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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 8  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 24  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 38  J. Mar. Syst., 145, 69-90. Line 30  J. Mar. Syst., 145, 69-90.
30  </li></ul>  </li></ul>
31    
32  <ul><li>  <ul><li>
33    I. Fenty, D. Menemenlis, and H. Zhang, 2015:
34    <a href="http://ecco2.org/manuscripts/2015/Fenty2015.pdf">
35    Global Coupled Sea Ice-Ocean State Estimation.</a> Clim. Dyn.,
36    doi:10.1007/s00382-015-2796-6
37    </li></ul>
38    
39    <ul><li>
40  M.M. Flexas, M. Schodlok, L. Padman, D. Menemenlis, and A. Orsi, 2015:  M.M. Flexas, M. Schodlok, L. Padman, D. Menemenlis, and A. Orsi, 2015:
41  <a href="http://ecco2.org/manuscripts/2015/Flexas2015.pdf">  <a href="http://ecco2.org/manuscripts/2015/Flexas2015.pdf">
42  Role of tides on the formation of the Antarctic Slope Front at the  Role of tides on the formation of the Antarctic Slope Front at the
# Line 45  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., accepted.  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. Geosci. Model Dev. Discuss., 8, 3653-3743.  <a href="http://www.geosci-model-dev.net/8/3071/2015/gmd-8-3071-2015.pdf">
63    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  V. Le Fouest, M. Manizza, B. Tremblay, and M. Babin, 2015:  The ECCO Consortium (G. Forget, I. Fukumori, P. Heimbach, T. Lee, D. Menemenlis, and R.M. Ponte), 2015:
70  <a href="http://www.biogeosciences.net/12/3385/2015/bg-12-3385-2015.html">  <a href="http://ecco2.org/manuscripts/2015/ECCO_CLIVAR.pdf">
71  Modeling the impact of riverine DON removal by marine bacterioplankton on  Estimating the Circulation and Climate of the Ocean (ECCO): Advancing
72  primary production in the Arctic Ocean.</a> Biogeosciences, 12, 3385-3402.  CLIVAR Science.</a> CLIVAR Exchanges, 67, 41-45.
73    </ul></li>
74    
75    <ul><li>
76    I. Fukumori, 2015: Combining models and data in large-scale oceanography:
77    Examples from the Consortium for Estimating the Circulation and Climate of the
78    Ocean (ECCO). Advanced Data Assimilation for Geosciences: Lecture Notes of the
79    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 92  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 108  from NASA's Carbon Monitoring Flux Pilot Line 137  from NASA's Carbon Monitoring Flux Pilot
137  <ul><li>  <ul><li>
138  C. Piecuch, I. Fukumori, R. Ponte, and O. Wang, 2015: Vertical  C. Piecuch, I. Fukumori, R. Ponte, and O. Wang, 2015: Vertical
139  structure  of ocean pressure fluctuations with application to  structure  of ocean pressure fluctuations with application to
140  satellite-gravimetric observations. J. Atmos. Oce. Tech., in press.  satellite-gravimetric observations. J. Atmos. Oce. Tech., 32, 603-613.
141  </li></ul>  </li></ul>
142    
143  <ul><li>  <ul><li>
144  G. Spreen, R. Kwok, D. Menemenlis, and A. Nguyen, 2015: Sea ice  C. Piecuch, P. Heimbach, R.M. Ponte, and G. Forget, 2015: Sensitivity
145  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
146  sensing data. J. Geophys. Res., submitted.  of geothermal fluxes, Ocean Model., 96, 214-220.
147  </li></ul>  </li></ul>
148    
149  <ul><li>  <ul><li>
150  T. Van der Stocken, 2015:  K. J. Quinn, R. M. Ponte, and M. E. Tamisiea, 2015: Impact of self-attraction
151  <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.  
152  </li></ul>  </li></ul>
153    
154  <ul><li>  <ul><li>
155  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
156  ensemble of ocean reanalyses and objective analyses. Clim. Dyn., in press,  ensemble of ocean reanalyses and objective analyses. Clim. Dyn.,
157  doi:10.1007/s00382-015-2554-9  doi:10.1007/s00382-015-2554-9
158  </li></ul>  </li></ul>
159    
160  <ul><li>  <ul><li>
161  T. Toyoda, and 32 others, 2015: Intercomparison and validation of the mixed  Toyoda, T., and 32 others, 2015: Interannual-decadal variability of wintertime
162  layer depth fields of global ocean syntheses/reanalyses. Clim. Dyn., in press,  mixed layer depths in the north pacific detected by an ensemble of ocean
163  doi:10.1007/s00382-015-2637-7.  syntheses. Clim. Dyn., doi:10.1007/s00382-015-2762-3
164    </li></ul>
165    
166    <ul><li>
167    T. Toyoda, and 32 others, 2015: Intercomparison and validation of the
168    mixed layer depth fields of global ocean syntheses. Clim. Dyn.,
169    doi:10.1007/s00382-015-2637-7
170    </li></ul>
171    
172    <ul><li>
173    T. Van der Stocken, 2015:
174    <a href="http://ecco2.org/manuscripts/2015/Stocken2015.pdf"> Biological and
175    environmental drivers of mangrove propagule dispersal: A field and modeling
176    approach.</a>  Ph.D. Thesis, Vrije Universiteit Brussel and the Universite Libre de Bruxelles.
177  </li></ul>  </li></ul>
178    
179  <ul><li>  <ul><li>
# Line 144  Loading Effects.  J. Phys. Oceanogr., 45 Line 183  Loading Effects.  J. Phys. Oceanogr., 45
183  </li></ul>  </li></ul>
184    
185  <ul><li>  <ul><li>
186    X. Wang, L. Zhao, Z. Li, and D. Menemenlis, 2015:
187    <a href="http://ecco2.org/manuscripts/2015/Wang2015.pdf">
188    Regional ocean forecasting systems and their applications: Design
189    consideration of such a system for the South China Sea.</a>
190    Aquat. Ecosyst. Health Manag., 18, 443-453.
191    </li></ul>
192    
193    <ul><li>
194  J. Whitefield, P. Winsor, J. McClelland, and D. Menemenlis,  J. Whitefield, P. Winsor, J. McClelland, and D. Menemenlis,
195  2015: <a href="http://ecco2.org/manuscripts/2015/Whitefield2015.pdf"> A new  2015: <a href="http://ecco2.org/manuscripts/2015/Whitefield2015.pdf"> A new
196  river discharge and river temperature climatology data set for the  river discharge and river temperature climatology data set for the
197  pan-Arctic region.</a> Ocean Modelling, 88, 1-15.  pan-Arctic region.</a> Ocean Model., 88, 1-15.
198  </li></ul>  </li></ul>
199    
200  <ul><li>  <ul><li>
201  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
202  I. Hoteit, 2015: Tests of the K-Profile Parameterization of turbulent  Indian Ocean and west Pacific Ocean. Adv. Atmos. Sci., 32,
203  vertical mixing using seasonally averaged observations from the  1460-1472.
 TOGA/TAO array from 2004 to 2007. Ocean Modelling., in revision.  
204  </li></ul>  </li></ul>
205    
206  <ul><li>  <ul><li>
207  V. Zemskova, B. White, and A. Scotti, 2015: Available potential energy  V. Zemskova, B. White, and A. Scotti, 2015: Available potential energy
208  and the general circulation: Partitioning wind, buoyancy forcing, and  and the general circulation: Partitioning wind, buoyancy forcing, and
209  irreversible mixing. J. Phys. Oceanogr., submitted.  irreversible mixing. J. Phys. Oceanogr., 45, 1510-1531.
210    </li></ul>
211    
212    <ul><li>
213    Y. Zhang, D. Jacob, S. Dutkiewicz, H. Amos, M. Long, and E. Sunderland, 2015:
214    Biogeochemical drivers of the fate of riverine mercury discharged to the
215    global and Arctic oceans. Global Biogeochem. Cycles, 29, 854-864.
216  </li></ul>  </li></ul>
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