change affected precipitation and temperature trends in Spain? Why has climate change in the Iberian Peninsula had a greater impact on its vegetation areas? What is the trend of climate change in Spain?

The aim of this study was to analyze the climate changes experienced in Spain between 1971 and 2022 and to estimate the future climate (2050). The main objectives were as follows: (1) to analyze the temporal evolution of temperature from 1971 to the present, quantifying the warming process experienced in the case study and assessing the increase in extreme heat events (heat waves); (2) to study the evolution of the precipitation regime to determine whether there is a statistical trend towards a drier climate and an increase in extreme precipitation; (3) to investigate the interaction between annual precipitation and the continuous increase in temperature; and (4) to estimate a future climate scenario for mainland Spain and the Balearic Islands up to 2050, analyzing the trend in land dryness and predicting a possible change from a Mediterranean climate to a warm steppe climate, according to the Köppen classification. The aim of this study was to test the hypothesis that the increase in temperature caused by the global warming process will show a tendency towards progressive drought. Given the strong annual variability of climate, in addition to the ordinary least squares method, the techniques mainly used in this study were the Mann-Kendall test and the Kendall-Tille-Sen (KTS) regression. The Mann-Kendall test confirmed the very high statistical significance of the relationship between precipitation (RR) and maximum temperature (TX). If the warming trend experienced in recent years (1971-2022) continues, it is predicted that by 2050, there will be a reduction in precipitation in Spain of between 14 and 23% compared to the precipitation of the reference period (as the average between 1971 and 2000). The climate of Spain is likely to change from Mediterranean to warm steppe in the Köppen classification system (from "C" to "B").Keywords: Climate in Spain; Global warming; Heat wave; Drought; Extreme rainfall; Climate horizon 2050; Köppen climate classification .Introduction :Temperature and precipitation are major components of climate that affect human settlements. Global warming (GW) increases the risk of extreme weather events such as heat waves (HW), dry spells (DS) and floods (FL). The IPCC [1] (page 82) states: “It is almost certain that the frequency and intensity of extreme heat and the intensity and duration of heat waves have increased since 1950 and will continue to increase in the future, even if global warming is limited to 1.5°C. The frequency and intensity of heavy precipitation events have increased in most land areas with good observational coverage (high confidence) and are likely to increase in most land areas with additional global warming.”Since the 1960s, the frequency and duration of heat waves have increased in most parts of the world [2, 3]. Trends suggest that in the future, as the climate warms and average temperatures rise, heat waves will become more intense, longer, and/or more frequent [4]. Therefore, climate change is likely to increase heat waves, which will have negative impacts on human health. The increase in extreme heat events, as a result of global warming, appears to be associated with increased precipitation variability, with a gradual increase in droughts and extreme precipitation. Further warming on land alters key features of the water cycle.The rate of change in mean precipitation and runoff and their variability will increase with global warming. “The frequency and intensity of heavy precipitation events have increased since the 1950s in most regions where observational data are sufficient to analyze trends (high confidence), and human-induced climate change is likely to be the main driver. “Human-induced climate change has contributed to an increase in agricultural and environmental droughts in some regions due to increased evapotranspiration (medium confidence)” [1]

(p. 8). However, changes in drought duration are much less certain. These droughts affect specific regions, but not on a global scale [1]. Precipitation deficits and changes in evapotranspiration determine the net availability of water. The lack of adequate soil moisture, sometimes exacerbated by increased atmospheric evaporative demand, leads to agricultural and environmental droughts. The lack of runoff and surface water leads to hydrological droughts [5-9]. The Mediterranean region, and in particular the Iberian Peninsula, are hot spots of the global warming (GW) process. Over the past few decades, considerable research has shown that the rate of temperature increase in this region is significantly faster than the global average, with Spain particularly prominent in this trend [10-15]. Studies based on observational data and climate models have shown a significant increase in temperature in the Mediterranean region from the second half of the 20th century to the early 21st century. These results are consistent with the predictions of global and regional climate models [1]. Furthermore, in the CMIP5 global climate model suite, the Western Mediterranean region shows a significant warming trend, especially during summer, which is closely correlated with an increase in extreme temperature events [13]. Based on the results of the CMIP6 historical models, the average temperature in Spain has increased by 1.6 °C between 1971 and 2022, slightly higher than the Mediterranean temperature increase (1.58 °C) and much higher than the global average (1.19 °C).The Mediterranean region, with its dense and aging population, is one of the regions of the world most affected by climate change, due to the increased frequency and intensity of heat waves [16–21] and prolonged droughts [22,23].Evidence suggests that both the frequency and intensity of heat waves have increased across Spain and other European countries. An analysis of heat waves in Europe from 1971 to 2010 by Russo et al. [24] showed a significant increase in frequency in the Mediterranean, with Spain emerging as one of the countries most affected by these changes [15,25–29]. In parallel, European countries, and Spain in particular, have experienced significant changes in rainfall patterns under the influence of climate change [30, 31]. Projections suggest that the total mean annual rainfall in the Mediterranean region will decrease in the future with an increase in drought periods, while the frequency and intensity of extreme rainfall events may also increase. This trend is particularly evident in areas close to the Mediterranean coast, where there has been a significant increase in drought periods and extreme rainfall [12, 32]. The high variability in the rainfall regime in the Mediterranean region and Spain is another research topic that has been widely studied [33,34]. Despite these insights, many existing resources have focused primarily on changes in total rainfall. Interactions between different types of extreme rainfall Recurrent events are often overlooked. Furthermore, there is still a gap in understanding the mechanisms driving changes in precipitation patterns and regional variability under diverse geographical conditions [35,36]. Amid the ongoing changes caused by climate change, the link between temperature and precipitation changes, especially during extreme events, has become more evident [37, 38]. Studies have shown a strong negative correlation between increasing temperatures, especially maximum temperatures, and decreasing precipitation and increasing drought in the Mediterranean region and Spain [39, 40]. Further analyses have deepened this understanding, showing that extremely high temperatures are closely associated with decreasing precipitation, while increasing minimum nighttime temperatures are positively correlated with increasing extreme precipitation events [32]. In summary, although considerable research has been conducted on the impact of climate change on the climate of Spain, several research gaps remain. First, most studies have focused on relatively short timescales and lack in-depth analysis of climate change trends over longer timescales. Second, the complex interactions between temperature and precipitation changes, and the linkages and drivers of extreme events, have not been adequately explored. Finally, the variability in responses to climate change across geographic and climatic regions needs further investigation [35,36]. To better understand and predict changes in climate patterns, climate classification systems are essential tools. Common systems used worldwide include the Köppen-Geiger climate classification, the Torrent-Thwait climate classification, the Papadakis climate classification, the Trevarta climate classification, and the ASHRAE climate zones, among others. The Köppen-Geiger climate classification is one of the most widely used systems. Originally proposed by Wladimir Köppen in the late 19th century [41, 42] and later modified [43], this classification classifies global climates based on average monthly temperature and precipitation. The system divides global climates into 5 main categories and 30 subcategories. The system provides an effective way to describe the macro-characteristics of climate regions and their potential changes with climate change [44, 45]. In recent years, updates to the Köppen classification maps have incorporated 32 climate models from CMIP5 and high-resolution climate datasets to improve the accuracy of predictions and classifications for current and future climate scenarios [46]. These climate classification systems not only help researchers classify different climate types, but also provide a basis for predicting the impacts of climate change.In particular, the Köppen-Geiger system remains a cornerstone of climate research due to its adaptability to different climate data and scenarios. This makes it very useful for tasks such as global vegetation mapping, ecological modeling, and climate impact assessment [47,48]. Spain has adopted several climate classification systems to study regional climate dynamics and their impacts. Using data from 1931 to 1960, Inocencio Font, a member of the Spanish National Meteorological Institute (forerunner of the current AEMET), proposed a climate classification for the Iberian Peninsula in 1983 [49]. This classification, which is essentially based on two factors, the continental index and the precipitation regime, is fully consistent with the climatic characteristics of Spain. However, it does not take into account the significant climate changes that have occurred since 1960. Martin-Wade and Olchina Kantos [50] made another important contribution to this field. In this study, the authors proposed a climate classification based mainly on physiographic criteria, based on annual precipitation and mean temperature, seasonal precipitation and thermal range, and other characteristics. In addition to these studies, researchers in Spain have used other climate classification methods to understand different climatic and ecological aspects. Papadakis climate The classification, which focuses on bioclimatic zones defined by temperature and humidity, is particularly useful for agricultural and environmental studies. Recent research has used this method to assess the effects of climate change on the suitability of different Mediterranean crops in Spain [51]. In order to assess the energy efficiency of buildings, an adaptation of the European Directive on the Energy Performance of Buildings [52] has been implemented through the Technical Building Code (TBC), which divides the territory into climatic zones and assesses the energy performance of buildings according to these zones [53]. The Technical Building Code (TBC) divides Spain according to the climatic seasons. Some authors [54] have critically discussed the TBC climatic classification and proposed an alternative that is more compatible with the warming experienced by Spain in recent decades. In building comfort and energy efficiency assessments, the ASHRAE climatic classification has also been widely used. Studies have shown that ASHRAE standards [55] are useful for assessing thermal comfort in buildings with combined ventilation and natural ventilation. However, these standards often need to be adapted to take into account the Mediterranean climate. Optimization of ASHRAE standards through adaptive comfort models has been proposed to better adapt to the Spanish climate. These models can be used to improve energy simulations and optimize HVAC systems, to increase building performance and occupant comfort [56,57]. However, among all the studies that analyze the Spanish climate, the Köppen-Geiger classification is undoubtedly the most commonly used. This classification has been widely used to study regional climate changes and predict future trends. The State Meteorological Agency (AEMET) has provided an extensive analysis of the changes in Köppen climate types in Spain from 1951 to 2020 [58]. Based on these climate classification systems, understanding the dynamics of temperature and precipitation changes in the Mediterranean region, especially in Spain, is crucial for assessing the impacts of climate change [59,60]. The AEMET technical report highlights a trend from a Mediterranean climate to a warmer and drier steppe climate. This change is mainly due to the significant increase in maximum and minimum temperatures observed in recent decades. In addition, precipitation is expected to decrease by 14–20% by 2050 [58,60]. Recent studies have shown that the country is experiencing a significant shift from a Mediterranean climate to a drier climate, such as desert (BW) and semi-desert (BS) zones, especially in the southeastern regions. These changes are mainly due to increasing temperatures and decreasing precipitation, which are projected to continue under future climate scenarios [58,61]. Climate change in Spain and other Mediterranean regions will lead to a sharp increase in temperatures, especially heat waves, and a possible decrease in rainfall [62]. In turn, there will likely be a combination of intense and torrential rainfall events with prolonged periods of drought [63, 64]. The Mediterranean region, especially in mainland Spain and the Balearic Islands, is changing towards a progressively more extreme climate, both in terms of temperature [26, 27] and precipitation (droughts and extreme rainfall). The aim of this study was to analyze the climate changes experienced in Spain between 1971 and 2022 and to estimate the future climate (2050). The main objectives of this study include: (1) analyzing the temporal evolution of temperature from 1971 to the present, quantifying the warming process experienced in the case study and assessing the increase in extreme heat events (heat waves); (2) study the evolution of the precipitation regime to determine whether there is a representative statistical trend towards a drier climate and increased extreme rainfall; (3) investigate the interaction between annual rainfall and the continued increase in temperature; and (4) estimate future climate scenarios for mainland Spain and the Balearic Islands.Towards 2050, analysis of the land aridity trend and prediction of a possible change from a Mediterranean climate to a warm steppe climate, according to the Köppen classification. The main objective of this study was to analyze whether there is a temporal evolution in the precipitation regime in Spain towards less precipitation, and to investigate the relationship between annual precipitation and a tendency towards progressive warming. Specifically, the aim was to test the hypothesis that the increase in temperature due to the global warming process will show a tendency towards progressive drought in the Mediterranean geographical area, and in Spain in particular.2. Materials and Methods

The data bases, case study and methodology used to carry out the climate-territorial analysis are presented below.2.1. Databases In this study, we used the E-OBS dataset (https://surfobs.climate.copernicus.eu/ dataaccess/access_eobs.php, accessed on 25 June 2024) provided by the European Climate Assessment and Dataset (ECA&D) project. E-OBS is a high-resolution gridded daily climate dataset. This dataset has provided daily climate information for the European region since 1950. E-OBS is provided as a composite dataset and is available on a regular 0.1° and 0.25° grid for the elements of daily mean temperature (TG), daily minimum temperature (TN), daily maximum temperature (TX), daily precipitation total (RR), daily mean sea level pressure, daily mean relative humidity, daily mean wind speed and daily mean global radiation. The data cover the following region: 25°N-71.5°N × 25°W-45°E. The Global 30 Arc Second Elevation Dataset (GTOPO30), a global raster digital terrain model (DTM) with a horizontal grid spacing of 30 arc seconds (approximately 1 km) developed by the USGS, is also used for the elevation file. Station data collected by the ECA&D project form the basis of the E-OBS. All station data are obtained directly from the European National Meteorological and Hydrological Services (NMHSs) or other data hosting institutions. For a significant number of countries, the number of stations used is the entire national network. This is much denser than the station network typically shared between NMHSs (which is the basis for other gridded datasets). The station density is gradually increasing through collaboration with NMHSs in European research contracts. Initially, in 2008, this gridded dataset was developed to validate a set of Europe-wide climate model simulations produced as part of the European Union ENSEMLES project. However, due to data exchange limitations, the number of stations available for E-OBS is generally lower than the total number of stations available or the number of stations used in most national/supranational gridded datasets. Although most station series are quality controlled by the relevant organizations, they undergo a further quality control process after integration into ECA&D. These data are then combined with adjacent series to form more complete time series that are used in E-OBS [65]. The distinctive feature of the E-OBS dataset lies in its high resolution and continuity.Its spatial resolution is 0.1° × 0.1°, which geographically covers most of Europe, including Spain. Its continuity over time helps us to track and analyze long-term climate change trends, which is particularly important for understanding the dynamics of climate system changes. However, due to the lower density of weather stations in periods before the 1980s and therefore the greater uncertainty of the indicators when going back in time, it was decided to use a spatial resolution of 0.25° to increase the robustness of the research. The E-OBS dataset has been produced to match the 0.25° grid resolution of previous versions of E-OBS: “There is a need to produce a higher resolution version of E-OBS.”Higher spatial resolution than the current resolution of approximately 25 km [65] (page 9407). For this reason, a resolution of 0.25° was chosen for this research. In this study, we obtained daily temperature data, including mean, maximum and minimum temperatures and precipitation from 1971 to 2022 using the 27.0e dataset. The data from the last 52 years allow us to examine the current climate situation in Spain and trace the main trends of climate change in recent decades. With these data, we can perform a deeper analysis of the climate characteristics of Spain in order to make a more precise climate classification. 2.2. Study are : The study area covers the Spanish peninsula and the Balearic Islands between longitudes 8° W and 6° E and between latitudes 36° N and 44° N (Figure 1). The Iberian Peninsula and the Balearic Islands are located in temperate latitudes. The region is between the Atlantic Ocean and the Mediterranean Sea. This means that both types of climate, oceanic and Mediterranean, have a significant influence. The Spanish mainland is a relatively mountainous continental massif dominated by plateaus and high mountain ranges. In addition to the Pyrenees, the main mountain ranges are the Cantabrian Mountains, the Iberian System, the Central System, the Sierra Morena and the Baetic System. The Central Plateau (Meseta Central) is a vast plateau in the heart of the Spanish peninsula, divided into two parts by the Central System. The valleys of the main rivers, notably the Ebro in the northeast and the Guadalquivir in the southwest, together with the topography, determine the climate of the peninsula. The Spanish peninsula is characterized by a wide range of climatic patterns due to its complex orography and its geographical location between the subtropical and temperate zones of Europe. The geographical diversity of Spain probably makes it the country with the most climatic diversity in Europe. In general, the country is characterized by .... with a temperate climate, with warm summers and cold winters inland and milder summers and colder winters on the coast. In general, the climate of Spain can be classified into five distinct zones: Mediterranean climate with hot summers, Mediterranean climate with hot summers, oceanic climate, semi-arid climate and continental climate with hot summers. The spatial resolution is greater than the current spatial resolution of approximately 25 km” [65] (page 9407). For this reason, a resolution of 0.25 degrees was chosen for this study. In this study, we obtained daily temperature data, including mean, maximum and minimum temperatures and precipitation from 1971 to 2022 using the 27.0e dataset. The data from the last 52 years allow us to reflect on the current climate situation in Spain and trace the main trends of climate change in recent decades. With these data, we can perform a deeper analysis of the climate characteristics of Spain to obtain a more accurate climate classification. 2.2. Study area :The study area covers the Spanish peninsula and the Balearic Islands between longitudes 8°W and 6°E and between latitudes 36°N and 44°N (Figure 1). The Iberian Peninsula and the Balearic Islands are located in a temperate latitude zone, between the Atlantic Ocean and the Mediterranean Sea. This means that both oceanic and Mediterranean climates have a significant influence. The Spanish mainland is a relatively mountainous continental massif dominated by plateaus and high mountain ranges. In addition to the Pyrenees, the main mountain ranges are the Cantabrian Mountains, the Iberian System, the Central System, the Sierra Morena and the Baetic System. The Central Plateau (Meseta Central) is a vast plateau in the heart of the Spanish peninsula, divided into two parts by the Central System. The valleys of the main rivers, notably the Ebro in the northeast and the Guadalquivir in the southwest, together with the topography, determine the climate of the peninsula. The Spanish peninsula is characterized by a wide range of climatic patterns due to its complex orography and its geographical location between the subtropical and temperate zones of Europe. The geographical diversity of Spain makes it probably the country with the most climatic diversity in Europe. In general, the country is characterized by a temperate climate with hot summers and cold winters in the interior and milder summers and colder winters on the coast. In general, the climate of Spain can be classified into five distinct zones: Mediterranean climate with hot summers, Mediterranean climate with hot summers, oceanic climate, semi-arid climate and continental climate with hot summers. Figure 1. Study area. Source: ESRI. Personal elaboration. 2.3. Methodology Since the main objective of this study was to analyze the climatic trends of mainland Spain and the Balearic Islands, the basic information used consisted of daily data (between 1 January 1971 and 31 December 2022) provided by E-OBS corresponding to the mean (TG), maximum (TX) and minimum (TN) temperature and precipitation (RR) for each of the 839 cells that make up the study area.Figure 2. 0.25°C cells derived from E-OBS. In line with this initial information, the following indicators were used in this study: • Summer days (SU), the annual number of days with air temperatures above 25°C, tropical nights (TR) and the annual number of nights with air temperatures above 20°C (https://surfobs.climate.copernicus.eu/userguidance/indicesdictionary.php, accessed 25 June 2024). • To assess the trend of increasing extreme heat events, daily and night-time heat waves (warm and subtropical waters) experienced between 1971 and 2022 were analyzed. • For precipitation (RR), three annual drought indicators were used: the number of days without rain (RR = 0 or dry days, DD), the number of consecutive days with less than 1 mm of precipitation per day (CDRR1mm), and the total precipitation on days with less than 10 mm of precipitation (RR10mm). For extreme precipitation, three indicators were used: the highest 5-day precipitation (RRX5day), precipitation above the 99th percentile of wet days (total precipitation from very wet days, RR30mm), and torrential rainfall (95th percentile of very wet days, RR60mm). 2.3.1. Heat waves :There is no universal definition of a heat wave, but extreme events associated with particularly hot and sustained temperatures have a significant impact on human mortality, regional economies, and ecosystems [3,66]. As demonstrated by the high temperatures in Western Europe in 2003 [67] and the extreme heat events in Chicago in 1995 [68], a heat wave (HW) is identified when a number of consecutive days reach temperatures above a certain hot threshold. However, there are several hot threshold criteria to calculate the consecutive days of a HW [15–17,29,66,69]. In this study, we use the concept of heat wave as applied by AEMET. In this definition, a heat wave is considered as a period of at least three consecutive days in which the stations considered record maximum temperatures above the 95% percentile of the daily maximum temperature series for the months of July and August from the period 1971 to 2000 [70]. Therefore, the reference period for determining heat waves is set between 1971 and 2000, in order to assess the warming trend that has occurred since then. However, this definition has a major limitation: it only refers to the maximum temperature, not the minimum. Maximum temperatures can have serious consequences, especially in the case of heatstroke. However, the health effects are more pronounced in the case of nighttime heat, when the inability to rest (especially in homes without air conditioning, as is common in Spain) can cause a significant worsening of respiratory and cardiovascular diseases, which can lead to high blood pressure.Premature mortality ratio [28, 71]. For this reason, in this study, we distinguish between daytime heat waves (DHW) and nighttime heat waves (NHW). We use the concept of heat wave applied by AEMET, but distinguish between daytime heat waves (DHW) if TX ≥ daytime heat threshold (DHT) and nighttime heat waves (NHW) if TN ≥ nighttime heat threshold (NHT). 2.3.2. Precipitation: Extreme events: The precipitation pattern in most of Spain is typically Mediterranean, with irregular precipitation, sometimes due to the occurrence of heavy and intense floods in some months. In other months, precipitation is low. In addition, the varied topography of mainland Spain is associated with significant differences in precipitation between its regions. The variability in the precipitation regime has been widely studied [33,34]. In this study, we will focus on the analysis of drought and extreme rainfall periods. The occurrence of changes in the hydrological cycle for a high warming scenario is not limited to rainfall, but also significantly affects other variables such as soil moisture, runoff, atmospheric humidity, and evapotranspiration. These changes are not limited to the average annual rainfall, but may be stronger or weaker for specific seasons and for periods of extreme rainfall and drought [1]. Several methods have been developed and applied to study drought [30, 72]. The standard resolution of rainfall measuring devices (0.1 mm/day) usually distinguishes between wet or dry days. The environmental stress that accompanies a drought period is caused by multiple consecutive days with insufficient rainfall or insufficient rainfall to compensate for the lack of moisture in the environment. Therefore, it is appropriate to analyze additional thresholds that characterize average rainfall, which may be related to phenomena such as vegetation and soil degradation, desertification due to erosion, low crop yields or water resource availability. Three indicators related to the drought regime (DS) have been analyzed to improve knowledge of drought in Spain. These indicators are the number of days without rain (DD), the number of consecutive days with rainfall less than 1 mm per day (CDRR1 mm, related to evapotranspiration processes) and the total rainfall on days with rainfall less than 10 mm (RR10 mm, saturation of thin surface layers). The following indicators were used for the case of heavy rainfall: (a) the highest annual rainfall accumulated over five consecutive days (RRX5 days), (b) heavy rainfall, understood as the total daily rainfall above the 99th percentile of wet days (RR > 1 mm/day), and (c) torrential rainfall (above the 95th percentile of very wet days). According to the General Directorate of Civil Protection and Medical Emergencies [73], rainfall is considered heavy if it is between 15 and 30 mm/h; very heavy, between 30 and 60 mm/h; and torrential, above 60 mm/h. Since the data provided by E-OBS are of a daily nature, indicators on a more precise time scale were not available. This explains the adoption of the criterion (similar to that used to identify heat waves) of using percentiles of daily rainfall to define extreme rainfall. In the case study of mainland Spain and the Balearic Islands, the 99th percentile of rainy days (RR > 1 mm/day) for the period 1971–2022 is close to 30 mm/day (30.5 mm), so the variable RR30 mm (as the annual total of daily rainfall equal to or greater than 30 mm) was used as an indicator of extreme rainfall [74]. Furthermore, given that hourly weather data were not available, the “flood” rainfall index in this study was defined as “annual total of daily rainfall greater than the 95th percentile of days with extreme rainfall”.This 95th percentile of intense rainfall (“heavy”) for the Iberian Peninsula corresponds to a daily rainfall of around 60 mm (59.9 mm), so the threshold used to define torrential rainfall was set at 60 mm per day (RR60 mm).2.3.3. Trend Analysis . In climate data analysis, various regression methods have been employed to process data sets with diverse characteristics, especially in the presence of outliers or nonlinear trends. Ordinary least squares (OLS) regression is a common parametric method for estimating linear relationships between variables. However, OLS is very sensitive to outliers, which can lead to biased estimates when applied to data sets with significant variability or extreme values [75]. Given that climate data often exhibit such complexities, more robust methods are needed to ensure reliable trend estimates. To address these challenges, nonparametric methods such as the Mann–Kendall (MK) test and Kendall–Thield–Sen (KTS) regression are often used. Unlike parametric approaches, the MK test and KTS regression do not assume any specific underlying distribution of the data: • MK is one of the most widely used nonparametric tests for trend detection in climate studies. Unlike parametric methods, it does not require the data to be normally distributed. It only requires independent data [76]. The MK test is insensitive to sudden peaks caused by heterogeneous time series. • KTS regression estimates trend slopes based on the median of all possible pairwise slopes between data points. This makes KTS very robust to outliers. It provides more reliable estimates of trends in climate datasets that may not adhere to normal distribution assumptions [77,78]. The KTS method has been widely used in environmental and climate research due to its effectiveness in handling irregularities and extreme values in the data [79]. An alternative nonparametric method available in the scikit-learn Python library is TheilSenRegressor, which provides robust estimates by iteratively calculating slopes to effectively handle outliers. However, due to its simpler and more straightforward calculation process, KTS is often preferred, especially when large datasets are processed. In this study, temporal trends (using OLS and KTS regression models) were obtained using temperature (TG, TX, TN, SU, TR, DHWs, and NHWs) dependent variables and precipitation indices (RR, DD, CDRR1mm, RR10mm, RRX5day, RR30mm, and RR60mm) and year as independent variables. Since the main objective of this study was to assess the interactions between precipitation and temperature (to validate the study hypothesis), total precipitation (RR) and values of drought and extreme precipitation indices (using OLS and KTS regression models) were correlated with mean (TG), maximum (TX) and minimum (TN) temperatures. The age slopes obtained from the KTS regressions and the p-value of the MK test allow for the assessment of the positive or negative trend and statistical significance of the developed models. The criteria set by the IPCC (2021) used in this study are as follows [1]:

• If the p-value of the MK test is < 0.01, it is considered “almost certain” (99-100% statistical confidence).

• If the p-value is > 0.01 and 0.05 and 0.1 and 25 ◦C) and TR (TN > 20 ◦C) indices over time helps to better understand the warming process experienced in mainland Spain and the Balearic Islands. Figure 6 shows the increase in SU (left) and TR (right) between 1971 and 2022. • The OLS model between summer days as dependent variable and year as independent variable shows that SU has increased on average across the territory from 82.4 in 1971 to 117.9 in 2022. Between 1971 and 2022, summer days have increased on average by 36 days in Spain. • The OLS model of tropical nights and year shows that TR has increased from 1.73 in 1971 to 14.12 in 2022. Unlike the increase in SU, which was relatively homogeneous throughout the Spanish territory, the increase in TR was concentrated in the southern plateau, the valleys of the Guadalquivir and Ebro rivers, and the Mediterranean coast, increasing by more than 30 nights between 1971 and 2022.Therefore, the warming trend caused by climate change in mainland Spain and the Balearic Islands, which represent a real global warming hotspot, has been clearly observed. Spain has significantly exceeded the 2°C threshold compared to pre-industrial times [15]. Considering the temperature difference between 1971 and 2022, the temperature increase in mainland Spain and the Balearic Islands has been 2.19°C, which is much higher than the global average (1.19°C) and even higher than the average for the Mediterranean region (1.58°C), if the historical CMIP6 estimates (https://atlas.climate.copernicus.eu/atlas, accessed 25 June 2024) are taken as a reference. Consequently, Spain is undoubtedly a hotspot in the global warming process.

3.2. Evolution of extreme heat events (1971-2022)

Following the AEMET methodology, daytime [70] and nighttime [28] heat thresholds were determined for the reference period 1971-2000.

Figure 7 shows the results. The comparison between the two images allows us to understand the climatic differences in daytime extreme heat (DHT) and nighttime (NHT). The daytime extreme heat threshold (DHT) exceeds 35°C in the southern plateau and especially in the Guadalquivir and Ebro river valleys. However, it rarely exceeds 32°C on the Mediterranean coast. Furthermore, the nighttime heat threshold (NHT) exceeds 20°C in most of the Mediterranean coast, in addition to the Madrid region (probably due to the urban heat island of the Spanish capital) and the Guadalquivir and Ebro river valleys. Land 2025, 14, x for peer review 14 of 36

3.2. Evolution of extreme heat events (1971-2022)

Following the AEMET method, daily [70] and nighttime [28] heat thresholds were determined for the reference period 1971-2000.

Figure 7 shows the results. The comparison between the two images allows us to understand the climatic differences in daily extreme heat (DHT) and nighttime (NHT). The daily extreme heat threshold (DHT) exceeds 35°C in the southern plateau and especially in the Guadalquivir and Ebro river valleys. However, it rarely exceeds 32°C on the Mediterranean coast. Furthermore, the daily extreme heat threshold (NHT) exceeds 20°C on most of the Mediterranean coast, in addition to the Madrid region (probably influenced by the urban heat island of the Spanish capital) and the valleys of the Guadalquivir and Ebro rivers. Discussion : In this study, we have attempted to quantify the extent of the warming trend in Spain, manifested, among other indicators, in the evolution of mean, maximum and minimum temperatures and in the number of summer days and hot nights. We have also shown the increase in heat waves (day and night) and their duration in the period 1971-2022. The research carried out has shown a trend towards a decrease in annual rainfall and an increase in droughts and torrential rainfall. We have shown, and this is probably the greatest innovation of this research, that both processes (warming trend and change in the rainfall regime, especially droughts) are closely linked. If these trends continue in the coming decades, the climate of the peninsula and the islands (Balearic Islands) will change to a warmer and drier climate. This climate will be more extreme, with heat waves, drought periods and torrential rainfall. The previous section provides a summary of some of the main climate changes that have occurred in mainland Spain and the Balearic Islands since 1971. Conclusion: The warming process affecting the Iberian Peninsula and the Balearic Islands has a significant impact on the precipitation regime. There is an interaction between temperature (especially maximum) and precipitation. The hypothesis of this research is fully confirmed. It is almost certain that an increase in temperature is associated with precipitation of less than 10 mm per day.

However, this interaction occurs in reverse, depending on the thresholds that define the processes of drought (less than 10 mm per day) or extreme precipitation (more than 30 mm per day). An increase in temperature (especially subzero temperatures) significantly reduces the precipitation that defines the drought threshold (almost certain). This increase in temperature (especially subzero temperatures) determines an increase in extreme precipitation (highly probable). The common result of both opposing processes (RR) is the dominance of the drought tendency that determines the progressive aridification of the Iberian climate. Hence, it can be concluded with a very high degree of confidence that climate change is causing a tendency to decrease precipitation. These results are consistent with those obtained in other studies [40] and, in addition, add the quantification of the opposing process that indicates a tendency to drought. The results obtained, in turn, allow for a precise statistical confirmation of the estimates made by the IPCC [1,2]. The E-OBS data (0.25°C) used in this study show an even more intense warming in Spain than the estimates provided by the CMIP6 models. Between 1971 and 2022, the mean temperature (TG) has increased by 2.17°C (KTS regression), compared to 1.87°C estimated by CMIP6 climate models. In turn, the KTS regression model estimates the decrease in precipitation over the period 1971–2022 more accurately than the historical CMIP6 models. Compared to 10.72 mm in the IPCC models, the present study quantifies the decrease in precipitation at 40.31 mm. If the trend of the period 1971–2022 continues, the forward-looking models show that by the middle of this century, the climate will become significantly drier and warmer, with steppes and Even the deserts of Spain are affected. If the warming trend experienced in recent years (1971-2022) continues, it is expected that by 2050 there will be an increase of 2.70 °C in average temperatures and a decrease of 14 to 23% in precipitation in Spain compared to the reference period considered as the average between 1971 and 2000. This trend is more pronounced than that predicted by the CMIP6 ensemble models (SSP5-8.5 years for Spain).

These trends predict a very significant change in the climate of Spain in the coming years.

The climate of Spain is likely to change from "temperate" to "arid" in the Köppen classification system (from "C" to "B"), a much more pronounced change than that predicted in global studies [46] based on IPCC estimates. Author contributions: Conceptualization, BSc, MSc, MSc and PhD; Methodology, BSc, MSc and PhD; Software, BSc; Research, BSc; Data collection, BSc; Writing - original draft, BSc and PhD; Writing - review and editing, BSc; Supervision, BSc; Project management, BSc; Financing, BSc. The study described in this article was jointly conducted by the authors. All authors have read and approved the published version of the manuscript.

Funding: We thank the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (ERDF) for funding the project Spatial and Urban Planning Tool for Extreme Heat Waves and Flash Floods: Building Resilience for Cities and Regions (X-ClimPlan). Data access statement: Raw data supporting the conclusions of this article will be made available to the authors upon request.

Acknowledgements: We thank our research team, Dolores Martinez, Karina Serra, and Javier Lana, for their support and comments.

Conflicts of interest: The authors declare no conflicts of interest. List of abbreviations/titles

Spanish State Meteorological Agency (AEMET Agencia Estatal de Meteorología)

American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE)

CDRR1mm Consecutive days with less than 1 mm of precipitation per day

Coupled Model CMIP5/CMIP6 Cross-Comparison Project Phase 5/6: Climate Model

Comparison Projects

Dry Days DD: Days without precipitation

Daily Heat Threshold DHT: Temperature threshold for daily heat waves

Daily Heat Wave DHW: Period of unusually high daily temperatures

Dry Period DS: Prolonged period with little or no precipitation

Digital Terrain Model DTM

European Climate Assessment and Dataset ECA&D

E-OBS high-resolution gridded dataset for daily climate data across Europe, from the

European Climate Assessment and Dataset Project. Environmental Protection Agency EPA: United States government agency for environmental protection

Florida flood

Global warming GW: Increase in the average surface temperature of the Earth due to increasing

greenhouse gas levels

Air conditioning systems: Building climate control systems

Heat wave HW: Period of abnormally warm weather

Intergovernmental Panel on Climate Change IPCC

KTS Kendall-Tilson: Statistical method for robust linear regression

MK Mann-Kendall: Statistical test for identifying trends in time series data

NHMSs National Meteorological and Hydrological Service Nighttime heat threshold NHT: Temperature threshold for nighttime heat waves

NHW Nighttime heat wave: Period of abnormally high nighttime temperatures

OLS Ordinary least squares: Statistical method for estimating parameters in

Linear regression

RR Total daily precipitation

RR10 mm Precipitation less than or equal to 10 mm per day

RR30 mm Precipitation less than or equal to 30 mm per day

RR60 mm Precipitation less than or equal to 30 mm per day

RRX5 days Highest 5-day precipitation

SU Summer days: Days with a maximum temperature above 25 °C

TBC Technical Building Code: Spanish building regulations

TG Average temperature

TN Minimum temperature

TR Tropical nights: Nights with a minimum temperature above 20 °C

TX Maximum temperature

USGS United States Geological Survey

Appendix A. Number and duration of heat waves during the day and night between 1971 and 2022

Year Number of days of domestic hot water supply Days NHWs/NHWs

1971 1.08 3.71 1.17 4.40

1972 0.00 0.00 1.00 3.45

1973 1.00 3.43 1.05 3.79

1974 1.02 3.07 1.35 5.00

1975 1.13 3.73 1.15 4.60

1976 1.09 3.78 1.36 5.36

1977 0.00 0.00 0.00 0.00

1978 1.02 3.49 1.11 3.48

1979 1.02 3.42 1.06 3.40

1980 1.03 3.16 1.02 3.20

1981 1.07 3.52 1.89 7.24

1982 1.00 3.61 1.02 3.80

1983 1.32 4.19 1.38 4.76

1984 1.04 3.55 1.05 3.15

1985 1.01 3.39 1.03 3.40

1986 1.00 3.29 1.00 3.15

1987 1.38 5.85 1.10 4.34

1988 1.00 3.13 1.04 3.37

1989 1.36 5.19 1.62 6.08

1990 1.38 5.96 1.24 5.90

1991 1.80 7.42 1.27 5.12

1992 1.16 3.69 1.33 5.24

1993 1.10 3.53 1.10 3.74

1994 1.54 6.80 1.67 6.89

1995 1.06 5.31 1.27 5.33

1996 1.18 4.05 1.00 3.02

1997 1.10 3.30 1.15 4.26

1998 1.09 4.66 1.14 3.99

1999 1.02 3.10 1.31 4.43

2000 1.07 3.44 1.40 4.98

2001 1.10 3.85 1.31 4.20

2002 1.00 3.08 1.00 3.11

2003 1.86 12.20 1.85 12.63Land 2025, 14, 85 32 of 35

Year Num. DHWs Days/DHW Num. NHWs Days/NHW

2004 1.50 5.15 1.82 6.54

2005 1.27 4.03 1.41 4.92

2006 1.38 5.10 1.77 9.14

2007 1.03 3.41 1.23 4.08

2008 1.03 3.52 1.13 4.03

2009 1.64 7.56 1.56 5.70

2010 1.74 6.40 2.25 9.54

2011 1.11 4.08 1.54 5.58

2012 2.01 7.21 2.11 8.86

2013 1.66 7.49 1.24 4.47

2014 1.29 4.63 1.33 4.58

2015 2.31 9.95 3.10 18.64

2016 1.89 7.21 2.14 7.61

2017 2.20 8.94 2.51 14.20

2018 1.16 6.34 1.35 6.60

2019 2.13 9.01 1.62 7.77

2020 1.94 7.89 1.96 9.40

2021 1.24 5.71 1.25 6.78

2022 3.39 20.07 3.27 18.83

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