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Geographical contributions to global climate sensitivity in a General Circulation Model
Abstract
This paper addresses two questions: how do radiative contributions to global climate model feedbacks vary geographically, and hence which regions and physical processes are most important in determining final climate sensitivity in a General Circulation Model (GCM)? Offline radiation calculations were used to evaluate in detail the strength and spatial distribution of top of atmosphere (TOA) radiative perturbations for the BMRC GCM under a doubling of CO2. The long wave and short wave radiative perturbations were considered separately. The net global effect of these radiative perturbations determines the strength of the global model feedbacks, and hence the climate sensitivity. The geographical distribution of the radiative perturbations on the other hand helps to identify the model processes that are most important for determining the strength of model feedbacks. This study found that globally, the dominant positive feedbacks were for (a) water vapour amount and height, and cloud height for long wave radiation and (b) albedo and cloud amount for short wave radiation. The dominant negative feedback (apart from the surface temperature term itself) occurred for cloud amount changes in the long wave. Geographically, the contributions to the water vapour feedback strength varied markedly by location, with subtropical, and upper tropospheric regions contributing relatively strongly to the net global feedback. The water vapour height component correlated quite strongly with convective changes while the amount term was correlated with fractional precipitable water changes. The contribution of different precipitable water regimes in the tropics to global water vapour feedback was assessed—relatively dry areas contributed disproportionately, but did not dominate the overall feedback because of their small areas. Contributions to cloud amount and height feedbacks in the long wave were found to be uncorrelated in space, indicating their different controlling processes. The long wave amount component correlated strongly with upper cloud, and convective changes. The short wave component of the cloud feedback depended on cloud changes at all levels, producing its strongest contribution to feedbacks in mid latitudes, where the sign of cloud changes agreed at different heights. The effect of cloud cover on non-cloud feedbacks was also investigated. This study found that clouds weaken all feedbacks, except that of lapse rate, with the greatest impact being on the surface albedo and water vapour amount. The radiative perturbation analysis method presented here proves to be a powerful tool for identifying important physical processes that determine final climate model sensitivity.
... 1.1.1, but some also calculate the changes in TOA radiative flux due to the radiative forcing and feedbacks (e.g., Colman 2002Colman , 2003Taylor et al. 2011a,b). The conventional TOA feedback analysis implicitly assumes that an increase (decrease) of OLR or upward SW radiation at the TOA, due to a forcing or feedback, will be balanced by a decrease (increase) in OLR caused by a decrease (increase) of surface temperature. ...
... Positive values indicate an increase in energy flux convergence into the climate system, while negative values mean more energy is escaping to space (i.e., greater energy flux divergence). The CO 2 forcing ( Fig. 7.1a) at the TOA demonstrates a net increase in radiative energy flux convergence with a larger magnitude in the tropics and maximum in the subtropics that decreases towards the poles, similar to the results of previous studies (e.g., Colman 2002;Taylor et al. 2011a). This implies a warming of the surface, since the increase in net radiative flux into the climate system will be balanced by an increase in OLR due to the surface warming. ...
... Hansen et al. 1997 justifies this adjustment by stating "the adjusted forcing should be a better measure of the expected climate response for forcings which are present at least several months," since the relaxation time of the stratosphere to near equilibrium should only be several months compared to the much longer time-scale of the troposphere. Since the stratosphere cools, the adjustment increases the CO 2 forcing at the TOA but has little effect on the meridional pattern, partially explaining the smaller magnitude of the forcing at the TOA compared to studies using the adjusted forcing (e.g., Hansen et al. 1997;Colman 2002). ...
Climate feedback mechanisms are known to substantially affect the surface temperature response to an external forcing. This study aims to advance our physical and quantitative understanding of forcing and feedback contributions to the surface temperature response to an external forcing. The dissertation begins with a comprehensive overview of the climate feedback concept and the frameworks used to interpret the effects of forcing and feedbacks on surface temperature. The climate feedback-response analysis method (CFRAM), a relatively new climate feedback framework whose advantages over the traditional climate feedback analysis framework are delineated, is then used to study the seasonal surface temperature response to a doubling of CO2 in a global warming simulation of the NCAR CCSM4. This allows us for the first time to explain the major features of the seasonal warming structure quantitatively. Polar regions, for example, experience the largest warming and the greatest seasonal variation, with maximum warming in fall/winter and minimum warming in summer. In summer, the large cancelations between the shortwave and longwave cloud feedbacks and between the surface albedo feedback warming and the cooling from the ocean heat storage/dynamics feedback lead to a warming minimum. In polar winter, surface albedo and shortwave cloud feedbacks are nearly absent due to a lack of insolation. However, the ocean heat storage feedback relays the polar warming due to the surface albedo feedback from summer to winter, and the longwave cloud feedback warms the polar surface. Therefore, the seasonal variations in the cloud feedback, surface albedo feedback, and ocean heat storage/dynamics feedback, directly caused by the strong annual cycle of insolation, contribute primarily to the large seasonal variation of polar warming. Furthermore, the CO2 forcing, and water vapor and atmospheric dynamics feedbacks add to the maximum polar warming in fall/winter.
The CFRAM allows for a process-based decomposition of the temperature response into individual contributions by the forcing and non-temperature feedbacks, which implicitly include the thermal-radiative coupling (i.e., temperature feedback) effects between the surface and atmosphere. To uncover this hidden effect in the CFRAM, this study develops and introduces a method known as the surface feedback-response analysis method (SFRAM) to isolate the temperature feedback effects on surface temperature, allowing for a physical and quantitative understanding of the temperature feedback effects. The temperature feedback effect is found to be the most important contributor to the surface temperature change, accounting for nearly 76% of the global mean surface warming. From the CFRAM perspective, the temperature feedback effect is just the indirect effects of the forcing and non-temperature feedbacks. The SFRAM analysis, in conjunction with the CFRAM results, indicates that in general the indirect effects of the forcing and non-temperature feedbacks on the surface temperature change are larger than the direct effects; thus demonstrating the influence and strength of the temperature feedback effect in the CFRAM results. By isolating the temperature feedback loop, an understanding of why the indirect effects are generally larger than direct effects is achieved. The SFRAM also serves as a bridge to the traditional TOA feedback analysis. A comparison of the SFRAM results with those of the traditional TOA feedback analysis indicates the largest disparity in interpretation is given for the lapse-rate feedback, which is shown to just stem from a misinterpretation of the temperature feedback effects on surface temperature. A better and more intuitive explanation is achieved through the surface perspective of the SFRAM than the TOA perspective of the traditional feedback analysis. A reconciliation of the surface and TOA perspectives is achieved once the temperature feedback effects are included with the effects of the forcing and non-temperature feedbacks, as in the CFRAM analysis.
... A large intermodel spread in climate sensitivity exists among state-of-the-art general circulation models (GCMs) (Solomon et al. 2007). A number of model intercomparison studies have shown this spread to be a result of different model feedback strengths (Colman 2003a;Soden and Held 2006;Soden et al. 2008). Recent studies (Gregory and Webb 2008;Andrews and Forster 2008) have also suggested that a portion of the intermodel spread is due to ''fast feedbacks,'' which are changes in atmospheric variables that respond directly to the forcing and not global mean surface temperature change. ...
... Feedback strengths are typically characterized in terms of top-of-atmosphere (TOA) global, annual mean radiative perturbations normalized by the global mean surface temperature response assuming a quasi equilibrium (e.g., Wetherald and Manabe 1988). However, as shown by Colman (2002), Boer and Yu (2003), Winton (2006), Soden et al. (2008), and Taylor et al. (2011), geographical distributions of feedback strengths have a rich spatially varying structure. Further investigation of the feedback geographical structure was performed by Taylor et al. (2011) and Colman (2002), who investigated possible links between feedbacks and model physical processes, for example, between convection precipitation response and cloud feedbacks. ...
... However, as shown by Colman (2002), Boer and Yu (2003), Winton (2006), Soden et al. (2008), and Taylor et al. (2011), geographical distributions of feedback strengths have a rich spatially varying structure. Further investigation of the feedback geographical structure was performed by Taylor et al. (2011) and Colman (2002), who investigated possible links between feedbacks and model physical processes, for example, between convection precipitation response and cloud feedbacks. Such analyses suggest strong relationships between spatial feedback variations and the model convective and boundary layer height responses; however, causality has not been shown. ...
This study investigates the annual cycle of radiative contributions to global climate feedbacks. A partial radiative perturbation (PRP) technique is used to diagnose monthly radiative perturbations at the top of atmosphere (TOA) due to CO 2 forcing; surface temperature response; and water vapor, cloud, lapse rate, and surface albedo feedbacks using NCAR Community Climate System Model, version 3 (CCSM3) output from a Special Report on Emissions Scenarios (SRES) A1B emissions-scenario-forced climate simulation. The seasonal global mean longwave TOA radiative feedback was found to be minimal. However, the global mean shortwave (SW) TOA cloud and surface albedo radiative perturbations exhibit large seasonality. The largest contributions to the negative SW cloud feedback occur during summer in each hemisphere, marking the largest differences with previous results. Results suggest that intermodel spread in climate sensitivity may occur, partially from cloud and surface albedo feedback seasonality differences. Further, links between the climate feedback and surface temperature response seasonality are investigated, showing a strong relationship between the seasonal climate feedback distribution and the seasonal surface temperature response.
... These uncertainties are seen in the atmospheric part of the climate model as well as from the coupled system due to ocean mechanisms and coupled exchanges between the two mediums. The inter-model differences in simulating a response to a given forcing has been documented throughout the history of atmospheric model development (Cess et al. 1990(Cess et al. , 1996Colman et al. 2001;Colman 2002). They remain critical in understanding the large spread amongst climate change projections as seen in the third IPCC report (Cubasch et al. 2001). ...
... To investigate the uncertainties attached to climate change simulation, several projections provided by state-of-the-art GCMs of different origins were used. The models used cover a large spectrum of the observed model sensitivity spread (Colman 2002) and future climate projections (Meehl et al. 2000;Cubasch et al. 2001). A third level of uncertainty lies in the regionalization tool itself. ...
... The LMD model lies in between with a warming of around 3°C. This is coherent with the model global responses (Meehl et al. 2000) and their climate sensitivity (Colman 2002). In all three models, maximum warming tends to occur at high and low latitudes with minimum values over the northern parts For the sake of brevity, the other seasons will not be shown. ...
A statistical downscaling procedure based on an analogue technique is used to determine projections for future climate change in western France. Three ocean and atmosphere coupled models are used as the starting point of the regionalization technique. Models' climatology and day to day variability are found to reproduce the broad main characteristics seen in the reanalyses. The response of the coupled models to a similar CO2 increase scenario exhibit marked differences for mean sea-level pressure; precipitable water and temperature show arguably less spread. Using the reanalysis fields as predictors, the statistical model parameters are set for daily extreme temperatures and rain occurrences for seventeen stations in western France. The technique shows some amount of skill for all three predictands and across all seasons but failed to give reliable estimates of rainfall amounts. The quality of both local observations and large-scale predictors has an impact on the statistical model skill. The technique is partially able to reproduce the observed climatic trends and inter annual variability, showing the sensitivity of the analogue approach to changed climatic conditions albeit an incomplete explained variance by the statistical technique. The model is applied to the coupled model control simulations and the gain compared with direct model grid-average outputs is shown to be substantial at station level. The method is then applied to altered climate conditions; the impact of large-scale model uncertain responses and model sensitivities are quantified using the three coupled models. The warming in the downscaled projections are reduced compared with their global model counterparts.
... The HCC maximum positive values located over mid and high latitudes of the Northern Hemisphere may be related to the lapse rate feedback. The lapse rate has maximum values over land and sea ice covered areas, consistent with the associated SAT pattern (Colman 2002). The time series associated with the most coupled HCC and SAT spatial structures are maximally correlated (1.00) (Fig. 3e). ...
... Consistent with these bidirectional interactions, the SST and high cloud anomalies are parts of the long-wave fluxes positive feedback which amplifies them. Therefore, the solar effects might be subject to the same process (Colman 2002;Soden and Vecchi 2011). The 2-year lag of the negative correlation between the solar forcing and SST/ HCC could be generated by oceanic processes. ...
One of the main sources of uncertainty in climate projections is represented by clouds, which have a profound influence on the Earth’s radiation budget through the feedbacks in which they are involved. The improvement of clouds representation in General Circulation Models relies largely on constraints derived from observations and on correct identification of processes that influence cloud formation or lifetime. Here we identify solar forced high cloud cover (HCC) patterns in reanalysis and observed data extending over the 1871–2009 period, based on their associations with known fingerprints of the same forcing on surface air temperature, sea surface temperature (SST) and sea level pressure fields. The solar influence on HCC has maximum amplitudes over the Pacific basin, where HCC anomalies are distributed in bands of alternating polarities. The colocation of the HCC and SST anomalies bands indicates a thermal influence on high clouds through convection and an amplification of the HCC anomalies by a positive feedback of long-wave fluxes, which increases the solar signal. Consistent with numerical simulations, the solar forced HCC pattern appears to be generated through a constructive interference between the so-called “top-down” and “bottom-up” mechanisms of solar influence on climate and is amplified by ocean–atmosphere positive feedbacks.
... A number of studies have looked at the geographic distribution of climate feedbacks. Colman (2002) evaluated the strength and spatial distribution of the top-of-the-atmosphere (TOA) radiative perturbations attributable to radiative feedbacks in a low-resolution GCM using the partial radiative perturbation (PRP) method (Wetherald and Manabe 1988). Taylor et al. (2011) applied the PRP method with the Monte Carlo independent column approximation technique to model output from the National Center for Atmospheric Research (NCAR) Community Climate System Model, version 3 (CCSM3), to investigate the geographical distributions of radiative feedbacks. ...
... Because some feedback variables are generally highly correlated (e.g., cloud and water vapor) at short time scales, the standard PRP method may produce substantial bias in the radiative perturbation calculation when hourly model data are used (Soden et al. 2008). To remedy this problem, we perform a twosided PRP calculation for each feedback as suggested by Colman and McAvaney (1997), Colman (2002), and Soden et al. (2008). First, the radiative energy perturbation resulting from feedback pr in the control climate (13CO 2 ) is determined by the offline radiation calculation with all input hourly variables from 13CO 2 run, but substituting pr with that from the 23CO 2 run. ...
The climate feedback-response analysis method (CFRAM) was applied to 10-yr hourly output of the NCAR Community Climate System Model, version 3, using the slab ocean model (CCSM3-SOM), to analyze the strength and spatial distribution of climate feedbacks and to characterize their contributions to the global and regional surface temperature T-s changes in response to a doubling of CO2. The global mean bias in the sum of partial T-s changes associated with the CO2 forcing, and each feedback derived with the CFRAM analysis is about 2% of T-s change obtained directly from the CCSM3-SOM simulations. The pattern correlation between the two is 0.94, indicating that the CFRAM analysis using hourly model output is accurate and thus is appropriate for quantifying the contributions of climate feedback to the formation of global and regional warming patterns. For global mean T-s, the largest contributor to the warming is water vapor feedback, followed by the direct CO2 forcing and albedo feedback. The albedo feedback exhibits the largest spatial variation, followed by shortwave cloud feedback. In terms of pattern correlation and RMS difference with the modeled global surface warming, longwave cloud feedback contributes the most. On zonal average, albedo feedback is the largest contributor to the stronger warming in high latitudes than in the tropics. The longwave cloud feedback further amplifies the latitudinal warming contrast. Both the land-ocean warming difference and contributions of climate feedbacks to it vary with latitude. Equatorward of 50 degrees, shortwave cloud feedback and dynamical advection are the two largest contributors. The land-ocean warming difference on the hemispheric scale is mainly attributable to longwave cloud feedback and convection.
... Coral reefs such as the Great Barrier Reef (GBR), Australia, are ecosystems of enormous biological diversity, in addition to forming the basis of valuable tourism and fishing industries of great economic importance (Hoegh-Guldberg, 1999;Marshall and Johnson, 2007). Coral bleaching has been observed sporadically on the GBR since 1982, with severe bleaching events occurring during the summers of 1998, 2002(Berkelmans et al., 2004Weeks et al., 2008). Frequency and severity of bleaching is, however, predicted to increase under global warming, thus posing a serious threat to the future of the GBR and the world's coral reefs (Hoegh-Guldberg, 1999;Hughes et al., 2003;Donner et al., 2005;Pratchett et al., 2008). ...
... The POAMA is a global seasonal forecast system. It uses a coupled ocean-atmosphere general circulation model consisting of the Australian Bureau of Meteorology atmospheric model (BAM 3.0; Colman and McAvaney, 1995;Colman, 2002) and the CMAR Australian Community Ocean Model V.2 (ACOM2; Schiller et al., 2002). The atmospheric model component has a horizontal spectral resolution of T47 and 17 vertical levels, whilst the ocean model grid spacing is 2°in the zonal direction and 0.5°-1.5°in the meridional direction, with 25 vertical levels, of which 12 are in the upper 185 m. ...
Coral bleaching, triggered by elevated water temperatures, is a serious threat to the future health of the world coral reef systems and represents a considerable challenge for reef management. Seasonal forecast products from coupled ocean–atmosphere models can be used to predict anomalously warm conditions several months in advance and
provide early warning of bleaching, allowing for a proactive management response to bleaching. Predictions on a seasonal timescale are the most practical for reef managers, as strategies can be implemented at the start of summer prior to the onset of bleaching. To more accurately assess the potential for bleaching, both duration and magnitude of the thermal stress must be considered, in addition to the probability of an event occurring. In this study, we assess the ability of the Australian Bureau of Meteorology seasonal forecast model (POAMA) to forecast monthly HotSpots and Degree Heating
Months in the Great Barrier Reef, Australia, with particular focus on the major 1997/1998 and 2001/2002 bleaching events. Probabilistic forecasts for exceeding certain thresholds are also assessed. This work is part of an ongoing research effort to apply a dynamical seasonal model to the problem of coral bleaching and to provide valuable forecast tools for reef managers at useful time scales.
... Finally, the water in the atmosphere is the energy carrier, releasing or accumulating its resources during phase transitions, so it is a significant link in the energy exchange between atmosphere and ocean. Therefore, the water content in the atmosphere is taken into account in global and regional meteorological models [16][17][18]. In practice, PW is used to increase the accuracy of weather forecasts [19][20][21][22][23][24][25][26] and explains the course and occurrence of extreme weather events, such as heavy precipitation, violent storms, super-cell thunderstorms and others [27][28][29][30][31][32][33]. ...
In this work, the high-resolution spatial and temporal variability of precipitable water (PW) over Poland is presented. PW is one of the key parameters of the atmosphere taken into account in thermodynamic and radiation models. The daily PW values from years 2001–2010, calculated with the use of the WRF model, were compared with PW from soundings. The WRF modeled PW is in close agreement with measurements for the whole column of the troposphere and for individual levels: below 1.5 km, 1.5–3 km, 3–6 km and 6–10 km. The best agreement is observed in the lower part of the troposphere, especially for winter months. At the levels of 1.5 km to 10 km, the WRF model overestimates the PW values throughout the year, whereas up to 1.5 km PW is underestimated. The study shows an increasing trend of PW annual values between 1983 and 2010, but the trend is statistically insignificant. A significant positive trend with a high Sen’s slope is observed for the summer season up to 3 km in the troposphere, along with a significant negative tendency for spring. The trends in PW over Poland and Central Europe identified in this study contribute to the ongoing discussion on the observed climate changes.
... The atmospheric model component of POAMA 2.4 is based on the Bureau of Meteorology's Atmospheric Model version 3.0, with a horizontal spectral resolution of approximately 250 km and 17 vertical levels (Colman and McAvaney 1995;Colman 2002). The ocean model is the CMAR Australian Community Ocean Model V.2 (ACOM2), with model grid spacing of 2°in the zonal direction, and 0.5°to 1.5°in the meridional direction (Schiller et al. 2004) with 25 vertical levels, and a 15 m top layer. ...
Great Barrier Reef (GBR) marine park managers rely on seasonal forecasts of sea surface temperature (SST) to better inform and coordinate their management responses to mass coral bleaching events. The Bureau of Meteorology’s new seasonal forecast model ACCESS-S1 is well placed for integration in marine park managers’ risk management systems, with model benefits including high ocean resolution and probabilistic forecasts from a 99 member ensemble. The SST forecast skill was assessed for the GBR region against satellite SST observations over the model hindcast period 1990–2012. ACCESS-S1 was most successful in forecasting larger warm anomalies in the GBR associated with climate drivers that persisted over many months (e.g. ENSO events). The model consistently performed better than persistence reference forecasts over the critical summer period. The model was less successful in forecasting short-term events driven by regional weather patterns, with a reduction in skill between pre-monsoon and post-monsoon onset. Forecasts in the northern GBR often exhibited the highest skill. The model was successfully able to predict SST anomalies associated with the peak of the East Australian Current. The ability of the model to discriminate between two dichotomous events (whether or not a threshold is exceeded) ranged from excellent at lead time 0 (first month forecast) to reasonable at lead times 1 and 2. Increasing the ensemble size using time-lagged ensemble members showed improvement in probabilistic skill for warm anomaly events. Model reliability showed good ability in matching the observed frequency for warm anomaly events, although slightly overconfident. The results demonstrate that ACCESS-S1 can provide skilful SST forecasts in support of coral reef management activities on sub-seasonal to seasonal timescales. Seasonal SST forecasts from ACCESS-S1 are currently available at the Bureau of Meteorology’s website for the GBR and greater Coral Sea region.
... This change in thermal LW emission due to temperature changes is known as the temperature feedback. In the conventional top-of-atmosphere (TOA) feedback-analysis framework the temperature feedback is typically decomposed into a uniform temperature response equal to the surface temperature change (also referred to as the Planck feedback) and a lapse-rate feedback, which describes the deviation of the temperature response from uniformity (Wetherald and Manabe 1988;Colman 2002Colman , 2003Soden and Held 2006;Soden et al. 2008;Taylor et al. 2011). From the TOA perspective, the temperature feedback is a negative feedback as the general warming of the atmosphere and surface lead to an increase of the outgoing longwave radiation (e.g., Soden et al. 2008). ...
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 non-temperature 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.
We analyze a 1% yr 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 explain 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 three times larger than the next largest warming contribution, indicating that the temperature feedback loop is the preeminent contributor to the surface warming.
... Several studies have also looked at the spatial distribution of climate feedbacks. Colman (2002) examined feedbacks spatially (but with fixed cloud optical properties). Ogura et al. (2008) found sensitivity in a single GCM was altered by changes to ice microphysics in the * The National Center for Atmospheric Research is sponsored by the National Science Foundation. ...
An ensemble of simulations from different versions of the Community Atmosphere Model in the Community Earth System Model (CESM) is used to investigate the processes responsible for the intermodel spread in climate sensitivity. In the CESM simulations, the climate sensitivity spread is primarily explained by shortwave cloud feedbacks on the equatorward flank of the midlatitude storm tracks. Shortwave cloud feedbacks have been found to explain climate sensitivity spread in previous studies, but the location of feedback differences was in the subtropics rather than in the storm tracks as identified in CESM. The cloud-feedback relationships are slightly stronger in the winter hemisphere. The spread in climate sensitivity in this study is related both to the cloud-base state and to the cloud feedbacks. Simulated climate sensitivity is correlated with cloud-fraction changes on the equatorward side of the storm tracks, cloud condensate in the storm tracks, and cloud microphysical state on the poleward side of the storm tracks. Changes in the extent and water content of stratiform clouds (that make up cloud feedback) are regulated by the base-state vertical velocity, humidity, and deep convective mass fluxes. Within the storm tracks, the cloud-base state affects the cloud response to CO2-induced temperature changes and alters the cloud feedbacks, contributing to climate sensitivity spread within the CESM ensemble.
... So in Figure 3, after the zonal averaging, each feedback component has been divided by that GCM's surface warming and multiplied by the mean warming for all the GCMs, before the anomalies from the multimodel mean are taken. This removes the effects of different latitudinal distributions of warming -largely due to cloud and SW feedbacks [Senior and Mitchell, 2000;Colman, 2002;Ingram, 2012] -on the assumption that the changes in CSOLR are primarily a response to local near-surface warming, and so proportional to it [Senior and Mitchell, 2000]. ...
The clear-sky longwave component of the climate sensitivity
parameterλCSLWis estimated for 5 diverse
state-of-the-art general circulation models (GCMs). A common radiation
code is used to calculate 2 alternative breakdowns. The conventional
breakdown, into "surface temperature feedback", "lapse rate feedback"
and "water vapor feedback" shows only the well-known result of large but
mostly compensating variations in the latter two components, due to
variations in the distribution of warming. In one
GCM,λCSLW is rather stronger than the rest, tending to
reduce the sensitivity of climate. The "partly Simpsonian" breakdown
shows that this is because of a combination of having less water vapor
to start with and less increase in water vapor around the tropopause on
warming. Two GCMs show λCSLWrather weaker than the
rest, because of weaker amplification of the warming aloft, in one case
combined with stronger-than-average relative humidity increases. The net
effect of greater lapse rate changes (proportionally more warming aloft)
can be seen to tend consistently to reduce climate sensitivity slightly.
Also, though the impact of relative humidity changes is dominated by
reductions through most of the depth of the troposphere, its variation
across GCMs is dominated by increases around the tropopause. While the
results from so small a sample will not be quantitatively general, they
suggest that applying the new breakdown to a much wider range of GCMs
would give useful quantitative and physical information on the variation
ofλCSLW across current GCMs.
... The coupled model in POAMA (version 1.5; P1.5) consists of the Australian Bureau of Meteorology atmospheric model (BAM 3.0;Colman and McAvaney 1995;Colman 2002) and the CMAR Australian Community Ocean Model V.2 (ACOM2; Schiller et al. 2002), the latter based on the Geophysical Fluid Dynamics Laboratory Modular Ocean Model Version 2.0 (MOM2; Pacanowski 1995). The atmospheric model component has a horizontal spectral resolution of T47 and 17 vertical levels. ...
Sea surface temperature (SST) is now recognised as the primary cause of mass coral bleaching events. Coral bleaching occurs during times of stress, particularly when SSTs exceed the coral colony's tolerance level. Global warming is potentially a serious threat to the future of the world's reef systems with predictions by the international community that bleaching will increase in both frequency and severity. Advance warning of anomalous sea surface temperatures, and thus potential bleaching events, would allow for the implementation of management strategies to minimise reef damage. Seasonal SST forecasts from the coupled ocean-atmosphere model POAMA (Bureau of Meteorology) have skill in the Great Barrier Reef (Australia) several months into the future. We will present model forecasts and probabilistic products for use in reef management, and assess model skill in the region. These products will revolutionise the way in which coral bleaching events are monitored and assessed in the Great Barrier Reef and Australian region.
... Feedback studies have mostly concentrated on quantifying the global mean feedbacks due to changes in surface albedo, water vapor, lapse rate, and clouds (e.g., Bony et al. 2006). A number of studies have looked at the spatial pattern of feedback strength, but these have generally been either an assessment of multiple feedbacks in one model (e.g., Colman 2002;Boer and Yu 2003), an assessment of one feedback in multiple models (e.g., Winton 2006a), and/or application of a new method to estimate feedback patterns (e.g., Soden et al. 2008;Winton 2006a). They also usually assess the local contribution to the global mean feedback rather than the local feedback itself. ...
Spatial patterns of local climate feedback and equilibrium partial temperature responses are produced from eight general circulation models with slab oceans forced by doubling carbon dioxide (CO2). The analysis is extended to other forcing mechanisms with the Met Office Hadley Centre slab ocean climate model version 3 (HadSM3). In agreement with previous studies, the greatest intermodel differences are in the tropical cloud feedbacks. However, the greatest intermodel spread in the equilibrium temperature response comes from the water vapor plus lapse rate feedback, not clouds, disagreeing with a previous study. Although the surface albedo feedback contributes most in the annual mean to the greater warming of high latitudes, compared to the tropics (polar amplification), its effect is significantly ameliorated by shortwave cloud feedback. In different seasons the relative importance of the contributions varies considerably, with longwave cloudy-sky feedback and horizontal heat transport plus ocean heat release playing a major role during winter and autumn when polar amplification is greatest. The greatest intermodel spread in annual mean polar amplification is due to variations in horizontal heat transport and shortwave cloud feedback. Spatial patterns of local climate feedback for HadSM3 forced with 2 x CO2, +2% solar, low-level scattering aerosol and high-level absorbing aerosol are more similar than those for different models forced with 2 x CO2. However, the equilibrium temperature response to high-level absorbing aerosol shows considerably enhanced polar amplification compared to the other forcing mechanisms, largely due to differences in horizontal heat transport and water vapor plus lapse rate feedback, with the forcing itself acting to reduce amplification. Such variations in high-latitude response between models and forcing mechanisms make it difficult to infer specific causes of recent Arctic temperature change.
... The forecast system consists of a coupled model and initialisation systems for the ocean, land and atmosphere. The coupled model in POAMA (version 1.5; P1.5) consists of the Australian Bureau of Meteorology atmospheric model (BAM 3.0; Colman and McAvaney 1995; Colman 2002) and the CMAR Australian Community Ocean Model V.2 (ACOM2; Schiller et al. 2002), the latter based on the Geophysical Fluid Dynamics Laboratory Modular Ocean Model Version 2.0 (MOM2; Pacanowski 1995). The atmospheric model component has a horizontal spectral resolution of T47 and 17 vertical levels. ...
Coral bleaching is a serious problem threatening the world coral reef systems, triggered by high sea surface temperatures (SST) which are becoming more prevalent as a result of global warming. Seasonal forecasts from coupled ocean–atmosphere models
can be used to predict anomalous SST months in advance. In this study, we assess the ability of the Australian Bureau of Meteorology seasonal forecast model (POAMA) to forecast SST anomalies in the Great Barrier Reef, Australia, with particular focus on the
major 1998 and 2002 bleaching events. Advance warning of potential bleaching events allows for the implementation of management strategies to minimise reef damage. This study represents the first attempt to apply a dynamical seasonal model to the problem
of coral bleaching and predict SST over a reef system for up to 6months lead-time, a potentially invaluable tool for reef managers.
... Wyant et al., submitted). Studies of local feedbacks in individual climate models have also emerged; Colman (2002) applied methods derived from Wetherald and Manabe (1988; the so-called partial radiative perturbation (PRP) approach) to the Bureau of Meteorology Research Centre (BMRC) model, while a local analysis of feedbacks in the Canadian Climate Model (Boer and Yu 2003) separated the effects of clouds and clear-sky effects using a measure of cloud feedback based on cloud radiative forcing method of Cess and Potter (1988). These developments in cloud diagnosis and feedback analysis techniques are now being applied across a range of models as part of the Cloud Feedback Model Intercomparison Project (CFMIP; McAvaney and Le Treut 2003; http://www.cfmip.net). ...
Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO 2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/45863/1/382_2006_Article_111.pdf
This study performs offline, partial radiative perturbation calculations to determine the geographical distributions of climate feedbacks contributing to the top-of-atmosphere (TOA) radiative energy budget. These radiative perturbations are diagnosed using monthly mean model output from the NCAR Community Climate System Model version 3 (CCSM3.0) forced with the Special Report Emissions Scenario (SRES) A1B emission scenario. The Monte Carlo Independent Column Approximation (MCICA) technique with a maximum random overlap rule is used to sample monthly mean cloud frequency profiles to perform the radiative transfer calculations. It is shown that the MCICA technique provides a good estimate of all feedback sensitivity parameters. The radiative perturbation results are used to investigate the spatial variability of model feedbacks showing that the shortwave cloud and lapse rate feedbacks exhibit the most and second most spatial variability, respectively. It has been shown that the model surface temperature response is highly correlated with the change in the TOA net flux, and that the latter is largely determined by the total feedback spatial pattern rather than the external forcing. It is shown by representing the change in the TOA net flux as a linear combination of individual feedback radiative perturbations that the lapse rate explains the most spatial variance of the surface temperature response. Feedback spatial patterns are correlated with the model response and other feedback spatial patterns to investigate these relationships. The results indicate that the model convective response is strongly correlated with cloud and water vapor feedbacks, but the lapse rate feedback geographic distribution is strongly correlated with the climatological distribution of convection. The implication for the water vapor lapse rate anticorrelation is discussed.
Coral bleaching, triggered by high ocean temperatures, is a growing challenge for reef management. This paper assesses the ability of an operational seasonal prediction system (POAMA) to forecast summer SST anomalies in real-time across the Great Barrier Reef. Real-time POAMA SST forecasts compare well to observed conditions, particularly during ENSO active years. Prediction skill, however, can be limited by model resolution, ensemble system design and the inherent predictability of events such as monsoon onset. Advanced warning of anomalously warm conditions, and hence bleaching risk, allows for a proactive management approach and is an invaluable tool for reef management under a changing climate.
Model differences in projections of extratropical regional climate change due to increasing greenhouse gases are investigated
using two atmospheric general circulation models (AGCMs): ECHAM4 (Max Planck Institute, version 4) and CCM3 (National Center
for Atmospheric Research Community Climate Model version 3). Sea-surface temperature (SST) fields calculated from observations
and coupled versions of the two models are used to force each AGCM in experiments based on time-slice methodology. Results
from the forced AGCMs are then compared to coupled model results from the Coupled Model Intercomparison Project 2 (CMIP2)
database. The time-slice methodology is verified by showing that the response of each model to doubled CO2 and SST forcing from the CMIP2 experiments is consistent with the results of the coupled GCMs. The differences in the responses
of the models are attributed to (1) the different tropical SST warmings in the coupled simulations and (2) the different atmospheric
model responses to the same tropical SST warmings. Both are found to have important contributions to differences in implied
Northern Hemisphere (NH) winter extratropical regional 500mb height and tropical precipitation climate changes. Forced teleconnection
patterns from tropical SST differences are primarily responsible for sensitivity differences in the extratropical North Pacific,
but have relatively little impact on the North Atlantic. There are also significant differences in the extratropical response
of the models to the same tropical SST anomalies due to differences in numerical and physical parameterizations. Differences
due to parameterizations dominate in the North Atlantic. Differences in the control climates of the two coupled models from
the current climate, in particular for the coupled model containing CCM3, are also demonstrated to be important in leading
to differences in extratropical regional sensitivity.
An aquaplanet atmospheric general circulation model (GCM) coupled to a mixed layer ocean is analyzed in terms of its polar
amplified surface temperature response to a 2×CO2-like steady forcing and in terms of the phase space trajectory of the relaxation of a free perturbation to equilibrium. In
earlier studies concerned with linear stability analysis of the same system we have shown that the least stable mode of the
linearized surface budget operator has a polar amplified shape. We demonstrate that this shape of the least stable mode is
responsible for the polar amplified shape of the response to a uniform forcing and for the manner in which the system relaxes
back to equilibrium. Based on GCM and simple energy balance model results it is argued that the decay time-scale of this mode
is determined by the sensitivity of the net top-of-atmosphere radiation to surface temperature while its shape (and thus the
degree of polar amplification in a climate change experiment) is determined by the sensitivity of poleward heat transports
to low- and high-latitude temperatures by the faster time-scale atmospheric dynamics. This implies that the underlying mechanisms
for the polar amplification may be obscured when studying feedbacks during the slow evolution of climate change or considering
only the new equilibrium state after introduction of a steady forcing.
This study addresses the question: how do the contributions to feedbacks in a climate model vary over the seasonal cycle? To answer this the feedbacks are evaluated from an equilibrium doubled CO2 experiment performed using the Bureau of Meteorology Research Centre (BMRC) General Circulation Model. Monthly means of the top-of-atmosphere radiative perturbations (which together comprise the annual climate feedbacks) are extracted to produce a mean annual cycle. It is found that the radiative contributions to the total longwave (LW) feedback are fairly constant throughout the year. Those to the total shortwave (SW) feedback, on the other hand, vary by a factor of three, from a maximum in July to a minimum in November. Of the LW feedbacks, contributions to the lapse rate shows greatest seasonal variation, while those to water vapour and cloud feedbacks vary by relatively small amounts throughout the year. Contributions to the lapse rate feedback as a function of surface type and latitude reveal conflicting positive and negative radiative perturbations, which vary most strongly at high latitudes. Of the SW feedbacks, contributions to both albedo and cloud show large seasonal variations. Radiative perturbations contributing to albedo feedback vary in strength with snow and sea-ice retreat which occurs at different latitudes and in different months. They are shown to be highly sensitive to the amount of incident solar radiation in a given month. SW radiative perturbations due to cloud changes vary in sign between opposite seasons. Contributions to the seasonal variations of the cloud component feedbacks, which make up the total cloud feedback, are also examined. In the LW, the feedback is dominated by the total cloud water term. Radiative perturbations due to this component show relatively little variation throughout the year. In the SW, the main source of seasonal variation occurs for contributions to the cloud amount feedback: radiative perturbations vary from strongly positive in July to close to zero in December. The seasonal cycle of the perturbations making up the other cloud component feedbacks is also considered. Implications for climate sensitivity, and for the diagnosis of climate feedbacks are discussed.
The present study provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphazied that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback.
The correlations between interannual variations of tropical mean water vapor and temperature in the simulations by a low resolution (R15) GCM are stronger than those in the rawinsonde observations. The rate of fractional increase of tropical mean water vapor with temperature in the model simulations is also larger than that from the observations. The largest discrepancies are found in the region immediately above the tropical convective boundary layer (850-600 mb). The rate of fractional increase of tropical mean water vapor with temperature in the model simulations is close to that for a constant relative humidity. The correlations between variations of water vapor in the upper troposphere and those in the lower troposphere are also stronger in the model simulations than in the observations. In the horizontal, the characteristic spatial patterns of the normalized water vapor variations in the model simulations and observations are similar. The water vapor-temperature relationship in simulations by a GCM with a somewhat higher spatial resolution (R30) is almost identical to that in the simulations by the low resolution (R15) GCM. The implications of these findings for the radiative feedback of water vapor are discussed.
The model used is a general circulation model of the atmosphere coupled with a mixed layer model of the oceans. The sensitivity of each version of the model is inferred from the equilibrium response of the model to a doubling of the atmospheric concentration of carbon dioxide. In response to the increase of atmospheric carbon dioxide, cloudiness increases around the tropopause and is reduced in the upper troposphere, thereby raising the height of the cloud layer in the upper troposphere. This implies a reduction of the temperature of the cloud top and, accordingly, of the upward terrestrial radiation from the top of the model atmosphere. On the other hand, the increase of low cloudiness in high latitudes raises the planetary albedo and thus decreases the CO2 induced warming of climate. However, the contribution of this negative feedback process is much smaller than the effect of the positive feedbakc process involving the change of high cloud. -from Authors
A method is described for evaluating the ‘partial derivatives’ of globally averaged top-of-atmosphere (TOA) radiation changes
with respect to basic climate model physical parameters. This method is used to analyse feedbacks in the Australian Bureau
of Meteorology Research Centre general circulation model. The parameters considered are surface temperature, water vapour,
lapse rate and cloud cover. The climate forcing which produces the changes is a globally uniform sea surface temperature (SST)
perturbation. The first and second order differentials of model parameters with respect to the forcing (i.e. SST changes)
are estimated from quadratic least square fitting. Except for total cloud cover, variables are found to be strong functions
of global SST. Strongly non-linear variations of lapse rate and high cloud amount and height appear to relate to the non-linear
response in penetrative convection. Globally averaged TOA radiation differentials with respect to model parameters are also
evaluated. With the exception of total cloud contributions, a high correlation is generally found to exist, on the global
mean level, between TOA radiation and the respective parameter perturbations. The largest non-linear terms contributing to
radiative changes are those due to lapse rate and high cloud. The contributions of linear and non-linear terms to the overall
radiative response from a 4 K SST perturbation are assessed. Significant non-linear responses are found to be associated with
lapse rate, water vapour and cloud changes. Although the exact magnitude of these responses is likely to be a function of
the particular model as well as the imposed SST perturbation pattern, the present experiments flag these as processes which
cannot properly be understood from linear theory in the evaluation of climate change sensitivity.
To understand water vapor feedback's role in unperturbed surface temperature variability, a version of the GFDL coupled ocean-atmosphere model is integrated for 1000 years in two configurations, one with water vapor feedback, and one without. The model with water vapor feedback has more surface temperature variability on all spatial and time scales than the one without. In addition, water vapor feedback is more effective the longer the time scale of the surface temperature anomaly and the larger its spatial scale. To understand water vapor feedback's role in global warming, we also performed two 500-year integrations in which CO2 was doubled in both model configurations. The equilibrium surface global warming in the model with water vapor feedback is 3.78°C, while in the one without it is only 1.05°C. However, the model's water vapor feedback has a larger impact on surface warming in response to a doubling of CO2 than it does on internally-generated, low-frequency, global-mean surface temperature anomalies. Water vapor feedback's strength therefore depends on the type of temperature anomaly it affects. We found that the degree to which a surface temperature anomaly penetrates the troposphere is a critical factor in determining the effectiveness of its associated water vapor feedback. The more the anomaly penetrates, the stronger the feedback. We also show that the apparent impact of water vapor feedback is altered by other feedback mechanisms, such as albedo, and cloud feedback. We examine the sensitivity of our results to this fact. Finally, we compare the local and global-mean surface temperature time series from both unperturbed variability experiments to the observed record. The experiment without water vapor feedback does not have enough global- scale variability to reproduce the magnitude of the variability in the observed global-mean record, whether or not one removes the warming trend observed over the past century. In contrast, the amount of variability in the experiment with water vapor feedback is comparable to the global-mean record, provided the observed warming trend is removed. Thus, we cannot simulate the observed levels of variability without water vapor feedback.
We study climate sensitivity and feedback processes in three independent ways: (1) by using a three dimensional (3-D) global climate model for experiments in which solar irradiance S0 is increased 2 percent or CO2 is doubled, (2) by using the CLIMAP climate boundary conditions to analyze the contributions of different physical processes to the cooling of the last ice age (18K years ago), and (3) by using estimated changes in global temperature and the abundance of atmospheric greenhouse gases to deduce an empirical climate sensitivity for the period 1850–1980.
Lapse rate, moist adiabatic lapse rate and the critical lapse rate for baroclinic adjustment are calculated as was done by Stone and Carlson (1979) using a different data set covering both hemispheres. Results show very good agreement in low latitudes, where temperature lapse rate can be approximated by the moist adiabatic lapse rate. In midlatitudes of the Northern Hemisphere, the lapse rate agrees with the critical lapse rate for baroclinic adjustment. In midlatitudes of the Southern Hemisphere, the lapse rate follows the critical lapse rate for baroclinic adjustment with a 15-deg lag.
The greenhouse effect hypothesis is discussed. The effects of increasing CO2 levels in the atmosphere on global temperature changes are analyzed. The problems with models currently used to predict climatic changes are examined.
The global temperature rose by 0.2 degrees C between the middle 1960's and 1980, yielding a warming of 0.4 degrees C in the past century. This temperature increase is consistent with the calculated greenhouse effect due to measured increases of atmospheric carbon dioxide. Variations of volcanic aerosols and possibly solar luminosity appear to be primary causes of observed fluctuations about the mean trend of increasing temperature. It is shown that the anthropogenic carbon dioxide warming should emerge from the noise level of natural climate variability by the end of the century, and there is a high probability of warming in the 1980's. Potential effects on climate in the 21st century include the creation of drought-prone regions in North America and central Asia as part of a shifting of climatic zones, erosion of the West Antarctic ice sheet with a consequent worldwide rise in sea level, and opening of the fabled Northwest Passage.
It shows that the feedback factors in global and annual mean conditions are in the sequence of surface albedo, water vapor amount, water vapor distribution, cloud height, critical lapse rate and cloud cover, while in zonal and annual mean conditions in the tropical region the above sequence does not change except the two water vapor terms being the largest feedback components. Among the feedback components, the total water vapor feedback is the largest (about 50%). The diagnosis also gives a very small feedback of either the cloud cover or the lapse rate, which is substantially different from the 1-D feedback analysis by Hansen et al. (1984). The feedback effect for doubled CO2 is very different from that of the addition of other trace gases because of their different vertical distributions of radiative forcing although the non-feedback responses of surface air temperature for both cases are almost the same. -from Authors
This paper reviews the role of water vapor in climate sensitivity, the factors determining water vapor concentrations, comparisons of observed and model behavior of water vapor, and indirect and direct approaches to determining the actual climate feedback.
It is shown that the anthropogenic carbon dioxide warming should emerge from the noise level of natural climate variability by the end of the century, and there is a high probability of warming in the 1980's. Potential effects on climate in the 21st century include the creation of drought-prone regions in North American and central Asia as part of a shifting of climatic zones, erosion of the West Antarctic ice sheet with a consequent worldwide rise in sea level, and opening of the fabled Northwest Passage. -from Authors
Two versions of the National Center for Atmospheric Research Community Climate Model (CCM) are used to calculate the increase in solar energy absorbed by the Earth-atmosphere system if all sea ice on the planet were to melt. The increase in solar energy is determined at several time points in the seasonal cycle by brief integrations of the models with the surface albedo of sea ice changed to that of open ocean; temperature, cloudiness, and other climate parameters are unchanged during the short integrations, so that our results isolate the climatic effect of sea ice albedo changes in the absence of other processes and feedbacks. (In particular, we do not include the effects of removing the insulation between ocean underneath sea ice and the atmosphere above it.) We find that the globally and annually average enhancement of absorbed solar flux due to removal of sea ice is 2-3 Wm-2 a simple calculation indicates that most of the difference between model versions is due to differences in the surface albedo of sea ice. About half the albedo reduction at the surface is masked at the top of the atmosphere by clouds, even though the CCM versions we use tend to underestimate cloudiness. Our upper limit is significant compared to direct radiative forcing of a doubling of atmospheric carbon dioxide, but it suggests that for greenhouse gas warming equivalent to doubling of CO2 or greater, the sea ice albedo feedback is likely to be smaller than that from water vapor and potentially that from clouds.
The response of a general circulation model (GCM) to global perturbations in sea surface temperatures (SSTs) is examined. The feedback strengths in the model are diagnosed by the response of top of atmosphere (TOA) radiative fluxes determined after substitution of fields from the ``perturbed'' climate into the ``control.'' Total feedback is divided into terms due to water vapour, lapse rate, surface temperature, and clouds (in turn analysed in terms of cloud amount, height and types). The ``standard experiment'' prescribes a globally uniform SST perturbation with fixed soil moisture. Four additional experiments vary the number of model vertical levels, the pattern of SST changes, the convection scheme, and the soil moisture. The SST pattern change chosen follows that of an equilibrium 2×CO2 experiment, which shows polar amplification of the surface warming. Variations in the clear sky sensitivity of the model are shown to depend primarily on changes in the long wave response due to competing (positive) water vapor and (generally negative) lapse rate feedbacks. Results here indicate that these feedbacks may be very different for differing experimental boundary conditions. The long wave feedback due to cloud amount changes is negative in all experiments, due to a very consistent decrease in high and middle cloud fractions. Conversely, cloud height feedback is positive due to a general increase in the altitude of (particularly high) cloud. Cloud height feedback is very sensitive to the choice of the convection scheme and to the change in vertical resolution. Greatest changes in the strength of the short wave cloud feedback results from modifications to the soil moisture specification and the convection scheme. The results here indicate that large differences in cloud feedback may be diagnosed from a single model, even without changes being made to the cloud parametrization. The value of the sensitivity can thus be expected to be a function not only of the physical parametrizations chosen for the model (e.g. the penetrative convection scheme), but also of the details of the manner in which the experiment was performed (e.g. SST and soil moisture specifications). The TOA radiation perturbation analysis method proves to be a powerful technique for diagnosing and understanding the physical processes responsible for the range in climate sensitivity found between the experiments.
A method is proposed to diagnose climate feedbacks of water vapor, temperature lapse-rate, and cloud variations in atmospheric general circulation models. It is then applied to study differences in sensitivity of the National Center for Atmospheric Research community climate model (CCM2) and two hybrid versions of CCM2 with different cumulus-convection schemes. Water vapor feedback and temperature lapse-rate feedback differ among the models due to different efficiencies of heat and moisture transport by cumulus convections. A large compensation occurs between water vapor feedback and temperature lapse-rate feedback. This leads to similar clear-sky sensitivities in the models. Cloud-radiative feedback is negative in CCM2 with a DeltaSST climate change due to the vigorous cumulus-convective scheme. Stronger convection warms the upper troposphere and reduces its cloudiness more, resulting in negative longwave cloud-radiative feedback. In models where a moist-adiabatic-adjustment scheme and then a decoupling of the atmospheric boundary layer are subsequently used, intensity of cumulus convection is successively reduced and cloud-radiative feedback changes to either neutral or positive.
Changes in cloud distribution may provide a major feedback on climate change. General circulation model simulations show an upward shift of high cloud and a general reduction of free-tropospheric cloud when climate warms. The shift of high cloud seems due to an upward shift of the tropopause. It is argued that the reduction in relative humidity and cloud cover below can be attributed to the increased depth of vertical motions in the warmer climate, which in turn follows from the upward shift of atmospheric radiative cooling as specific humidifies increase. A diagnostic study of the response of a general circulation model is consistent with this mechanism.
The possibility that a drying of the tropical upper troposphere might accompany tropospheric warming, substantially reducing the climate's sensitivity to a change in radiative forcing, has been subject to extensive debate. A simple one-dimensional model of tropical convection and humidity originally proposed by Lindzen (1990a) and Sun (1990) is used to explore mechanisms for ``cumulus-induced drying,'' and a narrowband radiation model to investigate its radiative implications. Low-level moistening, which accompanies warming in all cases, significantly offsets the radiative effects of any upper-level drying, making the net effect on radiative forcing critically sensitive to undetermined parameters in the model. When the model is tuned to reproduce mean relative humidities from Pacific radiosonde data, no substantial drying is observed to accompany a 1 K tropospheric warming. However, the clear-sky moisture feedback is in all cases substantially less than that suggested by a scheme in which relative humidity is held constant, illustrating the importance of upper tropospheric relative humidity for climate sensitivity. Finally, the feasibility of placing constraints on critical parameters through satellite observations of interannual variability of the tropical clear-sky radiation field is investigated.
By using satellite observations and European Centre for Medium Range Weather Forecasts analyses, we study the seasonal variations of the precipitable water and the greenhouse effect, defined as the normalized difference between the longwave flux emitted at the surface and that emergent at the top of the atmosphere. Results show a strong systematic influence of the vertical structure of the atmosphere on geographical and seasonal variations of both precipitable water and greenhouse effect. Over ocean, in middle and high latitudes, the seasonal variation of the mean temperature lapse rate in the troposphere leads to large seasonal phase lags between greenhouse effect and precipitable water. By contrast, the seasonal variation of the clear-sky greenhouse effect over tropical oceans is mainly driven by the total atmospheric transmittance and thus the precipitable water variations. Over land, the seasonal variation of the tropospheric lapse rate acts to amplify the radiative impact of water vapor changes, giving a strong seasonal variation of the greenhouse effect. Over tropical land regions, monsoon activity generates a seasonal phase lag between surface temperature and relative humidity variations that gives a seasonal lag of about 2 months between the surface temperature and the clear-sky greenhouse effect. Generally, the cloudiness amplifies clear-sky tendencies. Finally, as an illustration, obtained results are used to evaluate the general circulation model of the Laboratoire de Météorologie Dynamique.
We examine the sensitivity of a climate model to a wide range of radiative forcings, including changes of solar irradiance, atmospheric CO2, O3, CFCs, clouds, aerosols, surface albedo, and a ``ghost'' forcing introduced at arbitrary heights, latitudes, longitudes, seasons, and times of day. We show that, in general, the climate response, specifically the global mean temperature change, is sensitive to the altitude, latitude, and nature of the forcing; that is, the response to a given forcing can vary by 50% or more depending upon characteristics of the forcing other than its magnitude measured in watts per square meter. The consistency of the response among different forcings is higher, within 20% or better, for most of the globally distributed forcings suspected of influencing global mean temperature in the past century, but exceptions occur for certain changes of ozone or absorbing aerosols, for which the climate response is less well behaved. In all cases the physical basis for the variations of the response can be understood. The principal mechanisms involve alterations of lapse rate and decrease (increase) of large-scale cloud cover in layers that are preferentially heated (cooled). Although the magnitude of these effects must be model-dependent, the existence and sense of the mechanisms appear to be reasonable. Overall, we reaffirm the value of the radiative forcing concept for predicting climate response and for comparative studies of different forcings; indeed, the present results can help improve the accuracy of such analyses and define error estimates. Our results also emphasize the need for measurements having the specificity and precision needed to define poorly known forcings such as absorbing aerosols and ozone change. Available data on aerosol single scatter albedo imply that anthropogenic aerosols cause less cooling than has commonly been assumed. However, negative forcing due to the net ozone change since 1979 appears to have counterbalanced 30-50% of the positive forcing due to the increase of well-mixed greenhouse gases in the same period. As the net ozone change includes halogen-driven ozone depletion with negative radiative forcing and a tropospheric ozone increase with positive radiative forcing, it is possible that the halogen-driven ozone depletion has counterbalanced more than half of the radiative forcing due to well-mixed greenhouse gases since 1979.
The net strength of the sea ice and surface albedo feedbacks in
simulations of climate change has been estimated for several general
circulation models (GCMs) using a variety of methods. Here several
methods are applied to quantify this feedback in a single
CO2-doubling experiment with the United Kingdom
Meteorological Office GCM. Different methods give values differing by up
to a factor of 2 and are shown to be estimating different quantities. An
unbiased comparison of models is made using consistent methods, and an
attempt is made to explain the differences in model sensitivity in terms
of control climate and parameterization. Comparing the standard
experiment to a parallel experiment using prescribed sea ice extents
allows examination of the feedback as it actually operates in the model.
The importance of cloud is emphasized, both in shielding surface albedo
changes and so reducing their effect, and in providing its own
contribution to planetary albedo changes. Statistical methods are used
to examine the relationship between surface albedo changes, which are
given directly by the surface heat balance and albedo parameterization,
and planetary albedo changes, which incorporate the effects of clouds
and determine the net feedback. Estimates of the magnitude of the
feedback in various GCMs vary from 0.16 to 0.7 W m-2
K-1, with the highest value exaggerated by the method of
analysis. We conclude that care is needed in quantifying these feedbacks
and that previously published numbers are not all comparable. The
feedbacks in two of the GCMs are exaggerated by unrealistically
extensive sea ice, but the smaller values given by other GCMs may still
be unrealistic, because of uncertainties in the treatment of clouds.
Three equilibrium doubled CO2 experiments have been performed using the Bureau of Meteorology Research Centre atmospheric general circulation model. These experiments used identical versions of the model, apart from changes in the convective parameterization and the horizontal resolution. The penetrative convection parameterizations used were variants of the Tiedtke (1989) mass flux and Kuo (1974) schemes. The shallow convection was also varied in strength. In the control climate the mass flux scheme produces a warmer, moister troposphere, with substantially more high cloud than the Kuo scheme. The precipitation distributions agree reasonably with observations overall, although the mass flux scheme gives improvements in some regions.The increase in resolution is generally found to have a smaller impact upon the climate than the change in convection. Under a doubling of atmospheric CO2, the equilibrium responses of all three experiments were extremely similar in surface and tropospheric temperatures and humidity changes. The model response is at the low end of the scale of simulated climate change, consistent with a strong negative feedback found due to clouds. This feedback is similar to that found in earlier fixed season experiments. It appears to be insensitive to differences in cloud cover simulated in the control climates of the present experiments.
A simple slab ocean of 50 m depth, which allows for seasonal ocean heat storage but no ocean heat transport, is coupled to a global spectral general circulation model with global domain, realistic geography, and computed clouds. The paper first describes the atmospheric and oceanic aspects of the model. Following that there is a general discussion of the model control experiment and comparison with observed data. The next two sections describe the zonal mean and geographical responses to a doubling of CO//2 concentration. Following those there is a section with a discussion of the swamp model results compared to the present mixed-layer model results. Finally, the last section draws conclusions from the experiments.
The present and doubled CO2 equilibrium climates simulated by slab ocean versions of the atmospheric general circulation models from the Commonwealth Scientific and Industrial Research Organisation (CSIRO, Mark 1 and Mark 2) and from the Bureau of Meteorology Research Centre (BMRC) are examined, with the aim of explaining the large variation in mean warming (4.8°C, 4.3°C, and 2.1°C). The present climates are compared firstly with observations. A graphical display of nondimensional measures of local and mean errors is used. For 15 quantities the models produce broadly similar skill, which indicates that such an evaluation is of limited use as a validation of these models for climate change prediction. Comparison of the two climates indicates that for temperature, snow/ice cover, and water column (but not necessarily other fields) the typical magnitudes of local changes are in rough proportion to the mean warming. For tropical precipitation, however, the BMRC model shows a similar sensitivity to CO2 doubling as do the CSIRO models. A standard diagnostic feedback analysis shows that the Mark 1 model has stronger albedo, water vapor, and cloud feedbacks than the BMRC model. A novel regional net feedback analysis is then applied to all three models. Feedbacks for the snow/ice region and clear-sky and cloud forcing components of the snow-free region indicate similar intermodel differences to those from the diagnostic approach. The feedbacks are examined in relation to the simulated climates and model parameterizations. As the application of the regional method requires only standard climatological fields, it is proposed as a convenient analysis tool in further model comparisons.
This paper describes an observational study of the clear sky components of the Earth's radiation budget (ERB), the relationship of these components to the sea surface temperature (SST), and the microwave-derived water vapor amount using observations that are coincident in both space and time. This study uses two sets of ERB data; the Nimbus 7 narrow field-of-view, broadband scanning radiometer data from June 1979 to May 1980 and the Earth Radiation Budget Experiment (ERBE) broadband scanning data from March 1985 to February 1986. Although it is not possible to observe feedback processes directly, it is argued that the results of the paper are consistent with conventional ideas about the operation of a positive feedback on Earth between the greenhouse effect, SST and w. -from Authors
Water vapor feedback is one of the important factors that determine the response of the atmosphere to surface warming. To take into account the compensating drying effects in downdraft regions, averaging over the whole Tropics is necessary. However, this operation drastically reduces the number of degrees of freedom and raises questions concerning the statistical significance of any correlative results obtained using observational data. A more involved statistical analysis is performed here, using multiple datasets, including the global water vapor datasets of Special Sensor for Microwave/Imaging (column water), upper-tropospheric relative humidity, the Television Infrared Observational Satellite Operational Vertical Sounder retrieved upper-tropospheric specific humidity, and the surface temperature data from the National Centers for Environmental Prediction-National Center for Atmospheric Research Reanalysis dataset. The tropical-mean correlations between relative humidity and surface temperature cannot be established, but those between specific humidity and the surface temperature are found to be positive and shown to be statistically significant. This conclusion holds even when the averaging is done on the natural logarithm of the upper-tropospheric water vapor content. The effect on the tropical-mean outgoing longwave radiation is also discussed.
This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.
This study addresses the question: what vertical regions contribute the most to water vapor, surface temperature, lapse rate
and cloud fraction feedback strengths in a general circulation model? Multi-level offline radiation perturbation calculations
are used to diagnose the feedback contribution from each model level. As a first step, to locate regions of maximum radiative
sensitivity to climate changes, the top of atmosphere radiative impact for each feedback is explored for each process by means
of idealized parameter perturbations on top of a control (1 × CO2) model climate. As a second step, the actual feedbacks themselves are calculated using the changes modelled from a 2 × CO2 experiment. The impact of clouds on water vapor and lapse rate feedbacks is also isolated using `clear sky' calculations.
Considering the idealized changes, it is found that the radiative sensitivity to water vapor changes is a maximum in the tropical
lower troposphere. The sensitivity to temperature changes has both upper and lower tropospheric maxima. The sensitivity to
idealized cloud changes is positive (warming) for upper level cloud increases but negative (cooling) for lower level increases,
due to competing long and shortwave effects. Considering the actual feedbacks, it is found that water vapor feedback is a
maximum in the tropical upper troposphere, due to the large relative increases in specific humidity which occur there. The
actual lapse rate feedback changes sign with latitude and is a maximum (negative) again in the tropical upper troposphere.
Cloud feedbacks reflect the general decrease in low- to mid-level low-latitude cloud, with an increase in the very highest
cloud. This produces a net positive (negative) shortwave (longwave) cloud feedback. The role of clouds in the strength of
the water vapor and lapse rate feedbacks is also discussed.
THE atmospheric water vapour feedback is thought to amplify the global climate response to increased concentrations of greenhouse gases1. As the oceans and atmosphere warm, there is increased evaporation, and it is generally believed that the additional moisture then adds to the greenhouse effect by trapping more infrared radiation. Lindzen2-4 has suggested that climate models overestimate this response; he argues that increased convective activity in a warmer climate will lead to a drying rather than a moistening of the upper troposphere (but see refs 5-7 for other views). An important part of Lindzen's argument is that it is only changes in upper tropospheric water vapour that can alter the radiative budget of the atmosphere significantly, and hence contribute to the water vapour feedback. Here we use radiative transfer calculations to show that this seems to be true if the water vapour concentration is perturbed by a constant absolute amount at all heights. But observations of the seasonal change in water vapour concentrations6,8 suggest that the climate response to increased concentrations of greenhouse gases may be closer to a constant relative change at all heights, corresponding to much larger absolute changes in the lower troposphere. We find that the Earth's radiation budget is most sensitive to changes in lower tropospheric water vapour concentrations, when such relative perturbations are considered.
The humidity of the free troposphere is being increasingly scrutinized in climate research due to its central role in global warming theory through positive water vapor feedback. This feedback is the primary source of global warming in general circulation models (GCMs). Because the loss of infrared energy to space increases nonlinearly with decreases in relative humidity, the vast dry zones in the Tropics are of particular interest. These dry zones are nearly devoid of radiosonde stations, and most of those stations have, until recently, ignored the low humidity information from the sondes. This results in substantial uncertainty in GCM tuning and validation based on sonde data. While satellite infrared radiometers are now beginning to reveal some information about the aridity of the tropical free troposphere, the authors show that the latest microwave humidity sounder data suggests even drier conditions than have been previously reported. This underscores the importance of understanding how these low humidity levels are controlled in order to tune and validate GCMs, and to predict the magnitude of water vapor feedback and thus the magnitude of global warming.
Six years ago, we compared the climate sensitivity of 19 atmospheric general circulation models and found a roughly threefold variation among the models; most of this variation was attributed to differences in the models' depictions of cloud feedback. In an update of this comparison, current models showed considerably smaller differences in net cloud feedback, with most producing modest values. There are, however, substantial differences in the feedback components, indicating that the models still have physical disagreements.
Satellite measurements are used to quantify the atmospheric greenhouse effect, defined here as the infrared radiation energy trapped by atmospheric gases and clouds. The greenhouse effect is found to increase significantly with sea surface temperature. The rate of increase gives compelling evidence for the positive feedback between surface temperature, water vapor and the greenhouse effect; the magnitude of the feedback is consistent with that predicted by climate models. This study demonstrates an effective method for directly monitoring, from space, future changes in the greenhouse effect.
The response of radiation budgets to changes in water vapor and clouds in an El Nino episode is investigated using the analyzed sea surface temperature (SST) and satellite-derived clouds and the earth radiation budgets for the tropical Pacific (30 deg N-30 deg S, 100 deg E-100 deg W). Analyses are performed for April 1985 and April 1987. The former is a non-El Nino year and the latter is an El Nino year. Compared to April 1985, when the SST over the central and eastern equatorial Pacific is approximately 2 C lower, the high-level cloudiness in April 1987 increases in the central and eastern equatorial Pacific. Corresponding to the increase in cloudiness, the outgoing longwave radiation and the net downward solar radiation at the top of the atmosphere decrease. The patterns of these changes are reversed in the western tropical Pacific and the Northern Hemispheric (NH) subsidence region centered at approximately 20 deg N, indicating an eastward shift of the convection center from the maritime continents to the central equatorial Pacific and a strengthened NH Hadley circulation. The earth-atmosphere system in the region receives less radiative energy by 4 W/sq m in the warmer month of April 1987 than in the month of April 1985, which is primarily caused by a reduced atmospheric clear sky greenhouse effect in the NH tropical Pacific in April 1987. Clouds have strong effects on both the IR and solar radiation, but the net effect on the radiation budget at the top of the atmopshere changes only slightly between April 1985 and April 1987. The results are consistent with Lindzen's hypothesis that reduced upper-tropospheric water vapor in the vicinity of the enhanced convection region produces cooling that counteracts warming in the Tropics.
Increases in the concentration of water vapor constitute the single largest positive feedback in models of global climate warming caused by greenhouse gases. It has been suggested that sinking air in the regions surrounding deep cumulus clouds will dry the upper troposphere and eliminate or reverse the direction of water vapor feedback. This hypothesis has been tested by performing an idealized simulation of climate change with two different versions of a climate model which both incorporate drying due to subsidence of clear air but differ in their parameterization of moist convection and stratiform clouds. Despite increased drying of the upper troposphere by cumulus clouds, upper-level humidity increases in the warmer climate because of enhanced upward moisture transport by the general circulation and increased accumulation of water vapor and ice at cumulus cloud tops.
The effects of surface temperature and clouds on the CO2 forcing are studied, based on use of the Colorado State University GCM. Results are reported from a pair of perpetual July simulations in which the sea surface temperatures differ by 4 K. The precipitable water is about 1.5 times larger in the warm run. The increased water vapor concentration amplifies the radiative effects of CO2, leading to greater CO2 forcing in the warm run. In the colder run the globally averaged reduction in upward longwave radiation due to a doubling of CO2 is 4.3 W/sq m at the level of maximum forcing, or the 'CO2 tropopause'. Above and below this level the CO2 forcing decreases, resulting in a net tropospheric warming of 0.033 K/day and a net stratospheric cooling. In the warm run the CO2 forcing at the CO2 tropopause is 4.6 W/sq m, and is associated with a tropospheric warming of 0.04 K/day. The clear-sky CO2 forcing at the CO2 tropopause is 5.0 W/sq m in the cold run, and 5.2 W/sq m in the warm run. By blocking infrared radiation that would otherwise be blocked by CO2, the clouds reduce the CO2 forcing of the surface-troposphere system by 0.66 W/sq m in the cold run, and by 0.59 W/sq m in the warm run.
Calculations of the effects of both natural and anthropogenic tropospheric sulfate aerosols indicate that the aerosol climate forcing is sufficiently large in a number of regions of the Northern Hemisphere to reduce significantly the positive forcing from increased greenhouse gases. Summer sulfate aerosol forcing in the Northern Hemisphere completely offsets the greenhouse forcing over the eastern United States and central Europe. Anthropogenic sulfate aerosols contribute a globally averaged annual forcing of -0.3 watt per square meter as compared with +2.1 watts per square meter for greenhouse gases. Sources of the difference in magnitude with the previous estimate of Charlson et al. are discussed.
The atmospheric General Circulation Model of the Laboratoire de M'et'eorologie Dynamique (LMD) is coupled to a slab ocean model and is used to investigate the climatic impact of a CO 2 doubling. Two versions of the model are used with two different representations of the cloudradiation interaction. Both of them contain a prognostic equation for the cloud liquid water content, but they differ in the treatment of the precipitation mechanism. The annual and global mean of the surface warming is similar in the two experiments in spite of regional differences. To understand the behavior of the model versions, we split the total climate change into a direct CO 2 forcing and different feedback effects (water vapor, cloud and surface albedo). The results show that, in the second model version, the cloud feedback decreases significantly, especially at high latitudes, due to an increase of low level clouds in the 2ThetaCO 2 simulation. The modification of the cloud scheme influences also the w...
Quantitative analysis of feedbacks in cli-mate model simulations of CO 2 induced warming Physically Based Modelling and Simu-lation of Climate and Climate Change
- M E Schlesinger
Schlesinger, M.E., 1988. Quantitative analysis of feedbacks in cli-mate model simulations of CO 2 induced warming. In: Schle-singer, M.E. (Ed.), Physically Based Modelling and Simu-lation of Climate and Climate Change. NATO ASI Series C, vol. 243. Kluwer Academic Publishing, Dordrecht, pp. 653 – 736.
Climate Change: the IPCC Scientific Assessment The Supplementary Report to the IPCC Scientific As-sessment Climate Change 1995: The Science of Climate Change
- J T Houghton
- G J Jenkins
- J J Ephraums
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