Software Open Access

Monthly Means of Instantaneous Diagnostics for Key Atmospheric Processes (MIND the KAP)

Madlen Kimmritz; Clemens Spensberger

DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="" xmlns="" xsi:schemaLocation="">
  <identifier identifierType="DOI">10.5281/zenodo.4607854</identifier>
      <creatorName>Madlen Kimmritz</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-6536-0221</nameIdentifier>
      <affiliation>Nansen Environmental Research Center and Bjerknes Centre for Climate Research</affiliation>
      <creatorName>Clemens Spensberger</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-9649-6957</nameIdentifier>
      <affiliation>Geophysical Institute and Bjerknes Centre for Climate Research, University of Bergen</affiliation>
    <title>Monthly Means of Instantaneous Diagnostics for Key Atmospheric Processes (MIND the KAP)</title>
    <date dateType="Issued">2021-03-16</date>
  <resourceType resourceTypeGeneral="Software"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4607853</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;Meteorologists typically characterise weather in terms of features, like cyclones or blocking high pressure systems. The instantaneous distribution of these features provides a very condensed summary of the atmospheric state. Consequently, monthly distributions of these features detected in the instantaneous fields retain much more relevant information about weather events than monthly averages of conventional meteorological variables, such as sea- level pressure. Weather events have been shown to provide a conceptual link between short- lived weather events and climate variability over longer time scales. This software project implements an optional automatic post-processing step the authors implemented for simulations based on the Norwegian Earth System Model (NorESM) and on the Norwegian Climate Prediction Model (NorCPM) to calculate monthly weather feature distributions.&lt;/p&gt;

&lt;p&gt;Documentation for the MIND the KAP project is available as Technical Report 401 of the Nansen Environmental and Remote Sensing Center, doi: &lt;a href=""&gt;10.13140/RG.2.2.13048.60167/3&lt;/a&gt;.&lt;/p&gt;

&lt;p&gt;MIND the KAP is based on &lt;a href=""&gt;dynlib&lt;/a&gt;, which contains the weather feature detection algorithms used here.&lt;/p&gt;</description>
    <description descriptionType="Other">The development was supported through internal funding from the Bjerknes Centre for Climate Research (FTI2019 - MIND the KAP).</description>
All versions This version
Views 5555
Downloads 1818
Data volume 114.9 MB114.9 MB
Unique views 4848
Unique downloads 88


Cite as