Water Vapor and Cloud Feedbacks

Water Vapor and Cloud FeedbacksDennis L. Hartmannin collaboration with Mark Zelinka

Department of Atmospheric SciencesUniversity of Washington

PCC Summer Institute 2010Basic Greenhouse EffectThe atmosphere is translucent to solar radiation.Because water vapor, other greenhouse gases and clouds are opaque to Earths thermal emission,And because the temperature decreases with altitude,The emission from Earth comes from the atmosphere about 5km up, where it is about 30C colder than the surface of Earth.Greenhouse EffectBB Curve minus OLR

10 mm20 mm5 mm50 mmHarries, QJ, 1996Surface30kmGreenhouseEffect3We begin by taking a look at the basic greenhouse effect.

Greenhouse Effect = Surface Emission - Outgoing Energy=390 Wm-2- 235 Wm-2155 Wm-2UW Atmospheric Sciences4If we go back to our energy budget diagram for the earth, we can define a quantitiative measure of the strength of the greenhouse effect that we can actually observe. We will define it to be the difference between the energy emitted by the surface, which we can compute if we know the Temperature, such as the SST. WE can also observe the energy flux leaving the planet from polar orbiting satellites. From this diagram we see that the global average value should be about 155Wm-2. The most important greenhouse gas is water vapor.

UW Atmospheric Sciences

W m-25Lets next look at a global map of the greenhouse effecdt as weve defined it. Here we are looking at the Earth in a Hammer equal-area projection. In such a projection each area of the Earth looks its actual size relative to the other parts of the globe, although the shape is egglike, rather than spherical. Yyou can see that the greenhouse effect is much bigger where the earth is warmer, and this is mostly because where the atmosphere is warmer, it holds more water vapor, the most important greenhouse gas. The next diagram shows the Sea Surface Temperature in the same projection. If we jump back and forth we can see the close relationship between the strength of the greenhouse effect and the surface temperature. IF we increased the surface temperature every where, we would expect that the4 water vapor would and consequently the greenhouse effect would also increase everywhere.Water Vapor FeedbackSaturation water vapor pressure increases about 7% for every 1K increase in temperatureSo if relative humidity is relatively constantThe greenhouse effect of water vapor increases with temperatureGiving strong water vapor FEEDBACK.Emission Temperature Lapse Rate and water Vapor

Fixed Absolute HumidityFixed Relative HumidityEmissionTemperatureRunaway GreenhouseWater Vapor FeedbackSince Manabe and Wetherald (1967) it has been estimated that fixed relative humidity is a good approximation and vapor feedback roughly doubles the sensitivity of climate.Because water vapor is so strongly positive and interacts with other feedbacks, small deviations from the fixed relative humidity behavior would be significant and are worth studying.Manabe & Wetherald 1967

300-600 ppm Fixed Clouds ClearFixed Absolute Humidity DT = 1.33K DT = 1.36KFixed Relative Humidity DT = 2.36K DT = 2.92KLapse Rate FeedbackThe Greenhouse effect depends on the lapse rate of temperature.If the lapse rate decreases with global warming, that is a negative feedback, since the difference in surface temperature and emission temperature will decrease, all else being equal.But all else is not equal, Water vapor feedback tends to lessen the importance of lapse rate feedback. See Cess, Tellus, 1975, page 193.

When relative humidity is fixed, so that absolute humidity is a function of temperature, lapse rate and relative humidity feedbacks on OLR tend to cancel.Since water vapor is the primary greenhouse gas, and depends only on temperature, emissivity is an increasing function of temperature.EmissionTemperatureWater Vapor Feedback vs Lapse Rate Feedback in AR4 modelsSlope = -1Validation for Fixed RH AssumptionSeasonal Variation Manabe and Wetherald 1967Many observational studies.Volcanic Eruption Soden et al 2002 ScienceAll the models do it fairly closely Sherwood et al 2010 JGR.El Nio La Nia Difference Zelinka 2011

ENSO Response Mark Zelinka

30S-30NENSO Response 1K Tropical Warming - Zelinka

Temperature and Humidity Response to ENSO Models(top) vs AIRS(bottom)

AIRS Data 2003-2010

AR4 Model Control Cloud FeedbackClouds have a strong impact on the radiation balance of EarthReduce OLR by about 30 Wm-2Reduce Absorbed Solar Radiation ~ 50Wm-2Net effect about -20 Wm-2

If their radiative effects change with global warming, the effect could be a very significant cloud feedback.Feedback Analysis using radiative KernelsSoden et al. 2008

Where i represents a vertical level.And x represents water vapor w, Temperature T, and surface albedo a.Cloudiness C, is too nonlinear and is done as a residual.Longwave Kernels: Temperature and HumidityAverage Cloudiness

Longwave Radiative Kernels: Surface Vs Atmospheric TemperatureSurface ContributionAtmosphere ContributionTotalFor Uniform 1K Temperature increaseZeroLongwave Radiative Kernels: Surface vs Atmospheric TemperatureSurfaceTotalHeavy Lines for modeled AR4 Temperature ChangeAtmosphereVertically Integrated FeedbackMultiply the Kernels times the changes and integrate vertically to get the change in top-of-atmosphere energy flux required by feedback processes.

Radiation Balance Change = Radiative Kernel x Change in state variableTemperature and Humidity ChangesSRES A2 Scenario AR4 Ensemble

Normalized for 1K Global Mean Surface Temperature increase Feedback = Kernel x ResponseNormalized to 1K global warming

TotalClearVertically Integrated Feedbacks TOA

Net Positive feedback near EquatorSome Consistent WigglesImplies increased poleward heat flux due to feedbacksIntegrated Feedbacks

LW and Shortwave Cloud feedbacks

Consistency of Longwave Cloud FeedbackZelinka from AR4 SRES A2Longwave Feedbacks Only

Summary of Feedback AnalysisNet positive feedback near equator comes from longwave water vapor and cloud feedbacks that seem robust.Consistent wiggle in Southern Ocean comes from shortwave cloud feedback and ocean upwelling, which provide heat sinks and cause atmosphere to increase its transport.Feedbacks and Meridional TransportIf you subtract the global mean and integrate the feedback over a polar cap, you get the change in meridional transport associated with feedback processes for each degree of global warming.If you combine this with the change in surface heat fluxes you can obtain the changes in atmospheric and oceanic heat flux. See also Dargans talk on Thursday.Feedbacks including surface fluxes

Feedbacks including surface fluxes

Warming induced Surface Flux changes: More heat from atmosphere to surface in high latitudes, especially in SH: Heat Uptake by OceanWarming induced Net flux into atmosphere from combined TOA and surface flux changes. Note net loss, and gradient in net loss are greater than for surface fluxes.

Transport ChangesAnnual Averages for AR4 Model EnsembleFeedbacksFlux FeedbacksNet O & A Flux FeedbacksIn AR4 sRES A2 Model Ensemble:Oceanic Heat fluxes decrease, but atmospheric fluxes overcompensate to increase net flux ~ 0.1 PW K-1. Cause: Atmospheric Feedbacks.Main PointsCombined Temperature, Water Vapor and Cloud longwave feedbacks give a net positive feedback in the equatorial region. In AR4 models and we think also in nature.Cloud Shortwave feedback is still uncertain, but models seem to give a consistently negative feedback in high latitudes.Atmospheric feedbacks and ocean heat uptake combine to give interesting changes in meridional heat transport in the atmosphere and ocean.

The EndRadiative Kernels: Temperature

Average CloudinessClear

Radiative Kernels: Water VaporAverage CloudinessClear

Relative humidity in ModelsSherwood et al 2010

Models vs Observed ENSOResponse of RH to Warming

Models: Sherwood et al 2010 JGRAIRS Data Tropical SST Regression: ZelinkaLongwave Radiative Kernels: Surface Vs Atmospheric TemperatureGreenhouse EffectSensitivity of OLR to Water Vapor

Harries, QJ, 199610 m20 m5 m50 m42In this case we will focus on the Pacific ITCZ region and compare the East and West Pacific ITCZ. We averaged the precipitation and the cloud properties over a small 100kmx100km subdomain of a larger region and then see how the composites compare between models and observationsManabe & Wetherald 1967

Manabe & Wetherald 1967

Longwave Radiative Kernels: Temperature Clear vs CloudyAverage CloudinessClear

Water vapor Longwave Radiative Kernels: Clear vs CloudyAverage CloudinessClear

Cloud FeedbackCloud feedback has been identified as one of the primary uncertainties in global warming projections for at least 20 years.Longwave cloud feedback seems to be more consistently modeled Shortwave cloud feedback seems to be very poorly constrained in models and uncertain in nature.

1.4 1.2 1 0.8 0.61.7

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90 53.136.923.611.5 0 11.5 23.6 36.9 53.1 906

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90 53.136.923.611.5 0 11.5 23.6 36.9 53.1 906

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90 53.136.923.611.5 0 11.5 23.6 36.9 53.1 906

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0.2 0 0.2 0.4 0.6 0.8 1 1.20.8

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90 53.136.923.611.5 0 11.5 23.6 36.9 53.1 906

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90 53.136.923.611.5 0 11.5 23.6 36.9 53.1 906

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90 53.136.923.611.5 0 11.5 23.6 36.9 53.1 906

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Sfc. Uniform +1 K, avg: 0.6Sfc. Actual Warming, avg: 0.7Atmos. Actual Warming, avg: 3.4Atmos. Uniform +1 K, avg: 2.7Sum Uniform +1 K, avg: 3.3Sum Actual Warming, avg: 4.1