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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.
12  submitted.  </li></ul>
13    
14    <ul><li> M. Buckley, R. Ponte, G. Forget, and P. Heimbach, 2015: Determining
15    the origins of advective heat transport variability in the North Atlantic. J.
16    Clim., 18, 3943-3956.
17    </li></ul>
18    
19    <ul><li>
20    R. Chen, G. Flierl, and C. Wunsch, 2015: Quantifying and Interpreting
21    Striations in a Subtropical Gyre: A Spectral Perspective. J. Phys. Oceanogr.,
22    45, 387-406.
23    </li></ul>
24    
25    <ul><li>
26    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
28    importance of vertical resolution in sea ice algae production models.</a>
29    J. Mar. Syst., 145, 69-90.
30  </li></ul>  </li></ul>
31    
32  <ul><li>  <ul><li>
33  M. Buckley, R. Ponte, G. Forget, and P. Heimbach, 2015: Determining the  I. Fenty, D. Menemenlis, and H. Zhang, 2015:
34  origins of advective heat transport variability in the North Atlantic. J.  <a href="http://ecco2.org/manuscripts/2015/Fenty2015.pdf">
35  Clim., in revision.  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>
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
43  Weddell-Scotia Confluence.</a> J. Geophys. Res., submitted.  Weddell-Scotia Confluence.</a> J. Geophys. Res., 120, 3658-3680.
44    </li></ul>
45    
46    <ul><li>
47    G. Forget, D. Ferreira, and X. Liang, 2015: On the observability of
48    turbulent transport rates by argo: supporting evidence from an
49    inversion experiment. Ocean Science, 11, 839-853.
50  </li></ul>  </li></ul>
51    
52  <ul><li>  <ul><li>
53  G. Forget and R.M. Ponte, 2015: The partition of regional sea level  G. Forget and R.M. Ponte, 2015:
54  variability.  Prog. Oceanogr., submitted.  <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>
58    
59    <ul><li>
60    G. Forget, J.M. Campin, P. Heimbach, C.N. Hill, R.M. Ponte, and
61    C. Wunsch, 2015:
62    <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  D. Halkides, D. Waliser, T. Lee, D. Menemenlis, and B. Guan, 2015:  The ECCO Consortium (G. Forget, I. Fukumori, P. Heimbach, T. Lee, D. Menemenlis, and R.M. Ponte), 2015:
70  Quantifying the processes controlling intraseasonal mixed-layer  <a href="http://ecco2.org/manuscripts/2015/ECCO_CLIVAR.pdf">
71  temperature variability in the tropical Indian  Estimating the Circulation and Climate of the Ocean (ECCO): Advancing
72  Ocean. J. Geophys. Res., in press.  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>
81    
82    <ul><li>
83    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
85    basins of the Arctic Ocean and the Nordic Seas. Prog. Oceanogr., 134, 152-172.
86    </li></ul>
87    
88    <ul><li>
89    D. Halkides, D. Waliser, T. Lee, D. Menemenlis, and B. Guan,
90    2015: <a href="http://ecco2.org/manuscripts/2015/Halkides2015.pdf">
91    Quantifying the processes controlling intraseasonal mixed-layer temperature
92    variability in the tropical Indian Ocean.</a> J. Geophys. Res., 120, 692-715.
93  </li></ul>  </li></ul>
94    
95  <ul><li>  <ul><li>
# Line 46  Tech., 32, 131-143. Line 101  Tech., 32, 131-143.
101  </li></ul>  </li></ul>
102    
103  <ul><li>  <ul><li>
104    P. Heimbach, 2015: Application of derivative code in climate modeling.
105    in: N. Gauger, M. Giles, M. Gunzburger, and U. Naumann (eds.):
106    Adjoint Methods in Computational Science, Engineering, and Finance.
107    Dagstuhl Reports, 4, 14-16.
108    </li></ul>
109    
110    <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. Submitted.  Vertical redistribution of oceanic heat. J. Clim., 28, 3821-3833.
120  </ul></li>  </ul></li>
121    
122  <ul><li>  <ul><li>
123  L. Ott, S. Pawson, J. Collatz, W. Gregg, D. Menemenlis, H. Brix,  K. McCaffrey, B. Fox-Kemper, and G. Forget, 2015: Estimates of Ocean
124  C. Rousseaux, K. Bowman, J. Liu, A. Eldering, M. Gunson, S. Kawa,  Macro-turbulence: Structure Function and Spectral Slope from Argo Profiling
125  2015: Quantifying the observability of CO2 flux uncertainty in  Floats. J. Phys. Oceanogr., 45, 1773-1793.
126  atmospheric CO2 records using products from NASA's Carbon Monitoring  </ul></li>
127  Flux Pilot Project. J. Geophys. Res., in press.  
128    <ul><li>
129    L. Ott, S. Pawson, G. Collatz, W. Gregg, D. Menemenlis, H. Brix, C. Rousseaux,
130    K. Bowman, J. Liu, A. Eldering, M. Gunson, and S. Kawa,
131    2015: <a href="http://ecco2.org/manuscripts/2015/Ott2015.pdf"> Assessing the
132    magnitude of CO2 flux uncertainty in atmospheric CO2 records using products
133    from NASA's Carbon Monitoring Flux Pilot Project.</a>  J. Geophys. Res., 120,
134    734-765.
135  </li></ul>  </li></ul>
136    
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  structure  of ocean pressure fluctuations with application to
140  to satellite-gravimetric observations. J. Atmos. Oce. Tech., in revision.  satellite-gravimetric observations. J. Atmos. Oce. Tech., 32, 603-613.
141    </li></ul>
142    
143    <ul><li>
144    C. Piecuch, P. Heimbach, R.M. Ponte, and G. Forget, 2015: Sensitivity
145    of contemporary sea level trends in a global ocean state estimate to effects
146    of geothermal fluxes, Ocean Model., 96, 214-220.
147    </li></ul>
148    
149    <ul><li>
150    K. J. Quinn, R. M. Ponte, and M. E. Tamisiea, 2015: Impact of self-attraction
151    and loading on Earth rotation. J. Geophys. Res., 120, 4510–4521.
152    </li></ul>
153    
154    <ul><li>
155    A. Storto, and 36 others, 2015: Steric sea level variability (1993-2010) in an
156    ensemble of ocean reanalyses and objective analyses. Clim. Dyn.,
157    doi:10.1007/s00382-015-2554-9
158    </li></ul>
159    
160    <ul><li>
161    Toyoda, T., and 32 others, 2015: Interannual-decadal variability of wintertime
162    mixed layer depths in the north pacific detected by an ensemble of ocean
163    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>  </li></ul>
171    
172  <ul><li>  <ul><li>
173  G. Spreen, R. Kwok, D. Menemenlis, and A. Nguyen, 2015: Sea ice  T. Van der Stocken, 2015:
174  deformation in a coupled ocean-sea ice model and in satellite remote  <a href="http://ecco2.org/manuscripts/2015/Stocken2015.pdf"> Biological and
175  sensing data. J. Geophys. Res., submitted.  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>
180  N. Vinogradova, R. Ponte, K. Quinn, M. Tamisiea, J. Campin,  N. Vinogradova, R. Ponte, K. Quinn, M. Tamisiea, J.M. Campin, and J. Davis,
181  and J. Davis, 2015: Dynamic adjustment of the ocean circulation to  2015: Dynamic Adjustment of the Ocean Circulation to Self-Attraction and
182  self-attraction and loading effects, J. Phys. Oceanogr., in revision.  Loading Effects.  J. Phys. Oceanogr., 45, 678-689.
183  </li></ul>  </li></ul>
184    
185  <ul><li>  <ul><li>
186  J. Whitefield, P. Winsor, J. McClelland, and D. Menemenlis, 2015: A new river  X. Wang, L. Zhao, Z. Li, and D. Menemenlis, 2015:
187  discharge and river temperature data set for the pan-Arctic region. Ocean  <a href="http://ecco2.org/manuscripts/2015/Wang2015.pdf">
188  Modelling, in press.  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>  </li></ul>
192    
193  <ul><li>  <ul><li>
194  S. Zedler, C. Jackson, F. Yao, P. Heimbach, A. Koehl, R. Scott, and  J. Whitefield, P. Winsor, J. McClelland, and D. Menemenlis,
195  I. Hoteit, 2015: Tests of the K-Profile Parameterization of turbulent  2015: <a href="http://ecco2.org/manuscripts/2015/Whitefield2015.pdf"> A new
196  vertical mixing using seasonally averaged observations from the  river discharge and river temperature climatology data set for the
197  TOGA/TAO array from 2004 to 2007. Ocean Modelling., in revision.  pan-Arctic region.</a> Ocean Model., 88, 1-15.
198    </li></ul>
199    
200    <ul><li>
201    C. Yan, J. Zhu, and J. Xie, 2015: An ocean data assimilation system in the
202    Indian Ocean and west Pacific Ocean. Adv. Atmos. Sci., 32,
203    1460-1472.
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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