Atmospheric Research 119 (2013) 131–139

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Atmospheric Research

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Evaluation of the warm season diurnal cycle of precipitation over Swedensimulated by the Rossby Centre regional climate model RCA3

Alexander Walther a,⁎, Jee-Hoon Jeong a, Grigory Nikulin b, Colin Jones b, Deliang Chen a,1

a Department of Earth Sciences, University of Gothenburg, Gothenburg, Swedenb Rossby Centre, SMHI, Norrköping, Sweden

a r t i c l e i n f o

⁎ Corresponding author at: Department of Earth SGothenburg, Box 460, 405 30 Gothenburg, Sweden. Te

E-mail address: alexander.walther@gvc.gu.se (A. W1 Currently on leave.

0169-8095/$ – see front matter © 2011 Elsevier B.V. Adoi:10.1016/j.atmosres.2011.10.012

a b s t r a c t

Article history:Received 20 January 2011Received in revised form 19 October 2011Accepted 21 October 2011

This study examines the diurnal cycle of precipitation over Sweden for the warm season (Aprilto September) both in hourly observational data and in simulations from the Rossby Centreregional climate model (RCA3). A series of parallel long-term simulations of RCA3 with differenthorizontal resolutions – 50, 25, 12, and 6 km –were analyzed to investigate the sensitivity of themodel's horizontal resolution to the simulated diurnal cycle of precipitation. Overall, a clear dis-tinction between an afternoon peak for inland stations and an early morning peak for stationsalong the Eastern coast is commonly found both in observation and model results. However,the diurnal cycle estimated from the model simulations show too early afternoon peaks withtoo large amplitude compared to the observation. Increasing horizontal model resolution tendsto reduce this bias both in peak timing and amplitude, but this resolution effect seems not to bemonotonic; this is clearly seen only when comparing coarser resolution results with the6 km resolution result. As the resolution increases, the peak timing and amplitude of the diurnalcycle of resolved large-scale precipitation become more similar to the observed cycle of totalprecipitation while the contribution of subgrid scale convective precipitation to the total pre-cipitation decreases. An increase in resolution also tends to reduce too much precipitation ofrelatively light intensity over inland compared to the observation, which may also contributeto the more realistic simulation of the afternoon peak in convective precipitation.

© 2011 Elsevier B.V. All rights reserved.

Keywords:Precipitation diurnal cycleRegional climate modelResolution dependencyConvective precipitation

1. Introduction

The diurnal cycle of precipitation is one of the fundamentalnatural variations found in the earth's climate system. Thepunctual diurnal variation of incoming solar radiation associatedwith diurnal changes in otherweather and climate variables liketemperature and vertical motion yield the diurnal cycle ofprecipitation. Extensive studies based on in-situ and satelliteobservation have addressed various dynamical mechanismsto cause and modulate diurnal variation of precipitation (e.g.Brier and Simpson, 1969; Dai and Deser, 1999; Dai and Wang,1999; Wallace, 1975), but still much uncertainty remains.

ciences, University ofl.: +46 31 7862867.alther).

ll rights reserved.

Overall, the nighttime peak in maritime climate vs. the lateafternoon peak in continental climate are the most pro-nounced features of the diurnal cycle of precipitation foundin the climate system (Dai, 2001a, 2001b), although de-tailed regional representations vary greatly depending on theseason and topographical conditions (e.g. Lee et al., 2007; Yinet al., 2009).

Despite of its fundamentality inweather and climate, globaland regional climate models still have large difficulties inreproducing the observed diurnal cycle of precipitation,especially those found on local and regional scale (Guichardet al., 2004; Lenderink and van Meijgaard, 2008; Michaelideset al., 2009; Rio et al., 2009; Shin et al., 2007; Zhang et al.,2008). One of the most common biases in climate models istoo early initiation of the afternoon peak in the continentalarea, which is known to attribute considerably to difficultiesin simulating realistic convective activities occurring on sub-

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Fig. 1. a) Geographical locations of observation stations of the hourly precipita-tion network over Sweden. The fraction of missing values in the original stationseries is indicated by symbols. b) An example of the estimated diurnal cycle ofprecipitation amount from observation and RCA3 simulations with 4 differentresolutions for the ‘Malexander’ station (marked with a black circle in themap).

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grid scales. For instance, too much sensitivity in the convectiveformulation in the currentmodels initiate too frequent convec-tive activities of relatively light intensity in the early afternoonwhich prevent the accumulation of available energy to invokestronger convection in the later afternoon (e.g. Lee et al.,2008; Rio et al., 2009; Shin et al., 2007). Previous studies withclimate models suggested that this bias is sensitive to thechoice of the models' convective or cumulus parameterization(e.g. Liang, 2004; Rio et al., 2009) as different schemes showdifferent diurnal cycle characteristics depending on thegeographical locations. Another crucial factor to determinethe characteristics of a realistic diurnal cycle is the model'sspatial resolution,which needs to be sufficiently fine to resolvesub-grid scale processes associated with convective activities,and it has been generally suggested that a finer horizontalresolution simulates the diurnal cycle and other precipitationparameters more realistically (Lee et al., 2007; Rauscher et al.,2010; Shin et al., 2007; Wehner et al., 2010).

The purpose of this study is to investigate the general per-formance of the Rossby Centre regional climate model (RCA3)to simulate the observed warm season diurnal cycle of precip-itation over Sweden. In our recentwork (Jeong et al., 2011), theoverall features of the diurnal precipitation cycle in Swedenwere estimated both in hourly observational data, and an initialcomparison with the simulated diurnal cycle by the RossbyCentre regional climate model (RCA3) with 50 km horizontalresolution was made. Here we utilized a parallel series ofRCA3 simulations for the same period but with finer horizontalresolution: 25, 12, and 6 km, in order to investigate the sensitiv-ity of the horizontal resolution on the simulated characteristicsof the diurnal cycle. The contribution of convective precipitationvs. precipitation from large-scale condensation to the total pre-cipitation amount and its diurnal cycle was investigated.

The following Section 2 describes the hourly observationaldata of precipitation in Sweden and the RCM simulations, andthe method used to estimate the peak and amplitude of thediurnal cycle. In Section 3 the general characteristics of thediurnal precipitation cycle in the observations and simulationsare presented, followed by discussions in Section 4.

2. Data and methods

2.1. Observed hourly precipitation data

The observed hourly precipitation records from93 stations inSweden for 1996–2008 provided by the SwedishMeteorologicaland Hydrological Institute (SMHI) are utilized. Measurements ateach station are conducted by wind-shielded GEONOR automat-ic precipitation gauges (Bakkehoi et al., 1985)which yield hourlyprecipitation rates with a resolution of 0.1 mm/h. The precipita-tion designated to a certain hour is the amount accumulatedduring the past 60 min. The stations are relativelywell distribut-ed over the entire Sweden, coveringmost of the plains in south-ern and middle Sweden, the northern mountainous region, aswell as the coastal region along the Baltic Sea (Fig. 1a). Followingthe guidelines of the SMHI data distribution center, initialquality control was conducted to remove erroneous negativevalues. Some additional quality control were conducted byfollowing Jeong et al. (2011) in order to remove unrealisticallyhigh values. All these erroneous values were set to missingrecords, but occupy only a very small fraction (0.0004%) of

total records. The research area, 55–70 N/10–25E, is locatedin the zone of boreal and sub-arctic climates with maritimecharacter along the west coast and the coast to the BalticSea and more continental influence in the Swedish inland

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on the lee-side of the Scandinavianmountains. There is year-round precipitation peaking summer to autumn with a bigamount originating from thunderstorms. The highest offi-cial daily total rainfall recorded is 198 mm (1997, NorthernSweden). Daily amounts above 20 mm are considered as heavyrain. According to Dahlström (2006), the maximum 10min (1-hour) rainfall recorded is around 30 mm (110 mm).

2.2. RCA3 experiments

Weevaluated the characteristics of the diurnal precipitationcycle simulated with a regional climate model by comparingthose with observational records. Long-term simulations ofthe Rossby Centre Atmospheric Model version 3 (RCA3) wereanalyzed. The RCA3 is known to be one of the best models insimulating weather and climate over Sweden and Scandinavia(Kjellström et al., 2005) and has been extensively utilized fornumerous climate impact studies (Ghatak et al., 2010).

We utilized RCA3 experiments conducted with 4 differentspatial resolutions: approximately 50, 25, 12, and 6 km with24 unequally spaced hybrid terrain-following vertical levels.Originally, all experiments were run from 1961-present.Only the 6 km experiment covers a shorter period — 1987-present. For the comparison only the results for the overlappingperiod with the hourly observations, 1996–2008, was used.From the model experiments, total precipitation (1-hourly),large-scale and convective precipitation (3-hourly) was used.All simulations were driven with data from the ERA40re-analysis (Uppala et al., 2005) until 8/2002 and ERA-Interim (Dee et al., 2011) thereafter. Identical model physicsand dynamics were utilized. The basic topography and landuse type datasets used are at 1 km resolution and were con-verted to each of the designated resolutions. The only differencebetween the simulations is the computation time-step interval(30 min, 20 min, 10 min, and 7.5 min for 50 km, 25 km, 12 km,and 6 km simulation respectively) in order to meet computa-tional stability for the chosen horizontal resolution. The modeldomain covers most of Europe using a rotated latitude-longitude coordinate system; the latitude range is about26–72°N, and the corresponding longitude range is about4°W–34°E and 33°W–57°E at the southern and northernboundary, respectively. The land-surface scheme used is aso-called tiled scheme (Samuelsson et al., 2006) meaningthat each grid cell consists of several tiles with individualsurface properties and for which a separate energy balanceis calculated. The Kain–Fritsch-scheme was used for theparameterization of convective clouds at subgrid scale. Re-solved large-scale clouds are described using the scheme ofRasch and Kristjánsson. For further details on the dynamicaland physical treatments of RCA3 the reader is referred toSamuelsson et al. (2006).

When comparing the simulation results with observa-tions, the simulated precipitation data were taken from gridpoints closest to the 93 observational stations without anyspatial interpolation process in order to preserve the ratherlocalized characteristics of precipitation events.

2.3. Determination of the diurnal cycle of precipitation

The diurnal cycle of precipitation was objectively estimatedby using long-term observational records and corresponding

results from RCA3 simulations. Here we followed the method-ology described in Jeong et al. (2011). Firstly, a long-termaverage of the hourly precipitation amount P– at each station(or corresponding grid points for model simulations) for theentire analysis period was calculated. Secondly, applying theharmonic analysis technique (Angelis and McGregor, 2004;Wilks, 2006) the diurnal variation of a chosen station (Pe) athour h was determined by the summation of sinusoidal har-monics as

Pe hð Þ ¼ P−þ∑

kCkcos

2πkh24

−θk

� �þ residual ð1Þ

where P−

is the 24-hour mean of P−, k is the harmonic number

(i.e., 1 for the 24-hour cycle), and Ck and θk are the amplitudeand the phase of the given kth harmonic. In this study, the sum-mation of the 1st (24-hour frequency; k=1) and 2nd (12-hourfrequency; k=2) part of the harmonics was defined as mean(smoothed) diurnal cycle. The amplitude of this smootheddiurnal cycle was determined as half the difference betweenmaximum and minimum value within the average 24-hourcycle, and the peak timing as the time when the maximumvalue is found. An example of the diurnal precipitation cycleobserved and modeled is shown in Fig. 1b. The diurnal cyclemodeled by the 1st and 2nd harmonics well represent both,amplitude and peak phase of the diurnal cycle obtained fromobserved raw data (Jeong et al., 2011).

3. Results

The observed diurnal cycle for the summer season overSweden shows clear temporal and spatial characteristics(Fig. 2a). A pronounced rainfall peak in the afternoon isfound for most inland stations all over Sweden, both in theSouthern plains and in the Northern mountains. The rainfallamounts peak largely between 15 and 18 LST. In contrast,stations along the Eastern coast show a night or early morningpeak around 02–06 LST. Jeong et al. (2011) suggested thatconvective precipitation activity is themain cause for the inlandafternoon peak while the night or early morning peak for sta-tions along the eastern coast is linked to non-convective rainfallevents emerging from frontal systemswithin the land-sea breezecirculation. It appears that all model simulations relatively wellcapture the principal spatial pattern of the diurnal cycle interms of the amplitude and peak timing, but there is a more orless pronounced deficiency. The amplitude is much overesti-mated in the 50 km model especially for the mid and southernplains, and gets closer to the observed as the model resolutionincreases to 25, 12 and 6 km. For the peak timing, the 50 kmsimulation exhibits the largest bias; most of the inland sta-tions produce a too early afternoon peak showing quite uniformpeak timing around noon, which is earlier than observed by upto 5 h. It appears that this bias becomes smaller as the horizontalresolution increases. However, this effect is the most distinctwhen the resolution comes to 6 km while there is only littleimprovement from the 50 via the 25 to the 12 km simulation.This is more clearly seen in Fig. 3 where the bias betweenobserved and modeled peak timing is presented. For the vastmajority of stations the peak timing is simulated too early(downward triangle). Light red to orange colors, i.e. bias of upto 4 h, are dominating the maps showing the bias of the 50, 25and 12 km simulations. There is a slight trend toward smaller

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Fig. 2. Observed and modeled peak timing of the diurnal cycle of precipitation amount (from left to right). The peak timing at each station is indicated by thefilling color of the circle. The strength of the diurnal cycle is indicated by gray shading [mm].

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bias in the 12 km simulation. However, as mentioned before, asignificant improvement in performance can be seen in the6 km simulation. Table 1 shows the bias between observedandmodeled peak timing as fraction of stations in [%] for differ-ent intervals. For the 50, 25 and 12 km simulations, the largestfraction is found in the bias range −4 and −2 h, but in therange between −1 h and +1 h for 6 km resolution (49.46%).For 15% of the locations the peak timing modeled matches thepeak observed with no bias in the 6 km run. The numbers are

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Fig. 3. Difference between simulated and observed peak timing of precipitation amtriangle, square) indicate the model simulating the peak at the same hour (earlier,

5.4%/9.7%/9.7% for the 50/25/12 km runs, respectively whichclearly underlines the better performance of the higher resolu-tions, and of the 6 km resolution in particular.

Jeong et al. (2011) found that the RCA3 model with 50 kmresolution tends to overestimate the occurrence frequency ofrelatively light precipitation over inland, which might contrib-ute the bias of the simulated diurnal cycle. This can also beseen in Fig. 4 where the observed versus simulated precipitationfrequency is shown for the three regional domains: Northern

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Table 1Fraction of stations [%] where the bias of the simulated peak timing withrespect to the peak timing observed falls into the designated range. Example:in the 25 km simulation for 11.83% of the stations the diurnal peak is modeled5 to 7 h earlier than observation.

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mountains (north of 60°N), Southern plains (south of 60°N), andEastern coast (within 20 km from the shore, east of 15°E) toexamine the regional difference. First, it is found that there isa clear difference between the two inland domains and theEastern coast. At the Eastern coast stations the model bias isrelatively smaller and there is no clear difference in performancefor different periods during the day, again confirming thatthe diurnal cycle along the Baltic Sea coast is present, but ratherweak. All simulations largely overestimate the precipitationfrequency compared to observation with a factor of 3–5.Model resolution increase is coupled to a decrease in precip-itation frequency coming closer to the observed values. Thisis most pronounced in the Northern mountains having themost complicated terrain, where the mean frequency isaround 60% in the 50 km simulation decreasing to 46% inthe 6 km run. When examining the observed vs modeledprecipitation amount (not shown here) it becomes obviousthat too high precipitation amounts originate from the runwith the coarsest resolution (50 km) around noon (12LST). The inter-model difference of the mean amount is notas large as for the modeled mean precipitation frequencyas shown in Fig. 4.

Based on the identified bias of the simulated diurnal cycledepending on the horizontal resolution, we further investigatedthe contribution from different precipitation processes – large-scale condensational and convective precipitation – to the biasin the diurnal cycle separately. The diurnal cycle estimatedfrom the total, convective and large-scale precipitation fromthe 4 different RCA3 simulations averaged for the tree regions

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Fig. 4. Scatter plot of observed versus simulated precipitation amount from the esdot represents the observed rainfall amount at one station at an hour of the diurnalcorresponding time of the day is indicated by colors and the respective model ressymbol.

are shown in Fig. 5. Again, a clear distinction between an after-noon peak for inland vs. an early morning peak in Easterncoast, as well as the model bias is seen. For the inland domain,the convective precipitation tends to decrease almostmonoton-ically with increasing resolution, whereas the large-scale partincreases: among the simulations the 6 km run has the highestlarge-scale and the least convective precipitation. For the inlandstations in the Northern and Southern domain the convectiveprecipitation cycle shows a distinct afternoon peak with thepeak timing slightly shifting later, that is closer to the observedone, with increasing model resolution, of which amplitude andtiming is getting to be more similar to those from total precipi-tation observed. The amplitude of the large-scale precipitationcycle is much weaker than that of convective precipitation andthe peak is found in the early morning for the 50, 25 and12 km simulations. In contrast, the 6 km simulation exhibitsan afternoon peak, even though with small amplitude, whichoccurs slightly after the peak timing of the observed diurnalcycle of total precipitation. Summarizing these results, we mayconclude that the least bias of peak timing and amplitudeof the diurnal cycle in the 6 km simulation is contributed by acombination of the more realistic simulation of the convectiveprecipitation cycle, and partly by the late afternoon peak inlarge-scale condensational precipitation. For the diurnal cyclein the East coast, all simulations roughly capture the earlymorning peak, which seems to be mostly contributed bylarge-scale precipitation. However, the effect of the increasingresolution is not obviously found in the East coast. The ampli-tude and peak timing in the 50 km and 25 km simulations aremore similar to observations than the 6 km experiment. Thepeak timing in the early morning peak along the Easterncoast is more contributed by the non-convective precipitationprocesses linked to the coastal environment along the BalticSea, thus increased resolution or improved simulation ofconvective precipitation does not have effective significanteffect on the performance of the simulation.

All 4 simulations largely overestimate the precipitationamount observed. Although the peak time and amplitude ofthe simulated diurnal cycle is much improved in the 6 kmresolution, the model still overestimates the total amount ofprecipitation by about 30% compared to the observation

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Fig. 5. Diurnal cycle of precipitation amount for 3 representative regions: observed total precipitation (bold blue line), simulated total precipitation (bold solidlines), simulated convective precipitation (thin solid lines) and simulated large-scale precipitation (dotted lines).

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(see lines with total precipitation in Fig. 3). This could becontributed by the too sensitive and frequent initiation ofconvective precipitation events as suggested by previousmodel studies (Lee et al., 2007; Sato et al., 2009; Shin et al.,2007). Focusing on the afternoon peak, we compare the ob-served and simulated total, convective and large-scale pre-cipitation frequency for 12–18 LST in Fig. 6. All simulationsoverestimate the frequency of total precipitation by about30 to 60% compared to observations with a frequency rangebetween 6 and 16%. The minimum frequency in the simula-tions is around 35% with a maximum of about 75% (50 km),65% (25 km), 55% (12 km) and 50% (6 km). For the RCA3simulations, the most pronounced pattern is too frequentprecipitation events in the Scandinavian mountain rangehaving the most complicated topography within the studyarea, while the observations provide a spatially diverse patternwith more regions of frequent precipitation events peaking insouthern and central Sweden. As the horizontal resolutionincreases, this bias continuously decreases. Recalling the de-creasing amount of convective precipitation with increasinghorizontal resolution shown in Fig. 5, the reduced amount ofprecipitation in finer resolution seems to bemostly contributedby the reduced convective precipitation, while showing more

similar amplitude and peak timing of the diurnal cycle to thosefrom observed total precipitation. Too high precipitationfrequency over themountains is also evident in the convectiveand large-scale simulations (Fig. 6). Resolution increase alsohere leads to frequency decrease over this area. Outside thecoremountain area large-scale precipitation frequency increaseswhereas convective precipitation frequency decreases withincreasing model resolution. The observed spatial frequencypattern (bottom left) in Southern and Central Sweden israther diverse and the spatial variability is best reproducedin the simulated 12 and 6 km convective precipitation.

4. Summary and discussion

The amplitude and peak timing of the diurnal cycle inSweden were objectively determined from hourly observationsand RCA3 simulations with 4 different horizontal resolutions.The simulations capture the principal characteristics of theobserved diurnal cycle quite well but, in general, show atoo early afternoon peak in large parts of the inland regionsbeing mostly contributed by convective activity which isfound in late afternoon (15–18 LST) in the observationaldata. The finer the model's horizontal resolution, the more

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Fig. 6. Frequency of precipitation events (prec>0 mm) for LST 12–18 obtained from the observations (bottom left) and from the RCA3 simulated total precipitation(p-tot, top panel), large-scale precipitation (p-ls, middle panel) and convective precipitation (p-conv, bottom panel) for all model resolutions (50-6 km from left toright) in [%]. Note the different color scales for obs/p-conv and p-tot/p-ls.

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realistically simulated the peak timing and amplitude of thediurnal cycle compared to the observations, and the less ofthe simulated precipitation coming from the parameterizedconvective precipitation on the sub-grid scale. The fractionof convective/large-scale precipitation gradually decreases/increases with finer grid resolution and the afternoon peakin the convective rainfall curve is shifting later towards therainfall peak observed. However, in the 6 km simulation thispeak is still 1–2 h earlier than the afternoon peak observed.There is an abrupt change in the shape of the diurnal cycle ofconvective/large-scale precipitation from 12 to 6 km. The

more realistic simulation of the afternoon peak in the 6 kmmodel is mostly contributed by the diurnal cycle of resolvedlarge-scale precipitation showing an inland afternoon peakone hour ahead the observed one, which is dominant overthe diurnal cycle of subgrid scale convective rainfall at thefinest resolution.

An improved convective parameterization scheme couldsignificantly improve the performance of the diurnal cyclesimulations. The scheme used for convective parameterizationin RCA3 – the Kain–Fritsch convection scheme –was enhancedcompared to the previous model version (RCA2) in the way

138 A. Walther et al. / Atmospheric Research 119 (2013) 131–139

that shallow convection is assumed to be non-precipitating.Nevertheless, the scheme seems to be still too sensitive whenit comes to the initiation of deep convection, which does notchange significantly with an increase in resolution regardingthe peak timing coinciding with findings obtained by Lee etal. (2007). The relative influence of convective and large-scaleprecipitation on the simulated diurnal cycle was suggested,but it remains uncertain and not easy to validate because thedistinction between the convective and large-scale precipitationin the observations is almost impossible. Depending on themodel resolution, convective and large-scale precipitationcontributes differently to the diurnal cycle of total precipita-tion. The rather abrupt improvement from the 12 km to the6 km simulation may indicate a direct coupling between thesetwo precipitation types. Convective processes in the 6 km simu-lation may act as a moisture supply triggering increased large-scale precipitation with some hours delay instead of producingprecipitation from the convective scheme. This question cannotbe answered satisfactorily with the data available at this stageand within the scope of this study. However, results froman initial analysis suggest that convective and large-scaleprecipitation are not coincident and in this way not relateddirectly.

The results of this study are based on precipitation recordsonly. Further examination of the local circulation, and energyand heating distribution associated with convective instabilityis required to reveal underlying physical processes in detail.For instance, our results suggest that the sensitivity of thesimulated diurnal cycle change is found to be not monotonicwith a considerable jump between 12 km and 6 km resolution.Thismay imply that a certain dynamical/physical process beingresolvable with a resolution finer then 12 km may greatlycontribute the realistic simulation of the diurnal cycle.

The summer season 24-h cycle is the main focus of thisstudy. However, also a semidiurnal (12-h) peak is evidentduring nighttime over the inland regions and afternoonalong the East coast. The 24-h cycle is well dominant overthe 12-h cycle and is rather weak when looking at the regionalmeans. Dai (2001b) distinguishes between different precipita-tion categories ranging from drizzle to showery precipitation,where the former contributes to nighttime peaks and the lattermostly to afternoon peaks over land. The cause for the semidi-urnal peak can be twofold. First, it could be a real secondarypeak as suggested by Dai (2001b). Another explanation is thesuperposition of precipitation peaks originating from differentdays being mixed when calculating the average cycle. Resultsfrom an initial analysis based on the data available suggestthat both causes contribute to similar extent in the studyarea. The time-mean total rainfall amount and the strengthof the diurnal cycle seem to be related to some degree. Forexample, precipitation amounts along the East coast arelower and the diurnal cycle weaker compared to higheramounts and a stronger cycle for the inland regions.

The performance to resolve a realistic diurnal cycle of pre-cipitation is, of course, very sensitive to the model's physicalparameterizations especially associatedwith parameterizationsin planetary boundary layer processes and cumulus convection.Given the aforementioned role of convective and large-scaleprecipitation among the simulations, an explicit sensitivity testof the convective parameterization scheme could help answer-ing the question whether an improved scheme would also lead

to a significantly better simulated total precipitation cycle. Weplan to test the changes in characteristics of the precipitation di-urnal cycle from the improvement of model physics in theupdated version of RCA – RCA4. The comparison of the sensi-tivity of the horizontal resolution and that of updated phys-ics on the precipitation diurnal cycle from two successiveversions of the model will possibly be made, and could providea good and simple metric to test the change in model perfor-mance. Also, efforts will be put on the investigation of possiblefuture changes of the diurnal cycle under climate change condi-tions using regional climate model simulations forced withdifferent GCM scenarios.

Acknowledgment

We thank the Swedish Meteorological and HydrologicalInstitute (SMHI) for providing the hourly rainfall observationsand the Rossby Centre for the access to the climate simulations.The Swedish Research Council (VR), the Gothenburg Atmo-spheric Science Centre (GAC) and FORMAS (grant #2007-1048-8700∗51) are thanked for support to Deliang Chen andAlexanderWalther. TheCentre of Earth SystemScience (TELLUS)at the University of Gothenburg supported Jee-Hoon Jeong. Partof this work was conducted under the Swedish Mistra-SWECIAprogram. Last but not least we thank the two reviewers forvery constructive and critical comments, which helped toimprove this manuscript significantly.

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