scholarly journals CLIMATIC VARIABILITY AND LIVELIHOOD VULNERABILITY IN KADUNA STATE, NIGERIA

2017 ◽  
Vol 1 (1) ◽  
pp. 36
Author(s):  
Muhammad, N. ◽  
Manu, H.I. ◽  
Maina- Bukar, Y. ◽  
Abdullahi, Y.R.
Keyword(s):  
Local Government ◽  
International Development ◽  
Minimum Temperature ◽  
Climatic Variability ◽  
Vulnerability Index ◽  
The State ◽  
Maximum Temperature ◽  
Sample Population ◽  
Climatic Zones ◽  
Farming Households

Purpose: This paper focused on livelihood vulnerability induced by climatic variability amongst farming households in Kaduna state, Nigeria. Methodology: The research used a sample population of 400 using Taro Yamane formula which represents about 0.05% of the population of the three selected local government areas and it purposively targeted farming households heads (FHHH) in one of each of the three eco-climatic zones in the state. Kagarko, BirninGwari and Makarfi local government areas were based on their eco-climatic location and rurality to represent humid, sub-humid and dry sub humid zones of the state respectively. A multi stage sampling technique was further adopted in which farming districts and villages were selected for the administration of 400 structured questionnaires proportionately distributed proportionately to the three local government areas. The Department for International Development (DFID) sustainable livelihoods framework was adopted in the design of the structured questionnaires. Coefficient of Variation (CV %) was deployed to determine the variability of rainfall and temperature of the three eco-climatic zones of the past thirty six years (1981-2016) which was employed into the Micah Hahn’s Livelihood Vulnerability Index model.The results show that Kagarko (humid) had a CV% of 105.43 of rainfall, 9.06 CV% of maximum temperature and CV% of 17.63 in minimum temperature. BirninGwari (sub-humid) had a CV% of 119.64 in rainfall, CV% of 14.17 in maximum temperature and CV% of 15.92 in minimum temperature while Makarfi (dry sub-humid) had a CV% of 124.71 in rainfall, CV%  of 9.72 in maximum temperature and 16.29 CV% in minimum temperature. The livelihood vulnerability index (LVI) of Kagarko was calculated to be 0.35, Makarfi and BirninGwari were calculated to be 0.36 respectively and vulnerability spider diagrams were used to capture and compare results. On a vulnerability scale of 0-1, the three eco-climatic zones were found to be very vulnerable to climatic variability. The paper has proved the applicability of Co-efficient of Variation (CV %) into the LVI model which is a departure from previous users who have consistently deployed Mean Standard Deviation into the model. Results: This study will serve as a spring board to meet the Sustainable Development Goals (SDGs) targets on vulnerable communities in Kaduna state. It is discovered that farmers in Makarfi and BirninGwari, even though in different eco-climatic zones of sub-humid and dry sub humid zones respectively, share equal level of livelihood vulnerability index of 0.36 while Kagarko area which is in humid zone, is having 0.35. These indicated that all the areas are within the very vulnerable values on a vulnerability scale of 0-1. The vulnerability levels of the study area can be attributed to weak Natural, Financial and Physical capitals. Recommendations: The paper recommended Integrated Farmers’ Livelihoods Support Strategy (IFLISS) so as to build the resilience of farming households’ livelihood capitals and reduce vulnerability levels.

Comparison of Spatial Interpolation Methods for Mapping Daily Air Temperature 

2021 ◽  
Author(s):  
Lasyamayee L Sahoo ◽  
Subashisa Dutta
Keyword(s):  
Minimum Temperature ◽  
Evaluation Method ◽  
Heat Waves ◽  
Interpolation Method ◽  
Climatic Variability ◽  
Labour Productivity ◽  
The State ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Interpolation Methods

<p>The sparsely distributed meteorological centers fails to provide enough information regarding spatial patterns. Even at places where dense meteorological stations are available, it is difficult to develop realistic gridded data due to the complex topography and climatic variability. Some of the climate as well as hydrological model require spatially continuous datasets as inputs. It is possible to obtain a continuous surface of raster datasets with the help of interpolation methods where each value is assigned based on surrounding values using specific mathematical formulas. For present study, various interpolation methods, like Inverse distance weighted, ordinary krigging, thin plate smoothing spline; has been compared for maximum and minimum temperature. Error in the interpolated data was analyzed by independent cross validation method, in which measurements like root mean square error (RMSE), mean squared relative error (MSRE), coefficient of determination (r<sup>2</sup>) and coefficient of efficiency (CE) were adopted for performance evaluation. Method with minimum error was chosen for developing the final map. It provides an effective way for mapping the meteorological variables in a topographically diverse region. In this case, an Indian state Odisha is chosen as study area. The state consists of 10 different agro-climatic zones and sees several weather systems across the year. The area suffers with floods, drought, heat waves and costal erosion almost every year with variable intensity. Strong heat waves in summer affect the human health, agriculture, construction efficiency and labour productivity. As three-fourth of the state is filled with mountains and high lands, monitoring network is sparsely distributed. Despite small latitudinal difference, temperature changes considerably with respect to both space and time. Here interpolation method plays a vital role to avoid uncertainty in modelling. Based on the generated maps, vulnerable areas on the basis of maximum temperature in summer and minimum temperature in winter is identified. Several indicators and vulnerability indices has been used.</p>

scholarly journals ASSESSMENT OF LONG TERM CLIMATIC VARIABILITY OF UTTARAKHAND

2018 ◽  
Vol 1 (4) ◽  
Author(s):  
Sujeet Kumar ◽  
Shakti Suryavanshi
Keyword(s):  
Minimum Temperature ◽  
Monsoon Season ◽  
Climatic Variability ◽  
Kendall Test ◽  
Summer Season ◽  
Climatic Variables ◽  
Maximum Temperature ◽  
Mountain Areas ◽  
Mk Test ◽  
Increasing Trend

A trend analysis was performed for historic (1901-2002) climatic variables (Rainfall, Maximum Temperature and Minimum Temperature) of Uttarakhand State located in Northern India. In the serially independent climatic variables, Mann-Kendall test (MK test) was applied to the original sample data. However, in the serially correlated series, prewhitening is utilized before employing the MK test. The results of this study indicated a declining trend of rainfall in monsoon season for seven out of thirteen districts of Uttarakhand state. However, an increasing trend was observed in Haridwar and Udhamsingh Nagar districts for summer season rainfall. For maximum and minimum temperature, a few districts exhibited a declining trend in monsoon season whereas many districts exhibited an increasing trend in winter and summer season. Mountain dominated areas (as Uttarakhand state) are specific ecosystems, distinguished by their diversity, sensitivity and intricacy. Thus the variability of rainfall and temperature has a severe and rapid impact on mountainous ecosystems. Nevertheless, mountains have significant impacts on hydrology, which may further threaten populations living in the mountain areas as well as in adjacent, lowland regions.

scholarly journals Analysis of Anomalies and Trends of Climate Change Indices in the State of Zacatecas, Mexico

2020 ◽  
Author(s):  
Oscar Pita-Díaz ◽  
David Ortega-Gaucin
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Agricultural Sector ◽  
Negative Impact ◽  
Southern Oscillation ◽  
Climate Scenario ◽  
The State ◽  
Data Availability ◽  
Sufficient Evidence ◽  
Maximum Temperature

Sufficient evidence is currently available to demonstrate the reality of the warming of our planet's climate system. Global warming has different effects on climate at the regional and local levels. The detection of changes in extreme events using instrumental data provides further evidence of such warming and allows for the characterization of its local manifestations. The present study analyzes changes in temperature and precipitation extremes in the Mexican state of Zacatecas using climate change indices developed by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDI). We studied a 40-year period (1976-2015) using annual and seasonal time scales. Maximum and minimum temperature data were used, as well as precipitation statistics from the Mexican climatology database (CLICOM) provided by the Mexican meteorological service. Weather stations with at least 80% of data availability for the selected study period were selected; these databases were subjected to quality control, homogenization, and data filling using Climatol, which runs in the R programming language. These homogenized series were used to obtain daily grides of the three variables at a resolution of 1.3 km. Results reveal important changes in temperature-related indices, such as the increase in maximum temperature and the decrease in minimum temperature. Irregular variability was observed in the case of precipitation, which could be associated with low-frequency oscillations such as the Pacific Decadal Oscillation and the El Niño–Southern Oscillation. The possible impact of these changes in temperature and the increased irregularity of precipitation could have a negative impact on the agricultural sector, especially given that the state of Zacatecas is the largest national bean producer. The most important problems in the short term will be related to the difficulty of adapting to these rapid changes and the new climate scenario, which will pose new challenges in the future.

Climate Change Effect on Productivity of Major Crops in Western Haryana

2020 ◽  
pp. 512-515
Keyword(s):  
Pearl Millet ◽  
Crop Yield ◽  
Minimum Temperature ◽  
Positive Impact ◽  
Linear Trend ◽  
The State ◽  
The Other ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Western Zone

The study was conducted in Sirsa, Hisar and Rewari districts from Western Zone of the State during the year 2017-18. Data related to rainfall and temperatures were collected from department of agro-meteorology, CCSHAU, Hisar, whereas data related to area, production and productivity of major crops like paddy, cotton, pearl millet, wheat and mustard were recorded from various issues of statistical abstract of Haryana. The results of the study revealed that linear trend was observed in minimum and maximum temperature, whereas, in case of annual rainfall, non-linear trend was found in both Kharif as well as Rabi seasons in during the 2006-07 to 2015-16. The rise in maximum temperature was positive and significant effect on paddy crop yield whereas, it was significantly negative impact on pearl millet yield but in case of cotton, it was negative but non-significant effect on cotton yield. On the other side, rise in minimum temperature was positive but non-significant effect on productivity of paddy as well as pearl millet. Rainfall coefficient was observed significantly positive impact on pearl millet crop productivity whereas; it was negative but non-significant affect the productivity of paddy and cotton. Rainfall coefficient was observed significantly positive impact on pearl millet productivity whereas; it was negative but non-significant effect on the productivity of paddy and cotton in Hisar, Sirsa and Rewari districts of western zone of the state. The rise in maximum temperature was significantly negative effect on wheat crop yield whereas, it was negative but non-significant impact on mustard yield. On the other side, rise in minimum temperature was negative but non-significant effect on productivity of wheat as well as mustard. The rainfall coefficient was observed significantly positive impact on productivity of wheat and mustard in Western Zone of the state.

scholarly journals Improving Princeton Forcing Dataset over Iran Using the Delta-Ratio Method

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 630
Author(s):  
Qinghuan Zhang ◽  
Qiuhong Tang ◽  
Xingcai Liu ◽  
Seyed-Mohammad Hosseini-Moghari ◽  
Pedram Attarod
Keyword(s):  
Wind Speed ◽  
Minimum Temperature ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Ratio Method ◽  
Climate Data ◽  
Climatic Zones ◽  
Humid Zone ◽  
Time Period ◽  
Skill Scores

In this study, we corrected the bias in the Princeton forcing dataset, i.e., precipitation, maximum and minimum temperatures, and wind speed, by adjusting its long-term mean monthly climatology to match observations for the period 1988–2012 using the delta-ratio method. To this end, we collected meteorological data from 97 stations covering the domain of Iran. We divided Iran into three climatic zones based on the De Martonne classification, i.e., Arid, Humid, and Per-Humid zones, and then applied the delta-ratio method for each climatic zone separately to adjust the bias. After adjustment, the new datasets were compared to the observations in 1958–1987. Results based on four skill scores, including the Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), root-mean-square error (RMSE), and R2, indicate that the adjustment greatly improved the quality of the gridded dataset, specifically, precipitation, maximum temperature, and wind speed. For example, NSE for annual precipitation during the validation time period increased from −0.03 to 0.72, PBIAS reduced from 29.2% to 6.6%, RMSE decreased by 182.44 mm, and R2 increased from 0.06 to 0.75. Assessing the results in different climatic zones of Iran reveals that precipitation improved more significantly in the Per-Humid zone followed by the Humid zone, while maximum temperature improved better in the Arid areas. For wind speed, the values improved comparably in the three climate zones. However, the delta values for monthly minimum temperature calculated during the adjustment time period cannot be applied in the validation time period, due to the fact that the Princeton climate data cannot follow the behavior of minimum temperature during the validation phase. In short, we showed that a simple bias adjustment approach, along with minimum observed station data, can significantly improve the performance of global gridded datasets.

scholarly journals Recent trends in meteorological parameters over Jammu and Kashmir

MAUSAM ◽  
2021 ◽  
Vol 61 (3) ◽  
pp. 369-382
Author(s):  
A. K. JASWAL ◽  
G. S. PRAKASA RAO
Keyword(s):  
Relative Humidity ◽  
Minimum Temperature ◽  
Meteorological Parameters ◽  
Cloud Amount ◽  
The State ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Jammu And Kashmir ◽  
Total Cloud Amount ◽  
Increasing Trends

Annual trends of meteorological parameters temperature, rainfall, relative humidity and clouds for ten stations in Jammu and Kashmir during the period 1976-2007 were studied. Trend analysis shows that temperatures are increasing over the state with significant increase in maximum temperature in the Kashmir region (+0.04 to                +  0.05° C/year) and minimum temperature in the Jammu region (+0.03 to + 0.08° C/year). The diurnal temperature range (DTR) is increasing over Kashmir region due to higher increasing trends in the maximum temperature while the strong increasing trends in the minimum temperature are contributing more towards the decrease in DTR over the Jammu region. Annual rainfall and rainy days trends are decreasing in both the regions of the state except at Jammu where rainfall trend is significantly increasing (+12.05 mm/year). Day-time relative humidity trends are mixed while total cloud amount trends are decreasing over Kashmir region and increasing over Jammu region. The effects of urbanization in the last two decades are more pronounced in Jammu region and this is strongly expressed in minimum temperature over the region. The warming trends observed over Jammu and Kashmir state during the period of study need further investigation in relation to variability of atmospheric circulation over North India.

scholarly journals Variability of climate, water and nitrogen status and its influence on vine phenology and grape composition inside a small winegrowing estate

2018 ◽  
Vol 50 ◽  
pp. 01016
Author(s):  
Laure de Rességuier ◽  
Renan Le Roux ◽  
Théo Petitjean ◽  
Séverine Mary ◽  
Hervé Quénol ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Malic Acid ◽  
Acid Content ◽  
Minimum Temperature ◽  
Sugar Content ◽  
Climatic Variability ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Nitrogen Status ◽  
Spatial Temperature

Climate is a major terroir factor in viticulture. In winegrowing regions, climate is studied at an increasingly refined scale. Results from the Life ADVICLIM project show substantial spatial variability of temperatures inside the region of Saint-Emilion, Pomerol and surrounding appellations (Bordeaux, France). In this study we investigated climatic variability at an even more refined scale, inside an 11 ha estate located in Saint-Emilion with significant topographic variability, planted with Merlot and Cabernet franc. Elevation ranges from 34 to 81 meters. 31 temperature sensors were set-up in 2013 inside the canopy, taking into account all parameters linked to the topography. Spatial temperature variability and its influence on vine phenology and grape composition were investigated. Vine water and nitrogen status were also taken into account through δ13C and N-tester measurements. Over the growing season (April 1 through September 30), spatial temperature variability was greater on minimum temperatures (1.6°C) compared to maximum temperatures (1.3°C). Spatial variability in minimum temperature was driven by elevation and slope. Further investigation is required for spatial variability in maximum temperature, which could not be explained by environmental co-variables. Temperature variability among vintages was driven by maximum temperature, while minimum temperature showed little variation from one year to another. The average Winkler Index measured in the canopy ranged from 1774 degree.days to 1978 degree.days. This spatial variability of 204 degree.days can induces potentially 20 days difference in maturity dates. The timing of flowering varied from one vintage to another but inside a given vintage spatial variability was small, and so was variability induced by the cultivar. Veraison dates were highly variable among vintages. Inside a given vintage, spatial variability and cultivar effect were significant. Berry weight was driven by vine water and nitrogen status. Berry malic acid content was impacted by temperature. Vine water and nitrogen status also influenced berry malic acid content. Berry sugar content depended mainly on vine nitrogen status. The grapevine variety influenced berry sugar and malic acid content, as well as berry mass.

scholarly journals Managing impact of extreme weather events in sugarcane in different agro-climatic zones of Uttar Pradesh

MAUSAM ◽  
2021 ◽  
Vol 67 (1) ◽  
pp. 233-250
Author(s):  
R. K. MALL ◽  
G. SONKAR ◽  
D. BHATT ◽  
N. K. SHARMA ◽  
A. K. BAXLA ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
Uttar Pradesh ◽  
Extreme Weather ◽  
The State ◽  
Extreme Weather Events ◽  
Annual Rainfall ◽  
Average Yield ◽  
Climatic Zones ◽  
Weather Events ◽  
Western Zone

Sugarcane is a cash crop in Uttar Pradesh; economic condition of the farmers is highly dependent on sugarcane production. However, average yield of the state has gone up from 39.5 t/ha (1950-51) to 59.2 t/ha (2009-10), was observed associated with fluctuating weather conditions, whereas other major sugar producing area in India have average yield of 70 t/ha. The result of the above study showed that there was an average rising trend in the annual minimum temperature (0.03° Cyr-1) over all the agro-climatic zones of the state. Out of nine agro-climatic zones, four zones namely South Western Zone, Central Plain Zone, Western Plain Zone and Eastern Plain zone, which were marked by decreasing annual rainfall trend. However, Vindhyan Zone, Mid Western Zone and Bhabhar and Tarai Zone show rising trend. To explain better relation between cane yield and weather parameters this study also show that maximum, minimum temperature and moisture plays the most important role during germination, tillering, grand growth and ripening phases of the sugarcane. Considering extreme weather, we found that temperature below 25 °C, above 35 °C and 40 °C are slowing down the growth and finally reducing the final yield. It is also noticed that temperature and rainfall extremes had high possibility of governing sugarcane yields but there were also quite a number of instances wherein the extremes couldn’t be reasoned directly for the yield fluctuations. Therefore, to sustain the productivity, this study recommends the improvements of the adoptive responses of varieties, management of the risk associated with extreme weather events by providing weather linked value-added advisory services to the farmers and crop insurance agencies.

An Update on Trends in Skill of Daily Forecasts of Temperature and Precipitation at the State University of New York at Albany

1983 ◽  
Vol 64 (4) ◽  
pp. 346-354 ◽  
Author(s):  
Lance F. Bosart
Keyword(s):  
New York ◽  
Minimum Temperature ◽  
Linear Regression Analysis ◽  
Precipitation Amount ◽  
The State ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
State University ◽  
Skill Levels ◽  
Temperature And Precipitation

Consensus (the average of all forecasts) skill levels in forecasting daily maximum and minimum temperature, precipitation probability across six class intervals, and precipitation amount at the State University of New York at Albany are reviewed for the period 1977–82. Skill is measured relative to a climatological control. Forecasts are made for four consecutive 24 h periods for Albany, N.Y., beginning at 1800 GMT of the current day. For minimum temperature, the skill levels average 57%, 41%, 26%, and 15%, respectively, for 24, 48, 72, and 96 h in advance. For maximum temperature, a more limited sample yields corresponding skill levels of 84%, 49%, 34%, and 19% for 12, 36, 60, 84 h ahead. Linear regression analysis yields little in the way of a definitive trend, given the smallness of the explained variance. Comparison with other readily available objective and subjective operational guidance establishes the credibility of the consensus forecast.

scholarly journals Analysis of rainfall and temperatures for climatic trend in Kullu valley

MAUSAM ◽  
2021 ◽  
Vol 62 (1) ◽  
pp. 77-84
Author(s):  
SUMAN JANGRA ◽  
MOHAN SINGH
Keyword(s):  
Minimum Temperature ◽  
Monsoon Rainfall ◽  
Climatic Variability ◽  
Winter Season ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Recent Period ◽  
Climatic Trend ◽  
Increasing Trend ◽  
Kullu Valley

Kullu valley is famous for tourism and agricultural activities but recently it has assumed importance for studies on climatic variability. There is an increasing trend in minimum and maximum temperatures but no trend in annual rainfall. The slope of regression line for annual rainfall was negative at Bajaura and positive at Katrain but both were non significant. The coefficient of variation for annual rainfall (22 %) and for monsoon rainfall (33 %) was showing the consistence of annual and southwest monsoon rainfall but, a shifting of monsoon from its wettest months was observed. The rainfall was most variable during post monsoon season at Bajaura and in winter at Katrain. The decreasing rate in rainfall was higher during the recent period than the decadal period. Monthly, seasonal and annual average minimum temperature was showing decreasing trend at Bajaura and an increasing trend at Katrain, but, maximum temperature is increasing at both the stations. The minimum temperature was most variable during the winter season whereas the maximum temperature was during summer. Higher the altitude higher the variability in minimum temperature but lower the altitude higher the variability in maximum temperature. Both maximum and minimum temperatures were showing a higher rate of increasing during the recent period.

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