scholarly journals Climate models can correctly simulate the continuum of global-average temperature variability

2019 ◽  
Vol 116 (18) ◽  
pp. 8728-8733 ◽  
Author(s):  
Feng Zhu ◽  
Julien Emile-Geay ◽  
Nicholas P. McKay ◽  
Gregory J. Hakim ◽  
Deborah Khider ◽  
...  
Keyword(s):  
Climate Models ◽  
Initial Conditions ◽  
Low Frequency ◽  
Deep Ocean ◽  
Critical Element ◽  
Average Temperature ◽  
Global Mean Temperature ◽  
Low Frequency Variability ◽  
Climate Forcings ◽  
Global Mean

Climate records exhibit scaling behavior with large exponents, resulting in larger fluctuations at longer timescales. It is unclear whether climate models are capable of simulating these fluctuations, which draws into question their ability to simulate such variability in the coming decades and centuries. Using the latest simulations and data syntheses, we find agreement for spectra derived from observations and models on timescales ranging from interannual to multimillennial. Our results confirm the existence of a scaling break between orbital and annual peaks, occurring around millennial periodicities. That both simple and comprehensive ocean–atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. This result implies that Holocene low-frequency variability is partly a consequence of the climate system’s integrated memory of orbital forcing. We conclude that climate models appear to contain the essential physics to correctly simulate the spectral continuum of global-mean temperature; however, regional discrepancies remain unresolved. A critical element of successfully simulating suborbital climate variability involves, we hypothesize, initial conditions of the deep ocean state that are consistent with observations of the recent past.

scholarly journals An Evaluation of Decadal Probability Forecasts from State-of-the-Art Climate Models

2013 ◽  
Vol 26 (23) ◽  
pp. 9334-9347 ◽  
Author(s):  
Emma B. Suckling ◽  
Leonard A. Smith
Keyword(s):  
Climate Models ◽  
State Of The Art ◽  
Simulation Models ◽  
Empirical Models ◽  
Regular Component ◽  
Climate Services ◽  
Global Mean Temperature ◽  
Operational Forecasts ◽  
Earth’S Climate ◽  
Global Mean

While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 years, nontrivial structural flaws still hinder their ability to forecast the decadal dynamics of the Earth system realistically. Contrasting the skill of these models not only with each other but also with empirical models can reveal the space and time scales on which simulation models exploit their physical basis effectively and quantify their ability to add information to operational forecasts. The skill of decadal probabilistic hindcasts for annual global-mean and regional-mean temperatures from the EU Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project is contrasted with several empirical models. Both the ENSEMBLES models and a “dynamic climatology” empirical model show probabilistic skill above that of a static climatology for global-mean temperature. The dynamic climatology model, however, often outperforms the ENSEMBLES models. The fact that empirical models display skill similar to that of today's state-of-the-art simulation models suggests that empirical forecasts can improve decadal forecasts for climate services, just as in weather, medium-range, and seasonal forecasting. It is suggested that the direct comparison of simulation models with empirical models becomes a regular component of large model forecast evaluations. Doing so would clarify the extent to which state-of-the-art simulation models provide information beyond that available from simpler empirical models and clarify current limitations in using simulation forecasting for decision support. Ultimately, the skill of simulation models based on physical principles is expected to surpass that of empirical models in a changing climate; their direct comparison provides information on progress toward that goal, which is not available in model–model intercomparisons.

scholarly journals Uncertainty in the relationship between climate forcing and hydrological response in UK catchments

2011 ◽  
Vol 15 (3) ◽  
pp. 897-912 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals An Ideal yet Highly Accurate Model Correlating Global Average Temperature to Excess CO2-Emissions

2021 ◽  
Author(s):  
Roland Hermann Pawelke
Keyword(s):  
Transition State Theory ◽  
Ideal Gas ◽  
State Theory ◽  
Average Temperature ◽  
Global Mean Temperature ◽  
Ideal Gas Law ◽  
System Temperature ◽  
First Time ◽  
Global Mean ◽  
The Ideal

The causality of preceding atmospheric excess-to-equilibrium CO<sub>2</sub>-amounts and trailing system temperature increase is captured in terms of the ideal gas law, equilibrium thermodynamics and transition state theory for the first time: the model’s performance is excellent, publicly available global mean temperature data from 1880 (13.58 °C / 290.7 ppm) to April 2021 (14.49 °C / 416.2 ppm) are reproduced at less than ±2 % deviation. Eight future global mean temperatures for atmospheric CO<sub>2</sub>-levels between 450 ppm and 7000 ppm are extrapolated and an empiric expression of the relation is derived. The model’s ideal nature allows adaption for other greenhouse gases and provides a reference for conclusions about the energetic weighting and the wider significance of the CO<sub>2</sub>-based proportion in the total Greenhouse effect.

scholarly journals Intrinsic oceanic decadal variability of upper-ocean heat content

2021 ◽  
pp. 1-42
Author(s):  
Navid C. Constantinou ◽  
Andrew McC. Hogg
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Low Frequency ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Upper Ocean ◽  
Climate Projections ◽  
Upper Ocean Heat Content ◽  
Modes Of Variability ◽  
Low Frequency Variability

AbstractAtmosphere and ocean are coupled via air–sea interactions. The atmospheric conditions fuel the ocean circulation and its variability, but the extent to which ocean processes can affect the atmosphere at decadal time scales remains unclear. In particular, such low-frequency variability is difficult to extract from the short observational record, meaning that climate models are the primary tools deployed to resolve this question. Here, we assess how the ocean’s intrinsic variability leads to patterns of upper-ocean heat content that vary at decadal time scales. These patterns have the potential to feed back on the atmosphere and thereby affect climate modes of variability, such as El Niño or the Interdecadal Pacific Oscillation. We use the output from a global ocean–sea ice circulation model at three different horizontal resolutions, each driven by the same atmospheric reanalysis. To disentangle the variability of the ocean’s direct response to atmospheric forcing from the variability due to intrinsic ocean dynamics, we compare model runs driven with inter-annually varying forcing (1958-2019) and model runs driven with repeat-year forcing. Models with coarse resolution that rely on eddy parameterizations, show (i) significantly reduced variance of the upper-ocean heat content at decadal time scales and (ii) differences in the spatial patterns of low-frequency variability compared with higher resolution simulations. Climate projections are typically done with general circulation models with coarse-resolution ocean components. Therefore, these biases affect our ability to predict decadal climate modes of variability and, in turn, hinder climate projections. Our results suggest that for improving climate projections, the community should move towards coupled climate models with higher oceanic resolution.

scholarly journals The relationship between climate forcing and hydrological response in UK catchments

2010 ◽  
Vol 7 (5) ◽  
pp. 7633-7667 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, it is likely that the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

qgs: A flexible Python framework of reduced-order multiscale climate models

2021 ◽  
Author(s):  
Lesley De Cruz ◽  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Open Source Software ◽  
Climate Models ◽  
Low Frequency ◽  
Atmospheric Dynamics ◽  
The Other ◽  
Research Use ◽  
Good Representation ◽  
Atmospheric Variability ◽  
Reduced Order ◽  
Low Frequency Variability

&lt;p&gt;In atmospheric and climate sciences, research and development is often first conducted with a simple idealized system like the Lorenz-&lt;em&gt;N&lt;/em&gt; models (&lt;em&gt;N &amp;#8712;&lt;/em&gt; {63, 84, 96}) which are toy models of atmospheric variability. On the other hand, reduced-order spectral quasi-geostrophic models of the atmosphere with a sufficient number of modes offer a good representation of the dry atmospheric dynamics. They allow one to identify typical features of the atmospheric circulation, such as blocked and zonal circulation regimes, and low-frequency variability. However, these models are less often considered in literature, despite their demonstration of more realistic behavior.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;qgs&lt;/strong&gt; (Demaeyer et al., 2020) aims to popularize these systems by providing a fast and easy-to-use Python framework for researchers and teachers to integrate this kind of model. The documentation makes it clear and efficient to handle the model, by explaining the equations and parameters and linking these to the code.&amp;#160;&lt;/p&gt;&lt;p&gt;The choice to use Python was specifically made to facilitate its use in Jupyter Notebooks and with the multiple recent machine learning libraries that are available in this language.&lt;/p&gt;&lt;p&gt;In this talk, we will present the modeling capabilities of &lt;strong&gt;qgs&lt;/strong&gt; and show its usage in a varieties of didactical and research use cases.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Reference&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Demaeyer, J., De Cruz, L., &amp; Vannitsem, S. (2020). qgs: A flexible Python framework of reduced-order multiscale climate models. Journal of Open Source Software, 5(56), 2597, https://doi.org/10.21105/joss.02597 .&lt;/p&gt;

scholarly journals The role of the North Atlantic overturning and deep-ocean for multi-decadal global-mean-temperature variability

2013 ◽  
Vol 4 (2) ◽  
pp. 967-1003 ◽  
Author(s):  
C. F. Schleussner ◽  
J. Runge ◽  
J. Lehmann ◽  
A. Levermann
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Heat Content ◽  
Deep Ocean ◽  
Meridional Overturning Circulation ◽  
Cmip5 Models ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. Earth's climate exhibits internal modes of variability on various time scales. Here we investigate multi-decadal variability of the Atlantic meridional overturning circulation (AMOC) in the control runs of an ensemble of CMIP5 models. By decomposing global-mean-temperature (GMT) variance into contributions of the AMOC and Northern Hemisphere sea-ice extent using a graph-theoretical statistical approach, we find the AMOC to contribute 8% to GMT variability in the ensemble mean. Our results highlight the importance of AMOC sea-ice feedbacks that explain 5% of the GMT variance, while the contribution solely related to the AMOC is found to be about 3%. As a consequence of multi-decadal AMOC variability, we report substantial variations in North Atlantic deep-ocean heat content with trends of up to 0.7 × 1022 J decade−1 that are of the order of observed changes over the last decade and consistent with the reduced GMT warming trend over this period. Although these temperature anomalies are largely density-compensated by salinity changes, we find a robust negative correlation between the AMOC and North Atlantic deep-ocean density with density lagging the AMOC by 5 to 11 yr in most models. While this would in principle allow for a self-sustained oscillatory behavior of the coupled AMOC–deep-ocean system, our results are inconclusive about the role of this feedback in the model ensemble.

OSNAP and water mass transport in CMIP6 models

2021 ◽  
Author(s):  
Laura Jackson
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Climate Model ◽  
Water Mass ◽  
Deep Convection ◽  
Low Frequency ◽  
Meridional Overturning Circulation ◽  
The West ◽  
Low Frequency Variability ◽  
Meridional Overturning

&lt;p&gt;The Atlantic Meridional Overturning Circulation (AMOC) influences our climate by transporting heat northwards in the Atlantic ocean. The subpolar North Atlantic plays an important role in this circulation, with transformation of water to higher densities, deep convection and formation of deep water. Recent OSNAP observations have shown that the overturning is stronger to the east of Greenland than the west.&lt;/p&gt;&lt;p&gt;Here we analyse a CMIP6 climate model at two resolutions (HadGEM3 GC3.1 LL and MM) and show both compare well with the OSNAP observations. We explore the source of low frequency variability of the AMOC and how it is related to the surface water mass transformation in different regions. We also investigate time-mean and low frequency water mass transformations in other CMIP6 climate models.&lt;/p&gt;

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