Investigation of Climate Change Anomaly by Using Nonparametric Test for Navsari District of South Gujarat

Navsari district of rainfall was shows highest increasing rainfall trend obtained September and negative January, July, October, November and December. The regression slope of the yearly time series is about 12.35 mm/36 years. Maximum temperature shows the highest increasing trend in month October, followed by December and August. The month highest decreasing trend was noticed that January, followed by February and July. The regression slope of the yearly time series is about 0.025°C/36 years. Minimum temperature highest values of the slope (0.109°C/36 year) with high value of regression Slope of determination (0.111°C), the annual Kendall’s tau statistic (0.492°C/36 year), the Kendall Score (310). All the month January to December shows increasing trend. The highest increasing trend found that November, followed by March and July, respectively. This finding shows that all the month shows increasing trend with the range between 0.308°C to 0.390°C. In case of RH-I the highest increasing trend shows September, followed by April and June. Similarly decreasing trend was found that January, followed by February and October, respectively. Relative humidity-II increasing trend was found only at the September month 0.084%, the increasing trend was detected in January to August and October to December, respectively. The strongest trend in the Bright sunshine hour’s decline of all month’s average daily sunshine hours was for the Navsari district. No significant trends were detected in all months and seasons for all weather elements. A similar trend was found in Sen’s slope and regression slope all the months for all the weather elements.

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TREND OF TEMPERATURE AND RELATIVE HUMIDITY IN EAST SIANG DISTRICT OF ARUNACHAL PRADESH, INDIA

PLANT ARCHIVES ◽

10.51470/plantarchives.2021.v21.no2.137 ◽

2021 ◽

Vol 21 (2) ◽

Author(s):

Avicha Tangjang ◽

Amod Sharma

Keyword(s):

Climate Change ◽

Relative Humidity ◽

Secondary Data ◽

Maximum Temperature ◽

Arunachal Pradesh ◽

Temperature Study ◽

Monthly Temperature ◽

Time Period ◽

Increasing Trend ◽

Official Data

A study was conducted in the East Siang District of Arunachal Pradesh for the time period from 2000 to 2018 in order to study the temperature and relative humidity parameters of climate change in the study area. The study was based on secondary data collected from the regional meteorological centre wherein official data was collected for the years 2000 to 2018 for temperature and 2006 to 2018 for relative humidity. It was observed that maximum temperature in the study area exhibited an increasing trend during the study period. A monthly temperature study also showed that maximum temperature for the study area exhibited a significant increase during the months of February, July and August. The average annual Relative Humidity for East Siang during 2006-2018 was found to be 76.72 and 77.04 at 0830 hrs and 1730 hrs IST respectively. The monthly study of the Relative Humidity showed significant increase for the evening hours of 1730 hours IST during the months of April, and a significant decreasing trend for the months of September and October

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NDVI dynamics as reflected in climatic variables: spatial and temporal trends – a case study of Hungary

GIScience & Remote Sensing ◽

10.1080/15481603.2018.1560686 ◽

2019 ◽

Vol 56 (4) ◽

pp. 624-644 ◽

Cited By ~ 10

Author(s):

Szabó ◽

Elemér ◽

Kovács ◽

Püspöki ◽

Kertész ◽

...

Keyword(s):

Climate Change ◽

Time Series ◽

Local Level ◽

Temporal Trends ◽

Maximum Temperature ◽

Time Range ◽

Climatic Data ◽

Spatial Pattern Analysis ◽

Short Period ◽

Temporal Variance

Understanding climate change and revealing its future paths on a local level is a great challenge for the future. Beside the expanding sets of available climatic data, satellite images provide a valuable source of information. In our study we aimed to reveal whether satellite data are an appropriate way to identify global trends, given their shorter available time range. We used the CARPATCLIM (CC) database (1961–2010) and the MODIS NDVI images (2000–2016) and evaluated the time period covered by both (2000–2010). We performed a regression analysis between the NDVI and CC variables, and a time series analysis for the 1961–2008 and 2000–2008 periods at all data points. The results justified the belief that maximum temperature (TMAX), potential evapotranspiration and aridity all have a strong correlation with the NDVI; furthermore, the short period trend of TMAX can be described with a functional connection with its long period trend. Consequently, TMAX is an appropriate tool as an explanatory variable for NDVI spatial and temporal variance. Spatial pattern analysis revealed that with regression coefficients, macro-regions reflected topography (plains, hills and mountains), while in the case of time series regression slopes, it justified a decreasing trend from western areas (Transdanubia) to eastern ones (The Great Hungarian Plain). This is an important consideration for future agricultural and land use planning; i.e. that western areas have to allow for greater effects of climate change.

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Assessment of climate change impacts on irrigation water requirement and rice yield for Ngamoeyeik Irrigation Project in Myanmar

Journal of Water and Climate Change ◽

10.2166/wcc.2014.114 ◽

2014 ◽

Vol 5 (3) ◽

pp. 427-442 ◽

Cited By ~ 12

Author(s):

S. Shrestha ◽

N. M. M. Thin ◽

P. Deb

Keyword(s):

Climate Change ◽

Irrigation Water ◽

General Circulation ◽

Water Requirement ◽

Maximum Temperature ◽

Climate Projections ◽

Irrigation Water Requirement ◽

Irrigation Project ◽

Aquacrop Model ◽

Increasing Trend

This study analyzes the impacts of climate change on irrigation water requirement (IWR) and yield for rainfed rice and irrigated paddy, respectively, at Ngamoeyeik Irrigation Project in Myanmar. Climate projections from two General Circulation Models, namely ECHAM5 and HadCM3 were derived for the 2020s, 2050s, and 2080s. The climate variables were downscaled to basin level by using the Statistical DownScaling Model. The AquaCrop model was used to simulate the yield and IWR under future climate. The analysis shows a decreasing trend in maximum temperature for three scenarios and three time windows considered; however, an increasing trend is observed for minimum temperature for all cases. The analysis on precipitation also suggests that rainfall in wet season is expected to vary largely from −29 to +21.9% relative to the baseline period. A higher variation is observed for the rainfall in dry season ranging from −42% for 2080s, and +96% in the case of 2020s. A decreasing trend of IWR is observed for irrigated paddy under the three scenarios indicating that small irrigation schemes are suitable to meet the requirements. An increasing trend in the yield of rainfed paddy was estimated under climate change demonstrating increased food security in the region.

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An Analysis of Land Surface Temperature Trends in the Central Himalayan Region Based on MODIS Products

Remote Sensing ◽

10.3390/rs11080900 ◽

2019 ◽

Vol 11 (8) ◽

pp. 900 ◽

Cited By ~ 8

Author(s):

Wei Zhao ◽

Juelin He ◽

Yanhong Wu ◽

Donghong Xiong ◽

Fengping Wen ◽

...

Keyword(s):

Climate Change ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Thermal Environment ◽

Himalayan Region ◽

Maximum Temperature ◽

Temperature Cycle ◽

Increasing Trend ◽

Nighttime Temperatures

The scientific community has widely reported the impacts of climate change on the Central Himalaya. To qualify and quantify these effects, long-term land surface temperature observations in both the daytime and nighttime, acquired by the Moderate Resolution Imaging Spectroradiometer from 2000 to 2017, were used in this study to investigate the spatiotemporal variations and their changing mechanism. Two periodic parameters, the mean annual surface temperature (MAST) and the annual maximum temperature (MAXT), were derived based on an annual temperature cycle model to reduce the influences from the cloud cover and were used to analyze their trend during the period. The general thermal environment represented by the average MAST indicated a significant spatial distribution pattern along with the elevation gradient. Behind the clear differences in the daytime and nighttime temperatures at different physiographical regions, the trend test conducted with the Mann-Kendall (MK) method showed that most of the areas with significant changes showed an increasing trend, and the nighttime temperatures exhibited a more significant increasing trend than the daytime temperatures, for both the MAST and MAXT, according to the changing areas. The nighttime changing areas were more widely distributed (more than 28%) than the daytime changing areas (around 10%). The average change rates of the MAST and MAXT in the daytime are 0.102 °C/yr and 0.190 °C/yr, and they are generally faster than those in the nighttime (0.048 °C/yr and 0.091 °C/yr, respectively). The driving force analysis suggested that urban expansion, shifts in the courses of lowland rivers, and the retreat of both the snow and glacier cover presented strong effects on the local thermal environment, in addition to the climatic warming effect. Moreover, the strong topographic gradient greatly influenced the change rate and evidenced a significant elevation-dependent warming effect, especially for the nighttime LST. Generally, this study suggested that the nighttime temperature was more sensitive to climate change than the daytime temperature, and this general warming trend clearly observed in the central Himalayan region could have important influences on local geophysical, hydrological, and ecological processes.

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Assessment of the future climate potential for tourism over Europe using a combination of downscaling approaches and quantitative impact models

10.5194/egusphere-egu2020-5037 ◽

2020 ◽

Author(s):

Maria Francisca Cardell ◽

Arnau Amengual ◽

Romualdo Romero

Keyword(s):

Climate Change ◽

Wind Speed ◽

Relative Humidity ◽

Future Climate ◽

Cumulative Distribution ◽

Maximum Temperature ◽

Model Errors ◽

Present Climate ◽

Ensemble Strategy ◽

The Future

Europe and particularly, the Mediterranean countries, are among the most visited tourist destinations worldwide, while it is also recognized as one of the most sensitive regions to climate change. Climate is a key resource and even a limiting factor for many types of tourism. Owing to climate change, modified patterns of atmospheric variables such as temperature, rainfall, relative humidity, hours of sunshine and wind speed will likely affect the suitability of the European destinations for certain outdoor leisure activities.Perspectives on the future of second-generation climate indices for tourism (CIT) that depend on thermal, aesthetic and physical facets are derived using model projected daily atmospheric data and present climate &#8220;observations&#8221;. Specifically, daily series of 2-m maximum temperature, accumulated precipitation, 2-m relative humidity, mean cloud cover and 10-m wind speed from ERA-5 reanalysis are used to derive the present climate potential. For projections, the same daily variables have been obtained from a set of regional climate models (RCMs) included in the European CORDEX project, considering the rcp8.5 future emissions scenario. The adoption of a multi-model ensemble strategy allows quantifying the uncertainties arising from the model errors and the GCM-derived boundary conditions. To properly derive CITs at local scale, a quantile&#8211;quantile adjustment has been applied to the simulated regional scenarios. The method detects changes in the continuous CIT cumulative distribution functions (CDFs) between the recent past and successive time slices of the simulated climate and applies these changes, once calibrated, to the observed CDFs.&#160;Assessments on the future climate potential for several types of tourist activities in Europe (i.e., sun, sea and sand (3S) tourism, cycling, cultural, football, golf, nautical and hiking) will be presented by applying suitable quantitative indicators of CIT evolutions adapted to regional contexts. It is expected that such kind of information will ultimately benefit the design of mitigation and adaptation strategies of the tourist sector.

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Relationship between heating/cooling period and changing temperature conditions in the urban areas of Hungary

10.5194/egusphere-egu2020-783 ◽

2020 ◽

Author(s):

Csenge Dian ◽

Attila Talamon ◽

Rita Pongrácz ◽

Judit Bartholy

Keyword(s):

Climate Change ◽

Time Series ◽

Energy Consumption ◽

Extreme Values ◽

Building Design ◽

Temperature Time Series ◽

Maximum Temperature ◽

Design Parameters ◽

Daily Average ◽

Temperature Time

Climate change, extreme weather conditions, and local scale urban heat island (UHI) effect altogether have substantial impacts on people&#8217;s health and comfort. The urban population spends most of its time in buildings, therefore, it is important to examine the relationship between weather/climate conditions and indoor environment. The role of buildings is complex in this context. On the one hand UHI effect is mostly created by buildings and artificial surfaces. On the other hand they account for about 40% of energy consumption on European average. Since environmental protection requires increased energy efficiency, the ultimate goal from this perspective is to achieve nearly zero-energy buildings. When estimating energy consumption, daily average temperatures are taken into account. The design parameters (e.g. for heating systems) are determined using temperature-based criteria. However, due to climate change, these critical values are likely to change as well. Therefore, it is important to examine the temperature time series affecting the energy consumption of buildings. For the analysis focusing on the Carpathian region within central/eastern Europe, we used the daily average, minimum and maximum temperature time series of five Hungarian cities (i.e. Budapest, Debrecen, Szeged, P&#233;cs and Szombathely). The main aim of this study is to investigate the effect of changing daily average temperatures and the rising extreme values on building design parameters, especially heating and cooling periods (including the length and average temperatures of such periods).

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Climate Change Impact in Flores Island, a Dry Region in Indonesia

Civil Engineering Dimension ◽

10.9744/ced.23.1.20-27 ◽

2021 ◽

Vol 23 (1) ◽

pp. 20-27

Author(s):

Cilcia Kusumastuti ◽

Dicky Gode ◽

Yobella Febe Kurnianto ◽

Frederik Jones Syaranamual

Keyword(s):

Climate Change ◽

Climate Change Impacts ◽

Annual Rainfall ◽

Rainfall Trend ◽

Simple Linear Regression ◽

Adaptation Measures ◽

Pattern Change ◽

Increasing Trend ◽

Change Impact ◽

Potential Climate Change

Climate change impacts have gained great attention to be studied in various fields. In this paper, an investigation of rainfall pattern change is performed using three statistical methods, i.e., simple linear regression, t-test, and Mann-Kendall’s test. The analysis is performed at 10- and 20-year time scales of daily, monthly, and annual rainfall in Flores Island, a dry region in Indonesia. In general, an increasing monthly rainfall trend is detected in the rainy season (October – April) at a 20-year period, using all three methods. Specifically, a significant increasing trend in March 1989 – 2008 is observed, and it contributes to the significant increasing trend of annual rainfall. The findings presented in this paper should be an alert for potential climate change impacts in the region. The positive consideration of having more rainfall in a dry region might turn into a negative reality when adaptation measures are not well-prepared.

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Classificação e Análises das Indicações de Mudanças Climáticas no Município de Sobral - Ceará (Classification and Analysis of Indications of Climate Change in the City of Sobral – Ceará)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v4i5.232758 ◽

2012 ◽

Vol 4 (5) ◽

pp. 1056

Author(s):

Raimundo Mainar Medeiros ◽

Paulo Roberto Megna Francisco ◽

Alexandra Lima Tavares

Keyword(s):

Climate Change ◽

Relative Humidity ◽

Water Balance ◽

Potential Evapotranspiration ◽

Temperature Fluctuations ◽

Maximum Temperature ◽

Temperature Variations ◽

Meteorological Elements ◽

The City

A partir das séries climatológicas normais de 1931-1960 e 1961-1990 dos elementos meteorológicos realizaram-se os cálculos do balanço hídrico climatológico, a classificação e as análises das indicações de mudanças climáticas no município de Sobral, estado do Ceará, utilizando O programa do BHnorm elaborado em planilhas eletrônicas no pacote Excel por Sentelhas et al. (1999) e a metodologia de cálculo do Balanço Hídrico Climático de Thornthwaite & Mather (1955) e a classificação de Thornthwaite (1955), com o objetivo de contribuir para a sustentabilidade do homem no campo. Identificou-se que o clima da área de estudo classifica-se como Megatérmico semiárido e o tipo climático passou do tipo dw2w2d’ para dw2Dd’ com reduções da temperatura mínima e com oscilações de -0,1 a -0,8ºC e temperatura máxima com variações de -1,7 à 2,1ºC. A umidade relativa do ar ocorreu flutuações positivas de 0,3 à 3,4%. A evapotranspiração potencial oscilou em -71,0 mm em relação aos períodos para o mês de outubro. Os índices de umidade; aridez e hídricos demonstraram valores de 28,6%, -23,9% e -47,5%, respectivamente. Observou-se que todas estas variabilidades ocorreram devido aos efeitos causados pelo homem na estrutura da cidade. Palavras-chave: Meteorologia. Balanço Hídrico Climático. Clima. Classification and Analysis of Indications of Climate Change in the City of Sobral – Ceará ABSTRACTFrom the series 1931-1960 climatological normal from 1961-1990 and meteorological elements were carried out calculations of the climatic water balance, classification and analysis of the indications of climate change in the city of Sobral, Ceará State, using the program BHnorm prepared in Excel spreadsheets in the package by Sentelhas et al. (1999) and the methodology of calculation of the Climatic Water Balance of Thornthwaite & Mather (1955) and the classification of Thornthwaite (1955), in order to contribute to the sustainability of the man in the field. It was found that the climate of the study area is classified as megathermal semiarid climate and the type has type dw2w2d 'to dw2Dd' with reductions in the minimum temperature fluctuations and from -0.1 to -0.8 º C and maximum temperature variations with 2.1 to -1.7 ° C. The relative humidity was positive fluctuations of 0.3 to 3.4%. The potential evapotranspiration fluctuated -71.0 mm for the periods for the month of October. The contents of moisture, drought and water showed values of 28.6% -23.9% and -47.5%, respectively. It was observed that all these effects occurred due to variability caused by man in the structure of the city. Keywords: Meteorology. Climatic Water Balance. Climate.

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Long term monthly and inter-seasonal weather variability analysis for the lower Shivalik foothills of Punjab

MAUSAM ◽

10.54302/mausam.v73i1.5090 ◽

2022 ◽

Vol 73 (1) ◽

pp. 173-180

Author(s):

NAVNEET KAUR ◽

M.J. SINGH ◽

SUKHJEET KAUR

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Minimum Temperature ◽

Maximum Temperature ◽

Linear Regression Method ◽

Post Monsoon ◽

Sunshine Hours ◽

Annual Minimum Temperature ◽

Weather Parameters

This paper aims to study the long-term trends in different weather parameters, i.e., temperature, rainfall, rainy days, sunshine hours, evaporation, relative humidity and temperature over Lower Shivalik foothills of Punjab. The daily weather data of about 35 years from agrometeorological observatory of Regional Research Station Ballowal Saunkhri representing Lower Shivalik foothills had been used for trend analysis for kharif (May - October), rabi (November - April), winter (January - February), pre-monsoon (March - May), monsoon (June - September) and post monsoon (October - December) season. The linear regression method has been used to estimate the magnitude of change per year and its coefficient of determination, whose statistical significance was checked by the F test. The annual maximum temperature, morning and evening relative humidity has increased whereas rainfall, evaporation sunshine hours and wind speed has decreased significantly at this region. No significant change in annual minimum temperature and diurnal range has been observed. Monthly maximum temperature revealed significant increase except January, June and December, whereas, monthly minimum temperature increased significantly for February, March and October and decreased for June. Among different seasons, maximum temperature increased significantly for all seasons except winter season, whereas, minimum temperature increased significantly for kharif and post monsoon season only. The evaporation, sunshine hours and wind speed have also decreased and relative humidity decreased significantly at this region. Significant reduction in kharif, monsoon and post monsoon rainfall has been observed at Lower Shivalik foothills. As the region lacks assured irrigation facilities so decreasing rainfall and change in the other weather parameters will have profound effects on the agriculture in this region so there is need to develop climate resilient agricultural technologies.

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Time series analysis of observed maximum and minimum air temperature at four urban cities of India during 1951-2015

MAUSAM ◽

10.54302/mausam.v71i1.6 ◽

2021 ◽

Vol 71 (1) ◽

pp. 57-68

Author(s):

PRAMANIK SAIKAT ◽

SIL SOURAV ◽

MANDAL SAMIRAN

Keyword(s):

Time Series ◽

Power Spectrum ◽

Air Temperature ◽

India Meteorological Department ◽

Wavelet Power Spectrum ◽

Maximum Temperature ◽

Coastal Cities ◽

Increasing Trend ◽

Two Peaks ◽

Minimum Air Temperature

A sixty - five year (1951-2015) long data for monthly minimum temperature (TMIN) and maximum temperature (TMAX), observed by the India Meteorological Department (IMD), is statistically analyzed at four urban stations namely Bhubaneswar, Delhi, Mumbai and Chennai of India. A bimodal nature in seasonality is noticed for TMAX and TMIN at all locations. Two peaks for TMAX and TMIN are observed in May and September. Exceptionally, Mumbai shows TMAX peaks during May and November and Delhi shows TMIN peaks during June and September. Higher standard deviations (SD) for TMAX is noted at Delhi with a maximum in March (1.78 °C), while for Chennai, the SD for TMIN is lesser compared to other cities. Two different periods 1951-1980 (P1, the first half of the study period) and 1981-2015 (P2, the second half of the study period) were identified from the time series of both TMAX and TMIN. A higher increasing trend is observed during P2 than P1 in all the cities except in TMIN at Mumbai. The highest increasing trend (0.040 °C/year) is observed for TMIN in Mumbai during P1 time, but the trend is almost constant (0.001 °C/year) during P2 time. The highest increasing trend for TMIN at Mumbai is mainly contributed by the increasing trend in post-monsoon and winter months in P1. Surprisingly, in both P1 and P2, the trends are less during monsoon months for all the cities. A consistent 5-year (3-year) band is observed throughout the wavelet power spectrum at the coastal cities Bhubaneswar, Mumbai (Chennai). However, the 5-year signal is not consistent at Delhi and it is observed only during the year 1975-1980. The global wavelet power spectrum showed that TMIN at Chennai has less power (0.6 °C2) corresponding to 3-year signal and Mumbai has highest power (12 °C2) corresponding to the 5-year signal in comparison to other cities.

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