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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Earth Sci.</journal-id>
<journal-title>Frontiers in Earth Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Earth Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-6463</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">771362</article-id>
<article-id pub-id-type="doi">10.3389/feart.2022.771362</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Earth Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Different Seasonal Precipitation Anomaly Patterns in Central Asia Associated With Two Types of El Ni&#xf1;o During 1891&#x2013;2016</article-title>
<alt-title alt-title-type="left-running-head">Feng et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">Different Seasonal Precipitation Anomaly Patterns</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Feng</surname>
<given-names>Fan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1330521/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Yong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1236120/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Anning</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1064936/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Yang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1657118/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhou</surname>
<given-names>Xin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/960880/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>School of Atmospheric Sciences, Chengdu University of Information Technology</institution>, <addr-line>Chengdu</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Plateau Atmosphere and Environment Key Laboratory of Sichuan Province</institution>, <institution>Chengdu University of Information Technology</institution>, <addr-line>Chengdu</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>School of Atmospheric Sciences</institution>, <institution>Nanjing University</institution>, <addr-line>Nanjing</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1067362/overview">Shangfeng Chen</ext-link>, Institute of Atmospheric Physics (CAS), China</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/989044/overview">Ming Luo</ext-link>, Sun Yat-sen University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1467977/overview">Jiepeng Chen</ext-link>, South China Sea Institute of Oceanology (CAS), China</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Fan Feng, <email>fengfan@cuit.edu.cn</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Interdisciplinary Climate Studies, a section of the journal Frontiers in Earth Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>25</day>
<month>02</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>771362</elocation-id>
<history>
<date date-type="received">
<day>06</day>
<month>09</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>03</day>
<month>02</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Feng, Zhao, Huang, Li and Zhou.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Feng, Zhao, Huang, Li and Zhou</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these&#x20;terms.</p>
</license>
</permissions>
<abstract>
<p>In this study, we examine the different seasonal precipitation anomaly patterns in Central Asia associated with the cold-tongue (CT) El Ni&#xf1;o and warm-pool (WP) El Ni&#xf1;o from the El Ni&#xf1;o developing autumn to the decaying spring based on the Global Precipitation Climatology Centre (GPCC) full data reanalysis version 2018 (GPCC V2018) data set. Overall, El Ni&#xf1;o are associated with more precipitations over Central Asia, but significant discrepancies can be found in the precipitation anomaly spatial patterns associated with the two types of El Ni&#xf1;o from the El Ni&#xf1;o developing autumn to the decaying spring. The precipitation associated with CT El Ni&#xf1;o is mostly concentrated in the plains and hilly areas of Central Asia and is more dispersed in space. Whereas the precipitation associated with WP El Ni&#xf1;o is mostly concentrated along Pamirs and Tian Shan Mountains with consistency throughout the autumn before El Ni&#xf1;o peaks to the spring when El Ni&#xf1;o decays. Also, the strength of the positive precipitation anomaly associated with WP El Ni&#xf1;o is significantly stronger than that of CT El Ni&#xf1;o. The analysis of anomalous atmospheric circulation caused by two types of El Ni&#xf1;o shows that the interconfiguration of anomalous high pressure in the south side of Central Asia at low and middle latitudes and anomalous low pressure and anomalous high pressure in the high latitudes of Eurasia affects the southwest water vapor flux and north side water vapor flux in Central Asia, thus causing different effects of different types of El Ni&#xf1;o on precipitation in Central Asia at different stages. The spatial consistency of the WP El Ni&#xf1;o effect on precipitation in Central Asia over three seasons may be related to the upward branch of the anomalous Walker circulation over the Indian Ocean induced by&#x20;it.</p>
</abstract>
<kwd-group>
<kwd>Central Asia</kwd>
<kwd>semi-arid to arid area</kwd>
<kwd>seasonal precipitation</kwd>
<kwd>two types of El Ni&#xf1;o</kwd>
<kwd>partial correlation</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>El Ni&#xf1;o-Southern Oscillation (ENSO) is the most important interannual signal of climate variability on earth. It influences the world climate through the ocean-atmospheric coupling process globally. Canonical El Ni&#xf1;o is characterized with maximum warm sea surface temperature (SST) anomalies in the eastern equatorial Pacific. However, since the 1990s, a new type of El Ni&#xf1;o has begun to occur frequently with the largest SST warm anomaly located in the central equatorial Pacific. It is often referred to as Dateline El Ni&#xf1;o (<xref ref-type="bibr" rid="B21">Larkin and Harrison, 2005</xref>), El Ni&#xf1;o Modoki <xref ref-type="bibr" rid="B1">Ashok et&#x20;al. (2007)</xref>, <xref ref-type="bibr" rid="B39">Weng et&#x20;al. (2007)</xref>, <xref ref-type="bibr" rid="B40">Weng et&#x20;al. (2009)</xref>, central Pacific (CP) El Ni&#xf1;o (Kao and Yu, 2009), and warm pool (WP) El Ni&#xf1;o (<xref ref-type="bibr" rid="B20">Kug et&#x20;al., 2009</xref>). Furthermore, it was recently shown that this new type of El Ni&#xf1;o may become even more frequent under global warming scenarios (<xref ref-type="bibr" rid="B41">Yeh et&#x20;al., 2009</xref>). In this study, this new type of El Ni&#xf1;o and the canonical El Ni&#xf1;o are referred to as warm pool (WP) El Ni&#xf1;o and cold tongue (CT) El Ni&#xf1;o, respectively.</p>
<p>Previous studies have discussed the different impacts of the two types of El Ni&#xf1;o on Atlantic hurricane frequency (<xref ref-type="bibr" rid="B19">Kim et&#x20;al., 2009</xref>), western North Pacific tropical cyclone frequency (<xref ref-type="bibr" rid="B5">Chen and Tam, 2010</xref>), precipitation patterns over the western United&#x20;States during boreal winter (<xref ref-type="bibr" rid="B40">Weng et&#x20;al., 2009</xref>), winter climate extremes over the eastern and central United&#x20;States (<xref ref-type="bibr" rid="B25">Ning and Bradley, 2015</xref>) and the austral spring and autumn rainfall in Australia (<xref ref-type="bibr" rid="B37">Wang and Hendon 2007</xref>; <xref ref-type="bibr" rid="B32">Taschetto and England 2009</xref>). Recently, their impacts on the variations of precipitation and temperature over East and Southeast Asia, the summer rainfall anomaly patterns in northeast China and the summer heat extremes in China have also been investigated in many studies (<xref ref-type="bibr" rid="B38">Weng et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B8">Feng et&#x20;al., 2011</xref>, <xref ref-type="bibr" rid="B7">Feng and Li, 2011</xref>; <xref ref-type="bibr" rid="B42">Yuan and Yang 2012</xref>; <xref ref-type="bibr" rid="B22">Luo and Lau 2020</xref>; <xref ref-type="bibr" rid="B9">Gao et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B44">Qin and Shuang-lin, 2009</xref>).</p>
<p>As one of the largest semi-arid to arid regions, Central Asia is located in the hintland of Eurasia, acting as a bond of cultural and economic communication between Europe and Asia. Central Asia expands from 34.3&#x00B0;to 55.4&#x00B0;N and from 46.5&#x00B0;to 96.4&#x00B0;E geographically and encompasses five countries: Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan (hereafter &#x2018;CAS5&#x2019;), and Xinjiang Uygur Autonomous Region of China. This region is characterized by typical continental climate with an annual total precipitation less than 300&#xa0;mm, implying a fragile ecosystem that is highly vulnerable to climate change (<xref ref-type="bibr" rid="B16">IPCC 2013</xref>; <xref ref-type="bibr" rid="B13">Huang et&#x20;al., 2016</xref>, <xref ref-type="bibr" rid="B14">Huang J.&#x20;et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B12">Hu et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B26">Peng et&#x20;al., 2020a</xref>, <xref ref-type="bibr" rid="B27">Peng et&#x20;al., 2020b</xref>). Thus, changes in precipitation have a great impact on people&#x2019;s living condition and ecosystem in Central Asia. Many studies of the precipitation in Central Asia focus on changes of precipitation under global warming (<xref ref-type="bibr" rid="B4">Chen et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B12">Hu et&#x20;al., 2017</xref>), under CMIP6 future projections (<xref ref-type="bibr" rid="B17">Jiang et&#x20;al., 2020</xref>) and the impacts of SST warming in the tropical Indian Ocean on the projected change in summer rainfall over Central Asia (<xref ref-type="bibr" rid="B43">Zhao and Zhang 2016</xref>). Some previous studies have documented the linkage between ENSO and the hydroclimatic variability of the southwest central Asia region (<xref ref-type="bibr" rid="B23">Mariotti, 2007</xref>). And the relationship between the changes of the seasonal precipitation over Central Asia and ENSO over the last century have be investigated recently (<xref ref-type="bibr" rid="B6">Chen et&#x20;al., 2018</xref>). However, there are significant differences in the anomalous Walker circulation caused by the two types of El Ni&#xf1;o, and there are also differences in the mid- and high-latitude teleconnection types caused, so are there also differences in the effects of the two types of El Ni&#xf1;o on precipitation in Central Asia? In addition, previous studies have shown seasonal differences in the impact of ENSO on precipitation in Central Asia (<xref ref-type="bibr" rid="B6">Chen et&#x20;al., 2018</xref>), so what is the impact of the two types of El Ni&#xf1;o on precipitation in Central Asia at different stages of their lifetime? And what are the possible physical mechanisms behind this? These are the questions that this study intends to answer.</p>
<p>The remainder of the study is organized as follows. In <italic>Section Data and Methods</italic>, we introduce the datasets and analysis methods applied in this study. In <italic>Section Results</italic>, we compare the different seasonal precipitation anomaly patterns in Central Asia associated with the two types of El Ni&#xf1;o from the El Ni&#xf1;o developing autumn to the decaying spring and possible physical mechanisms responsible for these features are investigated. <italic>Section Summary and Discussion</italic> gives a brief summary of the&#x20;study.</p>
</sec>
<sec id="s2">
<title>Data and Methods</title>
<p>The latest version of Global Precipitation Climatology Centre (GPCC) full data reanalysis version 2018 (GPCC full V2018) dataset (<xref ref-type="bibr" rid="B30">Schneider et&#x20;al., 2018</xref>) with a spatial resolution of 1.0&#xb0;&#xd7;1.0&#xb0; is used in this study. This gridded dataset is based on 75,000 meteorological stations world-wide with record durations of 10&#xa0;years or longer. It has been widely used to support regional climate monitoring, model validation, climate variability analysis, and water resources assessment studies because of its high-quality control (<xref ref-type="bibr" rid="B2">Becker et&#x20;al., 2013</xref>; <xref ref-type="bibr" rid="B34">Wan et&#x20;al., 2013</xref>; <xref ref-type="bibr" rid="B31">Schneider et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B10">Gu and Adler, 2015</xref>). In addition, <xref ref-type="bibr" rid="B12">Hu et&#x20;al. (2017)</xref> suggested that GPCC V7 has the higher accuracy than Climatic Research Unit (CRU) products and the data sets developed by Willmott and Matsuura from the University of Delaware (UDEL) when compared with the observed precipitation data from meteorological stations over Central Asia. Monthly SST data from the Hadley Centre Global Sea Ice and Sea Surface Temperature (<xref ref-type="bibr" rid="B28">Rayner et&#x20;al., 2003</xref>) and monthly atmospheric reanalysis data sets NCEP/NCAR Reanalysis 1 from January 1948 to December 2020 (<xref ref-type="bibr" rid="B18">Kalnay et&#x20;al., 1996</xref>) are also used in this&#x20;study.</p>
<p>For the GPCC precipitation dataset and the HadISST, the temporal coverage we used in this study is from January 1891 to December 2016 for data consistency and reliability; and for reanalysis we used data from January 1948 to December 2020. Anomalies of all variables are obtained by removing the annual mean of the whole period accordingly. Seasonal means are constructed by averaging data from March&#x2013;May (MAM), September&#x2013;November (SON), and December&#x2013;February (DJF).</p>
<p>In order to describe the two types of El Ni&#xf1;o quantitatively, the CT and WP ENSO indices proposed by <xref ref-type="bibr" rid="B45">Ren and Jin (2011)</xref> are used in this study. These indices are defined as follows:<disp-formula id="equ1">
<mml:math id="m1">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
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<mml:mi mathvariant="bold-italic">N</mml:mi>
<mml:mrow>
<mml:mi mathvariant="bold-italic">CT</mml:mi>
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<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
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<mml:mo>&#x2212;</mml:mo>
<mml:mi>&#x3b1;</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
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</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
<mml:mrow>
<mml:mi mathvariant="bold-italic">WP</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>&#x3b1;</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
</mml:mrow>
</mml:mtd>
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</mml:mrow>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">&#x3b1;</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="bold-italic">&#x3b1;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi mathvariant="bold-italic">N</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
<mml:mo>&#x3e;</mml:mo>
<mml:mn>0</mml:mn>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mn>0</mml:mn>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mi mathvariant="bold-italic">o</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
<mml:mi mathvariant="bold-italic">h</mml:mi>
<mml:mi mathvariant="bold-italic">e</mml:mi>
<mml:mi mathvariant="bold-italic">r</mml:mi>
<mml:mi mathvariant="bold-italic">w</mml:mi>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">s</mml:mi>
<mml:mi mathvariant="bold-italic">e</mml:mi>
<mml:mo>.</mml:mo>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
</p>
<p>Here, <inline-formula id="inf1">
<mml:math id="m2">
<mml:mrow>
<mml:msub>
<mml:mi>N</mml:mi>
<mml:mn>3</mml:mn>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf2">
<mml:math id="m3">
<mml:mrow>
<mml:msub>
<mml:mi>N</mml:mi>
<mml:mn>4</mml:mn>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> denote Ni&#xf1;o3 and Ni&#xf1;o4 indices, respectively. And <inline-formula id="inf3">
<mml:math id="m4">
<mml:mrow>
<mml:msub>
<mml:mi>N</mml:mi>
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>T</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf4">
<mml:math id="m5">
<mml:mrow>
<mml:msub>
<mml:mi>N</mml:mi>
<mml:mrow>
<mml:mi>W</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are the newly defined WP and CT ENSO indices. The parameter <inline-formula id="inf5">
<mml:math id="m6">
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b1;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is determined by a minimization procedure to make the cluster centers of the two types of El Ni&#xf1;o indicated by the Ni&#xf1;o indices away from the diagonal as far as possible [For detailed information, refer to <xref ref-type="bibr" rid="B45">Ren and Jin (2011)</xref>]. In this study, we use <inline-formula id="inf6">
<mml:math id="m7">
<mml:mrow>
<mml:msub>
<mml:mi>&#x3b1;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:mn>2</mml:mn>
<mml:mo>/</mml:mo>
<mml:mn>5</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> as the authors did in the original paper. Unlike the Ni&#xf1;o 3 and Ni&#xf1;o 4 indices, the CT and WP ENSO indices are of little simultaneous correlation. The SST patterns associated with these two new indices capture different characteristics of the phase propagations of the two types of El Ni&#xf1;o. <xref ref-type="table" rid="T1">Table&#x20;1</xref> shows the correlations between the Ni&#xf1;o indices, the CT and WP ENSO indices and the El Ni&#xf1;o Modoki index (EMI). The CT ENSO index and WP ENSO index are significantly correlated with the Ni&#xf1;o 3 (<italic>R</italic>&#x20;&#x3d; 0.98) and Ni&#xf1;o 4 indices (<italic>R</italic>&#x20;&#x3d; 0.86) respectively, but unlike the Ni&#xf1;o indices (<italic>R</italic>&#x20;&#x3d; 0.77), they are almost unrelated with each other simultaneously (<italic>R</italic>&#x20;&#x3d; 0.17). Meanwhile, the WP ENSO index is also highly correlated with EMI (<italic>R</italic>&#x20;&#x3d;&#x20;0.87).</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Correlations between the Ni&#xf1;o indices, the CT and WP ENSO indices and EMI calculated using the monthly HadISST. Correlation coefficients are all statistically significant at the confidence levels of&#x20;99%.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left"/>
<th align="center">Ni&#xf1;o 3 index</th>
<th align="center">Ni&#xf1;o 4 index</th>
<th align="center">CT ENSO index</th>
<th align="center">WP ENSO index</th>
<th align="center">EMI</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Ni&#xf1;o 3 Index</td>
<td align="char" char=".">1</td>
<td align="char" char=".">0.77</td>
<td align="char" char=".">0.98</td>
<td align="char" char=".">0.36</td>
<td align="char" char=".">0.22</td>
</tr>
<tr>
<td align="left">Ni&#xf1;o 4 Index</td>
<td align="char" char=".">0.77</td>
<td align="char" char=".">1</td>
<td align="char" char=".">0.63</td>
<td align="char" char=".">0.86</td>
<td align="char" char=".">0.72</td>
</tr>
<tr>
<td align="left">CT ENSO index</td>
<td align="char" char=".">0.98</td>
<td align="char" char=".">0.63</td>
<td align="char" char=".">1</td>
<td align="char" char=".">0.17</td>
<td align="char" char=".">0.05</td>
</tr>
<tr>
<td align="left">WP ENSO index</td>
<td align="char" char=".">0.36</td>
<td align="char" char=".">0.86</td>
<td align="char" char=".">0.17</td>
<td align="char" char=".">1</td>
<td align="char" char=".">0.87</td>
</tr>
<tr>
<td align="left">EMI</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">0.72</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">0.87</td>
<td align="char" char=".">1</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>To investigate the possible impacts of CT and WP El Ni&#xf1;o on the seasonal precipitation in Central Asia, composite analyses are conducted, and lag correlations are calculated between the normalized DJF CT and WP ENSO indices and other physical variables from El Ni&#xf1;o developing autumn to the decaying spring. Although the correlation between monthly CT and WP ENSO indices is weak (<italic>R</italic>&#x20;&#x3d; 0.17), the correlation coefficient between them in the mature phase (boreal winter DJF) of El Ni&#xf1;o is higher (<italic>R</italic>&#x20;&#x3d; 0.35) which is significant for the sample size of <italic>n</italic>&#x20;&#x3d; 66&#xa0;at the confidence levels of 99%. Therefore, partial correlations<disp-formula id="equ2">
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</mml:msub>
<mml:mo>&#x3d;</mml:mo>
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</mml:mrow>
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<mml:mrow>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
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<mml:msubsup>
<mml:mi mathvariant="bold-italic">r</mml:mi>
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</mml:mrow>
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</disp-formula>are considered throughout this study to exclude the possible influence dominated by any particular event (<xref ref-type="bibr" rid="B29">Sankar-Rao et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B3">Behera and Yamagata 2003</xref>). All statistical significance tests for correlations are performed using the two-tailed Student&#x2019;s <italic>t</italic>&#x20;test. The degrees of freedom (dof) are 64 for a time series of 66-season long (1951&#x2013;2016) and 71 for a time series of 73-season long (1948&#x2013;2020). The correlation coefficients at the confidence level of 95% (90%) are 0.24 (0.20) for dof &#x3d; 64 and 0.23 (0.19) for dof &#x3d;&#x20;71.</p>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>Precipitation Anomaly Patterns Associated With Two Types of El Ni&#xf1;o</title>
<p>
<xref ref-type="fig" rid="F1">Figure&#x20;1</xref> shows the partial correlations between seasonal SST anomalies and normalized DJF CT ENSO index (left panel) and WP ENSO index (right panel) from El Ni&#xf1;o developing summer (JJA0) to the decaying summer (JJA1), respectively. For the CT El Ni&#xf1;o, significant warming is always concentrated along the equatorial eastern Pacific from the developing summer to the decaying summer. The warming patterns extend from the west coast of the Americas up to the dateline with warming centers located at the equatorial eastern Pacific. Meanwhile, negative SST anomalies develop in the western Pacific to the east of the Philippines and extend both northeastward and southeastward (<xref ref-type="fig" rid="F1">Figures 1A&#x2013;E</xref>) forming a cold &#x2018;&#x2018;boomerang&#x2019;&#x2019; (<xref ref-type="bibr" rid="B33">Trenberth and Stepaniak 2001</xref>). The CT El Ni&#xf1;o is characterized by such a dipole SSTA pattern over the tropical Pacific throughout its life cycle. As for the WP El Ni&#xf1;o, the center of the warming SSTA pattern is located persistently at the equatorial central Pacific from the developing to the decaying phase, with a weak cold SSTA to the equatorial eastern Pacific around 90W (<xref ref-type="fig" rid="F1">Figures 1F&#x2013;J</xref>). On the other hand, the cold &#x2018;&#x2018;boomerang&#x2019;&#x2019; SSTA pattern is less significant than that of the CT El Ni&#xf1;o. This triple pattern along the tropical Pacific denotes a WP El Ni&#xf1;o. Overall, the CT and WP ENSO indices are capable of capturing the SSTA progression patterns for the two types of El Ni&#xf1;o events.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Partial correlations (shading) of seasonal SSTA with normalized DJF CT ENSO index <bold>(A&#x2013;E)</bold> and WP ENSO index <bold>(F&#x2013;J)</bold> for <bold>(A)</bold>, <bold>(F)</bold> JJA(0), <bold>(B,G)</bold> SON(0), <bold>(C,H)</bold> DJF(0), <bold>(D,I)</bold> MAM(1), and <bold>(E,J)</bold> JJA(1) in which 0 means the El Ni&#xf1;o developing year, 1 the next year. Correlation coefficients significant above the 95% confidence levels are marked with dots.</p>
</caption>
<graphic xlink:href="feart-10-771362-g001.tif"/>
</fig>
<p>
<xref ref-type="bibr" rid="B6">Chen et&#x20;al. (2018)</xref> concluded that ENSO has significantly positive impact on the precipitation of Central Asia in during 1951&#x2013;2013. Further, we found differences in the spatial patterns and intensity of the effects of the two types of El Ni&#xf1;o on monthly precipitation in Central Asia. <xref ref-type="fig" rid="F2">Figure&#x20;2</xref> shows the regression coefficients of the monthly precipitation anomalies averaged through SON0 to MAM1 in Central Asia on the Ni&#xf1;o3.4 index (<xref ref-type="fig" rid="F2">Figure&#x20;2A</xref>), CT ENSO index (<xref ref-type="fig" rid="F2">Figure&#x20;2B</xref>), and WP ENSO index (<xref ref-type="fig" rid="F2">Figure&#x20;2C</xref>) during 1891&#x2013;2016, respectively. Note that only regression coefficients that passed the 95% significance test are shown in these figures. It is shown that there are significant differences in the impact of the two types of El Ni&#xf1;o on precipitation in Central Asia. The positive precipitation anomalies associated with CT El Ni&#xf1;o are mainly located in the western Pamir Plateau (magnitudes about 2&#x2013;4&#xa0;mm/&#xb0;C), with no significant impact on most of the rest parts of Central Asia (<xref ref-type="fig" rid="F2">Figure&#x20;2B</xref>). In contrast, the positive precipitation anomalies associated with WP El Ni&#xf1;o cover most of Central Asia except Xinjiang, China. The positive precipitation anomaly has a maximum center on the Pamir Plateau and in the Tian Shan Mountains, with magnitude of 10&#x2013;12&#xa0;mm/&#xb0;C. In the hills, plains and desert areas of central and western Central Asia, the magnitude of the positive precipitation anomaly is about 2&#x2013;4&#xa0;mm/&#xb0;C (<xref ref-type="fig" rid="F2">Figure&#x20;2C</xref>). When the two types of El Ni&#xf1;o events are considered together, the positive precipitation anomalies associated with the Ni&#xf1;o3.4 index are found in the Pamir Plateau and Tian Shan Mountains regions (<xref ref-type="fig" rid="F2">Figure&#x20;2A</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Regression coefficients of the monthly precipitation anomalies averaged through SON0 to MAM1 in Central Asia on the <bold>(A)</bold> Ni&#xf1;o3.4 index, <bold>(B)</bold> CT ENSO index, and <bold>(C)</bold>WP ENSO index during 1891&#x2013;2016. Shades indicate regression coefficients with significance above the 95% confidence levels.</p>
</caption>
<graphic xlink:href="feart-10-771362-g002.tif"/>
</fig>
<p>Moreover, we further explore the seasonal precipitation anomalies patterns associated with the two types of El Ni&#xf1;o during their life cycle. <xref ref-type="bibr" rid="B6">Chen et&#x20;al. (2018)</xref> found that ENSO has the largest impact on the precipitation in Central Asia in boreal winter, followed by spring and autumn and there is no significant correlation between ENSO and the summer precipitation. Therefore, we mainly focus on the precipitation anomalies in the autumn before the El Ni&#xf1;o peaks (SON0), the El Ni&#xf1;o peaking winter (DJF0), and the next spring (MAM1). Composite analyses are conducted here to illustrate these patterns. First, we define the two types of El Ni&#xf1;o events according to Ren and Jin (2011), that is, when the WP (CT) index is positive greater than one standard deviation of its own, then the warm SST anomaly is regarded as a WP (CT) El Ni&#xf1;o state. Based on this criterion, the two types of El Ni&#xf1;o events that were determined using detrended monthly HadISST from 1891-2020 are as follows:<list list-type="bullet">
<list-item>
<p>CT El Ni&#xf1;o: 1896, 1899, 1902, 1905, 1911, 1913, 1918, 1925, 1930, 1940, 1941, 1951, 1957, 1965, 1972, 1976, 1982, 1986, 1991, 1997, 2009,&#x20;2015</p>
</list-item>
<list-item>
<p>WP El Ni&#xf1;o: 1900, 1940, 1941, 1957, 1958, 1968, 1977, 1986, 1987, 1990, 1991, 1992, 1993, 1994, 2002, 2003, 2004, 2006, 2009, 2014,&#x20;2015</p>
</list-item>
</list>
</p>
<p>It can be seen that several events (1940, 1941, 1957, 1986, 1991, 2009, 2015) are defined as both CT and WP El Ni&#xf1;o events based on this determination criterion, which is due to the fact that these events show significant warming in both Ni&#xf1;o3 and Ni&#xf1;o4 regions and are basin-wide warm events. Therefore, some studies also refer to these events as &#x201c;strong basin-wide&#x201d; events and do not regard them as a regular CT or WP El Ni&#xf1;o (<xref ref-type="bibr" rid="B36">Wang et&#x20;al., 2019</xref>; <xref ref-type="bibr" rid="B35">Wang et&#x20;al., 2020</xref>). In following analyses, we still keep these events in their respective categories.</p>
<p>The composites of seasonal precipitation anomaly associated with the CT El Ni&#xf1;o (left panel) and WP El Ni&#xf1;o (right panel) years during 1891&#x2013;2020 from SON0 to MAM1 are shown in <xref ref-type="fig" rid="F3">Figure&#x20;3</xref>. Only anomalies that passed the 90% significance test are shown in these figures. Consistent with the result in <xref ref-type="fig" rid="F2">Figure&#x20;2</xref>, the impacts of WP El Ni&#xf1;o on precipitation anomalies in Central Asia is stronger than CT El Ni&#xf1;o in terms of intensity and spatial extent. In addition, there are prominent discrepancies between the precipitation anomalies associated with the CT and WP El Ni&#xf1;o during every stage of the El Ni&#xf1;o lifetime. In the CT El Ni&#xf1;o developing autumn, positive precipitation anomalies are found in the plains of southwestern Central Asia and the northwestern Pamir Plateau (<xref ref-type="fig" rid="F3">Figure&#x20;3A</xref>). In the following winter, as the El Ni&#xf1;o peaks, the distribution of positive precipitation anomalies shifts northward, with more scattered wet conditions occurring in Kazakhstan (<xref ref-type="fig" rid="F3">Figure&#x20;3B</xref>). In the El Ni&#xf1;o decaying spring, a continuous positive precipitation anomaly appears in the Kazakh Hills and northern Xinjiang along with more precipitation in the northwestern Pamir Plateau (<xref ref-type="fig" rid="F3">Figure&#x20;3C</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Composites of seasonal precipitation anomaly in Central Asia over all CT El Ni&#xf1;o years <bold>(A&#x2013;C)</bold> and WP El Ni&#xf1;o years <bold>(D&#x2013;F)</bold> during 1891&#x2013;2016 for SON0, DJF0 and MAM1. Shades indicate regions with significance above the 90% confidence levels.</p>
</caption>
<graphic xlink:href="feart-10-771362-g003.tif"/>
</fig>
<p>There are prominent discrepancies between the precipitation anomalies associated with the CT and WP El Ni&#xf1;o during every stage of the El Ni&#xf1;o lifetime. More precipitation appears in the Tian Shan Mountains and the Turan Plain in the WP El Ni&#xf1;o developing autumn (<xref ref-type="fig" rid="F3">Figure&#x20;3D</xref>). The positive precipitation anomalies in the mountainous region along Pamir Plateau and Tian Shan Mountains become conspicuous in the WP El Ni&#xf1;o peaking winter along with some relatively weak positive rainfall anomalies in Xinjiang and plains around the Aral Sea (<xref ref-type="fig" rid="F3">Figure&#x20;3E</xref>). In the following spring, the positive rainfall anomaly patterns are quite similar to that in the last winter with more precipitation in the mountainous region and a wider range of rainfall around the Aral Sea (<xref ref-type="fig" rid="F3">Figure&#x20;3F</xref>). We also investigate the partial correlations between seasonal precipitation anomalies in Central Asia and the normalized DJF CT/WP ENSO indices in the same three seasons. And the results from the partial correlation are compatible with the above composite analyses (Figures not shown). Only that the area where the partial correlation coefficient between the precipitation anomaly and the CT/WP ENSO indices can pass the 90% significance test that is broader than that of the composite analysis. This is related to the size of the samples for which significance tests were carried&#x20;out.</p>
<p>In summary, when comparing the precipitation anomalies in Central Asia associated with the CT and WP El Ni&#xf1;o, three conspicuous characteristics need to be emphasized. First, overall, El Ni&#xf1;o are associated with more precipitations over Central Asia in SON(0), DJF(0) and MAM(1) which is consistent with the findings of <xref ref-type="bibr" rid="B6">Chen et&#x20;al. (2018)</xref>, although the wet condition patterns are not consistent spatially and temporally. Second, the impacts of WP El Ni&#xf1;o on Central Asia precipitation are stronger, more extensive, and longer lasting than that of CT El Ni&#xf1;o. Third, the precipitation anomaly spatial patterns associated with the two types of El Ni&#xf1;o is different from the El Ni&#xf1;o developing autumn to the decaying spring. To be specific, the precipitation associated with CT El Ni&#xf1;o is mostly concentrated in the plains and hilly areas of Central Asia and is more dispersed in space. Whereas the precipitation associated with WP El Ni&#xf1;o is mostly concentrated in the mountainous areas of Central Asia. In its peaking winter and decaying spring, WP El Ni&#xf1;o also brings a small amount of precipitation to Xinjiang and the plains around the Aral&#x20;Sea.</p>
</sec>
<sec id="s3-2">
<title>Atmospheric Circulation Associated With Two Types of El Ni&#xf1;o Over Central Asia</title>
<p>The different impacts of CT and WP El Ni&#xf1;o on precipitation in Central Asia in time and space suggest that precipitation in Central Asia in different seasons may be controlled by different atmospheric circulations when the two types of ENSO occur. In this section, we explore the possible physical mechanisms for the above features of precipitation in Asia, based on composite analyses of the geopotential height (<xref ref-type="fig" rid="F4">Figures 4</xref>, <xref ref-type="fig" rid="F5">5</xref>) and wind field (<xref ref-type="fig" rid="F6">Figures 6</xref>, <xref ref-type="fig" rid="F7">7</xref>) of the lower and middle troposphere, the vertical integral of eastward and northward water vapor flux and the vertical integral of divergence of moisture flux (<xref ref-type="fig" rid="F8">Figure&#x20;8</xref>) using the NCEP/NCAR Reanalysis 1 data. Previous studies suggested that ENSO has strong influences on the south-westerly water vapor flux coming from the Arabian Sea and tropical Africa and northeastern water vapor flux from Russia and thus can cause precipitation anomalies over Central Asia (<xref ref-type="bibr" rid="B23">Mariotti, 2007</xref>; <xref ref-type="bibr" rid="B12">Hu et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B6">Chen et&#x20;al., 2018</xref>). In the following content, we focus on the difference between these two sources of water vapor flux in the developing, peaking, decaying season of two types of El Ni&#xf1;o.</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Composites of 700hPa geopotential height (hgt) anomalies in Central Asia over all CT El Ni&#xf1;o years <bold>(A&#x2013;C)</bold> and WP El Ni&#xf1;o years <bold>(D&#x2013;F)</bold> during 1948&#x2013;2020 for SON0, DJF0 and MAM1. Dots denote regions with significance above the 90% confidence levels.</p>
</caption>
<graphic xlink:href="feart-10-771362-g004.tif"/>
</fig>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Same as <xref ref-type="fig" rid="F4">Figure&#x20;4</xref>, but for 700 hPa anomalous wind field. Grey areas denote regions with significance above the 90% confidence levels.</p>
</caption>
<graphic xlink:href="feart-10-771362-g006.tif"/>
</fig>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption>
<p>Same as <xref ref-type="fig" rid="F4">Figure&#x20;4</xref>, but for 500&#xa0;hPa anomalous geopotential height.</p>
</caption>
<graphic xlink:href="feart-10-771362-g005.tif"/>
</fig>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption>
<p>Same as <xref ref-type="fig" rid="F6">Figure&#x20;6</xref>, but for 500&#xa0;hPa anomalous wind&#x20;field.</p>
</caption>
<graphic xlink:href="feart-10-771362-g007.tif"/>
</fig>
<fig id="F8" position="float">
<label>FIGURE 8</label>
<caption>
<p>Same as in <xref ref-type="fig" rid="F4">Figure&#x20;4</xref>, but for vertically integrated water vapor flux (integrated from 1000&#xa0;hPa to 300&#xa0;hPa) (vectors) and its divergence (shades).</p>
</caption>
<graphic xlink:href="feart-10-771362-g008.tif"/>
</fig>
<p>In the autumn before the CT El Ni&#xf1;o peaks, anomalous high pressure dominates most of the low latitudes south of 30&#xb0;N, and north of this anomalous high pressure there are two weaker low pressure centers located in the eastern Mediterranean and over the Caspian Sea, with a deeper trough near the Mediterranean Sea (<xref ref-type="fig" rid="F4">Figures 4A</xref>, <xref ref-type="fig" rid="F5">5A</xref>), such that the atmospheric circulation pattern enhances westerly winds (<xref ref-type="fig" rid="F6">Figures 6A</xref>, <xref ref-type="fig" rid="F7">7A</xref>) and facilitates the transport of water vapor from the Mediterranean and Arabian Sea to the Central Asian region (<xref ref-type="fig" rid="F8">Figure&#x20;8A</xref>); while in Central Asia a weak high-pressure anomaly exists in northeastern Central Asia, which cooperates with the low-pressure center over the Caspian Sea (<xref ref-type="fig" rid="F4">Figures 4A</xref>, <xref ref-type="fig" rid="F5">5A</xref>), resulting in an easterly wind anomaly (<xref ref-type="fig" rid="F6">Figures 6A</xref>, <xref ref-type="fig" rid="F7">7A</xref>) in central Asia and a convergence of water vapor fluxes in south-central Central Asia (<xref ref-type="fig" rid="F8">Figure&#x20;8A</xref>), thus causing precipitation in these regions (<xref ref-type="fig" rid="F3">Figure&#x20;3A</xref>).</p>
<p>In the winter when CT El Ni&#xf1;o matures, the strength of anomalous high pressure at low latitudes increases significantly, the Mediterranean Sea and North Africa are controlled by anomalous high pressure, a weak low pressure center exists in the Arabian Peninsula, and a significant anomalous high pressure exists over the Tianshan Mountains (<xref ref-type="fig" rid="F4">Figures 4B</xref>, <xref ref-type="fig" rid="F5">5B</xref>), thus enhancing the northward transport of water vapor from the Indian Ocean (<xref ref-type="fig" rid="F6">Figures 6B</xref>, <xref ref-type="fig" rid="F7">7B</xref>, <xref ref-type="fig" rid="F8">8B</xref>); at the same time, the disappearance of anomalous low pressure over the Mediterranean Sea (<xref ref-type="fig" rid="F4">Figures 4B</xref>, <xref ref-type="fig" rid="F5">5B</xref>) weakens the southwest water vapor flux in Central Asia (<xref ref-type="fig" rid="F8">Figure&#x20;8B</xref>), resulting in more scattered precipitation in the northern part of the region (<xref ref-type="fig" rid="F3">Figure&#x20;3B</xref>).</p>
<p>In the spring when CT El Ni&#xf1;o decays, anomalous high pressure dominates most of the middle and low latitudes south of 40&#xb0;N, and a narrow anomalous low pressure exists at middle and high latitudes with two centers, one in western Europe and one near Siberia (<xref ref-type="fig" rid="F4">Figures 4C</xref>, <xref ref-type="fig" rid="F5">5C</xref>), and the above atmospheric circulation pattern also leads to stronger westerly winds (<xref ref-type="fig" rid="F6">Figures 6C</xref>, <xref ref-type="fig" rid="F7">7C</xref>), thus strengthening the western water vapor path in Central Asia (<xref ref-type="fig" rid="F8">Figure&#x20;8C</xref>); Meanwhile, there is anomalous high pressure at high latitudes, whose center is located near the Ural Mountains, and together with the anomalous low pressure at middle and low latitudes (<xref ref-type="fig" rid="F4">Figures 4C</xref>, <xref ref-type="fig" rid="F5">5C</xref>), it causes significant northeasterly wind anomalies in northern Central Asia (<xref ref-type="fig" rid="F6">Figures 6C</xref>, <xref ref-type="fig" rid="F7">7C</xref>), which makes water vapor from high latitudes transport to northern Central Asia and strengthens the northern water vapor path in Central Asia (<xref ref-type="fig" rid="F8">Figure&#x20;8C</xref>).</p>
<p>For WP El Ni&#xf1;o, in the autumn prior to its maturation, most of the low and middle latitudes south of 45&#xb0;N are controlled by significant anomalous high pressure, and anomalous high pressure exists at high latitudes in western Europe, while a widespread low pressure anomaly exists north of 45&#xb0;N in northeastern Europe and northern Asia (<xref ref-type="fig" rid="F4">Figures 4D</xref>, <xref ref-type="fig" rid="F5">5D</xref>), such a circulation pattern enhances northwesterly winds in northern Central Asia (<xref ref-type="fig" rid="F6">Figures 6D</xref>, <xref ref-type="fig" rid="F7">7D</xref>), allowing water vapor transport from high latitudes to Central Asia (<xref ref-type="fig" rid="F8">Figure&#x20;8D</xref>). Unlike CT El Ni&#xf1;o, a high-pressure anomaly center exists in eastern Central Asia, and a significant southwesterly wind anomaly exists at the low troposphere (<xref ref-type="fig" rid="F4">Figures 4D</xref>, <xref ref-type="fig" rid="F5">5D</xref>), enhancing the southwesterly water vapor path in Central Asia, and water vapor fluxes converge in the Tianshan Mountains and the Pamir Plateau (<xref ref-type="fig" rid="F8">Figure&#x20;8D</xref>), causing positive precipitation anomalies in these regions (<xref ref-type="fig" rid="F3">Figure&#x20;3D</xref>).</p>
<p>During the peaking season of WP El Ni&#xf1;o, anomalous low pressure in the higher latitudes of Eurasia further intensified and pushed southward, and anomalous high pressure in the middle and low latitudes also strengthened (<xref ref-type="fig" rid="F4">Figures 4E</xref>, <xref ref-type="fig" rid="F5">5E</xref>), thus enhancing the southwestern water vapor flux and northern water vapor flux in Central Asia (<xref ref-type="fig" rid="F6">Figures 6E</xref>, <xref ref-type="fig" rid="F7">7E</xref>, <xref ref-type="fig" rid="F8">8E</xref>) and bringing stronger precipitation to the aforementioned areas (<xref ref-type="fig" rid="F3">Figure&#x20;3E</xref>).</p>
<p>During its decaying season, a significant high pressure anomaly is maintained over most of the low latitudes south of 40&#xb0;N, and what was originally an anomalous low pressure at high Eurasian latitudes becomes a weak anomalous high pressure, while a low pressure center develops over central Europe at mid-latitudes, and a narrow low pressure trough exists in western Central Asia (<xref ref-type="fig" rid="F4">Figures 4F</xref>, <xref ref-type="fig" rid="F5">5F</xref>), such a circulation situation enhances water vapor transport from the Mediterranean, which is particularly significant in the troposphere (<xref ref-type="fig" rid="F6">Figures 6F</xref>, <xref ref-type="fig" rid="F7">7F</xref>). This circulation enhances water vapor transport from the Mediterranean, especially in the middle troposphere, resulting in increased southwest water vapor fluxes in Central Asia (<xref ref-type="fig" rid="F8">Figure&#x20;8F</xref>). Unlike CT El Ni&#xf1;o, the anomalous low pressure near Siberia is weak at this time, and there is no significant northeasterly wind level in the middle and lower troposphere, so the water vapor flux in the northern part of Central Asia fails at this time (<xref ref-type="fig" rid="F8">Figure&#x20;8F</xref>).</p>
</sec>
<sec id="s3-3">
<title>Possible Teleconnection</title>
<p>There are bound to be differences in the Walker circulation excited by the different SSTA patterns of the two types of El Ni&#xf1;o illustrated in <xref ref-type="fig" rid="F1">Figure&#x20;1</xref>, and such differences may have different effects on precipitation in more countries and regions around the world through the transmission of atmospheric bridges. To further analyze how the two types of El Ni&#xf1;o affect seasonal precipitation in Central Asia through changes in atmospheric circulation, we first examine the Walker circulation anomaly (<xref ref-type="fig" rid="F9">Figure&#x20;9</xref>) excited by the two types of El Ni&#xf1;o, and the local meridional circulation anomaly between 45&#xb0;E-75&#xb0;E (<xref ref-type="fig" rid="F10">Figure&#x20;10</xref>). <xref ref-type="fig" rid="F9">Figure&#x20;9</xref> shows the partial correlations between the anomalous Walker circulation averaged in 5&#xb0;S-5&#xb0;N and normalized DJF CT ENSO index (left panel) and WP ENSO index (right panel) from El Ni&#xf1;o developing autumn (SON0) to the decaying spring (MAM1). <xref ref-type="fig" rid="F10">Figure&#x20;10</xref> shows the partial correlations between the anomalous Hadley circulation averaged in 45&#xb0;E-75&#xb0;E and normalized DJF CT ENSO index (left panel) and WP ENSO index (right panel). In both figures, shadings indicate correlations above the 95 and 90% confidence levels.</p>
<fig id="F9" position="float">
<label>FIGURE 9</label>
<caption>
<p>Partial correlations (shading) of anomalous Walker circulation averaged over 5&#xb0;S-5&#xb0;N with normalized DJF CT ENSO index <bold>(A&#x2013;C)</bold> and WP ENSO index <bold>(D&#x2013;F)</bold> for SON0, DJF0 and MAM1. Light (Heavy) Shades indicate correlations above the 90% (95%) confidence levels.</p>
</caption>
<graphic xlink:href="feart-10-771362-g009.tif"/>
</fig>
<fig id="F10" position="float">
<label>FIGURE 10</label>
<caption>
<p>Same as <xref ref-type="fig" rid="F9">Figure&#x20;9</xref>, but for meridional circulation averaged over 45&#xb0;E-75&#xb0;E.</p>
</caption>
<graphic xlink:href="feart-10-771362-g010.tif"/>
</fig>
<p>For the CT El Ni&#xf1;o, two anomalous cells form over the equatorial Indian-Pacific Ocean in DJF when it peaks (<xref ref-type="fig" rid="F9">Figure&#x20;9B</xref>), a strong one over the Pacific and a weak one over the Indian Ocean. The rising branch over the Indian Ocean is weaker in autumn (<xref ref-type="fig" rid="F9">Figure&#x20;9A</xref>), strengthens in winter, and disappears in spring when CT El Ni&#xf1;o decays (<xref ref-type="fig" rid="F9">Figure&#x20;9C</xref>). The anomalous Walker circulation caused by WP El Ni&#xf1;o is significantly different from CT El Ni&#xf1;o. The most dominant upwelling branch is located in the equatorial central Pacific at 150&#xb0;E-180&#xb0;, with two sinking branches on each side of it (<xref ref-type="fig" rid="F9">Figures 9D,E</xref>). In the autumn before the peak of WP El Ni&#xf1;o, there is no significant rising motion over the Indian Ocean (<xref ref-type="fig" rid="F9">Figure&#x20;9D</xref>), and in the winter when WP El Ni&#xf1;o matures, there is a significant rising motion near 90E (<xref ref-type="fig" rid="F9">Figure&#x20;9E</xref>), and the extent of the rising branch over the Indian Ocean continues to expand as WP El Ni&#xf1;o decays (<xref ref-type="fig" rid="F9">Figure&#x20;9F</xref>). To sum up, there are significant differences in the evolution of the upwelling branch over the Indian Ocean during the development of the two types of El Ni&#xf1;o.</p>
<p>To examine the possible impact of the Indian Ocean upwelling branch on precipitation in Central Asia during the two El Ni&#xf1;o development phases, we next examine the anomalous Hadley circulation averaged over 45&#xb0;E-75&#xb0;E (<xref ref-type="fig" rid="F10">Figure&#x20;10</xref>). Note that since our results in <italic>Section Possible Teleconnection</italic> indicate that the two types of El Ni&#xf1;o have no significant effect on precipitation in Xinjiang, China, during their lifecycle, here we narrow the meridional range of the region of interest to 45&#xb0;E-75&#xb0;E to exclude the blocking effect of the Tibetan Plateau. It can be seen that around 30&#xb0;N-40&#xb0;N over Central Asia, there is a clear rising motion in the autumn before the peak of CT El Ni&#xf1;o, extending to the top of the troposphere (<xref ref-type="fig" rid="F10">Figure&#x20;10A</xref>); during the peaking winter of El Ni&#xf1;o, this rising branch moves northward to around 50&#xb0;N and weakens significantly (<xref ref-type="fig" rid="F10">Figure&#x20;10B</xref>); in the spring when El Ni&#xf1;o decays, there is no clear rising motion over Central Asia (<xref ref-type="fig" rid="F10">Figure&#x20;10C</xref>). For WP El Ni&#xf1;o, upward motion is present over Central Asia (30&#xb0;N-55&#xb0;N) in the autumn before its peak, in the winter when it matures, and in the spring when it decays (<xref ref-type="fig" rid="F10">Figures 10D&#x2013;F</xref>). This upward branch is strongest in the winter of El Ni&#xf1;o&#x2019;s maturation and reaches its widest extent and extends to the top of the troposphere (<xref ref-type="fig" rid="F10">Figure&#x20;10E</xref>). In spring, this upwelling branch is weaker but still present, which is a significant difference from CT El Ni&#xf1;o (<xref ref-type="fig" rid="F10">Figure&#x20;10F</xref>). That is, the influence of the Walker circulation anomaly over the Indian Ocean on precipitation anomalies in Central Asia differs during the life cycle of the two types of El Ni&#xf1;o, especially in winter and spring. We further examine the 200&#xa0;hPa velocity potential (VP200) composite over the two types of El Ni&#xf1;o (<xref ref-type="fig" rid="F11">Figure&#x20;11</xref>). A clear, persistent pattern of upper-level convergence over the Indian Ocean is present throughout the WP El Ni&#xf1;o peaking winter and decaying spring. Whereas the positive VP200 anomalies are weak in the winter of CT El Ni&#xf1;o peaks and disappear in the following spring.</p>
<fig id="F11" position="float">
<label>FIGURE 11</label>
<caption>
<p>Same as <xref ref-type="fig" rid="F4">Figure&#x20;4</xref>, but for 200&#xa0;hPa anomalous velocity potential.</p>
</caption>
<graphic xlink:href="feart-10-771362-g011.tif"/>
</fig>
</sec>
</sec>
<sec id="s4">
<title>Summary and Discussion</title>
<p>In this study, we examine the different seasonal precipitation anomaly patterns in Central Asia associated with the CT El Ni&#xf1;o and WP El Ni&#xf1;o from the El Ni&#xf1;o developing SON to the decaying MAM based on GPCC monthly precipitation data version 2018 and discover that there are distinguished differences between the effects of the two types of El Ni&#xf1;o on precipitation in Central Asia in terms of intensity, spatially and temporally. We then discuss two types of El Ni&#xf1;o-induced atmospheric circulation anomalies and water vapor flux anomalies in Central Asia and compare the effects of the rising branch of the Indian Ocean on precipitation in Central Asia in different Walker circulation anomalies patterns. The conclusion are as follows:</p>
<p>Overall, El Ni&#xf1;o are associated with more precipitations over Central Asia in SON, DJF and MAM which is consistent with the findings of <xref ref-type="bibr" rid="B6">Chen et&#x20;al. (2018)</xref>, but significant discrepancies can be found in the precipitation anomaly spatial patterns associated with the two types of El Ni&#xf1;o from the El Ni&#xf1;o developing autumn to the decaying spring. The strength of the positive precipitation anomaly associated with WP El Ni&#xf1;o is significantly stronger than that of CT El Ni&#xf1;o. The precipitation associated with CT El Ni&#xf1;o is mostly concentrated in the plains and hilly areas of Central Asia and is more dispersed in space. With the development and extinction of CT El Ni&#xf1;o, the positive anomaly regions of precipitation in Central Asia have a tendency to move northwestward, but the spatial pattern of precipitation anomalies lacks consistency from SON(0) to MAM(1). Whereas the precipitation associated with WP El Ni&#xf1;o is mostly concentrated along Pamirs and Tian Shan Mountains with consistency throughout the autumn before El Ni&#xf1;o peaks to the spring when El Ni&#xf1;o decays. Note that, among the three seasons studied, its influence on precipitation in Central Asia is most widespread and strongest in the spring when WP El Ni&#xf1;o decays. What we found in this study echoes the previous findings based on a synoptic diagnose for summertime extreme precipitation in Northwest China (e.g., <xref ref-type="bibr" rid="B15">Huang W. et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B24">Ning et&#x20;al., 2021</xref>).</p>
<p>Previous studies have indicated that the southwesterly water vapor fluxes from the Arabic Sea and Africa are the source of Central Asia precipitation during El Nino and the north water vapor fluxes from Russia are only detected in MAM which account for the maximum precipitation of Central Asia in this season (<xref ref-type="bibr" rid="B23">Mariotti, 2007</xref>; <xref ref-type="bibr" rid="B12">Hu et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B6">Chen et&#x20;al., 2018</xref>). We further found that the southwestern water vapor fluxes from the Indian Ocean are significantly greater during the maturing winter of WP El Ni&#xf1;o than during the winter of CT El Ni&#xf1;o, and this contribution persists from winter to the following spring and is enhanced in spring. In addition, the effect of northern water vapor fluxes on precipitation in Central Asia is mainly found in the spring when CT El Ni&#xf1;o begins to decay, which is not evident in the WP El Ni&#xf1;o&#x20;event.</p>
<p>The analysis of anomalous atmospheric circulation caused by two types of El Ni&#xf1;o shows that the interconfiguration of anomalous high pressure in the south side of Central Asia at low and middle latitudes and anomalous low pressure and anomalous high pressure in the high latitudes of Eurasia affects the southwest water vapor flux and north side water vapor flux in Central Asia, thus causing different effects of different types of El Ni&#xf1;o on precipitation in Central Asia at different stages. The spatial consistency of the WP El Ni&#xf1;o effect on precipitation in Central Asia over three seasons may be related to the rising branch of the anomalous Walker circulation over the Indian Ocean induced by&#x20;it.</p>
</sec>
</body>
<back>
<sec id="s5">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6">
<title>Author Contributions</title>
<p>YZ and AH contributed to the development and planning of the study. FF performed the data analysis and wrote the manuscript. YL and XZ assisted with data pre-processing and figure enhancement. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s7">
<title>Funding</title>
<p>This work was jointly supported by the Sichuan Science and Technology Program (Grant No. 2020JDJQ0050), National Natural Science Foundation of China (Grant No. U1903113, 41875102, 41805054, 41905037), and the Scientific Research Foundation of Chengdu University of Information Technology (Grant No. KYTZ201736).</p>
</sec>
<sec sec-type="COI-statement" id="s8">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s9">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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