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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">HESS</journal-id>
<journal-title-group>
<journal-title>Hydrology and Earth System Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">HESS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Hydrol. Earth Syst. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1607-7938</issn>
<publisher><publisher-name>Copernicus GmbH</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>

    <article-meta>
      <article-id pub-id-type="doi">10.5194/hess-19-3093-2015</article-id><title-group><article-title>Attribution of European precipitation and temperature<?xmltex \hack{\newline}?> trends to
changes in synoptic circulation</article-title>
      </title-group><?xmltex \runningtitle{changes in synoptic circulation}?><?xmltex \runningauthor{A.~K.~Fleig et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Fleig</surname><given-names>A. K.</given-names></name>
          <email>afl@nve.no</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Tallaksen</surname><given-names>L. M.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-8480-7842</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>James</surname><given-names>P.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Hisdal</surname><given-names>H.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Stahl</surname><given-names>K.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2159-9441</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Norwegian Water Resources and Energy Directorate, P.O. Box 5091, Majorstua, 0301 Oslo, Norway</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0316 Oslo, Norway</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Deutscher Wetterdienst, Frankfurter Strasse 135, 63037 Offenbach, Germany</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Hydrology, University of Freiburg, Fahnenbergplatz, 79098 Freiburg, Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">A. K. Fleig (afl@nve.no)</corresp></author-notes><pub-date><day>13</day><month>July</month><year>2015</year></pub-date>
      
      <volume>19</volume>
      <issue>7</issue>
      <fpage>3093</fpage><lpage>3107</lpage>
      <history>
        <date date-type="received"><day>22</day><month>October</month><year>2014</year></date>
           <date date-type="rev-request"><day>18</day><month>November</month><year>2014</year></date>
           <date date-type="rev-recd"><day>05</day><month>May</month><year>2015</year></date>
           <date date-type="accepted"><day>11</day><month>June</month><year>2015</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015.html">This article is available from https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015.html</self-uri>
<self-uri xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015.pdf">The full text article is available as a PDF file from https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015.pdf</self-uri>


      <abstract>
    <p>Surface climate in Europe is changing and patterns in trends have been found
to vary at sub-seasonal scales. This study aims to contribute to a better
understanding of these changes across space and time by analysing to what
degree observed climatic trends can be attributed to changes in synoptic
atmospheric circulation. The relative importance of synoptic circulation
changes (i.e. trends in synoptic type frequencies) as opposed to trends in
the hydrothermal properties of synoptic types (within-type trends) on
precipitation and temperature trends in Europe is assessed on a monthly
basis. The study is based on mapping spatial and temporal trend patterns and
their variability at a relatively high resolution (0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>;
monthly) across Europe. Gridded precipitation and
temperature data (1963–2001) originate from the Watch Forcing Data set and
synoptic types are defined by the objective SynopVis Grosswetterlagen (SVG).
During the study period, relatively high influence of synoptic circulation
changes are found from January to March, contributing to wetting trends in
northern Europe and drying in the south. Simultaneously, particularly dry
synoptic types get warmer first in south-western Europe in November and/or December
and affect most of Europe in March and/or April. Strong influence of
synoptic circulation changes is again found in June and August. In general,
changes in synoptic circulation has a stronger effect on climate trends in north-western
Europe than in the south-east. The exact locations of the strongest
influence of synoptic circulation changes vary with the time of year and to
some degree between precipitation and temperature. Throughout the year and
across the whole of Europe, precipitation and temperature trends are caused
by a combination of synoptic circulation changes and within-type changes
with their relative influence varying between regions, months and climate
variables.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>The need to understand the influence of global change on the water cycle
has led to considerable scientific effort as seen by a number of studies of
trends in hydrometeorological variables (IPCC, 2013). Large-scale studies
covering all of Europe include, for example, Klein Tank et al. (2002), Klein
Tank and Können (2003), Zolina et al. (2010), Teuling et al. (2011) and
van den Besselaar et al. (2012) for precipitation and temperature. These
studies cover both annual and seasonal averages as well as extremes and
document changes in averages and the structure of European hydroclimatology,
including more frequent precipitation extremes and longer wet periods.
Changes and trends in hydroclimatology are commonly analysed on an annual,
seasonal or event basis. However, the transition from winter to summer
conditions (and vice versa) in the atmospheric circulation over the North
Atlantic and Europe is generally a slow and gradual process (e.g. Vrac et
al., 2014). Thus, higher temporal resolutions may also be beneficial when
analysing changes in hydroclimatological variables. Up to now, less focus
has been on the monthly scale. One example is the work by Serrano
et al. (1999) who considered monthly precipitation trends on the Iberian Peninsula
(1921–1995). They found a significant trend in March only. Similarly, Paredes
et al. (2006) found a decrease in March precipitation in the Mediterranean
and southern France (1960–2000), and increasing precipitation in the
north-western parts of the British Isles, large parts of Scandinavia and
along the North Sea coast of the Netherlands and Germany.</p>
      <p>These climatic trends affect the continental hydrology. Stahl et al. (2010,
2012) systematically studied streamflow trends in Europe over the period
1962–2004 on annual, seasonal and monthly scales. Widespread increases in
streamflow were found across most of Europe during December, with an
exception around the Mediterranean and in the east. From January onwards,
decreasing trends expand towards the west and north, covering large parts of
Europe in June and, after a break in July, decreasing trends across Europe
reach a maximum in August. Despite the differing temporal scales and study
periods as well as the influence of locally varying hydrological
characteristics, similarities can be seen in the most dominating large-scale
patterns of monthly streamflow trends (Stahl et al., 2010, 2012) with
seasonal trends in European precipitation and temperature as reported by
Teuling et al. (2011) based on the E-OBS data set (1979–2008). Both show a
strong north-south gradient in trends across Europe during the winter season
(DJF). These broad-scale patterns of change suggest considerable synoptic
circulation forcing. However, the patterns in streamflow changes also
suggest additional thermal forcing, for instance through changing
proportions of rain versus snowfall. As such, Wilson et al. (2010)
attributed earlier snowmelt floods to increased temperature and a tendency
to longer summer droughts in rivers in south-eastern Norway, to an increase
in temperature and higher evapotranspiration. A better understanding of the
monthly varying large-scale patterns in European streamflow can be achieved
by assessing monthly trends and causing processes in the two main drivers of
streamflow: precipitation and temperature (through its influence on
evapotranspiration and snow accumulation and/or melt).</p>
      <p>Regional variability in hydroclimatology is part of larger-scale patterns
and processes, and synoptic-scale meteorological data can provide
complementary information on particular processes, as for example the
contrasting precipitation anomalies between northern and southern Europe
related to large-scale modes such as the North Atlantic Oscillation (NAO).
Large-scale atmospheric modes and smaller scale synoptic types are
frequently used for assessing local and regional climatic features (e.g.
Huth et al., 2008), as well as climate-hydrology connections as recently
reviewed by Hannah et al. (2014) for regional studies across Europe,
including extremes, such as floods (e.g. Prudhomme and Genevier, 2011) and
streamflow droughts (e.g. Fleig et al., 2010, 2011).</p>
      <p>Synoptic types (STs) characterise the synoptic atmospheric situation of a
large region as a single nominal variable and are usually strongly related
to a number of local climatic variables including precipitation and
temperature (e.g. James, 2007). They are most commonly characterised by
their main large-scale features, cyclonicity and/or location of high- and
low-pressure systems. However, their local climatological features may vary.
For instance, precipitation has a relatively high spatial variability within
the larger-scale atmospheric conditions. Temperature anomalies, on the other
hand, are more coherent, but the relation to high- and low-pressure systems
varies throughout the year and among regions according to absolute
temperature values.</p>
      <p>The hydrothermal properties of STs have also been found to be
non-stationary, in particular during the summer season (e.g. Beck et al.,
2007; Jacobeit et al., 2009; Cahynová and Huth, 2010; Küttel et al.,
2011). Thus, changes in precipitation and temperature can be caused by
changes in the occurrence frequencies of STs, which mainly corresponds to
changes in the atmospheric circulation, as well as by changes in the local
hydrothermal properties of a certain ST (known as within-type change).
This implies that the observed trend in precipitation (or temperature) is
the sum of trends caused by circulation change and within-type change,
respectively (e.g. Beck et al., 2007; Cahynová, 2010). Previous studies
on non-stationarities in the hydrothermal properties of STs have focused on
seasonal data or one season only (Küttel et al., 2011), on one region
and not on regional variability (Beck et al., 2007; Cahynová and Huth,
2010), or on specific processes such as the occurrence of extreme events
(Jacobeit et al., 2009). However, changes in the occurrences of STs in
Europe have been found to vary on a monthly timescale (Hoy et al., 2013a).</p>
      <p>The question arises to which degree the regionally varying trend patterns in
European hydroclimatology throughout the year are influenced by changes in
the atmospheric circulation (referred to as synoptic-circulation-induced
trends) as opposed to trends in the local hydrothermal properties of
synoptic types (referred to as within-type trends). Here, we investigate
their relative influence on trends in monthly precipitation and temperature.
Special focus is given to trends in the frequencies of locally wet and dry
STs, to improve our understanding of the physical causes controlling
regional precipitation changes and the relations between precipitation and
temperature trends within STs. As any trend analysis strongly depends on the
study period and to some degree on the methodology (e.g. Hannaford et al.,
2013), the focus in this study is not primarily on detecting trend
magnitudes. Rather, we aim to provide a better understanding of key
processes controlling observed trends in temperature and precipitation. The
study period 1963–2001 was chosen due to the availability of a high-quality
gridded data set for precipitation and temperature, the Watch Forcing Data set
(Weedon et al., 2011) and the comparability to previously observed monthly
trend patterns in European streamflow (Stahl et al., 2010, 2012). The work
adds to previous studies linking circulation and within-type changes to
hydroclimatological variables by using a higher temporal (monthly) and
spatial resolution (0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) as well as a larger
study domain (Europe).</p>
      <p>In the following, climate and synoptic type data are described (Sect. 2),
as well as the methods for analysing synoptic-circulation-induced trends in
precipitation and temperature and trends within wet and dry STs (Sect. 3).
Following the results (Sect. 4), the discussion in Sect. 5 attributes
monthly precipitation and temperature trends to changes in the atmospheric
circulation or within-type changes. Finally, conclusions are drawn and the
influence of changes in STs on monthly streamflow trends in Europe are
summarised.</p>
</sec>
<sec id="Ch1.S2">
  <title>Data</title>
<sec id="Ch1.S2.SS1">
  <title>Synoptic types</title>
      <p>Daily synoptic types (STs) for the European domain are defined according to
the classification procedure, SynopVis Grosswetterlagen (SVG). This is a new
objective-automatic classification of the well-known 29-type Hess and
Brezowsky Grosswetterlagen (GWL), which have been classified manually for
many years at the German Weather Service, a series which extends back to
1881 (Werner and Gerstengabe, 2010). The SVG system is similar to the
previously recommended (Fleig et al., 2010, 2011) Objective Grosswetterlagen
(OGWL; James, 2007), but has several significant improvements that are
summarised briefly below.</p>
      <p>Whereas OGWL was based on only two variables, mean sea-level pressure (MSLP)
and the 500 hPa geopotential height (Z500), SVG also adds the relative
thickness of the lower troposphere (Z500–Z1000) and total column
precipitable water (PWAT) fields to improve the method's ability to
distinguish between relevant air mass types affecting the European region.
This is especially important for hydroclimatological studies, since
precipitation totals are clearly influenced by air mass in terms of moisture
content and by the dynamics of frontal air mass boundaries. The data are
derived from the 20th Century reanalysis (20CR) product (1871–2010;
Compo et al., 2011) and the NCEP/NCAR reanalysis data for the most recent
period (2011 onwards) in order to obtain an ST series as long and homogenous
as possible. A spatial domain is used, which varies as a function of
variable and season, covering the eastern North Atlantic and Europe. As in
OGWL, the defining variables are correlated against a set of standard
seasonally varying base patterns for each type in the original GWL. These
base patterns have been significantly improved by James (2007) by
optimising their distribution across the phase space of possible synoptic
variability. For each synoptic situation, the highest correlating pattern is
chosen as the classified GWL-type for that day. Finally, a temporal filter
is employed to remove insignificant transient effects, resulting in a
classification that has similar temporal characteristics to the manual
Hess-Brezowsky GWL catalogue in which each ST must last at least 3 days
by definition.</p>
      <p>The 29 SVG-STs have a much flatter frequency distribution than the original
manual GWL-types, since the most common type occurs on average no more than
around four times as often as the least common type. This improves the
usefulness of the SVG series, due to higher total information content. The
SVG series has been used successfully, for example, to examine the
large-scale variability of circulation patterns around Europe (Hoy et al.,
2013a), to study the relationship between synoptic types and thunderstorm
occurrence over Germany (Wapler and James, 2015) and in a local study on
precipitation extremes in parts of Montenegro (Ducić et al., 2012). With
the 29 STs grouped into four major types, mainly representing westerlies,
northerlies, easterlies and southerlies, the SVG series has been found
useful also in comparison with other classifications analysing the impact of
large-scale atmospheric circulation on European temperature (Hoy et al.,
2013b) and precipitation (Hoy et al., 2014).</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Precipitation and temperature</title>
      <p>Gridded (0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) time series of daily
precipitation (<inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) and mean temperature (<inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) from the Watch Forcing Data set
(WFD) were used. The WFD is a historical climatic data set (1958–2001) based
on ERA-40 reanalysis with bias-corrected mean temperature and precipitation
based on CRU-TS2.1 and GPCCv4 observations, respectively (Weedon et al.,
2011). Precipitation is corrected for station undercatch, but not for
elevation. The grid cells follow the CRU land surface mask. The higher
spatial resolution as compared to ERA-40 and other climatological data set
makes the WFD particularly useful for application in hydrological studies. The
trends derived from the reanalysis and bias-corrected precipitation and
temperature are hereafter referred to as trends in WFD-precipitation (WFD-P)
and WFD-temperature (WFD-T).</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Methods</title>
<sec id="Ch1.S3.SS1">
  <title>Trends and trend ratios</title>
      <p>The extent to which observed trends in temperature and precipitation can be
explained by synoptic circulation changes or changes in the hydrothermal
properties of STs (within-type trends) is investigated following
Cahynová and Huth (2010). This implies calculating a
synoptic-circulation-induced trend and comparing it to the observed trend in
<inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>; here WFD-P and WFD-T are used). The synoptic-circulation-induced
trend calculation assumes that all changes in <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) come from synoptic
changes only. The changes are quantified in terms of monthly ST frequencies,
and the calculation procedure is as follows:
<list list-type="order"><list-item><p>For each ST, <inline-formula><mml:math display="inline"><mml:mi>s</mml:mi></mml:math></inline-formula>, a long-term WFD-P (or WFD-T) mean value,
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>T</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, is calculated for each
calendar month, <inline-formula><mml:math display="inline"><mml:mi>m</mml:mi></mml:math></inline-formula>, for each cell, <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>.
Example: the long-term mean <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> in cell 1, for ST1 in January,
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">Jan</mml:mi><mml:mo>,</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, is derived as the mean of all <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> values in cell 1
occurring on days with ST1 in any January in the whole study period.</p></list-item><list-item><p>Daily hypothetical <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) time series are then constructed by replacing
the daily WFD-P (or WFD-T) value with the long-term mean per calendar month
according to the actual observed ST on that day. In this way, the
hydrothermal properties of the STs are assumed stationary throughout the
study period.
Example: if the ST time series would start with the following STs on the
first 3 days of January:
ST5, ST9, ST9, etc., the corresponding hypothetical <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> series for cell <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula> would start with:
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">5</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">Jan</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">9</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">Jan</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">9</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">Jan</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>,
etc.</p></list-item><list-item><p>From the hypothetical daily series, hypothetical monthly <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) series
are derived.</p></list-item><list-item><p>Linear hypothetical, i.e. synoptic-circulation-induced, trends,
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">circ</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, are then calculated for each calendar month, <inline-formula><mml:math display="inline"><mml:mi>m</mml:mi></mml:math></inline-formula>,
and cell, <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>.</p></list-item><list-item><p>Monthly ratios, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mrow><mml:mi mathvariant="normal">circ</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, of the synoptic-circulation-induced
trend divided by the WFD trend, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">WFD</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, finally indicate the
proportion of the monthly WFD-P (or WFD-T) trends that can be related to
synoptic circulation changes:<disp-formula id="Ch1.E1" content-type="numbered"><mml:math display="block"><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mrow><mml:mi mathvariant="normal">circ</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">circ</mml:mi><mml:mo>,</mml:mo><mml:mi>m</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:mrow><mml:mi mathvariant="normal">WFD</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula></p><p>Hence, whereas the synoptic-circulation-induced trends inform whether there
is a trend or not due to synoptic circulation changes, the trend ratio
relates this trend to the total trend in WFD-P (or WFD-T). In order to
exclude irrelevant or unrealistic trend ratios due to very small trends in
WFD, trend ratios are only calculated for grid cells and months where the
WFD trend is significant at the 70 % significance level. Linear trends are
calculated using linear least-squares regression and the t-test is used to
test the statistical significance. The rather low significance level is
chosen as a compromise between excluding small trends and detecting
large-scale regional trend patterns. Trend ratio values of 0 and 1 mean that the whole WFD trend can be explained by the
synoptic-circulation-induced trend. Values larger than 1 mean that the
synoptic-circulation-induced trend is larger than the WFD trend, whereas
values smaller than zero imply opposite signs of the trends. This can occur
when circulation changes captured by the synoptic-circulation-induced trend
and within-type changes have opposite directions.</p></list-item></list></p>
</sec>
<sec id="Ch1.S3.SS2">
  <title>Trends and trend ratios within wet and dry STs</title>
      <p>To study the processes behind local precipitation and temperature trends
further, the 29 STs were combined into groups of dry, wet and
average-precipitation STs for each grid cell separately, and <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> and <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula> trends
explained by within-ST-group changes were derived. Local precipitation
properties associated with an ST can vary somewhat throughout the year. Here,
this seasonal variability is not accounted for, as a consistent grouping for
all calendar months was preferred. Therefore, the grouping is based on the
long-term mean precipitation per ST over the whole year in the considered
grid cell. Hence, the sets of STs defined as wet, dry or average
precipitation STs vary among grid cells. STs are defined as wet (dry), when
they on average bring more (less) precipitation than the mean, <inline-formula><mml:math display="inline"><mml:mi mathvariant="italic">μ</mml:mi></mml:math></inline-formula>, plus
(minus) half a standard deviation, <inline-formula><mml:math display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>, (of all STs) to a grid cell
(Eqs. 2 and 3). The remaining STs are considered as average-precipitation
STs, hereafter referred to as average STs (Eq. 4).

                <disp-formula specific-use="align" content-type="numbered"><mml:math display="block"><mml:mtable displaystyle="true"><mml:mlabeledtr id="Ch1.E2"><mml:mtd/><mml:mtd/><mml:mtd><mml:mrow><?xmltex \hack{\hbox\bgroup\fontsize{8.6}{8.6}\selectfont$\displaystyle}?><mml:mi mathvariant="normal">Wet</mml:mi><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mi mathvariant="normal">STs</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi mathvariant="normal">for</mml:mi><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mi mathvariant="normal">cell</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi>i</mml:mi><mml:mo>:</mml:mo><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>&gt;</mml:mo><mml:mi mathvariant="italic">μ</mml:mi><mml:mfenced close=")" open="("><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><mml:mo>+</mml:mo><mml:mn>0.5</mml:mn><mml:mi mathvariant="italic">σ</mml:mi><mml:mfenced open="(" close=")"><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><?xmltex \hack{$\egroup}?></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E3"><mml:mtd/><mml:mtd/><mml:mtd><mml:mrow><?xmltex \hack{\hbox\bgroup\fontsize{8.6}{8.6}\selectfont$\displaystyle}?><mml:mi mathvariant="normal">Dry</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi mathvariant="normal">STs</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi mathvariant="normal">for</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi mathvariant="normal">cell</mml:mi><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mi>i</mml:mi><mml:mo>:</mml:mo><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>&lt;</mml:mo><mml:mi mathvariant="italic">μ</mml:mi><mml:mfenced close=")" open="("><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><mml:mo>-</mml:mo><mml:mn>0.5</mml:mn><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">σ</mml:mi><mml:mfenced close=")" open="("><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><?xmltex \hack{$\egroup}?></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E4"><mml:mtd/><mml:mtd/><mml:mtd><mml:mrow><?xmltex \hack{\hbox\bgroup\fontsize{9}{9}\selectfont$\displaystyle}?><mml:mi mathvariant="normal">Average</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi mathvariant="normal">STs</mml:mi><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mi mathvariant="normal">for</mml:mi><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mi mathvariant="normal">cell</mml:mi><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi>i</mml:mi><mml:mo>:</mml:mo><mml:mi mathvariant="italic">μ</mml:mi><mml:mfenced open="(" close=")"><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><mml:mo>-</mml:mo><mml:mn>0.5</mml:mn><mml:mi mathvariant="italic">σ</mml:mi><mml:mfenced close=")" open="("><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><?xmltex \hack{$\egroup}?></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mtr><mml:mtd/><mml:mtd><mml:mrow><mml:mo>≤</mml:mo><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>≤</mml:mo><mml:mi mathvariant="italic">μ</mml:mi><mml:mfenced close=")" open="("><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><mml:mo>+</mml:mo><mml:mn>0.5</mml:mn><mml:mi mathvariant="italic">σ</mml:mi><mml:mfenced open="(" close=")"><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">ST</mml:mi><mml:mo>,</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn>29</mml:mn><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mfenced><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>

            where <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> is the mean precipitation of ST <inline-formula><mml:math display="inline"><mml:mi>s</mml:mi></mml:math></inline-formula> in cell <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula> over the
whole year. For each ST group, monthly frequency trends are derived.</p>
      <p>Trends in <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) within the groups of wet, dry and average STs are
calculated using only the days on which an ST of the respective ST group
occurred. For months when no ST of the considered ST group occurred, the
long-term monthly average WFD-P (or WFD-T) value for this ST group is
assigned, hence obtaining a complete monthly within-ST-group <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) time
series. This constitutes along with the cell-wise grouping into wet, dry and
average STs, a modification of the calculation suggested by Cahynová (2010).
The calculation procedure consists of the following steps:
<list list-type="order"><list-item><p>For each month, the days with an ST of the considered ST group are
selected and a monthly <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) value is calculated using the WFD-P (or
WFD-T) data of these days only.</p></list-item><list-item><p>For the considered ST group <inline-formula><mml:math display="inline"><mml:mi>g</mml:mi></mml:math></inline-formula>, a long-term WFD-P (or WFD-T) mean value,
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>g</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> (or <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>T</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi>g</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>), is calculated for each
calendar month, <inline-formula><mml:math display="inline"><mml:mi>m</mml:mi></mml:math></inline-formula>, and each cell, <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>.</p><p>Example: for cell <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>, the long-term mean P for wet STs in cell <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula> in January,
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>P</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mrow><mml:mi mathvariant="normal">wetSTs</mml:mi><mml:mo>,</mml:mo><mml:mi mathvariant="normal">Jan</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, would be calculated as the mean of all monthly
January <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> values in cell <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula> derived in step 1.</p></list-item><list-item><p>The monthly time series derived in step 1 might be incomplete as there
might be months during which no ST of the considered ST group occurred. For
these months, the long-term WFD-P (or WFD-T) mean value of this calendar
month is used.</p></list-item><list-item><p>Linear within-ST-group trends, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">wetSTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> (or
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">drySTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">averageSTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>), are then calculated for
each ST group and calendar month, <inline-formula><mml:math display="inline"><mml:mi>m</mml:mi></mml:math></inline-formula>, and cell, <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>.</p></list-item><list-item><p>The finally derived monthly ratios of the within-ST-group trends divided
by the WFD trend, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">WFD</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>, indicate the proportion of the
monthly WFD-P (or WFD-T) trends that can be related to changes in wet, dry
and average STs, respectively:<disp-formula specific-use="align" content-type="numbered"><mml:math display="block"><mml:mtable displaystyle="true"><mml:mlabeledtr id="Ch1.E5"><mml:mtd/><mml:mtd/><mml:mtd><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mrow><mml:mi mathvariant="normal">wetSTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">wetSTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</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:mrow><mml:mi mathvariant="normal">WFD</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E6"><mml:mtd/><mml:mtd/><mml:mtd><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mrow><mml:mi mathvariant="normal">drySTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">drySTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</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:mrow><mml:mi mathvariant="normal">WFD</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E7"><mml:mtd/><mml:mtd/><mml:mtd><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mrow><mml:mi mathvariant="normal">averageSTs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mi mathvariant="normal">average</mml:mi><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mi mathvariant="normal">STs</mml:mi><mml:mo>,</mml:mo><mml:mi>m</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:mrow><mml:mi mathvariant="normal">WFD</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:mtd></mml:mlabeledtr></mml:mtable></mml:math></disp-formula></p><p>Changes in the characteristics of wet, dry and average STs can either be
changes of the hydrothermal properties within the single STs of an ST group
(e.g. all wet STs are getting wetter/drier and warmer/colder), or the
frequencies of the single STs within an ST group are changing (e.g. the
wettest of the wet STs become more/less frequent and the driest of the wet
STs become less/more frequent). Ratios of the within ST group trends divided
by the WFD trends are here analysed to identify possible differences between
wet and dry STs and varying importance among regions and months. The overall
proportion of WFD trends caused by changes in the hydrothermal properties
summed over all STs is the difference between the total WFD trend and the
synoptic-circulation-induced trend, i.e. 1-<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mrow><mml:mi mathvariant="normal">circ</mml:mi><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>.</p></list-item></list></p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Synoptic-circulation-induced trends for precipitation (rows 1 and
3) and temperature (rows 2 and 4) significant at the 70 % (light colours)
and 95 % (dark colours). Precipitation: increasing trends in blue,
decreasing trends in red. Temperature: increasing trends in red, decreasing
trends in blue.</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f01.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S4">
  <title>Results</title>
<sec id="Ch1.S4.SS1">
  <title>Precipitation: synoptic-circulation-induced trends and trend ratios</title>
      <p>Monthly synoptic-circulation-induced precipitation trends during the study
period (1963–2001) are presented in Fig. 1 (rows 1 and 3). In most months
with strong trends, opposite synoptic-circulation-induced precipitation
trends are found in northern and southern Europe.
Synoptic-circulation-induced trends are strongest and most widespread in
January, February and March with increasing precipitation across northern
Europe and decreasing precipitation in the South. In April and May, there
are only few synoptic-circulation-induced precipitation trends (not
resembling the previous months). Clear regional trend patterns occur again
in June with increasing precipitation across Scandinavia and decreasing
trends mainly on the Iberian Peninsula. Strong synoptic-circulation-induced
precipitation trends are found also in August, September and November, but
the regional patterns differ considerably from the previous months with
strong trends (i.e. January–March and June). In August,
synoptic-circulation-induced precipitation increases are found in western
Scandinavia together with strong decreases across all of central Europe and
parts of south-eastern Europe. The picture is notably different just one
month later in September; now a strong precipitation decrease is seen in
north-eastern Scandinavia and no significant trends elsewhere. In November,
strongest decreasing synoptic-circulation-induced precipitation trends are
seen around and particularly south-east of the Baltic Sea, and increasing
trends in the very south of Europe from west to east. The latter are the
only increasing synoptic-circulation-induced precipitation trends in
southern Europe that are significant at the 95 % level.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p>Monthly trend ratios for synoptic-circulation-induced trends in
precipitation (rows 1 and 3) and temperature (rows 2 and 4).</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f02.pdf"/>

        </fig>

      <p>Trend ratios are presented in Fig. 2 (rows 1 and 3). They show that 50 %
or more of the precipitation trends in large parts of Europe can be
attributed to synoptic circulation change from January to March. Ratios as
high as 0.8–1.0 are found, particular in January and February, in August
in central Germany and in November in central Europe. Whereas trend ratios
less than 0.5 and often close to zero are found during late spring and early
summer, regionally higher values are found in June in eastern Scandinavia
and the south-western part of Iberia, locally in northern UK in March and in
small regions of central Europe in July. High trend ratios dominate again in
August and September with a centre over central Europe and north-eastern
Europe respectively. Trend ratios are also above 0.5 in western and parts
of central Europe in October and south of the Baltic region in November.</p>
</sec>
<sec id="Ch1.S4.SS2">
  <title>Temperature: synoptic-circulation-induced trends and trend ratios</title>
      <p>Synoptic-circulation-induced temperature trends are presented in Fig. 1
(rows 2 and 4). Strong synoptic-circulation-induced temperature trends are
found for the same months as synoptic-circulation-induced precipitation
trends, i.e. the most widespread and strongest trends are in February and
January, followed by March, June, August and November.
Synoptic-circulation-induced temperature trends are mostly positive.
However, weak decreasing trends are found around the North Sea and western
parts of the Baltic Sea in June, in eastern Europe in September and
south-eastern and central Europe in November.</p>
      <p>Trend ratios for temperature are shown in Fig. 2 (rows 2 and 4). As for
precipitation, they are highest in January and February with values of 0.4
and above across all of Europe except for the south-east. Values up to 0.8
are found in large parts of north-western Europe. Ratios decrease during
March and April. In May, they increase again on the British Isles and in
western and central Europe. In August, the highest ratios (around 0.5) are
centred over central Europe, but values of 0.3 and higher are seen in the
surrounding regions, in particular to the south-west.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Monthly frequency trends in wet STs significant at the 70 %
(light colours) and 95 % (dark colours); increasing trends in blue,
decreasing trends in red.</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f03.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS3">
  <title>ST frequencies trends</title>
      <p>Trends in the frequency of wet STs are shown in Fig. 3 (similar results are
obtained for dry and average STs, see the Supplement). The trends
show a pronounced north-south pattern for months with widespread regional
trends, including in January–March and August. There are increases
(decreases) in wet (dry) STs in the north and decreases (increases) in wet
(dry) STs in the south. Trends are strongest and most widespread in
February. In December, there are relatively few significant trends and the
trend pattern follows a more south-west to north-east divide (wetter in the
west, drier in the east). In August, the decreasing trends in wet STs extend
further north than during the winter months, whereas in March the increasing
trends in wet STs extend east and southwards. In March, on the other hand,
an increase in the frequency of dry STs is seen around the southern part of
the North Sea and further into Germany and northern France. In July,
September and November the strong north-south pattern (from January to March
and August) is completely reversed, but generally less strong, in particular
in July. Strong synoptic circulation changes are also found in June with
increasing frequencies in wet STs in the north and east and decreases in the
south-west. Frequency trends for all ST groups are fewest in April, July and
October.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p>Monthly trends within the groups of wet STs for precipitation
(rows 1 and 3) and temperature (rows 2 and 4) significant at the 70 %
(light colours) and 95 % (dark colours). Precipitation: increasing trends
in blue, decreasing trends in red. Temperature: increasing trends in red,
decreasing trends in blue.</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f04.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p>Monthly trends within the groups of dry STs for precipitation
(rows 1 and 3) and temperature (rows 2 and 4) significant at the 70 %
(light colours) and 95 % (dark colours). Precipitation: increasing trends
in blue, decreasing trends in red. Temperature: increasing trends in red,
decreasing trends in blue.</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f05.png"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS4">
  <title>Precipitation: trends and trend ratios within ST groups</title>
      <p>Precipitation and temperature trends within ST groups (Figs. 4–5) and
corresponding trend ratios (Figs. 6–7) show that changes within wet and dry
STs have varying effects. Precipitation amounts associated with the groups
of wet STs mainly increase or do not change throughout the year and across
Europe (Fig. 4, rows 1 and 3). In particular, during winter until April and
again in July, wetting trends are most widespread. Drying trends within wet
STs are more local and most widespread in eastern Europe in October.
Persisting drying trends are found in Iberia from January to March,
spreading from western Iberia in January north-eastward to also include
parts of France in March. Least wetting trends within wet STs are found in
August, when also drying trends are only local.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p>Monthly trend ratios for trends within the groups of wet STs for
precipitation (rows 1 and 3) and temperature (rows 2 and 4).</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f06.png"/>

        </fig>

      <p>The groups of dry STs show fewer wetting trends than the wet STs, with the
exception of August, when the dry STs get wetter in southern Scandinavia
(Fig. 5, rows 1 and 3). Throughout the year, there are large parts of Europe
without significant precipitation trends within dry STs, and regions with
drying trends dominate over those with wetting in December and January. Both
regional wetting and drying trends occur during the remaining months. In
February, the groups of dry STs get drier in eastern Europe and wetter in
central and north-western Europe. From April to August, drying within the
dry STs is mostly seen in central Europe.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p>Monthly trend ratios for trends within the groups of dry STs for
precipitation (rows 1 and 3) and temperature (rows 2 and 4).</p></caption>
          <?xmltex \igopts{width=\textwidth}?><graphic xlink:href="https://hess.copernicus.org/articles/19/3093/2015/hess-19-3093-2015-f07.pdf"/>

        </fig>

      <p>The regional trend patterns in precipitation within the groups of average
STs (see Supplement) show similarities to the precipitation
trend patterns within both the dry and wet ST groups. During the summer
months, trend patterns are weaker and regionally more variable than in the
other ST groups. Stronger precipitation trends are found in October in
southern Europe with drying in the south-west. This is in contrast to a
wetting trend within wet STs in the same region.</p>
      <p>Precipitation trends within wet STs explain the largest part of the overall
precipitation trends. High trend ratios are found regionally or locally
across Europe in December, April, June and July and in parts of Europe
during the remaining months (Fig. 6, rows 1 and 3). The groups of dry STs
(Fig. 7, rows 1 and 3) and, to some extent, the groups of average STs (see
Supplement) show low or negative trend ratios. High negative
trend ratios are in particular found from January to March in northern and
north-eastern Europe. In particular, August shows positive and negative
trend ratios varying on a small spatial scale for wet, dry and average ST
groups.</p>
</sec>
<sec id="Ch1.S4.SS5">
  <title>Temperature: trends and trend ratios within ST groups</title>
      <p>Warming or no temperature trends dominates the regional monthly trend
patterns within wet, dry and average ST groups (Fig. 4–5, rows 2 and 4).
Also, the cooling trends in south-eastern Europe in February and March,
northern and central Europe in June and part of eastern Europe during the
autumn months are at least partly found within the three kinds of groups.
The wet STs show, however, a strong cooling trend in south-eastern Europe in
January and south-western Europe in February, whereas the dry STs show
warming trends in the same months and regions. Furthermore, dry STs show
cooling trends in north-eastern Europe in May and July, where warming or no
trends are found within wet and average STs.</p>
      <p>Highest trend ratios for temperature are found within the groups of dry STs
(Fig. 7, rows 2 and 4). Covering south-western Europe in December, a belt of
high trend ratios extends to eastern Europe in February and then moves
northward, covering western to north-eastern and eastern Europe in April.
From July to November, higher ratios are again found in south-western
Europe, extending also to central and south-eastern Europe in August and
covering the west and north coast of Scandinavia in September. Negative
trend ratios are found within dry STs in Scandinavia in February, July and
November and locally in May and August.</p>
      <p>Within the groups of wet STs (Fig. 6, rows 2 and 4), negative trend ratios
are found in south-western Europe in January, eastern Europe in April and
August, south-eastern Europe in May and very locally otherwise. High
positive values are mostly found around the Baltic in December, May and
June, in south-eastern Europe in June and in northern and north-western
Europe in July and November.</p>
      <p>Within the groups of average STs, few negative temperature trend ratios are
found (see Supplement). The highest positive ratios occur in
central and parts of north-eastern Europe in January and April,
south-eastern Europe in May and eastern Europe in August.</p>
</sec>
</sec>
<sec id="Ch1.S5">
  <title>Discussion</title>
<sec id="Ch1.S5.SS1">
  <title>Attribution of trends: synoptic-circulation-induced versus
within-ST groups trends</title>
      <p>Trends in ST frequencies show that the STs, which are moist in the north and
dry in the south have become more frequent from January to March, whereas
the STs, which are moist in the south and dry in the north have become less
frequent. The studies of Paredes et al. (2006) and Hoy et al. (2014) support
these results. Comparing the two periods 1951–1980 and 1981–2010, Hoy et al. (2014)
found precipitation increases (decreases) during the winter half-year
in northern (southern) Europe to be correlated to increasing frequencies of
STs with westerly inflow over central Europe and decreasing frequencies of
easterly types. According to the authors, westerly (easterly) types are
predominantly wetter (drier) than normal in northern Europe and drier
(wetter) in the south. Similarly, Paredes et al. (2006), could explain
monthly precipitation changes (1941–1997) in Iberia specifically for the month
of March by decreasing frequencies of wet cyclonic types with respect to
Iberia and increasing frequencies of types which result in dry anticyclonic
conditions there. For the UK, they found the opposite, i.e. a decrease in
the frequency of dry anticyclonic types and an increase in the wet cyclonic
types. However, since the mid-1990s the frequencies of westerly types during
winter have slightly declined related to changes in the NAO (e.g. Hoy et
al., 2013a).</p>
      <p>As in our study, Hoy et al. (2013a) found generally less changes in
ST frequencies during the months of the summer half year as compared to
winter for the period 1901–2010. They found, however, an increase in
anticyclonic easterlies and decrease in westerlies during August. This is in
agreement with our results for August, which show an increase (decrease) in
wet (dry) STs in the north and a decrease (increase) in wet (dry) STs in the
south.</p>
      <p>In accordance with these changes in ST frequencies, we find that during our
study period a relatively high percentage of both precipitation and
temperature trends can be attributed to changes in the atmospheric
circulation (by the highest synoptic-circulation-induced trend ratios)
during January to March, as well as during the remaining months with strong
trends in the frequencies of wet and dry STs (i.e. in June, August, and
regionally in September, November and December).</p>
      <p>The trend patterns and trend ratio patterns often resemble the circular
shape of high- or low-pressure systems (e.g. patterns in January, February
and August). In particular, synoptic-circulation-induced temperature trends
often extend over larger areas, whereas synoptic-circulation-induced
precipitation trends and trend ratios are patchier. This is likely due to
the higher sensitivity to regional and local topography and the higher
spatial variability of precipitation compared to temperature. Furthermore,
the regions where the synoptic-circulation-induced trends in precipitation
and temperature are strongest do not necessarily coincide. On the contrary,
the strongest synoptic-circulation-induced temperature trends within a month
are often found in regions where synoptic-circulation-induced precipitation
trends are weakest, if they exist at all. This can be explained by the fact
that high precipitation amounts are typically found in regions with
low-pressure centres and their frontal systems and maritime air masses. The
largest deviations from the mean monthly temperature, on the other hand, are
more likely found in regions of high-pressure centres or high
pressure gradients, in particular when the air is coming from continental
areas or transported over large zonal distances. Hence, with changes in
circulation, i.e. in the location of high- and low-pressure systems and thus
in the frequencies of STs, the regions where the effects on the local
climate are strongest will also vary between precipitation and temperature.</p>
      <p>The regional patterns in June, August, September and November, notable for
precipitation, differ considerably from the previous months with strong
trends (i.e. January–March). In the winter months, i.e. January and February,
synoptic circulation changes imply increasing precipitation trends in
northern Europe associated with warming trends there. During the same
months, the decreasing synoptic-circulation-induced precipitation trends in
the south are mostly associated with no or decreasing temperature trends,
with the exception of Iberia in February, where decreasing precipitation
trends are accompanied by increasing temperature trends. During the summer
months, on the other hand, synoptic-circulation-induced precipitation
increases (decreases) are associated with cooling (warming) or no trends
throughout Europe. Overall, the relative importance of synoptic circulation changes appears to be slightly higher for precipitation than for temperature
trends. Regionally low or negative synoptic-circulation-induced trend ratios
similarly show the importance of within-type changes in particular for
temperature trends even during the months with strong synoptic circulation changes. For instance, in south-eastern Europe in January, the influence of
synoptic circulation changes on temperature is low, whereas it is high in
many other parts of Europe and for precipitation also in the south-east.</p>
      <p>Within-ST-group trend ratios for precipitation are mostly lower for dry STs
as compared to wet STs. Both dry STs as well as wet STs get wetter in some
regions and drier in others. For instance in February, wet STs get wetter in
central Europe and drier in the south, whereas dry STs get drier in the east
and wetter in the north-west. It has to be remembered that this applies to
the sets of STs, which are locally defined as wet or dry.</p>
      <p>Significant warming trends are found at least locally during all months
within both dry as well as wet STs. Fewest warming trends within ST groups
are found in October. Trend ratios show that higher proportions of
temperature trends can be attributed to warming within dry STs as opposed to
wet STs. Most notable is the warming within dry STs in southern Europe. The
fact that in particular dry STs get warmer in southern Europe may be related
to land-surface feedbacks; more frequent dry STs in southern Europe (January–March)
may lead to drier soils and the radiative energy, which cannot be used
anymore to evaporate water from the land surface, causes increasing
temperatures (Zampieri et al., 2009). Wet STs in northern Europe, on the
other hand, might get wetter in response to increased evaporation with
increasing temperature.</p>
      <p>Overall, somewhat higher proportions of precipitation and temperature trends
can be attributed to synoptic circulation changes in northern Europe as
compared to southern Europe. The only exception is the month of August, when
synoptic circulation changes have the strongest influence on temperature and
precipitation trends in central Europe. This north–south divide in the
role of synoptic circulation changes on local climate can be related to a
dominance of frontal (compared to local convective) precipitation that is
generally more frequent in northern and western Europe than in southern and
eastern Europe (Trenberth et al., 2003). The high importance of
synoptic circulation changes for precipitation trends in central Europe
during August is in this respect interesting, as normally the proportion of
convective precipitation compared to frontal precipitation would be higher
during summer. Thus, one could expect precipitation to be less sensitive to
circulation changes. The fact that these synoptic circulation changes occur
at the end of the summer season may suggest a memory effect in the system,
such as low soil moisture content or high sea-surface temperatures. By the
end of the summer, these conditions may have become strong enough to force
circulation changes. To test this hypothesis, a trend analysis on the
monthly frequencies of anticyclonic and cyclonic STs was performed, and
indeed, a strong increasing trend in anticyclonic circulation occurrence
over central Europe in August was found (not shown). This is in agreement
with, for instance, the results of Hoy et al. (2013a), who also found
increasing frequencies of anticyclonic circulation over central Europe in
summer (mid-July to mid-August) during the 20th century (1901–2010)
when studying changes in ST frequencies using a 31-day moving window.
Anticyclonic circulation may be caused by land surface feedbacks to the
atmosphere during dry and warm summers (Zampieri et al., 2009).</p>
      <p>Further work should investigate to what extent these circulation changes in
August are indeed feedbacks related to the general warming in Europe in
spring and summer and, in particular, to the drying within dry STs in
southern Europe. In addition, the wetting and cooling trends in June,
associated with both synoptic circulation changes as well as within-type
changes, could be related to local or more remote feedback processes, such
as changes in snow cover, sea surface temperatures or sea ice, and should be
investigated further. Matsumura et al. (2010) and Matsumura and Yamazaki (2012),
for instance, found that reduced springtime snow cover in northern
Eurasia affects atmospheric circulation in summer leading to precipitation
anomalies over northern Eurasia. On longer timescales, vegetation
changes may also play a role. According to Liess et al. (2012), a reduction in
albedo due to the expansion of the boreal forest may lead to a local increase in
net radiation and a warming of the northern hemisphere during June. The
associated changes in the meridional temperature gradient may enhance the
Arctic frontal zone, strengthen the summer jet and cause a shift in the
position of the storm tracks, which might result in changes in temperature
and precipitation regimes.</p>
</sec>
<sec id="Ch1.S5.SS2">
  <title>Uncertainty</title>
      <p>Trend ratios as well as the comparison between dry/wet ST frequencies and
climate variables suggest that the relative importance of
synoptic circulation changes on precipitation and temperature trends varies
among regions and months. However, some uncertainty issues should be
discussed. The mean precipitation fields associated with one ST can differ
in strength and exact location, so that the representativeness of the
defined wet/dry STs may vary slightly among months. This could in particular
affect transition months between winter and summer conditions in spring and
autumn. Furthermore, simultaneous changes in ST frequencies and within-type
changes may have opposite effects on climate variables, which may disguise
their real influence on precipitation (or temperature) in the trend ratios,
in particular in regions where the resulting precipitation or temperature
changes are non-significant. Still, it can be seen from the ST-frequency
trends that synoptic circulation changes are most important during late
winter (January–March), June and August, whereas there are small changes in
synoptic circulation in late spring (April–May), July and autumn,
particularly October. However, it is important to recall that the monthly
synoptic-circulation-induced trends (used in the trend ratios) and the
definition of wet/dry STs differ in their averaging period.
Synoptic-circulation-induced trends consider the long-term mean
precipitation values of an ST for each calendar month separately, whereas
wet/dry STs are defined based on the annual mean precipitation of each ST.</p>
      <p>The use of a monthly time resolution implies a higher risk of noise in the
results compared to e.g. seasonal studies. On the other hand, the higher
resolution shows that the sub-seasonal variability is important to consider
and that monthly differences do not necessarily follow the traditional
division into four seasons. Both months and seasons are arbitrary fixed
periods and do not necessarily capture the strongest signals occurring at
the respective resolution. As such, also differences in trend patterns
between consecutive months will be influenced by the temporal resolution and
fixed periods chosen. Future studies could consider for instance a 3-month
or 31-day moving average window as an alternative to fixed seasons or months
to better account for the gradual transitions within the annual cycle.</p>
      <p>Linear trends depend strongly on study period and method. This influences
also the synoptic-circulation-induced and within-ST-group trends. Therefore,
the proportions of circulation versus within-type changes on precipitation
and temperature trends cannot be seen as absolute and stationary magnitudes.
Non-stationarities in the proportions of circulation versus within-type
changes on European precipitation and temperature trends have previously
been found by Küttel et al. (2011) using seasonal atmospheric data for
the winter season. Strong regional patterns in trends and trend ratios, on
the other hand, give trust in the overall results for the considered study
period.</p>
</sec>
</sec>
<sec id="Ch1.S6" sec-type="conclusions">
  <title>Conclusions</title>
      <p>This study aimed to attribute observed climatological trends in Europe to
changes in the atmospheric circulation and in the hydrothermal properties of
synoptic types, as a first step towards a better understanding of monthly
varying patterns in streamflow trends in Europe. The relative importance of
frequency changes in STs as opposed to within-type changes in the
hydrothermal properties on precipitation and temperature trends was
analysed, as well as the overall changes in the groups of STs, which are
locally associated with wet and dry precipitation anomalies. Our results
support previous studies in that both frequency changes in the occurrence of
STs and within-type changes play an important role in controlling trends in
precipitation and temperature, and that the relative proportions vary within
the year and among regions. The importance of frequency changes is higher in
winter, whereas within-type changes are dominating in the summer, except for
August. The results further show the added value of studying trends over
larger spatial areas to identify regional patterns and that the monthly time
resolution reveals important within-year variability. Within the study
period, the strongest influence of synoptic circulation changes on both
precipitation and temperature occur from January to March, in June and in
August, and they are in general stronger in north-western Europe than in the
south-east. The exact locations of the areas with highest influence of
synoptic circulation changes differ, however, between precipitation and
temperature.</p>
      <p>The study shows that changes in the hydroclimatological system show a clear
seasonal pattern. The temporal variability in the large-scale patterns found
in trends of STs and their hydrothermal properties can, through their
combined effect on precipitation and temperature, explain monthly variations
in streamflow trend patterns as reported in previous studies by Stahl
et al. (2010, 2012). For instance, during late winter and early spring,
synoptic circulation changes dominate and STs, which are moist and warm in
northern Europe and dry in southern Europe, have become more frequent during
the study period (1963–2001). Stahl et al. (2010, 2012) accordingly found
increasing streamflow trends in northern Europe and decreasing trends in the
south. At the same time these STs, which are dry in the south, have become
warmer there, which may possibly be related to drier soils and subsequent
land-surface feedbacks. The warming within STs affects most of Europe during
March and/or April. Together with rather small precipitation changes during April
and May, this may account for decreasing streamflow trends first in southern
and eastern Europe and then later in large parts of Europe in May. By the
end of the summer, the drying and warming of the land surface may be
significant enough to cause the synoptic circulation changes found in August
with more frequent anticyclonic STs over central Europe. This again favours
drier and warmer conditions as reflected in widespread decreasing streamflow
trends. Synoptic-circulation-induced precipitation increase in north-eastern
Europe in June may explain increases streamflow trends there in June in
July.</p>
      <p>Considering the non-stationarities in the hydrothermal properties of STs as
well as the varying importance of circulation change and within-type changes
throughout the year and among regions, is a topic for further studies
linking streamflow characteristics to STs. As the relative importance of
within-type changes and circulation changes is not stationary, further
investigation of the processes controlling the within-type changes in the
hydrothermal properties of the synoptic types, is an important research
task. In addition, possible local and remote feedback processes and the
influence on the regional climate should be considered.</p>
</sec>

      
      </body>
    <back><app-group>
        <supplementary-material position="anchor"><p><bold>The Supplement related to this article is available online at <inline-supplementary-material xlink:href="http://dx.doi.org/10.5194/hess-19-3093-2015-supplement" xlink:title="pdf">doi:10.5194/hess-19-3093-2015-supplement</inline-supplementary-material>.</bold></p></supplementary-material>
        </app-group><ack><title>Acknowledgements</title><p>L. M. Tallaksen and K. Stahl acknowledge funding from the EU FP7 project
DROUGHT-R&amp;SPI (contract no. 282769).<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: H. Cloke</p></ack><ref-list>
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