Articles | Volume 15, issue 6
https://doi.org/10.5194/cp-15-1985-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-15-1985-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Can we use sea surface temperature and productivity proxy records to reconstruct Ekman upwelling?
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI 02912, USA
Baylor Fox-Kemper
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI 02912, USA
Timothy Herbert
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI 02912, USA
Related authors
No articles found.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Gustavo M. Marques, Nora Loose, Elizabeth Yankovsky, Jacob M. Steinberg, Chiung-Yin Chang, Neeraja Bhamidipati, Alistair Adcroft, Baylor Fox-Kemper, Stephen M. Griffies, Robert W. Hallberg, Malte F. Jansen, Hemant Khatri, and Laure Zanna
Geosci. Model Dev., 15, 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022, https://doi.org/10.5194/gmd-15-6567-2022, 2022
Short summary
Short summary
We present an idealized ocean model configuration and a set of simulations performed using varying horizontal grid spacing. While the model domain is idealized, it resembles important geometric features of the Atlantic and Southern oceans. The simulations described here serve as a framework to effectively study mesoscale eddy dynamics, to investigate the effect of mesoscale eddies on the large-scale dynamics, and to test and evaluate eddy parameterizations.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary
Short summary
Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Timothy D. Herbert, Rocio Caballero-Gill, and Joseph B. Novak
Clim. Past, 17, 1385–1394, https://doi.org/10.5194/cp-17-1385-2021, https://doi.org/10.5194/cp-17-1385-2021, 2021
Short summary
Short summary
The Pliocene represents a geologically warm period with polar ice restricted to the Antarctic. Nevertheless, variability and ice volume persisted in the Pliocene. This work revisits a classic site on which much of our understanding of Pliocene paleoclimate variability is based and corrects errors in data sets related to ice volume and ocean surface temperature. In particular, it generates an improved representation of an enigmatic glacial episode in Pliocene times (circa 3.3 Ma).
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
Short summary
Short summary
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
Short summary
Short summary
The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Valentin Resseguier, Wei Pan, and Baylor Fox-Kemper
Nonlin. Processes Geophys., 27, 209–234, https://doi.org/10.5194/npg-27-209-2020, https://doi.org/10.5194/npg-27-209-2020, 2020
Short summary
Short summary
Geophysical flows span a broader range of temporal and spatial scales than can be resolved numerically. One way to alleviate the ensuing numerical errors is to combine simulations with measurements, taking account of the accuracies of these two sources of information. Here we quantify the distribution of numerical simulation errors without relying on high-resolution numerical simulations. Specifically, small-scale random vortices are added to simulations while conserving energy or circulation.
Christopher Horvat, Lettie A. Roach, Rachel Tilling, Cecilia M. Bitz, Baylor Fox-Kemper, Colin Guider, Kaitlin Hill, Andy Ridout, and Andrew Shepherd
The Cryosphere, 13, 2869–2885, https://doi.org/10.5194/tc-13-2869-2019, https://doi.org/10.5194/tc-13-2869-2019, 2019
Short summary
Short summary
Changes in the floe size distribution (FSD) are important for sea ice evolution but to date largely unobserved and unknown. Climate models, forecast centres, ship captains, and logistic specialists cannot currently obtain statistical information about sea ice floe size on demand. We develop a new method to observe the FSD at global scales and high temporal and spatial resolution. With refinement, this method can provide crucial information for polar ship routing and real-time forecasting.
Seonmin Ahn, Baylor Fox-Kemper, Timothy Herbert, and Charles Lawrence
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-1, https://doi.org/10.5194/cp-2018-1, 2018
Revised manuscript not accepted
Arin D. Nelson, Jeffrey B. Weiss, Baylor Fox-Kemper, Royce K. P. Zia, and Fabienne Gaillard
Ocean Sci. Discuss., https://doi.org/10.5194/os-2016-105, https://doi.org/10.5194/os-2016-105, 2017
Revised manuscript has not been submitted
Short summary
Short summary
We quantify the skill in observing the variability of global upper ocean heat content (OHC) by applying the ISAS13 observing strategy to a CCSM simulation. We find that variability is unreliably observed before 2005, while observed annual running means for 2005–2013 correlate well with model "truth" to a median of 95 %. When scaled to the real ocean, we find signal-to-noise ratios of 1.9 for pre-Argo times (1990–2005) and 14.7 after Argo is introduced (2005–2013). The global warming is robust.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Related subject area
Subject: Proxy Use-Development-Validation | Archive: Marine Archives | Timescale: Centennial-Decadal
Palaeoceanographic changes in Hornsund Fjord (Spitsbergen, Svalbard) over the last millennium: new insights from ancient DNA
Development of coccolithophore-based transfer functions in the western Mediterranean sea: a sea surface salinity reconstruction for the last 15.5 kyr
A high-resolution δ18O record and Mediterranean climate variability
Nutrient utilisation and weathering inputs in the Peruvian upwelling region since the Little Ice Age
Multidecadal to millennial marine climate oscillations across the Denmark Strait (~ 66° N) over the last 2000 cal yr BP
An inter-laboratory investigation of the Arctic sea ice biomarker proxy IP25 in marine sediments: key outcomes and recommendations
Inferred changes in El Niño–Southern Oscillation variance over the past six centuries
Joanna Pawłowska, Marek Zajączkowski, Magdalena Łącka, Franck Lejzerowicz, Philippe Esling, and Jan Pawlowski
Clim. Past, 12, 1459–1472, https://doi.org/10.5194/cp-12-1459-2016, https://doi.org/10.5194/cp-12-1459-2016, 2016
Short summary
Short summary
The presented study focuses on the last millennium of the palaeoclimatic history of Svalbard region. The investigation was based on classical palaeoceanographic proxies, strengthened by the analysis of ancient foraminiferal DNA in down-core sediment samples. This study is the first attempt to implement the aDNA record in the palaeoenvironmental reconstruction. The aDNA data revealed even small environmetal changes that were not evidenced in the sedimentological and micropalaeontological record.
B. Ausín, I. Hernández-Almeida, J.-A. Flores, F.-J. Sierro, M. Grosjean, G. Francés, and B. Alonso
Clim. Past, 11, 1635–1651, https://doi.org/10.5194/cp-11-1635-2015, https://doi.org/10.5194/cp-11-1635-2015, 2015
Short summary
Short summary
Coccolithophore distribution in 88 surface sediment samples in the Atlantic Ocean and western Mediterranean was mainly influenced by salinity at 10m depth. A quantitative coccolithophore-based transfer function was developed and applied to a fossil sediment core to estimate sea surface salinity (SSS). The quality of this function and the reliability of the SSS reconstruction were assessed by statistical analyses and discussed. Several centennial SSS changes are identified for the last 15.5 ka.
C. Taricco, G. Vivaldo, S. Alessio, S. Rubinetti, and S. Mancuso
Clim. Past, 11, 509–522, https://doi.org/10.5194/cp-11-509-2015, https://doi.org/10.5194/cp-11-509-2015, 2015
Short summary
Short summary
The key to gaining information on climate over the last millennia is the study of proxy records in ice and sediment cores, trees, etc. We measured the oxygen isotopic ratio in planktonic foraminifera of a high-resolution, well-dated central Mediterranean core.
The comparison between the variability detected in this core and that characterizing the Northern Hemisphere allows for local and global (hemispheric) climate variations to be distinguished.
C. Ehlert, P. Grasse, D. Gutiérrez, R. Salvatteci, and M. Frank
Clim. Past, 11, 187–202, https://doi.org/10.5194/cp-11-187-2015, https://doi.org/10.5194/cp-11-187-2015, 2015
J. T. Andrews and A. E. Jennings
Clim. Past, 10, 325–343, https://doi.org/10.5194/cp-10-325-2014, https://doi.org/10.5194/cp-10-325-2014, 2014
S. T. Belt, T. A. Brown, L. Ampel, P. Cabedo-Sanz, K. Fahl, J. J. Kocis, G. Massé, A. Navarro-Rodriguez, J. Ruan, and Y. Xu
Clim. Past, 10, 155–166, https://doi.org/10.5194/cp-10-155-2014, https://doi.org/10.5194/cp-10-155-2014, 2014
S. McGregor, A. Timmermann, M. H. England, O. Elison Timm, and A. T. Wittenberg
Clim. Past, 9, 2269–2284, https://doi.org/10.5194/cp-9-2269-2013, https://doi.org/10.5194/cp-9-2269-2013, 2013
Cited articles
Abella-Gutiérrez, J. and Herguera, J. C.: Sensitivity of carbon
paleoproductivity in the Southern California Current System on different time
scales for the last 2ka, Paleoceanography, 31, 953–970,
https://doi.org/10.1002/2015PA002872, 2016. a, b
Abram, N. J., Mcgregor, H. V., Tierney, J. E., Evans, M. N., Mckay, N. P., and
Kaufman, D. S.: Early onset of industrial-era warming across the oceans and
continents, Nature, 536, 411–418, https://doi.org/10.1038/nature19082, 2016. a, b
Bakun, A., Black, B. A., Bograd, S. J., Garcia-Reyes, M., Miller, A. J.,
Rykaczewski, R. R., and Sydeman, W. J.: Anticipated Effects of Climate Change
on Coastal Upwelling Ecosystems, Curr. Clim. Change. Rep., 1, 85–93,
https://doi.org/10.1007/s40641-015-0008-4, 2015. a
Boyd, P. W., Claustre, H., Levy, M., Siegel, D. A., and Weber, T.:
Multi-faceted particle pumps drive carbon sequestration in the ocean, Nature,
568, 327–335, https://doi.org/10.1038/s41586-019-1098-2, 2019. a
Campbell, J. W.: The lognormal distribution as a model for bio‐optical
variability in the sea, J. Geophys. Res.-Oceans, 100, 13237–13254, 1995. a
Carton, J. A., Chepurin, G. A., and Chen, L.: SODA3: A New Ocean Climate
Reanalysis, J. Climate, 31, 6967–6983,
https://doi.org/10.1175/JCLI-D-18-0149.1, 2018. a
Checkley Jr., D. M. and Barth, J. A.: Patterns and processes in the California
Current System, Prog. Oceanogr., 83, 49–64,
https://doi.org/10.1016/j.pocean.2009.07.028, 2009. a
Chelton, D. and Freilich, M.: Scatterometer-Based Assessment of 10-m Wind
Analyses from the Operational ECMWF and NCEP Numerical Weather Prediction
Models, Mon. Weather Rev., 133, 409–429, https://doi.org/10.1175/MWR-2861.1, 2005. a, b
Cheung, A., Fox-Kemper, B., and Herbert, T.: Source code and data for “Can we use sea surface temperature and productivity proxy records to reconstruct Ekman Upwelling?”, https://doi.org/10.26300/41y9-ts23, 2019. a
Chhak, K. and Di Lorenzo, E.: Decadal variations in the California Current
upwelling cells, Geophys. Res. Lett., 34, L14604,
https://doi.org/10.1029/2007GL030203, 2007. a, b
Conte, M. H., Eglinton, G., and Madureira, L. A.: Long-chain alkenones and
alkyl alkenoates as palaeotemperature indicators: their production, flux and
early sedimentary diagenesis in the Eastern North Atlantic, Org.
Geochem., 19, 287–298,
https://doi.org/10.1016/0146-6380(92)90044-X, 1992. a
Dall'Olmo, G., Gitelson, A. A., Rundquist, D. C., Leavitt, B., Barrow, T., and
Holz, J. C.: Assessing the potential of SeaWiFS and MODIS for estimating
chlorophyll concentration in turbid productive waters using red and
near-infrared bands, Remote Sens. Environ., 96, 176–187, 2005. a
Di Lorenzo, E.: Climate science: The future of coastal ocean upwelling, Nature,
518, 310–311, https://doi.org/10.1038/518310a, 2015. a
Di Lorenzo, E., Miller, A. J., Schneider, N., and McWilliams, J. C.: The
Warming of the California Current System: Dynamics and Ecosystem
Implications, J. Phys. Oceanogr., 35, 336–362,
https://doi.org/10.1175/JPO-2690.1, 2005. a, b
Dolman, A. M. and Laepple, T.: Sedproxy: a forward model for sediment-archived climate proxies, Clim. Past, 14, 1851–1868, https://doi.org/10.5194/cp-14-1851-2018, 2018. a
Dunne, J. P., Armstrong, R. A., Gnanadesikan, A., and Sarmiento, J. L.:
Empirical and mechanistic models for the particle export ratio, Global
Biogeochem. Cy., 19, GB4026, https://doi.org/10.1029/2004GB002390, 2005. a, b
Freilich, M. H., Long, D. G., and Spencer, M. W.: SeaWinds: a scanning
scatterometer for ADEOS-II-science overview, Proceedings of IGARSS '94 –
1994 IEEE International Geoscience and Remote Sensing Symposium, Pasadena,
CA, USA, 2, 960–963, 1994. a
Garcia-Reyes, M., Sydeman, W. J., Schoeman, D. S., Rykaczewski, R. R., Black,
B. A., Smit, A. J., and Bograd, S. J.: Under Pressure: Climate Change,
Upwelling, and Eastern Boundary Upwelling Ecosystems, Front. Mar. Sci., 2,
109, https://doi.org/10.3389/fmars.2015.00109, 2015. a
Goni, M. A., Thunell, R. C., Woodwort, M. P., and Müller-Karger, F. E.:
Changes in wind‐driven upwelling during the last three centuries:
Interocean teleconnections, Geophys. Res. Lett., 33, L15604,
https://doi.org/10.1029/2006GL026415, 2006. a, b, c
Gruber, N., Lachkar, Z., Frenzel, H., Marchesiello, P., Münnich, M.,
McWilliams, J. C., Nagai, T., and Plattner, G.-K.: Eddy-induced reduction of
biological production in eastern boundary upwelling systems, Nat. Geosci., 4,
787–792, https://doi.org/10.1038/NGEO1273, 2011. a
Hannachi, A., Jolliffe, I. T., and Stephenson, D. B.: Empirical orthogonal
functions and related techniques in atmospheric science: A review, Int. J.
Climatol., 27, 1119–1152, https://doi.org/10.1002/joc.1499, 2007. a, b
Harrison, S. P., Bartlein, P. J., Izumi, K., Li, G., Annan, J., Hargreaves, J.,
Braconnot, P., and Kageyama, M.: Evaluation of CMIP5 palaeo-simulations to
improve climate projections, Nat. Clim. Change, 5, 735–743,
https://doi.org/10.1038/NCLIMATE2649, 2015. a
Henson, S. A., Sarmiento, J. L., Dunne, J. P., Bopp, L., Lima, I., Doney, S. C., John, J., and Beaulieu, C.: Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity, Biogeosciences, 7, 621–640, https://doi.org/10.5194/bg-7-621-2010, 2010. a, b
Hu, C., Lee, Z., and Franz, B.: Chlorophyll-a algorithms for oligotrophic
oceans: A novel approach based on three-band reflectance difference, J. Geophys. Res.-Oceans, 117, C01011, https://doi.org/10.1029/2011JC007395, 2012. a
Huybers, P. and Curry, W.: Links between annual, Milankovitch and continuum
temperature variability, Nature, 441, 329–332, https://doi.org/10.1038/nature04745,
2006. a
Jacox, M., Moore, A., Edwards, C., and Fiechter, J.: Spatially resolved
upwelling in the California Current System and its connections to climate
variability, Geophys. Res. Lett., 41, 3189–3196, 2014. a
Jacox, M. G., Hazen, E. L., and Bograd, S. J.: Optimal Environmental
Conditions and Anomalous Ecosystem Responses: Constraining Bottom-up Controls
of Phytoplankton Biomass in the California Current System, Sci. Rep., 6,
27612, https://doi.org/10.1038/srep27612, 2016. a
Kutzbach, J.: Empirical Eigenvectors of Sea-Level Pressure, Surface Temperature
and Precipitation Complexes over North America, J. Appl. Meteorol., 6,
791–802, 1967. a
Lam, P. J. and Marchal, O.: Insights into particle cycling from thorium and
particle data, Annual Rev. Mar. Sci., 7, 159–184, 2015. a
Large, W. and Pond, S.: Open Ocean Momentum Flux Measurements in Moderate to
Strong Winds, J. Phys. Oceanogr., 11, 324–336,
https://doi.org/10.1175/1520-0485(1981)011<0324:OOMFMI>2.0.CO;2, 1981. a
Laws, E. A., D'Sa, E., and Naik, P.: Simple equations to estimate ratios of new
or export production to total production from satellite-derived estimates of
sea surface temperature and primary production, Limnol. Oceanogr.-Meth., 9, 593–601, 2011. a
Leduc, G., Herbert, C. T., Blanz, T., Martinez, P., and Schneider, R.:
Contrasting evolution of sea surface temperature in the Benguela upwelling
system under natural and anthropogenic climate forcings, Geophys. Res. Lett.,
37, L20705, https://doi.org/10.1029/2010GL044353, 2010a. a, b, c
Leduc, G., Schneider, R., Kim, J.-H., and Lohmann, G.: Holocene and Eemian sea
surface temperature trends as revealed by alkenone and Mg/Ca
paleothermometry, Quaternary Sci. Rev., 29, 989–1004,
https://doi.org/10.1016/j.quascirev.2010.01.004, 2010b. a
Lynn, R. J. and Simpson, J. J.: The California Current system: The seasonal
variability of its physical characteristics, J. Geophys. Res., 92,
12947–12966, https://doi.org/10.1029/JC092iC12p12947, 1987. a
MARGO: Constraints on the magnitude and patterns of ocean cooling at the Last
Glacial Maximum, Nat. Geosci., 2, 127–132, https://doi.org/10.1038/NGEO411, 2009. a, b
McGregor, H. V., Dima, M., Fischer, H. W., and Mulitza, S.: Rapid 20th-Century
Increase in Coastal Upwelling off Northwest Africa, Science, 315,
637–639, https://doi.org/10.1126/science.1134839, 2007. a, b, c
Monahan, A. H., Fyfe, J. C., Ambaum, M. H. P., Stephenson, D. B., and North,
G. R.: Empirical Orthogonal Functions: The Medium is the Message, J.
Climate, 22, 6501–6514, https://doi.org/10.1175/2009JCLI3062.1, 2009. a
NOAA/NESDIS: GOES Level 3 6km Near Real Time SST 1 Hour. Ver. 1. PO.DAAC, CA,
USA, Dataset,
https://doi.org/10.5067/GOES3-1HOUR, 2003a. a, b
NOAA/NESDIS: GOES Level 3 6km Near Real Time SST 24 Hour. Ver. 1. PO.DAAC, CA,
USA, Dataset,
https://doi.org/10.5067/GOES3-24HOR, 2003b. a, b
NASA Goddard Space Flight Center: Ocean Ecology Laboratory, Ocean Biology Processing Group, Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Chlorophyll Data, v2018 Reprocessing, NASA OB.DAAC, Greenbelt, MD, USA,
https://doi.org/10.5067/AQUA/MODIS/L3M/CHL/2018, 2018. a, b
PAGES2k Consortium: Continental-scale temperature variability during the past
two millennia, Nat. Geosci., 6, 339–346, https://doi.org/10.1038/NGEO1797, 2013. a
Pauly, D. and Christensen, V.: Primary production required to sustain global
fisheries, Nature, 374, 255–257, 1995. a
Perry, K. L.: SeaWinds on QuikSCAT Level 3 Daily, Gridded Ocean Wind
Vectors (JPL SeaWinds Project), Version 1.1, JPL Document D-20335, Jet
Propulsion Laboratory, Pasadena, CA, 2001. a
Ravelo, A. C., Andreasen, D. H., Lyle, M., Lyle, A. O., and Wara, M. W.:
Regional climate shifts caused by gradual global cooling in the Pliocene
epoch, Nature, 429, 263, https://doi.org/10.1038/nature02567, 2004. a
Rykaczewski, R. R. and Dunne, J. P.: Enhanced nutrient supply to the
California Current Ecosystem with global warming and increased stratification
in an earth system model, Geophys. Res. Lett., 37, L21606,
https://doi.org/10.1029/2010GL045019, 2010. a, b
Ryther, J. H.: Photosynthesis and Fish Production in the Sea, Science, 166,
72–76, https://doi.org/10.1126/science.166.3901.72, 1969. a
SeaPAC: SeaWinds on QuikSCAT Level 3 Daily Gridded Ocean Wind Vectors (JPL
Version 2). Ver. 2. PO.DAAC, CA, USA, Dataset,
https://doi.org/10.5067/QSXXX-L3002, 2006. a, b
Shakun, J. D., Clark, P. U., He, F., Marcott, S. A., Mix, A. C., Liu, Z.,
Otto-Bliesner, B., Schmittner, A., and Bard, E.: Global warming preceded by
increasing carbon dioxide concentrations during the last deglaciation,
Nature, 484, 49–54, https://doi.org/10.1038/nature10915, 2012. a
Silverberg, N., Martínez, A., Aguíñiga, S., Carriquiry, J. D.,
Romero, N., Shumilin, E., and Cota, S.: Contrasts in sedimentation flux below
the southern California Current in late 1996 and during the El Niño event of
1997–1998, Estuar. Coast. Shelf Sci., 59, 575–587,
https://doi.org/10.1016/j.ecss.2003.11.003, 2004. a
Snyder, M. A., Sloan, L. C., Diffenbaugh, N. S., and Bell, J. L.: Future
climate change and upwelling in the California Current, Geophys. Res.
Lett., 30, https://doi.org/10.1029/2003GL017647, 2003. a
Thunell, R. C.: Particle fluxes in a coastal upwelling zone: sediment trap
results from Santa Barbara Basin, California, Deep-Sea Res. Pt. II, 45, 1863–1884, 1998. a
Thunell, R. C., Pride, C. J., Tappa, E., and Muller-Karger, F. E.: Biogenic
silica fluxes and accumulation rates in the Gulf of California, Geology, 22,
303–306, 1994. a
van Geen, A., Zheng, Y., Bernhard, J. M., Cannariato, K. G., Carriquiry, J.,
Dean, W. E., Eakins, B. W., Ortiz, J. D., and Pike, J.: On the preservation
of laminated sediments along the western margin of North America,
Paleoceanography, 18, 1098, https://doi.org/10.1029/2003PA000911, 2003. a
Vargas, G., Pantoja, S., Rutllant, J. A., Lange, C. B., and Ortlieb, L.:
Enhancement of coastal upwelling and interdecadal ENSO-like variability in
the Peru-Chile Current since late 19th century, Geophys. Res. Lett., 34,
L13607, https://doi.org/10.1029/2006GL028812, 2007. a, b, c
Wang, J., Emile-Geay, J., Guillot, D., Smerdon, J. E., and Rajaratnam, B.: Evaluating climate field reconstruction techniques using improved emulations of real-world conditions, Clim. Past, 10, 1–19, https://doi.org/10.5194/cp-10-1-2014, 2014. a, b
Ware, D. M. and Thomson, R. E.: Bottom-Up Ecosystem Trophic Dynamics Determine
Fish Production in the Northeast Pacific, Science, 308, 1280–1284,
https://doi.org/10.1126/science.1109049, 2005. a
Wick, G. A., Bates, J. J., and Scott, D. J.: Satellite and skin-layer effects
on the accuracy of sea surface temperature measurements from the GOES
satellites, J. Atmos. Ocean. Tech., 19, 1834–1848,
2002. a
Xiu, P., Chai, F., Curchitser, E. N., and Castruccio, F. S.: Future changes in
coastal upwelling ecosystems with global warming: The case of the California
Current System, Sci. Rep., 8, 2866, https://doi.org/10.1038/s41598-018-21247-7, 2018. a
Zhao, M., Eglinton, G., Read, G., and Schimmelmann, A.: An alkenone (U37K′)
quasi-annual sea surface temperature record (AD 1440 to 1940) using varved
sediments from the Santa Barbara Basin, Org. Geochem., 31, 903–917,
https://doi.org/10.1016/S0146-6380(00)00034-6, 2000. a, b
Short summary
We test two assumptions that are often made in paleoclimate studies by using observations and ask whether temperature and productivity proxy records in the Southern California Current can be used to reconstruct Ekman upwelling. By examining the covariation between alongshore wind stress, temperature, and productivity, we found that the dominant covarying pattern does not reflect Ekman upwelling. Other upwelling patterns found are timescale dependent. Multiple proxies can improve reconstruction.
We test two assumptions that are often made in paleoclimate studies by using observations and...