Data-driven dimensionality reduction and causal inference for spatiotemporal climate fields.

We propose a data-driven framework to describe spatiotemporal climate variability in terms of a few entities and their causal linkages. Given a high-dimensional climate field, the methodology first reduces its dimensionality into a set of regionally constrained patterns. Causal relations among such patterns are then inferred in the interventional sense through the fluctuation-response formalism. To distinguish between true and spurious responses, we propose an analytical null model for the fluctuation-dissipation relation, therefore allowing us for uncertainty estimation at a given confidence level. We showcase the methodology on the sea surface temperature field from a state-of-the-art climate model. The usefulness of the proposed framework for spatiotemporal climate data is demonstrated in several ways. First, we focus on the correct identification of known causal relations across tropical basins. Second, we show how the methodology allows us to visualize the cumulative response of the whole system to climate variability in a few selected regions. Finally, each pattern is ranked in terms of its causal strength, quantifying its relative ability to influence the system's dynamics. We argue that the methodology allows us to explore and characterize causal relations in spatiotemporal fields in a rigorous and interpretable way.

A new conceptual model of global ocean heat uptake.

We formulate a new conceptual model, named "MT2", to describe global ocean heat uptake, as simulated by atmosphere-ocean general circulation models (AOGCMs) forced by increasing atmospheric CO2, as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M). MT2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T. Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: ∙ Ocean heat uptake efficiency correlates strongly with the AMOC. ∙ Global ocean heat uptake is not correlated with the AMOC. ∙ Transient climate response (TCR) is anticorrelated with the AMOC. ∙ T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

Publisher Correction: Heat and carbon coupling reveals ocean warming due to circulation changes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The causes of sea-level rise since 1900.

The rate of global-mean sea-level rise since 1900 has varied over time, but the contributing factors are still poorly understood1. Previous assessments found that the summed contributions of ice-mass loss, terrestrial water storage and thermal expansion of the ocean could not be reconciled with observed changes in global-mean sea level, implying that changes in sea level or some contributions to those changes were poorly constrained2,3. Recent improvements to observational data, our understanding of the main contributing processes to sea-level change and methods for estimating the individual contributions, mean another attempt at reconciliation is warranted. Here we present a probabilistic framework to reconstruct sea level since 1900 using independent observations and their inherent uncertainties. The sum of the contributions to sea-level change from thermal expansion of the ocean, ice-mass loss and changes in terrestrial water storage is consistent with the trends and multidecadal variability in observed sea level on both global and basin scales, which we reconstruct from tide-gauge records. Ice-mass loss-predominantly from glaciers-has caused twice as much sea-level rise since 1900 as has thermal expansion. Mass loss from glaciers and the Greenland Ice Sheet explains the high rates of global sea-level rise during the 1940s, while a sharp increase in water impoundment by artificial reservoirs is the main cause of the lower-than-average rates during the 1970s. The acceleration in sea-level rise since the 1970s is caused by the combination of thermal expansion of the ocean and increased ice-mass loss from Greenland. Our results reconcile the magnitude of observed global-mean sea-level rise since 1900 with estimates based on the underlying processes, implying that no additional processes are required to explain the observed changes in sea level since 1900.

Heat and carbon coupling reveals ocean warming due to circulation changes.

Anthropogenic global surface warming is proportional to cumulative carbon emissions1-3; this relationship is partly determined by the uptake and storage of heat and carbon by the ocean4. The rates and patterns of ocean heat and carbon storage are influenced by ocean transport, such as mixing and large-scale circulation5-10. However, existing climate models do not accurately capture the observed patterns of ocean warming, with a large spread in their projections of ocean circulation and ocean heat uptake8,11. Additionally, assessing the influence of ocean circulation changes (specifically, the redistribution of heat by resolved advection) on patterns of observed and simulated ocean warming remains a challenge. Here we establish a linear relationship between the heat and carbon uptake of the ocean in response to anthropogenic emissions. This relationship is determined mainly by intrinsic parameters of the Earth system-namely, the ocean carbon buffer capacity, the radiative forcing of carbon dioxide and the carbon inventory of the ocean. We use this relationship to reveal the effect of changes in ocean circulation from carbon dioxide forcing on patterns of ocean warming in both observations and global Earth system models from the Fifth Coupled Model Intercomparison Project (CMIP5). We show that historical patterns of ocean warming are shaped by ocean heat redistribution, which CMIP5 models simulate poorly. However, we find that projected patterns of heat storage are primarily dictated by the pre-industrial ocean circulation (and small changes in unresolved ocean processes)-that is, by the patterns of added heat owing to ocean uptake of excess atmospheric heat rather than ocean warming by circulation changes. Climate models show more skill in simulating ocean heat storage by the pre-industrial circulation compared to heat redistribution, indicating that warming patterns of the ocean may become more predictable as the climate warms.

Identifying a human signal in the North Atlantic warming hole.

North Atlantic sea surface temperatures have large climate impacts affecting the weather of the Northern Hemisphere. In addition to a substantial warming over much of the North Atlantic, caused by increasing greenhouse gases over the 21st century, climate projections show a surprising region of considerable future cooling at midlatitudes, referred to as the North Atlantic warming hole. A similar pattern of surface temperature trends has been observed in recent decades, but it remains unclear whether this pattern is of anthropogenic origin or a simple manifestation of internal climate variability. Here, analyzing state-of-the-art climate models and observations, we show that the recent North Atlantic warming hole is of anthropogenic origin. Our analysis reveals that the anthropogenic signal has only recently emerged from the internal climate variability, and can be attributed to greenhouse gas emissions. We further show that a declining northward oceanic heat flux in recent decades, which is linked to this surface temperature pattern, is also of anthropogenic origin.

Global reconstruction of historical ocean heat storage and transport.

Most of the excess energy stored in the climate system due to anthropogenic greenhouse gas emissions has been taken up by the oceans, leading to thermal expansion and sea-level rise. The oceans thus have an important role in the Earth's energy imbalance. Observational constraints on future anthropogenic warming critically depend on accurate estimates of past ocean heat content (OHC) change. We present a reconstruction of OHC since 1871, with global coverage of the full ocean depth. Our estimates combine timeseries of observed sea surface temperatures with much longer historical coverage than those in the ocean interior together with a representation (a Green's function) of time-independent ocean transport processes. For 1955-2017, our estimates are comparable with direct estimates made by infilling the available 3D time-dependent ocean temperature observations. We find that the global ocean absorbed heat during this period at a rate of 0.30 ± 0.06 W/[Formula: see text] in the upper 2,000 m and 0.028 ± 0.026 W/[Formula: see text] below 2,000 m, with large decadal fluctuations. The total OHC change since 1871 is estimated at 436 ± 91 [Formula: see text] J, with an increase during 1921-1946 (145 ± 62 [Formula: see text] J) that is as large as during 1990-2015. By comparing with direct estimates, we also infer that, during 1955-2017, up to one-half of the Atlantic Ocean warming and thermosteric sea-level rise at low latitudes to midlatitudes emerged due to heat convergence from changes in ocean transport.

Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty.

Accurate forecasts of the ocean state and the estimation of forecast uncertainties are crucial when it comes to providing skilful seasonal predictions. In this study we analyse the predictive skill and reliability of the ocean component in a seasonal forecasting system. Furthermore, we assess the effects of accounting for model and observational uncertainties. Ensemble forcasts are carried out with an updated version of the ECMWF seasonal forecasting model System 4, with a forecast length of ten months, initialized every May between 1981 and 2010. We find that, for essential quantities such as sea surface temperature and upper ocean 300 m heat content, the ocean forecasts are generally underdispersive and skilful beyond the first month mainly in the Tropics and parts of the North Atlantic. The reference reanalysis used for the forecast evaluation considerably affects diagnostics of forecast skill and reliability, throughout the entire ten-month forecasts but mostly during the first three months. Accounting for parametrization uncertainty by implementing stochastic parametrization perturbations has a positive impact on both reliability (from month 3 onwards) as well as forecast skill (from month 8 onwards). Skill improvements extend also to atmospheric variables such as 2 m temperature, mostly in the extratropical Pacific but also over the midlatitudes of the Americas. Hence, while model uncertainty impacts the skill of seasonal forecasts, observational uncertainty impacts our assessment of that skill. Future ocean model development should therefore aim not only to reduce model errors but to simultaneously assess and estimate uncertainties.