Watershed-wide trend analysis of temperature characteristics in Karun-Dez watershed, southwestern Iran

Trend estimation of climatic characteristics for a watershed is required to determine developing compatible strategies related to design, development, and management of water resources. In this study, the trends of the annual maximum (T _max), minimum (T _min), and mean (T _mean) air temperature; temperature anomaly (T _anomaly); and diurnal temperature range (DTR) time series at 13 meteorological stations located in the Karun-Dez watershed were analyzed using the Mann–Kendall and linear regression trend tests. The pre-whitening method was used to eliminate the influence of serial correlation on the Mann–Kendall test. The result showed increasing trends in the T _min, T _mean, and T _anomaly series at the majority of stations and decreasing trend in the T _max and DTR series. A geographical analysis of the trends revealed a broad warming trend in most of the watershed, and the cooling trends were observed only in the southern parts. Furthermore, the geographical pattern of the trends in the T _mean and T _anomaly series was similar, and the T _max data did not show any dominant trend for the whole watershed. This study provides temperature change scenarios that may be used for the design of future water resource projects in the watershed.     

Analysis of the change in temperature trends in Subansiri River basin for RCP scenarios using CMIP5 datasets

This study focuses on changes in the maximum and minimum temperature over the Subansiri River basin for different climate change scenarios. For the study, dataset from Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) (i.e., coupled model intercomparison project phase five (CMIP5) dataset with representative concentration pathway (RCP) scenarios) were utilized. Long-term (2011–2100) maximum temperature (T _max) and minimum temperature (T_min) time series were generated using the statistical downscaling technique for low emission scenario (RCP2.6), moderate emission scenario (RCP6.0), and extreme emission scenario (RCP8.5). Trends and change of magnitude in T _max, T _min, and diurnal temperature range (DTR) were analyzed for different interdecadal time scales (2011–2100, 2011–2040, 2041–2070, 2070–2100) using Mann-Kendall non-parametric test and Sen’s slope estimator, respectively. The temperature data series for the observed duration (1981–2000) has been found to show increasing trends in T _max and T _min at both annual and monthly scale. Trend analysis of downscaled temperature for the period 2011–2100 shows increase in annual maximum temperature and annual minimum temperature for all the selected RCP scenarios; however, on the monthly scale, T _max and T _min have been seen to have decreasing trends in some months.

     

Trend analysis of Climatic Research Unit temperature dataset for Gangotri glacier,India

The absence of continuous long term meteorological dataset has led to limited knowledge of glaciers’ response to climate change over Himalayas. This study presents an open source long term temperature dataset Climatic Research Unit (CRU) available since 1901 to study trend analysis of temperature (T_max, T_min and T_mean) for Gangotri basin in Himalayas. The study first establishes close agreement between CRU time series data and observed temperature dataset available from National Institute of Hydrology (NIH), Roorkee for a period of 11 years from 2005 to 2015 using standard anomaly, Wilcoxon Signed-Rank (WSR) and correlation tests. The close agreement of CRU with NIH data validate the use of CRU time series to study variation in meteorological parameter for hilly terrain of Himalayas. The second part includes application of different statistical tests such as Mann-Kendall (MK), Sen’s slope and CUSUM technique on CRU data to detect existence of any possible trends and identification of change points in T_max, T_min and T_mean on long term scale. On annual scale, significant increasing trends for T_mean and T_min were observed with no significant trend for T_max. On seasonal and monthly scale, T_max showed significant decreasing trend for monsoon season and increasing trend for winters while T_min show significant increasing trend for all months (except May) and seasons. CUSUM technique identified 8 change points from 3 annual time series with 2 for T_mean (1974 and 1999), 3 each for T_max (1941, 1975 and 1999) and T_min (1941, 1965 and 1999) respectively. Overall, significant increase in T_min with no significant trend for T_max has been identified over the study area.     

Observed changes in relative humidity and dew point temperature in coastal regions of Iran

The analysis of trends in hydroclimatic parameters and assessment of their statistical significance have recently received a great concern to clarify whether or not there is an obvious climate change. In the current study, parametric linear regression and nonparametric Mann?CKendall tests were applied for detecting annual and seasonal trends in the relative humidity (RH) and dew point temperature (T _dew) time series at ten coastal weather stations in Iran during 1966?C2005. The serial structure of the data was considered, and the significant serial correlations were eliminated using the trend-free pre-whitening method. The results showed that annual RH increased by 1.03 and 0.28?%/decade at the northern and southern coastal regions of the country, respectively, while annual T _dew increased by 0.29 and 0.15°C per decade at the northern and southern regions, respectively. The significant trends were frequent in the T _dew series, but they were observed only at 2 out of the 50 RH series. The results showed that the difference between the results of the parametric and nonparametric tests was small, although the parametric test detected larger significant trends in the RH and T _dew time series. Furthermore, the differences between the results of the trend tests were not related to the normality of the statistical distribution.     

Long-term spatial and temporal trends in frost indices in Kansas, USA

Frost indices such as number of frost days (nFDs), number of frost-free days (nFFDs), last spring freeze (LSF), first fall freeze (FFF), and growing-season length (GSL) were calculated using daily minimum air temperature (T_min) from 23 centennial weather stations across Kansas during four time periods (through 1919, 1920–1949, 1950–1979, and 1980–2009). A frost day is defined as a day with T_min?<?0 °C. The long- and short-term trends in frost indices were analyzed at monthly, seasonal, and annual timescales. Probability of occurrence of the indices was analyzed at 5 %, 25 %, 50 %, 75 %, and 95 %. Results indicated a general increase in T_min from 1900 through 2009 causing a decrease in nFDs. LSF and FFF occurred earlier and later than normal in the year, respectively, thereby resulting in an increase in GSL. In general, northwest Kansas recorded the greatest nFD and lowest T_min, whereas southeast Kansas had the lowest nFD and highest T_min; however, the magnitude of the trends in these indices varied with location, time period, and time scales. Based on the long-term records in most stations, LSF occurred earlier by 0.1–1.9 days/decade, FFF occurred later by 0.2–0.9 day/decade, and GSL was longer by 0.1–2.5 day/decade. At the 50 % probability level, Independence in the south-eastern part of Kansas had the earliest LSF (6 April), latest FFF (29 October) and longest GSL (207 days). Oberlin (north-western Kansas) recorded the shortest GSL (156 days) and earliest FFF (7 October) had the latest LSF (2 May) at the 50 % probability level. A positive correlation was observed for combinations of indices (LSF and GSL) and elevation, whereas a negative correlation was found between FFF and elevation.     

Southern Quebec (Canada) summer-season heat spells over the 1941–2000 period: an assessment of observed changes

Summary Summer-season (May–September) daily maximum temperature (T _max) and daily minimum temperature (T _min) observations and three types of heat spells obtained from these temperature observations at seven weather stations located in southern Quebec (Canada) for the 60-year period from 1941 to 2000 are studied to assess temporal changes in their characteristics (i.e. frequency of occurrence, seasonal hot days and extremal durations of heat spells). Type-A and Type-B heat spells are obtained respectively from T _max and T _min observations and Type-C heat spells from simultaneous joint observations of T _max and T _min using suitable thresholds and spells of duration ≥1-day and ≥3-day. The results of this investigation show that the majority of the selected percentiles (i.e. 5P, 10P, 25P, 50P, 75P, 80P, 90P, 92P, 95P, and 98P) of T _max observations show a negative time-trend with statistically significant decreases (at 10% level) in some of the higher percentiles and in the maximal values at four out of seven stations. Almost all of the selected percentiles (same as for the T _max) and the maximal and minimal values of T _min observations show a positive trend, with statistically significant increases for all seven stations. Examination of frequencies of occurrence of heat spells, seasonal hot days and annual extremes of heat spell durations indicate that many of these characteristics of heat spells have undergone statistically significant changes over time at some of the stations for Type-A and Type-B heat spells as compared to Type-C heat spells. The Type-C heat spells are generally small in number and are found to be relatively temporally stable. More severe Type-C heat spells, i.e. the ones having T _max and T _min values simultaneously above very high thresholds and with duration ≥3-day have been rarely observed in southern Quebec.     

Spatial dependence of diurnal temperature range trends on precipitation from 1950 to 2004

This paper analyzes the spatial dependence of annual diurnal temperature range (DTR) trends from 1950–2004 on the annual climatology of three variables: precipitation, cloud cover, and leaf area index (LAI), by classifying the global land into various climatic regions based on the climatological annual precipitation. The regional average trends for annual minimum temperature (T _min) and DTR exhibit significant spatial correlations with the climatological values of these three variables, while such correlation for annual maximum temperature (T _max) is very weak. In general, the magnitude of the downward trend of DTR and the warming trend of T _min decreases with increasing precipitation amount, cloud cover, and LAI, i.e., with stronger DTR decreasing trends over drier regions. Such spatial dependence of T _min and DTR trends on the climatological precipitation possibly reflects large-scale effects of increased global greenhouse gases and aerosols (and associated changes in cloudiness, soil moisture, and water vapor) during the later half of the twentieth century.     

Evaluation of spatial and temporal characteristics of rainfall in Malawi: a case of data scarce region

This paper presents the methods, procedure and results in studying spatial and temporal characteristics of rainfall in Malawi, a data scarce region, between 1960 and 2006. Rainfall variables and indicators from rainfall readings at 42 stations in Malawi, excluding Lake Malawi, were analysed at monthly, seasonal and annual scales. In the study, the data were firstly subjected to quality checks through the cumulative deviations test and the standard normal homogeneity test. Spatial rainfall variability was investigated using the spatial correlation function. Temporal trends were analysed using Mann?CKendall and linear regression methods. Heterogeneity of monthly rainfall was investigated using the precipitation concentration index (PCI). Finally, inter-annual and intra-annual rainfall variability were tested using normalized precipitation anomaly series of annual rainfall series (|AR|) and the PCI (|APCI|), respectively. The results showed that (1) most stations revealed statistically non-significant decreasing rainfall trends for annual, seasonal, monthly and the individual months from March to December at the 5% significance level. The months of January and February (the highest rainfall months), however, had overall positive but statistically non-significant trends countrywide, suggesting more concentration of the seasonal rainfall around these months. (2) Spatial analysis results showed a complex rainfall pattern countrywide with annual mean of 1,095?mm centred to the south of the country and mean inter-annual variability of 26%. (3) Spatial correlation amongst stations was highest only within the first 20?km, typical of areas with strong small-scale climatic influence. (4) The country was further characterised by unstable monthly rainfall regimes, with all PCIs more than 10. (5) An increase in inter-annual rainfall variability was found.     

Characterization and estimation of urban heat island at Toronto: impact of the choice of rural sites

In this study, the urban heat island of Toronto was characterized and estimated in order to examine the impact of the selection of rural sites on the estimation of urban heat island (UHI) intensity (?T _u-r). Three rural stations, King Smoke Tree (KST), Albion Hill, and Millgrove, were used for the analysis of UHI intensity for two urban stations, Toronto downtown (Toronto) and Toronto Pearson (Pearson) using data from 1970 to 2000. The UHI intensity was characterized as winter dominating and summer dominating, depending on the choice of the rural station. The analyses of annual and seasonal trends of ?T _u-r suggested that urban heat island clearly appears in winter at both Toronto and Pearson. However, due to the mitigating effect on temperature from Lake Ontario, the estimated trend of UHI intensity was found to be less at Toronto compared to that at Pearson which has no direct lake effect. In terms of the impacts of the rural stations, for both KST and Millgrove, the trends in UHI intensity were found to be statistically significant and also were in good agreement with the estimates of UHI intensities reported for other large cities in the USA. Depending on the choice of the rural station, the estimated trend for the UHI intensity at Toronto ranges from 0.01°C/decade to 0.02°C/decade, and that at Pearson ranges from 0.03°C/decade to 0.035°C/decade during 1970–2000. From the analysis of the seasonal distribution of ?T _u-r, the UHI intensity was found to be higher at Toronto in winter than that at Pearson for all three rural stations. This was likely accounted for by the lower amount of anthropogenic heat flux at Pearson. Considering the results from the statistical analysis with respect to the geographic and surface features for each rural station, KST was suggested to be a better choice to estimate UHI intensity at Toronto compared to the other rural stations. The analysis from the current study suggests that the selection of a unique urban–rural pair to estimate UHI intensity for a city like Toronto is a critical task, as it will be for any city, and it is imperative to consider some key features such as the physiography, surface characteristics of the urban and rural stations, the climatology such as the trends in annual and seasonal variation of UHI with respect to the physical characteristics of the stations, and also more importantly the objectives of a particular study in the context of UHI effect.     

A survey of temporal and spatial reference crop evapotranspiration trends in Iran from 1960 to 2005

Reference crop evapotranspiration (ET₀) is one of the most important climatic parameters which plays a key role in estimating crop water demand and scheduling irrigation. Under global warming and climate change conditions, it is needed to survey the trend of ET₀ in Iran. In this study, ET₀ values were determined based on FAO-56 Penman-Monteith equation over 32 synoptic meteorological stations during 1960–2005; and analyzed spatially and temporally in monthly, seasonal and annual time scales. After removing the significant lag-1 serial correlation effect by pre-whitening, non-parametric statistical Mann–Kendall (MK) test was used to detect the trends. The slope of the changes was determined by Sen’s slope estimator. In order to facilitate in trend analysis, the 10 moving average low pass filter were also applied on the normalized annual ET₀ time series. Annual ET₀ time series and filtered ones were then classified by hierarchical clustering in three clusters and then mapped in order to show the patterns of different clusters. Results showed that the significant decreasing trends were more considerable than increasing ones. Among surveyed stations, and on an annual time scale, the highest and lowest annual values of Sen’s slope estimator were observed in Tabas with (+) 72.14 mm per decade and Shahrud with (?) 62.22 mm per decade, respectively. Results also indicated that the clustered map based on normalized and filtered annual ET₀ time series is in accordance with another map which showed spatial distribution of increasing, decreasing and non-significant trends of ET₀ on annually time scale. Exploratory and visual analysis of smoothed time series showed increasing trend in recent years especially after 1980 and 1995. In brief, the upward trend of ET₀ in recent years is a crucial issue with regard to the high cost of dam construction for agricultural aims in arid and semi-arid regions e.g. Iran.     

Shift changes and monotonic trends in autocorrelated temperature series over Iran

Temperature data from 29 synoptic stations in Iran for a period of 40?years (1966–2005) were analyzed to test for the existence of monotonic trends and shift changes in the annual, seasonal, and monthly mean air temperature series using the Mann–Kendall and Mann–Whitney tests. The influences of significant lag-1 serial correlation were eliminated from data by the trend-free pre-whitening method prior to the trend analysis. The magnitude of the temperature trends was derived from the Theil–Sen’s slope estimator. It was found that annual mean air temperature increased at 25 out of the 29 stations, of which 17 stations showed significant monotonic trends. The magnitude of the annual mean air temperature trends averagely was (+)0.224°C per decade. Most of the stations with the significant positive monotonic trends had a significant upward shift change. The analysis indicated that the change point year of the significant upward shift changes was 1972 for the whole stations except the coastal ones. Moreover, the strongest monotonic increasing trends and upward shift changes were observed in summer especially in August and September. The spatial analysis of the mean air temperature trends revealed the highest numbers of significant monotonic trends in the big cities of Iran. These findings provide more insights for better understanding of regional temperature behavior in the study area.     

Spatiotemporal trends of aridity index in arid and semi-arid regions of Iran

The spatiotemporal trends of aridity index in the arid and semi-arid regions of Iran in 1966–2005 were investigated using the Mann–Kendall test and Theil–Sen’s slope estimator. The results of the analysis showed negative trends in annual aridity index at 55 % of the stations, while just one site had a statistically significant (α?=?0.1) negative trend. Furthermore, the positive trends in the annual aridity index series were significant at the 95 % confidence level at Bushehr and Isfahan stations. The significant negative trend in the annual aridity index was obtained over Mashhad at the rate of ?0.004. In the seasonal series, the negative trends in the spring and winter aridity index were larger compared with those in the other seasonal series. A noticeable decrease in the winter aridity index series was observed mostly in the southeast of the study area. In the summer and autumn aridity index, two significant positive trends were found.     

Detection and attribution of anthropogenic forcing to diurnal temperature range changes from 1950 to 1999: comparing multi-model simulations with observations

Observations show that the surface diurnal temperature range (DTR) has decreased since 1950s over most global land areas due to a smaller warming in maximum temperatures (T _max) than in minimum temperatures (T _min). This paper analyzes the trends and variability in T _max, T _min, and DTR over land in observations and 48 simulations from 12 global coupled atmosphere-ocean general circulation models for the later half of the 20th century. It uses the modeled changes in surface downward solar and longwave radiation to interpret the modeled temperature changes. When anthropogenic and natural forcings are included, the models generally reproduce observed major features of the warming of T _max and T _min and the reduction of DTR. As expected the greenhouse gases enhanced surface downward longwave radiation (DLW) explains most of the warming of T _max and T _min while decreased surface downward shortwave radiation (DSW) due to increasing aerosols and water vapor contributes most to the decreases in DTR in the models. When only natural forcings are used, none of the observed trends are simulated. The simulated DTR decreases are much smaller than the observed (mainly due to the small simulated T _min trend) but still outside the range of natural internal variability estimated from the models. The much larger observed decrease in DTR suggests the possibility of additional regional effects of anthropogenic forcing that the models can not realistically simulate, likely connected to changes in cloud cover, precipitation, and soil moisture. The small magnitude of the simulated DTR trends may be attributed to the lack of an increasing trend in cloud cover and deficiencies in charactering aerosols and important surface and boundary-layer processes in the models.     

Extreme normalised residuals of daily temperatures in Catalonia (NE Spain): sampling strategies, return periods and clustering process

Extreme normalised residuals, defined as departures from the average values, of 65 daily maximum, T _max, and minimum, T _min, temperature series recorded in Catalonia (NE Spain) during 1950–2004 are analysed. Similarly to the sampling strategies applied to long dry spells, the partial duration series (PDS) offer some advantages in comparison with the annual extreme series. Instead of using a common percentile threshold for all temperature series, PDS are chosen according to the mean excess plot procedure. Series of extreme residuals are modelled, in terms of the L-moments formulation, by the generalised Pareto distribution. Extreme residuals of T _max and T _min are estimated for return periods ranging from 2 to 50 years and their spatial distribution is represented for selected return periods of 2, 5, 10, 25 and 50 years. Two daily extreme temperatures events, a hot episode (in August) and a cold episode (in February), are simulated taking into account the average T _max (T _min) for a day in August (February), their standard deviations and the extremes for a 50-year return period. Both simulations are compared with outstanding real episodes recorded on August 13th 2003 and February 11th 1956. Additionally, a spatial regionalisation of Catalonia in several clusters, in terms of the extreme residuals for return periods from 2 to 50 years, is done. A principal component analysis is applied to the extreme residual curves characterising every temperature series and, using as variables the principal components, the regionalisation is obtained by applying the average linkage clustering algorithm. Finally, each cluster is characterised by its average extreme residual curve for return periods ranging from 2 to 50 years at 1-year interval.     

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.     

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.     

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.     

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.     

Spatial gridding of daily maximum and minimum temperatures in Europe

We developed an operationally applicable land-only daily high-resolution (5?km?×?5?km) gridding method for station observations of minimum and maximum 2?m temperature (T _min/T _max) for Europe (WMO region VI). The method involves two major steps: (1) the generation of climatological T _min/T _max maps for each month of the year using block regression kriging, which considers the spatial variation explained by applied predictors; and (2) interpolation of transformed daily anomalies using block kriging, and combination of the resulting anomaly maps with climatological maps. To account for heterogeneous climatic conditions in the estimation of the statistical parameters, these steps were applied independently in overlapping climatic subregions, followed by an additional spatial merging step. Uncertainties in the gridded maps and the derived error maps were quantified: (a) by cross-validation; and (b) comparison with the T _min/T _max maps estimated in two regions having very dense temperature observation networks. The main advantages of the method are the high quality of the daily maps of T _min/T _max, the calculation of daily error maps and computational efficiency.     

Spatial gridding of daily maximum and minimum 2 m temperatures supported by satellite observations

The usefulness of two remotely sensed variables, land surface temperature (LST) and cloud cover (CC), as predictors for the gridding of daily maximum and minimum 2 m temperature (T _min/T _max) was assessed. Four similar gridding methods were compared, each of which applied regression kriging to capture the spatial variation explained by the predictors used; however, both methods differed in the interpolation steps performed and predictor combinations used. The robustness of the gridding methods was tested for daily observations in January and July in the period 2009–2011 and in two different regions: the Central European region (CER) and the Iberian Peninsula (IP). Moreover, the uncertainty estimate provided by each method was evaluated using cross-validation. The regression analyses for both regions demonstrated the high predictive skills of LST for T _min and T _max on daily and monthly timescales (and lower predictive skills of CC). The application of LST as a predictor considerably improved the gridding performance over the IP region in July; however, there was only a slight improvement over the CER region. CC reduced the loss of spatial variability in the interpolated daily T _min/T _max values over the IP region. The interpolation skill was mainly controlled by the station density, but also depended on the complexity of the terrain. LST was shown to be of particular value for very low station densities (1 station per 50,000 km²). Analyses with artificially decreasing station densities showed that even in the case of very low station densities, LST allows the determination of useful regression functions.