Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Decadal predictability without ocean dynamics.

ABSTRACT: This paper shows that the most predictable components of internal variability in coupled atmosphere-ocean models are remarkably similar to the most predictable components of climate models without interactive ocean dynamics (i.e., models whose ocean is represented by a 50-m-deep slab ocean mixed layer with no interactive currents). Furthermore, a linear regression model derived solely from dynamical model output can skillfully predict observed anomalies in these components at least a year or two in advance, indicating that these model-derived components and associated linear dynamics are realistic. These results suggest that interactive ocean circulation is not essential for the existence of multiyear predictability previously identified in coupled models and observations.

SUBMITTER: Srivastava A

PROVIDER: S-EPMC5338527 | biostudies-other | 2017 Feb

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Publications

Decadal predictability without ocean dynamics.

Srivastava Abhishekh A DelSole Timothy T

Proceedings of the National Academy of Sciences of the United States of America 20170213 9

This paper shows that the most predictable components of internal variability in coupled atmosphere-ocean models are remarkably similar to the most predictable components of climate models without interactive ocean dynamics (i.e., models whose ocean is represented by a 50-m-deep slab ocean mixed layer with no interactive currents). Furthermore, a linear regression model derived solely from dynamical model output can skillfully predict observed anomalies in these components at least a year or two ...[more]

PMID: 28193900

Similar Datasets

Role of subsurface ocean in decadal climate predictability over the South Atlantic.

Project description:Decadal climate predictability in the South Atlantic is explored by performing reforecast experiments using a coupled general circulation model with two initialization schemes; one is assimilated with observed sea surface temperature (SST) only, and the other is additionally assimilated with observed subsurface ocean temperature and salinity. The South Atlantic is known to undergo decadal variability exhibiting a meridional dipole of SST anomalies through variations in the subtropical high and ocean heat transport. Decadal reforecast experiments in which only the model SST is initialized with the observation do not predict well the observed decadal SST variability in the South Atlantic, while the other experiments in which the model SST and subsurface ocean are initialized with the observation skillfully predict the observed decadal SST variability, particularly in the Southeast Atlantic. In-depth analysis of upper-ocean heat content reveals that a significant improvement of zonal heat transport in the Southeast Atlantic leads to skillful prediction of decadal SST variability there. These results demonstrate potential roles of subsurface ocean assimilation in the skillful prediction of decadal climate variability over the South Atlantic.

| S-EPMC5986776 | biostudies-literature

Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme.

Project description:Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean.

| S-EPMC5786087 | biostudies-other

Decadal trends in the ocean carbon sink.

Project description:Measurements show large decadal variability in the rate of [Formula: see text] accumulation in the atmosphere that is not driven by [Formula: see text] emissions. The decade of the 1990s experienced enhanced carbon accumulation in the atmosphere relative to emissions, while in the 2000s, the atmospheric growth rate slowed, even though emissions grew rapidly. These variations are driven by natural sources and sinks of [Formula: see text] due to the ocean and the terrestrial biosphere. In this study, we compare three independent methods for estimating oceanic [Formula: see text] uptake and find that the ocean carbon sink could be responsible for up to 40% of the observed decadal variability in atmospheric [Formula: see text] accumulation. Data-based estimates of the ocean carbon sink from [Formula: see text] mapping methods and decadal ocean inverse models generally agree on the magnitude and sign of decadal variability in the ocean [Formula: see text] sink at both global and regional scales. Simulations with ocean biogeochemical models confirm that climate variability drove the observed decadal trends in ocean [Formula: see text] uptake, but also demonstrate that the sensitivity of ocean [Formula: see text] uptake to climate variability may be too weak in models. Furthermore, all estimates point toward coherent decadal variability in the oceanic and terrestrial [Formula: see text] sinks, and this variability is not well-matched by current global vegetation models. Reconciling these differences will help to constrain the sensitivity of oceanic and terrestrial [Formula: see text] uptake to climate variability and lead to improved climate projections and decadal climate predictions.

| S-EPMC6576185 | biostudies-literature

Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?

Project description:Seasonal-to-decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here.

| S-EPMC4373130 | biostudies-literature

Decadal acidification in the water masses of the Atlantic Ocean.

Project description:Global ocean acidification is caused primarily by the ocean's uptake of CO2 as a consequence of increasing atmospheric CO2 levels. We present observations of the oceanic decrease in pH at the basin scale (50 °S-36 °N) for the Atlantic Ocean over two decades (1993-2013). Changes in pH associated with the uptake of anthropogenic CO2 (ΔpHCant) and with variations caused by biological activity and ocean circulation (ΔpHNat) are evaluated for different water masses. Output from an Institut Pierre Simon Laplace climate model is used to place the results into a longer-term perspective and to elucidate the mechanisms responsible for pH change. The largest decreases in pH (∆pH) were observed in central, mode, and intermediate waters, with a maximum ΔpH value in South Atlantic Central Waters of -0.042 ± 0.003. The ΔpH trended toward zero in deep and bottom waters. Observations and model results show that pH changes generally are dominated by the anthropogenic component, which accounts for rates between -0.0015 and -0.0020/y in the central waters. The anthropogenic and natural components are of the same order of magnitude and reinforce one another in mode and intermediate waters over the time period. Large negative ΔpHNat values observed in mode and intermediate waters are driven primarily by changes in CO2 content and are consistent with (i) a poleward shift of the formation region during the positive phase of the Southern Annular Mode in the South Atlantic and (ii) an increase in the rate of the water mass formation in the North Atlantic.

| S-EPMC4538673 | biostudies-literature

Limits on determining the skill of North Atlantic Ocean decadal predictions.

Project description:The northern North Atlantic is important globally both through its impact on the Atlantic Meridional Overturning Circulation (AMOC) and through widespread atmospheric teleconnections. The region has been shown to be potentially predictable a decade ahead with the skill of decadal predictions assessed against reanalyses of the ocean state. Here, we show that the prediction skill in this region is strongly dependent on the choice of reanalysis used for validation, and describe the causes. Multiannual skill in key metrics such as Labrador Sea density and the AMOC depends on more than simply the choice of the prediction model. Instead, this skill is related to the similarity between the nature of interannual density variability in the underlying climate model and the chosen reanalysis. The climate models used in these decadal predictions are also used in climate projections, which raises questions about the sensitivity of these projections to the models' innate North Atlantic density variability.

| S-EPMC5923258 | biostudies-literature

Seasonal to decadal spatiotemporal variations of the global ocean carbon sink.

Project description:The global ocean has absorbed approximately 30% of anthropogenic CO2 since the beginning of the industrial revolution. However, the spatiotemporal evolution of this important global carbon sink varies substantially on all timescales and has not yet been well evaluated. Here, based on a reconstructed observation-based product of surface ocean pCO2 and air-sea CO2 flux (the MPI-SOMFFN method), we investigated seasonal to decadal spatiotemporal variations of the ocean CO2 sink during the past three decades using an adaptive data analysis method. Two predominant variations are modulated annual cycles and decadal fluctuations, which account for approximately 46% and 25% of all extracted components, respectively. Although the whole summer to non-summer seasonal difference pattern is determined by the Southern Ocean, the non-summer CO2 sink at mid-latitudes in both hemispheres shows an increasing trend (a total increase of approximately 1.0 PgC during the period 1982-2019), while it is relatively stable in summer. On decadal timescales for the global ocean carbon sink, unlike the weakening decade (1990-1999) and the reinvigoration decade (2000-2009) in which the Southern Ocean plays the dominant role, the reinforcement decade (2010-2019) is mainly the result from the weakening source effect in the equatorial Pacific Ocean. Our results suggest that except for the Southern Ocean's role in the global ocean carbon sink, the strengthening non-summer's sink at mid-latitudes in both hemispheres and the decadal or longer timescales of equatorial Pacific Ocean dynamics should be fully considered in understanding the oceanic carbon cycle on a global scale.

| S-EPMC9299973 | biostudies-literature

A decadal perspective on north water microbial eukaryotes as Arctic Ocean sentinels.

Project description:The North Water region, between Greenland and Ellesmere Island, with high populations of marine birds and mammals, is an Arctic icon. Due to climate related changes, seasonal patterns in water column primary production are changing but the implications for the planktonic microbial eukaryote communities that support the ecosystem are unknown. Here we report microbial community phenology in samples collected over 12 years (2005-2018) from July to October and analysed using high throughput 18S rRNA V4 amplicon sequencing. Community composition was tied to seasonality with summer communities more variable than distinct October communities. In summer, sentinel pan-Arctic species, including a diatom in the Chaetoceros socialis-gelidus complex and the picochlorophyte Micromonas polaris dominated phytoplankton and were summer specialists. In autumn, uncultured undescribed open water dinoflagellates were favored, and their ubiquity suggests they are sentinels of arctic autumn conditions. Despite the input of nutrients into surface waters, autumn chlorophyll concentrations remained low, refuting projected scenarios that longer ice-free seasons are synonymous with high autumn production and a diatom dominated bloom. Overall, the summer sentinel microbial taxa are persisting, and a subset oceanic dinoflagellate should be monitored for possible ecosystem shifts as later autumn ice formation becomes prevalent elsewhere.

| S-EPMC8052464 | biostudies-literature

Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction.

Project description:Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network.

| S-EPMC6750049 | biostudies-literature

Ocean surface temperature variability: large model-data differences at decadal and longer periods.

Project description:The variability of sea surface temperatures (SSTs) at multidecadal and longer timescales is poorly constrained, primarily because instrumental records are short and proxy records are noisy. Through applying a new noise filtering technique to a global network of late Holocene SST proxies, we estimate SST variability between annual and millennial timescales. Filtered estimates of SST variability obtained from coral, foraminifer, and alkenone records are shown to be consistent with one another and with instrumental records in the frequency bands at which they overlap. General circulation models, however, simulate SST variability that is systematically smaller than instrumental and proxy-based estimates. Discrepancies in variability are largest at low latitudes and increase with timescale, reaching two orders of magnitude for tropical variability at millennial timescales. This result implies major deficiencies in observational estimates or model simulations, or both, and has implications for the attribution of past variations and prediction of future change.

| S-EPMC4250160 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data