Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955–2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann–Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.     

Long-term trend analysis for temperature in the Jinsha River Basin in China

On the basis of the mean annual and seasonal temperatures from 30 meteorological stations in the Jinsha River Basin (JRB) from 1961 to 2008, the temperature trends are analyzed by using Mann–Kendall test and linear trend analysis. There is an increasing trend in mean annual and seasonal temperatures during this period, and the increasing trends in winter seem more significant than those in the other three seasons. The mean annual temperature has increased by 0.0158°C/year during the last 48 years. There are more than 70% of stations exhibiting increasing trends for annual and seasonal temperatures. The increasing trends in the headwater and upper reaches are more dominant than those in the middle and lower reaches. The largest increase magnitude occurred in the low temperature area, while the largest decrease magnitude occurred in the high temperature area. The decreasing trends are mainly characterized for the maximum temperature time series, and summer is the only season showing a slight and insignificant increasing trend. All the time series showed a statistically significant increasing trend at the level of α?=?0.05 for the minimum temperature time series. As a whole, the increasing magnitude of the minimum temperature is significantly greater than the decreasing magnitude of the maximum temperature.     

A stochastic model for the analysis of maximum daily temperature

Accurately predicting precipitation trends is vital in the economic development of a country. Ground observed data from the Nigeria Meteorological Agency (NIMET) was analyzed to study the long-term spatio-temporal trends of rainfall on annual and seasonal scales for 23 stations in Nigeria during a 40-year period spanning from 1974 to 2013. After testing the presence of autocorrelation, Mann–Kendall (modified Mann–Kendall) test was applied to non-autocorrelated (autocorrelated) series to detect the trends in rainfall data. Theil and Sen’s slope estimator test was used to find the magnitude of change over a time period. Pettitt’s test, Standard Normal Homogeneity Test, and Buishand’s test were further used to test the homogeneity of the rainfall series. The results show an increasing trend in annual rainfall; however, only nine stations have a significant increase during the period of study. On the seasonal time scale, a significant increasing trend was observed in the pre- and post-monsoon seasons, while only nine stations show a significant increasing trend in monsoon rainfall and a significant decreasing trend in the winter rainfall over the last 40 years. During the study period, 15.4 and 13.90 % increase were estimated for annual and monsoonal rainfall, respectively. Furthermore, seven stations exhibit changes in mean rainfall while majority of the stations considered (Eighteen stations) exhibit homogeneous trends in annual and seasonal rainfall over the country. The performance of the different tests used in this study was consistent at the verified significance level.     

Changes in daily and monthly rainfall in the Middle Yellow River,China

Highly concentrated precipitation, where a large percentage of annual precipitation occurs over a few days, may include a high risk of flooding and severe soil erosion. Thus, areas with severe erosion such as the Loess Plateau in China are particularly vulnerable to highly concentrated precipitation events due to climate change. In this study, we investigated spatial and temporal patterns in the concentration of rainfall in the Middle Yellow River (MYR) from the last 56 years (1958–2013). We used daily and monthly precipitation data from 26 meteorological stations in the study area to calculate the precipitation concentration index (PCI) and the concentration index (CI). The southern and northern parts of the MYR were characterized by a lower CI with a decreasing trend, while the middle parts had a higher CI with an increasing trend. High PCI values occurred in the southern MYR, while lower PCIs with a more homogenous rainfall distribution were found mainly in the northern parts of the MYR. The annual PCI and CI exhibited positive trends at most stations, although only a minority of stations had significant trends (P < 0.05). At seasonal scales, CI exhibited significantly increasing trends in winter at most stations, while a few stations had significant trends in the other three seasons. These findings provide important reference information to facilitate ecological restoration and farming operations in the study region.     

Recent Climate Change at the Upper Danube—A temporal and spatial analysis of temperature and precipitation time series

The following study investigates temperature and precipitation trends in instrumental time series between 1960 and 2006 at 88 meteorological stations located in the Upper Danube Basin. Time series were tested for inhomogeneities with several common homogeneity tests, trend magnitudes of annual and seasonal time series were calculated by least square fitting and the significance of trend values was checked and quantified by the Mann-Kendall test. The results confirm a particularly strong recent Climate Change in the investigation area. Increasing temperature trends show remarkably high trend values up to 0.8°C/decade in the summer season. The trends are highly significant for all investigated summer, spring and annual time series. Winter and spring temperature trends show consistently positive trend values as well even though some time series show no significance at all and the calculated trend values are smaller. Autumn temperature trends are mostly non-significant with low values (up to 0.3°C/decade) and several negative trends. Most of the highest trend values can be found in lower altitudes whereas stations situated in alpine regions tend to show low trend magnitudes and often exhibit non-significant results. Precipitation time series show positive as well as negative trends in the annual and seasonal analysis. At most stations a precipitation decrease in summer and autumn and an increase in winter was observed during the last 47?years whereas the spring and mean annual precipitation exhibits no change at all. But most time series are not conclusive since they show predominantly no significance and they often exhibit only low trend values.     

Analysis of mid-twentieth century rainfall trends and variability over southwestern Uganda

A methodology has been applied to investigate the spatial variability and trends existent in a mid-twentieth century climatic time series (for the period 1943–1977) recorded by 58 climatic stations in the Albert–Victoria water management area in Uganda. Data were subjected to quality checks before further processing. In the present work, temporal trends were analyzed using Mann–Kendall and linear regression methods. Heterogeneity of monthly rainfall was investigated using the precipitation concentration index (PCI). Results revealed that 53 % of stations have positive trends where 25 % are statistically significant and 45 % of stations have negative trends with 23 % being statistically significant. Very strong trends at 99 % significance level were revealed at 12 stations. Positive trends in January, February, and November at 40 stations were observed. The highest rainfall was recorded in April, while January, June, and July had the lowest rainfall. Spatial analysis results showed that stations close to Lake Victoria recorded high amounts of rainfall. Average annual coefficient of variability was 19 %, signifying low variability. Rainfall distribution is bimodal with maximums experienced in March–April–May and September–October–November seasons of the year. Analysis also revealed that PCI values showed a moderate to seasonal rainfall distribution. Spectral analysis of the time components reveals the existence of a major period around 3, 6, and 10 years. The 6- and 10-year period is a characteristic of September–October–November, March–April–May, and annual time series.     

Streamflow trend analysis by considering autocorrelation structure,long-term persistence,and Hurst coefficient in a semi-arid region of Iran

Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

The analysis of aridity in Central Serbia from 1949 to 2015

In this study, we apply De Martonne and Pinna combinative indices to analyze the aridity in Central Serbia. Our dataset consists of mean monthly surface air temperature (MMT) and mean monthly precipitation (MMP) for 26 meteorological stations during the period 1949–2015. MMT and MMP are used for calculating monthly, seasonal, and annual aridity indices for period of 66 years. According to the De Martonne climate classification, we determine five, three, and four types of climate on the monthly, seasonal, and annual basis, respectively. During the observed period, winter was extremely humid, spring and autumn were humid, and summer was semi-humid. Humid and semi-humid climate with Mediterranean vegetation are identified by the annual Pinna combinative index. We find that there is no change in aridity trend in Central Serbia for the period 1949–2015. Aridity indices are additionally compared with the North Atlantic Oscillation and El-Niño South Oscillation in order to establish a possible connection with the large-scale processes. Results are further compared with several earlier studies of aridity in Serbia. With this study, the analysis of aridity in whole Serbia has become complete.     

Climate-induced changes in river water temperature in North Iberian Peninsula

With the surface air temperature (SAT) data at 37 stations on Central Yunnan Plateau (CYP) for 1961–2010 and the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, the temporal-spatial patterns of the SAT trends are detected using Sen’s Nonparametric Estimator of Slope approach and MK test, and the impact of urbanization on surface warming is analyzed by comparing the differences between the air temperature change trends of urban stations and their corresponding rural stations. Results indicated that annual mean air temperature showed a significant warming trend, which is equivalent to a rate of 0.17 °C/decade during the past 50 years. Seasonal mean air temperature presents a rising trend, and the trend was more significant in winter (0.31 °C/decade) than in other seasons. Annual/seasonal mean air temperature tends to increase in most areas, and higher warming trend appeared in urban areas, notably in Kunming city. The regional mean air temperature series was significantly impacted by urban warming, and the urbanization-induced warming contributed to approximately 32.3–62.9 % of the total regional warming during the past 50 years. Meantime, the urbanization-induced warming trend in winter and spring was more significant than that in summer and autumn. Since 1985, the urban heat island (UHI) intensity has gradually increased. And the urban temperatures always rise faster than rural temperatures on the CYP.     

Spatiotemporal distributions of thermal peaks in summer and winter over South Korea

This study investigated the spatial distributions and long-term trends of the annual highest and lowest temperatures (summer peak temperature, SPT; winter peak temperature, WPT) and their timings (summer peak day, SPD; winter peak day, WPD) in South Korea and analyzed their relationship with the general circulation patterns. The two peaks were determined by selecting the highest and the lowest points after extracting temperature variations longer than the seasonal scale (91 days) in the time series of daily mean temperatures. For the long-term trend, we examined data for 100 years (1909–2008) for five stations and data for 35 years (1974–2008) for 61 stations. The SPD in South Korea is August 4 on average. It is earliest (July 31) in the central inland region, the central hilly sections, and the southern inland region and latest (August 10) in the southern coastal region and on Jeju Island (Seogwipo). The WPD in South Korea is January 16 on average. It is earliest (January 13) in the central inland region and southern inland region and latest (January 24) on Jeju Island (Jeju) and in Ulleungdo. The SPT and WPT are highest on Jeju Island (Seogwipo; 27.3 and 6.4 °C, respectively) and lowest in the central hilly sections (Daegwallyeong; 20.2 and ?7.9 °C, respectively). The interannual variations in the WPD and WPT are greater than those in SPD and SPT. A significant increasing trend in the WPT was observed for all of the analyzed stations only for the second half of the 100-year period (1959–2008). In the case of the 35-year period, the SPD did not show any clear changes at all stations, but the WPD tended to occur earlier at three stations in the east coastal area. The WPT showed an increasing trend at 55 stations for 35 years, but the SPT showed an increasing trend only in Seogwipo (0.041 °C/year) and even showed a decreasing trend in Mungyeong (?0.049 °C/year). General circulation patterns were indexed and their correlations with the seasonal peaks were investigated. No correlations were found with the SPD. However, the WPD showed a significant positive correlation with the day of the highest Siberian High Intensity (SHI) and the day of the lowest Arctic Oscillation Index (AOI). Furthermore, the SPT showed negative correlations with the intensities of the Okhotsk High and North Pacific High, whereas the WPT showed a negative correlation with SHI and a positive correlation with AOI and with the intensity of the northerly wind that flows into the Korean Peninsula.     

Recent trends of mean maximum and minimum air temperatures in the western half of Iran

In this study, the trends of the annual, seasonal and monthly maximum (T _max) and minimum (T _min) air temperatures time series were investigated for 20 stations in the western half of Iran during 1966?C2005. Three statistical tests including Mann?CKendall, Sen??s slope estimator and linear regression were used for the analysis. The annual T _max and T _min series showed a positive trend in 85% of the stations and a negative trend in 15% of the stations in the study region. The highest increase of T _max and T _min values were obtained over Kermanshah and Ahwaz at the rates of (+)0.597°C/decade and (+)0.911°C/decade, respectively. On the seasonal scale, the strongest increasing trends were identified in T _max and T _min data in summer. The highest numbers of stations with positive significant trends occurred in the monthly T _max and T _min series in August. In contrast, the lowest numbers of stations with significant positive trends were observed between November and March. Overall, the results showed similar increasing trends for the study variables, although T _min generally increased at a higher rate than T _max in the study period.     

Warming and drying trends on the Tibetan Plateau (1971–2005)

Annual and seasonal trends in maximum and minimum temperatures, precipitation and vapour pressure deficit (VPD) were examined with the goal of understanding trends in temperature and moisture across the Tibetan Plateau, using meteorological data (1971–2005) collected at 63 stations. Trends in pan evaporation (PE; 1971–2001, 68 stations) and runoff (1971–2002) in the headwater of the Yellow River were also analysed. Positive trends in maximum and minimum temperatures were observed across the Tibetan Plateau. The highest increases were observed during winter, with results from the majority of stations statistically significant at the 95% level. A decrease trend in diurnal temperature range (DTR) was also observed. Trends in annual and seasonal precipitation and VPD were positive, while the trend in PE was negative. However, the increase in precipitation was not as pronounced as the increase in temperature. Although PE decreased during the time series, actual evaporation probably increased because of the warming across the Tibetan Plateau, where the annual potential water loss measured as PE is three to four times the annual water supply by precipitation. Warming was expected to increase evapotranspiration, causing more water vapour to escape into the atmosphere, thus counteracting or even exceeding the slight increase in precipitation. The increases in annual and seasonal VPD trends indicated a drying tendency and were further substantiated by the observed decrease in runoff in the headwater catchment of the Yellow River. The results provided insight into recent climatic changes across the Tibetan Plateau.     

Iranian rainfall series analysis by means of nonparametric tests

The study of the trends and fluctuations in rainfall has received a great deal of attention, since changes in rainfall patterns may lead to floods or droughts. The objective of this study was to analyze the annual, seasonal, and monthly rainfall time series at seven rain gauge stations in the west of Iran for a 40-year period (from October 1969 to September 2009). The homogeneity of the rainfall data sets at the rain gauge stations was checked by using the cumulative deviations test. Three nonparametric tests, namely Kendall, Spearman, and Mann–Kendall, at the 95 % confidence level were used for the trend analysis and the Theil–Sen estimator was applied for determining the magnitudes of the trends. According to the homogeneity analysis, all of the rainfall series except the September series at Vasaj station were found to be homogeneous. The obtained results showed an insignificant trend in the annual and seasonal rainfall series at the majority of the considered stations. Moreover, only three significant trends were observed at the February rainfall of Aghajanbolaghi station, the November series of Vasaj station, and the March rainfall series of Khomigan station. The findings of this study on the temporal trends of rainfall can be implemented to improve the water resources strategies in the study region.     

Time trend and change point of reference evapotranspiration over Iran

Identifying changes in reference evapotranspiration (ET_o) can help in future planning of crop water requirements and water resources for high water-use efficiency. This study analyzes the ET_o trends on a seasonal and annual timescale by applying various statistical tools to data from 41 Iranian weather stations during the period between 1966 and 2005. The Mann–Kendall test after removal of significant serial correlation was used to determine the statistical significance of the trends, and the change point in the ET_o time series was determined using the cumulative sum technique. The results showed that (1) the significant increasing trends of annual ET_o were observed at seven stations which are located in different parts of Iran, (2) the stations located at the southeast, northeast, and northwest corners of Iran experienced the highest positive change of annual ET_o, and (3) the changes in seasonal ET_o were most pronounced in the winter season, both in terms of trend magnitude and the number of stations with significant trends.     

Annual and seasonal variability of precipitation in Vojvodina,Serbia

Annual and seasonal variability of precipitation observed at 92 stations in Vojvodina (Serbia) were analyzed during the period 1946–2006. The rainfall series were examined by means of the empirical orthogonal functions (EOF). The first set of singular vectors explains from 68.8 % (in summer) to 81.8 % (in winter) of the total variance. The temporal variability of the time series associated with the main EOF configurations (the principal components, PCs) was examined using the Mann–Kendall test and the spectral analysis. The time series of PC1 revealed decreasing trend in the winter and spring precipitation and increasing trend in the autumn, summer, and annual precipitation. The relationships between the first PC and circulation patterns, such as the North Atlantic Oscillation (NAO), the East Atlantic (EA) pattern, and East Atlantic/West Russia pattern, were also investigated. The PC1, displaying temporal behavior of the first mode, demonstrated evident correspondence with the NAO index in analysis of the annual, winter, and autumn precipitation. Power spectra of the PC1 show statistically significant oscillations of about 3.3 years for the spring precipitation and about 8 and 15 years for the winter precipitation. Comparisons with spectral analysis of authors for some regions in Europe, most of them in the Mediterranean domain, show that similar periodicities are detected.     

Spatial and temporal analysis of dry spells in Croatia

Systematic statistical analysis of dry day sequences, which are defined according to 0.1, 1, 5 and 10 mm of precipitation-per-day thresholds, is performed on seasonal and yearly basis. The data analysed come from 25 Croatian meteorological stations and cover the period 1961–2000. Climatological features of the mean and maximum dry spell durations, as well as the frequency of long dry spells (>20 days) are discussed. The results affirm the three main climatological regions in Croatia, with the highlands exhibiting shorter dry spells than the mainland, and the coastal region exhibiting longer dry spells. The prevailing positive trend of both mean and maximal durations is detected during winter and spring seasons, while negative trend dominate in autumn for all thresholds. Positive field significant trends of mean dry spell duration with 5 and 10 mm thresholds are found during spring and the same is valid for annual maximum dry spell duration with a 10 mm threshold. It is found that the Discrete Autoregressive Moving Average (DARMA(1,1)) model can be used to estimate the probabilities of dry spells in Croatia that are up to 20–30 days long.     

Precipitation analysis over southwest Iran: trends and projections

Analysis of trends and projection of precipitation are of significance for the future development and management of water resource in southwest Iran. This research has been divided into two parts. The first part consists of an analysis of the precipitation over 50 stations in the study region for the period 1950–2007. The trends in this parameter were detected by linear regression and significance was tested by t test. Mann–Kendall rank test was also employed to confirm the results. The second part of the research involved future projection of precipitation based on four models. The models used were Centre National de Recherches Meteorologiques (CNRM), European Center Hamburg Model (ECHAM), Model for Interdisciplinary Research on Climate (MIROCH) and United Kingdom Meteorological Office (UKMOC). Precipitation projections were done under B1 and A1B emissions scenarios. The results of precipitation series indicated that most stations showed insignificant trend in annual and seasonal series. The highest numbers of stations with significant trends occurred in winter while no significant trends were detected by statistical tests in summer precipitation. No decreasing significant trends were detected by statistical tests in annual and seasonal precipitation series. The result of projections showed that precipitation may decrease according to majority of the models under both scenarios but the decrease may not be large, except according to MIROCH model. Autumn precipitation may increase with higher rates than other seasons at the end of this century.     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Analysis of recent climatic variations in Castile and Leon (Spain)

This paper reports the results of the analysis of annual mean temperature and precipitation series from 171 meteorological stations distributed over Castile and Leon [Castilla y León in Spanish] in Spain on monthly, seasonal and annual time-scales for a 37-year study period (1961–1997). Various statistical tools were used to detect and characterize significant changes in these series. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the statistical significance was determined by means of nonparametric tests. Positive trends of about 0.33 °C in the annual mean temperature were found for the whole period. Mean temperatures increased in spring and winter, the winter trend being statistically significant. The months of December and March also showed significant trends. Decreases in rainfall were found for three seasons (winter, spring and autumn), with statistically significant trends in March. Summer precipitation showed slight increases over the 37-year period. On this basis, the authors consider that the increase in summer precipitation and the decrease in the range of average temperatures between the warmest and the coldest months of the year (continentality), point towards a trend to a more oceanic climate in Castile and Leon.