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

Climate ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 55
Author(s):  
Oscar Pita-Díaz ◽  
David Ortega-Gaucin

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 and Indices (ETCCDI). We studied a 40-year period (1976–2015) using annual and seasonal time series. 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 grids 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.

Author(s):  
Oscar Pita-Díaz ◽  
David Ortega-Gaucin

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.


2019 ◽  
Vol 60 ◽  
pp. C109-C126 ◽  
Author(s):  
Joshua Hartigan ◽  
Shev MacNamara ◽  
Lance M Leslie

Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature. References R. A., R. L. Kitching, F. Chiew, L. Hughes, P. C. D. Newton, S. S. Schuster, A. Tait, and P. Whetton. Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of Working Group II to the Fifth Assessment of the Intergovernmental Panel on Climate Change. Technical report, Intergovernmental Panel on Climate Change, 2014. URL https://www.ipcc.ch/report/ar5/wg2/. Bureau of Meteorology. Climate Glossary-Drought. URL http://www.bom.gov.au/climate/glossary/drought.shtml. K. M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. B. Am. Meteorol. Soc., 76:23912402, 1995. doi:10.1175/1520-0477(1995)0762391:CSDUWT>2.0.CO;2. M. B. Richman and L. M. Leslie. Uniqueness and causes of the California drought. Procedia Comput. Sci., 61:428435, 2015. doi:10.1016/j.procs.2015.09.181. M. B. Richman and L. M. Leslie. The 20152017 Cape Town drought: Attribution and prediction using machine learning. Procedia Comput. Sci., 140:248257, 2018. doi:10.1016/j.procs.2018.10.323.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.


Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 489
Author(s):  
Jinxiu Liu ◽  
Weihao Shen ◽  
Yaqian He

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.


2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.


Agronomy ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 25 ◽  
Author(s):  
Tapan Pathak ◽  
Mahesh Maskey ◽  
Jeffery Dahlberg ◽  
Faith Kearns ◽  
Khaled Bali ◽  
...  

California is a global leader in the agricultural sector and produces more than 400 types of commodities. The state produces over a third of the country’s vegetables and two-thirds of its fruits and nuts. Despite being highly productive, current and future climate change poses many challenges to the agricultural sector. This paper provides a summary of the current state of knowledge on historical and future trends in climate and their impacts on California agriculture. We present a synthesis of climate change impacts on California agriculture in the context of: (1) historic trends and projected changes in temperature, precipitation, snowpack, heat waves, drought, and flood events; and (2) consequent impacts on crop yields, chill hours, pests and diseases, and agricultural vulnerability to climate risks. Finally, we highlight important findings and directions for future research and implementation. The detailed review presented in this paper provides sufficient evidence that the climate in California has changed significantly and is expected to continue changing in the future, and justifies the urgency and importance of enhancing the adaptive capacity of agriculture and reducing vulnerability to climate change. Since agriculture in California is very diverse and each crop responds to climate differently, climate adaptation research should be locally focused along with effective stakeholder engagement and systematic outreach efforts for effective adoption and implementation. The expected readership of this paper includes local stakeholders, researchers, state and national agencies, and international communities interested in learning about climate change and California’s agriculture.


2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.


Climate ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 165
Author(s):  
Prem B. Parajuli ◽  
Avay Risal

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.


Author(s):  
AWO Sourou Malikiyou ◽  
ALE Agbachi Georges ◽  
YABI Ibouraïma

La variabilité climatique dans les communes de Djidja et de Djougou engendre des conséquences aussi bien sur les niveaux de productivités, de production que sur les revenus des exploitants agricoles. L’objectif de cette recherche est d’étudier la vulnérabilité future des systèmes de productions agricoles face aux changements climatiques dans les Communes de Djidja et de Djougou.L’approche méthodologique utilisée comprend la collecte des données, leur traitement et l’analyse des résultats. Les enquêtes ont été faites dans les villages choisis sur la base de critères bien définis (la taille de la population agricole et son implication dans la production agricole). La méthode de D. Schwartz (1995, p. 94) a permis de constituer l’échantillon de 377 producteurs. Enfin, une projection climatique sur la période 2019-2050/2075 est faite au moyen du logiciel climatique « Climate explorer ».Il ressort des résultats de l’étude que, dans la commune de Djougou, la variation au niveau de la température minimale actuelle (RCP8.5) est comprise entre -1,62°C en 1992 et 2,29°C en 2075. La température maximale quant à elle varie entre -1,40°C en 1994 à 2,18°C en 2075. C’est à partir de 2071 que l’augmentation de la température minimale va dépasser les 2°C et si rien n’est fait cette hausse va s’accroître et devenir permanente. De même, dans la commune de Djidja, la température minimale la plus élevée est observée en 2075 avec des variations de 1 à 2°C pour les RCP4.5 et RCP8.5. Au niveau de la température maximale, l’année la moins chaude est 1992 (-1,33mm/jour) pour RCP8.5 et 1991 (-1,02mm/jour) pour RCP4.5. La même évolution s’observe au niveau des températures maximales. L’année 1992 reste la plus déficitaire avec une chute de -1,60°C et l’année la plus excédentaire sera l’année 2075 avec une hausse de 2,18 mm par jour, sur la période 1992-2080. La corrélation est observée en 2042 avec une valeur de 0,322 mm par jour. L’examen des résultats révèle que les valeurs des paramètres climatiques à savoir précipitations et évaporation sont à la hausse sur la période 1980-2080 dans la commune de Djidja. Suivant la trajectoire actuelle, RCP8.5, les années les plus arrosées sont 2037, 2070 et 2073 avec respectivement des variations égales à 0,17mm et 0,27mm de pluie par jour. Face à ces difficultés, les populations agricoles adoptent des mesures pour contrer les contraintes climatiques.ABSTRACTClimatic variability in the communes of Djidja and Djougou has consequences both on the levels of productivity and production and on the income of farmers. The objective of this research is to study the vulnerability of agricultural production systems to climate change in the Communes of Djidja and Djougou.The methodological approach used includes data collection, processing and analysis of the results. The surveys were carried out in the villages chosen on the basis of well-defined criteria (the size of the agricultural population and its involvement in agricultural production). The method of D. Schwartz (1995, p. 94) made it possible to constitute the sample of 377 producers. Finally, a climate projection over the period 2019-2050 / 2075 is made using the climate software "Climate explorer".The results of the study show that, in the municipality of Djougou, the variation in the current minimum temperature (RCP8.5) is between -1.62 ° C in 1992 and 2.29 ° C in 2075. The maximum temperature varies between -1.40 ° C in 1994 to 2.18 ° C in 2075. It is from 2071 that the increase in the minimum temperature will exceed 2 ° C and if nothing is In fact, this increase will increase and become permanent. Similarly, in the municipality of Djidja, the highest minimum temperature is observed in 2075 withvariations of 1 to 2 ° C for RCP4.5 and RCP8.5. At maximum temperature, the coolest year is 1992 (-1.33mm / day) for RCP8.5 and 1991 (-1.02mm / day) for RCP4.5. The same development can be observed at the level of maximum temperatures. The year 1992 remains the most in deficit with a fall of -1.60 ° C and the year the most in surplus will be the year 2075 with an increase of 2.18mm per day, over the period 1992-2080. The correlation is observed in 2042 with a value of 0.322 mm per day. Examination of the results reveals that the values of climatic parameters, namely precipitation and evaporation, are on the rise over the period 1980-2080 in the municipality of Djidja. Following the current trajectory, RCP8.5, the wettest years are 2037, 2070 and 2073 with respectively variations equal to 0.17mm and 0.27mm of rain per day. Faced with these difficulties, agricultural populations are adopting measures to counter climatic constraints. Keywords: Djidja, Djougou, vulnerability, production system, agriculture, climate change.


2013 ◽  
Vol 31 (1) ◽  
pp. 27 ◽  
Author(s):  
Ravind Kumar ◽  
Mark Stephens ◽  
Tony Weir

This paper analyses trends in temperature in Fiji, using data from more stations (10) and longer periods (52-78 years) than previous studies. All the stations analysed show a statistically significant trend in both maximum and minimum temperature, with increases ranging from 0.08 to 0.23°C per decade. More recent temperatures show a higher rate of increase, particularly in maximum temperature (0.18 to 0.69°C per decade from 1989 to 2008). This clear signal of climate change is consistent with that found in previous studies of temperatures in Fiji and other Pacific Islands. Trends in extreme values show an even stronger signal of climate change than that for mean temperatures. Our preliminary analysis of daily maxima at 6 stations indicates that for 4 of them (Suva, Labasa, Vunisea and Rotuma) there has been a tripling in the number of days per year with temperature >32°C between 1970 and 2008. The correlations between annual mean maximum (minimum) temperature and year are mostly strong: for about half the stations the correlation coefficient exceeds 60% over 50+ years. Trends do not vary systematically with location of station. At all 7 stations for which both trends are available there is no statistically significant difference between the trends in maximum and minimum temperatures.


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