Analysis of tropical cyclone intensification trends and variability in the North Atlantic Basin over the period 1970–2003

Summary Over the past three decades, the sea-surface temperatures of the lower latitudes of the North Atlantic basin have increased while the lower-tropospheric temperatures show no upward trend. This differential warming of the atmosphere may have a destabilizing effect that could influence the development and intensification of tropical cyclones (TCs). In this investigation, we find that in general, TC intensification (a) is higher during the daytime period and during the later months of the storm season, (b) tends to be higher in the western portion of the North Atlantic basin, and (c) is not explained by current month or antecedent SSTs. Any changes associated with warming of the surface compared to a smaller temperature rise in the lower-troposphere (and resultant changes in atmospheric stability) have not produced detectable impacts on intensification rates of tropical cyclones in the North Atlantic basin.     

Trends in temperature extremes over nine integrated agricultural regions in China, 1961–2011

By characterizing the patterns of temperature extremes over nine integrated agricultural regions (IARs) in China from 1961 to 2011, this study performed trend analyses on 16 extreme temperature indices using a high-resolution (0.5° × 0.5°) daily gridded dataset and the Mann-Kendall method. The results show that annually, at both daytime and nighttime, cold extremes significantly decreased but warm extremes significantly increased across all IARs. Overall, nighttimes tended to warm faster than daytimes. Diurnal temperature ranges (DTR) diminished, apart from the mid-northern Southwest China Region and the mid-Loess Plateau Region. Seasonally, DTR widely diminished across all IARs during the four seasons except for spring. Higher minimum daily minimum temperature (TNn) and maximum daily maximum temperature (TXx), in both summer and winter, were recorded for most IARs except for the Huang-Huai-Hai Region; in autumn, all IARs generally encountered higher TNn and TXx. In all seasons, warming was observed at daytime and nighttime but, again, nighttimes warmed faster than daytimes. The results also indicate a more rapid warming trend in Northern and Western China than in Southern and Eastern China, with accelerated warming at high elevations. The increases in TNn and TXx might cause a reduction in agriculture yield in spring over Northern China, while such negative impact might occur in Southern China during summer. In autumn and winter, however, the negative impact possibly occurred in most of the IARs. Moreover, increased TXx in the Pearl River Delta and Yangtze River Delta is possibly related to rapid local urbanization. Climatically, the general increase in temperature extremes across Chinese IARs may be induced by strengthened Northern Hemisphere Subtropical High or weakened Northern Hemisphere Polar Vortex.

     

Spatial and temporal variability of precipitation in Serbia for the period 1961–2010

Monthly, seasonal and annual sums of precipitation in Serbia were analysed in this paper for the period 1961–2010. Latitude, longitude and altitude of 421 precipitation stations and terrain features in their close environment (slope and aspect of terrain within a radius of 10 km around the station) were used to develop a regression model on which spatial distribution of precipitation was calculated. The spatial distribution of annual, June (maximum values for almost all of the stations) and February (minimum values for almost all of the stations) precipitation is presented. Annual precipitation amounts ranged from 500 to 600 mm to over 1100 mm. June precipitation ranged from 60 to 140 mm and February precipitation from 30 to 100 mm. The validation results expressed as root mean square error (RMSE) for monthly sums ranged from 3.9 mm in October (7.5% of the average precipitation for this month) to 6.2 mm in April (10.4%). For seasonal sums, RMSE ranged from 10.4 mm during autumn (6.1% of the average precipitation for this season) to 20.5 mm during winter (13.4%). On the annual scale, RMSE was 68 mm (9.5% of the average amount of precipitation). We further analysed precipitation trends using Sen’s estimation, while the Mann-Kendall test was used for testing the statistical significance of the trends. For most parts of Serbia, the mean annual precipitation trends fell between −5 and +5 and +5 and +15 mm/decade. June precipitation trends were mainly between −8 and +8 mm/decade. February precipitation trends generally ranged from −3 to +3 mm/decade.

     

Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003

An understanding of the relative impacts of the changes in climate variables on crop yield can help develop effective adaptation strategies to cope with climate change. This study was conducted to investigate the effects of the interannual variability and trends in temperature, solar radiation and precipitation during 1961–2003 on wheat and maize yields in a double cropping system at Beijing and Zhengzhou in the North China Plain (NCP), and to examine the relative contributions of each climate variable in isolation. 129 climate scenarios consisting of all the combinations of these climate variables were constructed. Each scenario contained 43 years of observed values of one variable, combined with values of the other two variables from each individual year repeated 43 times. The Agricultural Production Systems Simulator (APSIM) was used to simulate crop yields using the ensemble of generated climate scenarios. The results showed that the warming trend during the study period did not have significant impact on wheat yield potential at both sites, and only had significant negative impact on maize yield potential at Beijing. This is in contrast with previous results on effect of warming. The decreasing trend in solar radiation had a much greater impact on simulated yields of both wheat and maize crops, causing a significant reduction in potential yield of wheat and maize at Beijing. Although decreasing trends in rainfed yield of both simulated wheat and maize were found, the substantial interannual variability of precipitation made the trends less prominent.     

Peculiarities of surface air temperature variations over the Far East regions in 1976–2005

Peculiarities are investigated of the air temperature variation tendencies at some stations of the Far East in 1976–2005. The estimate of linear trend equation coefficients is computed according to the air temperature observation data using the least squares method. It is demonstrated that the air temperature trend in northern regions possesses a small probability at small values of residual variability. In the southern regions, the trend significance increases for almost all seasons at small values of residual variability. At midlatitude stations, the trend significance in January and February decreases considerably due to the large values of residual variability.     

Interannual and decadal variability of the subsurface thermal structure in the Pacific Ocean: 1961–90

Heat content anomalies are analyzed to understand subsurface variability on both aparticular focus on the evolving basinwide patterns and oceanic connections between the extratropics and tropics. Various analyses indicate two distinct modes, one interannual and the other decadal, that involve the tropics and the North Pacific subtropical gyre, respectively. Interannual variability is associated with El Niño in the tropics, with a prominent “see-saw” pattern alternately on and off the equator, and in the east and west, respectively. The interannual cycle features a coherent propagation of subsurface signals around the tropical Pacific, eastward along the equator but westward off the equator at 10–15?°N. Decadal signals are dominant in the subtropics and midlatitudes but also have a tropical component that appears to be independent of interannual variations. An oceanic connection can be seen between subsurface anomalies in the midlatitudes, in the subtropics and tropics on decadal time scales. Subsurface thermal anomalies associated with midlatitude decadal variability can propagate through the subtropics into the tropics, which may modulate the intensity of interannual variability in the tropics. For example, in the middle and late 1970s, a significant warm temperature anomaly appeared to penetrate into the western and central tropics at depth, warming the tropical upper ocean and depressing the thermocline. During the development of El Niño, therefore, an extratropically preconditioned subsurface state (e.g., an enhanced positive heat content anomaly) in the western and central tropical Pacific would favor a warmer sea surface temperature anomaly in the eastern equatorial Pacific, potentially increasing the intensity of ocean-atmosphere coupling. These changes in the thermocline structure and possibly in the coupling strength can further alter the very character of tropical air-sea interactions. This may help to explain decadal variability of El Niño evolution in the tropical Pacific as observed in the 1980s. Our subsurface variability analysis presents observational evidence for the detailed space-time structure of decadal oceanic links between the extratropics and the tropics.     

Climatological responses of winter precipitation in Turkey to variability of the North Atlantic Oscillation during the period 1930–2001

Summary Climatological responses of winter (DJFM) precipitation at 78 stations of Turkey to variability of the North Atlantic Oscillation (NAO) were investigated for the period 1930–2001. The analysis was performed with respect to relationships between precipitation and three different NAO indices (NAOIs) and composite precipitation changes corresponding to the extreme phases of the NAOIs, and individual wet conditions and drought events linked to the extreme NAOI events. Main conclusions of the study can be evaluated as follows:(a) The Ponta Delgada–Reykjavik (PD–R) NAOI is superior among the three NAOIs compared, followed by the Lisbon–Stykkisholmur/Reykjavik NAOI, with regards to its ability to control year-to-year variability in winter precipitation series and composite precipitation conditions corresponding to the extreme NAOI phases in Turkey. (b) Variability of winter precipitation at most stations in Turkey is significantly correlated with variability of the three NAOIs. Negative relationships are stronger over the Marmara, the Mediterranean Transition and the Continental Central Anatolia regions, and the Aegean part of the Mediterranean region. (c) Composite precipitation analysis exhibited an apparent opposite anomaly pattern at the majority of stations between the weak and strong phases of the NAOIs. Composite precipitation means corresponding to the weak NAOI phase are explained mostly by wetter than long-term average conditions, whereas composite precipitation responses to the strong NAOI phase mostly produce drier than long-term average conditions. (d) Composite wet (dry) conditions during the weak (strong) phase of the NAOI are significant at about 32% (69%) of 78 stations for the PD–R NAOI, and about 38% (55%) for the L–S(R) NAOI. The dry signals from the strong NAO phases are stronger and show a larger spatial coherence over Turkey. The significant signals are evident in the west, centre and south of the country. (g) Widespread severe droughts in 1943, 1957, 1973, 1974, 1983, 1989, 1990, 1992, 1993 and 1994, and widespread strong wet conditions in 1940–1942, 1956, 1963, 1966, 1969 and 1970 were linked to the extreme high- and low-index events of at least two NAOIs, respectively.     

Sea surface temperature variability in the shelf‐slope region of the Northwest Atlantic

Abstract

Sea surface temperature (SST) variability in the shelf‐slope region of the northwest Atlantic is described and then explained in terms of latent and sensible heat exchange with the atmosphere. The basic data are primarily engine‐intake temperature measurements made by merchant ships over the period 1946–80. The data have been grouped by month and area and an empirical orthogonal function analysis has been performed to determine the dominant modes of variation. The first two modes account for 44% of the total variance. The first mode corresponds to in‐phase changes of SST from the Grand Banks to Mid‐Atlantic Bight; the second mode corresponds to opposite changes of SST on the Grand Banks and Mid‐Atlantic Bight. The time‐dependent amplitudes of these large‐scale modes have pronounced low‐frequency components; the associated changes in SST are typically 3°C. It is also shown that winter anomalies last longer than summer anomalies; their typical decay scales are 6 and 3 months, respectively.

The onshore component of geostrophic wind is significantly correlated with the amplitude of the first mode in winter. We note the strong land‐sea contrast of temperature and humidity in this region during winter and explain the wind‐SST correlation in terms of latent and sensible heat exchanges. The second mode (i.e. the difference in SST between the Grand Banks and Mid‐Atlantic Bight) also appears to be related to changes in atmospheric circulation during the winter. A stochastic model for mixed layer temperature is finally used to model the SST autocorrelation functions. Following Ruiz de Elvira and Lemke (1982), it includes a seasonally‐varying feedback coefficient. The model successfully reproduces the extended persistence of winter anomalies with physically realistic parameter values but it cannot account for the summer reinforcement of winter anomalies on the Scotian Shelf. We speculate that this is due to the occasional entrainment of water, cooled the previous winter, into the shallow summer mixed layer.     

Trends in extreme temperature indices in Huang-Huai-Hai River Basin of China during 1961–2014

Spatial and temporal characteristics of temperature extremes have been investigated in Huang-Huai-Hai (HHH) region based on the daily series of temperature observations from 162 meteorological stations. A total of 11 indices were used to assess the changes of temperature pattern. Linear trend analyses revealed that the daily maximum temperature (TXx) increased at α = 0.05 level with a magnitude of 0.15 °C per decade on the regional scale during the period of 1961–2014. More pronounced warming trend of the daily minimum temperature (TNn) was detected at a rate of 0.49 °C per decade (α = 0.01 level). Consequently, a decreasing trend of the temperature range of TXx and TNn (extreme temperature range) was observed. The frequency of hot days (TXf90) and annual average of warm events (warm spell duration indicator, WSDI) showed significant increasing trends, while that of cold nights (TNf10) and cold events (cold spell duration indicator, CSDI) showed opposite behaviors. Both warm winter (W-W) and hot summer (H-S) series displayed significant increasing trends at α = 0.01 confidence level. The cold winter (C-W) series showed a decreasing trend at α = 0.01 confidence level, while the cool summer (C-S) series showed a nonsignificant decreasing trend that is not passing the 90% confidence level (α = 0.1). Abrupt increments of warm­related extremes (TXx, TXf90, WSDI) have been detected since 1990s, and a steadily decreasing trend of cold related extremes (TNf10, CSDI) was found since 1970s. Ten hot summers out of 11 and nine warm winters out of 10 occurred after 1990s. Altitude has a large impact on spatial pattern of extreme temperature indices, and the urban heat island effect also has an impact on amplitude of variation in extreme temperature. Trend magnitudes are significantly larger at sites with high altitudes for warm­related indices (TXx, TXf90, WSDI), while those involving cold-related indices (TNn, TNf10) are remarkably larger for stations with low altitudes.     

High temperature extremes in the Czech Republic 1961–2010 and their synoptic variants

Our research focuses on the analysis of extreme high maximum air temperature events (EXHTEs) in the Czech Republic in the period 1961–2010, their climatological characteristics, and on the identification of synoptic-scale circulation conditions conductive to them. EXHTEs are detected using the Weather Extremity Index (WEI) combining return periods of daily maximum air temperature, duration of events, and the extent of the affected area. We selected 37 EXHTEs as non-overlapping periods with the highest WEI. Some long EXHTEs were divided into several shorter synoptically homogeneous episodes. Using the two-level divisive clustering of 700 hPa air temperature and wind field anomalies, we obtained four main variants of synoptic-scale circulation conditions. The most frequent variant associated with extreme episodes is characterized by a westerly flow connected with a high pressure ridge extending northeastward from North Africa over Central Europe or with an anticyclone centered over the Central Mediterranean. The most extreme episodes occurred during the variant characterized by an easterly flow between a high pressure area to the northeast and a low pressure area to the southeast.     

Cycles and shifts: 1,300 years of multi-decadal temperature variability in the Gulf of Alaska

The Gulf of Alaska (GOA) is highly sensitive to shifts in North Pacific climate variability. Here we present an extended tree-ring record of January–September GOA coastal surface air temperatures using tree-ring width data from coniferous trees growing in the mountain ranges along the GOA. The reconstruction (1514–1999), based on living trees, explains 44% of the temperature variance, although, as the number of chronologies decreases back in time, this value decreases to, and remains around ∼30% before 1840. Verification of the calibrated models is, however, robust. Utilizing sub-fossil wood, we extend the GOA reconstruction back to the early eighth century. The GOA reconstruction correlates significantly (95% CL) with both the Pacific Decadal Oscillation Index (0.53) and North Pacific Index (−0.42) and therefore likely yields important information on past climate variability in the North Pacific region. Intervention analysis on the GOA reconstruction identifies the known twentieth century climate shifts around the 1940s and 1970s, although the mid-1920s shift is only weakly expressed. In the context of the full 1,300 years record, the well studied 1976 shift is not unique. Multi-taper method spectral analysis shows that the spectral properties of the living and sub-fossil data are similar, with both records showing significant (95% CL) spectral peaks at ∼9–11, 13–14 and 18–19 years. Singular spectrum analysis identifies (in order of importance) significant oscillatory modes at 18.7, 50.4, 38.0, 91.8, 24.4, 15.3 and 14.1 years. The amplitude of these modes varies through time. It has been suggested (Minobe in Geophys Res Lett 26:855–858, 1999) that the regime shifts during the twentieth century can be explained by the interaction between pentadecadal (50.4 years) and bidecadal (18.7 years) oscillatory modes. Removal of these two modes of variance from our GOA time series does indeed remove the twentieth century shifts, but many are still identified prior to the twentieth century. Our analysis suggests that climate variability of the GOA is very complex, and that much more work is required to understand the underlying oscillatory behavior that is observed in instrumental and proxy records from the North Pacific region.

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Regional mean and variability characteristics of temperature and precipitation over Thailand in 1961–2000 by a regional climate model and their evaluation

This study presents the characterization of regional means and variability of temperature and precipitation in 1961–2000 for Thailand using regional climate model RegCM3. Two fine-resolution (20 km) simulations forced by ERA-40 reanalysis data were performed, with the default land covers and with a land-cover modification strategy suggested by a previous work. The strategy was shown to substantially alleviate the problem of systematic underestimation of temperature given by the default simulation, for most part of Thailand in both dry and wet seasons. The degree of bias in precipitation tends to vary differently in every sub-region and season considered. The patterns of seasonal variation of both climatic variables are acceptably reproduced. Simulated 850-hPa winds have general agreement with those of ERA-40, but wind speed is overestimated over the Gulf of Thailand during the dry months, potentially bringing excessive moisture to and causing more rain than actual in the south. Long-term trends in temperature are reasonably predicted by the model while those in observed and simulated precipitations for upper Thailand are in the opposite directions. Apart from the conventional methods used in characterization, spectral decomposition using Kolmogorov–Zurbenko filters was applied to inspect the model’s capability of accounting for variability (here, in terms of variance) in both climatic variables on three temporal scales (short term, seasonal, and long term). The model was found to closely estimate the total variances in the original time series and fairly predict the relative variance contributions on all temporal scales. The latter finding is in line with the results from an additional spectral coherence analysis. Overall, the model was shown to be acceptably adequate for use in support of further climate studies for Thailand, and its evident strength is the capability of reproducing seasonal characteristics and, to a lesser degree, trends.     

Analysis of the Trends of Thunderstorms in 1951–2007 in Jiangsu Province

Based on the 1951–2007 thunderstorms in Jiangsu, a study is conducted for their climate trends, periodicity, spatiotemporal patterns, and the distributions of the first and last days of the thunderstorms at different guarantee rates (GRs) using climate tendency rate, wavelet analysis, and GR for diagnosis. Results suggest that the inter-annual number of thunderstorm days (TSDs) exhibits a decreasing trend in this province. The trend is displayed mainly in the decreasing TSD number in summer and autumn except in spring, when the variation is not significant in the study period. In this province, the TSD number declines by ~2 days per 10 years. On an inter-annual basis, the pronounced positive departures of the number take place chiefly in the early 1960s, the late 1960s to the early-mid-1970s, the late 1980s, and the late 1990s compared with the negative anomalies dominant in the late 1970s to the mid-1980s, the mid-to-late-1990s, and the late 1990s to 2007. There are vast differences in the initial and ending days at diverse GRs in different areas of the province. At 50% GR, the earliest (last) days occur from mid-March to early April (early to late September) while at 80% GR, the initial (last) days are from late March to early May (early to late October). For the distribution of periods, the periods >8–10 years are relatively stable for the entire province. Based on 1951–2007 period analysis, the region north (south) of the Huaihe River experiences TSDs less (more) than normal days in recent years.     

Long-term variability of UV radiation in the spectral range of 300–380 nm in Moscow

The seasonal and interannual variability of global ultraviolet (UV) radiation in the spectral range of 300-380 nm (0380) in Moscow in 1968-2014 is analyzed. The effect of cloudiness on the magnitude of 0380 is assessed. The smallest (-22...-26%) losses due to cloudiness are registered in May-August, and the highest ones (to -45%) are observed in October-November. According to the UV radiation reconstruction model and measurement data, the long-term deviations of 0380 from the average (for 1968-1997) due to clouds can reach + (11-12)%. The statistically significant positive linear trend in total annual 0380 is revealed from the data of both the reconstruction model and observations (about 1.5% per decade for 1968-2014 and 3% per decade for 1979-2014).     

Interdecadal Variability of the ENSO–North Pacific Atmospheric Circulation in Winter

The interdecadal change in the relationship between the El Niño–Southern Oscillation (ENSO) and atmospheric circulation over the North Pacific is investigated using both observational data and an atmospheric general circulation model. There are two prominent modes of winter mid-latitude atmospheric variability in the North Pacific: the West Pacific (WP) teleconnection and the Aleutian Low (AL). The relationship between ENSO and the WP-AL patterns changed notably around the late 1970s. From 1957 to 1975, during the mature phase of ENSO, significant sea surface temperature anomalies (SSTAs) occurred, mainly in the equatorial eastern Pacific Ocean; the associated atmospheric circulation anomaly pattern resembles the negative phase of a WP teleconnection pattern. In contrast, for the 1978–2011 period, significant negative SSTAs were observed in the western and extratropical Pacific in both hemispheres, with some significant positive SSTAs appearing over the eastern Pacific. This is in agreement with the defined regions of a mega-ENSO, the associated atmospheric circulation anomaly pattern resembles the AL mode. Further analysis suggests that a negative–positive anomaly pattern in the 500?hPa geopotential height throughout the entire North Pacific, possibly enhanced by the SSTAs in the extratropical North Pacific associated with the mature phase of ENSO, is responsible for modulating the relationship between ENSO and the North Pacific atmospheric circulation.     

The role of the intra-daily SST variability in the Indian monsoon variability and monsoon-ENSO–IOD relationships in a global coupled model

The impact of diurnal SST coupling and vertical oceanic resolution on the simulation of the Indian Summer Monsoon (ISM) and its relationships with El Ni?o-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events are studied through the analysis of four integrations of a high resolution Coupled General Circulation Model (CGCM), but with different configurations. The only differences between the four integrations are the frequency of coupling between the ocean and atmosphere for the Sea Surface Temperature (SST) parameter (2 vs. 24?h coupling) and/or the vertical oceanic resolution (31 vs. 301 levels) in the CGCM. Although the summer mean tropical climate is reasonably well captured with all the configurations of the CGCM and is not significantly modified by changing the frequency of SST coupling from once to twelve per day, the ISM–ENSO teleconnections are rather poorly simulated in the two simulations in which SST is exchanged only once per day, independently of the vertical oceanic resolution used in the CGCM. Surprisingly, when 2?h SST coupling is implemented in the CGCM, the ISM–ENSO teleconnection is better simulated, particularly, the complex lead-lag relationships between the two phenomena, in which a weak ISM occurs during the developing phase of an El Ni?o event in the Pacific, are closely resembling the observed ones. Evidence is presented to show that these improvements are related to changes in the characteristics of the model’s El Ni?o which has a more realistic evolution in its developing and decaying phases, a stronger amplitude and a shift to lower frequencies when a 2-hourly SST coupling strategy is implemented without any significant changes in the basic state of the CGCM. As a consequence of these improvements in ENSO variability, the lead relationships between Indo-Pacific SSTs and ISM rainfall resemble the observed patterns more closely, the ISM–ENSO teleconnection is strengthened during boreal summer and ISM rainfall power spectrum is in better agreement with observations. On the other hand, the ISM–IOD teleconnection is sensitive to both SST coupling frequency and the vertical oceanic resolution, but increasing the vertical oceanic resolution is degrading the ISM–IOD teleconnection in the CGCM. These results highlight the need of a proper assessment of both temporal scale interactions and coupling strategies in order to improve current CGCMs. These results, which must be confirmed with other CGCMs, have also important implications for dynamical seasonal prediction systems or climate change projections of the monsoon.     

Precipitation and temperature space–time variability and extremes in the Mediterranean region: evaluation of dynamical and statistical downscaling methods

This study evaluates how statistical and dynamical downscaling models as well as combined approach perform in retrieving the space–time variability of near-surface temperature and rainfall, as well as their extremes, over the whole Mediterranean region. The dynamical downscaling model used in this study is the Weather Research and Forecasting (WRF) model with varying land-surface models and resolutions (20 and 50 km) and the statistical tool is the Cumulative Distribution Function-transform (CDF-t). To achieve a spatially resolved downscaling over the Mediterranean basin, the European Climate Assessment and Dataset (ECA&D) gridded dataset is used for calibration and evaluation of the downscaling models. In the frame of HyMeX and MED-CORDEX international programs, the downscaling is performed on ERA-I reanalysis over the 1989–2008 period. The results show that despite local calibration, CDF-t produces more accurate spatial variability of near-surface temperature and rainfall with respect to ECA&D than WRF which solves the three-dimensional equation of conservation. This first suggests that at 20–50 km resolutions, these three-dimensional processes only weakly contribute to the local value of temperature and precipitation with respect to local one-dimensional processes. Calibration of CDF-t at each individual grid point is thus sufficient to reproduce accurately the spatial pattern. A second explanation is the use of gridded data such as ECA&D which smoothes in part the horizontal variability after data interpolation and damps the added value of dynamical downscaling. This explains partly the absence of added-value of the 2-stage downscaling approach which combines statistical and dynamical downscaling models. The temporal variability of statistically downscaled temperature and rainfall is finally strongly driven by the temporal variability of its forcing (here ERA-Interim or WRF simulations). CDF-t is thus efficient as a bias correction tool but does not show any added-value regarding the time variability of the downscaled field. Finally, the quality of the reference observation dataset is a key issue. Comparison of CDF-t calibrated with ECA&D dataset and WRF simulations to local measurements from weather stations not assimilated in ECA&D, shows that the temporal variability of the downscaled data with respect to the local observations is closer to the local measurements than to ECA&D data. This highlights the strong added-value of dynamical downscaling which improves the temporal variability of the atmospheric dynamics with regard to the driving model. This article highlights the benefits and inconveniences emerging from the use of both downscaling techniques for climate research. Our goal is to contribute to the discussion on the use of downscaling tools to assess the impact of climate change on regional scales.