<?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" specific-use="SMUR" dtd-version="3.0" xml:lang="en">
<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-2026-2063</article-id>
<title-group>
<article-title>Impact of High-Volume GNSS Radio Occultation Data on the Navy&apos;s Global Numerical Weather Prediction</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Christophersen</surname>
<given-names>Hui W.</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>Ruston</surname>
<given-names>Benjamin</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Tyndall</surname>
<given-names>Dan</given-names>
<ext-link>https://orcid.org/0000-0002-1424-7149</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Naval Research Laboratory Marine Meteorology Division, Monterey, CA, USA</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Joint Center for Satellite Data Assimilation (JCSDA) at the University Corporation Atmospheric Research (UCAR), Boulder, CO, USA</addr-line>
</aff>
<pub-date pub-type="epub">
<day>22</day>
<month>04</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>17</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Hui W. Christophersen et al.</copyright-statement>
<copyright-year>2026</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/2026/egusphere-2026-2063/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2063/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2063/egusphere-2026-2063.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2063/egusphere-2026-2063.pdf</self-uri>
<abstract>
<p>This study assesses the impact of assimilating high-volume Radio Occultation (RO) data from the RO modeling experiment (ROMEX) on the Navy&apos;s global operational Naval Global Environment Model (NAVGEM). A series of observation system experiments were conducted, including a control run, a standard assimilation of all ROMEX data, and two sensitivity tests: one with an empirical bias correction and another with a modified refractivity coefficient. Results indicate that while the standard assimilation of ROMEX data improved free-tropospheric moisture forecasts, it amplified existing model biases in temperature and geopotential height, leading to forecast degradation. In contrast, both sensitivity experiments led to substantial improvements in forecast skill. The empirical bias correction method proved most effective, yielding consistent forecast improvements across temperature, moisture, and geopotential height. A Forecast Sensitivity to Observation Impact (FSOI) analysis confirmed the positive contribution of all ROMEX missions, with Spire missions providing the largest total impact and COSMIC-2 showing the highest per-observation effectiveness. The findings underscore that an adjustment to the current treatment of the observation was critical to fully realize the benefits of the large volume of RO observations. While the empirical bias correction delivers the greatest forecast improvements, it may obscure and reinforce persistent model biases. The refractivity coefficient adjustment offers an alternative that preserves the unbiased nature of RO observations.</p>
</abstract>
<counts><page-count count="17"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>Office of Naval Research</funding-source>
<award-id>N0001423WX00473, N0001424WX00933, N0001425GI02277</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
<body/>
<back>
</back>
</article>