Increase In Minimum Temperature Research Articles

Downscaling climate parameters in Fars province, using models of the fifth report and RCP scenarios

Climate change is responsible for many extreme weather events on the Earth, including sea level rising, drastic shifts in temperature and precipitation regimes, and changes in flood and drought frequency. In the present study, based on IPCC's latest report, outputs of three GCMs, the EC-EARTH, the HadGEM2-ES and the MIROC5 were downscaled by the LARS-WG model and under RCP4.5 and RCP8.5 scenarios. Also, variations in precipitation, maximum and minimum temperatures for the time series 2021–2040, 2041–2060 and 2061–2080 have been projected and the precipitation extreme values in Gumbel distribution were evaluated. For this purpose, the climate records obtained from Shiraz, Lar and Abadeh synoptic stations in Fars province were used to establish the baseline period (1985–2010). The results of all the stations show that Changes in maximum and minimum temperatures under RCP4.5 and RCP8.5 scenarios have increased. The increase in minimum temperature for the baseline period compared to the upcoming period 2021–2040 under the selected scenarios were 1.43 and 1.65C, respectively. The increase in precipitation for the baseline period compared to the upcoming period (2021–2040) under the two scenarios were up to 2.93 and 1.95, respectively. Furthermore, longer return periods are accompanied by higher amounts of probable maximum precipitation under RCP4.5 and RCP8.5, where extreme precipitation is showing higher level of rise under the latter scenario.

ПРОСТРАНСТВЕННО-ВРЕМЕННАЯ ДИНАМИКА АМПЛИТУДЫ СУТОЧНЫХ КОЛЕБАНИЙ ТЕМПЕРАТУРЫ АТМОСФЕРНОГО ВОЗДУХА НА ДАЛЬНЕМ ВОСТОКЕ РОССИИ

To identify the spatial, inter-annual and inter-seasonal dynamics of the daily amplitude of air temperature, the author uses the data from 99 weather stations in the Russian Far East for the period of 2000– 2019. It is shown that the maximum values of the daily amplitude are typical for the continental territories in the north, while the minimum ones – for the continental areas in the south, and for sea stations. For almost all weather stations, the amplitude is minimal in winter – in December and January. In general, a clear annual range and significant differences in values during the year were revealed for continental stations. The maximum at the continental northern stations is shown for April, while at the continental southern stations – in February. Marine areas are characterized by a smoothed seasonal course of the studied parameter, with a certain dimly marked maximum in February-March. A decrease in the day–to-day dynamics of air temperature amplitude over the period of 2000–2019 was revealed due to a faster increase in minimum temperatures as compared to maximum, which is typical for most of the weather stations. At the same time, an increase in the amplitude is shown at some stations, which is associated with a higher positive trend of maximum temperatures.

Projection of reference evapotranspiration over Ondo State using an ensemble of climate models

Reference evapotranspiration (ETo) is a significant component of the hydrological cycle useful to develop integrated water resources management (IWRM). Climate change may have potential effects on ETo over Ondo State. It is essential to determine uncertainties in ETo for designing future water-holding structures and projecting crop water requirements (CWR). The sensitivity analysis over the study area indicated that an ensemble of six general circulation models (GCMs) from the 5th Coupled Model Intercomparison Project (CMP5) under Representative Concentration Pathways (RCP 4.5) projected increases in maximum and minimum temperatures (Tmax and Tmin) for the 2050s (2035-2065) and 2080s (2070-2100). The simulation run outputs showed that the projected ETo increased for the periods 2050s and 2080s in response to the baseline period (1975-2005), with larger increases in the 2080s. Generally, the predicted increases in ETo over Ondo State could be attributed to the expected increases in Tmax and Tmin.

Vegetative shoot flush dynamics of ‘Pera’ sweet orange on three rootstock cultivars

The dynamics and intensity of new shoot flushes of ‘Pera’ sweet orange scions [Citrus × sinensis (L.) Osbeck] grafted onto ‘Rough’ lemon (Citrus × limonia var. jambhiri Lush.), ‘Swingle’ citrumelo [Citrus × aurantium var. paradisi x Poncirus trifoliata (L.) Raf.] and ‘Sunki’ mandarin (Citrus reticulata ‘Sunki’) rootstocks were evaluated in the field at a citrus farm located in a northern region of the state of Sao Paulo, Brazil. Every 20 days for 16 months, new shoots were counted within a square frame of 0.25 m2 set on the central portion of the canopy and classified based on their phenological stages. Trees on ‘Swingle’ rootstock produced a lower area under the flush shoot dynamics curve (AUFSD) and mean number of new shoots than trees on ‘Rough’ lemon or ‘Sunki’ mandarin. For trees on all three rootstocks, new shoot intensities varied significantly over time with the greatest number of new shoots developing during late spring and early summer. Increases in minimum air temperature and available soil water were important indicators of overall emergence of new shoots. 

CLIMATIC CHARACTERISTICS OF THE COLD PERIOD IN UFA

The article presents the results of a study of the climatic characteristics of the cold period in the city of Ufa of the Republic of Bashkortostan in the modern period. For the analysis, the authors used traditional processing methods. To identify climate changes, different base periods were considered (1961-1990, 1981-2010, 1991-2020). In some cases, time series of long-term observations were available only since 1973, so in these cases two base periods were distinguished. The statistical characteristics and changes in air temperature and its amplitude, the dates of the beginning/end and duration of the cold period, the amount of precipitation, relative humidity, the height of the snow cover and its moisture reserves, the dates of establishment/destruction and the duration of the snow cover are analyzed. Correlations between climatic indicators are shown. The study revealed that in all months of the cold period there is a tendency to increase air temperature, while the greatest contribution is made by an increase in minimum temperatures. A steady reduction in the duration of the cold period was found due to the shift of the start date to a later date, and the end date to an earlier one. The amount of precipitation tends to increase. Due to the reduction of the cold period, the duration of the snow cover in the city of Ufa decreases.

Temperature extremes and their future projections in selected Indian cities along with their meteorological subdivisions and temperature homogeneous zones

Various observational and modelling studies indicate rise in surface air temperature and its extremes at several places in the world. With the availability of more data both from observations and models, it is possible to comprehensively examine future projections in order to get meaningful climate information and identify strong climate signals anywhere. This study is focused on rise in surface air temperatures and the associated temperature related extreme events such as warm days & nights and cold days and nights at four city clusters in India such as Delhi, Mumbai, Chennai and Guwahati. Dynamically downscaled future projections at the four selected city clusters are examined using RegCM CORDEX simulations. Further, selected CMIP model projections are used. In this study, uniformity of the trends in the selected indices found in each city are tested against those found in the corresponding Meteorological Sub-Divisions and Temperature Homogeneous Zones. Increase in the surface air minimum and maximum temperatures along with the frequency of occurrence of warm nights at all the four city clusters are the strong signals of climate projection obtained from this study.

Trend Analysis of Temperature and Rainfall of Rajasthan, India

Increasing temperature and declining and erratic rainfall is one of the greatest global challenges. This study presents the trend analysis of temperature and rainfall in five divisional headquarters of Rajasthan, namely, Bikaner, Jaipur, Jodhpur, Kota, and Udaipur. The historic data of minimum and maximum temperature and rainfall for a period of 49 years from 1971 to 2019 were collected from Climate Research and Services, India Meteorological Department, Pune. Detection of trends and change in magnitude was done using the Mann–Kendall (MK) test and Sen’s slope, respectively. The results of the study indicated a significant increase in both minimum and maximum temperature over time for all the five stations. However, rainfall showed a nonsignificant increasing trend for Kota and Udaipur district, whereas Bikaner, Jaipur, and Jodhpur detected a negative trend.

Effect of different land use land cover on surface heat budget – A case study from a tropical humid region of India

Surface energy balance largely depends on the state of atmospheric variables and a change in their interrelation propagates a change in the balance. Other than the meteorological factors, land use land cover (LULC) also plays a major role deciding the proportional participation of different heat fluxes in the heat balance of an area. Delineating the effects of LULC on energy budget is rather easy over extensive areas than doing it locally, especially over the regions where the influence of any certain climatic characteristics is pre-dominant. Burdwan district in the Indian state of West Bengal is located under tropical Gangetic type climate where the influence of monsoon is at large. Mann-Kendall test at 95% confidence interval showed significant trends of the atmospheric variables over three decades there and t-test at 5% confidence level found significant difference in variables over different LULCs. The Pearson’s correlation coefficients between LST and NDVI and NDBI are more than 0.81 and −0.74 respectively over different LULCs. Sensible heat flux (SHF) is found to be dominant in pre-monsoon and latent heat flux (LHF) in monsoon seasons, when an increase in minimum temperature about 1.2–2°C is also noticed. Albedo, net radiation, SHF and LULC are demarcated as the principal factors by PCA analysis. The screen temperature is related to the heat fluxes and LULC by the equations – ‘t = −57.0166 + 1.402SHF-0.203LHF+0.25vegetation cover+0.064 urban land’ in the western part and ‘t = 33.88–0.19SHF-0.047LHF-0.29 vegetation cover+0.76 settlement area’ in eastern part of the district. Based on the interrelationship of heat fluxes and LULC, LHF is predicted to decrease in near future by 0.17% whereas SHF can increase up to 1.58% with an increase of LST and screen temperature by 1.2% and 0.88% respectively if the present rate of change in LULC sustains.

The long-term trend in the diurnal temperature range over Sri Lanka from 1985 to 2017 and its association with total cloud cover and rainfall

This study is focused on studying the long-term trend of the diurnal temperature range (DTR) in three temperature zones in Sri Lanka using daily maximum and minimum temperature data set for the recent 33-year (1985–2017). We investigate the potential reasons for the long-term trend in the DTR by studying the response of the DTR to Total Cloud Cover (TCC) and rainfall on a seasonal basis. On an annual basis, results indicate that the DTR significantly decreased per decade by −0.14 °C, −0.16 °C, and −0.18 °C over the high elevation temperature zone (HT), low-elevation temperature zone one (LT-2), and low elevation temperature zone two (LT-2), respectively. The annual decreasing trend of DTR in three temperature zones is mainly due to the larger increase in minimum temperature over the HT (0.13 °C/decade), LT-1 (0.23 °C/decade), and LT-2 (0.14 °C/decade) zones than the maximum temperature from 1985 to 2017. Furthermore, a decreasing trend in DTR is observed during the southwest monsoon (SWM), first inter-monsoon (FIM), second inter-monsoon (SIM), and northeast monsoon (NEM) seasons, where the most prominent decreasing trend in HT, LT-1, and LT-2 is seen in NEM (−0.19 °C/decade), SIM (−0.24 °C/decade), and SWM (−0.40 °C/decade) seasons, respectively. The strong inverse correlation between the DTR and TCC in all seasons indicates that increasing TCC influences the decrease in DTR over the HT, LT-1, and LT-2 zones. Concomitant increasing trends in rainfall during NEM, FIM, and SIM seasons may be one of the possible causes of the DTR decreases in the aforementioned seasons over three temperature zones in Sri Lanka.

Modeling wheat and triticale winter hardiness under current and predicted winter scenarios for Central Europe: A focus on deacclimation

Winter hardiness depends on the ability of plants to tolerate a wide spectrum of environmental stresses, which can be affected by climate change in complex ways. Here, empirical Partial Least Squares Regression (PLSS) models of winter survival (WS) of winter wheat (Triticum aestivum L.) and triticale (Triticosecale x Wittmack) were created using data from six years of field experiments at multiple locations throughout Poland. These included 553 winter wheat and 155 triticale accessions. Our aims were to: 1) predict WS on the basis of meteorological data; 2) identify the most critical weather events affecting WS of winter wheat and triticale under Polish conditions; and 3) predict WS for the simulated winters of 2040, 2060 and 2080 under climate change scenarios RCP2.6, RCP4.5, RCP6.0 and RCP8.5 for the experimental site with the lowest mean WS rate during the field experiments. The empirical models showed a high R2 for winter wheat (0.751), and a low R2 for winter triticale (0.160), because of the low winter damage to triticale observed during the experiments. The key climate factors affecting WS varied between species. Winter wheat was affected by winter severity, the number of freezing-thawing cycles, the thermal vegetation index and the freezing index in various winter months. Triticale was affected by late winter ice encasement and high numbers of freeze-thaw events. The predictions indicated that the WS of both winter wheat and triticale may decrease in the future, especially when more extreme climate change scenarios were considered. The main issue will be cold deacclimation connected with climate warming which will be more important for WS than the general increase in minimum winter temperatures. This finding indicates that deacclimation tolerance should be included in wheat and triticale breeding programs as a trait crucial for WS under future winters, at least in Central Europe.

Modeling of climate change in cold arid regions of north western Himalayas using multiple linear regression (MLR)


 The present study aimed at modeling the impacts of climate change on precipitation and temperature and its trend in the context of changing climate in cold arid regions of north western Himalayas using multiple linear regression (MLR) model. The study was carried out in three different time slices viz., near future (2017-2045), mid future (2046-2072) and far future (2073-2099). The study includes the calibration of the observed climate data (maximum temperature, minimum temperature and precipitation) for fourteen years (2002-2015) and the outputs of downscaled scenario A2 of the Global Climate Model (GCM) data of Hadley Centre Coupled Model, (HadCM3) was used for validation, for the future. Daily climate (maximum temperature, minimum temperature and precipitation) scenarios were generated from 1961 to 2099 under A2 defined by Intergovernmental Panel on Climate Change (IPCC). During calibration, the maximum temperature, minimum temperature and precipitation showed decreasing trend. During validation, the maximum temperature showed an increasing trend in near future (2017- 2045) and decreasing trend in mid (2046-2072) and far future (2073-2099). While as, the minimum temperature and precipitation showed an increasing trend and decreasing trend respectively, in three futuristic phases. After validation, on comparison with the measured data, the variation in maximum temperature was found -2.59 oC in near future, -3.17 oC in mid future and -3.41 oC in far future. Similarly, for minimum temperature and precipitation, the variations with observed data were found 0.91 oC and -32.2 mm, respectively in near future, 2.01 oC and -34.6 mm, respectively in mid future, 4.08 oC and -3.4 mm, respectively in far future. These changes may be found due to global warming which lead to decrease in average annual precipitation and increase in average minimum temperatures causing the melting of glaciers.

Characterizing winter season severity in the Midwest United States, Part I: Climatology and recent trends

AbstractSevere winter weather is a staple of Midwest United States (U.S.) climate and is an important natural hazard that has significant economic and environmental impacts. Winter season severity varies both spatially and temporally in the Midwest, and past studies have documented significant changes in Midwest winter characteristics, including increases in temperature and decreases in snow depth. In this study, we use the Accumulated Winter Season Severity Index (AWSSI) to characterize winter severity across the Midwest and assess its variability and change on various spatial and temporal scales during the 1951–2020 period. AWSSI is derived from daily records of snowfall (SF), snow depth (SD), maximum surface air temperature (TMAX), and minimum surface air temperature (TMIN) during the winter season. The daily total AWSSI index value reflects the sum of points accumulated from daily values of each of these four variables surpassing pre‐determined thresholds, and the total season sum reflects the overall winter season severity. We find AWSSI provides a unique perspective by which to describe climatological differences in winter season character in the Midwest. Namely, over three quarters of winter season days accumulate points in the northern Midwest, compared to just over half in the southern Midwest. Meanwhile, the relative contribution of extreme winter days to total winter severity is much larger in the southern Midwest than farther north. In addition, we find overall winter season severity has significantly decreased at only a quarter of stations and the frequency of extreme winter days has significantly decreased at only a fifth of stations, despite widespread increases in winter daily maximum and minimum temperature. The results suggest Midwest U.S. winter season severity as described by the AWSSI has not significantly changed over the past 70 years.

Bias correction of regional climate model simulations for the impact assessment of the climate change in Egypt.

This study projected the future temperature change for Egypt during the late of this century (2071-2100) for three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5), by correcting regional climate model (RCM) simulations of average, maximum, and minimum daily temperature with reference to observed data of 26 stations. Four commonly used methods of bias correction have been applied and evaluated: linear scaling, variance scaling, and theoretical and empirical quantile mapping. The compromise programing results of the applied evaluation criteria show that the best method is the variance scaling, and thus it was applied to transfer the correction factor to the projections. All temperature indices are expected to increase significantly under all scenarios and reach the highest record by the end of the century, i.e., the expected increase in average, maximum, and minimum temperature ranges between 4.08-7.41°C, 4.55-7.89°C, and 3.88-7.23°C, respectively. The largest temperature rise will occur in the summer, with the highest increase in the maximum (minimum) temperature of 10.9°C (10°C) in July and August under RCP8.5. The maximum (minimum) winter temperature, on the other hand, will drop by a maximum of 2°C (1.35°C) under RCP2.6. The Western Desert and Upper Egypt are the regions most affected by climate change, while the northern region of Egypt is the least affected. These findings would help in impact assessment and adaptation strategies and encourage further investigation to evaluate various climate models in order to obtain a comprehensive assessment of the climate change impacts on different hydrometeorological processes in Egypt.

Temperature variability over urban, town, and rural areas: The case of Pakistan

AbstractThis study investigates the evolution of temperatures at several locations in Pakistan. Data on annual and seasonal minimum (Tn) and maximum (Tx) temperatures from 1950 to 2013 of urban (16 stations), town (11 stations), and rural (nine stations) areas are analysed to establish the mean decadal rate of change in urban, town, and rural temperatures. The homogeneity of the data was assessed using HOMER 2.6. To measure the temporal intensity of change in temperature, the data were split into two different periods: 1950–1981 (P1, phase of less urbanization) and 1982–2013 (P2, phase of highly urbanized period) and were analysed separately for both phases of 32 years each. The per decade changes of annual minimum and maximum temperatures (dTna and dTxa, respectively) over most stations show an increase in temperatures. The trends of annual and seasonal dTn and dTx observed over urban, town, and rural stations during P2 are significantly higher than those observed during P1. The increase in minimum temperatures is more significant than that in maximum temperature, and it is also more significant on urban stations than the town and rural stations. However, the maximum temperatures increase more at town stations than urban and rural stations. Overall, the tendencies in temperatures reflect less change in summer temperatures than other seasons of the year over the whole period.

Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

Land use land cover (LULC) change is one of the main drivers contributing to global climate change. It alters surface hydrology and energy balance between the land surface and atmosphere. However, its impacts on surface air temperature have not been well understood in a dynamic region of LULC changes like Southeast Asia (SEA). This study quantitatively examined the contribution of LULC changes to temperature trends in Myanmar and Thailand as the typical parts of SEA during 1990–2019 using the “observation minus reanalysis” (OMR) method. Overall, the average maximum, mean, and minimum temperatures obtained from OMR trends indicate significant warming trends of 0.17 °C/10a, 0.20 °C/10a, and 0.42 °C/10a, respectively. The rates of minimum temperature increase were larger than maximum and mean temperatures. The decreases of forest land and cropland, and the expansions of settlements land fractions were strongly correlated with the observed warming trends. It was found that the effects of forest land converted to settlement land on warming were higher than forest conversion to cropland. A comprehensive discussion on this study could provide scientific information for the future development of more sustainable land use planning to mitigate and adapt to climate change at the local and national levels.

Statistical downscaling of global circulation models to assess future climate changes in the Black Volta basin of Ghana

Statistical Downscaling Model (SDSM) is a powerful model for climate change assessment. However, its usage remains very gray with limited studies on climate change (CC) assessment in Ghana. This study explored the applicability and suitability of SDSM for CC assessment in the Black Volta section of Ghana. The hydro-climatic parameters of Hadley center Coupled Model, version 3 (HadCM3) under the A2 and B2 Emissions Scenarios and the second-generation Canadian Earth System Model (CanESM2) under the Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 of the Coupled Model Intercomparison Project Phase 5 were downscaled with SDSM over the Black Volta section in Ghana using 40-year ground station data. The R2, NSE, Pbias, RMSE, and KGE of the calibrated and validated results ranged from 64% to 99%, 50–99%, -0.30–21.1, 0.01 °C–1.48 °C and 49%–99%, respectively for both models indicating a good agreement between the historical and the simulated data. The future climate change showed an increase in average minimum temperature of 0.05 °C (2020s), 0.11 °C (2050s), 0.21 °C (2080s) under the A2 scenario, 0.05 °C (2020s), 0.13 °C (2050s), 0.19 °C (2080s) under the B2 scenario, 0.01 °C (2020s), 0.02 °C (2050s), 0.02 °C (2080s) under the RCP 2.6, 0.06 °C (2020s), 0.13 °C (2050s), 0.19 °C (2080s) under the RCP 4.5, and 0.06 °C (2020s), 0.15 °C (2050s), 0.32 °C (2080s) under the RCP 8.5. For Maximum temperature, the average changes showed an increase of 0.17 °C (2020s), 0.36 °C (2050s), 1.14 °C (2080s) under the A2 scenario, 0.18 °C (2020s), 0.39 °C (2050s), 1.01 °C (2080s) under the B2 scenario, 0.03 °C (2020s), 0.16 °C (2050s), 0.17 °C (2080s) under the RCP 2.6, 0.02 °C (2020s), 0.26 °C (2050s), 0.45 °C (2080s) under the RCP 4.5, and 0.03 °C (2020s), 0.29 °C (2050s), 0.61 °C (2080s) under the RCP 8.5. The change in precipitation is not uniform with increase and decrease depending on the months and the scenarios. Overall, A2, B2 scenarios showed higher decrease in precipitation compared to RCPs scenarios. The SDSM is suitable for CC assessment and impact studies. The results from this study are to support the Climate Action, goal 13 of the SDGs.

Projected changes in the near‐future mean climate and extreme climate events in northeast Thailand

AbstractThis study provides an assessment of changes in mean and extreme climate in northeast Thailand, focusing on the near‐future period (2021–2050). Spatiotemporal changes in climate extremes and return values are investigated compared to 1981–2010. Climate model‐related uncertainties are quantified using 14 models from the Coupled Model Intercomparison Project phase 5 (CMIP5) and 8 models from phase 6 (CMIP6). CMIP6 models have a higher sensitivity to external forcings as the CMIP6 ensemble suggests an increase in maximum and minimum temperatures by 1.45°C (0.8–1.9°C) and 1.54°C (1.1–1.9°C) under the high emission scenario, which is greater than by CMIP5 ensemble: 1.10°C (0.5–1.7°C) and 1.13°C (0.7–1.6°C), respectively. No significant changes in annual rainfall are projected, although it will be temporally more uneven with decreases (6–11%) during the pre‐rainy season (March–May) and increases (2–8%) during the rainy season (June–October). The bootstrap analysis technique shows the inter‐model uncertainties for rainfall projections in CMIP6 have reduced by 40% compared to CMIP5. The annual number of hot days will increase more than twofold and warm nights, more than threefold. Near‐future will experience an increase in the rainfall intensity, a decrease in the number of rainy days, and an increase in the 20‐year return values of annual maximum 1‐day rainfall and consecutive 5‐days rainfall (>30%). In addition, the rainy season will be shortened in the future as onset and retreat are delayed, which may have implications in agricultural activities in the basin since cultivation is primarily rainfed. These findings suggest that anthropogenic activities will significantly amplify the climate extremes. The study results will be useful for managing climate‐related risks and developing adaptation measures to improve resilience towards potential climate hazards.

Warming Increases the Carbon Sequestration Capacity of Picea schrenkiana in the Tianshan Mountains, China

As an essential part of terrestrial ecosystems, convenient and accurate reconstruction of the past carbon sequestration capacity of forests is critical to assess future trends of aboveground carbon storage and ecosystem carbon cycles. In addition, the relationship between climate change and carbon sequestration of forests has been vigorously debated. In this study, dynamic change of carbon sequestration capacity in aboveground biomass of Picea schrenkiana (hereinafter abbreviated as P. schrenkiana) in the Tianshan Mountains, northwestern China, from 1850–2017, were reconstructed using dendrochronology. The main climate drivers that affected carbon sequestration capacity in aboveground biomass of P. schrenkiana were then investigated. The results showed that: (1) tree-ring width and diameter at breast height (DBH) of P. schrenkiana obtained from different altitudes and ages were an effective and convenient estimation index for reconstructing the carbon sequestration capacity of P. schrenkiana. The carbon storage of P. schrenkiana forest in 2016 in the Tianshan Mountains was 50.08 Tg C calculated using tree-ring width and DBH, which was very close to the value determined by direct field investigation data. (2) The annual carbon sequestration potential capacity of P. schrenkiana exhibited an increasing trend from 1850–2017. Temperature, especially minimum temperature, constituted the key climatic driver resulting in increased carbon sequestration capacity. The contribution rates of temperature and minimum temperature to the change of P. schrenkiana carbon sequestration capacity was 75% and 44%, respectively. (3) The significant increase of winter temperature and minimum temperature led to warming in the Tianshan Mountains, resulting in a significant increase in carbon sequestration capacity of P. schrenkiana. The results indicate that, with the continuous increase of winter temperature and minimum temperature, carbon sequestration of P. schrenkiana in the Tianshan Mountains is predicted to increase markedly in the future. The findings of this study provide a useful basis to evaluate future aboveground carbon storage and carbon cycles in mountain systems possessed similar characteristics of the Tianshan Mountains.

Development of agro-climatic grape yield model with future prospective

Agriculture sector is most vulnerable to climate change. To predict the crop yield in accordance with the changing climate is a need of hour than choice. To know the climate in advance is crucial for grape growing farmers and grape export agencies for its better planning and security of grape industries from climate change perspective. In the present study, the Agro-Climatic Grape Yield (ACGY) model is developed on monthly scale climatic parameters using correlation, significance and multi-regression analysis approach. The developed model is statistically tested for its predictive ability. The discrepancy ratio, the standard deviation of discrepancy ratio, mean percentage error and standard deviation of mean percentage error for the developed model is obtained as 1.03, 0.19, 0.03% and 0.19 respectively. Sensitivity analysis is carried out for the developed ACGY model using the parametric sensitivity method. In order to know the grape yield for future using developed ACGY model, climate scenarios are generated under Canadian Earth System Model (CanESM2) for three emissions Representative Concentration Pathways (RCP) as RCP2.6, RCP4.5, and RCP8.5. Model response variability is carried out to understand the variation of grape yield. It is observed that grape yield is showing adverse variation with the increase in minimum temperature in January and November months, and precipitation in August and November months. Whereas, minimum temperature in April and sum of monthly mean evapotranspiration showing accordance effect on the grape yield. It is recommended the use of ACGY model for grape yield estimations applicable for the present and future climate of the study area based on the predictive capability of developed model.

Spatiotemporal Analysis of the Frost Regime in the Iberian Peninsula in the Context of Climate Change (1975–2018)

Climate change is having many effects in the agricultural sector, which are being studied worldwide. Undoubtedly, warmer winters and earlier springs produce changes in frost regimes and severity that will affect the sustainability of agricultural production in the area. The Mediterranean region and the Iberian Peninsula (IP) are among the areas where the greatest impact of climate change is expected. Daily data from 68 weather stations of the IP belonging to the European Climate Assessment and Dataset (1975–2018) were used to conduct a spatiotemporal study of the frost regime. The variables calculated include the probability of three frost types according to their severity, frost day, mean absolute minimum yearly temperature, first frost day, last frost day, and frost-free period. These variables were integrated into a geographic information system, which allowed the graphical visualization of their patterns using of geostatistical interpolation techniques (kriging). Changes in frost variables were investigated using the Mann–Kendall test and Sen’s slope estimator. A general reduction in the number of frosts per year is observed (values between −0.04- and −0.8-day frosts per year), as well as an increase in the mean absolute minimum temperature (values between 0.04 and 0.10 °C per year), with very high significant trends throughout the territory. The reduction in the number of frosts is more pronounced at a higher elevation. Frost dates vary greatly due to the orographic characteristics of the IP. The generalized trend is of a significant delay of the autumn frosts (values between 0.4 and 1.06 days/year), as well as early spring frosts (between −0.429 and −1.29 days/year), and as a consequence a longer frost-free period, all changes were much stronger than those found in other regions of the world. These effects of climate change must be mitigated by modifying species, varieties, and cultivation techniques to guarantee sustainable agriculture.