Mean Annual Minimum Temperature Research Articles

Analysis of Maximum and Minimum Temperature in Qilian Mountainous, Northwest China

As one of the key elements of climate change, the temperature changes can affects the energy balance and hydrological cycle. The variations and trend of mean annual maximum temperature (Tmax) and minimum temperature (Tmin) were analyzed by using linear regress for 44 stations inside and surrounding the Qilian Mountains for period of 1960-2017. The results have shown that the variations of mean annual Tmax and Tmin have significant increasing in whole study regions. The warming trend of mean annual Tmix is higher than that of Tmax. Both the trend of mean annual Tmax and Tmin in the southern slope is warmer than those in the northern slope of Qilian Mountains. In spring, the warming trend of Tmax is significantly weaker inside than that outside the Qilian Mountains. For all seasons, the trend of Tmax and Tmin is the highest in winter, and is weakest in spring.

Observed and Projected Changes in Temperature and Precipitation in the Core Crop Region of the Humid Pampa, Argentina

The core crop region of the Humid Pampa is one of the most productive agricultural lands around the world and depends highly on climate conditions. This study assesses climate variability, climate extremes, and observed and projected climate changes there, using 1911–2019 observations and CMIP5 model simulations. Since 1970, the annual mean temperature has risen by 1 °C and the mean annual minimum and maximum temperatures by 2 and 0.5 °C, respectively. The frequency of warm days and nights increased, and cold days and nights decreased. Heatwaves became longer and more intense, and cold waves decreased with less frost events. Annual precipitation increased by 10% from 1911, mainly in summer, and years with excess precipitation outnumbered those with a deficit. Both intense precipitation events and consecutive dry days grew, suggesting more annual precipitation falling on fewer days. Projections show a warming of 1 °C by 2035, regardless of the scenario. From then on until 2100, mean temperature will increase by 2 and 3–3.5 °C in the RCP4.5 and RCP8.5 scenarios, respectively. Annual precipitation will grow 8 and 16% from current values by 2100 in the RCP4.5 and RCP8.5 scenarios, respectively. No major precipitation changes are projected in the RCP2.6 scenario.

Predicting land cover changes using a CA Markov model under different shared socioeconomic pathways in Greece

ABSTRACT Land change modeling (LCM) is a complex GIS procedure aiming at predicting land cover changes in the future, contributing thus to the design of interventions that help maintain ecosystem services and mitigate climate change impacts. In the present work, the land change model for Greece, a typical Mediterranean country, has been developed, based on historical information from remotely sensed land cover data. Land cover types based on the International Geosphere-Biosphere Program (IGBP) classification were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product, i.e. MCD12Q1, provided annually from 2001 to 2018 at a spatial resolution of 500 m. Initially, the dominant land cover changes and their driving variables for the decade of 2001 to 2011 were determined and the transition potential of land was mapped using a multi-layer perceptron (MLP) neural network. Four dominant land-cover transformations were found in Greece from 2001 to 2011, i.e. land transformation from Savannas to Woody Savannas, from Savannas to Grasslands, from Grasslands to Savannas, and from Croplands to Grasslands. Driving variables were found to be the Evidence Likelihood of Land Cover, i.e. the relative frequency with which different land cover categories occurred within the areas that transitioned, the Altitude as realized in the Digital Elevation Model of Greece from ASTER GDEM, the Distance from previously changed land and two climate variables i.e. Mean Annual Precipitation and Mean Annual Minimum Temperature. After the model was calibrated, its predictive ability was tested for land cover prediction for 2018 and was found to be 96.7%. Future land cover projections up to 2030 were developed incorporating CMIP6 climate data under two Shared Socioeconomic Pathways (SSPs), i.e SSP126 corresponding to a sustainable future and SSP585, which describes the future world based on fossil-fueled development. The results indicate that major historical land transformations in Greece, do not correspond to land degradation or desertification, as it has been reported in previous works. On the contrary, the land cover transitions indicate that the Woody Savannas gain areas constantly, whereas Grasslands and Croplands lose areas, and forested areas of all types demonstrate moderate gains. Concerning future land cover, the present work indicates that the direction of historical changes will also prevail in the next decade, with the most severe scenario, i.e. SSP585 slowing down the rate of changes and the most sustainable one, i.e. SSP126, accelerating the rate of expansion of woody vegetation land cover type.

Impact of lake surface changes on climate fluctuation within a lake‐affected region

Wetlands are one of the most important aquatic ecosystems that are vulnerable to various factors, including human activity or natural events such as drought. Remote sensing technology is an effective technique for managing and monitoring changes in these ecosystems caused by natural events and human activities. The present study evaluated the effects of changes at Bakhtegan Lake on six climatic parameters in its surrounding environments. Landsat satellite imagery was used to monitor changes in the Bakhtegan Lake surface during times of maximum extent in the period from 2000 to 2015. Support vector machine (SVM) classification was applied to extract the characteristics of the lake surface. Then, the distance of 80 km from the lakeshore was identified as the environment of its influence on the surrounding land, which was divided into three buffers from 0 to 25, 26–55 and 56–80 km. The results showed that a higher accuracy than the index for extracting lake area was achieved using the SVM classification method. Additionally, the climate parameters of mean annual precipitation, relative humidity, and percentage of cloud cover significantly influenced (0.001) lake surface changes in buffer one, indicating the highest impact among all climatic parameters. In buffer two, the significance level of the precipitation parameter decreased to about 0.05, and the annual mean minimum temperature was significantly lower (0.05); however, the mean annual minimum and maximum temperatures were not significant

The response of annual minimum temperature on the eastern central Tibetan Plateau to large volcanic eruptions over the period 1380–2014 CE

Abstract. Volcanic eruptions have a significant impact on global temperature; their consequences are of particular interest in regions that are especially sensitive to climate change, like the Tibetan Plateau. In this study, we develop a temperature-sensitive tree-ring-width standard chronology covering the period 1348–2014 CE using Qilian juniper (Sabina przewalskii (Kom.)) samples collected from the Animaqin Mountains on the Tibetan Plateau. We reconstruct the annual (prior August to current July) mean minimum temperature (Tmin) since 1380 CE and show that our reconstruction explains 58 % of the variance during the 1960–2014 calibration period. Our results demonstrate that in 77.8 % of cases in which a volcanic eruption with a Volcanic Explosivity Index of 5 or greater occurs, temperature decreases in the year of or the year following the eruption. The results of the superposed epoch analysis also indicate that there is a high probability that the Tmin decreases for 2 years after a large volcanic eruption, especially when such eruptions occur in the Northern Hemisphere.

Climate change assessment using spatial climate datasets: Theodore Roosevelt National Park (South Unit), 1895-2019

Climate change poses a major challenge to park managers of the United States National Park Service. Several studies have surveyed system-wide climate change, but limited funds prevent the development of local-scale climate change studies. We examined climate change at Theodore Roosevelt National Park (South Unit) in Medora, North Dakota (USA), using spatial climate datasets. We surveyed the period 1895-2019 to provide a long-term perspective, and more closely analyzed the period 1960-2019, when the quality assurance of the database was highest, concerns over anthropogenic climate change effects were greatest, and relevance to current management was most critical. Our results show moderate changes over the past 60 yr. Interannual and decadal-scale climatic variation dominated long-term climate and weakened the statistical significance of most long-term climate trends. The most pronounced changes were an increase in mean annual minimum air temperature and a decrease in mean annual diurnal temperature range. Mean annual precipitation showed a small increase, while an increase in fall precipitation was the most pronounced seasonal precipitation change. Estimated snow water equivalent and snow fraction increased slightly. Climatic water balance results indicate an increase in mean annual soil moisture storage and annual moisture index. Vegetation growing season changes include an increase in the frost-free season length but a decrease in the length of the thermal growing season. The sign and magnitude of change of individual climate variables is sensitive to the period of record examined. Study results provide a baseline for park managers to assess climate change impacts upon grassland productivity, wildfire hazard, and invasive species, and reveal an opportunity to lengthen the tourism season in this summer peak tourism climate.

Assessing the Impacts of Climate Change on Crop Yields in Different Agro-climatic Zones of India

The study attempts to estimate and predict climate impact on crop yields using future temperature projections under two climate emissions scenarios of RCP 4.5 and 8.5 for three different time periods (2030s, 2050s and 2080s) across Agro-climatic zones (ACZ) of India. During the period 1966-2011, a significant rise was observed in both the annual mean maximum and minimum temperature across ACZs. Rainfall recorded an annual decline in Himalayan Regions and Gangetic Plains and a rise in Coastal Regions, Plateau & Hills and Western Dry Region. Our results showed high heterogeneity in climate impact on kharif and rabi crop yields (with both negative and positive estimates) across ACZs. It was found that rainfall had a positive effect on most of crop yields, but was not sufficient enough to counterbalance the impact of temperature. Changes in crop yield were more pronounced for higher emission scenario of RCP 8.5. Thus, it was evident that the relative impacts of climate change and the associated vulnerability vary by ACZs, hence comprehensive crop and region-specific adaptation measures should be emphasized that helps in enhancing resilience of agricultural system in short to medium term.

Spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia

Climate analysis at relevant time scales is important for water resources management, agricultural planning, flood risk assessment, ecological modeling and climate change adaptation. This study analyses spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia. Our analysis is focused on describing spatial and temporal variability of rainfall in the study area including detection of trends, with no attempt at providing meteorological explanations to any of the patterns or trends. The study is based on gridded monthly rainfall and maximum and minimum temperature data series at a resolution of 4 × 4 km which were obtained from the National Meteorological Agency of Ethiopia for the period 1983–2016. The study area is represented by 558 points (each point representing 4 × 4 km area). Mean annual rainfall of the watershed is > 1600 mm. Annual, June–September (Kiremt), March–May (Belg) rainfall totals exhibit low inter-annual variability. Annual and October-February (Bega) rainfalls show statistically significant increasing trends at p = 0.01 level. May and November rainfall show statistically significant increasing trends at p = 0.01 level. March shows statistically significant decreasing trend at p = 0.1 level. The mean annual temperature of the watershed is 25 °C with standard deviation of 0.31 °C and coefficient of variation of 0.01 °C. Mean annual minimum and maximum temperatures show statistically non-significant decreasing trends. Bega season experienced statistically significant deceasing trend in the maximum temperature at p = 0.01 level. The year-to-year variability in the mean annual minimum and maximum temperatures showed that the 2000s is cooler than the preceding decades. Unlike our expectations, annual and seasonal rainfall totals showed increasing trends while maximum and minimum temperatures showed decreasing trends. Our results suggest that local level investigations such as this one are important in developing context-specific climate change adaptation and agricultural planning, instead of coarse-scale national level analysis guiding local level decisions.

Asymmetric trends of extreme temperature over the Loess Plateau during 1998–2018

AbstractA slowdown in the warming rate of the global mean surface temperature has been observed since late 1990s. However, it is still controversial whether the spatiotemporal variability of extreme temperature events will increase after global warming slowdown, and whether the regional diversity of change trends will increase. Here, we investigated the variations in extreme temperature indices over the Loess Plateau in China since 1961 and focused on the recent global warming slowdown (1998–2018). We found that, during 1961–2018, all the extreme temperature indices showed a significant warming trend and its intensity varied according to extreme temperature indices over different regions. A warming slowdown of annual mean temperature during 1998–2018 was primarily due to the slight increases of annual mean maximum temperatures (TXm) while the annual mean minimum temperature (TNm) still indicated prominently warming trends. During the recent warming slowdown period, the warm indices showed continued intensification of the warming trends, while the cold indices showed a slight cooling trend. Moreover, all extreme temperature indices showed the largest warming trend in summer and a slight cooling trend in winter. Overall, the extreme temperature events have become more diverse in spatial and temporal, indicating that regional climate are more unstable than previously reported for this region. Further analyses revealed that the extreme temperature events during the recent warming slowdown were primarily the result of the natural variability of the climate system, especially the large‐scale ocean–atmosphere interactions of the Pacific and Atlantic oceans.

Projections of future rainfall and temperature using statistical downscaling techniques in Tana Basin, Ethiopia

Global climate changes are becoming main threats to hydrological cycle, which thus influence environmental, social, and economic systems. Climate change studies using global climate models (GCMs) are mostly used for mitigation and adaptation strategies regarding the changing climate. The current GCMs’ data are, however, too coarse to use directly at the regional and local scales for climate change studies. Two widely used statistical downscaling methods, namely LARS-WG and SDSM models, were used to study the current and future climate change of Tana Basin, Ethiopia. Four GCMs (GFCM21, HadCM3, MPEH5, and NCCCS) for LARS-WG and two GCMs (HadCM3 and CanESM2) for SDSM with different emission scenarios were evaluated. Overall results indicated an acceptable response of the models to simulate and forecast climatic variables under HadCM3 and CanESM2 GCMs. Rainfall results downscaled by LARS-WG from the four GCMs indicated high intermodal variabilities and non-consistence; Increasing trend of rainfall showed on three of the GCMs while one GCM showed a decreasing trend in the range of − 9.6% to 45.2%. The four GCMs rainfall average ensemble value showed an increasing trend ranging from 3.9% to 18.8%, which is also consistent with HadCM3 projections ranging from 4.1% to 19.2%. However, the downscaled results from all four models showed increasing maximum and minimum temperature for all time periods. The mean annual maximum and minimum temperature change increased from 0.9 °C to 2.9 °C and 0.6 °C to 2.5 °C, respectively, while annual mean relative change of rainfall ranged from 9.9% to 44.7%. Both SDSM and LARS-WG methods were obtained good monthly rainfall data series than daily rainfall data series in the study area. However, both models with the selected GCMs (HadCM3 and CanESM2) performed reasonably well to simulate temperature than rainfall.

Application of Empirical Land-Cover Changes to Construct Climate Change Scenarios in Federally Managed Lands

Sagebrush-dominant ecosystems in the western United States are highly vulnerable to climatic variability. To understand how these ecosystems will respond under potential future conditions, we correlated changes in National Land Cover Dataset “Back-in-Time” fractional cover maps from 1985-2018 with Daymet climate data in three federally managed preserves in the sagebrush steppe ecosystem: Beaty Butte Herd Management Area, Hart Mountain National Antelope Refuge, and Sheldon National Wildlife Refuge. Future (2018 to 2050) abundance and distribution of vegetation cover were modeled at a 300-m resolution under a business-as-usual climate (BAU) scenario and a Representative Concentration Pathway (RCP) 8.5 climate change scenario. Spatially explicit map projections suggest that climate influences may make the landscape more homogeneous in the near future. Specifically, projections indicate that pixels with high bare ground cover become less bare ground dominant, pixels with moderate herbaceous cover contain less herbaceous cover, and pixels with low shrub cover contain more shrub cover. General vegetation patterns and composition do not differ dramatically between scenarios despite RCP 8.5 projections of +1.2 °C mean annual minimum temperatures and +7.6 mm total annual precipitation. Hart Mountain National Antelope Refuge is forecast to undergo the most change, with both models projecting larger declines in bare ground and larger increases in average herbaceous and shrub cover compared to Beaty Butte Herd Management Area and Sheldon National Wildlife Refuge. These scenarios present plausible future outcomes intended to guide federal land managers to identify vegetation cover changes that may affect habitat condition and availability for species of interest.

파키스탄 신드주의 밀 재배지역 생산량과 기후자료와의 상관분석

This study investigated the relationship analysis between wheat cultivated area and the climate data in Sindh province of Pakistan. The extraction of wheat cultivation area is detected using the remote sensing technique. The analysis of the study area reveals the annual mean maximum and the mean minimum temperature tends to risen with a large range of changes. The trend of average annual precipitation showed a large change, thus it was confirmed that the increase and decrease yield of wheat were depend on the various growth periods of wheat crop. The most influential factors are the annual mean precipitation and the annual mean minimum temperature at the seedling stage of wheat crop. The annual precipitation, annual mean maximum, and the annual mean minimum temperature are significant at the growth period. The annual mean maximum and the annual mean minimum temperatures are significant during the ripening stage of wheat crop in the study area. The results of the study showed that wheat production varies with climate change in the Sindh province. In addition, this study will be used as an important basis for solving crop cultivation areas and production problems caused by climate change in the region.

Stability evaluation of radial growth of Picea schrenkiana in different age groups in response to climate change in the eastern Tianshan Mountains

Global warming causes an unstable response in tree radial growth at high latitudes in the Northern Hemisphere. Additionally, different climatic responses of different age groups of trees have been found due to their different physiological mechanisms. In this study, the response stability and growth trend of three age groups (young < 100a, middle 100–200a, old ≥ 200a) of Picea schrenkiana (Schrenk spruce) to climate change and the causes of the different responses in different age groups were analyzed in the relatively dry climate of the eastern Tianshan Mountains. The results showed that: (1) With the abrupt increase in temperature in 1989, the annual mean minimum temperature became the dominant radial growth-limiting factor of the three age groups of Schrenk spruce. (2) The radial growth of the middle and young groups was more sensitive than that of the old group based on growth-climate correlation analysis. (3) The radial growth of the different age groups had different responses to climate factors, and all age groups were unstable on time scales. (4) The trend of the linear regression simulation of the basal area increment (BAI) indicated that the Schrenk spruce had the same growth trends in different age groups with growth first increased and then decreased; however, the decreased growth rate was higher in the middle and young age groups than in the old age group after the abrupt increase in temperature. Therefore, we should pay active attention to the impact of drought on Schrenk spruce in the eastern Tianshan Mountains and should particularly strengthen the conservation and management of the middle and young age groups.

Tree ring–based minimum temperature reconstruction in the central Hengduan Mountains, China

We developed a tree ring-width chronology of Abies georgei at the timber line in the Big Snow Mountain Scenic Area in northwestern Yunnan, China. The climate-tree growth response analysis indicated that temperature was the predominant regulator of A. georgei growth in this region. An annual mean minimum temperature (AMMT) reconstruction spanning A.D. 1837–2016 was developed with a linear regression model (y = 1.0x − 6e − 5) that accounted for 50.7% of the actual temperature variance during the common period (1960–2016). Based on the reconstructed temperature series, the warmer periods were 1840–1845, 1855–1865, 1880–1895, 1945–1965, and from 1995 until the present day, and the cold periods were 1870–1880, 1900–1930, and 1966–1980. By comparing our results with other regional tree ring records from surrounding areas, a distinctive amount of common warm and cold periods were found, indicating the reliability of our temperature reconstruction and suggesting that the climate in the study area was part of a large-scale climate system.

Study of Spatial and Temporal Characteristics of ETo and Temperature in Khorasan Razavi Province Using CRU TS Dataset and Their Future Projections Based on CMIP5 Climate Models

Evapotranspiration is significantly affected by global climate changes as an essential component of both climate and hydrological cycles. Comprehensive analyses of the spatiotemporal changes of ETo enhance the understanding of hydrological processes and improve water resource management. The main objective of this study is to investigate and predict the temporal trend and spatial distributions of the mean maximum temperature (Tmax), the mean minimum temperature (Tmin) and reference evapotranspiration (ETo) during 1961-2014, 2021-2050 and 2051-2080 over Khorasan Razavi Province using CRUTS3.23 dataset and the outputs of four CMIP5 climate models. The results were as follows: (i) the ability of CRU dataset in simulating monthly mean of Tmax and Tmin is suitable, (ii) generally, ETo increased from north to south across the province (ii) from 1961 to 2014, annual ETo exhibited an increasing continuous trend across the area under study (iii) the mean annual minimum temperature projected to increase by 1.6 under RCP4.5 and RCP8.5 scenarios during two future periods. During 2051-2080, this variable will have an increase by 3ᵒ C under RCP8.5 scenario. The maximum temperature will increase by 4ᵒ C during the middle future period under RCP8.5 scenario. (v) The difference between mean annual ETo values of two periods was statistically significant in all grid points covering this province. The results showed that these increases may lead to the increase in crop water requirements and aggravate the water shortage in this area in view of the increase in ETo in response to ongoing climate change.

Prioritization of the effectiveness rate of various climatic variables on the annual yield of rain-fed winter wheat using different statistical models

The annual yield of different plant species is affected by various parameters such as soil and water properties, climatic variables, etc. Due to the importance of the role of climatic variables on the yield of rain-fed winter wheat (as a strategic and effective plant species in the food security of the people of Iran), in this research the influence of climatic variables including the mean annual maximum temperature (MAT), the mean annual minimum temperature (MIT), the mean annual sunshine (SS), the mean annual relative humidity (HU), the mean annual wind speed (W) and the annual rainfall (R) on the annual yield of rain-fed winter wheat (AYWW) were evaluated based on the records of 10 stations from 1967 to 2016 scattered in Iran. To evaluate the impact of climate variables on the AYWW, the backward time series regression (BTSR), the backward logistic generalized estimating equation (BLGEE) and the backward generalized estimating equation (BGEE) statistical methods were used. All the statistical methods showed that W and SS variables were respectively the most and the least effective variables on the AYWW. Effective variables on AYWW in the BTSR were found to be the W, MIT and R (in 5, 4 and 1 stations out of 10), Effective variables on AYWW in the BLGEE were found to be the W, MIT, R and MAT (in 5, 3, 1 and 1 stations out of 10) and effective variables on AYWW in the BGEE were found to be the W, MIT, R and HU (in 5, 3, 1 and 1 stations out of 10).

MOTEDAS century: A new high‐resolution secular monthly maximum and minimum temperature grid for the Spanish mainland (1916–2015)

AbstractInformation was retrieved from the Annual Climate Summaries (ACS) on average monthly temperatures in Spain for the period 1916–1949, and combined with the digitalized data from the National Climate Data Bank of the Spanish meteorological service (AEMET) to create the new MOTEDAS_century (MOnthly Temperature Dataset of Spain) database of mean monthly maximums (Tmax) and minimums (Tmin). This database was used to calculate a high‐resolution (10 × 10 km) grid that allowed to make a detailed analysis of the temporal evolution of temperature in Spain during the period 1916–2015. Over the period, mean Tmax increased by 1.2°C, while Tmin increased by 1.0°C (this ratio is reversed in the second half of the century). In the last 30 years, however, mean annual Tmax and Tmin trends have not been significant. There are some differences between the new mean annual maximum and minimum temperature series and previous versions, which seem to arise from the much higher number of weather stations analysed, their location and the processing used. There is a discussion on the improved spatial representativeness of the new MOTEDAS_century that provides a more detailed representation of the spatial variability of temperatures in continental Spain.

Changes of Tree Species Composition and Distribution Patterns in Mts. Jiri and Baegun, Republic of Korea over 15 Years

Long-term changes in the abundance and distribution of tree species in the temperate forests of South Korea remain poorly understood. We investigated the changes in tree species composition in temperate mountainous forests using survey data from 130 permanent plots (0.1 ha) from the past 15 years (1998–2012) distributed across Mts. Jiri and Baegun, South Korea. The tree communities showed positive net changes in terms of stand density, richness, diversity, and evenness. At the species level, the change in relative species composition has been mainly driven by species such as Quercus mongolica, Carpinus laxiflora, Quercus serrata, Quercus variabilis, Styrax japonicus, Lindera erythrocarpa, and Pinus densiflora. These changes were categorized into five groups representing gradual increase or decrease, establishment, extinction, or fluctuation in species populations. At the community level, the changes in species composition showed consistent and directional increases in the annual rate of change for the mean species traits, including stand prevalence, pole growth rate, adult growth rate, and adult stature. Based on additive models, topographic variables (elevation, latitude, longitude, slope, topographic wetness index, and curvature) were more strongly associated with the distribution of species diversity than climate variables (annual mean minimum and maximum temperatures, temperature seasonality, annual rainfall, rainfall seasonality). Elevation was the most significant driver, followed by latitude and longitude. This study reveals the dynamics of change in tree species composition and distribution along topographical and climate gradients in South Korea and contributes to a broader understanding of temperate forest ecosystems for the purpose of better forest management.

Selection for Winter Survivorship in Lowland Switchgrass

Development of switchgrass (Panicum virgatum L.) as a sustainable biomass crop for conversion to bioenergy requires substantial increases in biomass yield. Because switchgrass is highly photoperiodic, one approach toward this goal is to collect germplasm populations from the Southern USA, then screen and select them in northern environments where they represent a delay in flowering time of up to 6 weeks compared with local ecotypes. This delay in flowering has been linked to increases in biomass yield of up to 50%. The objective of this study was to conduct and evaluate selection progress for winter survivorship in 14 southern lowland populations of switchgrass. The populations originated from USDA Plant Hardiness Zones (PHZ) 7 or 8 (mean annual extreme minimum temperature = − 12.2 °C) and the selection and evaluation were conducted in PHZ 4 or 5 (mean annual extreme minimum temperature = − 28.8 °C). Seven of the 14 populations responded to selection, with increases in winter survivorship and/or biomass yield across four evaluation locations. Winter survivorship and biomass yield were highly correlated with each other, so that increases in survivorship usually translated to increases in biomass yield. The top-ranked population represented the third cycle of selection within the cultivar Kanlow, indicating that the greatest gains from selection represented longer-term efforts than a single generation of field-based selection. This study verified that alleles for winter survivorship and plants capable of surviving in PHZ 4 or 5 can be found across a broad geographic area in the Southern USA, albeit at very low frequencies in most populations.

KONYA KAPALI HAVZASI (TÜRKİYE) YILLIK SICAKLIK VERİLERİNİN TREND ANALİZİ VE DEĞİŞİM NOKTALARININ BELİRLENMESİ

Climate change is expressed as major changes in the average climate which exist for many years. Although climate change occurs on a global scale, the impact of climate change varies from region to region. Therefore, the analysis of the variations in meteorological variables is a very vital issue in monitoring of climate change. In this study, assignment of the change points and trends of annual mean temperature, maximum temperature and minimum temperature data of the Konya Closed Basin in Turkey is examined. For this aim, air temperature data of 11 meteorology station were used. The change point of temperature time series data was examined using the Pettitt test, Standard Normal Homogeneity test and Buishand Range test. The Mann-Kendall, Spearman Rho and Innovative Şen Trend methods were used to determine trends of air temperature.