Increase In Minimum Temperature Research Articles

Continued spring phenological advance under global warming hiatus over the Pan-Third Pole.

The global surface temperature has witnessed a warming hiatus in the first decade of this century, but how this slowing down of warming will impact spring phenology over Pan-Third Pole remains unclear. Here, we combined multiple satellite-derived vegetation indices with eddy covariance datasets to evaluate the spatiotemporal changes in spring phenological changes over the Pan-Third Pole. We found that the spring phenology over Pan-Third Pole continues to advance at the rate of 4.8 days decade-1 during the warming hiatus period, which is contrasted to a non-significant change over the northern hemisphere. Such a significant and continued advance in spring phenology was mainly attributed to an increase in preseason minimum temperature and water availability. Moreover, there is an overall increasing importance of precipitation on changes in spring phenology during the last four decades. We further demonstrated that this increasingly negative correlation was also found across more than two-thirds of the dryland region, tentatively suggesting that spring phenological changes might shift from temperature to precipitation-controlled over the Pan-Third Pole in a warmer world.

Does agroecosystem management mitigate historic climate impacts on dryland winter wheat yields?

AbstractGlobal studies that quantify climate effects on crop yields using top‐down spatial frameworks are invaluable for assessing generalized effects on world food supplies, yet do not contain the resolution necessary to identify local mediating effects of management. Our objectives were to identify (a) what climate factors have historically affected winter wheat (Triticum aestivum L.) yields in eastern Colorado, (b) how management may mitigate climate impacts, and (c) the potential for varietal selection to climate extremes. We paired long‐term yield data for wheat in rotations that varied in management (tillage intensity, with and without fallow) with robust on‐site weather data. We also used data from colocated variety trials to investigate trade‐offs between mean yields and the ability to withstand water and temperature stress. Precipitation in April–June was nearly as predictive of yields as full growing season precipitation. While precipitation and air temperatures are tightly linked in this agroecosystem, temperatures were more predictive of yields than precipitation. Increases in minimum May temperatures positively affected yields, likely because of minimizing freeze damage, but did not offset detrimental effects of warmer daytime spring and summer temperatures. The largest negative temperature effects were caused by extreme maximum temperatures in June. No‐till with fallow maximized yields. Low‐ and high‐yielding varieties did not differ in yield responses to high temperatures, suggesting that future advancements in heat stress resistance will not necessarily require yield trade‐offs. Climate pressures will likely require producers to balance yield goals with maintaining soil cover, underscoring the difficulty of identifying win–win climate adaptations.

Downscaled Climate Change Projections in Urban Centers of Southwest Ethiopia Using CORDEX Africa Simulations

Projections of future climate change trends in four urban centers of southwest Ethiopia were examined under a high Representative Concentration Pathways (RCP8.5) scenario for near- (2030), mid- (2050), and long-term (2080) periods based on high-resolution (0.220) Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa data. The multi-model ensemble projects annual maximum and minimum temperatures increasing by 0.047 °C per year (R2 > 0.3) and 0.038 °C per year (R2 > 0.7), respectively, with the rates increased by a factor of 10 for decadal projections between the 2030s and 2080s. The monthly maximum temperature increase is projected to be 1.41 °C and 2.82 °C by 2050 and 2080, respectively. In contrast, the monthly minimum temperature increase is projected to reach +3.2 °C in 2080. The overall seasonal multi-model ensemble average shows an increment in maximum temperature by +1.1 °C and +1.9 °C in 2050 and 2080, with the highest change in the winter, followed by spring, summer, and autumn. Similarly, the future minimum temperature is projected to increase across all seasons by 2080, with increases ranging from 0.4 °C (2030s) to 3.2 °C (2080s). All models consistently project increasing trends in maximum and minimum temperatures, while the majority of the models projected declining future precipitation compared to the base period of 1971–2005. A two-tailed T-test (alpha = 0.05) shows a significant change in future temperature patterns, but no significant changes in precipitation were identified. Changes in daily temperature extremes were found in spring, summer, and autumn, with the largest increases in extreme heat in winter. Therefore, our results support proactive urban planning that considers suitable adaptation and mitigation strategies against increasing air temperatures in urban centers in southwest Ethiopia. Future work will examine the likely changes in temperature and precipitation extremes.

Changes in the pattern of heat waves and the impacts on Holstein cows in a subtropical region.

This study aimed to evaluate the change in the air temperature and the impacts of heat waves using Climate Change Indexes on the physiological and productive responses of lactating Holstein cows. Daily data of maximum and minimum air temperature for 1981-2021 were used. Heat waves were determined using six Climate Change Indexes. Individual data on respiratory rate, rectal temperature, and milk yield were collected in the summers of 2018, 2019, and 2021. The temperature trend analysis showed a significant (p < 0.0001) increase in maximum temperature, minimum temperature, and days in a heat wave. All six indexes increased significantly (p > 0.01). The increase in warm nights (> 20°C) and the hottest days (> 35°C) was the highest since 2010. Heat waves were classified into short (< 5days) and long (> 5days) of greater (> 36°C) or lesser (< 36°C) intensity. During the long and short heat waves of greater intensity, the respiratory rate increased (p < 0.05) until the fourth day. On the other hand, rectal temperature was higher (p < 0.05) from the fourth day until the end of the long heat waves. Therefore, the decrease in milk yield was significantly greater from the fourth or fifth day onwards. Finally, the evaluation method based on indexes was efficient to demonstrate the negative effects on physiological parameters and milk yield and can be indicated to evaluate heat stress in lactating cows.

Temperature Variability and Trust in Vietnamese Rural Households

AbstractThis paper investigates the impact of climate variability on trust in Vietnamese rural households. I contribute to the existing literature, mainly focused on natural disasters, by studying the impact on trust of smooth climate changes. Climate variations are measured using deviations of the minimum temperature in June from the average. I argue that increases in this variable are relevant for the rice, which is the staple food in Viet Nam. Increases in minimum temperatures may reduce rice yields and this, in turn, may affect individuals’ propensity to cooperate. Trust is measured using VARHS survey conducted from 2008 to 2014. Estimation of a linear probability model reveals a significantly positive association between the two variables of interest, which is robust after controlling for several checks.

Assessing the impact of climate change on the agricultural economy in Thailand: an empirical study using panel data analysis.

This study estimates the impact of climate change on the economic growth of the agricultural sector and its variability using a panel dataset from 1995 to 2019 for 76 provinces in Thailand. The panel data analysis consists of unit root tests for identifying stationary characteristics, autoregressive distributed lag (ARDL) bounds for analyzing cointegration, and pool mean group (PMG) estimation for detecting long-run and short-run effects. The cointegration results indicate the existence of long-run equilibrium in the agricultural economy and its variability to climatic and non-climatic variables. Results from the PMG estimation suggest that extreme weather events have a negative impact on the agricultural economy, but increased total rainfall has a positive association with the agricultural economy. The increases in mean average and mean minimum temperatures will reduce the variability of agricultural growth. The obtained results suggest that the productivity of agricultural households and water resources increases the agricultural revenue and reduces its variability for long-term development in the agricultural sector of Thailand.

Spatiotemporal Changes in Frost Indicators in Southeastern Spain (1950–2020): Influence of the East Atlantic Index (EA)

Abstract The southeastern interior of the Iberian Peninsula (Spain) is characterized by a complex orography, which determines a pronounced altitudinal gradient, significant slopes, and marked valleys with important temperature inversion processes. In this work, to analyze the yearly and seasonal evolution of minimum temperatures, six indicators related to minimum temperatures were used: the frost days (FD) and number of days with minimum temperature below −2°C (TNltm2), 10th temperature minimum percentile (TN10p), absolute minimum temperatures (TNn), average minimum temperatures (TNm), and cold-spell duration index (CSDI). For this, the Spearman nonparametric statistical test was used to analyze data from a total of 22 meteorological stations (1950–2020), using a daily resolution of minimum temperatures. Significant changes during the study period were revealed, especially between the 1960s and 1990s. In most cases, there has been a statistically significant increase in the minimum temperatures in the study area, except in the western (most mountainous) part, where the dynamics differed from the rest of the interior of the southeast of the peninsula. Nine large global teleconnection patterns were analyzed in relation to the average minimum temperatures in the study area. These are well-characterized indices for the Northern Hemisphere, which show a very high correlation of the average minimum temperatures with the temporal evolution of the global climate pattern of the east Atlantic (EA) index, especially in the Mediterranean region of the Iberian Peninsula, where it seems to have a very marked influence. Significance Statement We analyzed variation in observed minimum temperatures during 1950–2020 in inland southeastern Spain. Temporal analysis of “east Atlantic index” cycles and their interrelation with frost days and minimum temperatures is very relevant for seasonal meteorological prediction in the study area, where agroindustry represents 20% of GDP. The results show a significant decrease in frost days and an increase in average minimum temperature, especially in coastal and prelittoral areas. The variations are less important mountainous western areas, where frost days have even increased. This is explained by a change in the atmospheric dynamics in midlatitudes of the Atlantic Ocean, quantified by the east Atlantic global teleconnection index, which has a high statistical correlation with Spanish minimum temperatures, especially in winter.

Periods and Amplitudes of Southern Pine Beetle Infestations under Climate Change

The southern pine beetle (SPB), Dendroctonus frontalis Zimmermann, is one of the most destructive insects to pine forests in North and Central America. Historical SPB infestations have shown strong cyclical patterns and are attributed to an array of abiotic and biotic factors with climatic conditions being the dominant. Climate change has been projected to increase SPB infestations; however, its impacts on the cyclical patterns of SPB infestations remain unknown. Here, we estimated the statistical relationship between SPB infestations and climatic and other factors using generalized linear regression modeling and historical data, analyzed the cyclical patterns of SPB infestations via periodogram analysis and explored how these patterns would evolve with the projected future climate change in 11 states of the Southern United States. We found that SPB infestations intensified with increases in seasonal average temperatures and minimum winter temperatures and decreases in spring and winter precipitations. Compared to the historical SPB infestation patterns, climate change was estimated to nearly double SPB infestation frequencies although with smaller amplitudes in the region. Our findings advance the understanding of cyclical patterns of SPB infestations, especially climate change impacts on such patterns, aiding in developing and deploying future SPB management practices and strategies.

Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia

BackgroundAs Indonesia aims for malaria elimination by 2030, provisional malaria epidemiology and risk factors evaluation are important in pursue of this national goal. Therefore, this study aimed to understand the risk factor of malaria in Northern Sumatera.MethodsMalaria cases from 2019 to 2020 were obtained from the Indonesian Ministry of Health Electronic Database. Climatic variables were provided by the Center for Meteorology and Geophysics Medan branch office. Multivariable logistic regression was undertaken to understand the risk factors of imported malaria. A zero-inflated Poisson multivariable regression model was used to study the climatic drivers of indigenous malaria.ResultsA total of 2208 (indigenous: 76.0% [1679] and imported: 17.8% [392]) were reported during the study period. Risk factors of imported malaria were: ages 19–30 (adjusted odds ratio [AOR] = 3.31; 95% confidence interval [CI] 1.67, 2.56), 31–45 (AOR = 5.69; 95% CI 2.65, 12.20), and > 45 years (AOR = 5.11; 95% CI 2.41, 10.84). Military personnel and forest workers and miners were 1,154 times (AOR = 197.03; 95% CI 145.93, 9,131.56) and 44 times (AOR = 44.16; 95% CI 4.08, 477,93) more likely to be imported cases as compared to those working as employees and traders. Indigenous Plasmodium falciparum increased by 12.1% (95% CrI 5.1%, 20.1%) for 1% increase in relative humidity and by 21.0% (95% CrI 9.0%, 36.2%) for 1 °C increase in maximum temperature. Plasmodium vivax decreased by 0.8% (95% CrI 0.2%, 1.3%) and 16.7% (95% CrI 13.7%, 19.9%) for one meter and 1 °C increase of altitude and minimum temperature. Indigenous hotspot was reported by Kota Tanjung Balai city and Asahan regency, respectively. Imported malaria hotspots were reported in Batu Bara, Kota Tebing Tinggi, Serdang Bedagai and Simalungun.ConclusionBoth indigenous and imported malaria is limited to a few regencies and cities in Northern Sumatera. The control measures should focus on these risk factors to achieve elimination in Indonesia.

A multi-tier layer-wise thermal management study for long-scale wire-arc additive manufacturing

High heat input during layer-wise deposition in the Gas Metal Arc-based Wire-Arc Additive Manufacturing (GMA-WAAM) process leads to significant defects such as high residual stress and distortion. However, the choice of layer-wise heat input is constrained due to the requirement of an optimal set of weld parameters. It is essential to study the effect of heat input on the evolution and control of residual stress in the long-scale WAAM fabricated components. Therefore, this study investigates a novel multi-tier heat input strategy represented by four levels for a GMA-WAAM fabricated long-scale thin-walled component. Accordingly, a layer-wise single-, two-, three-, and four-tier heat input strategy in a twelve-layered long-scale thin-walled component is investigated for transient thermal and residual stress distributions through Finite Element Modelling (FEM). Further, a set of validation experiments was performed, which agreed with the predicted results. It is concluded that a reduced heat input during successive layer deposition greatly influences the cumulative heat input into the system. The two-tier heat-input (case 2) system is found suitable among proposed case studies as an appropriate thermal management system with a variation of 6.98% in peak (melt pool) temperature and 198.4 °C increase of minimum temperature during complete deposition. Also, the four-tier heat input (case 4) produced the component's lowest longitudinal and transverse stresses by 13.07% and 25.83%, respectively.

Triangulating Indigenous Place Names and Meteorological Data for a Better Understanding of Climate Change in Same District, Tanzania

Aims: The study sought to triangulate climate-related place names and quantitative evidence of climate change from meteorological data from 1960 to 2021 so as to establish the extent of climate change in Same District. Triangulating the two was important in ascertaining the strategies developed to adapt to climate change.&#x0D; Study Design: The study deployed a mixed research design which allows for the triangulation of qualitative and quantitative methods to gain a better understanding of the studied topic. This was important, as the study needed both qualitative and quantitative data.&#x0D; Methodology: Four villages with climate-related names were purposefully selected. In-depth interviews, structured interviews and direct observations were used in collecting primary data from 152 respondents. Meteorological data were collected from the Tanzania Meteorological Authority (TMA).&#x0D; Results: Seven place names associated with wet conditions were found in the villages. The climatic conditions that led to the invention of the names have changed such that if the villages were to be named today, their names would reflect the dry condition found in the villages. These findings were supported by meteorological data, which indicated a significant decrease in rainfall (b = -1.1 and R = 0.1) and increase in maximum and minimum temperature (b = 0.02) and R = 0.4 and 0.5, respectively). Besides, the intensity and frequency of drought has been increasing over time such that currently (1991 to 2021) the area experiences intensive drought every three years, but did so every ten years, from 1960 to 1990. Farmers’ adaptation strategies included growing early maturing crops (EMCs), changing planting dates, growing drought-tolerant crops (DTCs), reducing the number of meals, and migration. However, most of the strategies are ineffective due to rapid climate change.&#x0D; Conclusion: Farmers’ adoption of strategies which can be effective in adapting to the current rapid climate change is important in having sustainable livelihoods. The strategies may include beekeeping and the cultivation of drought-tolerant crops.

Population Dynamics of Shoot Fly &lt;i&gt;Atherigona soccata&lt;/i&gt;

Population dynamics of shoot fly Atherigona soccata Rondani was carried out at the Sorghum Research field, College of Agriculture, Indore, Madhya Pradesh during kharif, 2019-20. The incidence was assessed in terms of egg, deadheart, adult flies’ activity. The results revealed that the peak incidence was observed during 29th and 30th standard meteorological week (SMW). The fish meal trap correlation studies showed that shoot fly eggs, showed a positive and significant correlation with maximum temperature (r = 0.73). Every unit increase in maximum temperature, results in increase of 0.81 eggs/ 5 plants, while deadheart (r = 0.68) and adult flies (r = 0.79) showed positive significant correlation with minimum temperature. The regression analysis revealed that for deadheart and adult flies, with every unit increase in minimum temperature there was a increase of 16.30% deadhearts and 7.79 adults.

Projecting spatiotemporal changes of precipitation and temperature in Iraq for different shared socioeconomic pathways with selected Coupled Model Intercomparison Project Phase 6

AbstractChanges in precipitation and temperature have crucial implications in the arid region due to their fragile environment. This study was an attempt to estimate possible spatiotemporal alteration of annual and seasonal precipitation and temperature in Iraq. Statistical downscaling of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model (GCM) simulations for different shared socioeconomic pathways (SSP) was utilized. The GCMs were ranked according to their skills in simulating climate research unit (CRU) precipitation and temperature climatology along with their seasonality. Nonlocal model output statistics (MOS) models were implemented using a support vector machine (SVM) for downscaling and projection of selected GCM precipitation and temperature. Results revealed ACCESS‐CM2, BCC‐CSM2‐MR, GISS‐E2‐1‐G and MRI‐ESM2‐0 GCMs are most suitable for Iraq. The spatiotemporal changes in precipitation indicated a substantial decrease to north (up to −7.8%·mm−1) while an increase (around 3.0%) to south for different SSPs. Far future (2060–2099) showed both increase and decrease in precipitation than near future (2020–2059). The precipitation was projected to reduce in winter and increase in summer for all climate zones during both periods. The maximum temperature was projected to increase by 4.5°C to the north and 0.9–2°C to the south. In contrast, the minimum temperature was projected to rise by 1.0–3.5°C to both north and south. Both maximum and minimum temperatures may increase; however, more increases might be in winter and less in summer. The minimum temperature increase will be higher than the maximum temperature in the cold northern region and vice versa. Uncertainty in precipitation and temperature projections was higher for the far‐future period with higher SSPs than for the near‐future period with lower SSPs. The results of this study can guide the development of strategic policies for climate resiliency development in Iraq.

Responses of Vegetation Autumn Phenology to Climatic Factors in Northern China

Understanding the dynamics of vegetation autumn phenology (i.e., the end of growing season, EOS) is crucial for evaluating impacts of climate change on vegetation growth. Nevertheless, responses of the EOS to climatic factors were unclear at the regional scale. In this study, northern China was chosen for our analysis, which is a typical ecologically fragile area. Using the Enhanced Vegetation Index (EVI) and climatic data from 1982 to 2016, we extracted the EOS and analyzed its trends in northern China by using the linear least-squares regression and the Bayesian change-point detection method. Furthermore, the partial correlation analysis and multivariate regression analysis were used to determine which climatic factor was more influential on EOS. The main findings were as follows: (1) multi-year average of EOS mainly varied between 275 and 305 day of year (DOY) and had complicated spatial differences for different vegetation types; (2) the percentage of the pixel showing delaying EOS (65.50%) was larger than that showing advancing EOS (34.50%), with a significant delaying trend of 0.21 days/year at the regional scale during the study period. As for different vegetation types, their EOS trends were similar in sign but different in magnitude; (3) temperature showed a dominant role in governing EOS trends from 1982 to 2016. The increase in minimum temperature led to the delayed EOS, whereas the increase in maximum temperature reversed the EOS trends. In addition to temperature, the impacts of precipitation and radiation on EOS trends were more complex and largely depended on the vegetation types. These findings can provide a crucial support for developing vegetation dynamics models in northern China.

Temporal evolution of threshold temperatures for extremely cold days in Spain

In contrast to research on heat waves, there are no studies in recent years that analyze the temporal evolution of threshold temperatures (Tthreshold) for extremely cold days (ECD). It is unknown whether threshold temperatures have increased more quickly than the minimum daily temperature (Tmin) in recent years.The objective of this study was to analyze the temporal evolution of the minimum daily temperature (Tmin) in a group of Spanish provinces and compare it with the evolution of threshold temperatures.An ecological, retrospective time series study was carried out using daily observations between January 1, 1983 and December 31, 2018 (36 years) in 10 provinces that are representative of the different climate territories in Spain. For each representative observatory in each province, the values of Tmin were obtained for the winter months (November–March). The value of Tthreshold was determined for each province and each year, using dispersion diagrams for the pre-whitened series, with daily mortality due to natural causes displayed on the Y axis (CIEX: A00-R99) and Tmin grouped by 10 degree intervals on the X axis. To determine the temporal evolution of Tmin and Tthreshold for each province, linear models were fitted, with time as the independent variable.During the winter months, Tmin increased at an average rate of 0.2 °C/decade (IC95: 0.1–0.3), while Tthreshold remained practically constant during the period, at 0.1 °C/decade (IC95% -0.1 0.3). These values are much lower than those obtained in the case of heat, both in terms of the evolution of maximum daily temperature and that of Tthreshold.In conclusion, the fact that this trend has been maintained across time in a scenario of climate change, with a slow increase in minimum daily temperatures and constant values of Threshold, suggests a decrease in the number of ECD.

Spatial patterns and climate drivers of malaria in three border areas of Brazil, Venezuela and Guyana, 2016–2018

In 2020, 77% of malaria cases in the Americas were concentrated in Venezuela, Brazil, and Colombia. These countries are characterized by a heterogeneous malaria landscape and malaria hotspots. Furthermore, the political unrest in Venezuela has led to significant cross-border population movement. Hence, the aim of this study was to describe spatial patterns and identify significant climatic drivers of malaria transmission along the Venezuela-Brazil-Guyana border, focusing on Bolivar state, Venezuela and Roraima state, Brazil. Malaria case data, stratified by species from 2016 to 2018, were obtained from the Brazilian Malaria Epidemiology Surveillance Information System, the Guyana Vector Borne Diseases Program, the Venezuelan Ministry of Health, and civil society organizations. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. A Poisson regression model was developed with a conditional autoregressive prior structure and posterior parameters were estimated using the Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. There were 685,498 malaria cases during the study period. Plasmodium vivax was the predominant species (71.7%, 490,861). Malaria hotspots were located in eight municipalities along the Venezuela and Guyana international borders with Brazil. Plasmodium falciparum increased by 2.6% (95% credible interval [CrI] 2.1%, 2.8%) for one meter increase in altitude, decreased by 1.6% (95% CrI 1.5%, 2.3%) and 0.9% (95% CrI 0.7%, 2.4%) per 1 cm increase in 6-month lagged precipitation and each 1 °C increase of minimum temperature without lag. Each 1 °C increase of 1-month lagged maximum temperature increased P. falciparum by 0.6% (95% CrI 0.4%, 1.9%). P. vivax cases increased by 1.5% (95% CrI 1.3%, 1.6%) for one meter increase in altitude and decreased by 1.1% (95% CrI 1.0%, 1.2%) and 7.3% (95% CrI 6.7%, 9.7%) for each 1 cm increase of precipitation lagged at 6-months and 1 °C increase in minimum temperature lagged at 6-months. Each 1°C increase of two-month lagged maximum temperature increased P. vivax by 1.5% (95% CrI 0.6%, 7.1%). There was no significant residual spatial clustering after accounting for climatic covariates. Malaria hotspots were located along the Venezuela and Guyana international border with Roraima state, Brazil. In addition to population movement, climatic variables were important drivers of malaria transmission in these areas.

Influence of Seasonal Climate Variability on Newcastle Disease Spread on Free Range Chicken Production in Kitutu Chache, Kenya

Newcastle Disease is a frequent disease that occurs every year in Kitutu Chache South Constituency. However, the disease is directly or indirectly linked to changes in climate patterns during the outbreak and spread periods. Therefore, the study sought to examine the influence of climate variability on Free Range Indigenous Chicken (FRIC) death occurrence due to the spread of Newcastle Disease. The study adopted a descriptive research design with a sampling size of 500 farmers. The research used purposive selection to administer a questionnaire to poultry farmers in Kitutu Chache. From 1990 to 2019, climate data were obtained from the Kisii Meteorological Services office. The data were analysed using descriptive statistics in STATA-14, and multiple linear regression models were used to examine the relationship between climate variability and NCD. To determine trends in climatic variability, the climate trend data were analysed in R-Studio using the Mann-Kendall trend test with Sense slope estimators. The results showed that there was a significant increase in minimum and maximum temperatures at (p &lt; 0.05); and a decreasing trend in the mean amount of rainfall, though it was not significant (p &gt; 0.05). Moreover, climate factors were found to strongly influence the spread of Newcastle Disease (p &lt; 0.001) hence FRIC death occurrence; rainfall was found to positively influence the spread of Newcastle Disease, while minimum temperatures were found to be negatively correlated. Therefore, the study concluded that climate factors were influencing the spread of the Newcastle Disease Virus. Finally, the study recommended that the county and the national governments of Kenya harmonise climate issues when drafting policies to curb the spread of Newcastle Disease among FRIC.

Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia

The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p &lt; 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.

Climate extremes and their impacts on agriculture across the Eastern Corn Belt Region of the U.S.

The Eastern Corn Belt Region (ECBR) is an important agricultural sector for the U.S. This study analyzes the climate extremes over the contemporary (1980–2018) and future (2036–2099) periods over the ECBR. We evaluated the performance of 32 downscaled models from the U.S. Global Change Research Program's Localized Constructed Analogs (LOCA) of the Coupled Model Intercomparison Project (CMIP5) to simulate extreme temperature and precipitation indices. The LOCA downscaled models were evaluated for the recent past against the National Aeronautics and Space Administration (NASA)-supported gridded observational dataset DAYMET. Results reveal key trends throughout the region that are consistent with previous studies, including significant increases in extreme minimum temperatures, reduction of cold nights, increase of warm nights, and decreases in diurnal temperature ranges. Much of the region demonstrates extreme warming trends in the coldest night of the year (more than 5 °C) and an increase in the heaviest precipitation events over 1980–2018. An optimal model ensemble (OME) was constructed using a Kling-Gupta Efficiency and Bhattacharyya coefficient evaluation to construct a comprehensive ranking procedure. Having outperformed a standard multi-model ensemble approach, the OME was used to evaluate the future changes of extreme climate indices under RCP4.5 and RCP8.5 scenarios. Though the OME showed consistently strong warming throughout the ECBR, variability among the optimal models and across watersheds is quite significant, especially for precipitation indices. Thus, constraining the uncertainty in future climate models, specifically as it relates to agriculture decisions that support climate-resilience, remains a challenge.

Observations on the Frequency, Duration, and Geographical Extent of Summertime Cold-Front Activity in the Southeastern USA: 1973–2020

We analyzed summertime (June–August) cold-front activity via frequency and duration in the southeastern USA during 1973–2020 to summarize and identify the temporal trends of the annual and total number of hours associated with cold fronts, cold-front days, and multi-day cold-front events. Using data from 34 ASOS Network stations, we defined summertime cold fronts as events that lowered the dew point temperature below 15.56 °C (&lt; 60 °F). Additionally, we examined 500 hPa geopotential height anomalies associated with years with cold front frequency/duration deviations of +/− 1.0 SD. The extent of the cold-front activity exhibited a north–south latitudinal gradient with a more southerly latitudinal expression on the east side of the Appalachian Mountains and was negligible south of the 30°N latitude. The cold-front activity was most prominent during the first half of June. Our results suggest that all three metrics of summertime cold-front activity were stable at a regional scale during the 48-year study period with a few (three–five) stations experiencing significant decreases. A regional-scale stability was coincident with significant increases in minimum, maximum, and average summertime temperatures in the southeastern USA. Years with either above-average or below-average cold-front activity were concurrent with synoptic conditions that supported either troughing or ridging in the southeastern USA. We conclude that the observed weakening in the southeastern USA warming hole is the result of external and/or internal forcings unrelated to reductions in anomalously cool summer weather.