<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="3.0" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">ADGEO</journal-id>
<journal-title-group>
<journal-title>Advances in Geosciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ADGEO</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Adv. Geosci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1680-7359</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/adgeo-10-139-2007</article-id>
<title-group>
<article-title>On evaluation of ensemble precipitation forecasts with observation-based ensembles</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ahrens</surname>
<given-names>B.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jaun</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Institute for Atmosphere and Environment, University of Frankfurt, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland</addr-line>
</aff>
<pub-date pub-type="epub">
<day>26</day>
<month>04</month>
<year>2007</year>
</pub-date>
<volume>10</volume>
<fpage>139</fpage>
<lpage>144</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2007 B. Ahrens</copyright-statement>
<copyright-year>2007</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Generic License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by-nc-sa/2.5/">https://creativecommons.org/licenses/by-nc-sa/2.5/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://adgeo.copernicus.org/articles/10/139/2007/adgeo-10-139-2007.html">This article is available from https://adgeo.copernicus.org/articles/10/139/2007/adgeo-10-139-2007.html</self-uri>
<self-uri xlink:href="https://adgeo.copernicus.org/articles/10/139/2007/adgeo-10-139-2007.pdf">The full text article is available as a PDF file from https://adgeo.copernicus.org/articles/10/139/2007/adgeo-10-139-2007.pdf</self-uri>
<abstract>
<p>Spatial interpolation of precipitation data is uncertain. How important is
this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation
forecasts? These questions are discussed by experimental evaluation of the
COSMO consortium&apos;s limited-area ensemble prediction system COSMO-LEPS. The
applied performance measure is the often used Brier skill score (BSS).
The observational references in the evaluation are (a)
analyzed rain gauge data by ordinary Kriging and (b) ensembles of interpolated
rain gauge data by stochastic simulation. This permits the consideration of
either a deterministic reference (the event is observed or not with 100%
certainty) or a probabilistic reference that makes allowance for uncertainties
in spatial averaging. The evaluation experiments show that the
evaluation uncertainties are substantial even for the large area
(41 300 km&lt;sup&gt;2&lt;/sup&gt;) of
Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day
precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.</p>
</abstract>
<counts><page-count count="6"/></counts>
</article-meta>
</front>
<body/>
<back>
<ref-list>
<title>References</title>
<ref id="ref1">
<label>1</label><mixed-citation publication-type="other" xlink:type="simple"> Ahrens, B.: Evaluation of precipitation forecasting with the limited area model ALADIN in an Alpine watershed, Meteorol. Z., 12, 245&amp;ndash;255, 2003. </mixed-citation>
</ref>
<ref id="ref2">
<label>2</label><mixed-citation publication-type="other" xlink:type="simple"> Ahrens, B. and Beck, A.: On upscaling of rain&amp;ndash;gauge data for evaluating numerical weather forecasts, Meteorol. Atmos. Phys., in print, 2007. </mixed-citation>
</ref>
<ref id="ref3">
<label>3</label><mixed-citation publication-type="other" xlink:type="simple"> Atkinson, P. and Lloyd, C.: Mapping precipitation in Switzerland with ordinary and indicator Kriging, J. Geographic Information and Dec. Analysis, 2, 65&amp;ndash;76, 1998. </mixed-citation>
</ref>
<ref id="ref4">
<label>4</label><mixed-citation publication-type="other" xlink:type="simple"> Beck, A. and Ahrens, B.: Multiresolution evaluation of precipitation forecasts over the European Alps, Meteorol. Z., 13, 55&amp;ndash;62, 2004. </mixed-citation>
</ref>
<ref id="ref5">
<label>5</label><mixed-citation publication-type="other" xlink:type="simple"> Chilès, J.-P.: Geostatistics: modeling spatial uncertainty, John Wiley &amp; Sons, New York, 1999. </mixed-citation>
</ref>
<ref id="ref6">
<label>6</label><mixed-citation publication-type="other" xlink:type="simple"> Creutin, J. and Obled, C.: Objective analyses and mapping techniques for rainfall fields: an objective comparison, Water Resour. Res., 18, 413&amp;ndash;431, 1982. </mixed-citation>
</ref>
<ref id="ref7">
<label>7</label><mixed-citation publication-type="other" xlink:type="simple"> Ehrendorfer, M.: Predicting the uncertainty of numerical weather forecasts: a review, Meteorol. Z., 6, 147&amp;ndash;183, 1997. </mixed-citation>
</ref>
<ref id="ref8">
<label>8</label><mixed-citation publication-type="other" xlink:type="simple"> Grasso, L D.: The differentiation between grid spacing and resolution and their application to numerical modeling, Bull. Amer. Meteorol. Soc., 81, 579&amp;ndash;580, 2000. </mixed-citation>
</ref>
<ref id="ref9">
<label>9</label><mixed-citation publication-type="other" xlink:type="simple"> Johnson, M.: Multivariate Statistical Simulation, Wiley, New York, 1987. </mixed-citation>
</ref>
<ref id="ref10">
<label>10</label><mixed-citation publication-type="other" xlink:type="simple"> Journel, A.: Geostatistics for conditional simulation of ore bodies, Econom. Geol., 69, 673&amp;ndash;687, 1974. </mixed-citation>
</ref>
<ref id="ref11">
<label>11</label><mixed-citation publication-type="other" xlink:type="simple"> Marsigli, C., Boccanera, F., Montani, A., and Paccagnella, T.: The COSMO-LEPS mesoscale ensemble system: validation of the methodology and verification, Nonlin. Processes Geophys., 12, 527&amp;ndash;536, 2005. </mixed-citation>
</ref>
<ref id="ref12">
<label>12</label><mixed-citation publication-type="other" xlink:type="simple"> Molteni, F., Buizza, R., Marsigli, C., Montani, A., Nerozzi, F., and Paccagnella, T.: A strategy for high-resolution ensemble prediction. I: Definition of representative members and global-model experiments, Quart. J. Roy. Meteorol. Soc., 127, 2069&amp;ndash;2094, 2001. </mixed-citation>
</ref>
<ref id="ref13">
<label>13</label><mixed-citation publication-type="other" xlink:type="simple"> Montani, A., Capaldo, M., Cesari, D., Marsigli, C., Modigliani, U., Nerozzi, F., Paccagnella, T., Patruno, P., and Tibaldi, S.: Operational limited-area ensemble forecasts based on the Lokal Modell, ECMWF Newsletter, 98, 2&amp;ndash;7, 2003. </mixed-citation>
</ref>
<ref id="ref14">
<label>14</label><mixed-citation publication-type="other" xlink:type="simple"> Müller, W., Appenzeller, C., Doblas-Reyes, F., and Liniger, M.: A debiased ranked probability skill score to evaluate probabilistic ensemble forecasts with small ensemble sizes, J. Climate, 18, 1513&amp;ndash;1523, 2005. </mixed-citation>
</ref>
<ref id="ref15">
<label>15</label><mixed-citation publication-type="other" xlink:type="simple"> Palmer, T N.: Predicting uncertainty forecasts of weather and climate, Rep. Prog. Phys., 63, 71&amp;ndash;116, 2000. </mixed-citation>
</ref>
<ref id="ref16">
<label>16</label><mixed-citation publication-type="other" xlink:type="simple"> Pebesma, E.: Multivariable geostatistics in S: the gstat package, Comp. &amp; Geosci., 30, 683&amp;ndash;691, 2004. </mixed-citation>
</ref>
<ref id="ref17">
<label>17</label><mixed-citation publication-type="other" xlink:type="simple"> Stanski, H., Wilson, L., and Burrows, W.: Survey of common verification methods in meteorology, Tech. Rep. WMO/TD No 358, WMO World Weather Watch, 1989. </mixed-citation>
</ref>
<ref id="ref18">
<label>18</label><mixed-citation publication-type="other" xlink:type="simple"> Weigel, A., Liniger, M., and Appenzeller, C.: The discrete Brier and ranked probability skill scores, Mon. Wea. Rev., 135, 118&amp;ndash;124, 2007. </mixed-citation>
</ref>
<ref id="ref19">
<label>19</label><mixed-citation publication-type="other" xlink:type="simple"> Wilks, D S.: Statistical Methods in the Atmospheric Sciences, Academic Press, San Diego, 2006. </mixed-citation>
</ref>
<ref id="ref20">
<label>20</label><mixed-citation publication-type="other" xlink:type="simple"> Zhu, Y., Toth, Z., Wobus, R., Richardson, D., and Mylne, K.: The economic value of ensemble&amp;ndash;based weather forecasts, Bull. Amer. Meteorol. Soc., 83, 73&amp;ndash;83, 2002. </mixed-citation>
</ref>
</ref-list>
</back>
</article>