Influence of some climatic factors on tourism activities on Co To Island, Vietnam

Co To is a small Island that is a well-known tourist destination for Vietnamese people and it is known to have a very special climate for each season of the year. The purpose of this study is to discuss the limitations of climatic factors as well as find out a favorable time for tourism activities on Co To Island, Vietnam. One of the important things to choose Co To Island to become the main subject is because it has a very special geographic location and tourism is one of the most important drivers of economic development on Co To Island. However, in addition to social reasons, Co To Island tourism is also influenced by climatic factors. Each climate factor has different effects, but the assessment shows that temperature, humidity, and precipitation have the strongest influence. The results also show that in the summer (May-September) on Co To Island, the most frequent and dangerous weather conditions for humans are related to hot weather as well as heavy rainstorms. Mainly in winter (December, January, February), outdoor tourism activities are limited by the cold climate and changing northeast monsoon. However, March, April, October, and November have very favorable tourist conditions.

The Effects of Some Climate Factors upon Frequency Distribution of Local Sandflies Breed in Misan Province, Iraq

The genus Phlebotomus is naturally responsible for the transmission of many protozoal parasites like Leishmania. The study was conducted to determine the effect of some climate factors on sandflies distribution over a year from December 2019 to November 2020. A total of 268 sandflies of both sexes were collected from different areas in Misan province, Iraq. Sandflies were collected using light traps and stick oil paper, then placed in cups or Petri dishes containing sterile normal saline for examination. The current study showed an inverse relationship between the presence and number of sandflies with temperatures. Rainfall had a significant impact on parasite distribution, while wind speed had a potential impact on sandfly activity. The percentage of female sandflies was significantly (P<0.05) higher than that of males (54.85% for females versus 45.15% for males). In conclusion, heavy precipitation is the main climate factor that affects the frequency distribution of local breed sandflies followed by rising temperature degrees that are seen in the summer season. The climate can affect the activity, spreading, and distribution of sandflies with detected one peak of their activity in December.

CORRELATION BETWEEN CLIMATE FACTORS WITH DENGUE HEMORRHAGIC FEVER CASES IN SURABAYA 2007 – 2017

Dengue Hemorrhagic Fever (DHF) is a disease caused by dengue virus. DHF is mediated by the mosquito vector, the Aedes mosquito. The proliferation of dengue vector is influenced by many factors, one of which is climate factors. DHF is one of the main public health problems in Indonesia. Cases of dengue were first discovered in 1968 in the city of Jakarta and Surabaya. Currently Surabaya is one of the dengue endemic areas in Indonesia. . The case of DHF in the city of Surabaya can be said to be still quite high compared with another city in Indonesia, although there is a decrease in the number from year to year. When examined, many factors influence the high number of dengue cases in Surabaya, one of which is climate factor. Climate factors play a role in the proliferation of DHF vectors. Therefore, this study aims to examine for 10 years, namely in 2007 - 2017 whether there is a correlation between climate factors with dengue cases in the city of Surabaya., which in this study the climate factors used are rainfall, average temperature, and average air humidity. This research uses an analytical method namely Spearman on the SPSS software version 20. The results obtained that the case of DHF in the city of Surabaya has no relationship with climatic factors such as rainfall and average temperature with a significance value of the relationship p> 0.05. While the climate factor that has a relationship with DHF cases in Surabaya City is air humidity with a significance value of p <0.05 and has a positive relationship with the value of r = + 0.190. It can be concluded that not all climate factors have a relationship with the DHF case in Surabaya in 2007 - 2017, which has a relationship with the DHF case is air humidity.

Identifying robust bias adjustment methods for European extreme precipitation in a multi-model pseudo-reality setting

Severe precipitation events occur rarely and are often localised in space and of short duration, but they are important for societal managing of infrastructure. Therefore, there is a demand for estimating future changes in the statistics of the occurrence of these rare events. These are often projected using data from regional climate model (RCM) simulations combined with extreme value analysis to obtain selected return levels of precipitation intensity. However, due to imperfections in the formulation of the physical parameterisations in the RCMs, the simulated present-day climate usually has biases relative to observations; these biases can be in the mean and/or in the higher moments. Therefore, the RCM results are adjusted to account for these deficiencies. However, this does not guarantee that the adjusted projected results will match the future reality better, since the bias may not be stationary in a changing climate. In the present work, we evaluate different adjustment techniques in a changing climate. This is done in an inter-model cross-validation set-up in which each model simulation, in turn, performs pseudo-observations against which the remaining model simulations are adjusted and validated. The study uses hourly data from historical and RCP8.5 scenario runs from 19 model simulations from the EURO-CORDEX ensemble at a 0.11∘ resolution. Fields of return levels for selected return periods are calculated for hourly and daily timescales based on 25-year-long time slices representing the present-day (1981–2005) and end-21st-century (2075–2099). The adjustment techniques applied to the return levels are based on extreme value analysis and include climate factor and quantile-mapping approaches. Generally, we find that future return levels can be improved by adjustment, compared to obtaining them from raw scenario model data. The performance of the different methods depends on the timescale considered. On hourly timescales, the climate factor approach performs better than the quantile-mapping approaches. On daily timescales, the superior approach is to simply deduce future return levels from pseudo-observations, and the second-best choice is using the quantile-mapping approaches. These results are found in all European subregions considered. Applying the inter-model cross-validation against model ensemble medians instead of individual models does not change the overall conclusions much.

DEVELOPMENT OF AN APPROACH TO DETERMINATION OF COUPLING QUALITIES OF ROAD COVERING USING WEATHER-CLIMATE FACTOR

Assessing the grip of the road surface is an extremely important task both in the field of traffic management, and in the field of investigation and examination of traffic accidents. The coupling quality of the road surface is fully ensured by the grip coefficient, which is subject to constant monitoring in order to ensure road safety. There are a large number of methods for determining the magnitude of the grip coefficient. In their study, the authors propose an improved approach for determining the investigated value using the weather and climate factor. Previously, a group of researchers in the course of scientific research determined the dependence of the grip coefficient on the temperature of the road surface, as a result of mathematical analysis, the authors obtained a dependence that allows to determine the studied value by air temperature and the condition of the road surface (presence of precipitation). The performed experiment allowed us to test the obtained dependence within the framework of the object of study and to make a comparative assessment of the results obtained with the data obtained using the road laboratory.

Asymmetry of Daytime and Nighttime Warming in Typical Climatic Zones along the Eastern Coast of China and Its Influence on Vegetation Activities

In this dissertation, the author adopted the normalized difference vegetation index (NDVI) and meteorological data from 1982 to 2016 of the typical climate zones in coastal areas of China to analyze the influence of daytime and nighttime warming asymmetric changes in different seasons on vegetation activities during the growing season period according to the copula function theory optimized based on Markov chain Monte Carlo (MCMC). The main conclusions are as follows: (1) The seasonal daytime and nighttime warming trends of Guangdong, Jiangsu and Liaoning over the past 35 years were significant, and the daytime and nighttime warming rates were asymmetric. In spring and summer of Guangdong province, the warming rate in the daytime was higher than that at night, while, in autumn, the opposite law was observed. However, the warming rate in the daytime was lower than that at night in Jiangsu and Liaoning provinces. There were latitude differences in diurnal and nocturnal warming rate. (2) The daytime and nighttime warming influences on vegetation showed significant seasonal differences in these three regions. In Guangdong, the influence of nighttime warming on vegetation growth in spring is greater than that in summer, and the influences of daytime warming on vegetation growth from strong to weak were spring, summer and autumn. In Jiangsu, both the influences of daytime and nighttime warming on vegetation growth in summer were less than that in autumn. In Liaoning, both the influences of daytime and nighttime warming on vegetation growth from strong to weak were autumn, spring and summer. (3) In Guangdong, Jiangsu and Liaoning provinces, their maximum temperature (Tmax) and minimum temperature (Tmin) and the joint probability distribution functions of NDVI, all had little effect on NDVI when Tmax and Tmin respectively reached their minimum values, but their influences on NDVI were obvious when Tmax and Tmin respectively reached their maximum values. (4) The smaller the return period, the larger the range of climate factor and NDVI, which has indicated that when the climate factor is certain, the NDVI is more likely to have a smaller return period, and the frequency of NDVI over a certain period is higher. In addition, the larger the climate factor, the greater the return period is and NDVI is less frequent over a certain period of time. This research can help with deep understanding of the dynamic influence of seasonal daytime and nighttime asymmetric warming on the vegetation in typical coastal temperature zones of China under the background of global climate change.