Frei, Christoph

Isotta, Francesco A.

Schwanbeck, Jan

English

Bern Open Repository and Information System (BORIS)

Explanatorytext©HydrologicalAtlasofSwitzerland,Bern2018–1B: Water in the atmosphere 1/2Mean Precipitation 1981–2010AbstractThe maps depicting the mean monthly, seasonal, and annual precipitation for the standard normal period1981–2010 are based on grid data set Rnorm of MeteoSwiss. For catchments with an area of 20 km2 orlarger, area mean values can be displayed and downloaded from the maps.Authors: Christoph Frei1, Francesco A. Isotta1, Jan Schwanbeck21Federal Office of Meteorology and Climatology MeteoSwiss, Operation Center 1, CH-8058 Zurich-Flughafen2Hydrological Atlas of Switzerland, Hallerstrasse 12, CH-3012 Bern1 IntroductionPrecipitation data provide an important quantitativebasis for answering questions regarding water man-agement and hydrology, agriculture and ecology, inenergy and civil engineering, and many more. Themaps presented here depict mean precipitation of thenorm period 1981–2010 for a calendar year, the twelvecalendar months, and the four seasons composed ofthree months each.The normal period 1981–2010 was introduced in 2013by the Federal Office of Meteorology and Climato-logy MeteoSwiss. In so doing, MeteoSwiss followedthe 2011 recommendation of the World Meteorolo-gical Organization (WMO) to introduce a new 30-yearnormal period every ten years, in addition to the non-overlapping WMO standard reference periods 1901–1930, 1931–1960, 1961–1990, and so on [1]. TheHydrological Atlas depicts the mean precipitation ofthe last completed normal period, as these data arerelevant to addressing current questions.2 Data and methodsThe maps of mean annual and monthly precipitationare based on the data sets RnormY [2] and RnormM[3]. RnormY and RnormM are spatial analyses of pre-cipitation normals, derived from measurements at 418stations for the normal period 1981–2010 [1]. The griddata sets cover the territory of Switzerland and providea detailed picture of the spatial distribution of precip-itation, with a resolution of 1.6 km x 2.3 km. However,the effective spatial resolution of interpolated data setsalways depends on the density of the measurementnetwork and the distribution of underlying measure-ment stations. In the Rnorm data sets, neighbouringmeasurement stations display a typical separation of10–20 km.The following steps were required to create the griddata sets:1. The annual and monthly station values for theyears 1981–2010 were summarised as meanvalues for the 30-year normal period.2. The relative anomalies from (1) were calculatedin relation to the climatological mean values forthe period 1971–1990.3. For spatial interpolation of measurement-site an-omalies, a modified version of the SYMAP al-gorithm [4], [5] was applied.4. The anomaly fields from step (3) were multipliedby the corresponding climatological precipitationanalyses of the period 1971–1990 [6], [7], [8].Systematic measurement errors and interpolation er-rors can impact the accuracy of spatially interpolateddata sets. Accordingly, the accuracy of RnormM andRnormY depend, on the one hand, on the quality ofthe underlying measurement values, and, on the other,on the ability of the interpolation scheme to reproduceprecipitation at unmeasured locations.Systematic errors occur when wind, evaporation andwetting cause measurement instruments to miss someof the precipitation water. According to [9], the bias inSwitzerland ranges from approximately 4% at low alti-tudes in summer to more than 40% at altitudes above1500 m a.s.l. in winter. In general, the measurementvalues underestimate the actual precipitation amounts.Interpolation errors affect the grid cells between meas-urement sites. Interpolation errors can be calculatedby means of leave-one-out cross-validation. This ana-lysis yielded a relative standard error of about ± 20 %for grid point estimates in the Jura and the CentralLowlands, and ± 25–30% in the Alps and the southernside of the Alps. Seasonal variation of error is low.Particularly large relative interpolation errors occur indry calendar months, in inner Alpine valleys (e.g. Val-ais) and at high elevations. As the number of grid cellsused for spatial-mean calculation increases, the ex-pected rate of interpolation error decreases (see also[10]).In the Hydrological Atlas, grid values from RnormYand RnormM for catchments 20 km2 or larger are spa-tially aggregated and indicated as an area mean. Forcatchments composed of more than 5% foreign ter-ritory, no area mean is calculated because RnormYand RnormM data are only provided for areas withinSwitzerland.3 ResultsIn the normal period 1981–2010, an average of1397 mm of precipitation fell over Switzerland per year.High precipitation levels can be observed at the elev-ations of the alpine foothills, along the Bernese Alps,www.hydrologicalatlas.chsource: https://doi.org/10.7892/boris.141634 | downloaded: 3.6.20202/2 – B: Water in the atmospherethe Gotthard Massif, in the Ticino Alps, and in thewestern part of the Swiss Jura. Peak values are es-timated for the southern flank of the Jungfrau Massif.But as a result of the small number and poor repres-entativity of stations in this region, these estimatesare very uncertain. By contrast, exceptionally lowprecipitation levels occur in the inner Alpine valleys,namely the Valais Rhône Valley, the Matter Valley, andin Engadin. In the Central Lowlands, mean annualprecipitation ranges between 900 and 1300 mm/y. Fig-ure 1 shows the average monthly precipitation levelsacross Switzerland. The largest monthly sums oc-cur in the months of May to August. Between 140mm/month and 144 mm/m of precipitation fall in thesemonths. The least precipitation occurs in Februaryat 82 mm/month. The monthly precipitation amountsincrease by 58 mm between February and May, anddecrease from 144 mm/m to 82 mm/month betweenAugust and February.J F M A M J J A S O N D04080120P [mm]Figure 1. Mean monthly precipitation (P) in thestandard normal period 1981–2010: area means forSwitzerlandThe spatial distribution of precipitation in individualmonths is generally similar to that of the year. Thelargest precipitation amounts occur along the moun-tain ridges of the Jura, in the alpine foothills, and in theBernese Alps. The driest regions also consistently re-main along the floor of the Rhône Valley between Mar-tigny and Brig, in the valleys to the south, as well as inEngadin along the River Inn. In Ticino, it is much drierin December, January, February, and March than in theother months. In April, the precipitation amounts in Ti-cino increase, remaining at roughly the same level untilNovember with a peak in October. North of the Alps,the season begins with larger precipitation amounts inMay and lasts until August.References[1] Begert, M., Frei, C. and Abbt, M. (2013).Einführung der Normperiode 1981-2010.Fachbericht MeteoSchweiz 245. 50 pp.[2] MeteoSwiss, ed. (2014a). Norm valuesRnormY8110 v1.0: Annual precipitation totals(30-year average). URL: http : / / www .meteoswiss.admin.ch/home/climate/past / climate - normals / norm - value -charts.html#precip.[3] MeteoSwiss, ed. (2014b). Norm valuesRnormM8110 v1.0: Monthly precipita-tion totals (30-year average). URL: http :/ / www . meteoswiss . admin . ch / home /climate/past/climate-normals/norm-value-charts.html#precip.[4] Shepard, D. S. (1984). Computer Mapping: TheSYMAP Interpolation Algorithm. In: Spatial Stat-istics and Models. Theory and Decision Library.Springer, Dordrecht, pp. 133–145. ISBN: 978-94-017-3048-8. DOI: 10.1007/978-94-017-3048-8_7. URL: https://link.springer.com/chapter/10.1007/978- 94- 017-3048-8_7 (visited on 22/01/2018).[5] Frei, C. and Schär, C. (1998). A precipitationclimatology of the Alps from high-resolutionrain-gauge observations. In: InternationalJournal of Climatology 18.8, pp. 873–900. ISSN:1097-0088. DOI: 10 . 1002 / (SICI ) 1097 -0088(19980630 ) 18 : 8<873 :: AID -JOC255 > 3 . 0 . CO ; 2 - 9. URL: http ://onlinelibrary.wiley.com/doi/10.1002/(SICI)1097- 0088(19980630)18:8%3C873::AID- JOC255%3E3.0.CO;2-9/abstract (visited on 22/01/2018).[6] Schwarb, M. (2000). The Alpine PrecipitationClimate. Evaluation of a high-resolution analysisscheme using comprehensive rain-gauge data.Dissertation 13911. Zürich: ETHZ.[7] Schwarb, M., Daly, C., Frei, C. and Schär, C.(2001a). Mittlere jährliche Niederschlagshöhenim europäischen Alpenraum 1971-1990. In: Hy-drologischer Atlas der Schweiz. Vol. 1. 2 vols.Tafel 2.6. Bern. URL: http://www.hydrologischeratlas.ch/de/produkte/druckausgabe/niederschlag/tafel-2-6.[8] Schwarb, M., Daly, C., Frei, C. and Schär, C.(2001b). Mittlere saisonale Niederschlagshöhenim europäischen Alpenraum 1971-1990. In: Hy-drologischer Atlas der Schweiz. Vol. 1. 2 vols.Tafel 2.7. Bern. URL: http://www.hydrologischeratlas.ch/de/produkte/druckausgabe/niederschlag/tafel-2-6.[9] Sevruk, B. (1985). Systematischer Niedersch-lagsmessfehler in der Schweiz. Beiträge zurGeologie der Schweiz – Hydrologie 31. Bern.[10] Frei, C., Germann, U., Fukutome, S. and Lini-ger, M. (2008). Möglichkeiten und Grenzen derNiederschlagsanalysen zum Hochwasser 2005.In: Ereignisanalyse Hochwasser 2005 Teil 2:Analyse von Prozesse, Massnahmen und Ge-fahrengrundlagen, pp. 15–32.

Mean Precipitation – Interactive map B01, Hydrological Atlas of Switzerland

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Mean Precipitation – Interactive map B01, Hydrological Atlas of Switzerland

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