scholarly journals Investigating climate tipping points under various emission reduction and carbon capture scenarios with a stochastic climate model

2021 ◽  
Vol 477 (2256) ◽  
Author(s):  
Alexander Mendez ◽  
Mohammad Farazmand
Keyword(s):  
Upper Bound ◽  
Emission Reduction ◽  
Carbon Capture ◽  
Climate Model ◽  
Sufficient Conditions ◽  
Coupled System ◽  
Tipping Point ◽  
Balance Model ◽  
Critical Threshold ◽  
Stochastic Climate Model

We study the mitigation of climate tipping point transitions using an energy balance model. The evolution of the global mean surface temperature is coupled with the CO 2 concentration through the green-house effect. We model the CO 2 concentration with a stochastic delay differential equation (SDDE), accounting for various carbon emission and capture scenarios. The resulting coupled system of SDDEs exhibits a tipping point phenomena: if CO 2 concentration exceeds a critical threshold (around 478   ppm ), the temperature experiences an abrupt increase of about six degrees Celsius. We show that the CO 2 concentration exhibits a transient growth which may cause a climate tipping point, even if the concentration decays asymptotically. We derive a rigorous upper bound for the CO 2 evolution which quantifies its transient and asymptotic growths, and provides sufficient conditions for evading the climate tipping point. Combining this upper bound with Monte Carlo simulations of the stochastic climate model, we investigate the emission reduction and carbon capture scenarios that would avert the tipping point.

scholarly journals Delay-Dependent Robust Stabilization for Nonlinear Large Systems via Decentralized Fuzzy Control

2011 ◽  
Vol 2011 ◽  
pp. 1-20 ◽  
Author(s):  
Chun-xia Dou ◽  
Zhi-sheng Duan ◽  
Xing-bei Jia ◽  
Xiao-gang Li ◽  
Jin-zhao Yang ◽  
...  
Keyword(s):  
Time Delay ◽  
Fuzzy Control ◽  
Upper Bound ◽  
Time Delays ◽  
Sufficient Conditions ◽  
Large System ◽  
Disturbance Attenuation ◽  
Robust Controller ◽  
Large Systems ◽  
Delay Dependent

A delay-dependent robust fuzzy control approach is developed for a class of nonlinear uncertain interconnected time delay large systems in this paper. First, an equivalent T–S fuzzy model is extended in order to accurately represent nonlinear dynamics of the large system. Then, a decentralized state feedback robust controller is proposed to guarantee system stabilization with a prescribedH∞disturbance attenuation level. Furthermore, taking into account the time delays in large system, based on a less conservative delay-dependent Lyapunov function approach combining with linear matrix inequalities (LMI) technique, some sufficient conditions for the existence ofH∞robust controller are presented in terms of LMI dependent on the upper bound of time delays. The upper bound of time-delay and minimizedH∞performance index can be obtained by using convex optimization such that the system can be stabilized and for all time delays whose sizes are not larger than the bound. Finally, the effectiveness of the proposed controller is demonstrated through simulation example.

Modelling nitrogen transport across compartments over northern Europe

2021 ◽  
Author(s):  
Stefan Hagemann ◽  
Ute Daewel ◽  
Volker Matthias ◽  
Tobias Stacke
Keyword(s):  
Baltic Sea ◽  
Land Surface ◽  
Climate Model ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Regional Climate ◽  
Marine Ecosystem ◽  
Coupled System ◽  
Nutrient Concentrations ◽  
Nutrient Loads

<p>River discharge and the associated nutrient loads are important factors that influence the functioning of the marine ecosystem. Lateral inflows from land carrying fresh, nutrient-rich water determine coastal physical conditions and nutrient concentration and, hence, dominantly influence primary production in the system. Since this forms the basis of the trophic food web, riverine nutrient concentrations impact the variability of the whole coastal ecosystem. This process becomes even more relevant in systems like the Baltic Sea, which is almost decoupled from the open ocean and land-borne nutrients play a major role for ecosystem productivity on seasonal up to decadal time scales.</p><p> </p><p>In order to represent the effects of climate or land use change on nutrient availability, a coupled system approach is required to simulate the transport of nutrients across Earth system compartments. This comprises their transport within the atmosphere, the deposition and human application at the surface, the lateral transport over the land surface into the ocean and their dynamics and transformation in the marine ecosystem. In our study, we combine these processes in a modelling chain within the GCOAST (Geesthacht Coupled cOAstal model SysTem) framework for the northern European region. This modelling chain comprises:</p><p> </p><ul><li>Simulation of emissions, atmospheric transport and deposition with the chemistry transport model CMAQ at 36 km grid resolution using atmospheric forcing from the coastDat3 data that have been generated with the regional climate model COSMO-CLM over Europe at 0.11° resolution using ERA-Interim re-analyses as boundary conditions</li> <li>Simulation of inert processes at the land surface with the global hydrology model HydroPy (former MPI-HM), i.e. considering total nitrogen without any chemical reactions</li> <li>Riverine transport with the Hydrological Discharge (HD) model at 0.0833° spatial resolution</li> <li>Simulation of the North Sea and Baltic Sea ecosystems with 3D coupled physical-biogeochemical NPZD-model ECOSMO II at about 10 km resolution</li> </ul><p> </p><p>We will present first results and their validation from this exercise.</p><p> </p>

scholarly journals An advanced scheme for wet scavenging and liquid-phase chemistry in a regional online-coupled chemistry transport model

2013 ◽  
Vol 13 (3) ◽  
pp. 1177-1192 ◽  
Author(s):  
C. Knote ◽  
D. Brunner
Keyword(s):  
Aqueous Phase ◽  
Climate Model ◽  
Transport Model ◽  
Measurement Data ◽  
Coupled System ◽  
Cloud Microphysics ◽  
Microphysics Scheme ◽  
Meteorological Model ◽  
Wet Scavenging ◽  
Phase Chemistry

Abstract. Clouds are reaction chambers for atmospheric trace gases and aerosols, and the associated precipitation is a major sink for atmospheric constituents. The regional chemistry-climate model COSMO-ART has been lacking a description of wet scavenging of gases and aqueous-phase chemistry. In this work we present a coupling of COSMO-ART with a wet scavenging and aqueous-phase chemistry scheme. The coupling is made consistent with the cloud microphysics scheme of the underlying meteorological model COSMO. While the choice of the aqueous-chemistry mechanism is flexible, the effects of a simple sulfur oxidation scheme are shown in the application of the coupled system in this work. We give details explaining the coupling and extensions made, then present results from idealized flow-over-hill experiments in a 2-D model setup and finally results from a full 3-D simulation. Comparison against measurement data shows that the scheme efficiently reduces SO2 trace gas concentrations by 0.3 ppbv (−30%) on average, while leaving O3 and NOx unchanged. PM10 aerosol mass was increased by 10% on average. While total PM2.5 changes only little, chemical composition is improved notably. Overestimations of nitrate aerosols are reduced by typically 0.5–1 μg m−3 (up to −2 μg m−3 in the Po Valley) while sulfate mass is increased by 1–1.5 μg m−3 on average (up to 2.5 μg m−3 in Eastern Europe). The effect of cloud processing of aerosols on its size distribution, i.e. a shift towards larger diameters, is observed. Compared against wet deposition measurements the system tends to underestimate the total wet deposited mass for the simulated case study.

scholarly journals A Two-Dimensional Coupled Atmosphere-Ice-Sheet-Continent Model Designed for Paleoclimatic Simulations

1990 ◽  
Vol 14 ◽  
pp. 55-57 ◽  
Author(s):  
M.B. Esch ◽  
K. Herterich
Keyword(s):  
Climate Model ◽  
Hydrological Cycle ◽  
Vertical Plane ◽  
Ice Sheet ◽  
Ice Age ◽  
Balance Model ◽  
Two Dimensional ◽  
Geothermal Heat ◽  
The North ◽  
Slow Evolution

We present a two-dimensional climate model to be used for basic dynamic studies on ice-age time scales (103 to 106 years). The model contains an ice sheet, where flow and temperature are calculated in a vertical plane, oriented in the north-south direction. The model ice sheet is forced by a zonally-averaged atmospheric energy-balance model, including a seasonal cycle and a simplified hydrological cycle, which specifies ice temperature and the mass balance at the ice-sheet surface. At the bottom of the ice sheet, the geothermal heat flux is prescribed. In addition, delayed bedrock sinking (or bedrock rising) is assumed.A stationary state is achieved after 200 000 model years. This long time scale is introduced by the slow evolution of the temperature field within the ice sheet. Using reasonable parameter values and presently observed precipitation patterns, modified by ice-sheet orography, the observed thickness to length ratio (4 km/3300 km) of the Laurentide ice sheet can be simulated within a realistic build-up time (40 000 years). Near the ice bottom, temperate regions developed. They may have had an important effect on ice-sheet build-up and ice-sheet decay.

scholarly journals A strict upper bound for size multipartite Ramsey numbers of paths versus stars

2017 ◽  
Vol 1 (2) ◽  
pp. 9
Author(s):  
Chula Jayawardene
Keyword(s):  
Natural Number ◽  
Complete Graph ◽  
Upper Bound ◽  
Sufficient Conditions ◽  
Necessary And Sufficient Conditions ◽  
Infinite Class ◽  
Ramsey Numbers ◽  
Necessary And Sufficient

<p>Let $P_n$ represent the path of size $n$. Let $K_{1,m-1}$ represent a star of size $m$ and be denoted by $S_{m}$. Given a two coloring of the edges of a complete graph $K_{j \times s}$ we say that $K_{j \times s}\rightarrow (P_n,S_{m+1})$ if there is a copy of $P_n$ in the first color or a copy of $S_{m+1}$ in the second color. The size Ramsey multipartite number $m_j(P_n, S_{m+1})$ is the smallest natural number $s$ such that $K_{j \times s}\rightarrow (P_n,S_{m+1})$. Given $j,n,m$ if $s=\left\lceil \dfrac{n+m-1-k}{j-1} \right\rceil$, in this paper, we show that the size Ramsey numbers $m_j(P_n,S_{m+1})$ is bounded above by $s$ for $k=\left\lceil \dfrac{n-1}{j} \right\rceil$. Given $j\ge 3$ and $s$, we will obtain an infinite class $(n,m)$ that achieves this upper bound $s$. In the later part of the paper, will also investigate necessary and sufficient conditions needed for the upper bound to hold.</p>

A global decadal mode in a high-end climate model and in observations: Any connection to the solar cycle?

2021 ◽  
Author(s):  
Michael Ghil ◽  
Yizhak Feliks ◽  
Justin Small
Keyword(s):  
Solar Cycle ◽  
Sea Level ◽  
North Atlantic ◽  
Climate Model ◽  
Decadal Variability ◽  
Singular Spectrum Analysis ◽  
Coupled System ◽  
The North ◽  
Spatio Temporal ◽  
Decadal Mode

&lt;p&gt;The present work addresses two persistent quandaries of the climate sciences: (i) the existence of global oscillatory modes in the coupled ocean&amp;#8211;atmosphere system; and (ii) solar effects on this coupled system. Interannual oscillatory modes, atmospheric and oceanic, are present in several large regions of the globe. We examine here interannual-to-decadal variability over the entire globe in the Community Earth System Model (CESM) and in the NCEP-NCAR reanalysis, and apply multichannel singular spectrum analysis (MSSA) to these two datasets.&lt;/p&gt;&lt;p&gt;In the fully coupled CESM1.1 model, with its resolution of 0.1 &amp;#215; 0.1 degrees in the ocean and 0.25 &amp;#215; 0.25 degrees in the atmosphere, the &amp;#64257;elds analyzed are surface temperatures, sea level pressures and&amp;#160; the 200-hPa geopotential. The simulation is 100-yr long and the last 66 yr are used in the analysis. The two statistically signi&amp;#64257;cant periodicities in this IPCC-class model are 11 and 3.4 yr.&lt;/p&gt;&lt;p&gt;In the reanalysis, the &amp;#64257;elds of sea level pressure and of 200-hPa geopotential are analyzed at its resolution of 2.5 &amp;#215; 2.5 degrees over the 68-yr interval 1949&amp;#8211;2016. Oscillations with periods of 12 and 3.6 yr are found to be statistically signi&amp;#64257;cant in this dataset. The spatio-temporal patterns&amp;#160; of the oscillations in the two datasets are quite similar. The spatial pattern of these&amp;#160; global oscillations over the North Paci&amp;#64257;c and North Atlantic resemble the Paci&amp;#64257;c Decadal Oscillation and the interannual variability found in the western North Atlantic, respectively.&lt;/p&gt;&lt;p&gt;The two global modes, with their 11&amp;#8211;12-yr and 3.4&amp;#8211;3.6-yr periodicities, are quite robust, suggesting potential contributions of both to predictability at 1&amp;#8211;3-yr horizons. On the other hand, the CESM run has no year-to-year changes in the prescribed insolation, excluding any role of the solar cycle in the model&amp;#8217;s 11-yr mode. The solar cycle is present, however, in the reanalysis, since it is present in nature and hence it does affect the observations. We speculate, therefore, that regional oscillations &amp;#8212; with their distinct near-periodicities and spatial patterns &amp;#8212; are synchronized&amp;#160; over the globe, thus yielding both the global oscillatory modes found in CESM. In nature, the decadal mode could be further synchronized with the solar cycle, but that does not seem to be the case, given the slight difference in period &amp;#8212; 12 yr for the reanalysis and 11 yr for the solar cycle, which makes them drift in and out of phase.&lt;/p&gt;&lt;p&gt;The work&amp;#8217;s tentative conclusion is, therefore: (i) yes, there are global oscillatory modes in the climate system, especially a decadal mode; but (ii) no, this mode has little or nothing to do with the solar cycle.&lt;/p&gt;

scholarly journals Numerical Development and Evaluation of an Energy Conserving Conceptual Stochastic Climate Model

2019 ◽  
Vol 5 (1) ◽  
pp. 45-64 ◽  
Author(s):  
Federica Gugole ◽  
Christian L. E. Franzke
Keyword(s):  
Energy Conservation ◽  
Total Energy ◽  
Prediction Models ◽  
Climate Model ◽  
Empirical Orthogonal Functions ◽  
Correlated Noise ◽  
Spatial Covariance ◽  
Conservation Of Energy ◽  
Stochastic Climate Model ◽  
Energy Conserving

AbstractIn this study we aim to present the successful development of an energy conserving conceptual stochastic climate model based on the inviscid 2-layer Quasi-Geostrophic (QG) equations. The stochastic terms have been systematically derived and introduced in such away that the total energy is conserved. In this proof of concept studywe give particular emphasis to the numerical aspects of energy conservation in a highdimensional complex stochastic system andwe analyzewhat kind of assumptions regarding the noise should be considered in order to obtain physical meaningful results. Our results show that the stochastic model conserves energy to an accuracy of about 0.5% of the total energy; this level of accuracy is not affected by the introduction of the noise, but is mainly due to the level of accuracy of the deterministic discretization of the QG model. Furthermore, our results demonstrate that spatially correlated noise is necessary for the conservation of energy and the preservation of important statistical properties, while using spatially uncorrelated noise violates energy conservation and gives unphysical results. A dynamically consistent spatial covariance structure is determined through Empirical Orthogonal Functions (EOFs). We find that only a small number of EOFs is needed to get good results with respect to energy conservation, autocorrelation functions, PDFs and eddy length scale when comparing a deterministic control simulation on a 512 × 512 grid to a stochastic simulation on a 128 × 128 grid. Our stochastic approach has the potential to seamlessly be implemented in comprehensive weather and climate prediction models.

scholarly journals The effect of a dynamic soil scheme on the climate of the mid-Holocene and the Last Glacial Maximum

2016 ◽  
Vol 12 (1) ◽  
pp. 151-170 ◽  
Author(s):  
M. Stärz ◽  
G. Lohmann ◽  
G. Knorr
Keyword(s):  
Last Glacial Maximum ◽  
Positive Feedback ◽  
Climate Model ◽  
Soil Characteristics ◽  
Glacial Maximum ◽  
Balance Model ◽  
Primary Control ◽  
Last Glacial ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract. In order to account for coupled climate–soil processes, we have developed a soil scheme which is asynchronously coupled to a comprehensive climate model with dynamic vegetation. This scheme considers vegetation as the primary control of changes in physical soil characteristics. We test the scheme for a warmer (mid-Holocene) and colder (Last Glacial Maximum) climate relative to the preindustrial climate. We find that the computed changes in physical soil characteristics lead to significant amplification of global climate anomalies, representing a positive feedback. The inclusion of the soil feedback yields an extra surface warming of 0.24 °C for the mid-Holocene and an additional global cooling of 1.07 °C for the Last Glacial Maximum. Transition zones such as desert–savannah and taiga–tundra exhibit a pronounced response in the model version with dynamic soil properties. Energy balance model analyses reveal that our soil scheme amplifies the temperature anomalies in the mid-to-high northern latitudes via changes in the planetary albedo and the effective longwave emissivity. As a result of the modified soil treatment and the positive feedback to climate, part of the underestimated mid-Holocene temperature response to orbital forcing can be reconciled in the model.

scholarly journals Multiple input control strategies for robust and adaptive climate engineering in a low-order 3-box model

2018 ◽  
Vol 474 (2217) ◽  
pp. 20180447 ◽  
Author(s):  
F. Bonetti ◽  
C. McInnes
Keyword(s):  
Adaptive Control ◽  
Radiative Forcing ◽  
Climate Model ◽  
Control Strategies ◽  
Adaptive Controller ◽  
Multivariable Control ◽  
Balance Model ◽  
Solar Radiation Management ◽  
Climate Engineering ◽  
Low Order

A low-order 3-box energy balance model for the climate system is employed with a multivariable control scheme for the evaluation of new robust and adaptive climate engineering strategies using solar radiation management. The climate engineering measures are deployed in three boxes thus representing northern, southern and central bands. It is shown that, through heat transport between the boxes, it is possible to effect a degree of latitudinal control through the reduction of insolation. The approach employed consists of a closed-loop system with an adaptive controller, where the required control intervention is estimated under the RCP 4.5 radiative scenario. Through the online estimation of the controller parameters, adaptive control can overcome key issues related to uncertainties of the climate model, the external radiative forcing and the dynamics of the actuator used. In fact, the use of adaptive control offers a robust means of dealing with unforeseeable abrupt perturbations, as well as the parametrization of the model considered, to counteract the RCP 4.5 scenario, while still providing bounds on stability and control performance. Moreover, applying multivariable control theory also allows the formal controllability and observability of the system to be investigated in order to identify all feasible control strategies.

scholarly journals ESD Ideas: The stochastic climate model shows that underestimated Holocene trends and variability represent two sides of the same coin

2018 ◽  
Vol 9 (4) ◽  
pp. 1279-1281 ◽  
Author(s):  
Gerrit Lohmann
Keyword(s):  
Climate Model ◽  
Sea Surface ◽  
System Sensitivity ◽  
Statistical Fluctuations ◽  
Fluctuation Dissipation ◽  
Temperature Trends ◽  
Fluctuation Dissipation Theorem ◽  
Stochastic Climate Model ◽  
Two Sides

Abstract. Holocene sea surface temperature trends and variability are underestimated in models compared to paleoclimate data. The idea is presented that the local trends and variability are related, which is elaborated in a conceptual framework of the stochastic climate model. The relation is a consequence of the fluctuation–dissipation theorem, connecting the linear response of a system to its statistical fluctuations. Consequently, the spectrum can be used to estimate the timescale-dependent climate response. The non-normality in the propagation operator introduces enhanced long-term variability related to nonequilibrium and/or Earth system sensitivity. The simple model can guide us to analyze comprehensive models' behavior.

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