论文标题
通过随机气候模型调查各种排放减少和碳捕获场景下的气候临界点
Investigating climate tipping points under various emission reduction and carbon capture scenarios with a stochastic climate model
论文作者
论文摘要
我们使用能量平衡模型研究了气候转化点转变的缓解。通过温室效应，全球平均表面温度的演变与二氧化碳浓度相结合。我们用随机延迟差分方程（SDDE）对二氧化碳浓度进行建模，以考虑各种碳发射和捕获场景。所得的SDDES耦合系统表现出临界点现象：如果CO2浓度超过临界阈值（约478ppm），则温度会突然增加约6摄氏度。我们表明，二氧化碳浓度表现出瞬时生长，即使浓度渐近地衰减，也可能导致气候转化点。我们为二氧化碳演化提供了严格的上限，该连接量化了其瞬态和渐近生长，并为逃避气候临界点提供了足够的条件。将这种上限与随机气候模型的蒙特卡洛模拟相结合，我们研究了将避免转化点的发射减少和碳捕获场景。
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 CO2 concentration through the green house effect. We model the CO2 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 CO2 concentration exceeds a critical threshold (around 478ppm), the temperature experiences an abrupt increase of about six degrees Celsius. We show that the CO2 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 CO2 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.
