scholarly journals Flexible parameter-sparse global temperature time profiles that stabilise at 1.5 and 2.0  °C

2017 ◽  
Vol 8 (3) ◽  
pp. 617-626 ◽  
Author(s):  
Chris Huntingford ◽  
Hui Yang ◽  
Anna Harper ◽  
Peter M. Cox ◽  
Nicola Gedney ◽  
...  
Keyword(s):  
Climate Model ◽  
Algebraic Curves ◽  
Climate Impacts ◽  
Global Temperature ◽  
Temperature Profiles ◽  
Average Temperature ◽  
Time Profiles ◽  
Generational Changes ◽  
Climate Model Simulations ◽  
Two Parameters

Abstract. The meeting of the United Nations Framework Convention on Climate Change (UNFCCC) in December 2015 committed parties at the convention to hold the rise in global average temperature to well below 2.0 °C above pre-industrial levels. It also committed the parties to pursue efforts to limit warming to 1.5 °C. This leads to two key questions. First, what extent of emissions reduction will achieve either target? Second, what is the benefit of the reduced climate impacts from keeping warming at or below 1.5 °C? To provide answers, climate model simulations need to follow trajectories consistent with these global temperature limits. It is useful to operate models in an inverse mode to make model-specific estimates of greenhouse gas (GHG) concentration pathways consistent with the prescribed temperature profiles. Further inversion derives related emissions pathways for these concentrations. For this to happen, and to enable climate research centres to compare GHG concentrations and emissions estimates, common temperature trajectory scenarios are required. Here we define algebraic curves that asymptote to a stabilised limit, while also matching the magnitude and gradient of recent warming levels. The curves are deliberately parameter-sparse, needing the prescription of just two parameters plus the final temperature. Yet despite this simplicity, they can allow for temperature overshoot and for generational changes, for which more effort to decelerate warming change needs to be made by future generations. The curves capture temperature profiles from the existing Representative Concentration Pathway (RCP2.6) scenario projections by a range of different Earth system models (ESMs), which have warming amounts towards the lower levels of those that society is discussing.

scholarly journals Flexible parameter-sparse global temperature time-profiles that stabilise at 1.5 °C and 2.0 °C

2017 ◽  
Author(s):  
Chris Huntingford ◽  
Hui Yang ◽  
Anna Harper ◽  
Peter M. Cox ◽  
Nic Gedney ◽  
...  
Keyword(s):  
Climate Model ◽  
Algebraic Curves ◽  
Climate Impacts ◽  
Global Temperature ◽  
Temperature Profiles ◽  
Average Temperature ◽  
Generational Changes ◽  
Scenario Model ◽  
Climate Model Simulations ◽  
Two Parameters

Abstract. The UNFCCC Paris climate meeting of December 2015 committed to holding the rise in global average temperature to below 2.0 °C above pre-industrial levels. It also committed to pursue efforts to limit warming to 1.5 °C. This leads to two key questions. First, what extent of reductions in emissions will achieve either target? Second, given emissions cuts to achieve the lower target may be especially difficult to achieve, then what is the benefit from reduced climate impacts by keeping warming at or below 1.5 °C? To provide answers climate model simulations need to follow trajectories consistent with these global temperature limits. This implies operating models in an invertible form, to make model-specific estimates of greenhouse gas (GHG) concentration pathways consistent with prescribed temperature profiles. Further inversion derives related emissions pathways for these concentrations. For this to happen, and to enable climate research centres to compare GHG concentrations and emissions estimates, common temperature trajectory scenarios are required. Here we define algebraic curves which asymptote to a stabilised limit, while also matching the magnitude and gradient of recent warming levels. The curves are deliberately parameter-sparse, needing prescription of just two parameters plus the final temperature. Yet despite this simplicity they can allow for temperature overshoot and for generational changes where more effort occurs to decelerate warming change by future generations. The curves capture temperature profiles from the existing rcp2.6 scenario model projections, which have warming amounts towards the lower levels of those that society is discussing.

scholarly journals Estimating Changes in Global Temperature since the Preindustrial Period

2017 ◽  
Vol 98 (9) ◽  
pp. 1841-1856 ◽  
Author(s):  
Ed Hawkins ◽  
Pablo Ortega ◽  
Emma Suckling ◽  
Andrew Schurer ◽  
Gabi Hegerl ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Temperature ◽  
Radiative Forcings ◽  
Global Average ◽  
Average Temperature ◽  
Climate Model Simulations ◽  
Temperature Levels ◽  
Definition Of

Abstract The United Nations Framework Convention on Climate Change (UNFCCC) process agreed in Paris to limit global surface temperature rise to “well below 2°C above pre-industrial levels.” But what period is preindustrial? Somewhat remarkably, this is not defined within the UNFCCC’s many agreements and protocols. Nor is it defined in the IPCC’s Fifth Assessment Report (AR5) in the evaluation of when particular temperature levels might be reached because no robust definition of the period exists. Here we discuss the important factors to consider when defining a preindustrial period, based on estimates of historical radiative forcings and the availability of climate observations. There is no perfect period, but we suggest that 1720–1800 is the most suitable choice when discussing global temperature limits. We then estimate the change in global average temperature since preindustrial using a range of approaches based on observations, radiative forcings, global climate model simulations, and proxy evidence. Our assessment is that this preindustrial period was likely 0.55°–0.80°C cooler than 1986–2005 and that 2015 was likely the first year in which global average temperature was more than 1°C above preindustrial levels. We provide some recommendations for how this assessment might be improved in the future and suggest that reframing temperature limits with a modern baseline would be inherently less uncertain and more policy relevant.

Assessing Goodness of Fit to a Gamma Distribution and Estimating Future Projection on Daily Precipitation Frequency Using Regional Climate Model Simulations over Japan with and without the Influence of Tropical Cyclones

2020 ◽  
Vol 21 (12) ◽  
pp. 2997-3010
Author(s):  
Akihiko Murata ◽  
Shun-ichi I. Watanabe ◽  
Hidetaka Sasaki ◽  
Hiroaki Kawase ◽  
Masaya Nosaka
Keyword(s):  
Tropical Cyclones ◽  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Climate Model ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Precipitation Data ◽  
Precipitation Frequency ◽  
Climate Model Simulations ◽  
Two Parameters

AbstractGoodness of fit in daily precipitation frequency to a gamma distribution was examined, focusing on adverse effects originating from the shortage of sampled tropical cyclones, using precipitation data with and without the influence of tropical cyclones. The data used in this study were obtained through rain gauge observations and regional climate model simulations under the RCP8.5 scenario and the present climate. An empirical cumulative distribution function (CDF), calculated from a sample of precipitation data for each location, was compared with a theoretical CDF derived from two parameters of a gamma distribution. Using these two CDFs, the root-mean-square error (RMSE) was calculated as an indicator of the goodness of fit. The RMSE exhibited a decreasing tendency when the influence of tropical cyclones was removed. This means that the empirical CDF derived from sampled precipitation more closely resembled the theoretical CDF when compared with the relationship between empirical and theoretical CDFs, including precipitation data associated with tropical cyclones. Future changes in the two parameters of the gamma distribution, without the influence of tropical cyclones, depend on regions in Japan, indicating a regional dependence on changes in the shape and scale of the CDF. The magnitude of increases in no-rain days was also dependent on regions of Japan, although the number of no-rain days increased overall. This simplified approach is useful for analyzing climate change from a broad perspective.

scholarly journals Significant climate benefits from near-term climate forcer mitigation in spite of aerosol reductions

2021 ◽  
Author(s):  
Robert Allen ◽  
Larry Horowitz ◽  
Vaishali Naik ◽  
Naga Oshima ◽  
Fiona O'Connor ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Model ◽  
Climate Impacts ◽  
Ozone Pollution ◽  
Surface Cooling ◽  
Methane Mitigation ◽  
Surface Warming ◽  
Near Term ◽  
Climate Model Simulations ◽  
Reactive Gases

<p>Near-term climate forcers (NTCFs), including aerosols and chemically reactive gases such as tropospheric ozone and methane, offer a potential way to mitigate climate change and improve air quality--so called "win-win" mitigation policies.   Prior studies support improved air quality under NTCF mitigation, but with conflicting climate impacts that range from a significant reduction in the rate of global warming to only a modest impact.  Here, we use state-of-the-art chemistry-climate model simulations conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) to quantify the 21st-century impact of NTCF reductions, using a realistic future emission scenario with a consistent air quality policy.  Non-methane NTCF (NMNTCF; aerosols and ozone precursors) mitigation improves air quality, but leads to significant increases in global mean precipitation of 1.3% by mid-century and 1.4% by end-of-the-century, and corresponding surface warming of 0.23 and 0.21 K.  NTCF (all-NTCF; including methane) mitigation further improves air quality, with larger reductions of up to 45% for ozone pollution, while offsetting half of the wetting by mid-century (0.7% increase) and all the wetting by end-of-the-century (non-significant 0.1% increase) and leading to surface cooling of -0.15 K by mid-century and -0.50 K by end-of-the-century.  This suggests that methane mitigation offsets warming induced from reductions in NMNTCFs, while also leading to net improvements in air quality.</p>

scholarly journals Large variations in volcanic aerosol forcing efficiency due to eruption source parameters and rapid adjustments

2020 ◽  
Author(s):  
Lauren Marshall ◽  
Christopher Smith ◽  
Piers Forster ◽  
Thomas Aubry ◽  
Anja Schmidt
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Source Parameters ◽  
Volcanic Eruptions ◽  
Stratospheric Aerosol ◽  
Climate Impacts ◽  
Intergovernmental Panel ◽  
Aerosol Forcing ◽  
Effective Radiative Forcing ◽  
Climate Model Simulations

<p>The relationship between volcanic stratospheric aerosol optical depth (SAOD) and volcanic forcing is key to quantify the climate impacts of volcanic eruptions. In their fifth assessment report, the Intergovernmental Panel on Climate Change uses a single scaling factor between volcanic SAOD and effective radiative forcing (ERF) based on climate model simulations of the 1991 Mt. Pinatubo eruption, which may not be appropriate for eruptions of different magnitudes. Using a large-ensemble of aerosol-chemistry-climate simulations of eruptions with different SO<sub>2</sub> emissions, latitudes, emission altitudes and seasons, we find that the effective radiative forcing is on average 21% less than the instantaneous radiative forcing, predominantly due to a positive shortwave cloud adjustment.  In our model, the volcanic SAOD to ERF relationship is non-unique and depends strongly on eruption latitude and season. We recommend a power law fit in the form of ERF = -15.1 × SAOD<sup>0.88</sup> to convert SAOD (in the range of 0.01-0.7) to ERF.</p>

scholarly journals Simulating the Climate Response to Atmospheric Oxygen Variability in the Phanerozoic

2018 ◽  
Author(s):  
David C. Wade ◽  
Nathan Luke Abraham ◽  
Alexander Farnsworth ◽  
Paul J. Valdes ◽  
Fran Bragg ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Oxygen Content ◽  
Climate Model ◽  
Atmospheric Oxygen ◽  
Climate Impacts ◽  
Climate Response ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Proxy Reconstructions ◽  
Global Mean

Abstract. The amount of dioxygen (O2) in the atmosphere may have varied from as little as 10 % to as high as 35 % during the Phanerozoic eon (541 Ma–Present). These changes in the amount of O2 are large enough to have lead to changes in atmospheric mass, which may alter the radiative budget of the atmosphere, leading to this mechanism being invoked to explain discrepancies between climate model simulations and proxy reconstructions of past climates. Here we present the first fully 3D numerical model simulations to investigate the climate impacts of changes in O2 during different climate states using the HadGEM3-AO and HadCM3-BL models. We show that simulations with an increase in O2 content result in increased global mean surface air temperature under conditions of a pre-industrial Holocene climate state, in agreement with idealised 1D and 2D modelling studies. We demonstrate the mechanism behind the warming is complex and involves trade-off between a number of factors. Increasing atmospheric O2 leads to a reduction in incident shortwave radiation at Earth's surface due to Rayleigh scattering, a cooling effect. However, there is a competing warming effect due to an increase in the pressure broadening of greenhouse gas absorption lines and dynamical feedbacks, which alter the meridional heat transport of the ocean, warming polar regions and cooling tropical regions. Case studies from past climates are investigated using HadCM3-BL which show that in the warmest climate states, increasing oxygen may lead to a temperature decrease, as the equilibrium climate sensitivity is lower. For the Maastrichtian (72.1–66.0 Ma), increasing oxygen content leads to a better agreement with proxy reconstructions of surface temperature at that time irrespective of the carbon dioxide content. For the Asselian (298.9–295.0 Ma), increasing oxygen content leads to a warmer global mean surface temperature and reduced carbon storage on land, suggesting that high oxygen content may have been a contributing factor in preventing a Snowball Earth during this period of the early Permian. These climate model simulations reconcile the surface temperature response to oxygen content changes across the hierarchy of model complexity and highlight the broad range of Earth system feedbacks that need to be accounted for when considering the climate response to changes in atmospheric oxygen content.

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