bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short vertical-wavelength gravity wave activities in the upper troposphere lower stratosphere observed with global navigation satellite system radio occultation under different QBO phases
Authors: Rasyad Firas , Hadi Tri Wahyu , Noersomadi  
Published: December 2021

AbstractGravity Waves (GWs) are believed to play important role in the generation of the driving force of the stratospheric Quasi-Biennial Oscillation (QBO). Deep convection in the equatorial region can generate large amount of GW with short vertical wavelength (λz<1 km) but studies of these wave activities in the upper troposphere lower stratosphere (UTLS) region are still limited. Recent advances in Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieval techniques have made it possible to derive global temperature profile with vertical resolution of less than 1 km. In this research, activities of GW with λzfrom 0.5 to 3.5 km in the UTLS region of 20-27 km heights are identified by calculating the GW potential energy (Ep). Correlation between GW activities and QBO phases is examined using 50 hPa zonal wind as the QBO index. The results show that during both easterly and westerly QBO phases, the GWEpvalue increases gradually with time and reaches its peak in the transition periods. This pattern is seen inEpwith all vertical wavelengths between 0.5-3.5 km but the percentage value ofEpfor λz<1 km is higher during the transition from westerly to easterly QBO. The GWEpvalues exhibit downward propagation with the QBO phase but there are also discernible upward propagations of GW activities below 24 km height and intersect those two bring large changes in QBO phases. Additionally, higher percentage ofEpwith λz<1 km is also found to be associated with El Niño events.
Forest Fire in East Nusa Tenggara during 2015-2019: Comparison to Forest Fire in Kalimantan and Sumatera
Authors: Sumaryati  , Andarini D F , Cholianawati N , Indrawati A 
Published: December 2021

AbstractEast Nusa Tenggara is one of the provinces in Indonesia that has big forest fires following some provinces in Kalimantan and Sumatra. However, forest fires in East Nusa Tenggara have less attention in forest fires discussion in Indonesia. This study aims to analyze forest fires in East Nusa Tenggara and their impact on reducing visibility and increasing carbon monoxide (CO) from 2015 to 2019. In this study, hotspot, forest fire area, Oceanic Niño Index, visibility, and CO total column data were used to analyze the forest fires using a statistical comparison method in East Nusa Tenggara, Kalimantan, and Sumatra. The result shows that the number of hotspots in East Nusa Tenggara less than in Kalimantan and Sumatra for the same forest fire area. The forest fires in East Nusa Tenggara do not harm the atmospheric environment significantly. East Nusa Tenggara dominantly consists of savanna areas with no peatland, hence, the forest biomass burning produces less smoke and CO. Furthermore, the forest fire in East Nusa Tenggara has not an impact on decreasing visibility and increasing CO total column, in contrast, visibility in Sumatra and Kalimantan has fallen to 6 km from the annual average, and CO total column rise three times of normal condition during peak fire.
Analysis of Multi-Scale Hydrometeorological Triggering Flash Flood Event of the 13 July 2020 in North Luwu, South Sulawesi
Authors: Paski J A I , Makmur E E S , Permana D S , Nurrahmat M H , Praja A S , Riama N F , Fitria W , Hartanto  
Published: December 2021

Abstract
During 12-13 July 2020, heavy rainfall had caused Masamba, Rongkong, and Rada rivers to overflow, causing flash floods in the North Luwu regency. This event resulted in many casualties; at least 38 people died and displaced thousands of people. This study presents an analysis of the multi-scale hydrometeorological settings that led to the development of these intense storms in the North Luwu fl ood. Boreal Summer Intraseasonal Oscillation (BSISO) Normalized PC2 has entered phases 4 and 5 on 7 - 13 July 2020, associated with cloud growth in the Indonesian Maritime Continent. Besides, the sub-seasonal tropical disturbance of Kelvin Waves is convectively active in the Sulawesi region on 7 - 13 July, increasing the intensity of rainfall at the location. Sea Surface Temperatures (SSTs) were in warmer conditions in the Bonne Bay region south of North Luwu, supplying more water vapor into the atmosphere. The easterly wind (Australian monsoon) enhanced the diurnal cycle of the water vapor mass movement from Bonne Bay to the highlands of North Luwu. From the observation of GPM satellite imagery, the accumulation of spatial rainfall on July 12 and 13 was concentrated in the eastern region of Sulawesi, which reached >150 mm/day and >50 mm/day in North Luwu.
Study of Mesoscale Convective Complex (MCC) and its impact over the Makassar Strait (case study: 9 December 2014)
Authors: Ni’amillah A , Ismail P , Siadari E L , Saragih I J A 
Published: December 2021

Abstract
A mesoscale Convective System (MCS) is a system consisting of groups of convective cells in the mesoscale. One of the largest types of MCS subclass is Mesoscale Convective Complex (MCC) occurred in the eastern part of the Makassar Strait near the Madjene and Polewali Mandar regions on 9 December 2014, morning to evening (09.00-15.00 LT). Using MTSAT-2 Satellite Imagery data, reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) interim era, the Global Satellite Mapping of Precipitation (GsMap) rainfall, sea surface temperature, surface air observation, and upper air observation, the author will examine the existence of MCC in the Makassar Strait in terms of atmospheric conditions when MCC enters the initial until extinct and the accompanying effects of precipitation. In general, it is known that the MCC formed in the waters of the Makassar Strait in the morning, and then it moved westward. The mechanism of its formation was through a process of convergence of the lower layers in the waters of the Makassar Strait and its surroundings to trigger the process of cloud formation. Warm thermal conditions also gave a big influence on the lower layers to the top and activate convective in the study area. Meanwhile, the MCC occurrence region also has high relative humidity, negative divergence values, and maximum vorticity values. The impact of the emergence of MCC on that date resulted in areas with very large humidity and cloud formation and produced rain in the surrounding area, in this case using rainfall data from Hasanuddin Meteorological Station, Makassar, South Sulawesi. With a duration of up to seven hours extinct, MCC in the Makassar Strait produces heavy rainfall in the Makassar Strait waters.
Improvement in WRF model prediction for heavy rain events over North Sumatra region using satellite data assimilation
Authors: Saragih Immanuel Jhonson Arizona , Mukhsinin Huda Abshor , Tarigan Kerista , Sinambela Marzuki , Situmorang Marhaposan , Sembiring Kurnia , Humaidi Syahrul 
Published: December 2021

AbstractLocated adjacent to the Indian Ocean and the Malacca Strait as a source of water vapour, and traversed by the Barisan Mountains which raise the air orographically causing high diurnal convective activity over the North Sumatra region. The convective system that was formed can cause heavy rainfall over a large area. Weather Research and Forecasting (WRF) was a numerical weather model used to make objective weather forecasts. To improve the weather forecasts accuracy, especially for predict heavy rain events, needed to improve the output of the WRF model by the assimilation technique to correct the initial data. This research was conducted to compare the output of the WRF model with- and without assimilation on 17 June 2020 and 14 September 2020. Assimilation was carried out using the 3D-Var technique and warm starts mode on three assimilation schemes, i.e. DA-AMSU which used AMSU-A satellite data, DA-MHS which used MHS satellite data, and DA-BOTH which used both AMSU-A and MHS satellite data. Model output verification was carried out using the observational data (AWS, AAWS, and ARG) and GPM-IMERG data. The results showed that the satellite data assimilation corrects the WRF model initial data, so as increasing the accuracy of rainfall predictions. The DA-BOTH scheme provided the best improvement with a final weighted performance score of 0.64.
Simulation of daily variation of precipitation during anomalously-wet dry season event over the western Maritime Continent
Authors: Yulihastin E , Suaydhi  , Satyawardhana H , Ihsan C N 
Published: December 2021

Abstract
Local seas play a significant role in causing anomalously wet of the dry season over the Indonesia Maritime Continent (10°S-8°N, 95-145°E). As a result, modeling the anomalously-wet dry season over Indonesia lead challenges due to several subregional processes over local seas could not be captured well in the regional climate model. This study explores subregions processes of sea-air interaction over the western Maritime Continent by simulating diurnal precipitation using Cubic Conformal Atmospheric Model (CCAM) with a spatial resolution of 32 km during the anomalously-wet dry season periods during May-to-September (MJJAS) 2020. The simulated results were confirmed by precipitation data from Tropical Rainfall Measuring Mission (TRMM) satellite observation. The results show anomalous circulation patterns induce anomalous regional precipitation over western MC is induced by anomalous circulation patterns over four keys of seas subregion, i.e., Indian Ocean, South China Sea, southern Sumatra (Lampung and Sunda strait), and the Java Sea. Furthermore, the anomalous circulation also modulates anomalous local circulation and enhances surface water vapor by an increased surface latent heat flux.
Coastal storm waves detection system design using Beaufort scale standardization and Sugianto wave forecasting method in Timbulsloko, Demak, Central Java, Indonesia
Authors: Ginanjar S , Adiningsih S , Fadlilah Y N , Wulandari S , Petrova C B , Ikhtiarino S 
Published: December 2021

Abstract
Storm is defined as a disturbance of the atmosphere marked by winds and usually by rain. Coastal storms must comprise a maritime component, such as waves, currents and/or water levels. Coastal storm detection is necessary so the number of casualties and losses caused by these events can be reduced. The method used in this system is the Sugianto wave forecasting method with standardization of coastal storms using the Beaufort scale. The purpose of this study is to built up an internet of things based system to observe coastal storm information and wave forecasting data from wind speed data that obtained in Timbulsloko, Demak, Central Java, Indonesia. The tidal data is processed using the Admiralty method. This system was built using Arduino Uno equipped with anemometer JL-FS2 to measure wind and waves parameters. The power source from 100 wp solar panels stored in a 40 Ah accumulator. Data from field instrument is stored to the IoT MAPID database using NodeMCU ESP8266. This system is placed in Timbulsloko, Demak. The results of field observation then validated using BMKG. This method could be applied in other location along the north coast of Java. The results of field observation showed an average wind speed 3.9848 m/s; significant wave height 0.4632 m; significant wave period 3.8641 s; wave energy 493.90 J/m2; wind energy 116.74 W/m2.
Analyzing Rainfall and Greenness Vegetation Level on Forest/Land Fire Area in Jambi and Central Kalimantan Provinces using Remote Sensing Data
Authors: Rahmi Khalifah Insan Nur , Prasasti Indah , Nugroho Jalu Tejo , Rokhis Khomaruddin M. 
Published: December 2021

Abstract
El-Nino, which occurred in 2019 in Indonesia, caused longer dry conditions than usual. Low rainfall and vegetation drought cause widespread forest/land fires. This study aims to know the relationship between drought conditions and forest/land fires from the parameters of rainfall and vegetation greenness level. The study located in Jambi and Central Kalimantan Provinces during the peak months of fires which is September 2019. To see fluctuations in the peak of fires, eight daily data were taken for this period. Extraction of rainfall information is derived from the Himawari-8 infrared band L1 image into L2 rainfall rate data. Vegetation greenness level information is derived from Terra/Aqua MODIS red and near-infrared band images into L2 Enhance Vegetation Index (EVI) data. Hotspot data comes from the images of Terra, Aqua MODIS, SNPP VIIRS, and NOAA20. Fire data was extracted from hotspot data and delineation of MODIS RGB image smoke. Rainfall fluctuation affects the number of forest/land fire hotspots. The decrease in rainfall was followed by an increase of hotspot numbers and vice versa. In Jambi Province, rainfall decreased in first to second period i.e. 40 to 0 mm was followed by an increase of hotspot number which dominated by high confidence level. In Central Kalimantan rainfall increased from third to fourth period i.e. 0 to 100-400 mm followed by the decreasing of hotspot number which dominated by medium confidence level. Meanwhile, the TKV variable had little effect on the number of hotspots but related with rainfall data. In Central Kalimantan Province, the driest TKV (0.1) on September 14-21, 2019, was influenced by low rainfall in the previous period which also has highest number of fire hotspots. In Jambi Province, the driest TKV happened on third period which also the result of lowest rainfall and highest number of fire hotspot in the previous period.
DINEOF reconstruction for creating long-term cloud-free sea surface temperature data records: A Case study in Lombok Strait, Indonesia
Authors: Andrawina Yochi Okta , Kismawardhani Ratu Almira , Rejeki Hasti Amrih 
Published: December 2021

Abstract
A long-term reliable sea surface temperature (SST) satellite data record is requisite resources for monitoring to understand climate variability. Creating a long-term data record especially for climate variability requires a combination of multiple satellite products. Consequently, missing data issues are inevitable. Hence, DINEOF (Data Interpolating Empirical Orthogonal Functions) has been applied to attain a complete and coherent multi-sensor SST data record with EOF-based technique by reconstructing the missing data. Unfortunately, the technique can lead to large discontinuities in the data reconstruction due to images depiction within long time series data. For that reason, filtering the temporal covariance matrix had been applied to reduce the spurious variability and more realistic reconstructions are obtained. However, this approach has not yet tested in tropical region with higher evaporation which cause incomplete satellite image coverage. Therefore, the objective of this research is to reconstruct SST of Lombok strait with data gaps up to 58.16% in one year. It is successfully reconstructed until the last iteration of 42 optimal EOF modes with the convergence achieved up to 0.9806×10-3, including previous set-aside data for internal cross-validation. The results highlight that the DINEOF method can effectively reconstruct SST data in Lombok Strait.
Application of hydrometeorological data to analyze water balance conditions in Bengkulu watershed
Authors: Faski G I S L , Purnama Ig L S , Suprayogi S 
Published: December 2021

Abstrak
Water balance serves to determine hydrological conditions in a watershed, one of which is by analyzing the surplus (excess water) and deficit (water shortage) that occurs. Extreme surpluses or deficits can cause hydrometeorological disasters, such as floods or droughts. This study aims to calculate the monthly water balance using the Thornthwaite-Mather method to determine variations in the incidence of surplus and deficit months in all three sub-watersheds in Bengkulu Watershed, namely Rindu Hati, Susup, and Bengkulu Hilir sub-watershed. The data used are monthly hydrometeorological data for 2009-2018 (10 years) were divided into two periods of water balance based on land use data. Water balance period 1 (2009-2013) uses 2009 land use data, while period 2 (2014-2018) uses 2014 land use data. The results show that the surplus, deficit, runoff, and discharge in the three sub-watersheds in the Bengkulu watershed are affected by rainfall. In general, the deficit incidents in all three sub-watersheds occur almost every three years. The Rindu Hati and Susup sub-watersheds have the same variations of surplus and deficit month incidents, while the Bengkulu Hilir sub-watershed is different, both in periods 1 and 2. It is not only the rainfall that affects the variation in the events of surplus and deficit in all three sub-watersheds of the Bengkulu watershed, but also the amount of water holding capacity (WHC). Therefore, the application of hydrometeorological data to analyze the water balance conditions in the Bengkulu watershed provides information on climate impact on water resources and environmental impact on flows in the watershed.
Mapping of mangrove forest tree density using SENTINEL 2A satelit image in remained natural mangrove forest of Sumatra eastern coastal
Authors: Samsuri  , Zaitunah A , Meliani S , Syahputra O K , Budiharta S , Susilowati A , Rambe R , Ulfa M , Harahap M M , Arinah H , Elfiati D , Rangkuti A B , Sucipto T , Hakim L , Iswanto AH , Manurung H , Azhar I 
Published: December 2021

Abstract
The mangrove ecosystem in Forest Managemen Unit - VII (FMU) Sumatera Utara is a natural forest. FMU has not managed and utilizes mangrove forests optimally. It can open up opportunities for illegal loggers and trigger damage to these natural ecosystems. This condition requires prevention and mitigation so that severe damage to mangrove forests does not occur. This study aims to determine the relationship between vegetation index and mangrove density in the field and map the mangrove density distribution based on the image vegetation index value. The density distribution mapping was carried out by compiling a vegetation density estimator model NDVI, GNDVI, and TVI as independent variables. Correlation test and regression analysis between the vegetation index value (NDVI, GNDVI, and TVI) to the number of trees per unit area. The distribution model for the density of mangrove stands was chosen based on the coefficient of determination (R2). The study resulted from NDVI selected as the vegetation index used to map the distribution of mangrove density with a Pearson correlation coefficient (R) of 0.738. The selected model is Y = 2.48e2.8667x, which is an exponential equation with a coefficient of determination (R2) of 61.3%. Based on this model, the distribution of mangrove density has the lowest density reaching 400, and the highest density is 2,200 trees per hectare
The Bamboo Standing Stock Analysis in Karo Highland, North Sumatera - Indonesia
Authors: Samsuri  , Zaitunah A , Ahmad A G , Ramadhan M F 
Published: December 2021

AbstractBamboo is a type of grass with a high growth rate and can be a substitute for wood. The bamboo container is vast in range, so it is easy to cultivate. The number and distribution of Bamboo need to know how much Bamboo is available to meet market demand. This study aims to determine the standing stock of Bamboo in Karo districts. The method used is the multistage sampling method, which is to take samples on the map and continue with sampling in the field. Research shows that the dominant types are rope bamboo rope and green bamboo. The number of clumps found was between 600 and 1,600 per hectare. The average number of stems is 1,231 stems per ha. The most number clump bamboo ranges from 20 – 30 unit/ha; the most length bamboo section is between 25 – 30 cm.
Framework application of e-DNA metabarcoding as a variable to evaluate mangrove ecosystem
Authors: Basyuni M , Susilowati A , Susetya I E , Kajita T 
Published: December 2021

Abstract
Indonesia has the largest mangrove forests in the world, about 22.6% of the global total area. Mangrove forests are known to provide great benefits to the community as an ecosystem service and globally. Mangrove forests are threatened with loss due to anthropogenic and non-anthropogenic activities. Our previous research results show the important role of mangroves in the context of climate change for reducing greenhouse gas emissions and the diversity of terpenoids for salinity defense. The term metabarcoding of environmental DNA as a key indicator for evaluating mangrove ecosystems was introduced. This work proposed framework to study environmental DNA metabarcoding applications that can provide accurate information for evaluating mangrove ecosystems using an easy and fast method. The rich mangrove forest is getting disappeared without being recognized by its true diversity, function, and potential services to human beings. Application of conservation activities based on the species diversity in the mangrove ecosystem is almost impossible, because it is too difficult to study, in term of time and effort, despite the importance of acquiring the biodiversity information. However, DNA metabarcoding can be a “dream-like” tool and will contribute to obtain the species diversity data of the mangrove ecosystem, rapidly, globally, and massively.
Life cycle analysis (LCA) of the production of wood waste briquettes from Pinus spp.: Case study San Francisco Pichátaro, México.
Authors: Medina-Ríos E , Morales-Máximo M , López-Sosa L B , Aguilera-Mandujano A , Corral-Huacuz J C 
Published: December 2021

Abstract
This study shows a life cycle analysis (LCA) of the production of briquettes from wood residues of Pinus spp. in an indigenous community in Mexico. The analysis was carried out considering one Mega Joule (1MJ) of heat as a functional unit, including mainly environmental sustainability indicators, through the Life Cycle Analysis (LCA), and generating environmental impact scenarios for the functional unit by: a) comparing the carbon footprint using solar drying and firewood drying in the production of briquettes and (b) comparing the carbon footprint of the heat obtained by the briquettes from both previous systems with heat obtained from liquefied petroleum gas (LP gas) and firewood. The results show that solar-dried briquettes have the lowest carbon footprint, and more than 80% of the emissions are biogenic, making it an excellent choice as a clean and renewable energy source. In addition, the methane emissions from LP gas is much higher than emissions from briquettes, but the carbon monoxide (CO) and particulate matter (PM2.5) emissions are lower. This methodology applied to the production process will help decision-making in the creation of a micro-enterprise for the generation of solid biofuels in rural communities in Mexico.
Release of nickel ions and changes in surface microstructure of stainless steel archwire after immersion in tomato and orange juice
Authors: Lubis H F , Simamora G H 
Published: December 2021

Abstract
Stainless steel archwire is an important component of orthodontic appliances that have the potential to corrode. Consumption of foods and beverages with a low pH, such as fruit-based juices, can trigger the release of nickel ions in stainless steel archwire. This study aimed to determine the difference in the amount of nickel ions release and the surface microstructure of stainless steel archwire after immersed in tomato and orange juice. The sample used is stainless steel archwire with a diameter of 0.016 inches and length of 5 cm immersed in 15 ml of solution and then stored at 37°C in an incubator for 24 hours. The samples were divided into three groups (immersed in tomato juice,orange juice and artificial saliva), each group consisted of 9 samples. The solution was tested using an Inductively Coupled Plasma Mass Spectrometer (ICP-MS) to determine the number of nickel ions released. The archwire surface microstructure was tested using a Scanning Electron Microscope (SEM). The results showed that the average amount of nickel ion release in orange juice is more than tomato juice. There was a significant difference between the amount of nickel ion released and surface microstructure on stainless steel archwire after being immersed in tomato and orange juice.