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<front>
<journal-meta>
<journal-id journal-id-type="publisher">NPG</journal-id>
<journal-title-group>
<journal-title>Nonlinear Processes in Geophysics</journal-title>
<abbrev-journal-title abbrev-type="publisher">NPG</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Nonlin. Processes Geophys.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1607-7946</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/npg-15-503-2008</article-id>
<title-group>
<article-title>Controlling instabilities along a 3DVar analysis cycle by assimilating in  the unstable subspace: a comparison with the EnKF</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Carrassi</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Trevisan</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Descamps</surname>
<given-names>L.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Talagrand</surname>
<given-names>O.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Uboldi</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Royal Meteorological Institute of Belgium – RMI, Bruxelles, Belgium</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Dept. of Physics – University of Ferrara, Ferrara, Italy</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Istituto di Scienze dell&apos;Atmosfera e del Clima (ISAC) – Consiglio  Nazionale delle Ricerche (CNR), Largo Gobetti 101, Bologna, Italy</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Laboratoire de Météorologie Dynamique, École Normale Supérieure, Paris, France</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>Consultant, Novate Milanese, Italy</addr-line>
</aff>
<pub-date pub-type="epub">
<day>01</day>
<month>07</month>
<year>2008</year>
</pub-date>
<volume>15</volume>
<issue>4</issue>
<fpage>503</fpage>
<lpage>521</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2008 A. Carrassi et al.</copyright-statement>
<copyright-year>2008</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://npg.copernicus.org/articles/15/503/2008/npg-15-503-2008.html">This article is available from https://npg.copernicus.org/articles/15/503/2008/npg-15-503-2008.html</self-uri>
<self-uri xlink:href="https://npg.copernicus.org/articles/15/503/2008/npg-15-503-2008.pdf">The full text article is available as a PDF file from https://npg.copernicus.org/articles/15/503/2008/npg-15-503-2008.pdf</self-uri>
<abstract>
<p>A hybrid scheme obtained by combining 3DVar with the Assimilation in the Unstable
 Subspace (3DVar-AUS) is tested in a QG model, under perfect model conditions, with
 a fixed observational network, with and without observational noise. The AUS scheme,
 originally formulated to assimilate adaptive observations, is used here to
 assimilate the fixed observations that are found in the region of local maxima of
 BDAS vectors (Bred vectors subject to assimilation), while the remaining observations are assimilated by 3DVar.
 The performance of the hybrid scheme is compared with that of 3DVar and of an EnKF.
 The improvement gained by 3DVar-AUS and the EnKF with respect to 3DVar alone is similar
 in the present model and observational configuration, while 3DVar-AUS outperforms the EnKF during the forecast stage.
The 3DVar-AUS algorithm is easy to implement and the results obtained in the idealized
conditions of this study encourage further investigation toward an implementation in more realistic contexts.</p>
</abstract>
<counts><page-count count="19"/></counts>
</article-meta>
</front>
<body/>
<back>
<ref-list>
<title>References</title>
<ref id="ref1">
<label>1</label><mixed-citation publication-type="other" xlink:type="simple"> Anderson, J.: A local least squares framework for ensemble filtering, Mon. Wea. Rev., 131, 634–642, 2003. </mixed-citation>
</ref>
<ref id="ref2">
<label>2</label><mixed-citation publication-type="other" xlink:type="simple"> Anderson, J. and Anderson, S.: A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilation and forecast, Mon. Wea. Rev., 127, 2741–2758, 1999. </mixed-citation>
</ref>
<ref id="ref3">
<label>3</label><mixed-citation publication-type="other" xlink:type="simple"> Benettin, G., Galgani, L., Giorgilli, A., and Strelcyn, J.: Lyapunov characteristic exponents for smooth dynamical systems and for Hamiltonian systems; a method for computing them, Meccanica, 15, 9–30, 1980. </mixed-citation>
</ref>
<ref id="ref4">
<label>4</label><mixed-citation publication-type="other" xlink:type="simple"> Bergman, K H.: Multivariate analysis of temperature and winds using optimum interpolation., Mon. Wea. Rev., 107, 1423–1444, 1979. </mixed-citation>
</ref>
<ref id="ref5">
<label>5</label><mixed-citation publication-type="other" xlink:type="simple"> Bleck, R.: Simulation of coastal upwelling frontogenesis with an isopycnic coordinate model, J. Geophys. Res., 83C, 6163–6172, 1978. </mixed-citation>
</ref>
<ref id="ref6">
<label>6</label><mixed-citation publication-type="other" xlink:type="simple"> Carrassi, A., Trevisan, A., and Uboldi, F.: Adaptive observations and assimilation in the unstable subspace by breeding on the data-assimilation system, Tellus, 59A, 101–113, 2007. </mixed-citation>
</ref>
<ref id="ref7">
<label>7</label><mixed-citation publication-type="other" xlink:type="simple"> Carrassi, A., Ghil, M., Trevisan, A., and Uboldi, F.: Data Assimilation as a nonlinear dynamical system problem: Stability and convergence of the prediction-assimilation system, Chaos, 18, 023112, 2008. </mixed-citation>
</ref>
<ref id="ref8">
<label>8</label><mixed-citation publication-type="other" xlink:type="simple"> Corazza, M., Kalnay, E., Patil, D., Yang, S.-C., Morss, R., Cai, M., Szunyogh, I., Hunt, B., and Yorke, J.: Use of the breeding technique to estimate the structure of the analysis &quot;error of the day&quot;, Nonlin. Processes Geophys., 10, 233–243, 2003. </mixed-citation>
</ref>
<ref id="ref9">
<label>9</label><mixed-citation publication-type="other" xlink:type="simple"> Corazza, M., Kalnay, E., and Yang, S.-C.: An implementation of the Local Ensemble Kalman filter for a simple quasi-geostrophic model: Results and comparison with a 3D-Var data assimilation system, Nonlin. Processes Geophys., 14, 89–101, 2007. </mixed-citation>
</ref>
<ref id="ref10">
<label>10</label><mixed-citation publication-type="other" xlink:type="simple"> Descamps, L. and Talagrand, O.: On some aspects of the definition of initial conditions for ensemble prediction, Mon. Wea. Rev., 135, 3260–3272, 2007. </mixed-citation>
</ref>
<ref id="ref11">
<label>11</label><mixed-citation publication-type="other" xlink:type="simple"> Etherton, B. and Bishop, C.: Resilience of hybrid ensemble/3DVAR analysis schemes to model error and ensemble covariance error, Mon. Wea. Rev.,  132, 1065–1080, 2004. </mixed-citation>
</ref>
<ref id="ref12">
<label>12</label><mixed-citation publication-type="other" xlink:type="simple"> Evensen, G.: Inverse Methods and Data Assimilation in Nonlinear Ocean Models, Physica D, 77, 108–129, 1994. </mixed-citation>
</ref>
<ref id="ref13">
<label>13</label><mixed-citation publication-type="other" xlink:type="simple"> Evensen, G.: The Ensemble Kalman Filter: theoretical formulation and practical implementation, Oc. Dyn., 53, 343–367, 2003. </mixed-citation>
</ref>
<ref id="ref14">
<label>14</label><mixed-citation publication-type="other" xlink:type="simple"> Evensen, G.: Sampling strategies and square root analysis schemes for the EnKF, Oc. Dyn., 53, 539–560, 2004. </mixed-citation>
</ref>
<ref id="ref15">
<label>15</label><mixed-citation publication-type="other" xlink:type="simple"> Gaspari, G. and Cohn, S.: Construction of correlation functions in two and three dimensions, Quart. J. Roy. Meteor. Soc., 125, 723–757, 1999. </mixed-citation>
</ref>
<ref id="ref16">
<label>16</label><mixed-citation publication-type="other" xlink:type="simple"> Hamill, T M. and Snyder, C.: A hybrid ensemble Kalman filter 3D variational scheme., Mon. Wea. Rev., 129, 2905–2919, 2000. </mixed-citation>
</ref>
<ref id="ref17">
<label>17</label><mixed-citation publication-type="other" xlink:type="simple"> Houtekamer, P L.: Global and local skill forecast, Mon. Wea. Rev., 121, 1834–1846, 1993. </mixed-citation>
</ref>
<ref id="ref18">
<label>18</label><mixed-citation publication-type="other" xlink:type="simple"> Houtekamer, P L. and Mitchell, H L.: A sequential ensemble Kalman filter fot atmospheric data assimilation, Mon. Wea. Rev., 129, 123–137, 2001. </mixed-citation>
</ref>
<ref id="ref19">
<label>19</label><mixed-citation publication-type="other" xlink:type="simple"> Hunt, B., Kostelich, E., and Szunyogh, I.: Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter, Physica D, p. in print, 2007. </mixed-citation>
</ref>
<ref id="ref20">
<label>20</label><mixed-citation publication-type="other" xlink:type="simple"> Ide, K., Courtier, P., Ghil, M., and Lorenc, A.: Unified notation for data assimilation: Operational, variational and sequential, J. Met. Soc. Japan, 75, 181–189, 1997. </mixed-citation>
</ref>
<ref id="ref21">
<label>21</label><mixed-citation publication-type="other" xlink:type="simple"> Jazwinski, A H.: Stochastic Processes and Filtering Theory, Academic Press, 1970. </mixed-citation>
</ref>
<ref id="ref22">
<label>22</label><mixed-citation publication-type="other" xlink:type="simple"> Langland, R H.: Observation Impact during the North Atlantic TReC-2003, Mon. Wea. Rev., 133, 2297–2309, 2005. </mixed-citation>
</ref>
<ref id="ref23">
<label>23</label><mixed-citation publication-type="other" xlink:type="simple"> Lorenz, E.: Predictability: A problem partly solved., Proc. Seminar on\ Predictability Vol 1, ECMWF, Reading, Berkshire, UK, 1–18, 1996. </mixed-citation>
</ref>
<ref id="ref24">
<label>24</label><mixed-citation publication-type="other" xlink:type="simple"> Morss, R., Emanuel, K., and Snyder, C.: Idealized adaptive observation strategies for improving numerical weather prediction, J. Atmos. Sci., 58, 210–232, 2001. </mixed-citation>
</ref>
<ref id="ref25">
<label>25</label><mixed-citation publication-type="other" xlink:type="simple"> Morss, R E.: Adaptive observations: Idealized sampling strategies for improving numerical weather prediction., PhD thesis, Massachusetts Institute of Technology, 1999. </mixed-citation>
</ref>
<ref id="ref26">
<label>26</label><mixed-citation publication-type="other" xlink:type="simple"> Ochotta, T., Gebhardt, C., Saupe, D., and Wergen, W.: Adaptive thinning of atmospheric observations in data assimilation with vector quantization and filtering methods, Quart. J. Roy. Meteorol. Soc., 131, 3427–3437, 2005. </mixed-citation>
</ref>
<ref id="ref27">
<label>27</label><mixed-citation publication-type="other" xlink:type="simple"> Ott, E., Hunt, B., Szunyogh, I., Zimin, A., Kostelich, E., Corazza, M., Kalnay, E., Patil, D., and Yorke, J.: A local ensemble Kalman filter for atmospheric data assimilation, Tellus, 56, 415–428, 2004. </mixed-citation>
</ref>
<ref id="ref28">
<label>28</label><mixed-citation publication-type="other" xlink:type="simple"> Patil, D., Hunt, B., Kalnay, E., Yorke, J., and Ott, E.: Local low dimensionality of atmospheric dynamics, Phys. Rev. Lett., 86, 5878–5881, 2001. </mixed-citation>
</ref>
<ref id="ref29">
<label>29</label><mixed-citation publication-type="other" xlink:type="simple"> Rotunno, R. and Bao, J.: A case study of cyclogenesis using a model hierarchy, Mon. Weather Rev., 124, 1051–1066, 1996. </mixed-citation>
</ref>
<ref id="ref30">
<label>30</label><mixed-citation publication-type="other" xlink:type="simple"> Snyder, C. and Hamill, T H.: Leading Lyapunov Vectors of a Turbolent Baroclinic Jet in a Quasigeostrophic Model, J. Atmos. Sci., 60, 683–688, 2003. </mixed-citation>
</ref>
<ref id="ref31">
<label>31</label><mixed-citation publication-type="other" xlink:type="simple"> Szunyogh, I., Toth, Z., Zimin, A., Majumdar, S., and Persson, A.: Propagation of the Effect of Targeted Observations: The 2000 Winter Storm Reconnaissance Program, Mon. Wea. Rev., 130, 1144–1165, 2002. </mixed-citation>
</ref>
<ref id="ref32">
<label>32</label><mixed-citation publication-type="other" xlink:type="simple"> Szunyogh, I., Kostelich, E., Gyarmati, G., Patil, D., Kalnay, E., Ott, E., and Yorke, J.: Assessing a local ensemble Kalman filter: Perfect model experiments with the National Center for the Environmental Prediction global model, Tellus, 57, 528–545, 2005. </mixed-citation>
</ref>
<ref id="ref33">
<label>33</label><mixed-citation publication-type="other" xlink:type="simple"> Talagrand, O.: Assimilation of observations, an introduction, J. Met. Soc. Japan, 75, 191–209, 1997. </mixed-citation>
</ref>
<ref id="ref34">
<label>34</label><mixed-citation publication-type="other" xlink:type="simple"> Tippet, M., Anderson, J., Bishop, C., Hamill, T., and Whitaker, J.: Ensemble square root filters, Mon. Wea. Rev., 131, 1485–1490, 2003. </mixed-citation>
</ref>
<ref id="ref35">
<label>35</label><mixed-citation publication-type="other" xlink:type="simple"> Toth, Z. and Kalnay, E.: Ensemble forecasting at NMC. The generation of perturbations, Bull. Amer. Meteor. Soc., 74, 2317–2330, 1993. </mixed-citation>
</ref>
<ref id="ref36">
<label>36</label><mixed-citation publication-type="other" xlink:type="simple"> Toth, Z. and Kalnay, E.: Ensemble forecasting at NCEP: the breeding method, Mon. Wea. Rev., 125, 3297–3318, 1997. </mixed-citation>
</ref>
<ref id="ref37">
<label>37</label><mixed-citation publication-type="other" xlink:type="simple"> Trevisan, A. and Pancotti, F.: Periodic orbits, Lyapunov vectors and singular vectors in the Lorenz system, J. Atmos. Sci., 55, 390–398, 1998. </mixed-citation>
</ref>
<ref id="ref38">
<label>38</label><mixed-citation publication-type="other" xlink:type="simple"> Trevisan, A. and Uboldi, F.: Assimilation of Standard and Targeted Observations within the Unstable Subspace of the Observation-Analysis-Forecast Cycle System, J. Atmos. Sci., 61, 103–113, 2004. </mixed-citation>
</ref>
<ref id="ref39">
<label>39</label><mixed-citation publication-type="other" xlink:type="simple"> Uboldi, F. and Trevisan, A.: Detecting unstable structures and controlling error growth by assimilation of standard and adaptive observations in a primitive equation ocean model, Nonlin. Processes Geophys., 13, 67–81, 2006. </mixed-citation>
</ref>
<ref id="ref40">
<label>40</label><mixed-citation publication-type="other" xlink:type="simple"> Uboldi, F., Trevisan, A., and Carrassi, A.: Developing a dynamically based assimilation method for targeted and standard observations, Nonlin. Processes Geophys., 12, 149–156, 2005. </mixed-citation>
</ref>
<ref id="ref41">
<label>41</label><mixed-citation publication-type="other" xlink:type="simple"> Wang, X., Hamill, T., Whitaker, J., and Bishop, C.: A comparison of hybrid ensemble transform Kalman filter-OI and ensemble square root filter analysis schemes, Mon. Wea. Rev., 135, 1055–1076, 2007a. </mixed-citation>
</ref>
<ref id="ref42">
<label>42</label><mixed-citation publication-type="other" xlink:type="simple"> Wang, X., Snyder, C., and Hamill, T.: On the theoretical equivalence of differently proposed ensemble-3DVAR hybrid analysis schemes, Mon. Wea. Rev.,  135, 222–227, 2007b. </mixed-citation>
</ref>
<ref id="ref43">
<label>43</label><mixed-citation publication-type="other" xlink:type="simple"> Whitaker, J. and Hamill, T.: Ensemble data assimilation without perturbed observations, Mon. Wea. Rev., 130, 1913–1924, 2002. </mixed-citation>
</ref>
<ref id="ref44">
<label>44</label><mixed-citation publication-type="other" xlink:type="simple"> Whitaker, J., Hamill, T., Wei, X., Song, Y., and Toth, Z.: Ensemble Data Assimilation with the NCEP global forecast system, Mon. Wea. Rev., 136, 463–482, 2008. </mixed-citation>
</ref>
<ref id="ref45">
<label>45</label><mixed-citation publication-type="other" xlink:type="simple"> Wolfe, C L. and Samelson, R M.: An efficient method for recovering Lyapunov vectors from singular vectors, Tellus, 59A, 355–366, 2007. </mixed-citation>
</ref>
</ref-list>
</back>
</article>