port than from the existing stationary humidity sto humidity stationary existing the from than port balancing influence of the North Sea and the Baltic the and Sea North the of influence balancing precipitation depths. The drier regions lie on the the on lie regions drier The depths. precipitation there is mainly convective. Then precipitation is g is precipitation Then convective. mainly is there a fluxes humidity related weather-type changing, on German Southern In fields. precipitation subsequent variability with with deviation: standard percentage the to equal coeffi variability The percentage. as it express to arithm the with it standardise to but s, use to not Conseque of the spatial distribution precipitation. tion. of Mapping would thus the deviation standard also is higher the depth, precipitation the higher it around series observation an of scatter temporal simple a as used is s deviation standard the Often, years, single in site months.given a at values mean these o may to deviate how the know wide values necessary it computations, hydrological in values mean using mean these from considerably may deviate and months of the reference period 1961–1990. However, single obs the of values mean the show 2.6 to 2.2 Maps The precipitation.than v less much are whil years and months, days, sunshine, over on values dependent course diurnal temperature air distinct like elements weather other events, di the to contrast In precipitation. of variability mainly is WMO, by defined period reference 30-year groundwater recharge. The length of the currentdeterminati int or balance water a of establishment the range from 0 to 100 percent. 100 to 0 from range the of values The conditions. orographic and types variations of precipitation depths around the mean bet a gives standardisation The series. observation However, besides spatial variability, knowledge of of knowledge variability, spatial besides However, is average areal the 1961–1990; period the of values annual 1 about of span a with depths precipitation mean of wide the of impression an give 2.6 to 2.2 Maps The Variability Coefficient of Precipitation Depth2.7 ity coefficients of the single months shown in Map Map in shown months single the of coefficients ity distributi The different. very be may months single distribution the that illustrate examples two These mm. 5 than toward decreases depth precipitation character, tal received precipitation depths above 25 mm. With inc the Saarland, the southern Black Forest, and the ea (Rhineland Rheinland-Pfalz of south-west the tains, Sa the only 1972 and February in Consequently, country. south-west extreme the over only influence gain over Germany, so that low-pressure areas with ai humid southeasterly 1972, February of month dry the In mm. 400 than more to mm 25 from spatial the of Mountain span The Altmark. the in Harz and Forest, the Forest), (Palatinate Wald Pfälzer st areas these mountains, all of sides windward the mean annual precipitation distribution (Map 2.2). D mer month. The of distribution coinci precipitation for a mo is and exemplary types weather western ent Precipitation in the wet month of July 1980 is char ten-fold. the than more e. i. 1980 July in and mm 10.8 to amounted 1972 February depth precipitation 2). areal mean (Figure The 1972 one lowest the with month the and – 1) (Figure 1980 reference the of depth precipitation areal highest durin distribution precipitation the by va illustrated may depths precipitation monthly extent which To averaged.then ity coefficients of the single months are first com 1990 to of a precipitatio mean distribution monthly rela by computed not are months the of coefficients mont of variations annual the eliminate to order In precipi annual of scatter little the for reason One lit only differ uplands Harz and Sauerland the Also with Oberrheingraben, minor differences between the (Black Forest), the variability coefficient of annu insta For depths. precipitation annual mean the ing however, Here do not sh of the mountains the ridges of Spessa uplands the around and (Lusatia), Lausitz m Other Mountains. Harz the of foreland eastern the coefficien variability the Germany, Central Towards slightly only is deviation standard percentage the throug and coast, Sea Baltic the on Lowland, German below remaining lowest, the the are In variations temporal percent. 24 and 11 between range cells grid annu the of coefficient variability Map the A shows elimin to smoothed is representation data. grid The computa all error, measuring systematic the of tion Since the behaviour of the temporal precipitation v determined. is months me the Additionally, 1961–1990. period the of years com is coefficient variability the 2.6, to 2.2 Maps Similar to the mean depths precipitation of the yea } } }}}} }}}}  Variability coefficient of the years Map Structures Variability coefficient of the months

being the mean value of the single elements x elements single the of value mean the being V is essential in any water-resources planning issue planning water-resources any in essential is s x ⋅= 100 with with s = n 1 − 1 ∑ j = n 1 j − )xx( 2

al precipitation depths is just as high as in the g the month with the with month the g puted separately andputed separately cient V in percent is percent V cient in etic mean value and value mean etic ntly, it is reasonable this standard devia- standard this screte precipitation screte acterised by persist- higher at 16 percent. 16 at higher tation depths on the coasts is probably the probably is coasts the on depths tation leeward side of the of side leeward rs rs and hydrological half-years shown in the value due to different influences of weather ernationally agreed stern stern Alpine region ariability ariability is nearly independent of a correc- puted for the years und hydrological half- hydrological und years the for puted rage. enerated less by advective humidity trans- humidity advective by less enerated of precipitation in precipitation of des des nearly with the ter area-related visualisation of the spatial the of visualisation area-related ter s mean value. The value. mean s n, n, but the variabil- ate station extremes. station ate nce on higher ground in the Schwarzwald the in ground higher on nce ue to stemming on tle from the surrounding lowland regions. lowland surrounding the from tle on of the variabil- the of on variation reaches variation and out with high with out and essentially reflectessentially rt, Odenwald, and and VogelsbergOdenwald, rt, mountains. series – i. e. July e. i. – series tions use uncorrected precipitation depth precipitation uncorrected use tions over Germany in Germany over al precipitation depths. The values of the of values The depths. precipitation al ow outstanding values as do they regard-values ow outstanding years, years, half-years, reasing continen- ting the 360 months of the period 1961– period the of months 360 the ting s the east to less to east the s measure for the for measure B is very similar very is B y, precipitation is usually less dependent less usually y,is precipitation air masses could nsoon-type sum-nsoon-type s – especially in summer – precipitation – summer in especially – s hly precipitation depths, the variability the depths, precipitation hly variability coefficient are always in the in always are coefficient variability t increases and reaches its maximum in maximum its reaches and increases t spatial variation spatial axima are located around Kassel, in the in Kassel, around located are axima northern and the southern Black Forest. 14 percent, with minima in the North- the in minima with percent, 14 -Palatinate) and -Palatinate) – i. e. February e. i. – is consequently is on of the mean the of on Sea with high humidity transport and transport humidity high with Sea rflow prevailed rflow 500 mm in the in mm 500 an variability coefficient of the single the of coefficient variability an n average fromn average uerland Moun- uerland due to the high the to due hout the Alpine piedmont. In the the Alps, In piedmont. the Alpine hout ariable in time in ariable north and the south of Germany, the Germany, of south the and north ervation series ervation half-years, or half-years, values. values. When often have a have often the the e their mean their e to 133.5 mm, 133.5 to south of the of south j ry in time is time in ry s, the Black the s, and n the number of values in the in values of number the n and temporal 779 mm. 779 , such as such , Fig. 1 Precipitation depth of the wettest month of t of month wettest the of depth Precipitation 1 Fig. Fig. 2 Precipitation depth of the dryest month of th of month dryest the of depth Precipitation 2 Fig. 10 75 100 125 150 175 200 300 400 mm 400 300 200 175 150 125 100 75 10 10 75 100 125 150 175 200 300 400 mm 400 300 200 175 150 125 100 75 10 30 30 reference period 1961–1990: July 1980July 1961–1990: period reference reference period 1961–1990: February 1972 February 1961–1990: period reference 50 50 precipitation conditions of the reference series 19 series reference is the of conditions March precipitation percent); (10 higher markedly is November between Koblenz and Köln (Cologne). Elsewhere the p the Elsewhere (Cologne). Köln and Koblenz between preserved preserved if considered over longer periods (e.g. 1 November merely between 29 and 107 mm. 107 and 29 between merely November ber, with a second maximum in February. For instanc bring a rather balanced precipitation regime to Nor to regime precipitation balanced rather a bring } from those of the 100-year period 1900–1999. period 100-year the of those from with least deviations. However, in the period 1900– period the in However, deviations. least with widest the with month the remains October smoothed. northern foreland of the Harz Mountains, the middle the Mountains, Harz the of foreland northern years, one observes an increase from the eastern pa southwe again Germany,drop to central towards west coefficie the variability In half-years, the summer Ha the of north and Main, River the of basin middle t in exist Maxima percent. 22 around uniform tively Bran in and Lusatia in only occur Minima different: somewhat higher than those of summer half-years. Ho coefficients variability the percent, 30 to 15 With summer. in dominant particularly are whi processes generating precipitation since years, lar the minima of half-year variability coefficient o foreland Uplands, around eastern Frankfurt/Main, and in the northern the in Lusatia, in located again pi southern Alpine the in as well as Bremen, around m here finds one years, the of analysis the in Like co variability the of cells grid the half-year, mer The Maps C and D show the variability coefficients over Germany in the reference period range in Octob in range period reference the in Germany over The shown yearly course of the variability coeffici variability the of course yearly shown The the lowest scatter, followed by June. Conversely, p Conversely, June. by followed scatter, lowest the months. single the for Germany of cells grid all of year.of the course in the differences Fig distinct the Considering coefficients variability of the sin val mean the to relative variations too, Here cles. of uplift by intensified is precipitation regions, values values of the coefficient are monthly variability a a uplands, the of ridges the on Alps, German the In }}}} Variability coefficient of the hydrological half-ye he e Fränkische Alb (Franconian Alb). Towards the wester the Towards Alb). (Franconian Alb Fränkische country and the northern value the northern the and piedmont, Alpine country mm around the mean value for these periods by multi the compute to possible is it half-years, and years precipita mean the show 2.4 to 2.2 Maps the Because variability coefficients of the Maps A, C, and D. D. T and C, Maps A, the of coefficients variability values of the corrected precipitation depths (Maps (Maps depths precipitation corrected the of values of order same the in transferable also are ficients the period under consideration: The values of annua of values The consideration: under period the vari the of size regional specific the for Decisive 12 and 29 percent, of winter half-years between 15 range between 11 and 24 percent, those of summer ha When mean precipitation depths are used for water-re for used are depths precipitation mean When percent. 59 and 44 between months the of finally dependence on the issue in question and potential e potential and o question in issue the left on dependence be not must variability temporal their ning, factors, the whole span of variability coefficients variability of span whole the factors, value or even its station extremes may become relev become may extremes station its even or value periods of high pressure may be the underlying caus underlying the be may pressure high of periods precipitation extreme rare to due be also may basin ability coefficients in these regions (above 80 per 80 (above convective events alternating with regions little precipita these in coefficients ability show October and February of months the especially Baden-Wü of part southernmost the in and Forest ian called Vb weather patterns. Other rare maxima occur vari wide The areas. dry rather otherwise monthly in depths high brought which Niederlausitz, the over rainfal heavy the as such events precipitation tive and in the lee of the Palatinate Forest. The causes i regions driest the in highest the percent 58 than The temporal variations of monthly precipitation de scatter. annual the mar are values grid-cell the percent, 59 to 44 with of coefficients variability the of structure the to Fig. 3 Variability coefficient of the individual mo individual the of coefficient Variability 3 Fig. variability coefficient in percent 40 45 50 55 60 65 Jan Practical Practical Information ence period 1961–1990 period ence Feb Mar Apr air masses on the windward side of the obsta- the of side windward the on masses air ure 3 shows the mean variability coefficients variability mean the 3 ure shows s are even more pronounced than those of the gle gle months in the reference period, one finds round round 48 windswesterly Prevailing percent. ue are small. are ue efficient range between 12 and 29 percent. 29 and 12 between range efficient nt of precipitation increases from the north-increases nt of precipitation 900–1999), 900–1999), although the values are slightly 61–1990 deviate in both months distinctly months both in deviate 61–1990 May rts rts of Germany to a maximum between the of the hydrological winter half-years are half-years winter hydrological the of inima in the north of Germany, especiallyGermany, of north the in inima ch influence the distribution over the year the over distribution the influence ch recipitation depths vary strongly in Octo- in strongly vary depths recipitation In the course of the year, November has November year, the of course the In of the hydrological half-years. In the sum- ents of the months remains qualitatively remains months the of ents thwest Germany. In the hilly and upland and hilly the In Germany. thwest rz Mountains. rz edmont and in the Alps. The maxima are the maxima in The and Alps. edmont 1999, the mean variability coefficient of coefficient variability mean the 1999, parts of Baden-Württemberg. In particu- nd throughout Northwest Germany, theGermany, Northwest throughout nd e, e, the depthsmonthly areal precipitation he High Rhine region, in the upper and upper the in region, Rhine High he f the Harz Mountains, in the Hessian the in Mountains, Harz the f wever, their distribution pattern is much stwards to the Alps. In the winter half- winter the In the to Alps. stwards scatter from year to year, to one year the from June scatter denburg and along the Middle Rhine Middle the along and denburg reach of the River Neckar, and the and Neckar, River the of reach Jun ercentage standard deviation is rela- is deviation standard ercentage er between 14 and 127 mm, but in but mm, 127 and 14 between er similar with 5 percent. Therefore, percent. 5 with similar month ars AugJul ability coefficients is coefficients ability tion during persistent the years. However, years. the Sep are summer convec- nths in the refer- the in nths and 30 percent, and absolute scatter in scatter absolute n eastern Germany eastern n he variability coef- variability he 2.5 and 2.6). and 2.5 magnitude to the to magnitude pths are with more around the mean the around ations in the Odra the in ations events during so- during events kedly higher than higher kedly nvironmental risk nvironmental s decrease again. decrease s ut of account. In account. of ut l in August 1978 August in l ant. plication with the e. red red in the Bavar- lf-years lf-years between cent), extreme cent), very high vari- high very Oct l distributions l tion depths of depths tion n parts of the of parts n rttemberg. As rttemberg. sources plan- sources precipitation Nov Dec