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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">ACP</journal-id>
<journal-title-group>
<journal-title>Atmospheric Chemistry and Physics</journal-title>
<abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1680-7324</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/acp-17-12121-2017</article-id><title-group><article-title>Oscillations in atmospheric water above Switzerland</article-title>
      </title-group><?xmltex \runningtitle{Oscillation in atmospheric water}?><?xmltex \runningauthor{K. Hocke et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff2">
          <name><surname>Hocke</surname><given-names>Klemens</given-names></name>
          <email>klemens.hocke@iap.unibe.ch</email>
        <ext-link>https://orcid.org/0000-0003-2178-9920</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Navas-Guzmán</surname><given-names>Francisco</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-0905-4385</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Moreira</surname><given-names>Lorena</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4791-8500</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Bernet</surname><given-names>Leonie</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-0771-3025</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Mätzler</surname><given-names>Christian</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Institute of Applied Physics, University of Bern, Bern, Switzerland</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Klemens Hocke (klemens.hocke@iap.unibe.ch)</corresp></author-notes><pub-date><day>12</day><month>October</month><year>2017</year></pub-date>
      
      <volume>17</volume>
      <issue>19</issue>
      <fpage>12121</fpage><lpage>12131</lpage>
      <history>
        <date date-type="received"><day>22</day><month>March</month><year>2017</year></date>
           <date date-type="rev-request"><day>17</day><month>May</month><year>2017</year></date>
           <date date-type="rev-recd"><day>13</day><month>July</month><year>2017</year></date>
           <date date-type="accepted"><day>13</day><month>September</month><year>2017</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri>
<self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>


      <abstract>
    <p>Cloud fraction (CF), integrated liquid water (ILW) and integrated water vapour (IWV) were continuously
measured from 2004 to 2016  by the TROpospheric WAter RAdiometer (TROWARA) in Bern, Switzerland. There are
indications for interannual variations of CF and ILW.
A spectral analysis shows that IWV is dominated by an annual oscillation, leading to  an IWV
maximum of 24 kg m<inline-formula><mml:math id="M1" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  in July to August and a minimum of 8 kg m<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  in  February.
The seasonal behaviour of CF and ILW is composed by both the annual and the semiannual oscillation.
However, the annual oscillation of CF has a maximum in December while the annual oscillation of ILW has a
maximum in July.  The semiannual oscillations of  CF and ILW are strong from 2010 to 2014.
The normalized power spectra of ILW and CF  show statistically significant spectral components with periods of  76, 85, 97 and 150 days.
We find a similarity between the power spectra of ILW and CF with those of zonal wind at 830 hPa (1.5 km)
above Bern.  Particularly, the occurrence of higher harmonics in the CF and ILW spectra is possibly forced by the behaviour of the lower-tropospheric wind.
The mean amplitude spectra of CF, ILW and IWV show increased short-term variability on timescales less than 40 days from spring to fall.
We find a weekly cycle of CF and ILW  from June to September with increased values on Saturday, Sunday and Monday.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Time series of  CF, ILW and IWV at Bern. The monthly means are given by the green lines
while the red lines denote the annual means (12-month sliding average with a step of 1 month). The blue lines
shows the standard deviations of the annual means.</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f01.jpg"/>

      </fig>

      <p>Observation and characterization of the oscillations of
atmospheric water lead to a better understanding of the cloud processes, the
cloud-induced changes in the Earth radiative fluxes and the water cycle. In
this study, we investigate the oscillations in 12-year time series of
cloud fraction (CF), integrated liquid water (ILW) and integrated water
vapour (IWV) above Bern, Switzerland. The combined spectral analysis of
atmospheric water parameters can give hints about cloud formation and
transport processes.
The  seasonal cycle of the atmospheric water parameter CF   at  midlatitudes  has  only been described in a
few articles,  while the seasonal cycle in ILW remains undescribed as of now.  The climatology of IWV at
Bern was presented by <xref ref-type="bibr" rid="bib1.bibx16" id="normal.1"/>, showing an annual oscillation (AO) with a summer maximum of about  22 kg m<inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and
a winter minimum of about 8 kg m<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. This simple seasonal cycle in IWV   is a consequence of  the Clausius–Clapeyron
equation and the seasonal cycle of air temperature at midlatitudes.</p>
      <p><xref ref-type="bibr" rid="bib1.bibx6" id="normal.2"/> presented a 10-year cloud fraction climatology of liquid water clouds over Bern observed by the
TROpospheric WAter RAdiometer (TROWARA).
CF had  a maximum of 60.9 % in winter and a minimum of 42.0 % in summer.  They did not discuss the indication of a
semiannual oscillation (SAO) in the seasonal cycle of CF.
<xref ref-type="bibr" rid="bib1.bibx10" id="normal.3"/>  divided the liquid water clouds into three classes, thin clouds, supercooled thick clouds and warm
thick clouds, using the TROWARA data set at Bern.  The warm thick clouds showed a CF maximum of 30 % in the summer months
and a minimum of 6 % in winter. The CF of  supercooled thick clouds was maximal in winter (29 %)  and
minimal in summer (2 %).  Thin clouds had a fairly constant CF ranging from  30 % in winter to 24 % in summer.
<xref ref-type="bibr" rid="bib1.bibx12" id="normal.4"/>  derived the seasonal cycle of cloud fraction using Meteosat images.  CF  was about 50 % over
the Iberian peninsula during winter and about 30 % in summer</p>
      <p>Compared to these few articles about the seasonal cycle of CF at
midlatitudes, there are more articles about the seasonal change of CF over
Antarctica, Arctic and the tropics. <xref ref-type="bibr" rid="bib1.bibx14" id="normal.5"/> described the mechanism
of a SAO in sea level pressure in the Southern
Hemisphere which arises from different responses to the surface heat budget
over the polar continent and the midlatitude ocean.
Van den Broeke (2000)
investigated a possible relation between the SAO, the near-surface wind and
cloudiness. He found only at the Antarctic stations Halley and Faraday a
firmly established half-yearly wave in the mean annual cycles of wind speed
and cloudiness. <xref ref-type="bibr" rid="bib1.bibx4" id="normal.6"/> gave a review about tropospheric clouds
in Antarctica. One focus was on the seasonal and interannual variability of
cloud amounts. Over the Southern Ocean equatorward of 60<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, only
CloudSat and CALIPSO showed a minimum in cloudiness occurring in summer (5 %
lower than in winter). <xref ref-type="bibr" rid="bib1.bibx25" id="normal.7"/> suggested that this summertime
minimum is consistent with the seasonality of the extratropical cyclone
activity.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p>Normalized power spectra of CF, ILW and IWV at Bern for the time interval from January
2004 to November 2016. In addition we show the normalized power of the zonal wind <inline-formula><mml:math id="M6" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> from ECMWF operational
reanalysis at  830 hPa (1.5 km altitude) above Bern and for the same time interval.
The red line is the <inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula> level (95 % confidence).</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f02.jpg"/>

      </fig>

      <p>Over the Arctic ocean, <xref ref-type="bibr" rid="bib1.bibx3" id="normal.8"/> compared observations and
simulations of the seasonal cycle of the total cloud amount. The observed
seasonal cycle of CF is from 60 % in winter to 85 % in summer while the
simulated seasonal cycle goes from 65 % in winter to 75 % in summer (if the
simulation includes ice microphysics). The results of <xref ref-type="bibr" rid="bib1.bibx3" id="normal.9"/>
suggest that the duration of the summertime cloudy season over the Arctic
Ocean would be longer in a warmer climate and shorter in a cooler climate.
The influence of wind speed on shallow marine cumulus convection was
investigated by <xref ref-type="bibr" rid="bib1.bibx17" id="normal.10"/>. Their model simulations showed that an
increase in the trade winds leads to a deepening of the cloud layer.</p>
      <p>For health and environmental reasons, the weekly cycle of aerosol
concentration and precipitation is of high interest. <xref ref-type="bibr" rid="bib1.bibx22" id="normal.11"/>
detected weekly cycles in the SO<inline-formula><mml:math id="M8" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and NO<inline-formula><mml:math id="M9" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentrations in the
polluted region of the black triangle of Czech Republic, Germany and Poland.
The weekly cycles of the SO<inline-formula><mml:math id="M10" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and NO<inline-formula><mml:math id="M11" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentrations have decreased
values at the weekend and increased values in the midweek. The microphysical
effect of the aerosol concentration on the formation and the size of cloud
droplets may induce weekly cycles in cloud parameters and precipitation.
Another cause could be that the amount of aerosol concentration triggers
surface diabatic heating and convective motions <xref ref-type="bibr" rid="bib1.bibx7" id="paren.12"/>.
<xref ref-type="bibr" rid="bib1.bibx22" id="normal.13"/> found that weekly cycles of cloud amount and the frequency
of light precipitation events above the Czech Republic are dominated by
midweek decreases and weekend maxima.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Annual oscillation <bold>(a)</bold>, semiannual oscillation <bold>(b)</bold> and time series
of monthly means of CF (green line in panel <bold>c</bold>) derived from TROWARA measurements at Bern. The black
line is the sum of the annual oscillation, the semiannual oscillation and the total mean of CF. </p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f03.jpg"/>

      </fig>

      <p>Our study extends the research on oscillations in atmospheric water by
analysing the continuous measurements of TROWARA in Bern, Switzerland. In Sect. 2, we describe the ground-based
microwave radiometer TROWARA, its data set and the data analysis methods
which we use in this study. Section 3 presents the seasonal cycles, the power
spectra, and the bandpass-filtered annual and semiannual oscillations in CF,
ILW and IWV. Inspired by the study of <xref ref-type="bibr" rid="bib1.bibx17" id="normal.14"/>, we look at the
seasonal cycle and power spectrum of lower-tropospheric wind, which is
provided by ECMWF operational analyses at the grid point close to Bern.
Section 4 presents the climatologies of short-term variability in CF, ILW,
IWV and <inline-formula><mml:math id="M12" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> derived from daily means in the time interval from 2004 to 2016.
We find a weekly cycle for CF and ILW in spite of the relatively clean air
above Bern, Switzerland. Conclusions are given in Sect. 5.</p>
</sec>
<sec id="Ch1.S2">
  <title>Instrument, data and analysis</title>
<sec id="Ch1.S2.SS1">
  <title>The microwave radiometer TROWARA</title>
      <p>The study is  based on the measurements of TROWARA. TROWARA is a dual-channel microwave radiometer built by <xref ref-type="bibr" rid="bib1.bibx18" id="normal.15"/>.
It provides vertically integrated water vapour and vertically integrated cloud liquid water, also known as liquid
water path. TROWARA is located inside a temperature-controlled room on the roof of the EXWI building of the University of
Bern (46.95<inline-formula><mml:math id="M13" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,  7.44<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E; 575 m a.s.l.).  Since TROWARA is operated indoors, it is capable to measure IWV  even during rainy periods.</p>
      <p>The two microwave channels are at 21.4 GHz (bandwidth 100 MHz) and 31.5 GHz (bandwidth 200 MHz).  The lower frequency is more sensitive to microwaves from
water vapour,  and the higher frequency is more sensitive to microwaves from  atmospheric liquid water.</p>
      <p>The radiative transfer equation  of  a non-scattering atmosphere  is
            <disp-formula id="Ch1.E1" content-type="numbered"><mml:math id="M15" display="block"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">B</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:msub><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">τ</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">mean</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>(</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>-</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">τ</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:msup><mml:mo>)</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where <inline-formula><mml:math id="M16" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">B</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> is the observed brightness temperature of the <inline-formula><mml:math id="M17" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>th frequency channel (e.g. 21 GHz).
<inline-formula><mml:math id="M18" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">τ</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the opacity along the line of sight of the radiometer and <inline-formula><mml:math id="M19" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>  is the contribution of the cosmic microwave  background.
<inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">mean</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> is the effective mean temperature of the troposphere <xref ref-type="bibr" rid="bib1.bibx11 bib1.bibx13" id="paren.16"/>.</p>
      <p>From Eq. (<xref ref-type="disp-formula" rid="Ch1.E1"/>) we can derive the opacities
            <disp-formula id="Ch1.E2" content-type="numbered"><mml:math id="M21" display="block"><mml:mrow><mml:msub><mml:mi mathvariant="italic">τ</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>ln⁡</mml:mi><mml:mfenced close=")" open="("><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">B</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">mean</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">mean</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac></mml:mstyle></mml:mfenced><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where the radiances <inline-formula><mml:math id="M22" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mrow><mml:mi mathvariant="normal">B</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>  are measured by TROWARA.</p>
      <p>For a plane-parallel atmosphere, the opacity is closely related to IWV and ILW by a quasi-linear relationship
            <disp-formula id="Ch1.E3" content-type="numbered"><mml:math id="M23" display="block"><mml:mrow><mml:msub><mml:mi mathvariant="italic">τ</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msubsup><mml:mi>a</mml:mi><mml:mi>i</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>b</mml:mi><mml:mi>i</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msubsup><mml:mi mathvariant="normal">IWV</mml:mi><mml:mo>+</mml:mo><mml:msubsup><mml:mi>c</mml:mi><mml:mi>i</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msubsup><mml:mi mathvariant="normal">ILW</mml:mi><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where the coefficients <inline-formula><mml:math id="M24" display="inline"><mml:mrow><mml:msup><mml:mi>a</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M25" display="inline"><mml:mrow><mml:msup><mml:mi>b</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> are not really constant since they can
partly depend on air pressure. <xref ref-type="bibr" rid="bib1.bibx13" id="normal.17"/> show that these
coefficients can be statistically derived by means of nearby radiosonde
measurements and fine-tuned in periods with a clear atmosphere. The
radiosonde yields the atmospheric profile, which is used for forward modelling
of the brightness temperatures and opacities that would have been observed
by TROWARA. Further, the radiosonde provides IWV so that the equation set (Eq. <xref ref-type="disp-formula" rid="Ch1.E3"/>) can be solved for the coefficients <inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:msup><mml:mi>a</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M27" display="inline"><mml:mrow><mml:msup><mml:mi>b</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> for clear
sky <xref ref-type="bibr" rid="bib1.bibx13" id="paren.18"/>. The coefficient <inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:msup><mml:mi>c</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> is the mass absorption
coefficient of cloud water. It depends on temperature (and frequency) but
not on pressure. It is derived from the physical expression of Rayleigh
absorption by clouds <xref ref-type="bibr" rid="bib1.bibx13" id="paren.19"/>. The equation set (Eq. <xref ref-type="disp-formula" rid="Ch1.E3"/>)
permits the retrieval of IWV and ILW if the opacities are measured at 21 and
31 GHz. Thus, a dual-channel microwave radiometer can monitor IWV and ILW
with a time resolution of 6–11 s and nearly all-weather capability
during day and nighttime.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p>Annual oscillation <bold>(a)</bold>, semiannual oscillation <bold>(b)</bold> and time
series of monthly means of ILW (green line in panel <bold>c</bold>) derived from TROWARA measurements at Bern.
The black line is the sum of the annual oscillation, the semiannual oscillation and the total mean of ILW.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f04.jpg"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p>Mean seasonal behaviour  of annual oscillation (blue), semiannual oscillation
(red), monthly means (green) and the sum of AO and SAO (black) derived from TROWARA measurements of
the time interval 2004 to 2016.
The top panels <bold>(a)</bold> and <bold>(b)</bold> are for CF, the middle panels <bold>(c)</bold> and <bold>(d)</bold> are for ILW and the bottom panels
<bold>(e)</bold> and <bold>(f)</bold> are for IWV.  The standard error of the mean is given by green error bars.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f05.jpg"/>

        </fig>

      <p>An infrared radiometer channel is operated at <inline-formula><mml:math id="M29" display="inline"><mml:mrow><mml:mi mathvariant="italic">λ</mml:mi><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 9.5–11.5 <inline-formula><mml:math id="M30" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m, which measures the physical temperature at the cloud base
when the cloud is optically thick (ILW <inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">30</mml:mn></mml:mrow></mml:math></inline-formula> g m<inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>).
TROWARA's antenna coil has a full width at half power of 4<inline-formula><mml:math id="M33" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> and is pointing at the sky at an zenith angle of 50<inline-formula><mml:math id="M34" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
towards southeast. The
view direction is always constant, and the microwave and infrared channels of TROWARA observe the short-term temporal variations of the
brightness temperature in  the same volume of the atmosphere.  This contributes  to the high sensitivity of TROWARA for cloud detection.
Further details of the sensors  and retrieval technique are given in <xref ref-type="bibr" rid="bib1.bibx6" id="text.20"/> and <xref ref-type="bibr" rid="bib1.bibx13" id="text.21"/>.</p>
      <p>TROWARA has been operated since 1994, and it has delivered an almost uninterrupted time series of ILW
since 2004,  with a time resolution of 11 s until the end of 2009 and 6 s  afterwards.
The cloud detection in the line of sight of TROWARA is performed with the same  time resolution,
and the criterion is that ILW <inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">3</mml:mn><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">noise</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2.3</mml:mn></mml:mrow></mml:math></inline-formula> g m<inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. <xref ref-type="bibr" rid="bib1.bibx6" id="normal.22"/> determined the instrumental noise
<inline-formula><mml:math id="M37" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">noise</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.77</mml:mn></mml:mrow></mml:math></inline-formula> g m<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> of TROWARA  from the noise of ILW during 245 cloud-free days.
If a ILW value exceeds the  <inline-formula><mml:math id="M39" display="inline"><mml:mrow><mml:mn mathvariant="normal">3</mml:mn><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">noise</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> level, then we are 99.7 % confident that the
ILW value was generated by a cloud and not by instrumental noise.
We emphasize that this is a remarkable sensitivity for a microwave radiometer.
Contrary to the ILW series, the time series of IWV have been used since 1994 for trend analyses, as   shown by <xref ref-type="bibr" rid="bib1.bibx16" id="text.23"/> and <xref ref-type="bibr" rid="bib1.bibx9" id="text.24"/></p>
      <p>Thin liquid water clouds were  the focus of the study by <xref ref-type="bibr" rid="bib1.bibx8" id="normal.25"/>. They derived the microphysical and
optical properties of thin liquid water clouds and emphasized that
these clouds should be considered in climate studies since these clouds are frequent and they  change the radiative
forcing of the climate system. Measurements indicated that
the downwelling infrared radiance of  a thin liquid water cloud is increased by about 60<inline-formula><mml:math id="M40" display="inline"><mml:mrow><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">%</mml:mi></mml:mrow></mml:math></inline-formula> compared to clear sky.  <xref ref-type="bibr" rid="bib1.bibx8" id="normal.26"/>  reported that
thin liquid water cloud areas are often located at the edges of and in the region between clouds (<italic>twilight</italic> zone of clouds).</p>
      <p>Since TROWARA is not sensitive to ice clouds, CF of TROWARA is in general smaller  compared to synoptic observations.
<xref ref-type="bibr" rid="bib1.bibx6" id="normal.27"/> found a CF difference of about 17 % between TROWARA and synoptic observations in the same region over a period of 6 years.
In addition, some of the very thin and tenuous  clouds which are still visible by eye might be  not seen by TROWARA.
<xref ref-type="bibr" rid="bib1.bibx10" id="normal.28"/> derived  CF of  different classes of liquid water clouds using the TROWARA measurements and performed a trend analysis.
In the present study, we only consider the class of all liquid water clouds with   ILW <inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2.3</mml:mn></mml:mrow></mml:math></inline-formula> g m<inline-formula><mml:math id="M42" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Finally,  the CF, ILW and IWV measurements of TROWARA at Bern are  within the central basin of the Swiss plateau. In the following, we investigate
the monthly means of CF, ILW and IWV, which we derived from the TROWARA data.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Data analysis</title>
      <p>CF  was determined in  time domain.  CF  is the quotient of the time intervals when  ILW <inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2.3</mml:mn></mml:mrow></mml:math></inline-formula> g m<inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and the
total observation time.
The time intervals are as small as 6 s for ILW data after 2009 and 11 s for ILW data before 2009. Thus, we  set the
cloud flag with a high temporal resolution
(6 or 11 s),  which is required because of the high spatiotemporal variability of clouds floating through the fixed line of sight of TROWARA.
Monthly mean of ILW were obtained by averaging of the temporally high-resolution data. An upper threshold of 400 g m<inline-formula><mml:math id="M45" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> is used
that means in the presence of rain droplets we take the value 400 g m<inline-formula><mml:math id="M46" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> as an estimate of the ILW of the cloud droplets.
During precipitation intervals  TROWARA overestimates  ILW of the cloud droplets  because of the strong microwave emission from the
rain droplets (<inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:mi>d</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula> mm).  This is the reason why we take an upper threshold of 400 g m<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  for  vertically integrated cloud
liquid water path during rainy periods.  Monthly means of IWV are well defined because of the continuous monitoring of IWV by  TROWARA.</p>
      <p>The power spectra are obtained by folding the time series of IWV, ILW or CF with a Hamming window and by applying zero padding at
the beginning and end of the time series.
After the Fourier transformation, the power spectra  are normalized by the power of the strongest spectral component.</p>
      <p>The time series of the AO and the SAO are derived by means of bandpass filtering.
The time series
are filtered  with a digital non-recursive, finite impulse response bandpass filter performing zero-phase filtering by
processing the time series in forward and reverse directions. The number of filter coefficients corresponds to a time window
of three times the central period, and a Hamming window has been selected for the filter. Thus, the bandpass filter has a fast
response time to temporal changes in the data series. The variable choice of the filter order permits the analysis of wave trains
with a resolution that matches their scale. The bandpass cut-off frequencies are at <inline-formula><mml:math id="M49" display="inline"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>f</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>±</mml:mo><mml:mn mathvariant="normal">10</mml:mn><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">%</mml:mi><mml:msub><mml:mi>f</mml:mi><mml:mi>p</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math id="M50" display="inline"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mi>p</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the central
frequency. More details about the bandpass filtering are given by <xref ref-type="bibr" rid="bib1.bibx23" id="normal.29"/>.</p>
      <p>The mean seasonal behaviour of the time series is obtained by sorting the data for the month and taking the mean and the standard error of the mean.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><caption><p>Mean seasonal behaviour  of  zonal wind <inline-formula><mml:math id="M51" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> from ECMWF operational reanalysis at
830 hPa (1.5 km altitude) above Bern. The standard error of the mean is given by  error bars.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f06.jpg"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p>Mean amplitude spectra of CF, ILW and IWV  from TROWARA at Bern for the
time interval from January 2004 to November 2016. In addition, we show the coincident amplitude
spectrum of   zonal wind <inline-formula><mml:math id="M52" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>  from ECMWF operational reanalysis at  830 hPa (1.5 km altitude) above Bern.
The amplitude is determined by a bandpass filter with a fast response time.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f07.jpg"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <?xmltex \opttitle{Long-term oscillations in atmospheric water with periods $>$ 60 days}?><title>Long-term oscillations in atmospheric water with periods <inline-formula><mml:math id="M53" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 60 days</title>
      <p>The time series of CF, ILW and IWV are shown in Fig. <xref ref-type="fig" rid="Ch1.F1"/>. The green
line corresponds to the monthly means while the red line is the 12-month moving average. The blue lines denote the standard deviations of the
parameter for an interval of 12 months. The annual cycle is only clear for
the IWV series in the lower panel. The interannual variations (red line) of
CF and ILW are quite similar. The seasonal variations of CF and ILW are
rather unclear. A spectral analysis of the monthly mean series gives us more
information.</p>
      <p>Figure <xref ref-type="fig" rid="Ch1.F2"/> shows the normalized power spectra of the monthly mean
series of CF, ILW, IWV and <inline-formula><mml:math id="M54" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>. The horizontal red lines denote the <inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula> level, where the confidence is 95 %. The power spectrum of IWV is
simple. IWV has only one dominant AO. The power
spectra of CF and ILW resemble each other to some extent. The SAO is approximately of the same size as the AO
in the
case of CF, ILW and the zonal wind <inline-formula><mml:math id="M56" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>. Further, there are statistically
significant spectral components with periods of 76, 85, 97 and 150 days.
However, the component at 150 days only occurs in CF and ILW. For the
interpretation of the CF and ILW spectra we add a power spectrum of the zonal
wind at 830 hPa (ca. 1.5 km altitude). The zonal wind series originates from
ECMWF operational reanalysis at the grid point nearest to Bern
(46.95<inline-formula><mml:math id="M57" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 7.44<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E). It is surprising that the power spectrum
of the zonal wind has strong annual harmonics that reach up to the fourth
harmonic. Actually, one would assume only an AO in the
prevailing westerly wind at northern midlatitudes that is larger during the
winter than during the summer. The cyclones and anticyclones embedded in the
westerly mean flow would be expected to have a random nature, which would
produce white noise in the spectrum. However, the <inline-formula><mml:math id="M59" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> spectrum in Fig. <xref ref-type="fig" rid="Ch1.F2"/> shows that there is an harmonic order in the temporal
<inline-formula><mml:math id="M60" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> fluctuations favouring the occurrence of annual harmonics up to the
fourth order. The harmonics may result from an interaction between the AO and intra-seasonal oscillations where the latter could be
connected to synoptic-scale variations or synoptic weather types.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><caption><p>Climatologies  of the short-term variability of  CF, ILW and IWV from
TROWARA  at Bern for the time interval from January 2004 to November 2016. In addition, we show
the coincident climatology of  zonal wind <inline-formula><mml:math id="M61" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>  from ECMWF operational reanalysis at  830 hPa (1.5 km altitude) above Bern.</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f08.jpg"/>

      </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><caption><p>Weekly cycle  of  CF, ILW and IWV  at Bern for the June to September
observations of TROWARA  during  the time interval from January 2004 to November 2016.
Weekday 1 corresponds to Sunday, weekday 2 corresponds to Monday, and so on.  The vertical
lines indicate the error of the mean of the averaged values.</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/12121/2017/acp-17-12121-2017-f09.jpg"/>

      </fig>

      <p>Since lower-tropospheric wind is a major player for cloud formation and
transport processes, we suggest that the spectral components in the zonal wind
spectrum could be one cause for the annual and semiannual oscillations in
the power spectra of CF and ILW. In addition, the periodicities of 97 and 85
days (close to the fourth harmonic) are strong in the spectra of <inline-formula><mml:math id="M62" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>, CF and
ILW. However, cloud formation also depends on synoptic weather types which
often have a seasonal dependence. For example, the situation of a
flat-pressure gradient weather type (or convective indifferent type) in
western
and central Europe is typical for summer, when convective forcing is often
larger than advective forcing above Switzerland
<xref ref-type="bibr" rid="bib1.bibx21 bib1.bibx5 bib1.bibx15" id="paren.30"/>. The high evaporation rate
during summer also supports that a moist atmosphere is getting unstable, and
a diurnal convection cycle leads to cumuliform clouds in the afternoon and
evening hours <xref ref-type="bibr" rid="bib1.bibx21 bib1.bibx15" id="paren.31"/>.</p>
      <p>During winter, the Swiss plateau often has low stratus which develops from
condensation of atmospheric water vapour near to the cold Earth surface.
Turbulence spreads the fog or cloud droplets up to the inversion layer in
about 1.5 km altitude. <xref ref-type="bibr" rid="bib1.bibx20" id="normal.32"/> reported that 6–8 days per month
in the Swiss plateau during winter have fog and stratus over an half day or
more (e.g. low stratus before noon). Stratus in the Swiss plateau during
winter is often associated with a cold wind from the northeast, which is
called the bise <xref ref-type="bibr" rid="bib1.bibx15" id="paren.33"/>. <xref ref-type="bibr" rid="bib1.bibx5" id="normal.34"/> reported that there
is also a seasonal cycle of the advective weather types with an occurrence
rate of about 45–50 % during winter and about 20 % in summer. Particularly,
the warm and cold fronts of cyclones pass Switzerland, where the rising
air masses at the warm front induce middle and high-level clouds. Further the
north and the south foehn can be associated with cloud formation over the
Swiss plateau. The occurrence of foehn is decreased during summer
<xref ref-type="bibr" rid="bib1.bibx5" id="paren.35"/>. Thus, the enhancement of cloud fraction by low stratus and
advective weather types in winter and cumuliform clouds in summer may induce
a SAO in CF and ILW over Bern.</p>
      <p>Figure <xref ref-type="fig" rid="Ch1.F3"/> shows the 12-month bandpass-filtered series of CF in the
upper panel, which corresponds to the AO. The amplitude of the AO was strongest around 2010 to 2011. The middle panel shows
the SAO, which is obtained by means of a 6-month bandpass
filter. The SAO is strong from 2010 to 2014. The lower
panel shows the combination of the AO and SAO (black line), which fits well to
the unfiltered green line of the monthly means of CF. Figure <xref ref-type="fig" rid="Ch1.F4"/> shows
the bandpass-filtered AO and SAO for the parameter ILW. Similar to CF, the
SAO in ILW is strong from 2010 to 2014. The lower panel shows the combination
of the AO and SAO (black line), which fits well to the unfiltered green line
of the monthly means of ILW. A relationship between CF and ILW is expected
since CF <inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:math></inline-formula> if ILW <inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">2.3</mml:mn></mml:mrow></mml:math></inline-formula> g m<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. An interannual change of the occurrence
rate of certain weather types could explain the interannual variation of the
SAO. For example, an enhancement in the occurrence of cumuliform clouds in
the summers from 2010 to 2014 may lead to the enhanced SAO from 2010 to 2014.
In future, the automated cloud type classification by thermal infrared
cameras may provide objective time series of cloud type frequencies.</p>
      <p>Figure <xref ref-type="fig" rid="Ch1.F5"/> depicts the climatologies of CF, ILW and IWV averaged over
the time interval from 2004 to 2016. The left-hand-side panels show the mean
AO (blue) and the mean SAO (red). It is surprising that the AO of CF is
almost in anti-phase to the AO in ILW, which peaks in July. We think that
convective cumuliform clouds are responsible for the high ILW values in June
and July since cumuliform clouds are typical for the flat-pressure gradient
situation, which has an occurrence frequency of about 35–40 % in summer
<xref ref-type="bibr" rid="bib1.bibx5 bib1.bibx15" id="paren.36"/>. The right-hand-side panels show the mean
behaviour of the combined AO and SAO in black while the green lines show the
mean behaviour derived from the monthly mean series of CF, ILW and IWV. In
addition, the standard error of the mean is given by green error bars. We can
see that the AO and the SAO component fit a major part of the observed
monthly mean series. There are only a few month-to-month variations in the
climatology of monthly means (green curve), which are not approximated by the
combined AO and SAO (black curve).</p>
      <p>Figure <xref ref-type="fig" rid="Ch1.F6"/> shows the climatology of eastward wind at 830 hPa (1.5 km)
above Bern over the time from 2004 to 2016. It is obvious that the
climatology of <inline-formula><mml:math id="M66" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> is rather similar to the climatology of CF in Fig. <xref ref-type="fig" rid="Ch1.F5"/>.
It seems that the strong eastward wind in December and January is
associated with the advective weather type which generates middle and high
clouds over Switzerland in the warm zone and the warm front of cyclones
<xref ref-type="bibr" rid="bib1.bibx15" id="paren.37"/>. Related to the study of <xref ref-type="bibr" rid="bib1.bibx17" id="normal.38"/>, we argue
that an increase in the lower-tropospheric wind <inline-formula><mml:math id="M67" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> leads to a deepening of
the cloud layer. In addition, one may argue that an eastward advection of
moist air from the Atlantic towards the Swiss plateau and the Alps occurs,
which leads to a maximum of CF in winter. The so-called advective west
weather type is enhanced by about 10 % during winter compared to summer
<xref ref-type="bibr" rid="bib1.bibx5" id="paren.39"/>. Generally the sum of the advective weather types has an
occurrence rate of about 45–50 % during winter and below 25 %
during summer <xref ref-type="bibr" rid="bib1.bibx5" id="paren.40"/>. Further, there is frequently low stratus in
the Swiss plateau in winter that is often connected with the advective northeast weather type (bise) and the cold Earth surface.</p>
</sec>
<sec id="Ch1.S4">
  <?xmltex \opttitle{Short-term oscillations in atmospheric water with periods $<$ 60 days}?><title>Short-term oscillations in atmospheric water with periods <inline-formula><mml:math id="M68" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 60 days</title>
      <p>For the investigation of the short-term variability, we change from the time
series of monthly means to the time series of daily means. It can be assumed
that the short-term oscillations with periods of a few days to weeks only
persist over time intervals of three wave cycles. Thus a Fourier transform over
the time interval from 2004 to 2016 is not adequate to address the role of
the short-term variability. Instead, we determine the mean amplitudes with a
bandpass filter with a fast response time. As described in the data analysis
section, the number of filter coefficients corresponds to each central
frequency to a time interval of three wave cycles. Thus short-term variations
existing over a short time interval contribute to the mean amplitude spectra,
which are shown in Fig. <xref ref-type="fig" rid="Ch1.F7"/>. The amplitude spectra of CF, ILW, IWV
and <inline-formula><mml:math id="M69" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> at Bern are derived by the wavelet-like bandpass filter method for
the time interval from 2004 to 2016. Again, <inline-formula><mml:math id="M70" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> originates from operational
ECMWF reanalysis at 830 hPa (1.5 km) above Bern. The spectra of CF, ILW and
<inline-formula><mml:math id="M71" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> are dominated by short-term variability on timescales less than 50 days.
The amplitude maxima are at a period of 7 days for CF, 6 days for ILW, 365 days for IWV and 17 days for <inline-formula><mml:math id="M72" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>.</p>
      <p>The bandpass-filtered data sets are also appropriate for the derivation of
the climatologies of CF, ILW, IWV and <inline-formula><mml:math id="M73" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>. Figure <xref ref-type="fig" rid="Ch1.F8"/> depicts the mean
amplitudes as function of the month and the period. The climatologies of CF,
ILW and IWV show some similarities with increased amplitudes in the period
range 5–10 days from spring to fall. The climatology of the <inline-formula><mml:math id="M74" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> spectrum
shows a 20-day oscillation in winter which is possibly related to a Rossby
wave. The 20-day period is close to 16 days, which is a theoretical period of
a normal mode of a free Rossby wave with a westward-propagating zonal
wavenumber 1 <xref ref-type="bibr" rid="bib1.bibx19" id="paren.41"/>. However, it is evident that the climatology
of the <inline-formula><mml:math id="M75" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> spectrum cannot explain the 7-day oscillation of CF, ILW and IWV
during summer. This indicates that advective forcing is not the reason for the
7-day oscillation in summer. The 7-day oscillation could be a man-induced
effect that may be enabled by periodic human activities during flat-pressure
gradient situations which prevail during summer <xref ref-type="bibr" rid="bib1.bibx5" id="paren.42"/>. The
synoptic motion of the flat-pressure gradient weather type is dominated by
small-scale circulations.</p>
      <p>We investigate whether the 7-day oscillation is phase-locked to a
weekly cycle which is found in aerosol concentration as induced by manmade
air pollution <xref ref-type="bibr" rid="bib1.bibx7" id="paren.43"/>. In the following, we only consider the data
from 1 June to 30 September when the 7-day oscillation is strong. Figure <xref ref-type="fig" rid="Ch1.F9"/> shows a significant weekly cycle for CF and ILW, while the weekly
cycle in IWV is marginal. The weekly cycles in CF and ILW have the largest values
on Sunday (day 1) and Monday (day 2) while the smallest values occur on
Thursday (day 5). It remains unclear whether the observed weekly cycles
in CF and ILW are due to manmade air pollution. <xref ref-type="bibr" rid="bib1.bibx2" id="normal.44"/> found a
well-pronounced and statistical significant weekly cycle for particulate matter above Switzerland but they did not find  a  statistically
significant weekly cycle for  precipitation.</p>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Summary</title>
      <p>TROWARA continuously measured CF, ILW and IWV in Bern, Switzerland, from 2004 to 2016. We find indications for
interannual variations of CF and ILW.
Fourier transformation and bandpass filtering give the result that IWV is dominated by an annual oscillation, leading to
an IWV  maximum of 24 kg m<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  in July to August.
The seasonal behaviour of CF and ILW is composed by both the annual and the semiannual oscillation.
However, the AO of CF has a maximum in December while the AO of ILW has a maximum in July.
The SAO of  CF and ILW is strong from 2010 to 2014.   We suggest that the SAO
could be related to the occurrence frequency of certain weather types that lead, for example,  to low stratus
in winter and cumuliform clouds in summer. In the future, we expect that automated cloud classification by thermal
infrared cameras will give us climatologies of cloud types,  which could be helpful for  interpretation of the periodicities in CF and ILW.</p>
      <p>The normalized power spectra of ILW and CF show statistically significant
spectral components with periods of 76, 85, 97 and 150 days. We find a
similarity between the power spectra of ILW and CF with those of zonal wind
at 830 hPa (1.5 km) above Bern. The occurrence of higher harmonics in the CF
and ILW spectra is possibly forced by the behaviour of the lower-tropospheric
wind and the occurrence rate of weather types. This observational result
emphasizes the role of the lower-tropospheric wind for generation and
transport of clouds over the Swiss plateau. The climatology of CF shows a
maximum in winter when the eastward wind is maximal. The mean amplitude
spectra of CF, ILW and <inline-formula><mml:math id="M77" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> are dominated by short-term variability on timescales less than 50 days. The short-term variability of CF, ILW and IWV has
increased amplitudes from spring to fall. We find weekly cycles in CF and ILW
for summer data (1 June to 30 September). The weekly cycles have largest
values on Sunday and Monday. This result is consistent with
<xref ref-type="bibr" rid="bib1.bibx22" id="normal.45"/>,
who found that the weekly cycles of cloud amount and the frequency of light
precipitation events are dominated by midweek decreases and weekend maxima
during summer. In contrast to this observational result,
<xref ref-type="bibr" rid="bib1.bibx1" id="normal.46"/> argued that increases in aerosol concentrations may
increase the amount of low-level cloudiness through a reduction in drizzle.
The relevant mechanisms which lead to the observed weekly cycles in CF and
ILW at Bern remain unclear.</p>
</sec>

      
      </body>
    <back><notes notes-type="codedataavailability">

      <p>Routines for data analysis and visualization are
available upon request by Klemens Hocke. Hourly measurements of IWV and ILW
from the radiometer TROWARA are available at the data centre STARTWAVE
(<uri>http://www.startwave.org</uri>) of University of Bern. Six-second data of IWV, ILW
and CF are available upon request by Klemens Hocke. We thank the European
Centre for Medium-range Weather Forecast (ECMWF) for operational reanalysis
data of zonal wind above Bern.</p>
  </notes><notes notes-type="authorcontribution">

      <p>KH carried out the spectral analysis. FNG and CM took care on the radiometer.
All authors contributed to the interpretation of the data set.</p>
  </notes><notes notes-type="competinginterests">

      <p>The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p>The study was supported by Swiss National Science Foundation under grant
number 200021-165516. We thank the reviewers for their valuable and helpful
comments. <?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: Martina Krämer<?xmltex \hack{\newline}?>
Reviewed by: two anonymous referees</p></ack><ref-list>
    <title>References</title>

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  </ref-list><app-group content-type="float"><app><title/>

    </app></app-group></back>
    <!--<article-title-html>Oscillations in atmospheric water above Switzerland</article-title-html>
<abstract-html><p class="p">Cloud fraction (CF), integrated liquid water (ILW) and integrated water vapour (IWV) were continuously
measured from 2004 to 2016  by the TROpospheric WAter RAdiometer (TROWARA) in Bern, Switzerland. There are
indications for interannual variations of CF and ILW.
A spectral analysis shows that IWV is dominated by an annual oscillation, leading to  an IWV
maximum of 24 kg m<sup>−2</sup>  in July to August and a minimum of 8 kg m<sup>−2</sup>  in  February.
The seasonal behaviour of CF and ILW is composed by both the annual and the semiannual oscillation.
However, the annual oscillation of CF has a maximum in December while the annual oscillation of ILW has a
maximum in July.  The semiannual oscillations of  CF and ILW are strong from 2010 to 2014.
The normalized power spectra of ILW and CF  show statistically significant spectral components with periods of  76, 85, 97 and 150 days.
We find a similarity between the power spectra of ILW and CF with those of zonal wind at 830 hPa (1.5 km)
above Bern.  Particularly, the occurrence of higher harmonics in the CF and ILW spectra is possibly forced by the behaviour of the lower-tropospheric wind.
The mean amplitude spectra of CF, ILW and IWV show increased short-term variability on timescales less than 40 days from spring to fall.
We find a weekly cycle of CF and ILW  from June to September with increased values on Saturday, Sunday and Monday.</p></abstract-html>
<ref-html id="bib1.bib1"><label>Albrecht(1989)</label><mixed-citation>
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness,
Science, 245, 1227–1230, <a href="https://doi.org/10.1126/science.245.4923.1227" target="_blank">https://doi.org/10.1126/science.245.4923.1227</a>, 1989.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>Barmet et al.(2009)</label><mixed-citation>
Barmet, P., Kuster, T., Muhlbauer, A., and Lohmann, U.: Weekly cycle in
particulate matter versus weekly cycle in precipitation over Switzerland,
J. Geophys. Res.-Atmos., 114,
D05206, <a href="https://doi.org/10.1029/2008JD011192" target="_blank">https://doi.org/10.1029/2008JD011192</a>,
2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>Beesley and Moritz(1999)</label><mixed-citation>
Beesley, J. A. and Moritz, R. E.: Toward an Explanation of the Annual
Cycle of Cloudiness over the Arctic Ocean, J. Climate, 12,
395–415, <a href="https://doi.org/10.1175/1520-0442(1999)012&lt;0395:TAEOTA&gt;2.0.CO;2" target="_blank">https://doi.org/10.1175/1520-0442(1999)012&lt;0395:TAEOTA&gt;2.0.CO;2</a>, 1999.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>Bromwich et al.(2012)</label><mixed-citation>
Bromwich, D. H., Nicolas, J. P., Hines, K. M., Kay, J. E., Key, E. L., Lazzara,
M. A., Lubin, D., McFarquhar, G. M., Gorodetskaya, I. V., Grosvenor, D. P.,
Lachlan-Cope, T., and van Lipzig, N. P. M.: Tropospheric clouds in
Antarctica, Rev. Geophys., 50, RG1004, <a href="https://doi.org/10.1029/2011RG000363" target="_blank">https://doi.org/10.1029/2011RG000363</a>,
2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>Collaud Coen et al.(2011)</label><mixed-citation>
Collaud Coen, M., Weingartner, E., Furger, M., Nyeki, S., Prévôt, A. S. H., Steinbacher, M.,
and Baltensperger, U.: Aerosol climatology and planetary boundary influence at the Jungfraujoch analyzed
by synoptic weather types, Atmos. Chem. Phys., 11, 5931–5944, <a href="https://doi.org/10.5194/acp-11-5931-2011" target="_blank">https://doi.org/10.5194/acp-11-5931-2011</a>, 2011.
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radiometers, Int. J. Remote Sens., 32, 751–765, 2011.
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