<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">ACS</journal-id><journal-title-group><journal-title>Atmospheric and Climate Sciences</journal-title></journal-title-group><issn pub-type="epub">2160-0414</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/acs.2015.54032</article-id><article-id pub-id-type="publisher-id">ACS-60166</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  MJO Modulation of Station Rainfall in the Semiarid Serid&#243;, Northeast Brazil
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>ati</surname><given-names>E. A. Valadão</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Paulo</surname><given-names>S. Lucio</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rosane</surname><given-names>R. Chaves</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Leila</surname><given-names>M. V. Carvalho</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Programa de Pós-Gradua&amp;amp;#231&amp;amp;#227o em Ciências Climáticas, Universidade Federal do Rio Grande do Norte, Natal, Brazil</addr-line></aff><aff id="aff2"><addr-line>Earth Research Institute and Department of Geography, University of California, Santa Barbara, USA</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>cati.valadao@gmail.com(AEAV)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>14</day><month>09</month><year>2015</year></pub-date><volume>05</volume><issue>04</issue><fpage>408</fpage><lpage>417</lpage><history><date date-type="received"><day>11</day>	<month>April</month>	<year>2015</year></date><date date-type="rev-recd"><day>accepted</day>	<month>6</month>	<year>October</year>	</date><date date-type="accepted"><day>9</day>	<month>October</month>	<year>2015</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  The influence of the Madden Julian Oscillation (MJO) on station rainfall over the Serid&#243; region of Rio Grande do Norte state, Northeast Brazil is examined based on 17 raingauge daily data over 30-year period (1 January-31 December, 1981-2010). The Serid&#243; is one of the driest regions in Northeast Brazil and is recognized as particularly vulnerable to desertification by the United Nations Convention to Combat Desertification. Firstly, daily anomalies were calculated by removing the 30-year daily climatology. Then, to distinguish the MJO signal from other patterns of climate variability, the daily anomalies were band pass filtered in the frequency domain (20 - 90 days) by applying Fast Fourier Transform (FFT). Composites of rainfall anomalies were computed for each of the eight phases of the MJO during February-May (FMAM) rainy season, based on the Jones-Carvalho MJO index. Only days classified as MJO events were considered in the composites. For each phase composite, statistical significance tests were computed independently at each individual station by applying a two-tailed Student’s t-test at 5% significance level. Preliminary results showed that the rainfall anomalies have a spatial coherence throughout the MJO cycle. Extreme positive (negative) anomalies occurred in phase 2 (phase 5), where 13 (12) out of the 17 stations showed statistically significant anomalies in the range of 0.9 - 1.9 mm/day (0.8 - 1.7 mm/day). The typical difference between the wet MJO phase 2 and dry phase 5 represented at least 50% modulation of the daily mean rainfall.
 
</p></abstract><kwd-group><kwd>Madden-Julian Oscillation</kwd><kwd> Intraseasonal</kwd><kwd> Raingauge</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The tropical Brazil does not only encompasses the Earths’s largest rain forest in the Amazon basin, but also the “Caatinga”, which is the dry forest in Northeast Brazil (NEB), occupying an area of around 800,000 Km<sup>2</sup> and covering approximately 11% of the national territory, as illustrated in <xref ref-type="fig" rid="fig1">Figure 1</xref>. The Caatinga is a fragile and unique ecosystem with a great variety of endemic species. Brazil’s Northeast is the third largest, the third most- populous, and also one of the poorest regions in the country. The region is characterized by marked interannual precipitation variability, and has a long history of severe recurrent droughts, which seriously affect its agricul- tural production and water resources.</p><p>Given NEB’s unique climatic characteristics and land degradation, the United Nations Convention to Combat Desertification (UNCCD, www.unccd.int) has recognized NEB as particularly vulnerable to desertification [<xref ref-type="bibr" rid="scirp.60166-ref1">1</xref>] . In this context, an area known as Serid&#243;, located in the semiarid interior of Rio Grande do Norte state (RN), has been assessed to be one of the most affected by desertification in this state (see <xref ref-type="fig" rid="fig1">Figure 1</xref> for location). This is due not only to its climatic conditions, but also to the human activities associated with inappropriate land management in the region. Land use patterns and practices in the Serid&#243; have increased land degradation, associated with deforestation of the Caatinga to create fields and pastures, and to supply the demand of fuel- wood for households, and for the production of wood charcoal for industries (e.g., ceramic, gypsum, plaster, limekilns). Salinization of soils and local water resources is another important factor of environmental degra- dation over the area [<xref ref-type="bibr" rid="scirp.60166-ref1">1</xref>] . Water supply in the Serid&#243; is basically provided through dams, small reservoirs, wells and cisterns that collect water during the rainy season.</p><fig-group id="fig1"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Areas susceptible to desertification according to the UNCCD, including the Caatinga biome area (see legend). The inset shows the location of Northeast Brazil (in red). The frame on the right side shows the study area: the Serid&#243; of Rio Grande do Norte state. Dots represent the raingauge station location. Adapted from the National Action Program to Combat Desertification and Mitigate the Effects of Drought PAN-Brazil [<xref ref-type="bibr" rid="scirp.60166-ref1">1</xref>] .</title></caption><fig id ="fig1_1"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/5-4700381x6.png"/></fig><fig id ="fig1_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/5-4700381x5.png"/></fig></fig-group><p>Precipitation over the Serid&#243; is concentrated in a short wet season, which comprises several spells of heavy rains, each lasting on the order of a few days to a week or more, separated by breaks of reduced rainfall as illustrated in <xref ref-type="fig" rid="fig2">Figure 2</xref>. The Serid&#243; experiences large fluctuations in annual rainfall: the year 2000 not only was wetter than 2001, but also showed spells of comparatively enhanced rainfall. Comparing with the annual climatology (see <xref ref-type="table" rid="table1">Table 1</xref>), the year 2000 showed wetter-than-normal conditions, whereas the year 2001 was drier-than-normal.</p><p>All these environmental impacts have contributed to increase social and economic impoverishment, and migration of people from rural areas. Given the importance of intraseasonal rainfall variations for agricultural production and water management in semiarid regions, this study focuses on the influence of the Madden-Julian Oscillation (MJO) over the environmental fragile Serid&#243;/RN region.</p>Background<p>The MJO has been documented as a major source of variability in the tropics. The MJO consists of a large-scale region of enhanced convection and precipitation that originates over the tropical Indian Ocean and propagates slowly eastward to the western-central Pacific [<xref ref-type="bibr" rid="scirp.60166-ref2">2</xref>] - [<xref ref-type="bibr" rid="scirp.60166-ref5">5</xref>] . Many studies have revealed that the propagation and evolution of the MJO events have great influence on precipitation not only in the tropical region, but also in the extratropics. For instance, over South America [<xref ref-type="bibr" rid="scirp.60166-ref6">6</xref>] - [<xref ref-type="bibr" rid="scirp.60166-ref11">11</xref>] , Africa [<xref ref-type="bibr" rid="scirp.60166-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.60166-ref13">13</xref>] , Mexico [<xref ref-type="bibr" rid="scirp.60166-ref14">14</xref>] , United States [<xref ref-type="bibr" rid="scirp.60166-ref15">15</xref>] - [<xref ref-type="bibr" rid="scirp.60166-ref18">18</xref>] , Canada [<xref ref-type="bibr" rid="scirp.60166-ref19">19</xref>] , Australia [<xref ref-type="bibr" rid="scirp.60166-ref20">20</xref>] , Indonesia [<xref ref-type="bibr" rid="scirp.60166-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.60166-ref22">22</xref>] , and China [<xref ref-type="bibr" rid="scirp.60166-ref23">23</xref>] [<xref ref-type="bibr" rid="scirp.60166-ref24">24</xref>] . The MJO also affects monsoon systems (e.g., [<xref ref-type="bibr" rid="scirp.60166-ref25">25</xref>] - [<xref ref-type="bibr" rid="scirp.60166-ref30">30</xref>] ).</p><p>Previous studies using gridded station rainfall over tropical South America showed that the MJO plays an important role in modulating its convection and precipitation. For example, Carvalho et al. [<xref ref-type="bibr" rid="scirp.60166-ref7">7</xref>] found evidence of an increase on extreme rainfall events over north-northeastern Brazil (based on the December-February 95th daily rainfall percentile) during the MJO phase characterized by enhanced convective activity over the central</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Station Details. Code refers to the station code in <xref ref-type="fig" rid="fig3">Figure 3</xref>. Annual total rainfall is based on 30-year period from January-December 1981-2010. FMAM (February-May) corresponds to the rainy season mean total (in parentheses as a percentage of the annual total). Units are in mm for rainfall and m for altitude</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Station name</th><th align="center" valign="middle" >Code</th><th align="center" valign="middle" >Location</th><th align="center" valign="middle" >Altitude</th><th align="center" valign="middle" >Annual total rainfall</th><th align="center" valign="middle" >FMAM (%)</th></tr></thead><tr><td align="center" valign="middle" >Acari</td><td align="center" valign="middle" >Aca</td><td align="center" valign="middle" >6.43˚S, 36.63˚W</td><td align="center" valign="middle" >270</td><td align="center" valign="middle" >546</td><td align="center" valign="middle" >404 (74)</td></tr><tr><td align="center" valign="middle" >Caic&#243;</td><td align="center" valign="middle" >Cai</td><td align="center" valign="middle" >6.45˚S, 37.08˚W</td><td align="center" valign="middle" >143</td><td align="center" valign="middle" >660</td><td align="center" valign="middle" >515 (78)</td></tr><tr><td align="center" valign="middle" >Carna&#250;ba dos Dantas</td><td align="center" valign="middle" >CDa</td><td align="center" valign="middle" >6.55˚S, 36.58˚W</td><td align="center" valign="middle" >460</td><td align="center" valign="middle" >574</td><td align="center" valign="middle" >427 (74)</td></tr><tr><td align="center" valign="middle" >Cruzeta</td><td align="center" valign="middle" >Cru</td><td align="center" valign="middle" >6.40˚S, 36.78˚W</td><td align="center" valign="middle" >140</td><td align="center" valign="middle" >623</td><td align="center" valign="middle" >445 (71)</td></tr><tr><td align="center" valign="middle" >Currais Novos</td><td align="center" valign="middle" >CNo</td><td align="center" valign="middle" >6.25˚S, 36.52˚W</td><td align="center" valign="middle" >350</td><td align="center" valign="middle" >537</td><td align="center" valign="middle" >399 (74)</td></tr><tr><td align="center" valign="middle" >Equador</td><td align="center" valign="middle" >Equ</td><td align="center" valign="middle" >6.93˚S, 36.72˚W</td><td align="center" valign="middle" >500</td><td align="center" valign="middle" >488</td><td align="center" valign="middle" >344 (70)</td></tr><tr><td align="center" valign="middle" >Ipueira</td><td align="center" valign="middle" >Ipu</td><td align="center" valign="middle" >6.80˚S, 37.18˚W</td><td align="center" valign="middle" >217</td><td align="center" valign="middle" >645</td><td align="center" valign="middle" >495 (77)</td></tr><tr><td align="center" valign="middle" >Jardim de Piranhas</td><td align="center" valign="middle" >JPi</td><td align="center" valign="middle" >6.37˚S, 37.35˚W</td><td align="center" valign="middle" >130</td><td align="center" valign="middle" >664</td><td align="center" valign="middle" >514 (77)</td></tr><tr><td align="center" valign="middle" >Jardim do Serid&#243;</td><td align="center" valign="middle" >JSe</td><td align="center" valign="middle" >6.58˚S, 36.77˚W</td><td align="center" valign="middle" >218</td><td align="center" valign="middle" >607</td><td align="center" valign="middle" >456 (75)</td></tr><tr><td align="center" valign="middle" >Ouro Branco</td><td align="center" valign="middle" >OBr</td><td align="center" valign="middle" >6.70˚S, 36.93˚W</td><td align="center" valign="middle" >195</td><td align="center" valign="middle" >599</td><td align="center" valign="middle" >461 (77)</td></tr><tr><td align="center" valign="middle" >Parelhas</td><td align="center" valign="middle" >Par</td><td align="center" valign="middle" >6.68˚S, 36.65˚W</td><td align="center" valign="middle" >325</td><td align="center" valign="middle" >571</td><td align="center" valign="middle" >436 (76)</td></tr><tr><td align="center" valign="middle" >Santana do Serid&#243;</td><td align="center" valign="middle" >SSe</td><td align="center" valign="middle" >6.77˚S, 36.73˚W</td><td align="center" valign="middle" >336</td><td align="center" valign="middle" >577</td><td align="center" valign="middle" >430 (75)</td></tr><tr><td align="center" valign="middle" >S&#227;o Jo&#227;o do Sabugi</td><td align="center" valign="middle" >SJSa</td><td align="center" valign="middle" >6.72˚S, 37.20W</td><td align="center" valign="middle" >187</td><td align="center" valign="middle" >680</td><td align="center" valign="middle" >529 (78)</td></tr><tr><td align="center" valign="middle" >S&#227;o Fernando</td><td align="center" valign="middle" >SFe</td><td align="center" valign="middle" >6.37˚S, 37.18˚W</td><td align="center" valign="middle" >139</td><td align="center" valign="middle" >663</td><td align="center" valign="middle" >503 (76)</td></tr><tr><td align="center" valign="middle" >S&#227; Jos&#233; do Serid&#243;</td><td align="center" valign="middle" >SJSe</td><td align="center" valign="middle" >6.43˚S, 36.87˚W</td><td align="center" valign="middle" >207</td><td align="center" valign="middle" >605</td><td align="center" valign="middle" >449 (74)</td></tr><tr><td align="center" valign="middle" >Serra Negra do Norte</td><td align="center" valign="middle" >SNN</td><td align="center" valign="middle" >6.65˚S, 37.38˚W</td><td align="center" valign="middle" >180</td><td align="center" valign="middle" >799</td><td align="center" valign="middle" >605 (76)</td></tr><tr><td align="center" valign="middle" >Timba&#250;ba dos Batistas</td><td align="center" valign="middle" >TBa</td><td align="center" valign="middle" >6.45˚S, 37.27˚W</td><td align="center" valign="middle" >161</td><td align="center" valign="middle" >705</td><td align="center" valign="middle" >551 (78)</td></tr></tbody></table></table-wrap><fig-group id="fig2"><label><xref ref-type="fig" rid="fig2">Figure 2</xref></label><caption><title> Time series of 3-day running-mean rainfall for four stations in the Serid&#243;/RN for the period of 1 January to 31 December 2000 (top panel) and 2001 (bottom panel). Also shown are smoothed climatological annual cycles for each station, computed using all daily data from 1981 to 2010. Positive (negative) rainfall anomalies with respect to the smoothed climatology are dark (light) shaded.</title></caption><fig id ="fig2_1"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/5-4700381x7.png"/></fig><fig id ="fig2_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/5-4700381x8.png"/></fig></fig-group><p>Pacific and suppression over the Maritime Continent. Opposite features were observed when the enhanced convection was over the Maritime Continent and suppression over the central Pacific. Souza et al. [<xref ref-type="bibr" rid="scirp.60166-ref31">31</xref>] examined precipitation variability over eastern Amazon and NEB during the autumn rainy season (March-May), com- bining the effects of the tropical Pacific and the Atlantic sea surface temperature (SST) anomalies in two extreme and contrasting scenarios. Their favorable (unfavorable) scenario was characterized by simultaneous occurrence of southward (northward) SST gradient in the intertropical Atlantic and La Ni&#241;a (El Ni&#241;o). They found evidence that, on intraseasonal timescale, anomalously deficient and abundant precipitation events occurred alternately in both extreme climatic scenarios. They suggested that the MJO played a key role in modulating deep convection and precipitation over the region during years under extreme climatic conditions. Souza and Ambrizzi [<xref ref-type="bibr" rid="scirp.60166-ref11">11</xref>] also documented that, on intraseasonal timescale, the MJO effectively contributes to a considerable fraction of the total rainfall during January-May season over southeastern Amazon and NEB. More recently, Mo et al. [<xref ref-type="bibr" rid="scirp.60166-ref32">32</xref>] examined the influence of the MJO on Pan America during December-March and June- September for the period 1979-2001. Analyzing the evolution of the MJO cycle, they showed that in South America, the largest influence was found over northeastern Brazil during December-March.</p><p>Although these studies greatly contributed to improve the understanding of the MJO’s influence over the South America, none of them focused specifically over NEB, or evaluated the MJO impact at individual station level. Even though a MJO signal may be difficult to detect at local scale, such information could be important for municipalities under water stress. Here, we introduce a study of the MJO’s influence on the Serid&#243; region, and we based our investigation on daily rainfall from 17 raingauge data over 30-year period. More specifically, we investigate the MJO signal at individual stations located in Serid&#243; for each phase of the MJO’s life cycle. This article is organized as follows. Data and methods are described in Section 2. The MJO signal on intraseasonal rainfall for each station in Serid&#243; is discussed in Section 3. Then, a summary and final remarks of our work are provided in the final section.</p></sec><sec id="s2"><title>2. Data and Methods</title><sec id="s2_1"><title>2.1. Data</title><p>The primary data used in this study were the time series of daily rainfall totals from raingauge records of the Rio Grande do Norte State, Northeast Brazil, provided by the Empresa Brasileira de Pesquisa Agropecu&#225;ria do Rio Grande do Norte (EMPARN), for a 30-year period from 1 January-31 December, 1981-2010. According to the Brazilian Ministry of Agrarian Development [Minist&#233;rio do Desenvolvimento Agr&#225;rio (MDA); www.mda.gov.br], the Serid&#243;/RN is divided into 25 municipalities, covering an area of 10,954.50 Km<sup>2</sup> (about 20.45% of the Rio Grande do Norte state) and has a population of around 295,700 inhabitants. In this study we selected a sub-set of 17 stations located in the Serid&#243;/RN region (see frame on the right side in <xref ref-type="fig" rid="fig1">Figure 1</xref> for location), following the geographical division of the Brazilian Institute of Geography and Statistics [Instituto Brasileiro de Geografia e Estat&#237;stica (IBGE)]. A quality control has been previously conducted by the EMPARN and all the records have no missing data.</p><p>As shown in <xref ref-type="table" rid="table1">Table 1</xref>, the Serid&#243; exhibits large spatial variability, with mean annual totals ranging between 480 - 800 mm/year. Our analysis focuses on February-May (FMAM), which is the region’s main rainy season, corresponding between 70% - 78% of the mean annual total. For the sake of simplicity, the stations were grouped into the Western Serid&#243; and Eastern Serid&#243; (according to IBGE). The Eastern Serid&#243; area corresponds to the highlands on the western border of the Borborema Plateau, with its highest point (807 m) located in the Serra das Queimadas, in the Equador municipality. The topography decreases to the west, where the depressions of the rivers Serid&#243; and Piranhas-A&#231;u are located, with altitudes ranging between 50 - 200 m.</p><p>The MJO index developed by Jones and Carvalho [<xref ref-type="bibr" rid="scirp.60166-ref16">16</xref>] (henceforth JCMi) was used to define and investigate the MJO influence on intraseasonal rainfall. The JCMi was derived from combined empirical orthogonal func- tion (EOF) analysis of equatorially daily averaged (15˚S - 15˚N) band-filtered anomalies (20 - 200 days) of zonal wind components at 850-hPa and 200-hPa, and constructed as follows. The seasonal cycle and trend were removed before applying the filtering procedure. The phase diagram of the first two normalized principal components (PC1, PC2) was used to identify MJO events according to four criteria: 1) the phase angle between PC1 and PC2 is required to systematically rotate counterclockwise to ensure the eastward propagation of the</p><p>oscillation at least to the Maritime Continent (phase 5); 2) the amplitude <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/5-4700381x9.png" xlink:type="simple"/></inline-formula> should be always</p><p>larger than 0.35; 3) the mean amplitude during the event larger than 0.9; and, the entire duration of the event should be between 30 and 90 days. Composites of band-filtered outgoing longwave radiation (OLR) anomalies were used to characterize the convective anomalies associated with each of the MJO.</p><p>Jones [<xref ref-type="bibr" rid="scirp.60166-ref33">33</xref>] and Jones and Carvalho [<xref ref-type="bibr" rid="scirp.60166-ref34">34</xref>] [<xref ref-type="bibr" rid="scirp.60166-ref35">35</xref>] , also used these same criteria, which are comparable to the criteria adopted by Matthews [<xref ref-type="bibr" rid="scirp.60166-ref36">36</xref>] [<xref ref-type="bibr" rid="scirp.60166-ref37">37</xref>] . The JCMi was available as daily time series, divided into 9 phases: phase 0 represents quiescent days (or MJO inactive). Phases 8 - 1 correspond to the period when the MJO’s active center is over the Western Hemisphere and Africa. In phases 2 - 3, the convective center is in the Indian Ocean; then in phases 4 - 5 the convective envelope is in the Maritime Continent, and during phases 6 - 7 its convective center is in the Western Pacific Ocean.</p></sec><sec id="s2_2"><title>2.2. Methods</title><p>Daily rainfall anomalies for each station were calculated by removing the 30-year daily climatology. Intra- seasonal anomalies were obtained by bandpass filtering the time series of daily anomalies (1 January-31 December, 1981-2010) in frequency domain (20 - 90 days) by applying Fast Fourier Transform (FFT). The composite MJO rainfall signal at each station was obtained by averaging the intraseasonal anomalies over days that fell in each phase of the MJO during the FMAM rainy season. The statistical significance of the composites was assessed through a two-tailed Student’s t-test at 5% significance level against the null hypothesis that the composite was equivalent to the climatological mean (that is, zero anomaly). All the significance tests were computed independently at each individual station.</p></sec></sec><sec id="s3"><title>3. The MJO Cycle in Daily Station Rainfall</title><p>To examine the influence of the MJO on rainfall in the semiarid Serid&#243;/RN we averaged intraseasonal rainfall anomalies at each station for the eight phases of the MJO. During FMAM 1981-2010, we found between 49 (phase 1) and 55 (phase 6) blocks of days (or “events”). For instance, for MJO phase 2 there were 50 events (24- 28 March 1981, 8-11 May 1981 …, 18-20 March 2010, 4-6 May 2010). The composite MJO rainfall signals for each station are shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>. If the rainfall anomaly at a particular station was statistically significant in a particular MJO phase, then a larger symbol was plotted on that phase.</p><p>During phases 1 - 3 the majority of stations showed enhanced rainfall. Maximum positive anomalies occurred in phase 2, where 13 out of the 17 stations showed statistically significant anomalies (between 0.9 - 1.9 mm/day). Significant positive anomalies are also found at 7 stations in phase 3 (between 1.1 - 1.7 mm/day). During phases 5 - 6 all stations showed suppressed rainfall. Statistically significant negative anomalies occurred at 12 stations in phase 5 (between 0.8 - 1.7 mm/day), and 10 stations in phase 6 (between 0.9 - 1.8 mm/h). Comparatively, stations located in the Western Serid&#243; showed the absolute magnitude of rainfall anomalies slightly greater than those in the Eastern Serid&#243;. Three stations did not show any statistically significant rainfall anomalies: Equador, Jardim de Piranhas and Santana do Serid&#243;. Possibly, this may be related to raingauge exposure and local micrometeorological conditions, since raingauge measurements are influenced by factors such as instrument placement, and the topographic (ridge top, valley, etc.) and environmental (urban, suburban, rural, etc.) settings.</p><p>The results showed that the stations exhibited a similar anomaly pattern. Notice that there is a clear MJO signal in all the individual stations throughout the MJO cycle. The rainfall increased by about 30% in phase 2 and decreased by about 25% in phase 5 relative to the climatological mean for the whole Serid&#243;/RN. Combining the MJO signals for wet phases 2 - 3 and dry phases 5 - 6, the difference represented about 50% - 150% modulation of the mean rainfall considering all stations.</p></sec><sec id="s4"><title>4. Summary and Final Remarks</title><p>Previous work on the MJO influence over tropical Brazil has been based only on gridded station rainfall data. Here, we hypothesize that the MJO effect on daily rainfall over the semiarid Serid&#243;/RN in NEB could be felt at the local station level. We composited the MJO rainfall signal for each station during the region’s main rainy season (FMAM). Each station composite was obtained averaging the rainfall anomalies over the contemporaneous (i.e., with zero lag) days that fell in each of the eight MJO phases, considering a 30-year period (1981-2010). Our results showed that the rainfall patterns in the Serid&#243; undergo substantial changes (from enhancement to suppression) as the convective center of the MJO propagates eastward. Considering a 5% significance level, the maximum positive rainfall anomalies occurred in phase 3 (or occasionally in phase 3)</p><fig-group id="fig3"><label><xref ref-type="fig" rid="fig3">Figure 3</xref></label><caption><title> MJO cycle of rainfall anomaly (mm/day) for 17 stations in the Serid&#243;/RN during February- May 1981-2010: (a) Western Serid&#243; area; (b) Eastern Serid&#243; area. Where a particular data point is statistically significant at the 5% significance level, a larger symbol is plotted. Station codes are in the legend (see <xref ref-type="table" rid="table1">Table 1</xref> for station names).</title></caption><fig id ="fig3_1"><label>(b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/5-4700381x10.png"/></fig><fig id ="fig3_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/5-4700381x11.png"/></fig></fig-group><p>when the MJO’s active convection was over the Indian Ocean, whereas the maximum negative anomalies occurred in phase 5 (or occasionally in phase 6), when its convection was passing through the Maritime Con- tinent/Western Pacific Ocean. The typical difference between the wet phase 2 and dry phase 5 represented at least 50% modulation of the daily mean rainfall in 13 out of the 17 stations.</p><p>As stated in the introduction, in vulnerable semiarid regions, such as NEB, land degradation and droughts have negative impact on the quantity, quality and availability of water resources resulting in water scarcity. Moreover, prolonged breaks or extreme rainfall events during the rainy season can disrupt several sectors of society, such as agriculture, leading to devastating socio-economic consequences. Hence, knowing when wet and dry MJO phases may occur over the region could complement regional weather and short-term seasonal forecasts by combining this information with the MJO monitoring and forecast provided by some agencies (e.g., www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/mjo.shtml). These preliminary results for a small- scale study area have motivated our ongoing investigation of the MJO’s modulation of rainfall over the entire NEB. We are combining multiple raingauge datasets in the analysis to evaluate the spatial extent of the rainfall signal at station level, whether there is a seasonal variation, and also the MJO-related changes in convection and circulation over the region.</p></sec><sec id="s5"><title>Acknowledgements</title><p>The rainfall data were provided by the EMPARN. We thank Dr. Charles Jones for providing the MJO index, and Dr. Rodrigo J. Bombardi for providing some programming routines. We also thank the two anonymous re- viewers for their comments and suggestions. Cati E. A. Valad&#227;o was supported by the Coordena&#231;&#227;o de Aper- fei&#231;oamento de Pessoal de N&#237;vel Superior (CAPES) PhD scholarships (REUNI, DS and BEX 9108/12-2).</p></sec><sec id="s6"><title>Cite this paper</title><p>Cati E. 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