Self-generated aperiodic behaviour in a simple climate model

1988 ◽  
Vol 3 (2) ◽  
pp. 105-114 ◽  
Author(s):  
JM Salazar ◽  
C Nicolis
Author(s):  
C R McInnes

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.


1983 ◽  
Vol 43 (5) ◽  
pp. 1019-1041 ◽  
Author(s):  
Michael Ghil ◽  
John Tavantzis

Author(s):  
Antero Ollila

The hiatus or temperature pause during the 21st century has been the subject of numerous research studies with very different results and proposals. In this study, two simple climate models have been applied to test the causes of global temperature changes. The climate change factors have been shortwave (SW) radiation changes, changes in cloudiness and ENSO (El Niño Southern Oscillation) events assessed as the ONI (Oceanic Niño Index) values and anthropogenic climate drivers. The results show that a simple climate model assuming no positive water feedback follows the satellite temperature changes very well, the mean absolute error (MAE) during the period from 2001 to July 2019 being 0.073°C and 0.082°C in respect to GISTEMP. The IPCC’s simple climate model shows for the same period errors of 0.191°C and 0.128°C respectively. The temperature in 2017-2018 was about 0.2°C above the average value in 2002–2014. The conclusion is that the pause was over after 2014 and the SW anomaly forcing was the major reason for this temperature increase. SW anomalies have had their greatest impacts on the global temperature during very strong (super) El Niño events in 1997-98 and 2015-16, providing a new perspective for ENSO events. A positive SW anomaly continued after 2015-16 which may explain the weak La Niña 2016 temperature impacts, and a negative SW anomaly after 1997-98 may have contributed two strong La Niña peaks 1998-2001. No cause and effect connection could be found between the SW radiation and temperature anomalies in Nino areas.


2017 ◽  
Author(s):  
Kuno Strassmann ◽  
Fortunat Joos

Abstract. The Bern Simple Climate Model (BernSCM v1.0) is a free open source reimplementation of a reduced form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRF). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near linear behaviour. Illustrative simulations of scenarios from previous multi-model studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided as open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal timesteps with high accuracy, it is suitable for studies with high computational load, and for coupling with, e.g., Integrated Assessment Models (IAM). Further applications include climate risk assessment in a business, public, or educational context, and the estimation of CO2 and climate benefits of emission mitigation options.


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