scholarly journals Assessment of Climate Variability for Coconut and Other Crops: A Statistical Approach

CORD ◽  
2008 ◽  
Vol 24 (1) ◽  
pp. 19
Author(s):  
T.S.G. Peiris
Keyword(s):  
Sri Lanka ◽  
Climate Variability ◽  
Air Temperature ◽  
Agricultural Sector ◽  
Maximum Temperature ◽  
Climate Data ◽  
Dry Spells ◽  
Rate Of Increase ◽  
Dry Spell ◽  
Maximum Air Temperature

Public opinion in Sri Lanka has been seriously concerned about the possible impact of climate change on different sectors, and in particular for the agricultural sector. Annual and weekly climate data were analyzed to provide useful information to farmers, planners and scientists to assess the suitability of different types of crops. The statistical methodology of the analysis is illustrated using daily rainfall and air temperature from 1951 to 2001 for Hambantota, a major coconut growing district in Sri Lanka. The increase in maximum air temperature and decrease in the amount of rainfall per effective rainy day (> 5mm) are the significant features of the climate variability in the Hambantota area. The warming rate for maximum air temperature was significantly higher (p<0.005) than that for minimum, mean and diurnal temperature, irrespective of time scales. The annual rate of increase of maximum temperature after 1995 is 0.0260C. The intensity of rainfall per effective rainy day (> 5mm) decreased significantly (p<0.005). Distribution of weekly rainfall during January to September is uncertain. The probability of weekly rainfall greater than 20 mm does not exceed 50% in any week during this period. Long-term weekly rainfall was greater than 30 mm only during mid October to early December, but the probability of weekly rainfall greater than 30 mm exceeds 50% only during the first three weeks of November. The probability of occurrence of dry spells of duration greater than 60 days in a year is around 70%, but the time of occurrence of such dry spell is not consistent among years. These findings suggest that the expected future climate would not be suitable for coconut cultivation, if growers do not apply the recommended practices to face long dry spells. Also the increasing temperature could impact to dominate plant pest during dry periods.

Effects of inter-annual climate variability on grape harvest timing in rainfed hilly vineyards of Piedmont (NW Italy)

2020 ◽  
Author(s):  
Danilo Rabino ◽  
Marcella Biddoccu ◽  
Giorgia Bagagiolo ◽  
Guido Nigrelli ◽  
Luca Mercalli ◽  
...  
Keyword(s):  
Climate Variability ◽  
Weather Data ◽  
Maximum Temperature ◽  
Data Series ◽  
Positive Trend ◽  
Climate Variables ◽  
Climate Data ◽  
Historical Series ◽  
Nw Italy ◽  
Level Of Significance

&lt;p&gt;Historical weather data represent an extremely precious resource for agro-meteorology for studying evolutionary dynamics and for predictive purposes, to address agronomical and management choices, that have economic, social and environmental effect. The study of climatic variability and its consequences starts from the observation of variations over time and the identification of the causes, on the basis of historical series of meteorological observations. The availability of long-lasting, complete and accurate datasets is a fundamental requirement to predict and react to climate variability. Inter-annual climate changes deeply affect grapevine productive cycle determining direct impact on the onset and duration of phenological stages and, ultimately, on the grape harvest and yield. Indeed, climate variables, such as air temperature and precipitation, affect evapotranspiration rates, plant water requirements, and also the vine physiology. In this respect, the observed increase in the number of warm days poses a threat to grape quality as it creates a situation of imbalance at maturity, with respect to sugar content, acidity and phenolic and aromatic ripeness.&lt;/p&gt;&lt;p&gt;A study was conducted to investigate the relationships between climate variables and harvest onset dates to assess the responses of grapevine under a global warming scenario. The study was carried out in the &amp;#8220;Monferrato&amp;#8221; area, a rainfed hillslope vine-growing area of NW Italy. In particular, the onset dates of harvest of different local wine grape varieties grown in the Vezzolano Experimental Farm (CNR-IMAMOTER) and in surrounding vineyards (affiliated to the Terre dei Santi Cellars) were recorded from 1962 to 2019 and then related to historical series of climate data by means of regression analysis. The linear regression was performed based on the averages of maximum and minimum daily temperatures and sum of precipitation (1962&amp;#8211;2019) calculated for growing and ripening season, together with a bioclimatic heat index for vineyards, the Huglin index. The climate data were obtained from two data series collected in the Experimental farm by a mechanical weather station (1962-2002) and a second series recorded (2002-2019) by an electro-mechanical station included in Piedmont Regional Agro-meteorological Network. Finally, a third long-term continuous series covering the period from 1962 to 2019, provided by Italian Meteorological Society was considered in the analysis.&lt;/p&gt;&lt;p&gt;The results of the study highlighted that inter-annual climate variability, with a general positive trend of temperature, significantly affects the ripening of grapes with a progressive anticipation of the harvest onset dates. In particular, all the considered variables excepted precipitation, resulted negatively correlated with the harvest onset date reaching a high level of significance (up to P&lt; 0.001). Best results have been obtained for maximum temperature and Huglin index, especially by using the most complete dataset. The change ratios obtained using datasets including last 15 years were greater (in absolute terms) than results limited to the period 1962-2002, and also correlations have greater level of significance. The results indicated clearly the relationships between the temperature trend and the gradual anticipation of harvest and the importance of having long and continuous historical weather data series available.&lt;/p&gt;

Soil temperatures in Egypt

1928 ◽  
Vol 18 (1) ◽  
pp. 90-122 ◽  
Author(s):  
E. McKenzie Taylor
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Soil Surface ◽  
Temperature Wave ◽  
Maximum Temperature ◽  
Straight Line ◽  
Temperature Waves ◽  
Soil Temperatures ◽  
The Times ◽  
Maximum Air Temperature

1. The soil temperatures in Egypt at a number of depths have been recorded by means of continuous recording thermometers. In general, the records show that the amplitude of the temperature wave at the surface of the soil is considerably greater than the air temperature wave. There is, however, a considerable damping of the wave with depth, no daily variation in temperature being observed at a depth of 100 cm.2. No definite relation between the air and soil temperatures could be traced. The maximum air temperature was recorded in May and the maximum soil temperature in July.3. The amplitude of the temperature wave decreases with increase in depth. The decrease in amplitude of the soil temperature wave is not regular owing to variations in the physical properties of the soil layers. Between any two depths, the ratio of the amplitudes of the temperature waves is constant throughout the year. The amplitude of the soil temperature wave bears no relation to the amplitude of the air temperature wave.4. The time of maximum temperature at the soil surface is constant throughout the year at 1 p.m. The times of maximum temperature at depths below the surface lag behind the time of surface maximum, but they are constant throughout the year. When plotted against depth, the times of maximum at the various soil depths lie on a straight line.

scholarly journals Trends of Changes of Maximum Air Temperature in Ukraine as an Impact Factor on Population Health

2020 ◽  
Keyword(s):  
Population Health ◽  
Air Temperature ◽  
Thermal Regime ◽  
Climate Changes ◽  
System Analysis ◽  
Global Climate ◽  
Maximum Temperature ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

Purpose. The aim of this research is detection of trends of changes (according to fact and scenario data) of extreme air temperature as a component of thermal regime in different regions of Ukraine because of global climate change. Methods. System analysis, statistical methods. Results. Time distribution of maximum air temperature regime characteristics based on results of observations on the stations located in different regions of Ukraine during certain available periods: Uzhgorod (1946-2018), Kharkiv (1936-2005), Оdessа (1894-2005), аnd also according to scenarios of low (RCP2.6), medium (RCP4.5) and high (RCP8.5) levels of greenhouse gases emissions. Meanwhile, air temperature ≥ 25°С was considered high (days with maximum temperature within 25,0-29,9°С are hot), ≥ 30°С was considered very high (days with such temperature are abnormaly hot). Trends of changes of extreme air temperatures were identified as a component of thermal regime in different regions of Ukraine within global climate changes. Dynamics of maximum air temperature and its characteristics in ХХ and beginning of ХХІ centuries were researched. Expected time changes of maximum air temperature and number of days with high temperature during 2021-2050 were analyzed by RCP2.6, RCP4.5 and RCP8.5 scenarios. There were identified the highest day air temperatures possible once in a century and also possibility of maximum day temperature more than 30°С by RCP4.5 scenario. Well-timed prediction of climate changes will help evaluate their impact on human and natural systems which will be useful for development and taking preventive measures towards minimization of negative influence of such changes. Conclusions. Processes of climate warming in Ukraine are activating. There was determined a strong trend on increasing of average maximum of air temperature in winter with speed 0.17-0,39 degrees centigrade/10 years. According to climatic norm this index mainly increased mostly (up to 3,3 degrees centigrade) in January in North-East of the country. In future such anomalies will grow. Determination of correlation between climate and health is the base for taking protective measures against perils for population health connected with climate.

scholarly journals Future Changes in Wet and Dry Season Characteristics in CMIP5 and CMIP6 simulations

2021 ◽  
Author(s):  
Caroline M. Wainwright ◽  
Emily Black ◽  
Richard P. Allan
Keyword(s):  
Climate Change ◽  
South America ◽  
West Africa ◽  
Southern Africa ◽  
Dry Season ◽  
Maximum Temperature ◽  
Wet Season ◽  
Dry Spells ◽  
Dry Spell ◽  
Spell Length

AbstractClimate change will result in more dry days and longer dry spells, however, the resulting impacts on crop growth depend on the timing of these longer dry spells in the annual cycle. Using an ensemble of Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6) simulations, and a range of emission scenarios, here we examine changes in wet and dry spell characteristics under future climate change across the extended tropics in wet and dry seasons separately. Delays in the wet seasons by up to two weeks are projected by 2070-2099 across South America, Southern Africa, West Africa and the Sahel. An increase in both mean and maximum dry spell length during the dry season is found across Central and South America, Southern Africa and Australia, with a reduction in dry season rainfall also found in these regions. Mean dry season dry spell lengths increase by 5-10 days over north-east South America and south-west Africa. However, changes in dry spell length during the wet season are much smaller across the tropics with limited model consensus. Mean dry season maximum temperature increases are found to be up to 3°C higher than mean wet season maximum temperature increases over South America, Southern Africa and parts of Asia. Longer dry spells, fewer wet days, and higher temperatures during the dry season may lead to increasing dry season aridity, and have detrimental consequences for perennial crops.

scholarly journals Forecasting of Air Maximum Temperature on Monthly Basis Using Singular Spectrum Analysis and Linear Autoregressive Model

2021 ◽  
Vol 877 (1) ◽  
pp. 012033
Author(s):  
Nabeel Saleem Saad Al-Bdairi ◽  
Salah L. Zubaidi ◽  
Hussein Al-Bugharbee ◽  
Khalid Hashim ◽  
Sabeeh L. Farhan ◽  
...  
Keyword(s):  
Air Temperature ◽  
Spectrum Analysis ◽  
Autoregressive Model ◽  
Fitness Function ◽  
Singular Spectrum Analysis ◽  
Maximum Temperature ◽  
Monthly Basis ◽  
Singular Spectrum ◽  
Prediction And Forecasting ◽  
Maximum Air Temperature

Abstract In this research, the singular spectrum analysis technique is combined with a linear autoregressive model for the purpose of prediction and forecasting of monthly maximum air temperature. The temperature time series is decomposed into three components and the trend component is subjected for modelling. The performance of modelling for both prediction and forecasting is evaluated via various model fitness function. The results show that the current method presents an excellent performance in expecting the maximum air temperature in future based on previous recordings.

scholarly journals Relationship between climate variability and radial growth of Pinus montezumae Lamb. in Coyuca de Catalán, Guerrero

2020 ◽  
Vol 27 (1) ◽  
pp. 109-126
Author(s):  
Otoniel Cortés-Cortés ◽  
◽  
Eladio H. Cornejo-Oviedo ◽  
Julián Cerano-Paredes ◽  
Rosalinda Cervantes-Martínez ◽  
...  
Keyword(s):  
Climate Variability ◽  
Response Function ◽  
Growth Rates ◽  
Function Analysis ◽  
Maximum Temperature ◽  
Climate Data ◽  
Statistical Parameters ◽  
Pinus Montezumae ◽  
Average Monthly Rainfall ◽  
Increment Borer

Introduction: Understanding the dendroclimatic potential of a species allows us to reconstruct the climate variability in the latitudes and altitudes of its distribution. Objective: To determine the potential of Pinus montezumae Lamb. to reconstruct climatic variables. Materials and methods: A total of 80 samples were extracted with a Pressler increment borer and dated, allowing growth rates to be generated. Average monthly rainfall and minimum and maximum temperature were obtained, and a response function analysis between growth rates and climate data was conducted. Results and discussion: Dated samples represented 75 % of the total. The COFECHA program indicated a correlation between series of r = 0.57 (P < 0.01) and a mean sensitivity of 0.31; P. montezumae is sufficiently sensitive to record climate variability. Three chronologies (standard, residual and arstan) covering 228 years (1790-2017) were generated for each of the three growth rates (total ring, early and latewood). The response function analysis showed that it is possible to reconstruct the spring rainfall and the May-July maximum temperature based on the total ring (r = 0.66; P < 0.01) and latewood (r = 0.35; P < 0.01) indices, respectively. Conclusion: Statistical parameters indicate that P. montezumae is an adequate proxy source for climate variability reconstruction studies.

Selecting the optimal fine-scale historical climate data for assessing current and future hydrological conditions

2022 ◽  
Keyword(s):  
Sierra Nevada ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Maximum Temperature ◽  
Climate Data ◽  
Ecological Processes ◽  
Historical Climate ◽  
Wide Range ◽  
Monthly Streamflow ◽  
Climate Maps

Abstract High-resolution historical climate grids are readily available and frequently used as inputs for a wide range of regional management and risk assessments including water supply, ecological processes, and as baseline for climate change impact studies that compare them to future projected conditions. Because historical gridded climates are produced using various methods, their portrayal of landscape conditions differ, which becomes a source of uncertainty when they are applied to subsequent analyses. Here we tested the range of values from five gridded climate datasets. We compared their values to observations from 1,231 weather stations, first using each dataset’s native scale, and then after each was rescaled to 270-meter resolution. We inputted the downscaled grids to a mechanistic hydrology model and assessed the spatial results of six hydrological variables across California, in 10 ecoregions and 11 large watersheds in the Sierra Nevada. PRISM was most accurate for precipitation, ClimateNA for maximum temperature, and TopoWx for minimum temperature. The single most accurate dataset overall was PRISM due to the best performance for precipitation and low air temperature errors. Hydrological differences ranged up to 70% of the average monthly streamflow with an average of 35% disagreement for all months derived from different historical climate maps. Large differences in minimum air temperature data produced differences in modeled actual evapotranspiration, snowpack, and streamflow. Areas with the highest variability in climate data, including the Sierra Nevada and Klamath Mountains ecoregions, also had the largest spread for Snow Water Equivalent (SWE), recharge and runoff.

scholarly journals Analysis of the episodes of tropospheric ozone concentration in relation with hot days and heat waves in Warsaw

2018 ◽  
Vol 57 ◽  
pp. 02010 ◽  
Author(s):  
Katarzyna Rozbicka ◽  
Tomasz Rozbicki
Keyword(s):  
Air Temperature ◽  
Ozone Concentration ◽  
Tropospheric Ozone ◽  
Heat Waves ◽  
Maximum Temperature ◽  
Limit Value ◽  
Average Maximum ◽  
Hot Days ◽  
Average Maximum Temperature ◽  
Maximum Air Temperature

The study presents the characteristics of the occurrence of smog episodes - days with exceeded the limit value of 8-hour tropospheric ozone concentration (120 μg.m-3) with the occurrence of hot days (maximum air temperature greater than 25°C), very hot (maximum air temperature greater than 30°C) and heat waves during 13-year period 2004-2016 in the area of Warsaw, Poland. In the analyzed period, the average number of hot days was 45, and very hot days was 8. The highest number of these days occurred in 2015, 54 and 20 days respectively. Heat waves were short and lasted usually 3-4 days. The highest number of them was recorded in 2010 and 2015 (14 days). The highest ozone concentration value 189 μg.m-3was recorded on 28 May 2005, thus exceeding the information threshold (180 μg.m-3for the value of 1 hour ozone concentration). However, the number of days with the exceeded limit value of ozone concentration was not in any year exceeded the target value, i.e. 25 days in a calendar year. The relatively stronger relationship (R=0.513) in comparison to others obtained between average maximum temperature during LTO exceedance days and average ozone concentration during these days but it was not statistically significant.

scholarly journals A Time-Series Analysis of Climate Variability in Urban and Agricultural Sites (Rome, Italy)

Agriculture ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 103 ◽  
Author(s):  
Luca Salvati ◽  
Ilaria Zambon ◽  
Giuseppe Pignatti ◽  
Andrea Colantoni ◽  
Sirio Cividino ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Variability ◽  
Air Temperature ◽  
Local Scale ◽  
Series Data ◽  
Urban Site ◽  
Severe Drought ◽  
Temperature And Precipitation ◽  
Dry Spells

Identifying early signals of climate change and latent patterns of meteorological variability requires tools analyzing time series data and multidimensional measures. By focusing on air temperature and precipitation, the present study compares local-scale climate regimes at two sites in Central Italy (urban Rome and a peri-urban cropland 10 km west of Rome), using descriptive and inferential statistics on both variables and a drought index (the Standardized Precipitation Index, hereafter SPI) recorded over the last 60 years (1958–2017). The present work assumes the importance of urban-rural gradients shaping local-scale climate regimes and spatial variability, with differential impacts on individual variables depending on territorial background and intrinsic biophysical characteristics. Considering together precipitations and minimum/maximum air temperature at month and year scale, the analysis developed here illustrates two coexisting climatic trends at distinctive spatial scales: A general trend toward warming—specifically influencing temperature regimes—and a more specific pattern evidencing changes in local-scale climate regime along the urban gradient, with a more subtle impact on both precipitations and temperatures. Empirical results indicate that climate variability increased over the study period, outlining the low predictability of dry spells typical of Mediterranean climate especially in the drier season (spring/summer). On average, absolute annual differences between the two sites amounted to 70 mm (more rainfall in the peri-urban site) and 0.9 °C (higher temperature in the urban site). A similar trend toward warming was observed for air temperature in both sites. No significant trends were observed for annual and seasonal rainfalls. SPI long-term trends indicate high variability in dry spells, with more frequent (and severe) drought episodes in urban Rome. Considering together trends in temperature and precipitation, the ‘urban heat’ effect was more evident, indicating a clearer trend toward climate aridity in urban Rome. These findings support the adoption of integrated strategies for climate change adaptation and mitigation in both agricultural systems and relict natural ecosystems surrounding urban areas.

scholarly journals Assessment and Evaluation of the Response of Vegetation Dynamics to Climate Variability in Africa

2021 ◽  
Vol 13 (3) ◽  
pp. 1234
Author(s):  
Vincent Nzabarinda ◽  
Anming Bao ◽  
Wenqiang Xu ◽  
Solange Uwamahoro ◽  
Liangliang Jiang ◽  
...  
Keyword(s):  
Climate Variability ◽  
Plant Species ◽  
Environmental Sustainability ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Global Climate ◽  
Terrestrial Ecosystems ◽  
Tree Cover ◽  
Climate Data ◽  
Rate Of Increase

Understanding the impacts of climate variability and change on terrestrial ecosystems in Africa remains a critical issue for ecology as well as for regional and global climate policy making. However, acquiring this knowledge can be useful for future predictions towards improved governance for sustainable development. In this study, we analyzed the spatial–temporal characteristics of vegetation greenness, and identified the possible relationships with climatic factors and vulnerable plant species across Africa. Using a set of robust statistical metrics on the Normalized Difference Vegetation Index (NDVI3g) for precipitation and temperature over 34 years from 1982 to 2015, relevant results were obtained. The findings show that, for NDVI, the annual rate of increase (0.013 y−1) was less than that of decrease (−0.014 y−1). In contrast, climate data showed a sharper increase than a marked decrease. Temperature is increasing while rainfall is decreasing, both at a sharp rate in central Africa. In Africa, tree cover, broadleaved, deciduous, closed to open (>15%) and shrubland plant species are critically endangered. The tropical vegetation devastated by the climate variability, causes different plant species to gradually perish; some were cleared out from the areas which experienced degradation, while others were from that of improvement. This study provides valuable information to African governments in order to improve environmental sustainability and development that will lead to the sustainability of natural resources.

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