecutive Dry Days (CDD) of South Sumatra Province from 1981-2020

El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)` are events where the phenomenon of rising and falling sea surface temperatures becomes unnatural. Stronger events where the sea surface temperature anomaly becomes large, then this disrupts local fish and bird populations. The ENSO and IOD phenomena also affect rainfall in several parts of Indonesia. This study analyzed the effect of ENSO and IOD phenomena on rainfall in South Sumatra Province from 1981 to 2020 and the correlation between Consecutive Dry Days (CDD) and Rainfall in South Sumatra Province for the last 40 years. ENSO data and IOD data were analyzed against rainfall data analyzed using a simple linear regression method and associated with CDD in South Sumatra Province with the correlation method. In addition, a correlation analysis was also carried out between the Niño 3.4 index and the Dipole Mode Index (DMI) with rainfall at two stations, namely the Palembang Climatology Station and the Sultan Mahmud Badaruddin II Meteorological Station to determine how much influence the ENSO and IOD phenomena had on rainfall in the Sumatra Province. South. The results of the analysis show that the effect of ENSO and IOD on rainfall at each station is generally not significant. The state of rainfall in the Province of South Sumatra for the last 40 years is almost not influenced by El Nio and La Nia. This is presumably due to the location of the South Sumatra Region which is in the Munsonal area. Monsoon areas are characterized by a unimodial type of rainfall (one peak of the rainy season) where in June, July and August the dry season occurs, while December, January and February are the wet months. The remaining six months is a transitional or transitional period (three months of transition from dry season to rainy season and three months of transition from rainy season to dry season).

Peramalan Curah Hujan dengan Pengelompokan Bulan Menggunakan Metode Double Exponential Smoothing dari Brown

It is important to know the future rainfall, the way is to predict rainfall. By knowing future rainfall, development strategies such as irrigation, dams, urban drainage, harbour docks, agriculture, and even disaster mitigation strategies will be right on target. The purpose of this study is to predict the rainfall for Boyolali Regency and Surakarta City, Central Java in 2020-2021 with Brown's double exponential smoothing method. The type of data used is secondary data, which is obtained from the Meteorology, Climatology and Geophysics Agency of Semarang Climatology Station. The smoothing value, alpha, used in each month was varies, because the rainfall data is grouped first based on the same month, before it was forecasted. The results showed that the highest rainfall in 2020 was 490.73 mm (April) and the lowest was 3.25 mm (August). While for 2021, the highest rainfall was 521.37 (April) and the lowest was 3.25 mm (August), with an MSE of 14731.56, RMSE of 121.37, MAD of 97.42, and SSE of 176778.69.

Validation of Rain Thickness Model Based on GPM Satellite and Surface Measurements

The limited acquisition of rainfall data from the Climatological Station of Deli Serdang has resulted in constraints on research in several fields. Global Precipitation Measurement (GPM) has spatial and temporal advantages as a solution to this problem. This study aims to provide information on the rain thickness equation model based on the Global Precipitation Measurement (GPM) Satellite as an alternative to calculating rain thickness at the Climatological Station of Deli Serdang. Data from the Global Precipitation Measurement (GPM) Satellite and Climatological Station of Deli Serdang were used, covering the period from January 1 to December 31, 2021. The Rescaled Adjusted Partial Sums (RAPS) method was used to verify the data quality, and the two data were consistent. The rain thickness equation model was obtained using a simple linear regression method. At the same time, the validation of the rain thickness equation model with surface measurements used the Root Mean Square Error (RMSE), Nash Sutcliffe Efficiency (NSE), and Correlation Coefficient (R) methods. The validation findings demonstrate that the rain thickness data from the Global Precipitation Measurement (GPM) Satellite was close to that of the Climatological Station of Deli Serdang, with an RMSE value of 5.85 mm, NSE of 0.99 mm, and R of 0.99. Hi = 5.21ti0.50 mm was the model used to calculate the equation for rain thickness. 6.84 mm, 0.69 mm, and 0.94 mm were the validation results of the equation model for RMSE, NSE, and R.Keywords: Rain Thickness, Global Precipitation Measurement (GPM), Climatological Station of Deli Serdang, Equation Model, Validation

Disclosing Strategy in Communicating Uncertainty: Case of Climatology Station Climate Information Dissemination in Lombok Island

Certainty of climate information is essential for farmers in developing farming decisions but, climate forecasts produced by Climatology Station contain 30 per cent uncertainty. The fact that climatology station has carried out climate information dissemination to farmers in Lombok. However, many farmers experienced harvesting and planting failure due to climatic uncertainty. The objectives of this research are to describe the communication strategy implemented by the Kediri Climatology Station in communicating climate information to farmers on Lombok Island and to identify obstacles experienced in disseminating climate information. This research was conducted at the Kediri Climatology Station and on the island of Lombok using a descriptive method. Data were collected through in-depth interviews. The collected data were analyzed using descriptive qualitative analysis. The results show that the strategies implemented by the Kediri Climatology Station were strategies to increase the station's credibility through the improvement of data collection technique and analysis to minimize uncertainty, compiling and packaging messages so that farmers easily understand them, conducting direct dissemination through climate field school (SLI) and indirect using media, trying to understand the social and economic conditions of the communicants as well as utilization of feedback. However, there are obstacles faced by the Kediri Climatology Station in providing climate information namely: many extension agents are reluctant to convey climate information to farmers, climate change that affects forecast accuracy, difficulty convincing the public, and lack of funds to conduct Climate Field School, limited personnel, and language barriers.

Karakteristik Iklim Di Kota Palembang Serta Implikasinya Terhadap Bencana Kabut Asap

This research was conducted to determine the characteristics of the climate and its relationship to the haze disaster in the city of Palembang by utilizing data from the BMKG observation station, namely the Palembang Climatology Station and the Sultan Mahmud Baharudin II Meteorological Station, from 1981 to 2020. The research method used is secondary data research with a quantitative approach. The analysis used is according to the rules of the Expert Team on Climate Change Detection and indices ETCCDI. Trend analysis was carried out using the non-parametric Mankendal statistical and sens tests. The indices that experienced a significant trend were the temperature index, which indicates that the temperature in Palembang is increasing from time to time. The relationship between dry days has a correlation level of >0.9. This shows a close relationship between haze disasters and days without rain (CDD). The months prone to smog occur in June, July, August and September (JJAS).

Climate Change Trends in a European Coastal Metropolitan Area: Rainfall, Temperature, and Extreme Events (1864–2021)

This paper summarises an updated climate change trends analysis—developed for the period from 1 October 1864 to 30 September 2021 within the scope of a Horizon 2020-funded project to increase climate resilience in European coastal cities—for a representative site of the Lisbon Metropolitan Area (Portugal). By using long ground-based daily records of rainfall and surface temperature at the Lisboa-Geofísico climatological station, the analysis aimed to identify (i) long-term and recent climate trends in rainfall and temperature, (ii) changes in extreme rainfalls, heatwaves, and droughts, and (iii) possible effects of the coupled changes of minimum and maximum daily temperatures (Tmin and Tmax, respectively) on drought development based on the diurnal temperature range (DTR) indicator. To detect these trends and quantify their magnitude, the Mann−Kendall and Sen’s slope estimator tests were implemented. The analysis of the mean annual temperatures indicated that the study area has warmed ∼1.91 °C through the 157 analysed years. Results evidenced statistically significant upward trends in both Tmin and Tmax, and in the number of Tmax heatwave days. In what concerns the extreme hydrological events, the analysis of annual maximum rainfall series and peaks-over-threshold (POT) techniques showed more frequent and intense events in recent years, reaching up to ∼120.0 mm in a single day. With regard to drought, the study proved that the characterisation based on the commonly used standardised precipitation index (SPI) might differ from that based on the standardised precipitation evapotranspiration index (SPEI), as the latter can take into account not only rainfall but also temperature, an important trigger for the development of drought. According to the SPEI index, severe and extreme drought conditions have been more frequent in the last 60 years than in any other recorded period. Finally, a decreasing DTR trend towards the present was found to influence evapotranspiration rates and thus drought characteristics.

Identification of the rain gauge stations for the participatory flood and landslide mitigation in the Serayu river basin, Central Java

Rainfall data is vital in analysing hydro-meteorological disasters, e.g., floods, landslides, or droughts. Currently, the location of climatological stations or rain gauges is preferred in areas that require climatological data, such as airports and near settlements. On the other hand, rainfall analysis for disaster mitigation purposes is more for remote areas, which are often far from the nearest rainfall station. This study aims to obtain accurate rainfall data through the placement of suited rain gauge locations and utilising community participation. The method used in this study is a literature review. This preliminary study was held upstream of the Serayu river basin, an area where it is usually challenging to access rainfall data. The references used are information about tropical rain, how to utilise a rain gauge network, and how to take advantage of community participation. The result shows that an Early Warning System should be developed in line with determining the location of the rain gauge because each location has a different rainfall threshold in each disaster. The placement of the rain gauge is strongly influenced by the landscape, the altitude of the place as well as the slope and aspect. For this study, the location of schools in remote areas is another parameter to determine the placement of a rain gauge since school children will be involved in the community participation.

PEMETAAN DISTRIBUSI CURAH HUJAN RATA-RATA MENGGUNAKAN METODE ISOHYET DI WILAYAH KABUPATEN TANGERANG

The purpose of this study was to obtain information related to the distribution mapping of average rainfall in the Tangerang Regency area. Hydrological analysis is needed in determining the average rainfall in an area, one of which is by using the Isohyet method. The isohyet method is a method of making a connecting line that brings together points of the same rain depth. The research was conducted by analyzing rainfall data in the Tangerang Regency area in the last five years, namely the period 2016 to 2020. The research data were obtained from three observation stations, namely: 1. Budiarto Curug Meteorological Station, 2. Pondok Betung Climatology Station, and 3. Ciputat Region II BMKG Station. This research was conducted in two activities, namely: 1. Rainfall data collection, and 2. Data processing using Minitab and ArcGIS applications. Based on the results of processing rainfall data for the 2016-2020 period at three observation stations, the P-Value was 0.115 and the Kolmogorof Smirnov test value was 0.103 for heading 1, P-Value was 0.115 and the Kolmogorof Smirnov test value was 0.103 for heading 2, and P-Value < 0.010 and the Kolmogorof-Smirnov test value of 0.195 for heading 3. The results of the calculation of rainfall from the three observation posts show that the rainfall in the Tangerang Regency area is normally distributed. The results of the rainfall mapping using the Isohyet method also show that the rainfall in the Tangerang Regency area is evenly distributed.

Pencarian dan Pemanfaatan Informasi Data Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)

The Meteorology, Climatology, and Geophysics Agency (BMKG) has the task of carrying out government duties in the fields of Meteorology, Climatology, Air Quality, and Geophysics by the provisions of the applicable legislation. This study aims to search and utilize BMKG meteorological data in the Yogyakarta area. This research was conducted at the Mlati Climatology Station, Sleman, Yogyakarta. The analysis used uses descriptive analysis. The data collection method uses observation techniques, interviews, documentation from offline data centers, and BMKG online data. From the results of the study, the search for meteorological data of BMKG Yogyakarta for the benefit of the community includes inputting data until processing until it is published to the public through social media such as Whatsapp, Instagram, Facebook, Twitter, Email, Radio, and Television. The utilization and importance of BMKG weather information are very influential for the survival of the people in Yogyakarta. With the information from the BMKG, the community can know the weather forecasts in the next few days and adjust the work that makes the weather as its indicator such as farming, tourism, fisheries, transportation, trade, and government as well as government agencies working in the field of disaster management.