Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review
Tóm tắt
The response to warming of tropical low-level clouds including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming, one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m−2 K−1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.
Từ khóa
Tài liệu tham khảo
Andrews T, Gregory JM, Webb MJ (2015) The dependence of radiative forcing and feedback on evolving patterns of sea surface temperature change in climate models. J Clim 28:1630–1648. doi:10.1175/JCLI-D-14-00545.1
Bellomo K, Clement A, Mauritsen T, Radel G, Stevens B (2014) Simulating the role of subtropical stratocumulus clouds in driving Pacific climate variability. J Clim 27:5119–5131. doi:10.1175/JCLI-D-13-00548.1
Bellomo K, Clement A, Mauritsen T, Radel G, Stevens B (2015) The influence of cloud feedbacks on Equatorial Atlantic variability. J Clim 28:2725–2744. doi:10.1175/JCLI-D-14-00495.1
Blossey PN et al (2013) Marine low cloud sensitivity to an idealized climate change: the CGILS LES intercomparison. J Adv Model Earth Syst. doi:10.1002/jame.20025
Bony S, Dufresne J-L (2005) Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys Res Lett 32:L20806. doi:10.1029/2005GL023851
Bony S, Stevens B, Ament F, Bigorre S, Chazette P, Crewell S, Delanoe J, Emanuel K, Farrell D, Flamant C, Gross S, Hirsch L, Karstensen J, Mayer B, Nuijens L, Ruppert Jr. JH, Sandu I, Siebesma P, Speich S, Szczap F, Totems J, Vogel R, Wendisch M, Wirth M (2017) EUREC4A: a field campaign to elucidate the couplings between clouds, convection and circulation. Surv Geophys. doi:10.1007/s10712-017-9428-0
Boucher O et al (2013) Clouds and aerosols. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University, Cambridge, pp 571–657
Bretherton CS (1993) Understanding Albrecht’s model of trade cumulus cloud fields. J Atmos Sci 50:2264–2283
Bretherton CS (2015) Insights into low-latitude cloud feedbacks from high-resolution models. Philos Trans R Soc A. doi:10.1098/rsta.2014.0415
Bretherton CS, Blossey PN (2014) Low cloud reduction in a greenhouse-warmed climate: results from Lagrangian LES of a subtropical marine cloudiness transition. J Adv Model Earth Syst. doi:10.1002/2013MS000250
Bretherton CS, Blossey PN, Jones CR (2013) Mechanisms of marine low cloud sensitivity to idealized climate perturbations: a single-LES exploration extending the CGILS cases. J Adv Model Earth Syst 5:316–337
Brient F, Schneider T (2016) Constraints on climate sensitivity from space-based measurements of low-cloud reflection. J Clim 29:5821–5834. doi:10.1175/JCLI-D-15-00897.1
Brient F, Schneider T, Tan Z, Bony S, Qu X, Hall A (2016) Shallowness of tropical low clouds as a predictor of climate models’ response to warming. Clim Dyn 47:433–449. doi:10.1007/s00382-015-2846-0
Brueck M, Nuijens L, Stevens B (2015) On the seasonal and synoptic time-scale variability of the North Atlantic trade wind region and its low-level clouds. J Atmos Sci 72:1428–1446
Caldwell PM, Bretherton CS (2009) Response of a subtropical stratocumulus-capped mixed layer to climate and aerosol changes. J Clim 22:20–38. doi:10.1175/2008JCLI1967.1
Caldwell PM, Zelinka MD, Taylor KE, Marvel K (2016) Quantifying the sources of intermodel spread in equilibrium climate sensitivity. J Clim 29:513–524. doi:10.1175/JCLI-D-15-00352.1
Ceppi P, McCoy DT, Hartmann DL (2016) Observational evidence for a negative shortwave cloud feedback in middle to high latitudes. Geophys Res Lett 43:1331–1339. doi:10.1002/2015GL067499
Chepfer H, Bony S, Winker D, Cesana G, Dufresne J, Minnis P, Stubenrauch C, Zeng S (2010) The GCM-oriented CALIPSO cloud product (CALIPSO-GOCCP). J Geophys 115:D00H16. doi:10.1029/2009JD012251
Christensen MW, Carri GG, Stephens GL, Cotton WR (2013) Radiative impacts of free-tropospheric clouds on the properties of marine stratocumulus. J Atmos Sci 70:3102–3118. doi:10.1175/JAS-D-12-0287.1
Deser C, Alexander MA, Xie S-P, Phillips AS (2010) 2010: sea surface temperature variability: patterns and mechanisms. Ann Rev Mar Sci 2:115–143. doi:10.1146/annurev-marine-120408-151453
De Szoeke SP, Verlinden KL, Yuter SE, Mechem DB (2016) The time scales of variability of marine low clouds. J Clim 29:6463–6481. doi:10.1175/JCLI-D-15-0460.1
Dufresne J-L, Bony S (2008) An assessment of the primary sources of spread of global warming estimates from coupled atmosphere–ocean models. J Clim 21:5135–5144. doi:10.1175/2008JCLI2239.1
Foster MJ, Heidinger A (2013) PATMOS-x: results from a diurnally corrected 30-yr satellite cloud climatology. J Clim 26:414–425. doi:10.1175/JCLI-D-11-00666.1
George RC, Wood R (2010) Subseasonal variability of low cloud properties over the southeast Pacific Ocean. Atmos Chem Phys 10:4047–4063. doi:10.5194/acp-10-4047-2010
Gordon ND, Klein SA (2014) Low-cloud optical depth feedback in climate models. J Geophys Res Atmos 119:6052–6065
Gregory JM, Andrews T (2016) Variation in climate sensitivity and feedback parameters during the historical period. Geophys Res Lett 43:3911–3920. doi:10.1002/2016GL068406
Gregory JM, Webb M (2008) Tropospheric adjustment induces a cloud component in CO2 forcing. J Clim 21:58–71. doi:10.1175/2007JCLI1834.1
Grise KM, Medeiros B (2017) Understanding the varied influence of mid-latitude jet position on clouds and cloud radiative effects in observations and global climate models. J Clim. doi:10.1175/JCLI-D-16-00295.1 (in press)
Hakuba MZ, Folini D, Wild M (2016) On the zonal near-constancy of fractional solar absorption in the atmosphere. J Clim 29:3423–3440. doi:10.1175/JCLI-D-15-0277.1
Klein SA, Hall A (2015) Emergent constraints for cloud feedbacks. Curr Clim Change Rep 1:276–287. doi:10.1007/s40641-015-0027-1
Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Clim 6:1587–1606. doi:10.1175/1520-0442(1993)006,1587:TSCOLS.2.0.CO;2
Klein SA, Hartmann DL, Norris JR (1995) On the relationships among low-cloud structure, sea surface temperature, and atmospheric circulation in the summertime Northeast Pacific. J Clim 8:1140–1155
Klein SA (1997) Synoptic variability of low-cloud properties and meteorological parameters in the subtropical trade wind boundary layer. J Clim 10:2018–2039. doi:10.1175/1520-0442(1997)010<2018:SVOLCP>2.0.CO;2
Loeb N, Wielicki B, Doelling D, Smith G, Keyes D, Kato S, Manalo-Smith N, Wong T (2009) Toward optimal closure of the Earth’s top-of-atmosphere radiation budget. J Clim 22:748–766. doi:10.1175/2008JCLI2637.1
Mace GG, Zhang Q, Vaughan M, Marchand R, Stephens G, Trepte C, Winker D (2009) A description of hydrometeor layer occurrence statistics derived from the first year of merged Cloudsat and CALIPSO data. J Geophys Res 114:D00A26. doi:10.1029/2007JD009755
Maddux BC, Ackerman SA, Platnick S (2010) Viewing geometry dependencies in MODIS cloud products. J Atmos Ocean Technol 27:1519–1528. doi:10.1175/2010JTECHA1432.1
Marchand R, Ackerman TP (2010) An analysis of cloud cover in multiscale modeling framework global climate model simulations using 4 and 1 km horizontal grids. J Geophys Res 115:D16207. doi:10.1029/2009JD013423
Mauger GS, Norris JR (2010) Assessing the impact of meteorological history on subtropical cloud fraction. J Clim 23:2926–2940. doi:10.1175/2010JCLI3272.1
McCoy DT, Eastman R, Hartmann DL, Wood R (2017) The change in low-cloud cover in a warmed climate inferred from AIRS, MODIS, and ECMWF-interim analyses. J Clim. doi:10.1175/JCLI-D-15-0734.1 (in press)
Myers TA, Norris JR (2013) Observational evidence that enhanced subsidence reduces subtropical marine boundary layer cloudiness. J Clim 26:7507–7524. doi:10.1175/JCLI-D-12-00736.1
Myers TA, Norris JR (2016) Reducing the uncertainty in subtropical cloud feedback. Geophys Res Lett 43:2144–2148. doi:10.1002/2015GL067416
Norris JR, Evan AT (2015) Empirical removal of artifacts from the ISCCP and PATMOS-x satellite cloud records. J Atmos Ocean Technol 32:691–702. doi:10.1175/JTECH-D-14-00058.1
Norris JR, Iacobellis SF (2005) North Pacific cloud feedbacks inferred from synoptic-scale dynamic and thermodynamic relationships. J Clim 18:4862–4878. doi:10.1175/JCLI3558.1
Nuijens L, Medeiros B, Sandu I, Ahlgrimm M (2015) Observed and modeled patterns of covariability between low-level cloudiness and the structure of the trade-wind layer. J Adv Model Earth Syst 7:1741–1764. doi:10.1002/2015MS000483
Pincus R, Platnick S, Ackerman SA, Hemler RS, Hofmann RJP (2012) Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators. J Clim 25:4699–4720. doi:10.1175/JCLI-D-11-00267.1
Pincus et al (this issue) The distribution of water vapor over low-latitude oceans: current best estimates, errors, and impacts. Surv Geophy (in press)
Platnick S, King MD, Ackerman SA, Menzel WP, Baum BA, Riedi JC, Frey RA (2003) The MODIS cloud products: algorithms and examples from Terra. IEEE Trans Geosci Remote Sens 41:459–473. doi:10.1109/TGRS.2002.808301
Qu X, Hall A, Klein SA, Caldwell PM (2014) On the spread of changes in marine low cloud cover in climate model simulations of the 21st century. Clim Dyn 42:2603–2626. doi:10.1007/s00382-013-1945-z
Qu X, Hall A, Klein SA, Caldwell PM (2015a) The strength of the tropical inversion and its response to climate change in 18 CMIP5 models. Clim Dyn 45:375–396. doi:10.1007/s00382-014-2441-9
Qu X, Hall A, Klein SA, DeAngelis AM (2015b) Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors. Geophys Res Lett 42:7767–7775. doi:10.1002/2015GL065627
Rieck M, Nuijens L, Stevens B (2012) Marine boundary layer cloud feedbacks in a constant relative humidity atmosphere. J Atmos Sci 69:2538–2550
Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Am Meteorol Soc 80:2261–2287
Rugenstein MAA et al (2016) Multiannual ocean-atmosphere adjustments to radiative forcing. J Clim 29:5643–5659. doi:10.1175/JCLI-D-16-0312.1
Schubert WH, Wakefield JS, Steiner EJ, Cox SK (1979) Marine stratocumulus convection. Part II: horizontally inhomogeneous solutions. J Atmos Sci 36:1308–1324
Seethala C, Norris JR, Myers TA (2015) How has subtropical stratocumulus and associated meteorology changed since the 1980s? J Clim 28:8396–8410. doi:10.1175/JCLI-D-15-0120.1
Shea DJ, Trenberth KE, Reynolds RW (1992) A global monthly sea surface temperature climatology. J Clim 5:987–1001
Sherwood SC, Bony S, DuFresne J-L (2014) Spread in model climate sensitivity traced to atmospheric convective mixing. Nature 505:37–42. doi:10.1038/nature12829
Sherwood SC et al (2015) Adjustments in the forcing-feedback framework for understanding climate change. Bull Am Meteorol Soc 96:228–277. doi:10.1175/BAMS-D-13-00167.1
Stevens B, Brenguier J-L (2009) Cloud-controlling factors: low clouds. In: Heintzenberg J, Charlson R (eds) Clouds in the perturbed climate system. MIT Press, Cambridge, pp 173–196
Stocker TF et al (2013) Technical summary. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University, Cambridge, pp 33–115
Terai CR, Klein SA, Zelinka MD (2016) Constraining the low-cloud optical depth feedback at middle and high latitudes using satellite observations. J Geophys Res Atmos 121:9696–9716. doi:10.1002/2016JD025233
van der Dussen JJ, de Roode SR, Gesso SD, Siebesma AP (2015) An LES model study of the influence of the free tropospheric thermodynamic conditions on the stratocumulus response to a climate perturbation. J Adv Model Earth Syst 7:670–691. doi:10.1002/2014MS000380
Vial J, Bony S, Stevens B, Vogel R (2017) Mechanisms and model diversity of trade-wind shallow cumulus cloud feedbacks: a review. Surv Geophys. doi:10.1007/s10712-017-9418-2
Vogel R, Nuijens L, Stevens B (2016) The role of precipitation and spatial organization in the response to trade-wind clouds to warming. J Adv Model Earth Syst 8:843–862. doi:10.1002/2015MS000568
Webb M, Lambert FH, Gregory JM (2013) Origins of difference in climate sensitivity, forcing, and feedback in climate models. Clim Dyn 40:677–707. doi:10.1007/s00382-012-1336-x
Wood R, Bretherton CS (2006) On the relationship between stratiform low cloud cover and lower-tropospheric stability. J Clim 19:6425–6432. doi:10.1175/JCLI3988.1
Zelinka MD, Klein SA, Hartmann DL (2012) Computing and partitioning cloud feedbacks using cloud property histograms. Part II: attribution to the nature of cloud changes. J Clim 25:3736–3754
Zelinka MD, Zhou C, Klein SA (2016) Insights from a refined decomposition of cloud feedbacks. Geophys Res Lett 43:9249–9259. doi:10.1002/2016GL069917
Zhai C, Jiang JH, Su H (2015) Long-term cloud change imprinted in seasonal cloud variation: more evidence of high climate sensitivity. Geophys Res Lett 42:8729–8737. doi:10.1002/2015GL065911
Zhang Y, Rossow WB, Lacis AA, Oinas V, Mishchenko MI (2004) Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: refinements of the radiative transfer model and the input data. J Geophys Res 109:D19105. doi:10.1029/2003JD004457
Zhang M, Bretherton CS, Blossey PN, Bony S, Brient F, Golaz J-C (2012) The CGILS experimental design to investigate low cloud feedbacks in general circulation models by using single-column and large-eddy simulation models. J Adv Model Earth Syst 4:M12001. doi:10.1029/2012MS000182
Zhang M et al (2013) CGILS: results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models. J Adv Model Earth Syst. doi:10.1002/2013MS000246