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![• [1] LWCF = OLRclr - OLR = f(OLRclr – OLRcld)
• [2] ΔLWCF = Δf(OLRclr – OLRcld) + fΔOLRclr – fΔOLRcld
• If we assume that f and OLRcld can be broken into a component
from high and from low clouds:
• [3] fOLRcld = fhiOLRhicld + floOLRlocld, where flo is the fraction of area
covered by low clouds that are not covered by high clouds
• Using a cloud-weighted temperature for clouds that are between
the freezing level and the tropopause as CTT, we write
[4] OLRhicld = σCTT4
• Using f = fhi + flo, we can solve [3] for fhi:
• [5]
where OLRcld is given by [1], OLRhicld is given by [4], and we
assume OLRlocld = OLRclr
• [6] ΔLWCF = Δfhi(OLRclr– OLRhicld) – fhiΔOLRhicld – floΔOLRlocld
+ f ΔOLRclr
locld
hicld
locld
cld
hi
OLR
OLR
OLR
OLR
f
f
](https://image.slidesharecdn.com/4946486-230723190419-7f44a6ce/75/4946486-ppt-39-2048.jpg)
4946486.ppt
- 1. ”Tropical Clouds andCloud Feedback” The importance of radiative constraints Dennis L. Hartmann Department of Atmospheric Sciences University of Washington Seattle, Washington USA Workshop on Large-Scale Circulations in Moist Convecting Atmospheres October 15-16, 2009 Papers online: Google Dennis L. Hartmann
- 2. Outline • Motivation fromAR4 simulations • Radiation-Convection-Dynamics Interaction • Fixed Anvil Temperature Hypothesis (FAT) • Application of FAT to AR4 GCM Simulation Interpretation
- 3. Courtesy of B.Soden Net cloud feedback from 1%/ yr CMIP3/AR4 simulations SW and LW cloud feedback LW feedbacks positive and comparable magnitude. SW feedbacks positive/negative, and dominate total feedback.
- 4. Clouds, Convection andRadiation Atmospheric Energy Balance • Atmospheric Energy Balance is Radiative –Convective • Radiative Cooling = Latent Heating + Advection of Energy • Clear-Sky Radiative Cooling is a key parameter.
- 5. Clear-sky Radiative Coolingand Relaxation: In the tropical atmosphere, and the in the global atmosphere, radiative cooling approximately balances heating by latent heat release in convection. The global mean precipitation rate is about 1 meter per year, which equals an energy input of about 80 Watts/sq. meter, Requiring a compensating atmospheric radiative cooling of about 0.7 ˚K/day, averaged over atmosphere. for tropical climatological conditions -2.0 -1.0 Adiabatic Heating
- 6. Atmospheric Radiative Cooling Altitudevs Frequency 10 m 20 m 5 m 50 m Harries, QJRMS, 1996 Upper Troposphere Cooling from Water Rotation Lines Lower Troposphere Cooling from Water Continuum 6.7 m
- 8. The FAT Hypothesis, TheFixed Anvil Temperature Hypothesis. Tropical anvil clouds appear at a fixed temperature given by fundamental considerations of: • Clausius-Clapeyron definition of saturation vapor pressure dependence on temperature. • Dependence of emissivity of rotational lines of water vapor on vapor pressure.
- 9. ‘Cloud-Resolving’ Model 1kmhorizontal resolution Doubly periodic domain 64km x 64km box with uniform SST (28, 30, 32C) Bulk microphysics RRTM radiation model Basically a radiative-convective model in which the Clouds are explicitly resolved at 1km resolution. Run to equilibrium and average last 50 days. Testing the FAT Hypothesis with a CRM. Zhiming Kuang’s work: Updated by Bryce Harrop
- 10. Recreating Kuang &Hartmann (2007) Results Using SAM with CAM 5˚C
- 11. Radiation • Change thelevel of clear-sky convergence • Two possibilities – Remove water vapor to lower convergence level – Add more water vapor to raise convergence level • SAM model: Two different water vapor variables – Bulk microphysics – Radiation
- 12. Temperature Base Case Removal Case BaseCase Altering Water Vapor in the Radiation Code Part I qv, stratospheric Water Vapor (radiation only) Water vapor change only applied to radiation calculation!! Reduces emissivity = Less cooling = ?
- 13. Removal of WaterVapor Comparison Base Removal
- 14. Base Case Removal Case AdditionCase Base Case Removal Case Water Vapor (radiation only) Temperature Altering Water Vapor in the Radiation Code Part II qv, stratospheric Water vapor change only applied to radiation calculation!!
- 15. Addition of WaterVapor Comparison Base Addition
- 16. Radiative Control • Ifyou change SST, cloud temperature remains about the same - FAT • If you change the emissivity of the upper troposphere in the Tropics, you can change the cloud temperature and associated circulation. In radiative-convective equilibrium in a CRM
- 17. Courtesy of B.Soden Net cloud feedback from 1%/ yr CMIP3/AR4 simulations SW and LW cloud feedback LW feedbacks positive and comparable magnitude. SW feedbacks positive/negative, and dominate total feedback.
- 18. Motivation: Why isthe Longwave Cloud Feedback Robustly Positive in the AR4 GCMs? • We hypothesize that it is largely due to the fact that tropical high clouds remain at approximately the same temperature as the climate warms • The clouds become higher as the surface warms, but do so in such a way as to remain at approximately the same temperature • If high cloud emission temperature stays constant (or warms less than the surface), then this would lead to a positive cloud feedback, assuming no change in cloud fraction.
- 19. Predicting level ofabundant high cloudiness from clear-sky balance • Input to Fu-Liou code: tropical-mean profiles of temperature and humidity averaged over decades calculate net (LW+SW) radiative cooling profiles • Assume that this radiative cooling is balanced by diabatic subsidence take vertical derivative to get clear-sky UT convergence assume from mass continuity that this is balanced by convective detrainment should see clouds there Mark Zelinka’s Work
- 20. Dashed: Clouds, Solid:Convergence
- 21.
- 22. Radiative cooling Staticstability (T/θ)dθ/dp Diabatic ω Diabatic convergence 2000-2010 2070-2080 2090-2100 2000-2010 2070-2080 2090-2100 2000-2010 2070-2080 2090-2100 2000-2010 2070-2080 2090-2100
- 23. SRES A2 Ensemble-Mean SfcWarms ~3 K Upper Troposp here warms ~6 K CTT warms ~1 K
- 24. Attempting to QuantifyContribution of FAT to Longwave Cloud Feedback First calculate ΔLWCF, then use radiative kernel technique to estimate LW Cloud Feedback Very difficult because cloud properties are not saved and so cannot calculate radiative effect of clouds
- 25. Compare ΔLWCF for‘FAT’ and ‘FAP’ • FAT ΔLWCFtropics = Δfhi(OLRclr– OLRhicld) – fhiΔOLRhicld – floΔOLRlocld + fΔOLRclr • FAP ΔLWCFtropics = Δfhi(OLRclr–OLRhicld) – fhiΔOLRhicld – floΔOLRlocld + fΔOLRclr assuming that OLRhi = σCTT4 in which the CTT increases as much as the temperature at a fixed pressure level (the initial cloud-weighted pressure) • Finally, apply the cloud mask as explained in Soden et al. 2008 to convert ΔLWCF to LW cloud feedback
- 26. FAP Actual FAP minus Actual FAT Actual FATminus Actual ENSEMBLE MEAN LW CLOUD FEEDBACK
- 28. Conclusion. • One resultof this is that the detrainment layer in the Tropics tends to have a nearly fixed temperature as the climate changes, or a nearly fixed anvil cloud temperature. • Radiative Convective Equilibrium, constrained by Clausius Clapeyron and basic radiation physics, seems to be a strong constraint on the depth of the convective layer in the Tropics. • Another result of this is that climate models tend to give a relatively strong positive cloud longwave feedback. • Also, the Hadley Cell will deepen in pressure thickness with global warming.
- 30. High Cloud-weighted P UT Convergence-weighted P Red:1:1 line, with nonzero y- intercept Each x is a decadal mean
- 31. High Cloud-weighted T UT Convergence-weighted T Red:1:1 line, with nonzero y- intercept Each x is a decadal mean
- 32. Radiative cooling Staticstability (T/θ)dθ/dp Diabatic ω Diabatic convergence 2000-2010 2070-2080 2090-2100 2000-2010 2070-2080 2090-2100 2000-2010 2070-2080 2090-2100 2000-2010 2070-2080 2090-2100
- 33. Attempting to QuantifyContribution of FAT to Longwave Cloud Feedback First calculate ΔLWCF, then use radiative kernel technique to estimate LW Cloud Feedback Very difficult because cloud properties are not saved and so cannot calculate radiative effect of clouds
- 34. Decomposing the changein LWCF for cloud fraction (f) and cloud properties • If OLR = f OLRcld + (1-f)OLRclr then LWCF = OLRclr – OLR = f (OLRclr – OLRcld) • ΔLWCF = Δf (OLRclr–OLRcld) + f ΔOLRclr – fΔOLRcld
- 35. HAD CM3 ΔLWCF Actual Sum Δf(OLRclr– OLRcld) – fΔOLRcld fΔOLRclr Sum minus actual
- 36. Decomposing the changein LWCF • LWCF = OLRclr – OLR = f(OLRclr – OLRcld) • ΔLWCF = Δf(OLRclr–OLRcld) + fΔOLRclr– fΔOLRcld • This term dominates, but not because of warming or cooling high clouds, but apparently because of different abundances of high vs. low clouds (see next slide)
- 37. Dashed: 2000-2010 Solid: 2090-2100 ΔLWCF<<0due to ΔOLRcld>>0 ΔLWCF>>0 due to ΔOLRcld<<0 HAD CM3 HAD CM3
- 38. Another ΔLWCF decomposition •Let’s assume we can break OLRcld and f into contributions from high and low clouds. • We do this separation only in the Tropics • Rather than trying to pretend like we know the effective high and low cloud fractions, lets assume that the high cloud-weighted temperature is a reasonable estimate of the high cloud emission temperature and that the low cloud emission is the same as clear-sky emission. • Then we can determine what fhi and flo must be such that fOLRcld = fhiOLRhicld + floOLRlocld
- 39. • [1] LWCF= OLRclr - OLR = f(OLRclr – OLRcld) • [2] ΔLWCF = Δf(OLRclr – OLRcld) + fΔOLRclr – fΔOLRcld • If we assume that f and OLRcld can be broken into a component from high and from low clouds: • [3] fOLRcld = fhiOLRhicld + floOLRlocld, where flo is the fraction of area covered by low clouds that are not covered by high clouds • Using a cloud-weighted temperature for clouds that are between the freezing level and the tropopause as CTT, we write [4] OLRhicld = σCTT4 • Using f = fhi + flo, we can solve [3] for fhi: • [5] where OLRcld is given by [1], OLRhicld is given by [4], and we assume OLRlocld = OLRclr • [6] ΔLWCF = Δfhi(OLRclr– OLRhicld) – fhiΔOLRhicld – floΔOLRlocld + f ΔOLRclr locld hicld locld cld hi OLR OLR OLR OLR f f
- 40. So the formulasare…. • ΔLWCFtropics = Δfhi(OLRclr– OLRhicld) – fhiΔOLRhicld – floΔOLRlocld + f ΔOLRclr • ΔLWCFextra-tropics = Δf(OLRclr–OLRcld) – fΔOLRcld + fΔOLRclr
- 41. Predictions from Clear-Sky RadiativeCooling • In the Tropics we should see two or three levels of cloud. – Boundary layer cloud - from strong radiative cooling of moist, warm low level air - H2O continuum – High cloud from strong cooling under tropopause by rotation bands of H2O – Middle cloud from 6.7 micron V/R band
- 42. High Middle Low Optical Depth MODIS Temperature-OpticalDepth Histogram Eastern Equatorial Pacific Ocean High-Anvil and Cirrus Clouds Middle- Congestus Low - Cumulus+ Stratocumulus Three Levels of Cloud Tropopause Kubar et al. 2007
- 43. Fundamental energy balancein atmosphere is: Convective heating = Radiative Cooling Question is, Which places a more fundamental Constraint on the climate system in the tropics? Answer: In the deep tropics radiative cooling, particularly in clear skies, may provide a more fundamental prediction of the depth of the convective layer.
- 44. First Law ofThermodynamics Using continuity in pressure coordinates In Tropics ~
- 45. Fact: 200 hPa Convectiveoutflow and associated large-scale divergence near 200 hPa are both associated with radiatively-driven divergence in clear skies. Fact: The radiatively-driven divergence in the clear regions is related to the decrease of water vapor with temperature following the Clausius-Clapeyron relation and the consequent low emissivity of water vapor at those low temperatures. Hypothesis: The temperature at which the radiatively-driven divergence occurs will always remain the same, and so will the temperature of the cloud anvil tops.
- 46.
- 47. Use Cloudsat todetect cloud tops and AMSR to estimate precipitation rate Heavy rain is 90th Percentile, 10% of frequency, but ~50% of total rainfall. Kubar & Hartmann 2008 West Pacific East Pacific
- 48. Use Cloudsat todetect cloud tops and AMSR to estimate precipitation rate Heavy rain is 90th Percentile, 10% of frequency, but ~50% of total rainfall. Kubar & Hartmann 2008
- 49. Why should convection stop/detrainat a fixed temperature? Vapor pressure depends only on temperature, and decreases exponentially as T decreases with altitude. Emissivity (radiative relaxation time) depends most importantly on vapor pressure. Temperature where water vapor emissivity becomes small is only weakly dependent on relative humidity and pressure. Heating of air by condensation also becomes small at this temperature
- 50. Larson and Hartmann(2002a,b) Model Study: MM5 in doubly periodic domain a) 16x16 box with uniform SST (297, 299, 301, 303K) b) 16x160 box with sinusoidal SST Clouds and circulation are predicted Clouds interact with radiation Basically a radiative-convective model with parameterized convection, in which the large-scale circulation is allowed to play a role by dividing the domain into cloudy (rising) and clear (sinking) regions. Testing the FAT Hypothesis in a model. c) 16x16 box with uniform SST and rotation.
- 51. Radiative Cooling in non-convective regionfor SST’s ranging from 297K to 303K. From Larson & Hartmann (2002a).
- 52. The temperature atwhich the radiative cooling reaches -0.5 K/day remains constant at about 212K. The temperature at which the visible optical depth of upper cloud reaches 0.1 remains constant at about 200K. The temperature of the 200 hPa surface increases about 13K, while the surface temperature rises 6K.
- 53. Kuang &Hartmann, J.Climate 2007 CRM in Rad/Conv. Equilibrium 28˚C, 30˚C and 32˚C SST Cloud Fraction versus Air Temperature 6˚C
- 54. Cloud Fraction vs AirTemp. vs Pressure
- 55. Stratospheric Transport andExchange
- 56. 1. Apply upwardmotion of Brewer-Dobson Circulation. 28, 30, 32C 30C +BDC
- 57. Test Impact ofRadiation Same SAM framework as Kuang & Hartmann • Alter the water vapor that the radiation code sees to change the emissivity of the upper tropical troposphere. • Expect that increasing upper tropospheric radiative cooling vapor will cool the average cloud tops, and vice versa. Bryce Harrop’s work
- 58. Divergence Calculations Subsidence warming= radiative cooling
- 59. Comparing CAM andRRTM Radiation Codes
- 60. Comparing CAM andRRTM Radiation Codes Continued
- 61. Convergence computed from clear-skyradiative cooling, and Cloud fraction from MODIS plotted versus air temperature (solid) for West Pacific (WP) and East Pacific (EP) 221K 217K Good agreement between clear-sky divergence and cloud fraction. Kubar et al. 2007
- 62. Kubar et al(2007) MODIS Anvil Top vs Convergence Temperature Kubar et al. 2007
- 63. Radiation Code Adjustments:Comparing Weighted Temperatures this study
- 64. Moist Thermodynamics • Doublethe Latent Heat of Fusion • Two Possibilities: – Lift the parcel – Warm the parcel
- 65. Doubling Latent Heatof Fusion Comparison
- 66. Radiation and LfAdjustments: Comparing Tconv and Tcld 2x Lf 2x Lf
- 67. Conclusions • When theradiation is changed, the cloud profile adjusts so that the cloud amount peaks near the level of clear-sky convergence. • A relationship exists between convergence weighted and cloud weighted temperatures.
- 68. AR4 Climate Simulations RobustLongwave Cloud Feedback • All AR4 models produce a similar positive longwave cloud feedback, compared to the large variability in shortwave cloud forcing. • Can basic constraints like saturation vapor pressure and radiative cooling explain this consistency in the models? Mark Zelinka’s work
- 69. Is any ofthis believable? • It is likely that some portion of Δfhi is actually including information about changes in the emission temperature of high clouds as well. • Because we enforce any error in our estimate of OLRhicld or OLRlocld will be subsumed into fhi (and by extension flo) • This could result in the ΔLWCF term due to Δfhi being overestimated and the ΔLWCF term due to ΔOLRhicld being underestimated • Would like a good method of assessing sensitivity to our assumptions locld hicld locld cld hi OLR OLR OLR OLR f f
- 70. Δfhi(OLRclr – OLRhicld) –fhiΔOLRhicld f ΔOLRclr – floΔOLRlocld Δfextra-tropical(OLRclr – OLRcld) – fextra-tropicalΔOLRcld ENSEMBLE MEAN ΔLWCF
- 71. Tropical-Mean Results • Varyingdegrees of agreement between UT convergence and level of high cloud abundance in models • In all models, both convergence- and cloud-weighted pressure (temperature) decrease (VERY slightly increase) in a nearly 1:1 fashion, but with a nonzero y-intercept (see previous point) • Tropical mean UT convergence and high cloud amount decrease slightly over the course of the 21st century (enhanced static stability out-pacing enhanced radiative cooling – see previous slide) – Can this explain Trenberth and Fasullo’s results about decreases in cloudiness allowing for more absorbed shortwave (next slide)? – Also, if high cloud coverage strongly impacts absorbed shortwave, and static stability vs. radiative cooling determines high cloud coverage, then this implies some dependency of SW cloud feedback on lapse rate feedback (at least in the tropics) • Those models with larger (negative) lapse rate feedback should tend to have larger positive (or less negative) SW cloud feedback due to this effect because strong increases in static stability will cause strong decreases in high cloud cover (I guess it depends on the importance of high clouds changes for SW cloud feedback)
- 73. Issues (1 of2) • Clouds plotted in previous figures are total cloud fraction in each pressure bin reported by the model: There is no information about cloud optical properties, nor does it provide information about cloud tops, which are emitting to space. • Can look at ISCCP simulator output from models that have participated in CFMIP, but – there are no CO2 scenarios, just 2XCO2 runs with slab oceans – The ISCCP pressure bin resolution is inadequately poor (7 vertical bins) • Have done simulations with the GFDL model in aquaplanet mode at .5x, 1x, 2x, and 4x CO2 using the ISCCP simulator – results look similar to here, but with more dramatic warming of high clouds / UT convergence and more dramatic decrease in high cloud coverage more dramatic because of factor of 8 variation in CO2? • To what degree should model clouds be collocated with the UT diabatic convergence? Probably depends on details of each model’s convective parameterization (detrainment based on neutral buoyancy?). Very thin stuff near tropopause probably unrelated to detrainment – but we don’t know how much of that type of cloud is represented in these profiles • Still need to show that the prevailing thought that detrainment occurs once the parcels reach neutral buoyancy is either incorrect or is consistent with this – if
- 74. Issues (2 of2) • Probably should be running the Fu-Liou code for each lat, lon, & season rather than just for tropical-mean annual-mean profiles currently working with Marc to run Fu Liou code more efficiently than I have been (currently have a Matlab script that calls the fortran code) • Very difficult to be quantitative: can only say that – in all the models – the entire cloud profile rises vertically but as a function of temperature the cloud profile stays nearly constant (warms slightly). (How realistic is the cloud- weighted temperature as a proxy for CTT?) • Two issues with using tropical-mean temperature and humidity profiles as input to the Fu-Liou code – 1. mean profiles calculated from clear-only regions will likely be different (certainly drier) than those calculated from both clear and cloudy this will affect the shape and magnitude of UT convergence (need to assess sensitivity) – 2. The presence of clouds alters the radiative cooling rates substantially. This is much more difficult to take into account in the radiation code, since one needs to know more about the cloud properties than is provided in the AR4 diagnostics. It is not clear to me to what extent real-world UT detrainment is affected by clouds in the surrounding regions altering the radiative cooling rate.
- 75. Rainrates from twodifferent algorithms. TOP: Satellite-derived method, based on cloud top temperature; BOTTOM: Derived from Microwave Sounding Unit, (Figure from Berg et al. 2002)
- 76. Modeling Tropical Convection ina Box or on a Line. The first set of experiments will be from a 3D doubly- periodic model run with fixed forcing in a dx=1km 256km x 256km domain with 64 levels, also use 2D version. The dynamics are anelastic, the radiation is that of the NCAR CCM. For this study we will use the SAM model from CSU. Khairoutdinov and Randall (2003) The cloud physics scheme has conservation equations for total water and precipitating water, apportionment among types is based on temperature. Note that 3D model has 5m/s shear imposed.
- 77. 3-D Model External forcingfrom Reanalysis for EP and WP, but use same SST of 302.49K converting cloud in to precip. Top Heavy Bottom-Heavy
- 78.
- 79. Use 2-D toTest Sensitivity • Use same SAM model in 2-D version • Apply SST sinusoid to force circulation. • No external forcing other than SST and Radiation
- 80. Thin Anvil Thick Middle Low OpticalDepth MODIS Temperature-Optical Depth Histogram Eastern Equatorial Pacific Ocean High-Anvil and Cirrus Clouds Middle- Congestus Low - Clumulus+ Stratocumulus Three Levels of Cloud Tropopause Kubar et al. 2007
- 81. We will seethat, with same microphysics 2-D model has similar strengths and weaknesses as 3-D Model • Decent thick and thin cloud distributions, but • Anvil clouds (intermediate optical depths) are too few and do not have correct dependence on precipitation rate.
- 82. Validation Methodology • Averageover comparable subdomains - about 100km square sub-domains to define local precip and cloud properties. • Use precipitation rate as an independent variable. • Tests relationship of cloud stuff to precipitation rate • Works equally well for column model, regional model, global model and data. • Don’t have to adjust anything about methodology in going from 3D to 2D
- 83. Test 3-D &2-D run against Satellite Data a la Kubar et al. 2007 Thick Cloud - about right 2-D Base Lopez et al. 2007 AMSR MODIS
- 84. Test 3-D runagainst Satellite Data a la Kubar et al. 2007 Anvil Cloud Error 2-D case Lopez et al. 2007
- 85. Test 3-D runagainst Satellite Data Albedo & OLR PDFs - Domain Mean Anvil Cloud is Missing Lopez et al. 2007 Anvil Cloud Signature
- 86. Use 2-D toTest Sensitivity Summary: • We can increase ice cloud by reducing ice sedimentation, but this also increases thick cloud unrealistically. • Increasing the Autoconversion/Accretion rate reduces the thick cloud preferentially. • AA rate preferentially controls water cloud, which is responsible for thick cloud fraction. • Accretion is more important than autoconversion.
- 87. Adjustments suggested by2-D Sensitivity Tests • We need to increase ice and decrease water to get the right albedo distribution of cold cloud. • This means decreasing ice sedimentation, while increasing accretion of cloud water.
- 88. Use 2-D toTest Sensitivity Multiple Changes • NOSED - set ice sedimation velocity to zero, but lower threshold for autoconversion of ice by a factor of 100. • AALIQN - increase liquid water accretion rate by factor of N. • NOSEDAALIQ5 - NOSED, plus increase liquid water accretion by factor of 5.
- 89. Multiple Changes toCloud Physics 2D Results 2-D Base Thick Cloud Lopez et al. 2007
- 90. Multiple Changes toCloud Physics - 2D 2-D Base Anvil Cloud Lopez et al. 2007
- 91. Use 2-D toTest Sensitivity Multiple Changes • We found a set of cloud physics parameters that produces better anvil cloud amounts and maintains the observed amount of thick cloud as a function of rain rate - NOSEDAALIQ5. • Let’s put these back in the 3-D West Pacific run and see what happens.
- 92. Improvement! • Cloud Forcinglooks more reasonable. Cloud fraction climbs out of sight! But most is thin cloud, and high coverage of thin cloud may not be unreasonable for the conditions of the simulation. Lopez et al. 2007
- 93. Conclusions • Satellite datacan be used to effectively test CRM cloud simulations, and GCM’s too. • It is very effective to do the test as a function of rain rate. • Something approaching the observed behavior of convective cores, anvil clouds and thin clouds can be achieved with judicious tuning of a simple bulk scheme. • Work continues. . .
- 95. Multiple Changes toCloud Physics - 2D 2-D Base Thin Cloud Lopez et al. 2007
- 96. Test 2-D runagainst Satellite Data a la Kubar et al. 2007 Thin Cloud - Not bad 2-D case Lopez et al. 2007 3D WP 3D EP
- 97. Model Clouds tooCylindrical
- 100. General Approach • Focuson Pacific ITCZ regions • Observe and model same regions. EP &WP • Average over comparable subdomains - about 100km square subdomains to define local precip and cloud properties. • Use precipitation rate as an independent variable.
- 101. Testing the RelativeRoles of Radiation and Latent Heating in Determining the Temperature of Tropical Cloud Tops Bryce Harrop
- 102. Clouds and Radiationin the Tropics • Greatest uncertainty in clouds • Changing cloud forcing can drive changes in worldwide circulations
- 103. LWCF = Fclear- Ftotal Weak LWCF Strong LWCF COLD WAR M
- 104. SWCF = Stotal- Sclear Weak SWCF Strong SWCF
- 105. Hartmann et al(2001)
- 106. Hartmann et al(2001)
- 107. Fixed Anvil Temperature Clear-sky Convergence at 200hPa Anvil Detrainment at200hPa Temperature Dependent
- 108.
- 109. PULL vs PUSH •PULL Mechanism – Clear-sky convergence level determines height of clouds • PUSH Mechanism – Buoyancy determines height of clouds
- 110. Hartmann & Larson(2002)
- 111. Kuang & Hartmann(2007)
- 112. Xu et al(2007) L A R G E M E D I U M S M A L >300km 150-300km 100-150km
- 113. Future Work • Howdo the moist thermodynamics influence the cloud level? • Is there a relationship between Tconv and Tcld when we change the moist thermodynamics? • Can we modify the moist thermodynamics in such a way that the cloud will reach a different level than the clear-sky convergence?
- 114. Acknowledgements • Dennis Hartmann •Peter Blossey • Grads 08
- 115.
- 123. Greenhouse Effect Sensitivity ofOLR to Water Vapor 10 m 20 m 5 m 50 m Harries, QJ, 1996
- 124. Atmospheric Radiative Cooling Altitudevs Frequency 10 m 20 m 5 m 50 m Harries, QJRMS, 1996 Upper Troposphere Cooling from Water Rotation Lines Lower Troposphere Cooling from Water Continuum 6.7 micron
- 125. High Middle Low Optical Depth MODIS Temperature-OpticalDepth Histogram Eastern Equatorial Pacific Ocean High-Anvil and Cirrus Clouds Middle- Congestus Low - Cumulus+ Stratocumulus Three Levels of Cloud Tropopause Kubar et al. 2007
- 126. Rotational Lines of WaterVapor and Upper- Tropospheric Cooling Total Beyond 18.5m --> Cooling efficiency of atmosphere declines in upper troposphere because of lack of water vapor to emit and absorb radiation.
- 127. Recreating Kuang &Hartmann (2007) Results Using SAM with CAM
- 128. Dr. Kuan-Man Xu NASALangley Research Center Kuan-Man Xu, Personal Communication
- 129. Analysis of NewData March 2003-November 2004: Aqua. • MODIS optical depth and cloud top temperature - 5km data • AMSR rain rates and column vapor. • Collocated three-day, 1-degree, averages • MLS upper tropospheric humidity: Aura • GPS upper tropospheric temperature profiles
- 130. Regions of Interest ▪Latitudeband of 5ºN-15ºN allows focus to be almost exclusively on convective areas, even in the East Pacific Fig 1. Ensemble SSTs for March 2003-November 2004 West Pacific Central Pacific East Pacific
- 131. Cloud as afunction of rainrate R A I N R A T E WEST CENTRAL EAST Temp-Opt Depth histograms as a function of rainrate (MODIS/AMSR).
- 134. Rain Rate/Anvil CloudArea More high cloud per unit of rain in the warmer West Pacific.
- 135.
- 137. Modifying the Fixed AnvilTemperature Hypothesis • Cloud Top Temp. 218-216K ( -3C) as SST 27C-30C ( +3C) • Cloud Fraction from 20-40% • Relative humidity ~ high cloud fraction es~ -20% for T~ -3C (es =Saturation Vapor Press.) RH ~ 20%, so e ~ (RH•es) ~ 0 at median anvil level. • Can conclude anvil cloud occurs at fixed e, or fixed T if RH constant.
- 138. Relative Humidity Profiles From MLSand AIRS and reanalysis for the Western Pacific (WP) Central Pacific (CP) and Eastern Pacific (EP) MLS humidity above 316mb, Temps. from GPS.
- 140. WP EP EP with WPhumidity
- 141. Fixed Anvil TemperatureHypothesis • Cloud Top Temp. 218-216K ( -3C) as SST 27C-30C ( +3C) • Cloud Fraction from 20-40% • Relative humidity ~ high cloud fraction es~ -20% for T~ -3C (es =Saturation Vapor Press.) RH ~ 20%, so e ~ (RH•es) ~ 0 at median anvil level. • Can conclude anvil cloud occurs at fixed e, or fixed T if RH constant.
- 142. Conclusions: The favored temperaturefor tropical anvil cloud tops should remain approximately constant during climate changes of reasonable magnitude. FAT Hypothesis. The emission temperature of the rotational lines of water vapor should also remain approximately constant during climate change. These assertions imply relatively strong water vapor and IR cloud feedback, all else being equal. Hartmann and Larson, GRL, 2002.
- 143. Some Remaining Questions: Willthe area occupied by tropical convection change with climate? If so, how? How do tropical convective clouds interact with other cloud types like marine boundary layer clouds? How do tropical cloud albedos respond to climate change? What will happen at the tropical tropopause? Will it get warmer or colder and what will this mean for climate? Fin Global models should be able to get FAT right, but do they?
- 145. Greenhouse Effect BB Curveminus OLR 10 m 20 m 5 m 50 m Harries, QJ, 1996