scholarly journals Rainfall Variability across the Agro-Climatic Zones of a Tropical Highland: The Case of the Jema Watershed, Northwestern Ethiopia

Environments ◽  
2019 ◽  
Vol 6 (11) ◽  
pp. 118 ◽  
Author(s):  
Taye ◽  
Simane ◽  
Zaitchik ◽  
Selassie ◽  
Setegn
Keyword(s):  
Climate Variability ◽  
Coefficient Of Variation ◽  
Rainfall Variability ◽  
Arithmetic Functions ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Climatic Zones ◽  
Climate Indicators

The objective of the study was to analyze the variability of various climate indicators across the agro-climatic zones (ACZs) of the Jema watershed. The variability was analyzed considering mean annual rainfall (MARF, mm), mean daily minimum temperature (MDMinT, °C), and mean daily maximum temperature (MDMaxT, °C). A one-way analysis of variance (ANOVA) was employed to test whether group mean differences exist in the values of the indicated climatic indicators among the ACZs of the watershed. The coefficient of variation was computed to analyze the degree of climate variability among the ACZs. Rainfall and temperature data sets from 1983 to 2017 were obtained from nearby meteorological stations. The effect of climate variability in the farming system was assessed with reference to local farmers’ experience. Ultimately, the values of the stated indicators of exposure to climate variability were indexed (standardized) in order to run arithmetic functions. The MARF decreases towards sub-alpine ACZs. Based on the result of the ANOVA, the two-tailed p-value (≤ 0.04) was less than 0.05; that is, there was a significant variation in MARF, MDMaxT (°C), and MDMinT (°C) among the ACZs. The coefficient of variation showed the presence of variations of 0.18–0.88 for MARF, 0.18 to 0.85 for MDMaxT, and 0.02–0.95 for MDMinT across the ACZs. In all of the indicators of exposure to climate variability, the lowest and highest indexed values of coefficient of variation were observed in the moist–cool and sub-alpine ACZs, respectively. Overall, the aggregate indexed values of exposure to various climate indicators ranged from 0.13–0.89 across the ACZs. The level of exposure to climate variability increased when moving from moist–cool to sub-alpine ACZs. The overall crop diversity declined across the ACZs of the watershed. Nevertheless, mainly because of the rise in temperature, the climate became suitable for cultivating maize and tef even at higher elevations. In order to adapt to the inter-annual variability of the rainy season, the process of adapting early-maturing crops and the use of improved seeds needs to be enhanced in the watershed, especially in the higher-elevation zones. It is also essential to revise traditional crop calendars and crop zones across the ACSz.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

Comparisons of Machine Learning Methods of Statistical Downscaling Method: Case Studies of Daily Climate Anomalies in Thailand

2021 ◽  
Author(s):  
Kanawut Chattrairat ◽  
Waranyu Wongseree ◽  
Adisorn Leelasantitham
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Performance Criteria ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Support Vector ◽  
Seasonal Temperature ◽  
Statistical Downscaling Method ◽  
Downscaling Method

The climate change which is essential for daily life and especially agriculture has been forecasted by global climate models (GCMs) in the past few years. Statistical downscaling method (SD) has been used to improve the GCMs and enables the projection of local climate. Many pieces of research have studied climate change in case of individually seasonal temperature and precipitation for simulation; however, regional difference has not been included in the calculation. In this research, four fundamental SDs, linear regression (LR), Gaussian process (GP), support vector machine (SVM) and deep learning (DL), are studied for daily maximum temperature (TMAX), daily minimum temperature (TMIN), and precipitation (PRCP) based on the statistical relationship between the larger-scale climate predictors and predictands in Thailand. Additionally, the data sets of climate variables from over 45 weather stations overall in Thailand are used to calculate in this calculation. The statistical analysis of two performance criteria (correlation and root mean square error (RMSE)) shows that the DL provides the best performance for simulation. The TMAX and TMIN were calculated and gave a similar trend for all models. PRCP results found that in the North and South are adequate and poor performance due to high and low precipitation, respectively. We illustrate that DL is one of the suitable models for the climate change problem.

A Note on Rainfall Variability and Trends in Nigeria: Implications for Agricultural Production*

2021 ◽  
pp. 232102222110514
Author(s):  
Kolawole Ogundari ◽  
Adebola Abimbola Ademuwagun ◽  
Ogechukwu Appah
Keyword(s):  
Food Security ◽  
Coefficient Of Variation ◽  
Agricultural Production ◽  
Hypothesis Test ◽  
Rainfall Variability ◽  
Climatic Variability ◽  
Least Square ◽  
Annual Rainfall ◽  
Average Annual Rainfall ◽  
Over Time

The climatic change crisis has led to a renewed interest in understanding the dynamic of climatic variability over time. This is because rainfall variability in response to climate change poses a severe threat to global food security and agricultural production in general. As a result of this, the study investigates the convergence of rainfall variability in Nigeria. We use historical climate data on annual rainfall collected from meteorological stations across 12 states and covering 1992–2013. This gives rise to a balanced panel data of 12 states and 20 periods, which yields 240 observations. The study used a sigma convergence hypothesis test estimated using ordinary least square, fixed-effect and feasible generalized least square models. The coefficient of variation is taken as a measure of rainfall variability in the study. The results showed a negative (declining) linear correlation between rainfall’s coefficient of variation and data year. This means that rainfall variability decreased over time. This indicates evidence of convergence of rainfall, which means states with lower average annual rainfall are catching up on states with higher average annual rainfall over time. And, from the agricultural production standpoint, this result shows that the potential threat of rainfall variability to food security is not severe. In addition, it indicates a decrease in risk and uncertainty in food crop production associated with rainfall variability. JEL Classifications: O13, O55, Q10, Q54

scholarly journals Farmers’ Perceptions on Climate Variability and Adaptation Strategies to Climate Change in Cinzana, Mali

2016 ◽  
Vol 4 (3) ◽  
pp. 13 ◽  
Author(s):  
Touré Halimatou ◽  
Zampaligre Nouhoun ◽  
Traoré Kalifa ◽  
Kyei-Baffour Nicholas
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Meteorological Data ◽  
Rainfall Variability ◽  
Adaptation Strategies ◽  
Sub Saharan Africa ◽  
Farm Size ◽  
Annual Rainfall ◽  
Sub Saharan ◽  
Future Economic Development

Several studies predict that climate change will highly affect the African continent. These changes in climate and climate variability may be challenging issues for future economic development of the continent in general, and particularly in the region of sub Saharan Africa. Offering a case study of Sahelian zone of Mali in the present study aimed to understand farmers’ perceptions of climate variability and change and to evaluate adaptation options used by farmers in the Cinzana commune of Mali. One hundred and nineteen farmers were interviewed using a questionnaire designed with six sections. The result showed that all farmers interviewed were aware of climate change and climate variability. The Farmers perceived a decrease in annual rainfall variability and an increase of temperature as main factors of climate change and climate variability. The observed meteorological data, showed a decrease of precipitation distribution during the last 14 years of which was observed by farmers. Several strategies such as selling animals, use of improved crop varieties, new activities (outside agriculture) and credit were the commonly preferred adaptation strategies to deal with climate change and variability. Factors surveyed, age, gender, education, household size, farm size were found to be significantly correlated to self-reported to adaptation.

scholarly journals Monthly Temperature Observations for Uganda

2013 ◽  
Vol 52 (10) ◽  
pp. 2363-2372 ◽  
Author(s):  
John R. Christy
Keyword(s):  
Time Series ◽  
Public Access ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Record Keeping ◽  
Monthly Average ◽  
Weather Observations ◽  
Temperature Observations

AbstractThe International Surface Temperature Initiative is a worldwide effort to locate weather observations, digitize them for public access, and attach provenance to them. As part of that effort, this study sought documents of temperature observations for the nation of Uganda. Although scattered reports were found for the 1890s, consistent record keeping appears to have begun in 1900. Data were keyed in from images of several types of old forms as well as accessed electronically from several sources to extend the time series of 32 stations with at least 4 yr of data back as far as data were available. Important gaps still remain; 1979–93 has virtually no observations from any station. Because many stations were represented by more than one data source, a scheme is described to extract the “best guess” values for each station of monthly averages of the daily maximum, minimum, and mean temperature. A preliminary examination of the national time series indicates that, since the early twentieth century, it appears that Uganda experienced essentially no change in monthly-average daily maximum temperature but did experience a considerable rise in monthly-average daily minimum temperature, concentrated in the last three decades. Because there are many gaps in the data, it is hoped that readers with information on extant data that were not discovered for this study will contact the author or the project so that the data may be archived.

Indices for daily temperature and precipitation based on quality controlled and homogenized data in Madagascar

2020 ◽  
Author(s):  
Luc Yannick Andréas Randriamarolaza ◽  
Enric Aguilar ◽  
Oleg Skrynyk
Keyword(s):  
Climate Change ◽  
Missing Data ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Indices ◽  
Low Density ◽  
Climate Data ◽  
Temperature And Precipitation

<p>Madagascar is an Island in Western Indian Ocean Region. It is mainly exposed to the easterly trade winds and has a rugged topography, which promote different local climates and biodiversity. Climate change inflicts a challenge on Madagascar socio-economic activities. However, Madagascar has low density station and sparse networks on observational weather stations to detect changes in climate. On average, one station covers more than 20 000 km<sup>2</sup> and closer neighbor stations are less correlated. Previous studies have demonstrated the changes on Madagascar climate, but this paper contributes and enhances the approach to assess the quality control and homogeneity of Madagascar daily climate data before developing climate indices over 1950 – 2018 on 28 synoptic stations. Daily climate data of minimum and maximum temperature and precipitation are exploited.</p><p>Firstly, the quality of daily climate data is controlled by INQC developed and maintained by Center for Climate Change (C3) of Rovira i Virgili University, Spain. It ascertains and improves error detections by using six flag categories. Most errors detected are due to digitalization and measurement.</p><p>Secondly, daily quality controlled data are homogenized by using CLIMATOL. It uses relative homogenization methods, chooses candidate reference series automatically and infills the missing data in the original data. It has ability to manage low density stations and low inter-station correlations and is tolerable for missing data. Monthly break points are detected by CLIMATOL and used to split daily climate data to be homogenized.</p><p>Finally, climate indices are calculated by using CLIMIND package which is developed by INDECIS<sup>*</sup> project. Compared to previous works done, data period is updated to 10 years before and after and 15 new climate indices mostly related to extremes are computed. On temperature, significant increasing and decreasing decade trends of day-to-day and extreme temperature ranges are important in western and eastern areas respectively. On average decade trends of temperature extremes, significant increasing of daily minimum temperature is greater than daily maximum temperature. Many stations indicate significant decreasing in very cold nights than significant increasing in very warm days. Their trends are almost 1 day per decade over 1950 – 2018. Warming is mainly felt during nighttime and daytime in Oriental and Occidental parts respectively. In contrast, central uplands are warming all the time but tropical nights do not appear yet. On rainfall, no major significant findings are found but intense precipitation might be possible at central uplands due to shortening of longest wet period and occurrence of heavy precipitation. However, no influence detected on total precipitation which is still decreasing over 1950 - 2018. Future works focus on merging of relative homogenization methodologies to ameliorate the results.</p><p>-------------------</p><p>*INDECIS is a part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).</p>

scholarly journals Effects of diurnal warming on soil respiration are not equal to the summed effects of day and night warming in a temperate steppe

2009 ◽  
Vol 6 (8) ◽  
pp. 1361-1370 ◽  
Author(s):  
J. Xia ◽  
Y. Han ◽  
Z. Zhang ◽  
Z. Zhang ◽  
S. Wan
Keyword(s):  
Soil Respiration ◽  
Temperature Increase ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperate Steppe ◽  
Positive Effects ◽  
Diurnal Warming ◽  
Night Warming

Abstract. The magnitude of daily minimum temperature increase is greater than that of daily maximum temperature increase under climate warming. This study was conducted to examine whether changes in soil respiration under diurnal warming are equal to the summed changes under day and night warming in a temperate steppe in northern China. A full factorial design with day and night warming was used in this study, including control, day (06:00 a.m.–06:00 p.m., local time) warming, night (06:00 p.m.–06:00 a.m.) warming, and diurnal warming. Day warming showed no effect on soil respiration, whereas night warming significantly increased soil respiration by 7.1% over the 3 growing seasons in 2006–2008. The insignificant effect of day warming on soil respiration could be attributable to the offset of the direct positive effects of increased temperature by the indirect negative effects via aggravating water limitation and suppressing ecosystem C assimilation. The positive effects of night warming on soil respiration were largely due to the stimulation of ecosystem C uptake and substrate supply via overcompensation of plant photosynthesis. Changes in both soil respiration (+20.7 g C m−2 y−1) and GEP (−2.8 g C m−2 y−1) under diurnal warming are smaller than their summed changes (+40.0 and +24.6 g C m−2 y−1, respectively) under day and night warming. Our findings that the effects of diurnal warming on soil respiration and gross ecosystem productivity are not equal to the summed effects of day and night warming are critical for model simulation and projection of climate-carbon feedback.

Germination of the Salt-Tolerant Grass Diplachne fusca. II. Salinity Responses

1989 ◽  
Vol 37 (3) ◽  
pp. 239 ◽  
Author(s):  
BA Myers ◽  
WC Morgan
Keyword(s):  
Germination Percentage ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Distilled Water ◽  
Nacl Solution ◽  
Salt Tolerant ◽  
Similar Reduction ◽  
Threshold Temperatures

The responses -of germination of the salt-tolerant grass Diplachne fusca (L.) Beauv. to salinity and various temperature regimes are described. At temperatures of 30/20°C (12 h light and dark periods), final germination was 70% in distilled water, decreased to 50% in 175 mol m-3 NaCl (π = - 0.8 MPa) and 7% in 380 mol m-3 NaCl (π = -1.8 MPa). Increasing salinity from 0-130mol m-3 NaCl decreased the final germination percentage, but did not modify the threshold temperatures (day or night temperature > 27°C) at which germination occurred. Presoaking in distilled water or 1% CaCl2· 2H20 solution did not significantly affect the final germination percentage of seeds which were subsequently placed in solutions with a range of salinities from 0-210 mol m-3 NaCl (*#960 = 0 to - 1.0 MPa). How- ever, addition of CaCl2 to NaCl solution increased the final germination percentage compared with that in pure NaCl solution. Presoaking in concentrated (400 mol m-3) NaCl solution caused a decrease in subsequent germinability of 20 or 40% in 0 and 40 mol m-3 NaCl, respectively. Under field conditions (in soil with mean daily maximum temperature of 33°C and mean daily minimum temperature of 15°C), rates of seedling establishment were similar (16% of seed sown) in soils irrigated with 0 or 50 mol m-3 NaCl, and were 1% in those irrigated with 100 mol m-3 NaCl. The inhibition of germination in NaCl solution was largely an osmotic effect since there was a similar reduction in the final germination percentage in iso-osmotic solutions of NaCl and mannitol. However, the proportion of seeds germinating in NaCl solution was enhanced by adding calcium. The inhibition of germination was greater in sulfate solutions compared with that in chloride solutions and, to a lesser degree, in potassium compared with sodium solutions. The practical implications of our results are discussed. The incorporation of gypsum into the soil and measures to leach salts from the topsoil are recommended before D. fusca is sown on saline land.

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