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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></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/egusphere-2024-1183</article-id>
<title-group>
<article-title>Assessing the Hydrological Impact Sensitivity to Climate Model Weighting Strategies</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rahimpour Asenjan</surname>
<given-names>Mehrad</given-names>
<ext-link>https://orcid.org/0000-0001-5031-8496</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Brissette</surname>
<given-names>Francois</given-names>
<ext-link>https://orcid.org/0000-0002-9754-3014</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Arsenault</surname>
<given-names>Richard</given-names>
<ext-link>https://orcid.org/0000-0003-2834-2750</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Martel</surname>
<given-names>Jean-Luc</given-names>
<ext-link>https://orcid.org/0000-0001-7142-6875</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Hydrology, Climate, and Climate Change Laboratory (HC³), École de technologie supérieure, Université du Québec, 1100 Notre-Dame Street West, Montreal, Quebec, H3C 1K3, Canada</addr-line>
</aff>
<funding-group>
<award-group id="gs1">
<funding-source>Natural Sciences and Engineering Research Council of Canada</funding-source>
<award-id>RGPIN-2020-07242</award-id>
</award-group>
</funding-group>
<pub-date pub-type="epub">
<day>05</day>
<month>06</month>
<year>2024</year>
</pub-date>
<volume>2024</volume>
<fpage>1</fpage>
<lpage>52</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2024 Mehrad Rahimpour Asenjan et al.</copyright-statement>
<copyright-year>2024</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1183/">This article is available from https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1183/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1183/egusphere-2024-1183.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1183/egusphere-2024-1183.pdf</self-uri>
<abstract>
<p>&lt;span&gt;Climate change impact studies rely on ensembles of General Circulation Model (GCM) simulations. Combining ensemble members is challenging due to uncertainties in how well each model performs. The concept of model democracy where equal weight is given to each model, is common but criticized for ignoring regional variations and dependencies between models. Various weighting schemes address these concerns, but their effectiveness in impact studies, which integrate GCM outputs with separate impact models, remains unclear. &lt;/span&gt;&lt;/p&gt;
&lt;p&gt;&lt;span&gt;This study evaluated the impact of six weighting strategies on future streamflow projections using a pseudo-reality approach, where each GCM is treated as &amp;ldquo;the true&amp;rdquo; climate. The analysis involved an ensemble of 22 CMIP6 climate simulations and used a hydrological model across 3,107 North American catchments. Since climate model outputs often undergo bias correction before being used in hydrological models, this study implemented two approaches: one with bias correction applied to precipitation and temperature inputs, and one without. Weighting schemes were evaluated based on biases relative to the pseudo-reality GCM for annual mean temperature, precipitation and streamflow.&lt;/span&gt;&lt;/p&gt;
&lt;p&gt;&lt;span&gt;Results show that unequal weighting schemes produce significantly better precipitation and temperature projections than equal weighting. For streamflow projections, unequal weighting offered minor improvement only when bias correction was not applied. However, with bias correction, both equal and unequal weighting delivered similar results. While bias correction has limitations, it remains essential for realistic streamflow projections in impact studies. A pragmatic strategy may be to combine model democracy with selective model exclusion based on robust performance metrics.&lt;/span&gt;&lt;/p&gt;
&lt;p&gt;&lt;span&gt;This study provides insights on how weighting affects hydrological assessments. It emphasizes the need for careful approaches and further research to manage uncertainties in climate change impact studies. These findings will help improve the accuracy of climate projections and improve the reliability of hydrological impact assessments in a changing climate.&lt;/span&gt;</p>
</abstract>
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