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 <ul><li>  
 Forget, G., D. Ferreira, and X. Liang, 2015: On the observability of  
 turbulent transport rates by argo: supporting evidence from an  
 inversion experiment. Ocean Science, 11, 839-853, doi:10.5194/os-11-839-2015.  
 </li></ul>  
   
 <ul><li>  
 Piecuch, C. G., P. Heimbach, R. M. Ponte, and G. Forget, 2015: Sensitivity  
 of contemporary sea level trends in a global ocean state estimate to effects  
 of geothermal fluxes, Ocean Model., in press.  
 </li></ul>  
   
1  <ul><li>  <ul><li>
2  R. Abernathey, D. Ferreira, and A. Klocker, 2015: Diagnostics of eddy  M. Balmaseda, M., et al., 2015: The ocean reanalyses intercomparison project
3  mixing in a circumpolar channel. Ocean Modelling, submitted.  (ora-ip). J. Oper. Oceanogr., 8 (sup1), s80-s97.
4  </li></ul>  </li></ul>
5    
6  <ul><li>  <ul><li>
# Line 21  H. Brix, D. Menemenlis, C. Hill, S. Dutk Line 8  H. Brix, D. Menemenlis, C. Hill, S. Dutk
8  K. Bowman, and H. Zhang, 2015:  K. Bowman, and H. Zhang, 2015:
9  <a href="http://ecco2.org/manuscripts/2015/Brix2015.pdf"> Using  <a href="http://ecco2.org/manuscripts/2015/Brix2015.pdf"> Using
10  Green's Functions to initialize and adjust a global, eddying ocean  Green's Functions to initialize and adjust a global, eddying ocean
11  biogeochemistry general circulation model.</a> Ocean Modelling,  biogeochemistry general circulation model.</a> Ocean Model., 95, 1-14.
 in press.  
12  </li></ul>  </li></ul>
13    
14  <ul><li> M. Buckley, R. Ponte, G. Forget, and P. Heimbach, 2015: Determining  <ul><li> M. Buckley, R. Ponte, G. Forget, and P. Heimbach, 2015: Determining
# Line 37  Striations in a Subtropical Gyre: A Spec Line 23  Striations in a Subtropical Gyre: A Spec
23  </li></ul>  </li></ul>
24    
25  <ul><li>  <ul><li>
 K. Childers, 2015:  
 <a href="http://ecco2.org/manuscripts/2015/Childers2015.pdf">  
 Circulation and Transport Across the Iceland Faroes Shetland Ridge.</a>  
 Ph.D. Thesis, Marine and Atmospheric Science, Stony Brook University, NY.  
 </li></ul>  
   
 <ul><li>  
26  P. Duarte, P. Assmy, H. Hop, G. Spreen, S. Gerland, and S. Hudson,  P. Duarte, P. Assmy, H. Hop, G. Spreen, S. Gerland, and S. Hudson,
27  2015: <a href="http://ecco2.org/manuscripts/2015/Duarte2015.pdf"> The  2015: <a href="http://ecco2.org/manuscripts/2015/Duarte2015.pdf"> The
28  importance of vertical resolution in sea ice algae production models.</a>  importance of vertical resolution in sea ice algae production models.</a>
# Line 53  J. Mar. Syst., 145, 69-90. Line 32  J. Mar. Syst., 145, 69-90.
32  <ul><li>  <ul><li>
33  I. Fenty, D. Menemenlis, and H. Zhang, 2015:  I. Fenty, D. Menemenlis, and H. Zhang, 2015:
34  <a href="http://ecco2.org/manuscripts/2015/Fenty2015.pdf">  <a href="http://ecco2.org/manuscripts/2015/Fenty2015.pdf">
35  Global Coupled Sea Ice-Ocean State Estimation.</a> Clim. Dyn., in press.  Global Coupled Sea Ice-Ocean State Estimation.</a> Clim. Dyn.,
36    doi:10.1007/s00382-015-2796-6
37  </li></ul>  </li></ul>
38    
39  <ul><li>  <ul><li>
# Line 64  Weddell-Scotia Confluence.</a> J. Geophy Line 44  Weddell-Scotia Confluence.</a> J. Geophy
44  </li></ul>  </li></ul>
45    
46  <ul><li>  <ul><li>
47  G. Forget and R.M. Ponte, 2015: The partition of regional sea level  G. Forget, D. Ferreira, and X. Liang, 2015: On the observability of
48  variability.  Prog. Oceanogr., (137), 173-195, doi:10.1016/j.pocean.2015.06.002.  turbulent transport rates by argo: supporting evidence from an
49    inversion experiment. Ocean Science, 11, 839-853.
50    </li></ul>
51    
52    <ul><li>
53    G. Forget and R.M. Ponte, 2015:
54    <a href="http://www.sciencedirect.com/science/article/pii/S0079661115001354">
55    The partition of regional sea level variability.</a> Prog. Oceanogr.,
56    137, 173-195.
57  </ul></li>  </ul></li>
58    
59  <ul><li>  <ul><li>
60  G. Forget, J.M. Campin, P. Heimbach, C.N. Hill, R.M. Ponte, and C. Wunsch,  G. Forget, J.M. Campin, P. Heimbach, C.N. Hill, R.M. Ponte, and
61  2015: ECCO version 4: an integrated framework for non-linear inverse modeling  C. Wunsch, 2015:
62  and global ocean state estimation. Geoscientific Model Development, 8,  <a href="http://www.geosci-model-dev.net/8/3071/2015/gmd-8-3071-2015.pdf">
63  3071-3104, doi:10.5194/gmd-8-3071-2015.  ECCO version 4: an integrated framework for non-linear inverse
64    modeling and global ocean state estimation.</a> Geosci. Model Dev., 8,
65    3071-3104.
66  </ul></li>  </ul></li>
67    
68  <ul><li>  <ul><li>
69  McCaffrey, K., B. Fox-Kemper, and G. Forget, 2015: Estimates of Ocean  The ECCO Consortium (G. Forget, I. Fukumori, P. Heimbach, T. Lee, D. Menemenlis, and R.M. Ponte), 2015:
70  Macro-turbulence: Structure Function and Spectral Slope from Argo Profiling  <a href="http://ecco2.org/manuscripts/2015/ECCO_CLIVAR.pdf">
71  Floats. JPO, 45, 1773-1793.  Estimating the Circulation and Climate of the Ocean (ECCO): Advancing
72    CLIVAR Science.</a> CLIVAR Exchanges, 67, 41-45.
73  </ul></li>  </ul></li>
74    
75  <ul><li>  <ul><li>
76  V. Le Fouest, M. Manizza, B. Tremblay, and M. Babin, 2015:  I. Fukumori, 2015: Combining models and data in large-scale oceanography:
77  <a href="http://www.biogeosciences.net/12/3385/2015/bg-12-3385-2015.html">  Examples from the Consortium for Estimating the Circulation and Climate of the
78  Modeling the impact of riverine DON removal by marine bacterioplankton on  Ocean (ECCO). Advanced Data Assimilation for Geosciences: Lecture Notes of the
79  primary production in the Arctic Ocean.</a> Biogeosciences, 12, 3385-3402.  Les Houches School of Physics: Special Issue, June 2012.
80  </li></ul>  </li></ul>
81    
82  <ul><li>  <ul><li>
83  I. Fukumori, O. Wang, W. Llovel, I. Fenty, and G. Forget, 2015: A near-uniform  I. Fukumori, O. Wang, W. Llovel, I. Fenty and G. Forget, 2015: A near-uniform
84  fluctuation of ocean bottom pressure and sea level across the deep ocean  fluctuation of ocean bottom pressure and sea level across the deep ocean
85  basins of the Arctic Ocean and the Nordic Seas.  Prog. Oceanogr., 134,  basins of the Arctic Ocean and the Nordic Seas. Prog. Oceanogr., 134, 152-172.
86  152-172.  </li></ul>
 </ul></li>  
87    
88  <ul><li>  <ul><li>
89  D. Halkides, D. Waliser, T. Lee, D. Menemenlis, and B. Guan,  D. Halkides, D. Waliser, T. Lee, D. Menemenlis, and B. Guan,
# Line 118  Dagstuhl Reports, 4, 14-16. Line 108  Dagstuhl Reports, 4, 14-16.
108  </li></ul>  </li></ul>
109    
110  <ul><li>  <ul><li>
111    V. Le Fouest, M. Manizza, B. Tremblay, and M. Babin, 2015:
112    <a href="http://www.biogeosciences.net/12/3385/2015/bg-12-3385-2015.html">
113    Modeling the impact of riverine DON removal by marine bacterioplankton on
114    primary production in the Arctic Ocean.</a> Biogeosciences, 12, 3385-3402.
115    </li></ul>
116    
117    <ul><li>
118  X. Liang, C. Wunsch, P. Heimbach, and G. Forget, 2015:  X. Liang, C. Wunsch, P. Heimbach, and G. Forget, 2015:
119  Vertical redistribution of oceanic heat. 28, 3821-3833.  Vertical redistribution of oceanic heat. J. Clim., 28, 3821-3833.
120    </ul></li>
121    
122    <ul><li>
123    K. McCaffrey, B. Fox-Kemper, and G. Forget, 2015: Estimates of Ocean
124    Macro-turbulence: Structure Function and Spectral Slope from Argo Profiling
125    Floats. J. Phys. Oceanogr., 45, 1773-1793.
126  </ul></li>  </ul></li>
127    
128  <ul><li>  <ul><li>
# Line 132  from NASA's Carbon Monitoring Flux Pilot Line 135  from NASA's Carbon Monitoring Flux Pilot
135  </li></ul>  </li></ul>
136    
137  <ul><li>  <ul><li>
138    C. Piecuch, 2015: Bottom-pressure signature of annual baroclinic
139    Rossby waves in the northeast tropical Pacific Ocean. J. Geophys.
140    Res., 120, 2449-2459.
141    </li></ul>
142    
143    <ul><li>
144  C. Piecuch, I. Fukumori, R. Ponte, and O. Wang, 2015: Vertical  C. Piecuch, I. Fukumori, R. Ponte, and O. Wang, 2015: Vertical
145  structure  of ocean pressure fluctuations with application to  structure  of ocean pressure fluctuations with application to
146  satellite-gravimetric observations. J. Atmos. Oce. Tech., in press.  satellite-gravimetric observations. J. Atmos. Oce. Tech., 32, 603-613.
147  </li></ul>  </li></ul>
148    
149  <ul><li>  <ul><li>
150  G. Spreen, R. Kwok, D. Menemenlis, and A. Nguyen, 2015: Sea ice  C. Piecuch, P. Heimbach, R.M. Ponte, and G. Forget, 2015: Sensitivity
151  deformation in a coupled ocean-sea ice model and in satellite remote  of contemporary sea level trends in a global ocean state estimate to effects
152  sensing data. J. Geophys. Res., submitted.  of geothermal fluxes, Ocean Model., 96, 214-220.
153  </li></ul>  </li></ul>
154    
155  <ul><li>  <ul><li>
156  T. Van der Stocken, 2015:  K. J. Quinn, R. M. Ponte, and M. E. Tamisiea, 2015: Impact of self-attraction
157  <a href="http://ecco2.org/manuscripts/2015/Stocken2015.pdf"> Biological and  and loading on Earth rotation. J. Geophys. Res., 120, 4510–4521.
 environmental drivers of mangrove propagule dispersal: A field and modeling  
 approach.</a>  Ph.D. Thesis, Vrije Universiteit Brussel and the Université  
 Libre de Bruxelles.  
158  </li></ul>  </li></ul>
159    
160  <ul><li>  <ul><li>
161  A. Storto, and 36 others, 2015: Steric sea level variability (1993-2010) in an  A. Storto, and 36 others, 2015: Steric sea level variability (1993-2010) in an
162  ensemble of ocean reanalyses and objective analyses. Clim. Dyn., in press,  ensemble of ocean reanalyses and objective analyses. Clim. Dyn.,
163  doi:10.1007/s00382-015-2554-9  doi:10.1007/s00382-015-2554-9
164  </li></ul>  </li></ul>
165    
166  <ul><li>  <ul><li>
167  Toyoda, T., and 32 others, 2015: Interannual-decadal variability of wintertime  Toyoda, T., and 32 others, 2015: Interannual-decadal variability of wintertime
168  mixed layer depths in the north pacific detected by an ensemble of ocean syntheses.  mixed layer depths in the north pacific detected by an ensemble of ocean
169  Climate Dynamics, 1-17, doi:10.1007/s00382-015-2762-3.  syntheses. Clim. Dyn., doi:10.1007/s00382-015-2762-3
170    </li></ul>
171    
172    <ul><li>
173    T. Toyoda, and 32 others, 2015: Intercomparison and validation of the
174    mixed layer depth fields of global ocean syntheses. Clim. Dyn.,
175    doi:10.1007/s00382-015-2637-7
176  </li></ul>  </li></ul>
177    
178  <ul><li>  <ul><li>
179  T. Toyoda, and 32 others, 2015: Intercomparison and validation of the mixed  T. Van der Stocken, 2015:
180  layer depth fields of global ocean syntheses/reanalyses. Clim. Dyn., in press,  <a href="http://ecco2.org/manuscripts/2015/Stocken2015.pdf"> Biological and
181  doi:10.1007/s00382-015-2637-7.  environmental drivers of mangrove propagule dispersal: A field and modeling
182    approach.</a>  Ph.D. Thesis, Vrije Universiteit Brussel and the Universite
183    Libre de Bruxelles.
184    </li></ul>
185    
186    <ul><li>
187    E. Villar, G. Farrant, M. Follows, et al, 2015, Environmental characteristics
188    of Agulhas rings affect interocean plankton transport, Science, Vol. 348,
189    6237.
190  </li></ul>  </li></ul>
191    
192  <ul><li>  <ul><li>
# Line 176  Loading Effects.  J. Phys. Oceanogr., 45 Line 196  Loading Effects.  J. Phys. Oceanogr., 45
196  </li></ul>  </li></ul>
197    
198  <ul><li>  <ul><li>
199    X. Wang, L. Zhao, Z. Li, and D. Menemenlis, 2015:
200    <a href="http://ecco2.org/manuscripts/2015/Wang2015.pdf">
201    Regional ocean forecasting systems and their applications: Design
202    consideration of such a system for the South China Sea.</a>
203    Aquat. Ecosyst. Health Manag., 18, 443-453.
204    </li></ul>
205    
206    <ul><li>
207  J. Whitefield, P. Winsor, J. McClelland, and D. Menemenlis,  J. Whitefield, P. Winsor, J. McClelland, and D. Menemenlis,
208  2015: <a href="http://ecco2.org/manuscripts/2015/Whitefield2015.pdf"> A new  2015: <a href="http://ecco2.org/manuscripts/2015/Whitefield2015.pdf"> A new
209  river discharge and river temperature climatology data set for the  river discharge and river temperature climatology data set for the
210  pan-Arctic region.</a> Ocean Modelling, 88, 1-15.  pan-Arctic region.</a> Ocean Model., 88, 1-15.
211  </li></ul>  </li></ul>
212    
213  <ul><li>  <ul><li>
214  S. Zedler, C. Jackson, F. Yao, P. Heimbach, A. Koehl, R. Scott, and  C. Yan, J. Zhu, and J. Xie, 2015: An ocean data assimilation system in the
215  I. Hoteit, 2015: Tests of the K-Profile Parameterization of turbulent  Indian Ocean and west Pacific Ocean. Adv. Atmos. Sci., 32,
216  vertical mixing using seasonally averaged observations from the  1460-1472.
 TOGA/TAO array from 2004 to 2007. Ocean Modelling., in revision.  
217  </li></ul>  </li></ul>
218    
219  <ul><li>  <ul><li>
220  V. Zemskova, B. White, and A. Scotti, 2015: Available potential energy  V. Zemskova, B. White, and A. Scotti, 2015: Available potential energy
221  and the general circulation: Partitioning wind, buoyancy forcing, and  and the general circulation: Partitioning wind, buoyancy forcing, and
222  irreversible mixing. J. Phys. Oceanogr., submitted.  irreversible mixing. J. Phys. Oceanogr., 45, 1510-1531.
223  </li></ul>  </li></ul>
224    
225  <ul><li>  <ul><li>
226  Balmaseda, M., et al., 2015: The ocean reanalyses intercomparison project  Y. Zhang, D. Jacob, S. Dutkiewicz, H. Amos, M. Long, and E. Sunderland, 2015:
227  (ora-ip). Journal of Operational Oceanography, 8 (sup1), s80-s97,  Biogeochemical drivers of the fate of riverine mercury discharged to the
228  doi:10.1080/1755876X.2015.1022329.  global and Arctic oceans. Global Biogeochem. Cycles, 29, 854-864.
229  </li></ul>  </li></ul>
   
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