The Argo Project: Global Ocean Observations for Understanding and Prediction of Climate Variability

The Southern Ocean plays an important role in the uptake, transport and storage of carbon by the global oceans. These properties are dominated by the response to the rise in anthropogenic CO2 in the atmosphere, but they are modulated by climate variability and climate change. Here we explore the effect of climate variability and climate change on ocean carbon uptake and storage in the Southern Ocean. We assess the extent to which climate change may be distinguishable from the anthropogenic CO2 signal and from the natural background variability. We use a combination of biogeochemical ocean modelling and observations from the GLODAPv2020 database to detect climate fingerprints in dissolved inorganic carbon (DIC).We conduct an ensemble of hindcast model simulations of the period 1920-2019, using a global ocean biogeochemical model which incorporates plankton ecosystem dynamics based on twelve plankton functional types. We use the model ensemble to isolate the changes in DIC due to rising anthropogenic CO2 alone and the changes due to climatic drivers (both climate variability and climate change), to determine their relative roles in the emerging total DIC trends and patterns. We analyse these DIC trends for a climate fingerprint over the past four decades, across spatial scales from the Southern Ocean, to basin level and down to regional ship transects. Highly sampled ship transects were extracted from GLODAPv2020 to obtain locations with the maximum spatiotemporal coverage, to reduce the inherent biases in patchy observational data. Model results were sampled to the ship transects to compare the climate fingerprints directly to the observational data.Model results show a substantial change in DIC over a 35-year period, with a range of more than +/- 30 &#181;mol/L. In the surface ocean, both anthropogenic CO2 and climatic drivers act to increase DIC concentration, with the influence of anthropogenic CO2 dominating at lower latitudes and the influence of climatic drivers dominating at higher latitudes. In the deep ocean, the anthropogenic CO2 generally acts to increase DIC except in the subsurface waters at lower latitudes, while climatic drivers act to decrease DIC concentration. The combined fingerprint of anthropogenic CO2 and climatic drivers on DIC concentration is for an increasing trend at the surface and decreasing trends in low latitude subsurface waters. Preliminary comparison of the model fingerprints to observational ship transects will also be presented.

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On The Determinations of Weather, Seasonal, Sub-Seasonal and Climate Scale Variability and Overall Trends in the Atmosphere and Ocean

Passive Remote Study of the Aerosol in the Upper Atmosphere of the Earth ◽

10.47363/jeesr/2020(2)121 ◽

2020 ◽

pp. 1-17

Author(s):

LJ Pietrafesa ◽

◽

S Bao ◽

Keyword(s):

Climate Variability ◽

Seasonal Variability ◽

Atmospheric Temperature ◽

Global Ocean ◽

Remotely Sensed Data ◽

Modes Of Variability ◽

Multi Scale ◽

Naturally Occurring ◽

Climate Scale ◽

Coastal Water Level

The traditional concepts and definitions of multi-scale “weather”, “seasonal variability”, “sub-seasonal variability”, “climate variability”, “trends” and “climate change” for both the global atmosphere and the global ocean are considered. We build upon existing literature and present new evidence that atmospheric and oceanic temporal multi-scale variability are the result of a mix of well-known frequency and amplitude modulated nonlinear and phenomena that occur simultaneously [1-3]. We harvest representative atmospheric temperature and wind data, oceanic temperature and coastal water level from United States (U.S.) and United Kingdom (U.K.) agency archives, collected via in-situ and satellite remotely sensed data and employ a mathematical methodology that can decompose nonlinear data. The data decomposition reveals a continuum of well-defined, modulated, internal modes of oscillations, each with broad spectral peaks and each representative of naturally occurring phenomena. We reveal that the conventional notions of weather and seasonal to subseasonal to climate variability, actually constitute an over-lapping continuum, with shorter period oscillations commuting with longer period oscillations onto overall record length trends. We relate these internal, intrinsic modes of variability to naturally occurring causal agents, from relatively high frequency weather to lower frequency seasonal to sub-seasonal to climate scale variability. Correlative relationships between climate factors reveal causal couplings of the oceanic and atmospheric systems.

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Alternate history: A synthetic ensemble of ocean chlorophyll concentrations

10.5194/egusphere-egu21-1375 ◽

2021 ◽

Author(s):

Geneviève Elsworth ◽

Nicole Lovenduski ◽

Karen McKinnon

Keyword(s):

Climate Variability ◽

Internal Variability ◽

Ensemble Member ◽

Global Ocean ◽

Large Ensemble ◽

Internal Climate Variability ◽

Surface Ocean ◽

Large Ensembles ◽

Long Term Trends

Internal climate variability plays an important role in the abundance and distribution of phytoplankton in the global ocean. Previous studies using large ensembles of Earth system models (ESMs) have demonstrated their utility in the study of marine phytoplankton variability. These ESM large ensembles simulate the evolution of multiple alternate realities, each with a different phasing of internal climate variability. However, ESMs may not accurately represent real world variability as recorded via satellite and in situ observations of ocean chlorophyll over the past few decades. Observational records of surface ocean chlorophyll equate to a single ensemble member in the large ensemble framework, and this can cloud the interpretation of long-term trends: are they externally forced, caused by the phasing of internal variability, or both? Here, we use a novel statistical emulation technique to place the observational record of surface ocean chlorophyll into the large ensemble framework. Much like a large initial condition ensemble generated with an ESM, the resulting synthetic ensemble represents multiple possible evolutions of ocean chlorophyll concentration, each with a different phasing of internal climate variability. We further demonstrate the validity of our statistical approach by recreating a ESM ensemble of chlorophyll using only a single ESM ensemble member. We use the synthetic ensemble to explore the interpretation of long-term trends in the presence of internal variability. Our results suggest the potential to explore this approach for other ocean biogeochemical variables.

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Assembling the Bathymetric Puzzle to Create a Global Ocean Map

Marine Technology Society Journal ◽

10.4031/mtsj.54.3.2 ◽

2020 ◽

Vol 54 (3) ◽

pp. 13-17

Author(s):

Vicki Ferrini

Keyword(s):

Data Science ◽

World Ocean ◽

Global Ocean ◽

Collaborative Relationships ◽

Systematic Mapping ◽

Mapping Technology ◽

Information Products ◽

Mapping Resource ◽

Coordination And Collaboration ◽

Ocean Observations

AbstractBathymetry data are fundamental ocean observations that are important for a variety of applications including exploration and research, habitat mapping, resource management, coastal and ocean resilience, and policy decisions. Despite the importance of these data, the majority of the ocean, and our planet, remains unmapped. As a result, we lack comprehensive integrated data and information products at the resolutions necessary to address fundamental questions about subaqueous environments. With the increasing availability of mapping technology, advances in computing and data science, and an evolving culture that embraces data sharing, there are new opportunities to produce high-quality, publicly available, integrated bathymetry data products. Coordinated efforts with grand aspirations to completely map the world's oceans come at a pivotal time as we confront global challenges related to a changing planet. Through coordination and collaboration across communities, scales, and sectors, we can accelerate toward delivering data and information products that are useful to society while developing strong collaborative relationships that will have long-lasting effects. The technical and collaborative approaches developed for completely mapping the world ocean can be applied to systematic mapping efforts in other subaqueous environments and can benefit initiatives such as Lakebed 2030.

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Simulating Southern Hemisphere extra-tropical climate variability with an idealised coupled atmosphere-ocean model

Geoscientific Model Development ◽

10.5194/gmd-5-1161-2012 ◽

2012 ◽

Vol 5 (5) ◽

pp. 1161-1175 ◽

Cited By ~ 2

Author(s):

H. Kurzke ◽

M. V. Kurgansky ◽

K. Dethloff ◽

D. Handorf ◽

S. Erxleben ◽

...

Keyword(s):

Climate Variability ◽

Southern Hemisphere ◽

Ocean Circulation ◽

Coupled Model ◽

Circulation Model ◽

Horizontal Resolution ◽

Global Ocean ◽

Simplified Model ◽

Cmip5 Models ◽

Decadal Climate Variability

Abstract. A quasi-geostrophic model of Southern Hemisphere's wintertime atmospheric circulation with horizontal resolution T21 has been coupled to a global ocean circulation model with a resolution of 2° × 2° and simplified physics. This simplified coupled model reproduces qualitatively some features of the first and the second EOF of atmospheric 833 hPa geopotential height in accordance with NCEP data. The variability patterns of the simplified coupled model have been compared with variability patterns simulated by four complex state-of-the-art coupled CMIP5 models. The first EOF of the simplified model is too zonal and does not reproduce the right position of the centre of action over the Pacific Ocean and its extension to the tropics. The agreement in the second EOF between the simplified and the CMIP5 models is better. The total variance of the simplified model is weaker than the observational variance and those of the CMIP5 models. The transport properties of the Southern Ocean circulation are in qualitative accord with observations. The simplified model exhibits skill in reproducing essential features of decadal and multi-decadal climate variability in the extratropical Southern Hemisphere. Notably, 800 yr long coupled model simulations reveal sea surface temperature fluctuations on the timescale of several decades in the Antarctic Circumpolar Current region.

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Effects of the 18.6-yr Modulation of Tidal Mixing on the North Pacific Bidecadal Climate Variability in a Coupled Climate Model

Journal of Climate ◽

10.1175/jcli-d-12-00051.1 ◽

2012 ◽

Vol 25 (21) ◽

pp. 7625-7642 ◽

Cited By ~ 32

Author(s):

Yuki Tanaka ◽

Ichiro Yasuda ◽

Hiroyasu Hasumi ◽

Hiroaki Tatebe ◽

Satoshi Osafune

Keyword(s):

Climate Variability ◽

North Pacific ◽

Climate Model ◽

Tidal Mixing ◽

Global Ocean ◽

Coupled Climate Model ◽

Orbital Inclination ◽

The North ◽

Sst Anomaly ◽

The North Pacific

Diapycnal mixing induced by tide–topography interaction, one of the essential factors maintaining the global ocean circulation and hence the global climate, is modulated by the 18.6-yr period oscillation of the lunar orbital inclination, and has therefore been hypothesized to influence bidecadal climate variability. In this study, the spatial distribution of diapycnal diffusivity together with its 18.6-yr oscillation estimated from a global tide model is incorporated into a state-of-the-art numerical coupled climate model to investigate its effects on climate variability over the North Pacific and to understand the underlying physical mechanism. It is shown that a significant sea surface temperature (SST) anomaly with a period of 18.6 years appears in the Kuroshio–Oyashio Extension region; a positive (negative) SST anomaly tends to occur during strong (weak) tidal mixing. This is first induced by anomalous horizontal circulation localized around the Kuril Straits, where enhanced modulation of tidal mixing exists, and then amplified through a positive feedback due to midlatitude air–sea interactions. The resulting SST and sea level pressure variability patterns are reminiscent of those associated with one of the most prominent modes of climate variability in the North Pacific known as the Pacific decadal oscillation, suggesting the potential for improving climate predictability by taking into account the 18.6-yr modulation of tidal mixing.

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Evaluation of CMIP3 and CMIP5 Wind Stress Climatology Using Satellite Measurements and Atmospheric Reanalysis Products

Journal of Climate ◽

10.1175/jcli-d-12-00591.1 ◽

2013 ◽

Vol 26 (16) ◽

pp. 5810-5826 ◽

Cited By ~ 46

Author(s):

Tong Lee ◽

Duane E. Waliser ◽

Jui-Lin F. Li ◽

Felix W. Landerer ◽

Michelle M. Gierach

Keyword(s):

Climate Variability ◽

Wind Stress ◽

Ocean Circulation ◽

Zonal Wind ◽

Global Ocean ◽

Equatorial Pacific Ocean ◽

Equatorial Atlantic ◽

Wind Stress Curl ◽

Meridional Heat Transport ◽

Easterly Wind

Abstract Wind stress measurements from the Quick Scatterometer (QuikSCAT) satellite and two atmospheric reanalysis products are used to evaluate the annual mean and seasonal cycle of wind stress simulated by phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The ensemble CMIP3 and CMIP5 wind stresses are very similar to each other. Generally speaking, there is no significant improvement of CMIP5 over CMIP3. The CMIP ensemble–average zonal wind stress has eastward biases at midlatitude westerly wind regions (30°–50°N and 30°–50°S, with CMIP being too strong by as much as 55%), westward biases in subtropical–tropical easterly wind regions (15°–25°N and 15°–25°S), and westward biases at high-latitude regions (poleward of 55°S and 55°N). These biases correspond to too strong anticyclonic (cyclonic) wind stress curl over the subtropical (subpolar) ocean gyres, which would strengthen these gyres and influence oceanic meridional heat transport. In the equatorial zone, significant biases of CMIP wind exist in individual basins. In the equatorial Atlantic and Indian Oceans, CMIP ensemble zonal wind stresses are too weak and result in too small of an east–west gradient of sea level. In the equatorial Pacific Ocean, CMIP zonal wind stresses are too weak in the central and too strong in the western Pacific. These biases have important implications for the simulation of various modes of climate variability originating in the tropics. The CMIP as a whole overestimate the magnitude of seasonal variability by almost 50% when averaged over the entire global ocean. The biased wind stress climatologies in CMIP not only have implications for the simulated ocean circulation and climate variability but other air–sea fluxes as well.

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