Radiative Forcing Time Series Research Articles

Influence of Weather and Climate on Multidecadal Trends in Atlantic Hurricane Genesis and Tracks

Abstract This study investigates the relative roles of sea surface temperature–forced climate changes and weather variability in driving the observed eastward shift of Atlantic hurricane tracks over the period from 1970 to 2021. A 10-member initial condition ensemble with a ∼25-km horizontal resolution tropical cyclone permitting atmospheric model (GFDL AM2.5-C360) with identical sea surface temperature and radiative forcing time series was analyzed in conjunction with historical hurricane track observations. While a frequency increase was recovered by all the simulations, the observed multidecadal eastward shift in tracks was not robust across the ensemble members, indicating that it included a substantial contribution from weather-scale variability. A statistical model was developed to simulate expected storm tracks based on genesis location and steering flow, and it was used to conduct experiments testing the roles of changing genesis location and changing steering flow in producing the multidecadal weather-driven shifts in storm tracks. These experiments indicated that shifts in genesis location were a substantially larger driver of these multidecadal track changes than changes in steering flow. The substantial impact of weather on tracks indicates that there may be limited predictability for multidecadal track changes like those observed, although basinwide frequency has greater potential for prediction. Additionally, understanding changes in genesis location appears essential to understanding changes in track location. Significance Statement From the 1970s to the present, there has been an increase in the frequency of North Atlantic hurricanes, but they have also shifted in location to the east, away from land. We explore whether this shift in hurricanes’ locations was caused by climatic factors or randomness to understand if and how these trends will persist. We also consider whether the shift was due to a change in where hurricanes started or how they moved over their lifespan. Analyzing data from observed and simulated hurricanes, we find that the shift was made more likely by climate factors, but ultimately occurred due to random variability in the hurricanes’ starting locations. These results suggest a higher uncertainty in the future location and impact of hurricanes and highlight the importance of studying why hurricanes originate where they do.

Historical total ozone radiative forcing derived from CMIP6 simulations

Radiative forcing (RF) time series for total ozone from 1850 up to the present day are calculated based on historical simulations of ozone from 10 climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, RF is calculated for ozone fields prepared as an input for CMIP6 models without chemistry schemes and from a chemical transport model simulation. A radiative kernel for ozone is constructed and used to derive the RF. The ozone RF in 2010 (2005–2014) relative to 1850 is 0.35 W m−2 [0.08–0.61] (5–95% uncertainty range) based on models with both tropospheric and stratospheric chemistry. One of these models has a negative present-day total ozone RF. Excluding this model, the present-day ozone RF increases to 0.39 W m−2 [0.27–0.51] (5–95% uncertainty range). The rest of the models have RF close to or stronger than the RF time series assessed by the Intergovernmental Panel on Climate Change in the fifth assessment report with the primary driver likely being the new precursor emissions used in CMIP6. The rapid adjustments beyond stratospheric temperature are estimated to be weak and thus the RF is a good measure of effective radiative forcing.

Decadal Attribution of Historic Temperature and Ocean Heat Content Change to Anthropogenic Emissions

AbstractWe present an alternative method of calculating the historical effective radiative forcing using the observed temperature record and a kernel based on the 5th Climate Model Intercomparison Project (CMIP5) temperature response. This estimate is the effective radiative forcing time series that the average climate model would need to simulate the observed global mean surface temperature anomalies. We further infer the anthropogenic aerosols radiative forcing as a residual using the better‐known greenhouse gas radiative forcing. This allows an independent estimate of anthropogenic aerosol radiative forcing, which suggests a cooling influence due to aerosols in the early part of the twentieth century. The temporal kernels are also used to calculate decadal contributions from the dominant forcing agents to present‐day temperature, ocean heat content, and thermosteric sea level rise. The current global mean temperature anomaly is dominated by emissions in the past two decades, while current ocean heat content is more strongly affected by earlier decades.

Climate sensitivity estimates – sensitivity to radiative forcing time series and observational data

Abstract. Inferred effective climate sensitivity (ECSinf) is estimated using a method combining radiative forcing (RF) time series and several series of observed ocean heat content (OHC) and near-surface temperature change in a Bayesian framework using a simple energy balance model and a stochastic model. The model is updated compared to our previous analysis by using recent forcing estimates from IPCC, including OHC data for the deep ocean, and extending the time series to 2014. In our main analysis, the mean value of the estimated ECSinf is 2.0 ∘C, with a median value of 1.9 ∘C and a 90 % credible interval (CI) of 1.2–3.1 ∘C. The mean estimate has recently been shown to be consistent with the higher values for the equilibrium climate sensitivity estimated by climate models. The transient climate response (TCR) is estimated to have a mean value of 1.4 ∘C (90 % CI 0.9–2.0 ∘C), and in our main analysis the posterior aerosol effective radiative forcing is similar to the range provided by the IPCC. We show a strong sensitivity of the estimated ECSinf to the choice of a priori RF time series, excluding pre-1950 data and the treatment of OHC data. Sensitivity analysis performed by merging the upper (0–700 m) and the deep-ocean OHC or using only one OHC dataset (instead of four in the main analysis) both give an enhancement of the mean ECSinf by about 50 % from our best estimate.

A lower and more constrained estimate of climate sensitivity using updated observations and detailed radiative forcing time series

Abstract. Equilibrium climate sensitivity (ECS) is constrained based on observed near-surface temperature change, changes in ocean heat content (OHC) and detailed radiative forcing (RF) time series from pre-industrial times to 2010 for all main anthropogenic and natural forcing mechanism. The RF time series are linked to the observations of OHC and temperature change through an energy balance model (EBM) and a stochastic model, using a Bayesian approach to estimate the ECS and other unknown parameters from the data. For the net anthropogenic RF the posterior mean in 2010 is 2.0 Wm−2, with a 90% credible interval (C.I.) of 1.3 to 2.8 Wm−2, excluding present-day total aerosol effects (direct + indirect) stronger than −1.7 Wm−2. The posterior mean of the ECS is 1.8 °C, with 90% C.I. ranging from 0.9 to 3.2 °C, which is tighter than most previously published estimates. We find that using three OHC data sets simultaneously and data for global mean temperature and OHC up to 2010 substantially narrows the range in ECS compared to using less updated data and only one OHC data set. Using only one OHC set and data up to 2000 can produce comparable results as previously published estimates using observations in the 20th century, including the heavy tail in the probability function. The analyses show a significant contribution of internal variability on a multi-decadal scale to the global mean temperature change. If we do not explicitly account for long-term internal variability, the 90% C.I. is 40% narrower than in the main analysis and the mean ECS becomes slightly lower, which demonstrates that the uncertainty in ECS may be severely underestimated if the method is too simple. In addition to the uncertainties represented through the estimated probability density functions, there may be uncertainties due to limitations in the treatment of the temporal development in RF and structural uncertainties in the EBM.

Radiative forcing and climate impact resulting from SO2 injections based on a 200,000-year record of Plinian eruptions along the Central American Volcanic Arc

We present for the first time a self-consistent methodology connecting volcanological field data to global climate model estimates for a regional time series of explosive volcanic events. Using the petrologic method, we estimated SO2 emissions from 36 detected Plinian volcanic eruptions occurring at the Central American Volcanic Arc (CAVA) during the past 200,000 years. Together with simple parametrized relationships collected from past studies, we derive estimates of global maximum volcanic aerosol optical depth (AOD) and radiative forcing (RF) describing the effect of each eruption on radiation reaching the Earth’s surface. In parallel, AOD and RF time series for selected CAVA eruptions are simulated with the global aerosol model MAECHAM5-HAM, which shows a relationship between stratospheric SO2 injection and maximum global mean AOD that is linear for smaller volcanic eruptions (<5 Mt SO2) and nonlinear for larger ones (≥5 Mt SO2) and is qualitatively and quantitatively consistent with the relationship used in the simple parametrized approximation. Potential climate impacts of the selected CAVA eruptions are estimated using an earth system model of intermediate complexity by RF time series derived by (1) directly from the global aerosol model and (2) from the simple parametrized approximation assuming a 12-month exponential decay of global AOD. We find that while the maximum AOD and RF values are consistent between the two methods, their temporal evolutions are significantly different. As a result, simulated global maximum temperature anomalies and the duration of the temperature response depend on which RF time series is used, varying between 2 and 3 K and 60 and 90 years for the largest eruption of the CAVA dataset. Comparing the recurrence time of eruptions, based on the CAVA dataset, with the duration of climate impacts, based on the model results, we conclude that cumulative impacts due to successive eruptions are unlikely. The methodology and results presented here can be used to calculate approximate volcanic forcings and potential climate impacts from sulfur emissions, sulfate aerosol or AOD data for any eruption that injects sulfur into the tropical stratosphere.

Anthropogenic radiative forcing time series from pre-industrial times until 2010

Abstract. In order to use knowledge of past climate change to improve our understanding of the sensitivity of the climate system, detailed knowledge about the time development of radiative forcing (RF) of the earth atmosphere system is crucial. In this study, time series of anthropogenic forcing of climate from pre-industrial times until 2010, for all well established forcing agents, are estimated. This includes presentation of RF histories of well mixed greenhouse gases, tropospheric ozone, direct- and indirect aerosol effects, surface albedo changes, stratospheric ozone and stratospheric water vapour. For long lived greenhouse gases, standard methods are used for calculating RF, based on global mean concentration changes. For short lived climate forcers, detailed chemical transport modelling and radiative transfer modelling using historical emission inventories is performed. For the direct aerosol effect, sulphate, black carbon, organic carbon, nitrate and secondary organic aerosols are considered. For aerosol indirect effects, time series of both the cloud lifetime effect and the cloud albedo effect are presented. Radiative forcing time series due to surface albedo changes are calculated based on prescribed changes in land use and radiative transfer modelling. For the stratospheric components, simple scaling methods are used. Long lived greenhouse gases (LLGHGs) are the most important radiative forcing agent with a RF of 2.83±0.28 W m−2 in year 2010 relative to 1750. The two main aerosol components contributing to the direct aerosol effect are black carbon and sulphate, but their contributions are of opposite sign. The total direct aerosol effect was −0.48±0.32 W m−2 in year 2010. Since pre-industrial times the positive RF (LLGHGs and tropospheric O3) has been offset mainly by the direct and indirect aerosol effects, especially in the second half of the 20th century, which possibly lead to a decrease in the total anthropogenic RF in the middle of the century. We find a total anthropogenic RF in year 2010 of 1.4 W m−2. However, the uncertainties in the negative RF from aerosols are large, especially for the cloud lifetime effect.

Black carbon in the atmosphere and snow, from pre-industrial times until present

Abstract. The distribution of black carbon (BC) in the atmosphere and the deposition of BC on snow surfaces since pre-industrial time until present are modelled with the Oslo CTM2 model. The model results are compared with observations including recent measurements of BC in snow in the Arctic. The global mean burden of BC from fossil fuel and biofuel sources increased during two periods. The first period, until 1920, is related to increases in emissions in North America and Europe, and the last period after 1970 are related mainly to increasing emissions in East Asia. Although the global burden of BC from fossil fuel and biofuel increases, in the Arctic the maximum atmospheric BC burden as well as in the snow was reached in 1960s, with a slight reduction thereafter. The global mean burden of BC from open biomass burning sources has not changed significantly since 1900. With current inventories of emissions from open biomass sources, the modelled burden of BC in snow and in the atmosphere north of 65° N is small compared to the BC burden of fossil fuel and biofuel origin. From the concentration changes radiative forcing time series due to the direct aerosol effect as well as the snow-albedo effect is calculated for BC from fossil fuel and biofuel. The calculated radiative forcing in 2000 for the direct aerosol effect is 0.35 W m−2 and for the snow-albedo effect 0.016 W m−2 in this study. Due to a southward shift in the emissions there is an increase in the lifetime of BC as well as an increase in normalized radiative forcing, giving a change in forcing per unit of emissions of 26 % since 1950.

The Climate Sensitivity and Its Components Diagnosed from Earth Radiation Budget Data

Abstract One of the major uncertainties in the ability to predict future climate change, and hence its impacts, is the lack of knowledge of the earth’s climate sensitivity. Here, data are combined from the 1985–96 Earth Radiation Budget Experiment (ERBE) with surface temperature change information and estimates of radiative forcing to diagnose the climate sensitivity. Importantly, the estimate is completely independent of climate model results. A climate feedback parameter of 2.3 ± 1.4 W m−2 K−1 is found. This corresponds to a 1.0–4.1-K range for the equilibrium warming due to a doubling of carbon dioxide (assuming Gaussian errors in observable parameters, which is approximately equivalent to a uniform “prior” in feedback parameter). The uncertainty range is due to a combination of the short time period for the analysis as well as uncertainties in the surface temperature time series and radiative forcing time series, mostly the former. Radiative forcings may not all be fully accounted for; however, an argument is presented that the estimate of climate sensitivity is still likely to be representative of longer-term climate change. The methodology can be used to 1) retrieve shortwave and longwave components of climate feedback and 2) suggest clear-sky and cloud feedback terms. There is preliminary evidence of a neutral or even negative longwave feedback in the observations, suggesting that current climate models may not be representing some processes correctly if they give a net positive longwave feedback.