bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disaster mapping as decision support system to decrease abrasion impact due to climate change in Bantul Coastal Area
Authors: Naufal M , Nandini M , Rahmanu Y A , Najib D W A , Kusumaningrum P B , Ahyar M I , Hizbaron D R 
Published: August 2019

Abstract
Global climate change affects the physical condition of coastal areas, one of which is the rise in wave height. The increase in wave height allows higher volume of carried substrate on the swash and backwash motions. These events have an impact on increasing the abrasion intensity, specifically on the coastal areas which consist of sand material (beaches). Coastal area of Bantul Regency is one of the areas exposed to abrasion because it is directly facing the Indian Ocean. Application of atmospheric science and technology is needed to reduce the impact of losses caused by abrasion. Disaster mapping is an effort to reach that expectation. This research aimed (1) to identify abrasion susceptibility, and (2) to analyse social vulnerability due to abrasion in Bantul coastal area. The assessment was done by GIS-based spatial-multi criteria analysis to process physical and socio-cultural aspects in regards of abrasion, which the analytical unit was the coastal area between Opak and Progo River estuaries. This research resulted in susceptibility map and social vulnerability map as references for coastal mitigation directives supporting the resilience of region and community towards climate change.
Rice plantation projection based on scenario representative concentration pathways (RCP) 4.5 in West Java Province
Authors: Hidayat N M , Agustina L , Wibawanty D R , Safril A 
Published: August 2019

Abstract
Climate change is characterized by the changing of weather and climate elements in the earth, such as temperature and precipitation over a long period. The changing of these climate elements will affect the water balance then affect the agricultural management system, especially in timing and cropping patterns. This study aims to explain the projection of climate change result in the future and its relation with the changing of planting time and crop patterns of rice in West Java Province based on Representative Concentration Pathways (RCP) 4.5 scenario from 2006 until 2040. The data used in this study were observation data of temperature and rainfall in period of 2006-2015 from 39 rainfall posts with the height data of each rainfall post. The analysis conducted in this study was based on Thorntwaite and Matter water balance models by using observation data (2006-2015) as the baseline and future periods (2021-2030 and 2031-2040). Air temperature and rainfall data in period of 2006-2015 were used to correct the model data. Calculation of groundwater availability was calculated for each representative of Oldeman climate type. Furthermore, the rice planting schedule can be known when the condition of the level of groundwater availability reaches field capacity. The results of the analysis show changes in the Oldeman climate type and the level of groundwater availability due to changes in air temperature and rainfall parameters resulting from projections on current conditions. This caused a change in the planting schedule. The planting schedule will start early when the climate type turns wet, so the condition of the level of groundwater availability increases. The planting schedule in September was seen more broadly in the East and West parts of West Java in the period of 2021-2030 compared to the period of 2006-2015 and 2031-2040.
Urban Heat Islands analysis towards topographic based land use change and daily commute effect along the Kaliurang Street in Yogyakarta
Authors: Suarma U , Hapsarini S A , Isnastuti N L , Ikhwani H R , Durrotunafisah  
Published: August 2019

Abstract
This paper’s aim is to analyse the correlation between land change pattern and its topography with Urban Heat Islands (UHI) in Kaliurang Street and surrounding area. Secondly, the effects of daily commuting activities from rural or sub urban area towards urban area are well identified. Kaliurang Street is one of the major streets in Sleman that uniquely represented the transition between rural, suburban, and urban area. Rural area is located in the furthest north, suburban located in the center, while the urban area is located in the southern part. Transect method carried out along Kaliurang Street to obtain primary data mainly temperature and vehicles number. Data collected during daytime (between 12-2 PM) and afternoon (between 3 to 5 PM). Furthermore, LANDSAT 8 OLI/TIRS satellite imagery was analyzed to obtain the Land Surface Temperature (LST) Information, while ALOS PALSAR was analyzed to obtain elevation data. One of the causes of temperature differences is the commuting which affects the variation of surface temperature along Kaliurang Street. Therefore, strong correlation between commuting and the UHI phenomenon are expected.
The influence of environmental conditions (vegetation, temperature, equator, and elevation) on tropospheric nitrogen dioxide in urban areas in Indonesia
Authors: Syafei A.D , Irawandani T. D , Boedisantoso R. , Assomadi A. F , Slamet A. , Hermana J. 
Published: August 2019

Abstract
Nitrogen dioxide (NO2) is one important species in the tropospheric layer that has a contribution towards air quality. In urban areas in Indonesia, urbanization and growing industrial activities have increased rapidly, which may have affected tropospheric NO2. This study investigates the effect of green spaces and other environmental variables (e.g., temperature, city, distance from the equator) had on tropospheric NO2 in over thirty (30) urban areas in Indonesia between 2007 to 2016. Data on land cover were obtained from Google Earth’s satellite imagery data, tropospheric NO2 readings came from Metop-A, and information on temperature was obtained from the Terra MODIS satellite. Our results show an annual decrease in green space over 10 years in all urban areas except Surabaya. Multiple linear regression analysis also reveals that a decline in vegetation decreases tropospheric NO2 significantly. Other influential environmental factors are surface temperature and distance to the equator. Despite a promising model being obtained from this study, adding variables is important to improve the forecasting.
Diurnal Pattern of PM10 and CO in Riau as a Forest Fire Risk Area
Authors: Sumaryati  , Budiwati T , Indrawati A , Syahrial  
Published: August 2019

Abstract
PM10 and CO are air pollutants emitted by fossil fuel combustion and biomass burning have the bad impact on human being. Riau as a forest fire risk area, it is supposed that air quality related to PM10 and CO affected by the fire. This paper studies diurnal pattern of PM10 and CO in Riau during 2015 when a strong El Nino phenomena occurs. The diurnal pattern of pollutant is useful for hazard mitigation of the pollutant especially when its concentration reaches maximum and potent to exceed the threshold value of ambient air quality. The result of the study shows plot scatter of PM10 and CO has got the correlation coefficient of 0.72 when no fire period and 0.91 when fire period. The strong correlation in fire period is caused by the similarity of major sources of biomass burning that ignored other sources. Both diurnal patterns, especially CO shows a bimodal shape when no fire period, and the pattern changes to being flat all of the day when a great forest fire occurs in Riau and its surrounding. The bimodal shape was characterized by two concentration peaks in the morning at 08.00 and in the evening at 20.00 local time that was related on rush hour, atmospheric stability, chemical reaction rate of CO. During one year of el Nino phenomena in 2015, CO concentration is still below national air quality standard although in a great fire period and the diurnal peak concentration, while PM10 concentration in some days in fire period exceeds the national air quality standard.
Forecast of Tropical Cyclone Occurrences based on Fuzzy Logic Algorithm
Authors: Irawan A M , Nugroho H A , Simanjuntak P P , Sugiarto S I 
Published: August 2019

Abstract
Most studies of the tropical cyclone (TC) forecasting are focused on the track and the wind radius forecasting, even though a tropical cyclone formation alerts also developed. This paper takes a different approach and explores and forecast the TC occurrences. This study presents the development of fuzzy logic (FL) models for predicting the occurrence of TC from five primary TC genesis parameters. These parameters are low-level relative vorticity (θ), horizontal wind of upper troposphere (u), sea surface temperature (SST), equivalent potential temperature (θe), and specific humidity (q). The FL model was developed by employing the trapezoidal and triangular fuzzy membership functions for the input and output variables. The fuzzy rules were inferred from the TC genesis parameters data, with a daily calculation period from 1989 to 2018. The amount of TC genesis parameters when the cyclone occurred of the lowest, middle, and upper tercile reconstruction was used as a threshold to build FL model. The model satisfactorily simulated the occurrence of TC with comparable error measures. The result exhibits the accuracy at 0.75 (range: 0 to 1, perfect score: 1). The evidence shows that the result provides insights into the adequacy of FL methods for forecasting the TC occurrences.
Indonesian Climate under 2°C and 4°C Global Warming: Precipitation Extremes
Authors: Supari  , Sopaheluwakan A , Linarka U A , Rizal J , Satyaningsih R , Chung J X 
Published: August 2019

Abstract
The Paris Agreement, signed in 2015, is intended to limit global warming well below 2°C. This paper is aimed to assess the potential key impact of 2°C and 4°C global warming on the characteristics of precipitation extremes over Indonesia. For this purpose, the CSIRO-Mk3.6.0 global projections forced by the representative concentration pathway (RCP8.5) scenario is dynamically downscaled using the RegCM modelling system. The results show that under these two global warming level, total annual precipitation (PRCPTOT) will decrease in most regions. Consistently, the dry spell duration (CDD, consecutive dry days) is projected to increase. On the other hand, the frequency and the intensity of precipitation extremes (R50mm and RX1day) are projected with mix increase and decrease tendency. Seasonally, the contrast changing of PRCPTOT is projected. PRCPTOT tends to decrease during dry season (June-July-August, JJA) and tends to increase during wet season (December-January-February, DJF). The similar pattern is found for other indices e.g. CDD, R50mm and RX1day. In general, changes at 4°C global warming are statistically more significant and more intensified compared to that at 2°C. Our findings suggest the benefit of limiting global warming at a lower level.
Sensitivity of Planetary Boundary Layer Scheme in WRF-Chem Model for Predicting PM10 Concentration (Case study: Jakarta)
Authors: Musthafa M , Turyanti A , Nuryanto D E 
Published: August 2019

Abstract
Weather Forecasting-Chemistry (WRF-Chem) is an air pollution model that combines meteorological factors and atmospheric chemistry simultaneously (online coupled). Many schemes selected on WRF-Chem according to boundary layer conditions of the study area. The objectives of this study were to evaluate WRF-Chem model and analyze the sensitivity of Yonsei University (YSU) scheme and Mellor Yamada Janjic (MYJ) scheme as physical boundary layer parameters, especially for Jakarta region. Particulate matter 10 micrometers or less in diameter (PM10) selected as the air pollutant parameter. The model outputs compared to observational data in five locations in Jakarta. The regression analysis between air temperature data shows that the values of R2 are 0.5 - 0.6 in February and 0.5 - 0.9 in August. Another result, the wind velocity from WRF-Chem overestimates but the hourly averages have a similar diurnal pattern with the observation. The PM10 concentration model output is underestimated which is caused by local emissions that are not accommodated in the model. The sensitivity analysis shows a higher sensitivity index for MYJ than YSU scheme, especially in August, so the model outcome of the MYJ scheme has a good response to the observations in Jakarta. It is seen that the extreme concentration of PM10 produced through the WRF-Chem with both schemes in February and August have the same time in morning. The model output of WRF-Chem through both schemes also demonstrate the minimum concentration of PM10 that follows during afternoon. The Planetary Boundary Layer (PBL) height analysis shows that in morning until noon, the PBL height with MYJ scheme is lower than YSU. It is different for other hours, that from the afternoon through the night until next morning, the height of PBL with MYJ scheme is thicker than YSU. At the point when the PBL is high, the pollutants assorted in a more volume so the estimation of the pollutant concentration estimated on the surface will be reduced.
Comparison of seasonal prediction outputs based on dynamic atmosphere model and observations (case study: seasonal prediction in 2016 - 2017)
Authors: Satyawardhana H , Gammamerdianti  
Published: August 2019

Abstract
Seasonal predictions are considered as an important factor for many sectors in Indonesia, especially for the agriculture sector. In Indonesia, the variability of seasonal characteristics is influenced by various regional atmospheric phenomena, such as monsoon, ENSO, and IOD. With such urgency, this research is conducted using dynamic models to generate accurate medium-term predictions. The dynamical atmospheric model, Cubical Conformal Atmospheric Model (CCAM) is used to produce daily predictions up to 8 months. CCAM result has been tested on major islands in Indonesia such as Java, Sumatra, Sulawesi, Borneo and Papua. It shows that during the rainy season, the value of rainfall predictions is lower than observations. Meanwhile, the rainfall predictions are overestimate when compared to observations during dry season. Nevertheless, the patterns of rainfall predictions are following satellite rainfall observations patterns, especially in Java.
The Indonesia In-House Radar Integration System (InaRAISE) of Indonesian Agency for Meteorology Climatology and Geophysics (BMKG): Development, Constraint, and Progress
Authors: Permana D S , Hutapea T D , Praja A S , Paski J A I , Makmur E E S , Haryoko U , Umam I H , Saepudin M , Adriyanto R 
Published: August 2019

Abstract
In 2017, BMKG has 41 weather radars covering most of Indonesia region and most of its data are automatically sent to the BMKG headquarter every 10 minutes. There are four different weather radar brands with its specific data format and software analysis. In recent years, the weather radar community has developed open-source software to handle several radar data formats. Based on this, BMKG has developed the Indonesia In-House Radar Integration System (InaRAISE) of BMKG using the open-source weather radar software. InaRAISE has been developed using Python-based libraries Wradlib and Py-ART for processing weather radar data. BMKG radar data have been successfully extracted and transformed into Cartesian coordinates for post-processing. The multiple radars have been successfully composited by comparing column-maximum reflectivity. Web-based near real-time radar images has been experimentally operated, but not officially launched. The main constraint is the susceptible communication network between radar sites and BMKG headquarter causing real-time data transfer problems. InaRAISE serves feasible data radar extraction for data assimilation in the numerical weather prediction model. InaRAISE could serve as a supporting of the existing radar integration system or possibly as a replacement.
WRF-3DVAR Radiance Data Assimilation Impact for Convective Rain Prediction on Jakarta
Authors: Fatmasari D , Rosita Dewi D M P , Gustari I 
Published: August 2019

AbstractWeather Research and Forecasting (WRF) is an open source numerical weather prediction model, but one of the main problems is the inaccuracy of initial condition that impacts the accuracy of weather predictions. Techniques that can be used to improve initial condition is to assimilate satellite radiance data using Three-Dimensional Variation (3DVAR) method. The Global Forecast System (GFS) data were used as initial conditions which were assimilated with several radiance data such as from AMSU-A sensors, MHS sensors, and ATMS sensors. The purpose of this study was to compare the effect of data assimilation on the initial condition model and the rainfall prediction for convective precipitation on February 24, 2016 in Jakarta. The results showed there is a clear flow of moisture to the northern part of Jabodetabek area that cause the model captured a high relative humidity which results in the heavy rain. The result of the study obtained different rainfall prediction between non-assimilation model and assimilation model. In general, both models have underestimated rainfall, but satellite radiance data assimilation is better able to describe the convective rain patterns and has better accuracy on the convective rainfall accumulation per hour.
Numerical Analysis using Empirical Orthogonal Function Based on Multivariate Singular Value Decomposition on Indonesian Forest Fire Signal
Authors: Septiawan P , Nurdiati S , Sopaheluwakan A 
Published: August 2019

Abstract
Over the past years, fires have burn Indonesian forest annually. The strength of the fire and many of fire points is vary each year. In 1997 there was 9.75 million ha forest burned in one year with 206,6 million ton of carbon emissions. In 2015 there was 2.089 million ha forest and 805 million tons carbon emissions. Both years involved the biggest incidences of burned forest in Indonesia. The purpose of this research is to analyze the pattern of burned forest in Indonesia and to analyze linkages of variables that affect it. Datasets that used in this research is monthly data from 1997 until 2016 Global Fires Emissions Database (GFED) with variable burned area, GFEDs with variable carbon emissions, and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Using Singular Value Decomposition and Empirical Orthogonal Function analysis, for the overlapping period detected that there is annual signal that dominate the incidences of fires in Indonesia, especially in Riau, Palembang, South Kalimantan and Central Kalimantan. There was 4 annual signal that can explain 72% of fires incidences in Indonesia in 1997-2016. In Riau there is another signal that have 6 months period caused by 6 months rainfall period.
Identification of rainfall area in Indonesia using infrared channels of Himawari-8 Advance Himawari Imager (AHI)
Authors: Risyanto  , Lasmono F , Nugroho GA 
Published: August 2019

Abstract
The study aims to investigate the use of Infrared (IR) channels of Himawari-8/AHI for identification of rainfall area in Indonesia. The parameters used include the IR brightness temperature (BT) at 10.4 microns (T10.4) and seven IR BT differences (BTD), which were inferred as proxies for cloud properties. Identification of rainfall in this study is based on lookup table (LUT) approach, which is used to create probability of rainfall map. The LUTs were developed by combining the IR at 10.4 microns and IR BTD with the transportable X-band radar data, gathered during the campaign period on 15 March – 5 May 2017. Statistical skill scores were used in the study to determine the overall performance of the methods. The study indicated that the best IR and BTD combination to identify rainfall area is from the bands correlated to cloud-top height proxy (T10.4 and BTD 13.3- 10.4). In visual comparison with Global Satellite Mapping of Precipitation (GSMaP) hourly rainfall image, this IR-BTD method produced rain maps with high similarity. In general, almost all IR-BTD combinations could be used to identify rainfall area with comparable results. However combination of T10.4 and BTD at 6.2 & 7.3 micron generate high false alarm rates and underestimate the area of rainfall.
Identification of The Influence of Long Winter Season in 2017 – 2018 to the Forming of Strong Northerly Cold Surge over West Indonesia
Authors: Nugroho Y A , Fajarianti R , Imami A F R , Winarso P A 
Published: August 2019

Abstract
This study identifies the characteristic of strong Northerly Cold Surge (NCS) over West Indonesia in the period from November 2017 until April 2018. Usually the NCS occurs in the DJF period that indicates the rainy season that usually goes to trigger some serve weather in Indonesia. The severe weather accompanying the intense northerly cold surge often brings more major disruptions that often trigger natural disasters like floods and landslides to the affected regions in West Indonesia. Descriptive and statistical methods are used in this study by classifying the intensity of NCS in November 2017 until April 2018. The real-time data from Ogimet Weather Information Service, GSMaP Satellite, and restudy data from National Centers for Environmental Prediction (NCEP) are used to determine the 925 millibar meridional wind, relative humidity in 1000, 925, 850, and 700 millibar, mean sea level pressure, and rainfall estimation to identify the passage of NCS in West Indonesia region. The long winter season in 2017 – 2018 triggered the NCS to stay active even it comes to March and April 2018. It is proven by the natural disaster that comes from consecutive intense rainfall like floods and landslides that still intensively occurred in the March until April 2018 in West Indonesia.
Examination of bark content for different species of short rotation coppice
Authors: Szalay D , Papp V , Hodúr C , Czupy I 
Published: August 2019

Abstract
Short rotation coppices (SRC) can produce large amount of dendromass in a short time. From an energetic point of view, one of the most important challenges are the outstanding amount of ash content, which is primarily generated due to the high bark content of the thin shoots. Our research was carried out for measuring bark content of four species/clones performed in three different vegetation years. The experimental plantation is located in the northwestern part of Hungary. The results show that the bark content strongly depends on the applied harvest frequency and tree species. Based on the measurements, the Robinia pseudoacacia and the Salix alba species have the largest bark content in the first year but the value can be reduced by around 50% by using longer harvest rotation. Having analyzed the whole stem, the bark percentage of the Populus x euramericana clones increased from 5.5% to 33.7% from the cutting height to the tip. The minimum value was at the diameter class of 24-28 mm. In the case of Robinia pseudoacacia the bark content ranges only between 3.0% and 20.0%.
Research and implementation of substation clock unsynchrony alarm system based on GPS pulse
Authors: Zhang Chuan-yu 
Published: August 2019

Abstract
In order to change the status quo within the substation bay control devices which only passive receiving IRIG-B GPS clock code or PPS, for the purpose of the research and the realization method of substation clock unsynchrony alarm system based on GPS pulse. On the basis of existing substation SCADA system and GPS time synchronization system, this paper realizes the real-time monitoring of time synchronization of substation bay control devices by simple modification and introduction of simple algorithm. This paper describes in detail the system construction method and relative time difference algorithm, as well as the project implementation method, to achieve the correct and punctual on-line monitoring of the bay control device, effective control of substation accidents caused by device time unsynchrony, greatly improving the stability of substation operation.