scholarly journals Detecting causality signal in instrumental measurements and climate model simulations: global warming case study

2019 ◽  
Author(s):  
Mikhail Y. Verbitsky ◽  
Michael E. Mann ◽  
Byron A. Steinman ◽  
Dmitry M. Volobuev
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Anthropogenic Forcing ◽  
Carbon Dioxide Concentrations ◽  
Climate Model Simulations ◽  
Earth’S Climate

Abstract. Detecting the direction and strength of the causality signal in observed time series is becoming a popular tool for exploration of distributed systems such as Earth's climate system. Here we suggest that in addition to reproducing observed time series of climate variables within required accuracy a model should also exhibit the causality relationship between variables found in nature. Specifically, we propose a novel framework for a comprehensive analysis of climate model responses to external natural and anthropogenic forcing based on the method of conditional dispersion. As an illustration, we assess the causal relationship between anthropogenic forcing (i.e., atmospheric carbon dioxide concentration) and surface temperature anomalies. We demonstrate a strong directional causality between global temperatures and carbon dioxide concentrations (meaning that carbon dioxide affects temperature stronger than temperature affects carbon dioxide) in both the observations and in (CMIP5) climate model simulated temperatures.

scholarly journals Detecting causality signal in instrumental measurements and climate model simulations: global warming case study

2019 ◽  
Vol 12 (9) ◽  
pp. 4053-4060 ◽  
Author(s):  
Mikhail Y. Verbitsky ◽  
Michael E. Mann ◽  
Byron A. Steinman ◽  
Dmitry M. Volobuev
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Coupled Model ◽  
Anthropogenic Forcing ◽  
Carbon Dioxide Concentrations ◽  
Climate Model Simulations ◽  
Earth’S Climate

Abstract. Detecting the direction and strength of the causality signal in observed time series is becoming a popular tool for exploration of distributed systems such as Earth's climate system. Here, we suggest that in addition to reproducing observed time series of climate variables within required accuracy a model should also exhibit the causality relationship between variables found in nature. Specifically, we propose a novel framework for a comprehensive analysis of climate model responses to external natural and anthropogenic forcing based on the method of conditional dispersion. As an illustration, we assess the causal relationship between anthropogenic forcing (i.e., atmospheric carbon dioxide concentration) and surface temperature anomalies. We demonstrate a strong directional causality between global temperatures and carbon dioxide concentrations (meaning that carbon dioxide affects temperature more than temperature affects carbon dioxide) in both the observations and in (Coupled Model Intercomparison Project phase 5; CMIP5) climate model simulated temperatures.

scholarly journals Snowfall-albedo feedbacks could have led to deglaciation of snowball Earth starting from mid-latitudes

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Philipp de Vrese ◽  
Tobias Stacke ◽  
Jeremy Caves Rugenstein ◽  
Jason Goodman ◽  
Victor Brovkin
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Climate Models ◽  
Hydrological Cycle ◽  
High Surface ◽  
Dust Deposition ◽  
Carbon Dioxide Concentrations ◽  
Maximum Temperatures ◽  
Carbon Dioxide Levels ◽  
Earth’S Climate

AbstractSimple and complex climate models suggest a hard snowball – a completely ice-covered planet – is one of the steady-states of Earth’s climate. However, a seemingly insurmountable challenge to the hard-snowball hypothesis lies in the difficulty in explaining how the planet could have exited the glaciated state within a realistic range of atmospheric carbon dioxide concentrations. Here, we use simulations with the Earth system model MPI-ESM to demonstrate that terminal deglaciation could have been triggered by high dust deposition fluxes. In these simulations, deglaciation is not initiated in the tropics, where a strong hydrological cycle constantly regenerates fresh snow at the surface, which limits the dust accumulation and snow aging, resulting in a high surface albedo. Instead, comparatively low precipitation rates in the mid-latitudes in combination with high maximum temperatures facilitate lower albedos and snow dynamics that – for extreme dust fluxes – trigger deglaciation even at present-day carbon dioxide levels.

scholarly journals Technical Note: Long-term memory effect in the atmospheric CO<sub>2</sub> concentration at Mauna Loa

2006 ◽  
Vol 6 (6) ◽  
pp. 11957-11970 ◽  
Author(s):  
C. Varotsos ◽  
M.-N. Assimakopoulos ◽  
M. Efstathiou
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Power Law ◽  
Carbon Dioxide Concentration ◽  
Global Climate Models ◽  
Fluctuation Analysis ◽  
Original Time Series ◽  
Mauna Loa ◽  
Carbon Dioxide Concentrations ◽  
Original Time

Abstract. The monthly mean values of the atmospheric carbon dioxide concentration derived from in-situ air samples collected at Mauna Loa Observatory, Hawaii, during 1958–2004 (the longest continuous record available in the world) are analyzed by employing the detrended fluctuation analysis to detect scaling behavior in this time series. The main result is that the fluctuations of carbon dioxide concentrations exhibit long-range power-law correlations (long memory) with lag times ranging from four months to eleven years, which correspond to 1/f noise. This result indicates that random perturbations in the carbon dioxide concentrations give rise to noise, characterized by a frequency spectrum following a power-law with exponent that approaches to one; the latter shows that the correlation times grow strongly. This feature is pointing out that a correctly rescaled subset of the original time series of the carbon dioxide concentrations resembles the original time series. Finally, the power-law relationship derived from the real measurements of the carbon dioxide concentrations could also serve as a tool to improve the confidence of the atmospheric chemistry-transport and global climate models.

Stochastic analysis of time-series related to ocean acidification

2021 ◽  
Author(s):  
Georgios Vagenas ◽  
Theano Iliopoulou ◽  
Panayiotis Dimitriadis ◽  
Demetris Koutsoyiannis
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Ocean Acidification ◽  
Atmospheric Carbon Dioxide ◽  
Anthropogenic Activities ◽  
Time Lag ◽  
Carbon Dioxide Concentration ◽  
Carbon Dioxide Partial Pressure ◽  
Chemical Transformations ◽  
Mauna Loa

&lt;p&gt;Since the pre-industrial era at the end of the 18&lt;sup&gt;th&lt;/sup&gt; century, the atmospheric carbon dioxide concentration (CO&lt;sub&gt;2&lt;/sub&gt;) has increased by 47.46% from the level of 280 ppmv (parts per million volume) to 412.89 ppmv (Mauna Loa &amp;#8211; NOAA Station, November 2020). These increased concentrations caused by natural &amp; anthropogenic activities, interact with the aquatic environment which acts as a safety valve. Nevertheless, the absorbed CO&lt;sub&gt;2 &lt;/sub&gt;amounts undergo chemical transformations, resulting in increasing ionized concentrations that can significantly reduce the water&amp;#8217;s pH, a process described as ocean acidification. Here, we use the HOT (Hawaii-Ocean-Time series) to perform time series analysis for temperature, carbon dioxide partial pressure and pH. More specifically, we analyze their temporal changes in month and annual time lag. Then, we proceed in comparisons with relevant studies on atmospheric data to evaluate the produced results. Finally, we make an effort to disentangle the results with simplified assumptions connected with the observed impact of ocean acidification on the aquatic ecosystems.&lt;/p&gt;

scholarly journals Space-based geoengineering: Challenges and requirements

2009 ◽  
Vol 224 (3) ◽  
pp. 571-580 ◽  
Author(s):  
C R McInnes
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Large Scale ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Complex Solution ◽  
Lagrange Point ◽  
Simple Climate Model ◽  
Earth’S Climate

The prospect of engineering the Earth's climate (geoengineering) raises a multitude of issues associated with climatology, engineering on macroscopic scales, and indeed the ethics of such ventures. Depending on personal views, such large-scale engineering is either an obvious necessity for the deep future, or yet another example of human conceit. In this article a simple climate model will be used to estimate requirements for engineering the Earth's climate, principally using space-based geoengineering. Active cooling of the climate to mitigate anthropogenic climate change due to a doubling of the carbon dioxide concentration in the Earth's atmosphere is considered. This representative scenario will allow the scale of the engineering challenge to be determined. It will be argued that simple occulting discs at the interior Lagrange point may represent a less complex solution than concepts for highly engineered refracting discs proposed recently. While engineering on macroscopic scales can appear formidable, emerging capabilities may allow such ventures to be seriously considered in the long term. This article is not an exhaustive review of geoengineering, but aims to provide a foretaste of the future opportunities, challenges, and requirements for space-based geoengineering ventures.

scholarly journals A Permafrost Implementation in the Simple Carbon-Climate Model Hector

2021 ◽  
Author(s):  
Dawn L. Woodard ◽  
Alexey N. Shiklomanov ◽  
Ben Kravitz ◽  
Corinne Hartin ◽  
Ben Bond-Lamberty
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Computational Cost ◽  
Carbon Dioxide Concentration ◽  
Climate Feedback ◽  
Permafrost Soil ◽  
Atmospheric Carbon Dioxide Concentration ◽  
Wide Range ◽  
Atmospheric Carbon

Abstract. Permafrost, soil that remains below 0 °C for two or more years, currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using Earth system models (ESMs), but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon-climate model Hector, calibrated to be consistent with both historical data and twenty-first century ESM projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane and carbon dioxide once thawed; the thaw rate is controlled by region-specific air temperature increases from a pre-industrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector's atmospheric carbon dioxide concentration by 10–15 % and the atmospheric methane concentration by 10–20 %, depending on the future scenario. This resulted in around 0.5 °C of additional warming over the next century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change and atmospheric carbon dioxide concentration in the model and became increasingly significant over even longer timescales. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and easily coupled with integrated assessment models to explore the economic consequences of warming from this feedback.

scholarly journals Do fossil plants signal palaeoatmospheric carbon dioxide concentration in the geological past?

1998 ◽  
Vol 353 (1365) ◽  
pp. 83-96 ◽  
Author(s):  
J. C. McElwain
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Middle Eocene ◽  
Stomatal Density ◽  
Carbon Dioxide Concentration ◽  
Fossil Plants ◽  
Early Devonian ◽  
Carbon Dioxide Concentrations ◽  
Atmospheric Carbon

Fossil, subfossil, and herbarium leaves have been shown to provide a morphological signal of the atmospheric carbon dioxide environment in which they developed by means of their stomatal density and index. An inverse relationship between stomatal density/index and atmospheric carbon dioxide concentration has been documented for all the studies to date concerning fossil and subfossil material. Furthermore, this relationship has been demonstrated experimentally by growing plants under elevated and reducedcarbon dioxide concentrations. To date, the mechanism that controls the stomatal density response to atmospheric carbon dioxide concentration remains unknown. However, stomatal parameters of fossil plants have been successfully used as a proxy indicator of palaeo–carbon dioxide levels. This paper presents new estimates of palaeo–atmospheric carbon dioxide concentrations for the Middle Eocene (Lutetian), based on the stomatal ratios of fossil Lauraceae species from Bournemouth in England. Estimates of atmospheric carbon dioxide concentrations derived from stomatal data from plants of the Early Devonian, Late Carboniferous, Early Permian and Middle Jurassic ages are reviewed in the light of new data. Semi–quantitative palaeo–carbon dioxide estimates based on the stomatal ratio (a ratio of the stomatal index of a fossil plant to that of a selected nearest living equivalent) have in the past relied on the use of a Carboniferous standard. The application of a new standard based on the present–day carbon dioxide level is reported here for comparison. The resultant ranges of palaeo–carbon dioxide estimates made from standardized fossil stomatal ratio data are in good agreement with both carbon isotopic data from terrestrial and marine sources and long–term carbon cycle modelling estimates for all the time periods studied. These data indicate elevated atmospheric carbon dioxide concentrations during the Early Devonian, Middle Jurassic and Middle Eocene, and reduced concentrations during the Late Carboniferous and Early Permian. Such data are important in demonstrating the long–term responses of plants to changing carbon dioxide concentrations and in contributing to the database needed for general circulation model climatic analogues.

scholarly journals Technical Note: Long-term memory effect in the atmospheric CO<sub>2</sub> concentration at Mauna Loa

2007 ◽  
Vol 7 (3) ◽  
pp. 629-634 ◽  
Author(s):  
C. Varotsos ◽  
M.-N. Assimakopoulos ◽  
M. Efstathiou
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Power Law ◽  
Carbon Dioxide Concentration ◽  
Global Climate Models ◽  
Fluctuation Analysis ◽  
Original Time Series ◽  
Mauna Loa ◽  
Carbon Dioxide Concentrations ◽  
Original Time

Abstract. The monthly mean values of the atmospheric carbon dioxide concentration derived from in-situ air samples collected at Mauna Loa Observatory, Hawaii, USA during 1958–2004 (the longest continuous record available in the world) are analyzed by employing the detrended fluctuation analysis to detect scaling behavior in this time series. The main result is that the fluctuations of carbon dioxide concentrations exhibit long-range power-law correlations (long memory) with lag times ranging from four months to eleven years, which correspond to 1/f noise. This result indicates that random perturbations in the carbon dioxide concentrations give rise to noise, characterized by a frequency spectrum following a power-law with exponent that approaches to one; the latter shows that the correlation times grow strongly. This feature is pointing out that a correctly rescaled subset of the original time series of the carbon dioxide concentrations resembles the original time series. Finally, the power-law relationship derived from the real measurements of the carbon dioxide concentrations could also serve as a tool to improve the confidence of the atmospheric chemistry-transport and global climate models.

CFD Analysis on Thermal Comfort and Indoor Air Quality Affected by Partitions in Air-Conditioned Building

2016 ◽  
Vol 836 ◽  
pp. 121-126
Author(s):  
Pradip Aryal ◽  
Thananchai Leephakpreeda
Keyword(s):  
Carbon Dioxide ◽  
Air Quality ◽  
Thermal Comfort ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Carbon Dioxide Concentration ◽  
Average Concentration ◽  
Cfd Analysis ◽  
Carbon Dioxide Concentrations

This paper presents a CFD analysis on thermal comfort and indoor air quality affected by partitions in an air-conditioned building. CFD experiments are carried out to simulate variables of indoor air before/after installation or removal of partitions. Accordingly, the Predicted Mean Vote (PMV) is determined as an indicator of thermal comfort while the carbon dioxide concentration within an air-conditioned space is used for the assessment of indoor air quality. Some simulated results are validated by measurements with good agreement where a case study is conducted in an air-conditioned space of a library. With the proposed methodology, it can be recommended in a case study that the significant effects of partition on thermal comfort are observed where the area with neutral sensation and slightly-cool sensation reduces significantly. The occupants feel uncomfortably cold after installing partition. The carbon dioxide concentrations slightly increase in some areas but the average concentration remains acceptable according to ASHRAE standard. Without the reinforcement of the air-conditioning units, the installation of partition at the desired location is not encouraged regarding to occupant’s thermal comfort and indoor air quality.

Communication: Photoinduced Carbon Dioxide Binding with Surface-Functionalized Silicon Quantum Dots

2018 ◽  
Author(s):  
Oscar A. Douglas-Gallardo ◽  
Cristián Gabriel Sánchez ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Carbon Dioxide ◽  
Quantum Dots ◽  
Atmospheric Carbon Dioxide ◽  
Density Functional ◽  
Tight Binding ◽  
Carbon Dioxide Concentration ◽  
Research Area ◽  
Silicon Quantum Dots ◽  
Dependent Model ◽  
Photoinduced Charge

<div> <div> <div> <p>Nowadays, the search of efficient methods able to reduce the high atmospheric carbon dioxide concentration has turned into a very dynamic research area. Several environmental problems have been closely associated with the high atmospheric level of this greenhouse gas. Here, a novel system based on the use of surface-functionalized silicon quantum dots (sf -SiQDs) is theoretically proposed as a versatile device to bind carbon dioxide. Within this approach, carbon dioxide trapping is modulated by a photoinduced charge redistribution between the capping molecule and the silicon quantum dots (SiQDs). Chemical and electronic properties of the proposed SiQDs have been studied with Density Functional Theory (DFT) and Density Functional Tight-Binding (DFTB) approach along with a Time-Dependent model based on the DFTB (TD-DFTB) framework. To the best of our knowledge, this is the first report that proposes and explores the potential application of a versatile and friendly device based on the use of sf -SiQDs for photochemically activated carbon dioxide fixation. </p> </div> </div> </div>

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