bluuebunny/crossref_metadata_2025 huggingface dataset:
CHARACTERIZATION OF CHILI SAUCE SMOKED TUNA FISH (THANNUS SP.)
Authors: Fattah Nurlaeli , Santi Andi , Matti Agussalim
Published: July 2023

The purpose of this study was to determine the shelf life of smoked fish chili sauce and the characterization of smoked tuna chili sauce. Proximate analysis data are presented in the form of tables and bar charts. Quantitative data generated from organoleptic testing were processed using Microsoft Excel and SPSS. Organoleptic test data is presented in the form of a bar chart. Quantitative data from the results of the TPC (Total Plate Count) test were processed using Microsoft Excel and presented in graphical form. Data analysis was carried out descriptively. From the process of making smoked tuna chili sauce, the results are obtained; Guava wood which is used in the smoking process as a source of smoke in tuna, affects the texture, aroma and taste, the characteristics of hard guava wood give a longer burning effect so that it affects the water content of smoked tuna, smoked tuna chili sauce from wood sources different influences on the levels of proximate composition in smoked tuna chili sauce.
Design Development of Embedded Flying Observer
Authors: S. A. Sawant  , S. A. Pawar  , S. A. Devakate  , A. A. Kamble  , R. B. Salunkhe
Published: July 2023

Concept of developing a powered Flying Observer taking into consideration ideas from colorful attempts to make similar machine in the history. The sect design has been made in such a way that it more or less imitates the natural flopping of the catcalls of suitable size and pattern. The medium mentioned in this report is grounded on multiple bar liaison in order to negotiate exact flopping geste of an factual raspberry. The idea is theoretically simplified and also reckoned and anatomized in the aerodynamic and other tools. posterior development and prototype testing would corroborate the authenticity of the theoretical conclusions reached
Bactericidal properties of donkey milk
Authors: Turganbaeva N. K. , Musulmanova M. M.
Published: July 2023

This paper provides a literature review focusing on the aspects of the preservation of the bactericidal properties of the main components of donkey milk, such as lysozyme and lactoferrin, which have an antibacterial function, inhibiting the development of a number of pathogenic and opportunistic microbes, which is an important factor in storage and production of dairy products. The review includes articles published in English and Russian from 2002 to 2022. The databases Scopus, Web of Science, Elsevier, ResearchGate and Elibrary were used for the search. A review of the literature showed that most of the available information is focused on the use of non-thermal and lowtemperature milk processing methods while preserving the biologically active components of native milk. Components of donkey milk can be used as an inhibitor of late bloating of semi-hard and hard cheeses from sheep milk caused by Clostridium and E. coli bacteria. The most favorable temperature regimes, at which the main characteristics of donkey milk are preserved, are: 10 days at 3°C and 3-4 days at 7°C. The combined use of HPP (High Pressure Processing) with pasteurisation extends the shelf life of the milk up to 30 days at 4 °C. The given data must be taken into account both when selecting the technology for the production of dairy products from donkey milk or in combi[1]nation with it and when carrying out research work with donkey milk.
Effect of very high frequency microwave light on bread properties
Authors: Тuychiyeva D. М. , Soliyeva D. A.
Published: July 2023

The article is devoted to the study of flour produced by disinfected microwave for the baking properties of grain. The study of methods aimed at ensuring the quality and safety of grain products. Pest control measures for grain storage facilities are complex, costly and require a complete shutdown of production. Therefore, methods using UV, IR, microwave radiation, electric fields and other physical methods that do not require production interruption are of considerable interest. These methods are among the most promising, environmentally friendly, operating continuously and allowing reducing the cost of pest control while increasing its effectiveness. Therefore, among the various measures to ensure the quantitative and qualitative preservation of grain stocks, pest control under the influence of microwave is essential.
Application of rosa canina l. to replace sodium nitrite in sausages
Authors: Kenenbay G. S. , Tursunov A. A. , Zhumalieva T. M. , Tultabaev N. Z.
Published: July 2023

Among meat products, sausages are in high demand among consumers, due to their readiness for consumption without additional processing, specific pleasant taste and aroma, and relatively long shelf life. However, a number of synthetic additives are used in the composition of sausages, which in the future can be replaced by natural plant ingredients with functional properties. The aim of this study was to evaluate the possibility of using rosehip extract (Rosa canina L.) as a natural ingredient to replace sodium nitrite in cooked sausages. 5 batches of boiled sausages were produced: 1) positive control with sodium nitrite, 2) negative control without sodium nitrite, 3) experimental batch with 3% concentration, 4) with 8% concentration, 5) with 15% extract concentration wild rose (Rosa canina L.). The study of extracts of Rosa canina L. on the content of solids, sugars, polyphenols and antioxidant activity showed their significant increase. Indicators of antioxidant activity of boiled sausages also showed a tendency to increase with an increase in the concentration of the extract in the composition. However, to recommend Rosa canina L. as an antioxidant component to replace sodium nitrite in the composition of sausages, additional studies on the development of microbiological indicators during storage and organoleptic analysis are required.
The influence of herbal supplement on the functional and technological properties of boiled camel sausage
Authors: Medeubayeva Zh. , Tayeva A. , Chernukha I. M. , Rskeldiyev B. , Tlevlessova D. , Kapbasova A.
Published: July 2023

This article deals with the possibility of improving the functional and technological properties of cooked sausage made of camel meat with the addition of humpback fat and chicken fillet. The aim of the research was to study the effect of selected vegetable additives on the functional and technological properties of cooked sausage. The effect of red currant powder on lipid oxidation, the effect of red currant powder and linseed flour on the functional and technological properties of sausages made from combined meat (camel meat, chicken fillet and hump fat) has been studied. Camel meat as a raw material has many advantages, such as low fat content, high nutritional value, hardly distinguishable from beef in taste. Flaxseed meal and dried redcurrant powder were added in various quantities and compared to improve the functional and technological properties. The control sample was made according to GOST for boiled sausage, with replacement of fat by hump fat, and replacement of beef by camel meat. A fractional-factor experiment plan was constructed for the experimental samples, taking into account the material balance. The additives were varied in 3 levels, from 0 to 3 %. We obtained 7 samples with control, a sausage prepared according to the same recipe, but without additives, was taken as a control sample. As a result of analysis of the data obtained the conclusion was made that the addition of flax meal should be no more than 3.5%, the addition of 3% is desirable, with the functional and technological properties of the sausage being improved. The addition of currant powder should not exceed 1.5%, a dose of 1% is desirable. Adding 3% changes the flavour to a more acidic one.
External Focus Affects Drop Jump Performance: Focusing on Different Aims and Words of Instruction
Authors: Furuhashi Yuki , Hioki Yusuke , Maemura Hirohiko , Hayashi Ryohei
Published: July 2023

Attentional focus strategies eliciting an external focus of attention effectively enhance drop jump (DJ) performance, however, their effects vary depending on the words used for the instructions. We aimed to examine the effects of different words on DJ performance using instructions eliciting external focus to minimize contact time (CT) or maximize jump height (JH). Twenty collegiate athletes performed DJs from a 30 cm platform after receiving one of four instructions: two instructions (COND 1 and 2) about minimizing CT and two instructions (COND 3 and 4) about maximizing JH. Reactive strength index (RSI), CT, JH, relative peak vertical ground reaction force (vGRF), and leg stiffness (kvert) were compared between conditions using repeated-measures analysis of variance. There was no significant main effect of conditions on RSI, relative peak vGRF, and kvert (p > 0.05). CT was significantly shorter in COND 1 and 2 than in COND 3 (p < 0.05); JH was significantly higher in COND 3 than in COND 1 and 2 (p < 0.05), and in COND 4 than in COND 1 (p < 0.05). When using attentional focus strategies in DJ, it is necessary to use different words and purposes according to the players' tasks.
Flipped Classroom Learning Model With Kahoot Media: the Effectiveness to Affect Students Motivation and Learning Outcomes in Biology Subject
Authors: Zulyetti Diana
Published: July 2023

The problem of low motivation and student learning outcomes in Biology after the Covid-19 pandemic is still found at SMAN 1 Payakumbuh District. In this study a flipped classroom type hybrid learning model was used combined with the use of the kahoot! game application. The research was conducted using a quasi-experimental quantitative approach with a one shot case study design in class XI MIPA 1 students totaling 32 people. Data were collected using motivational questionnaires and objective questions to measure student learning outcomes. The results of the study show the use of the flipped classroom type hybrid learning model combined with the use of the kahoot! effective effect on increasing motivation and student learning outcomes in Biology subject, besides that the use of this model also has a positive effect on student independence in learning.
Financial Literacy, Risk Perception, and Herding Effects on Investment Decisions
Authors: Oktasari Dian Primanita
Published: July 2023

This study aims to analyze financial literacy, risk perception, and herding and its impact on investment decisions. The population in this research is an investor in Jakarta. The sample used is 100 respondents. Calculate based on Lameshow’s formula. The method of data collection using the survey method, with the research instrument is a questionnaire. The data analysis method uses descriptive analytics. This study proves that financial literacy has a positive and significant effect on investment decisions, risk perception has a positive and significant effect on investment decisions and herding has not had a significant effect on investment decisions.
Newspapers’ Usage of Multiple Channels in News Dissemination and Its Implication on Their Business Survival
Authors: Ikeme Rosemary , Olley Wilfred Oritsesan , Akpor Daniel Ewomazino
Published: July 2023

The introduction of internet technology came with multiple channels through which newspaper now distributes their contents to readers to keep them informed to make profits. This study looks at newspapers’ use of multiple channels for news dissemination and the implication for their business survival. To tackle this research work, the survey method with the use of a questionnaire was adopted. The Technological Determinism theory was chosen for this study. Data for the research work were obtained from the staff of The Nation newspaper, a leading national daily in Nigeria. The data obtained were presented, analyzed, and interpreted with the use of the Statistical Package for the Social Sciences (SPSS). The study found that the introduction of multiple channels has affected news production as readers are now used to getting news content from various channels just as the profit from multiple channels is sustaining newspaper enterprises. The study recommended, among other things, that newspaper companies should seize the initiative from digital platforms to create workable online multi-channels to draw large readerships while still retaining their print version, and since it is obvious that readers are now adapting to multiple channels, they should fully adopt the use of multiple channels to stay afloat in business.
Carbon Monoxide Poisoning: Comparison of Paediatric and Adult Patients
Authors: ORHAN Özhan , YEŞİL Ahmet
Published: July 2023

Background: Carbon monoxide (CO) gas is a tasteless, odorless and colorless gas and causes many poisonings every year. In this study, paediatric and adult CO poisoning cases admitted to our emergency department were reviewed retrospectively.
Materials and Methods: Paediatric and adult patients who applied to the Emergency Department of Mardin Training and Research Hospital between 01 January 2021 and 31 December 2022 due to CO poisoning due to stove usage were included in the study. Patients were compared according to age, gender, month and time of admission to the emergency department, complaints at admission, laboratory test results and discharge status.
Results: 90 patients admitted to the emergency department due to CO poisoning caused by stoves between 2021-2022 were included in the study. While the rate of female patients in the paediatric age group was 53.3%, the rate of female patients in the adult group was 48.9% (p=0.673). When compared according to the complaints of admission to the hospital, the most common complaint in the paediatric age group was nausea-vomiting with 42.2%, while the most common complaint in the adult group was shortness of breath with 26.7%. In both groups, it was determined that the most frequent application was in January with 48.9%. While 15.6% of children were hospitalized, this rate was 4.4% for adults. (p=0.065). While the carboxyhemoglobin (COHb) value at the time of first admission was 18.36±6.60 in the paediatric group, it was 22.03±10.24 in the adult group (p:0.047). In the control blood gas values taken at discharge, COHb level was 2.76±1.83 in children and 5.10±3.02 in adults (p
Pelatihan Khutbah Jum’at Bagi Remaja Masjid Di Kecamatan Palabuhanratu Kabupaten Sukabumi
Authors: Acip
Published: July 2023

Khutbah jum’at adalah momen yang tepat bagi seorang da’i untuk menyampaikan nasihat kepada ummat meskipun dengan waktu yang singkat, karena justru nasihat itu akan sangat berkesan ketika disampaikan dengan singkat dan padat. Maka menjadi penting bagi seorang khatib memiliki kepiawaian dalam menyampaikan nasihatnya ketika berkhutbah. Tulisan ini bertujuan untuk mendeskripsikan pelaksanaan pelatihan khutbah jum’at bagi remaja masjid yang ada diwilayah kecamatan Palabuhanratu yang dilaksanakan di kampus STAI Pelabuhanratu. Metode pelaksanaanya adalah dengan meberikan pengetahuan dasar fiqih khutbah, tips-tips khutbah, dan cara menyusun naskah khutbah. Hasil dari pelatihan tersebut adalah: (1). Peserta dapat memahami pengetahuan dasar fiqh khutbah (2). Memahami cara membuat naskah khutbah.
Analisis Hukum Pernikahan Menggunakan Wali Hakim Persfektif Hukum Islam Dan Kompilasi Hukum Islam
Authors: Solahudin
Published: July 2023

Wali hakim ialah wali nikah yang ditunjuk oleh Menteri Agama atau pejabat yang ditunjuk olehnya, yang diberi hak dan wewenang untuk bertindak sebagai wali nikah. Wali hakim baru dapat bertindak sebagai wali nikah apabila wali nasab tidak ada, tidak mungkin menghadirkannya, tidak diketahui tempat tinggalnya atau gaib, adhal atau enggan. Khusus untuk wali adhal atau enggan maka wali hakim baru dapat bertindak sebagai wali nikah setelah ada putusan Pengadilan Agama. Peraturan Menteri Agama No. 30 tahun 2005 tentang wali hakim dalam pasal 3 ayat (1) dan ayat (2) menjelaskan ‚Kepala Kantor Urusan Agama Kecamatan (KUA) dalam wilayah kecamatan yang bersangkutan di tunjuk menjadi wali hakim untuk menikahkan mempelai wanita sebagaimana di maksud dalam pasal 2 ayat (1) peraturan ini‛. Dan ‚Apabila Kepala KUA Kecamatan sebagaimana di maksud pada ayat (1) berhalangan atau tidak ada, maka Kepala Seksi yang membidangi tugas Urusan Agama Islam atas nama Kepala Kantor Departemen Agama Kabupaten/ Kota di beri kuasa untuk atas nama Menteri Agama menunjuk salah satu penghulu pada kecamatan tersebut atau terdekat untuk sementara menjadi wali hakim dalam wilayahnya. Sifat penelitian ini merupakan deskriptif kualitatif. Dalam penelitian ini, teknik yang digunakan untuk mengumpulkan data berupa wawancara dan dokumentasi. Hasil dari penelitian ini didapatkan bahwa mengenai wali hakim yaitu wali penganti dari wali nasab, sedangkan mengenai syarat-syarat menikah dengan wali hakim yaitu apabila wali nasabnya sudah habis, tidak diketahui tempat tinggalnya dan enggan menikahkan .Kesimpulan terhadap pernikahan dengan wali hakim yaitu bahwa seharussnya wali hakim didapatkan dari proses putusan Pengadilan Agama.
Sleep quality and factors that disturb it in university students
Authors: Bayas Condo Xiomara Nataly , Herrera López José Luis
Published: July 2023

Introduction: Sleep deprivation is the situation of sleep incapacity. There are two classifications: chronic and acute. When there is not proper rest, the patient can get drowsiness, fatigue, weight loss and negative problems in cognitive functions. Objective: To analyze the quality of sleep and factors that disturb it in university nursing students, in the period September-December 2022. Methodology: Quantitative-descriptive and cross-sectional approach. 121 participants were approached using questionnaires (Sleep disturbing factors & Pittsburg sleep quality index) It was validated with a Cronbach's alpha of 0.75 and 0.81, which guarantees the reliability of the instrument. Results: The mean score of the participants of the Pittsburgh quality index is 7 which tells us that the students need medical attention. Conclusions: Despite not presenting several sleep disturbances, university students have poor sleep quality, and they are known as poor sleepers.
A model for rapid wildfire smoke exposure estimates using routinely-available data - rapidfire v0.1.3
Authors: Raffuse Sean , O'Neill Susan , Schmidt Rebecca
Published: July 2023

Abstract. Urban smoke exposure events from large wildfires have become increasingly common in California and throughout the western United States. The ability to study the impacts of high smoke aerosol exposures from these events on the public is limited by the availability of high-quality, spatially-resolved estimates of aerosol concentrations. Methods for assigning aerosol exposure often employ multiple data sets that are time consuming and expensive to create and difficult to reproduce. As these events have gone from occasional to nearly annual in frequency, the need for rapid smoke exposure assessments has increased. The rapidfire R package (version 0.1.3) provides a suite of tools for developing exposure assignments using data sets that are routinely generated and publicly available within a month of the event. Specifically, rapidfire harvests official air quality monitoring, satellite observations, meteorological modeling, operational predictive smoke modeling, and low-cost sensor networks. A machine learning approach (random forests regression) is used to fuse the different data sets. Using rapidfire, we produced estimates of ground-level 24-hour average particulate matter for several large wildfire smoke events in California from 2017–2021. These estimates show excellent agreement with independent measures from filter-based networks.
Toward seamless weather forecasts.
Authors: Moret Lionel , Spirig Christoph , Siegenthaler Colombe , Bhend Jonas , Nerini Daniele , Buzzi Matteo , Schaer Mathieu , Liniger Mark
Published: July 2023

On a daily basis, MeteoSwiss provides a wide range of automatic weather forecasts to the general public, the aviation and to private customers. These data are provided by an ensemble of heterogeneous individual system wich forces the end-user to choose between different sources and sometimes to combine them despite a limited knowledge of their quality and shortcomings. In addition, the forecasts of the different systems are provided in different formats and through different channels, making combined use even more difficult.
Furthermore, from a scientific point of view, combining nowcasting and post-processing approaches in a single step using statistical and/or machine learning methods has been shown to give the best forecast performance for twelve hour precipitation forecasts Deep learning for twelve-hour precipitation forecasts. Nat Commun 13, 5145 (2022)). In such an approach, there is no need for a separate system for the nowcasting range, and therefore no need to combine different forecasts a posteriori, which requires further assumptions and introduces further source of errors and inconsistencies.
MeteoSwiss has therefore initiated a project to build a system that will integrate data from different weather observation and weather forecasts data (ECMWF, MeteoSwiss regional ICON implementation) in order to provide a consolidated and easily accessible weather forecast dataset. We aim as well for probabilistic gridded forecasts that are seamless in space and time which can be used by a wide range of application, like hydrological models, automatic generation of warning proposals for forecasters, probabilistic animation of precipitation for the MeteoSwiss App. This project is very much oritented toward end-users and a large effort will be made to assess and meet their needs.
Analysis of Wind Data and Assessment of Wind Energy Potential in North-West Hungary
Authors: Mendyl Abderrahmane , Peter K. Musyimi Peter , Adrás Zénó Gyöngyösi , Weidinger Tamás
Published: July 2023

Recently, the world is facing an increasing use of renewable sources of energy that will require a clear understanding of wind energy as an affordable source for sustainability. North-West part of Transdanubia is the windiest region of Hungary. Energy production from two Energon type wind generators are investigated in a wind farm near Mosonmagyaróvár, 10 km from the Austrian border. Wind speed, direction and energy production were recorded with 10 minutes time resolution for a period of 6 years (2010-2015). The hourly wind speed and direction dataset from ERA5 are also investigated. The collection of historical wind data serves the same objective as any other statistical information to improve weather forecasting by knowing what the wind was like on a specific period of time at a specific location and identifying a wind pattern allows you to compare this information to the prediction. This was done using E40 wind-turbine on 65 m height (Max power 600 kW), with mean wind speed of 5.26 ±2.8 m/s and an average power of 103 kW and E70 wind-turbine on 113 m height (Max power 2000 kW), measured wind speed of 5.87±3.12 m/s with an average power of 457 kW. The study adopted Weibull distribution to model wind speeds and applied Power density method to estimate the scale and shape parameters. This is a relatively new, simple formulation and requires less computation. The values of k and c factors were retrieved as functions of the mean wind speed, wind sectors and energy pattern factor respectively.Wind energy production forecasts were provided by WRF model system for 48 hours with site specific model output statistics. The model was run twice a day (00 and 12 UTC) with 10 km horizontal resolution and 28 vertical level based on GFS model outputs. Uncertainties of energy forecasts were also investigated. In most cases, the model underestimated the wind speed. Further application of the developed model system will be carried out in semi-arid region of Morocco.
Evaluation of selected bias correction methods for the development of local climate projections in Slovakia
Authors: Kristekova Nikola , Lapin Milan
Published: July 2023

Regional and local climate projections are important for climate change impact research. However, the outputs of global and regional climate models show deviations from observations on regional and local scales. Generally, the deviations increase with a larger difference between model and observation scales. These deviations hinder the usage of climate model output for practical applications. To improve agreement of the model outputs to observations without the necessity of running a higher resolution climate model, statistical downscaling methods are utilized.
One widely used group of methods are bias correction methods, which are relatively simple, computationally undemanding, and only adjust the model output. However, both bias correction in general, and individual bias correction methods have limitations, and their application may not always be appropriate. Therefore before using any bias correction method to obtain climate projections, it is first necessary to evaluate the performance of the method, and also to determine the effect it has on the simulated climate change signal.
In this work we evaluated four existing bias correction methods. Two of these methods perform a correction by a factor (additive for temperature, scaling for precipitation). The other two are quantile mapping methods, one of which was specifically designed to preserve the simulated climate signal. We applied the methods to daily average, maximum and minimum air temperatures, and daily precipitation totals, which were simulated by an ensemble of regional climate models from the EURO-CORDEX framework. Before applying the methods, the model outputs were interpolated to locations corresponding to meteorological stations.
Based on the evaluation, we selected methods for air temperature and for precipitation that achieved the best results in terms of both 1) effective reduction of bias, and 2) low modification of the simulated climate signal. Using these methods, we then created local projections of air temperature and precipitation until the year 2100 for selected meteorological stations in Slovakia.
Interrupting Normal Television Programming to Broadcast Ongoing Derechos
Authors: Trobec Jay
Published: July 2023

It is common in the United States for commercial television stations to break away from scheduled programs for live coverage of tornadoes and hurricanes. It is much rarer for stations to interrupt programs for severe thunderstorm events such as derechos.  
Climatologically, the eastern half of the state of South Dakota experiences moderate and high intensity (MH) derechos approximately once every one to three years (Coniglio and Stensrud 2004). But in 2022, there were two such events in the region in 54 days. During the storms, one television station interrupted programming non-stop for several hours to broadcast coverage of the derechos and their projected movement.  
While it is unusual practice to broadcast non-tornadic storms, due to the size and temporal longevity of derechos it is possible they pose a greater threat to persons and property than localized tornadoes. Post-event audience measurements confirmed there was significant viewership of the derechos, providing the public with advance notice of incoming damaging winds. 
Novel machine-learning-based fire weather indices
Authors: Shmuel Assaf , Heifetz Eyal
Published: July 2023

In light of the increasing frequency of droughts and extreme fire weather events, in Europe and world wide, the need for accurate wildfire risk estimation is becoming more and more acute. Wildfire risk depends however on complex non-linear interactions between multiple factors such as fuel moisture content, winds, humidity, topography and others.Traditional fire indices, currently used by weather services, are based on linear models and or empirical and statistical analyses. Consequently their performance is somewhat limited.  Here we propose a novel set of fire weather indices (FWIs), developed using machine learning (ML) – the MLFWI.  We find that the MLFWI significantly outperforms the traditional fire indices in predicting wildfire occurrence, achieving an AUC score of 0.99 compared to 0.62-0.80.We also analyze the influence of the various factors and their interactions on the models, providing scientific insights and understanding of the mechanism by which the models work. Finally, we compare the performance of the MLFWIs to that of traditional indices in predicting the 100 largest wildfires in the dataset. We find that our models were able to predict the vast majority of these 100 extreme events.In the talk we will present the Machine Learning methodology and examine the performance of the the MLFWI. The ultimate goal of this research is to allow implementation of  the MLFWI in actual wildfire warning systems. We propose to build upon this study to gradually replace the existing fire weather indices with ML-based indices, which have the potential of substantially improving fire weather alerts.
Understanding predictability of tropical cyclones over the North Atlantic Ocean
Authors: Chung Shun Yiu Brett , Fink Andreas H. , Riemer Michael
Published: July 2023

Tropical cyclones (TCs) are extreme weather events capable of causing major loss of life and property. Despite continued improvements in our understanding of TC dynamics and the advancement of numerical models over the past few decades, accurate and precise forecasting of TCs beyond the short-term (<=72 hours) window remains an operational challenge. In other words, there seems to be a ‘predictability barrier’ for TCs at several days in lead time. For example, according to the US National Hurricane Centre (NHC), the average error for a 5-day track forecast of Atlantic TCs generally exceeds 300 km over the last ten years with little change in trend. The predictability of TCs is thus an interesting and practically relevant topic for investigation.
We evaluate TC-relevant ensemble statistics with lead time of up to 8 days before genesis for the Atlantic basin, starting from 2017. ECMWF operational ensemble forecast data are used on NHC best-tracked tropical and subtropical systems. TC-like vortices are first tracked using the feature-tracking algorithm TRACK based on lower-tropospheric relative vorticity. They are then matched against the respective TCs from the operational analysis data by a technique known as Dynamic Time Warping, which allows for some spatio-temporal discrepancies. Two main groups of TCs, i.e., those that form in the Main Development Region (MDR) and those that undergo tropical transition (TT) are selected for analysis due to their distinctly different genesis characteristics. Special attention is drawn to the phenomenon of ‘forecast jumps’ (i.e., sudden and substantial shifts in the ensemble probabilities with lead time) as identified in previous work on this topic. The evaluation parameters used include minimum central MSLP, maximum 10m mean wind, storm location and various parameters on tropospheric thermal structures (for storms with TT).
Preliminary results suggest MDR and TT storms do exhibit very different behaviours with regard to genesis predictability. The more ‘classical’ TCs that form in the deep tropics are typically better forecast in advance and provide a longer window of predictability, perhaps to more than a week. In contrast, their mid-latitude counterparts are sometimes only captured by the model a few days prior to the TT event. Ensemble members can struggle to distinguish between a warm or cold-core system, before converging on a solution rather abruptly. The case study of Hurricane Ophelia (2017) is useful to illustrate this phenomenon. Additional results will be presented as further work is done to establish and analyse behavioural statistics while enlarging the TC sample set.
Convection initiation in complex terrain – can it be linked to meso-scale convergence?
Authors: Gasch Philipp , Oertel Annika , Hervo Maxime , Team the Swabian MOSES
Published: July 2023

In the summer of 2021, the Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign was carried out in southwestern Germany. The campaign focused on the initiation and development of deep convective systems between the Black Forest and the Swabian Jura. During the campaign, the first measurements with a new airborne Doppler lidar system were conducted and a ground-based Doppler lidar network consisting of eight stations was deployed.
This contribution presents combined airborne and ground-based lidar observations which provide new insight into meso-scale flow processes in the vicinity of deep convective systems initiating in complex terrain. The unique spatial sampling characteristics of the airborne Doppler lidar are exploited to evaluate whether a quantitative retrieval of meso-scale convergence during convection initiation in complex terrain is possible and meaningful. The combination with radar observations provides context for the convective activity associated with the observed flow field. The convergence estimation approach is then also applied to the ground-based Doppler lidar network, providing also insight into the temporal evolution of the flow field.
The observations and convergence estimates are compared to the operational convective-scale analysis produced by the Icosahedral Nonhydrostatic modelling framework (ICON) of the German Weather Service. This facilitates the evaluation of the validity of assumptions inherent to the network-based convergence retrieval. Subsequently, the network-based convergence estimates can be used to gain insight into the analysis accuracy.
Overall, the influence of meso-scale convective systems on flow characteristics is detectable both in airborne and ground-based measurements. A quantitative estimation of convergence appears possible and can be used to enhance process understanding and improve model evaluation. The combination of airborne Doppler lidar measurements with a ground-based Doppler lidar network proves useful. While the former provides both extended spatial coverage and high resolution during intensive observation periods, the latter allows for temporally resolved observations over extended periods. Thus, together these measurement systems prove to be a suitable and promising technique to gain new insights into flow phenomena in the vicinity of convective systems in complex terrain.
Assessment of daily and monthly precipitation record data over the Fiji Islands for the period 1905-202
Authors: Fernández-Duque Beatriz , Vicente-Serrano Sergio M. , Kumar Rovil , Domínguez-Castro Fernando , Peña-Angulo Dhais , Noguera Iván , El Kenawy Ahmed
Published: July 2023

Over the last century, climate change has become a subject of great interest and is recognized as one of the major global challenges facing humankind in the 21st century. Changing precipitation patterns including extreme events such as more intense and prolonged dry periods have become a growing concern for people living in the Pacific Island region given their high dependence on rainfall for their freshwater needs as well as the precipitation impact on different sectors and socioeconomic activities. However, up to date, little attention has been paid to understanding the implications of climatic changes for people and their capacity to manage these changes. Here we have analyzed the temporal evolution of precipitation data over the Fiji islands for the period 1905–2021, using observational in-situ data from 23 meteorological stations and using 23 climate indices calculated with the ClimInd R package by using daily precipitation data. These indices are focused on extreme precipitation events which characterizes the data record as regards the frequency (e.g. the number of dry days or the number of very wet days), the duration (e.g. the longest dry period or the longest wet period) and the precipitation intensity (e.g. the total precipitation amount) among others. Positive increasing trends were found for the majority of daily climate indices although no statistically significant trends were dominant. The results derived from this study can be useful as validation of climate models helping to better understand climate change processes in this vulnerable climate region from a wide perspective which could help for climate decision-making.
 Keywords: precipitation pattern, extreme events, Pacific Island region, trends, climate indices, ClimInd.
Downscaling of climate indicators to 10x10 m resolution
Authors: Lehner Fabian , Klisho Tatiana , Formayer Herbert
Published: July 2023

Climate impact research sometimes needs climatological input data at a much higher spatial resolution than that of typical meteorological data sets (e.g. reanalysis, regional climate models, gridded observational data sets). We contribute climate data to a large interdisciplinary project “FORSITE II”, where forest site classification maps are produced for three provinces of Austria under the influence of climate change. The climate data involves many climate indicators relevant for vegetation with a spatial resolution of 10x10 m, leading to about 400 million grid cells for the research domain. Complex climate indicators such as potential evapotranspiration calculated with the Penman-Monteith equation need temperature, wind speed, humidity, and radiation as input.
Most meteorological variables are highly correlated with elevation, especially on a regional scale. Thus, for the downscaling to 10 m, a local vertical gradient of the climate indicator is calculated. Combining the vertical gradient with the difference of the topography on the fine and coarse grid yields the climate indicator on the high-resolution grid with a clear imprint of the fine topography.
Radiation-based indicators require a more advanced approach: For realistic shading effects of the topography, a solar radiation model is used to calculate potential direct radiation on both the coarse and the 10x10 m topography on each day of the year. Indirect radiation is directly downscaled with the difference of the sky view factors between coarse and fine resolution. These two downscaling methods are then applied to actual daily indirect and direct radiation, which was provided on a 100x100 m grid by GeoSphere Austria.  
RoadSurf – Open-source library for predicting road conditions
Authors: Karsisto Virve
Published: July 2023

Ice and snow cause hazardous road conditions every winter, especially in northern countries. Accurate road surface temperature and road condition forecasts are essential for road maintenance personnel to keep the roads safe for driving. With accurate forecasts, the roads can be salted before the freezing occurs and thus the roads can be kept free of ice. Finnish Meteorological Institute has used its road weather model called RoadSurf for over two decades to predict road conditions. RoadSurf is one dimensional model and calculates the heat transfer in the road and the heat balance at the road surface. The model requires atmospheric values, like air temperature, wind speed and radiation as input values and calculates the road surface temperature and amounts of ice, snow, frost, and water on the road. Shadowing caused by the surrounding objects can have a large effect on the road surface temperature. If sky view factor and local horizon angles are known at the to forecast location, the model will use those to modify the radiation input. Soon other institutes and companies can also use RoadSurf, as the main parts of the model will be published as an open-source Fortran library. The library will not include all the model features like friction calculation, but it is programmed so that implementing one’s own features is easy. When the model is implemented to new locations, some model parameters might need calibration to better fit the local road structure. The model is light to run and can be run in parallel mode, so the forecasts can be made easily to thousands of road points. The quality of the forecasts made by RoadSurf has been assessed previously in many verification studies, and new studies will be made to ensure that the new open-source library performs well.
Inter-comparison and validation of high-resolution surface air temperature reanalysis fields over Italy
Authors: Cavalleri Francesco , Viterbo Francesca , Brunetti Michele , Bonanno Riccardo , Manara Veronica , Lussana Cristian , Maugeri Maurizio
Published: July 2023

Since its release in 2019 by ECMWF, ERA5 has represented the state-of-the-art for global reanalysis, also providing initial and boundary conditions for many regional reanalysis products. These latter have been developed using parametrizations optimized for specific locations and observations not used in ERA5, to resolve physical processes which occur at smaller scales and thus better describe the atmospheric variables at finer resolutions than the 31 km of ECMWF global reanalysis. In this study, we investigate the capability of different reanalysis products to reproduce the characteristic atmospheric processes of the Italian peninsula. For example, a dynamical downscaling of ERA5 to higher resolutions can be an asset in studying the occurrence of extreme events, where the small scales play an important role, because of the Italian complex orography and coastal-sea interactions. For these reasons, inter-comparison and validation of different reanalysis products over Italy are carried on in this study, comparing the ERA5, ERA5-Land (9 km resolution), the MEteorological Reanalysis Italian Dataset (MERIDA, 7 km), the Copernicus European Regional ReAnalysis (CERRA, 5.5 km) and the Very High-Resolution dynamical downscaling of ERA5 REAnalysis over ITaly (VHR-REA_IT, 2.2 km). 
In particular, this work focuses on the evaluation of the 1991-2020 monthly climatology of surface air temperature over the Italian territory for each reanalysis product. The climatologies obtained from the different reanalyses at their native resolution are compared with the climatology obtained from a high-density station observational network. These observations were gridded for each reanalysis over its native grid, using a methodology that specifically accounts for elevation adjustments given the elevation differences between reanalysis grid points and station locations.
The results show that ERA5 underestimates temperature over most of the Italian territory. The bias is around -1 °C on average, with peaks of -3 °C over the Alps, and a positive temperature bias of around +0.5 °C over the Po valley. ERA5-Land, MERIDA, and CERRA reflect a similar cold bias distribution over the Italian region, even if some differences in the pattern distribution can be found, with local cold bias intensification in some areas. VHR-REA_IT, on the contrary, presents a warm summer bias of about +3 °C on average over the Po valley. In addition to that, ERA5 exhibits a negative bias over the Alpine region which increases with elevation in winter. A similar gradient is also found in the other higher resolution reanalyses (ERA5-Land, MERIDA, and CERRA), with the only exception of VHR-REA_IT which, conversely, shows a positive bias increase with decreasing elevation in summer.
Modeling the warming effectiveness of wind machines operation in fruit orchards
Authors: Dai Yi , Boekee Judith , van Hooft Antoon , ten Veldhuis Marie-Claire , van de Wiel Bas
Published: July 2023

Spring frost events can cause significant economic losses in the agricultural sector. Wind machines have become increasingly popular for mitigating frost damage. During radiative frost nights, wind machines generate strong jets to erode the near-surface thermal inversion through air mixing. This process accelerates both vertical air-air and local plant-air heat exchange, which causes the plants to warm up. However, previous studies have been limited in scope, either focusing on the warming effectiveness of inversion erosion (air-air) or local plant-air heat exchange at specific measurement points. The dynamic interaction between the warm air jet and canopy layer, as well as the heterogeneous plant-air heat exchange over the orchard, are not yet fully understood.
 
To this end, we introduce a multilayer canopy model (Patton et al., 2016) and a wind machine model (Heusinkveld et al., 2020) in a large-eddy simulation (LES). The wind machine model incorporates a momentum source with an idealized actuator disk. The coupled canopy model parametrizes canopy-induced drag, turbulence dissipation, and plant-air heat exchange (Boekee et al., 2023). This coupled model allows evaluation of the wind machine effectiveness in enhancing plant tissue temperature. We evaluate model performance with two observational cases in different seasons (leafless and full leave periods). Temperature data were obtained using a grid of fiber optic cables with a resolution of 25 cm along the cable over 6.75 ha. The preliminary results indicate that the coupled model is capable to simulate both plant-air heat exchange and in-canopy temperature dynamics. Finally, as to guide optimal frost mitigation, we conducted a sensitivity analysis for various machine operation scenarios in different seasons. This will guide wind machine operation and reduce fruit frost damage.
 
Are seasonal soil moisture forecasts a reliable source for agricultural drought predictions in Germany?
Authors: Leppelt Thomas , Wehring Sabrina , Paxian Andreas , Fröhlich Kristina
Published: July 2023

Increasing summer drought periods in Central Europe represent a serious threat for rain-fed agriculture. Recent drought events in 2018, 2019, 2020 and 2022 cause yield loss in Germany for wheat, corn, sugar beet and grassland production. In the future, climate projections show further increase of drought periods due to climate change. Hence, the requirement of long-range drought forecasts, which could provide useful predictions for agricultural applications over several month rises. Seasonal forecasts could offer guidance for medium-term management adjustments like irrigation planning or reduced fertilizer usage in case of expected severe drought periods. Unfortunately, long range precipitation forecasts often exhibit lower prediction skill. Here we assess another relevant parameter for drought prediction, the soil moisture, for its long range predictability.  Due to the small variability and persistence of soil moisture values, it is proposed, that this storage variable is well suited for climate services like agricultural drought predicting systems on seasonal time scales. We present a coupled modelling attempt, that combines seasonal forecasts from the German Climate Forecast System (GSFS) with the soil-vegetation-atmosphere-transfer (SVAT) impact model AMBAV to simulate the soil moisture for topsoil layers on a down scaled 5x5 km grid in Germany. A quality assessment of forecast ensemble means has been done with the corresponding hindcasts for the preceding 30 years. We used the mean squared error skill score (MSESS) of monthly averages to compare soil moisture forecasts in the upper 60 cm against long term reference climatology and other parameters, like precipitation. The results of this study reveal an adequate forecast skill over lead times up to several months. This shows the potential of seasonal soil moisture forecasts for agricultural applications, like fertilization advisement and drought prediction. Overall, the impact modelling system might contribute to the adaptation of agriculture to climate change in Germany.