scholarly journals Understanding the Intermodel Spread in Global-Mean Hydrological Sensitivity*

2016 ◽  
Vol 29 (2) ◽  
pp. 801-817 ◽  
Author(s):  
Dagmar Fläschner ◽  
Thorsten Mauritsen ◽  
Bjorn Stevens

Abstract This paper assesses intermodel spread in the slope of global-mean precipitation change ΔP with respect to surface temperature change. The ambiguous estimates in the literature for this slope are reconciled by analyzing four experiments from phase 5 of CMIP (CMIP5) and considering different definitions of the slope. The smallest intermodel spread (a factor of 1.5 between the highest and lowest estimate) is found when using a definition that disentangles temperature-independent precipitation changes (the adjustments) from the slope of the temperature-dependent precipitation response; here this slope is referred to as the hydrological sensitivity parameter η. The estimates herein show that η is more robust than stated in most previous work. The authors demonstrate that adjustments and η estimated from a steplike quadrupling CO2 experiment serve well to predict ΔP in a transient CO2 experiment. The magnitude of η is smaller in the coupled ocean–atmosphere quadrupling CO2 experiment than in the noncoupled atmosphere-only experiment. The offset in magnitude due to coupling suggests that intermodel spread may undersample uncertainty. Also assessed are the relative contribution of η, the surface warming, and the adjustment on the spread in ΔP on different time scales. Intermodel variation of both η and the adjustment govern the spread in ΔP in the years immediately after the abrupt forcing change. In equilibrium, the uncertainty in ΔP is dominated by uncertainty in the equilibrium surface temperature response. A kernel analysis reveals that intermodel spread in η is dominated by intermodel spread in tropical lower tropospheric temperature and humidity changes and cloud changes.

2012 ◽  
Vol 12 (1) ◽  
pp. 2853-2861 ◽  
Author(s):  
M. Previdi ◽  
L. M. Polvani

Abstract. Stratospheric ozone recovery is expected to figure prominently in twenty-first century climate change. In a recent paper, Hu et al. (2011) argue that one impact of ozone recovery will be to enhance the warming of the surface-troposphere system produced by increases in well-mixed greenhouse gases; furthermore, this enhanced warming would be strongest in the Northern Hemisphere, which is surprising since previous studies have consistently shown the effects of stratospheric ozone changes to be most pronounced in the Southern Hemisphere. Hu et al. (2011) base their claims largely on differences in the simulated temperature change between two groups of IPCC climate models, one group which included stratospheric ozone recovery in its twenty-first century simulations and a second group which did not. Both groups of models were forced with the same increases in well-mixed greenhouse gases according to the A1B emissions scenario. In the current work, we compare the surface temperature responses of the same two groups of models in a different experiment in which atmospheric CO2 was increased by 1% per year until doubling. We find remarkably similar differences in the simulated surface temperature change between the two sets of models as Hu et al. (2011) found for the A1B experiment, suggesting that the enhanced warming which they attribute to stratospheric ozone recovery is actually a reflection of different responses of the two model groups to greenhouse gas forcing.


2015 ◽  
Vol 28 (4) ◽  
pp. 1630-1648 ◽  
Author(s):  
Timothy Andrews ◽  
Jonathan M. Gregory ◽  
Mark J. Webb

Abstract Experiments with CO2 instantaneously quadrupled and then held constant are used to show that the relationship between the global-mean net heat input to the climate system and the global-mean surface air temperature change is nonlinear in phase 5 of the Coupled Model Intercomparison Project (CMIP5) atmosphere–ocean general circulation models (AOGCMs). The nonlinearity is shown to arise from a change in strength of climate feedbacks driven by an evolving pattern of surface warming. In 23 out of the 27 AOGCMs examined, the climate feedback parameter becomes significantly (95% confidence) less negative (i.e., the effective climate sensitivity increases) as time passes. Cloud feedback parameters show the largest changes. In the AOGCM mean, approximately 60% of the change in feedback parameter comes from the tropics (30°N–30°S). An important region involved is the tropical Pacific, where the surface warming intensifies in the east after a few decades. The dependence of climate feedbacks on an evolving pattern of surface warming is confirmed using the HadGEM2 and HadCM3 atmosphere GCMs (AGCMs). With monthly evolving sea surface temperatures and sea ice prescribed from its AOGCM counterpart, each AGCM reproduces the time-varying feedbacks, but when a fixed pattern of warming is prescribed the radiative response is linear with global temperature change or nearly so. It is also demonstrated that the regression and fixed-SST methods for evaluating effective radiative forcing are in principle different, because rapid SST adjustment when CO2 is changed can produce a pattern of surface temperature change with zero global mean but nonzero change in net radiation at the top of the atmosphere (~−0.5 W m−2 in HadCM3).


2017 ◽  
Vol 30 (7) ◽  
pp. 2679-2695 ◽  
Author(s):  
Chuan-Yang Wang ◽  
Shang-Ping Xie ◽  
Yu Kosaka ◽  
Qinyu Liu ◽  
Xiao-Tong Zheng

The impact of internal tropical Pacific variability on global mean surface temperature (GMST) is quantified using a multimodel ensemble. A tropical Pacific index (TPI) is defined to track tropical Pacific sea surface temperature (SST) variability. The simulated GMST is highly correlated with TPI on the interannual time scale but this correlation weakens on the decadal time scale. The time-scale dependency is such that the GMST regression equation derived from the observations, which are dominated by interannual variability, would underestimate the magnitude of decadal GMST response to tropical Pacific variability. The surface air temperature response to tropical Pacific variability is strong in the tropics but weakens in the extratropics. The regression coefficient of GMST against TPI shows considerable intermodel variations, primarily because of differences in high latitudes. The results have important implications for the planned intercomparison of pacemaker experiments that force Pacific variability to follow the observed evolution. The model dependency of the GMST regression suggests that in pacemaker experiments—model performance in simulating the recent “slowdown” in global warming—will vary substantially among models. It also highlights the need to develop observational constraints and to quantify the TPI effect on the decadal variability of GMST. Compared to GMST, the correlation between global mean tropospheric temperature and TPI is high on both interannual and decadal time scales because of a common structure in the tropical tropospheric temperature response that is upward amplified and meridionally broad.


2012 ◽  
Vol 12 (11) ◽  
pp. 4893-4896 ◽  
Author(s):  
M. Previdi ◽  
L. M. Polvani

Abstract. Stratospheric ozone recovery is expected to figure prominently in twenty-first century climate change. In a recent paper, Hu et al. (2011) argue that one impact of ozone recovery will be to enhance the warming of the surface-troposphere system produced by increases in well-mixed greenhouse gases. Furthermore, this enhanced warming would be strongest in the Northern Hemisphere, which is surprising since previous studies have consistently shown the effects of stratospheric ozone changes to be most pronounced in the Southern Hemisphere. Hu et al. (2011) base their claims largely on differences in the simulated temperature change between two groups of CMIP3 (Coupled Model Intercomparison Project 3) climate models, one group which included stratospheric ozone recovery in its twenty-first century simulations and a second group which did not. Both groups of models were forced with the same increases in well-mixed greenhouse gases according to the A1B emissions scenario. In the current work, we compare the surface temperature responses of the same two groups of models in a different experiment in which atmospheric CO2 was increased by 1% per year until doubling. We find remarkably similar differences in the simulated surface temperature change between the two sets of models as Hu et al. (2011) found for the A1B experiment, suggesting that the enhanced warming which they attribute to stratospheric ozone recovery is actually a reflection of different responses of the two model groups to greenhouse gas forcing.


2013 ◽  
Vol 26 (22) ◽  
pp. 8781-8786 ◽  
Author(s):  
Larissa Back ◽  
Karen Russ ◽  
Zhengyu Liu ◽  
Kuniaki Inoue ◽  
Jiaxu Zhang ◽  
...  

Abstract This study analyzes the response of global water vapor to global warming in a series of fully coupled climate model simulations. The authors find that a roughly 7% K−1 rate of increase of water vapor with global surface temperature is robust only for rapid anthropogenic-like climate change. For slower warming that occurred naturally in the past, the Southern Ocean has time to equilibrate, producing a different pattern of surface warming, so that water vapor increases at only 4.2% K−1. This lower rate of increase of water vapor with warming is not due to relative humidity changes or differences in mean lower-tropospheric temperature. A temperature of over 80°C would be required in the Clausius–Clapeyron relationship to match the 4.2% K−1 rate of increase. Instead, the low rate of increase is due to spatially heterogeneous warming. During slower global warming, there is enhanced warming at southern high latitudes, and hence less warming in the tropics per kelvin of global surface temperature increase. This leads to a smaller global water vapor increase, because most of the atmospheric water vapor is in the tropics. A formula is proposed that applies to general warming scenarios. This study also examines the response of global-mean precipitation and the meridional profile of precipitation minus evaporation and compares the latter to thermodynamic scalings. It is found that global-mean precipitation changes are remarkably robust between rapid and slow warming. Thermodynamic scalings for the rapid- and slow-warming zonal-mean precipitation are similar, but the precipitation changes are significantly different, suggesting that circulation changes are important in driving these differences.


2019 ◽  
Vol 46 (4) ◽  
pp. 2232-2241 ◽  
Author(s):  
Jules B. Kajtar ◽  
Matthew Collins ◽  
Leela M. Frankcombe ◽  
Matthew H. England ◽  
Timothy J. Osborn ◽  
...  

2018 ◽  
Vol 31 (23) ◽  
pp. 9641-9657 ◽  
Author(s):  
T. B. Richardson ◽  
P. M. Forster ◽  
T. Andrews ◽  
O. Boucher ◽  
G. Faluvegi ◽  
...  

The response of the hydrological cycle to climate forcings can be understood within the atmospheric energy budget framework. In this study precipitation and energy budget responses to five forcing agents are analyzed using 10 climate models from the Precipitation Driver Response Model Intercomparison Project (PDRMIP). Precipitation changes are split into a forcing-dependent fast response and a temperature-driven hydrological sensitivity. Globally, when normalized by top-of-atmosphere (TOA) forcing, fast precipitation changes are most sensitive to strongly absorbing drivers (CO2, black carbon). However, over land fast precipitation changes are most sensitive to weakly absorbing drivers (sulfate, solar) and are linked to rapid circulation changes. Despite this, land-mean fast responses to CO2 and black carbon exhibit more intermodel spread. Globally, the hydrological sensitivity is consistent across forcings, mainly associated with increased longwave cooling, which is highly correlated with intermodel spread. The land-mean hydrological sensitivity is weaker, consistent with limited moisture availability. The PDRMIP results are used to construct a simple model for land-mean and sea-mean precipitation change based on sea surface temperature change and TOA forcing. The model matches well with CMIP5 ensemble mean historical and future projections, and is used to understand the contributions of different drivers. During the twentieth century, temperature-driven intensification of land-mean precipitation has been masked by fast precipitation responses to anthropogenic sulfate and volcanic forcing, consistent with the small observed trend. However, as projected sulfate forcing decreases, and warming continues, land-mean precipitation is expected to increase more rapidly, and may become clearly observable by the mid-twenty-first century.


2016 ◽  
Vol 73 (8) ◽  
pp. 3287-3303 ◽  
Author(s):  
Sergio A. Sejas ◽  
Ming Cai

Abstract Climate feedback processes are known to substantially amplify the surface warming response to an increase of greenhouse gases. When the forcing and feedbacks modify the temperature response they trigger temperature feedback loops that amplify the direct temperature changes due to the forcing and nontemperature feedbacks through the thermal–radiative coupling between the atmosphere and surface. This study introduces a new feedback-response analysis method that can isolate and quantify the effects of the temperature feedback loops of individual processes on surface temperature from their corresponding direct surface temperature responses. The authors analyze a 1% yr−1 increase of CO2 simulation of the NCAR CCSM4 at the time of CO2 doubling to illustrate the new method. The Planck sensitivity parameter, which indicates colder regions experience stronger surface temperature responses given the same change in surface energy flux, is the inherent factor that leads to polar warming amplification (PWA). This effect explains the PWA in the Antarctic, while the direct temperature response to the albedo and cloud feedbacks further explains the greater PWA of the Arctic. Temperature feedback loops, particularly the one associated with the albedo feedback, further amplify the Arctic surface warming relative to the tropics. In the tropics, temperature feedback loops associated with the CO2 forcing and water vapor feedback cause most of the surface warming. Overall, the temperature feedback is responsible for most of the surface warming globally, accounting for nearly 76% of the global-mean surface warming. This is 3 times larger than the next largest warming contribution, indicating that the temperature feedback loop is the preeminent contributor to the surface warming.


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