All Publications

Below is the combined list of references from refs_sat.bib and refs_external.bib. It is intended for our group's internal use.

| 2c-ice | a-train | abs lookup | absorption | active | aerosol | aerosols | age of air | aggregation | airs | albedo | algorithm | amsos | amsu | annual cycle | anomalies | aqua | ar4 | ar5 | arctic | arm | arts | arts-dev | asr | assimilation | astronomy | astrophysics | asymmetry | atmosphere | atmospheric composition | atmospheric dynamics | atmospheric profiles | atsr-2 | avhrr | bachelor thesis | backscattering | basics | bayes | bias | biomass | book | calculation | calculations | calibration | calipso | ccn | cdr | ceres | cfmip | chemistry | cia | ciraclim | cirrus | cirrus anvil sublimation | cirrus cloud | cirrus clouds | cirrusstudy | ciwsir/cloudice | claus | cliccs | climate | climate change | climate dynamics | climate feedbacks | climate sensitivity | climate sensivity | climate variability | climatology | cloud feedback | cloud forcing | cloud fraction | cloud ice | cloud ice mission | cloud optical thickness | cloud properties | cloud radiative effects | cloud radiative forcing | cloud regimes | cloud top pressure | cloudice mission | clouds | cloudsat | clustering | cmip3 | cmip5 | cmip6 | cmsaf | co2 | collocation | collocations | comparison | computer science | continua | contrail | convection | convective clouds | convective processes | convective self-aggregation | correlated k | cosmic background | cosmic rays | cosp | cost 723 qjrms | cross-calibration | cth | cumulus | dardar | data assimilation | data bases | dda | deep convection | delta m | dimer | disort | diurnal cycle | dlr-smiles | dmsp | documentation | doppler | droplet size | dynamics | earth | earthcare | ec earth | echam | ecmwf | effective radius | electromagnetism | electron content | elevation | elevation satellite-2 | emd | emde | emissivity | enso | eof-pca-svd | erbe | error assessment | ers | eruption | esa planetary | exoplanets | extraterrestrial | fall speed | far-infrared | faraday-voigt | fcdr | feedback | feedbacks | fingerprinting | flux uav | forcing | forest fire | fox19_airborne_amt.pdf | friend | fun | fuzzy inference system | fuzzy logic | gcm | genesis | geostationary | gerrit_erca | global warming | gnss | goes | gps | gras | graupel | gravitational lensing | greenhouse effect | ground-based | groundbased | habil | hadley circulation | hail | hamburg | heating rate | heating rates | herschel | hiatus | hirs | history | hsb | humidity | hydrological sensitivity | hydrological sensivity | hydrometeors | iasi | ice | ice clouds | ice crystal growth | ice nucleation | ice water | icesat-2 | ici | icon | icz | in situ | infrared | infrared sounder | instruments | inter-calibration | intercalibration | intercomparison | interference | inverse modelling | ipcc | ir | ir/vis | iris | isccp | ismar | isotopes | itcz | iwc | iwp | iwv | john | jupiter | kalpana | kessler scheme | lblrtm | licentiate thesis | lidar | limb effect | limb sounding | limb-correction | linemixing | lineshape | liquid water | liquid water path | longwave radiation | low-cloud feedback | magnetic field | magnetism | mars | mas | mass-dimension relation | master thesis | masters thesis | math | megha-tropiques | mendrok | mesoscale organization | meteorology | meteosat | methane ocean | metop | mhs | microphysics | microwave | microwave humidity | microwave radiometry | milz | mipas | mirs | misr | mixed phase | mls | model | modeling | models | modis | monte carlo | moon | mspps | msu | mth | multi-moment scheme | multisensor | mwhs | mwi | net radiation | neural network | nicam | nlte | noaa | nonsphericity | npoess | observation | ocean | ocean reflection | ocean-atmosphere interactions | odin | olr | one-moment scheme | open loop | optical | optical depth | optical properties | optics | orbital drift | orbital drift correction | orbits | ozone | pacific ocean | particle orientation | particle shape | particle size | particle size distribution | passive | patmos-x | phase function | phd thesis | planetary evolution | polarimetry | polarization | polder | potss | precipitation | profile datasets | programming | projection | promet | propagation modeling | python | radar | radiation | radiation profiles | radiative convective equilibrium | radiative equilibrium | radiative feedback | radiative fluxes | radiative forcing | radiative processes | radiative transfer | radiative-convective equilibrium | radiative-equilibrium | radio occultation | radiometer | radiometers | radiosonde | radiosonde cloud liquid | radiosonde correction | radiosonde corrections | rain | reanalysis | refractive index | relative humidity | remote sensing | retrieval | retrievals | review | rodgers | rttov | sahara | sahel | sampling | sand/dust | sar | satellite | satellite missions | satellite observations | satellite simulator | sbuehler_habil | scattering | scattering databases | scintillations | scout-amma | self-aggregation | sensor geometry | seviri | shallow convection | simulated annealing | single scattering | smiles | sno | snow | snowfall | software | soil | solar | soot | sounders | spectral information | spectroscopy | split window technique | sreerekha | ssm/i | ssm/t | ssmis | ssmt2 | stability | stars | statistics | ste | stereo | stratosphere | submillimeter | submm | sun | supersaturation | surface | synergies | synergy | task2 | tempera | temperature | terra | thermodynamics | time series | titan | tkuhn | toa radiation | top of the atmosphere | total column | tovs | trade-wind clouds | trajectory analysis | trend | trmm | tropical circulation | tropical convection | tropical meteorology | tropics | tropopause | troposphere | ttl | turbulence | tutorial | two-moment scheme | upper troposphere | uth | uthmos | utls | validation | vater vapor | venus | visualization | volcanic ash | walker | walker circulation | walker rirculation | water | water cycle | water dimer | water vapor | water vapor continuum | water vapour | water vapour path | water-vapour | wind | zeeman |

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Group references

In the Pipeline

    Articles

      2016 Back to top

    1. Kottayil, A., V. O. John, S. A. Buehler, and K. Mohanakumar (2016), Evaluating the diurnal cycle of upper tropospheric humidity in two different climate models using satellite observations, Rem. Sens., 8(4), 325, doi:10.3390/rs8040325.

    Books and Book Contributions

      Theses

        2013 Back to top

      1. Kottayil, A. (2013), Representation and Diurnal Variation of Upper Tropospheric Humidity in Observations and Models, Ph.D. thesis, Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering Division of Space Technology.

      Technical Reports and Proposals

        Articles in Conference Proceedings and Newsletters

          Internal Reports

            External references

            1. Anderson, G. P., F. X. Keizys, J. H. Chetwynd, J. Wang, M. L. Hoke, L. S. Rothman, L. M. Kimball, R. A. McClatchey, E. P. Shettle, S. A. Clough, W. O. Gallery, L. W. Abreu, and J. E. A. Selby (1995), FASCODE/MODTRAN/LOWTRAN: Past/Present/Future, , 18th Annual Review Conference on Atmospheric Transmission Models.
            2. Baran, A. J., P. J. Connolly, and C. Lee (2009), Testing an ensemble model of cirrus ice crystals using midlatitude in situ estimates of Ice water content, volume extinction coefficient and the total solar optical depth, J. Quant. Spectrosc. Radiat. Transfer, 110, 1579–1598, doi:10.1016/j.jqsrt.2009.02.021.
            3. Bauer, P., A. J. Geer, P. Lopez, and D. Salmond (2010), Direct 4D-Var assimilation of all-sky radiances. Part I: Implementation, Q. J. R. Meteorol. Soc., 136(652), 1868–1885, doi:10.1002/qj.659.
            4. Bennhold, F. and S. Sherwood (2008), Erroneous Relationships among Humidity and Cloud Forcing Variables in Three Global Climate Models, J. Climate, 21, 4190–4206, doi:10.1175/2008JCLI1969.1.
            5. Berk, A., G. P. Anderson, P. K. Acharya, L. S. Bernstein, L. Muratov, J. Lee, M. Fox, S. M. Adler-Golden, J. H. Chetwynd, M. L. Hoke, R. B. Lockwood, J. A. Gardner, T. W. Cooley, C. C. Borel, and P. E. Lewis (2005), MODTRAN 5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options: update, In: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, pp. 662–667, Edited by Shen, S. S. and P. E. Lewis, SPIE, doi:10.1117/12.606026.
            6. Brands, S., S. Herrera, J. Fernández, and J. M. Gutiérrez (2013), How well do CMIP5 Earth System Models simulate present climate conditions in Europe and Africa?, Climate Dynamics, 41(3–4), 803–817, doi:10.1007/s00382-013-1742-8.
            7. Bugliaro, L., T. Zinner, C. Keil, B. Mayer, R. Hollmann, M. Reuter, and W. Thomas (2011), Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI, Atmos. Chem. Phys., 11, 5603–5624, doi:10.5194/acp-11-5603-2011.
            8. Cavazos, T. and B. C. Hewitson (2005), Performance of NCEP–NCAR reanalysis variables in statistical downscaling of daily precipitation, Climate Research, 28(2), 95–107, doi:10.3354/cr028095.
            9. Chen, C.-T. and E. Roeckner (1996), A Comparison of Satellite Observations and Model Simulations of Column-Integrated Moisture and Upper-Tropospheric Humidity, J. Climate, 9, 1561–1584.
            10. Clough, S. A., M. W. Shephard, E. J. Mlawer, J. S. Delamere, M. Iacono, K. Cady-Pereira, S. Boukabara, and P. D. Brown (2005), Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Radiat. Transfer, 91(2), 233–244, doi:10.1016/j.jqsrt.2004.05.058.
            11. Colman, R. (2003), A comparison of climate feedbacks in general circulation models, Climate Dynamics, 20, 865–873.
            12. Dai, A. and K. E. Trenberth (2004), The Diurnal Cycle and Its Depiction in the Community Climate System Model, J. Climate, 17, 930–951.
            13. Dessler, A. E. and S. M. Davis (2010), Trends in tropospheric humidity from reanalysis systems, J. Geophys. Res., 115, D19127, doi:10.1029/2010JD014192.
            14. Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor (2016), Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9(5), 1937–1958, doi:10.5194/gmd-9-1937-2016.
            15. Feltens, J., M. Angling, N. Jackson-Booth, N. Jakowski, M. Hoque, M. Hernández-Pajares, A. Aragón-Àngel, R. Orús, and R. Zandbergen (2011), Comparative testing of four ionospheric models driven with GPS measurements, Radio Sci., 46, RS0D12, doi:10.1029/2010RS004584.
            16. Fläschner, D. (2016), Intermodel spread in global tropical precipitation changes, Ph.D. thesis, University of Hamburg.
            17. Fläschner, D., T. Mauritsen, and B. Stevens (2016), Understanding the Intermodel Spread in Global-Mean Hydrological Sensitivity, J. Climate, 29, 801–817, doi:10.1175/JCLI-D-15-0351.1.
            18. Forget, F., F. Hourdin, R. Foumier, C. Hourdin, and O. Talagran (1999), Improved general circulation models of the Martian atmosphere from the surface to above 80 km, J. Geophys. Res., 104, 155–175.
            19. Fu, Q. (1996), An Accurate Parameterization of the Solar Radiative Properties of Cirrus for Climate Models, J. Climate, 9(9), 2058–2082, doi:10.1175/1520-0442(1996)009<2058:AAPOTS>2.0.CO;2.
            20. Fu, Q., P. Yang, and W. B. Sun (1998), An Accurate Parameterization of the Infrared Radiative Properties of Cirrus Clouds for Climate Models, J. Climate, 11, 2223–2237, doi:10.1175/1520-0442(1998)011<2223:AAPOTI>2.0.CO;2.
            21. Giorgetta, M. and M. Wild (1995), The Water Vapour Continuum and its Representation in ECHAM4, Max-Planck-Institut fuer Meteorologie.
            22. Han, Y., P. van Delst, and F. Weng (2010), An improved fast radiative transfer model for special sensor microwave imager/sounder upper atmosphere sounding channels, J. Geophys. Res., 115, D15109, doi:10.1029/2010JD013878.
            23. Heymsfield, A. J. and L. J. Donner (1990), A scheme for parameterizing ice cloud water content in general circulation models, J. Atmos. Sci., 47, 1865–1877.
            24. Illingworth, A. J., R. J. Hogan, E. J. O'Connor, D. Bouniol, J. Delanoë, J. Pelon, A. Protat, M. E. Brooks, N. Gaussiat, D. R. Wilson, D. P. Donovan, H. Klein Baltink, G-J. van Zadelhoff, J. D. Eastment, J. W. F. Goddard, C. L. Wrench, M. Haeffelin, O. A. Krasnov, H. W. J. Russchenberg, J-M. Piriou, F. Vinit, A. Seifert, A. M. Tompkins, and U. Willén (2007), Cloudnet — Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations, Bull. Amer. Met. Soc., 88(6), 883–898, doi:10.1175/BAMS-88-6-883.
            25. Jakob, C. (2014), Going back to basics, Nature Clim. Change, 4(12), 1042–1045, doi:10.1038/nclimate2445.
            26. Jakob, C. and S. A. Klein (1999), The role of vertically varying cloud fraction in the parametrization of microphysical processes in the ECMWF model, Q. J. R. Meteorol. Soc., 125(555), 941–965, doi:10.1002/qj.49712555510.
            27. Jiang, J. H., H. Su, C. Zhai, V. S. Perun, A. Del Genio, L. S. Nazarenko, L. J. Donner, L. Horowitz, C. Seman, J. Cole, A. Gettelman, M. A. Ringer, L. Rotstayn, S. Jeffrey, T. Wu, F. Brient, J.-L. Dufresne, H. Kawai, T. Koshiro, M. Watanabe, T. S. L'Ecuyer, E. M. Volodin, T. Iversen, H. Drange, M. D. S. Mesquita, W. G. Read, J. W. Waters, B. Tian, J. Teixeira, and G. L. Stephens (2012), Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA "A-Train" satellite observations, J. Geophys. Res., 117, D14105, doi:10.1029/2011JD017237.
            28. Kang, S. M., I. M. Held, D. M. W. Frierson, and M. Zhao (2008), The Response of the ITCZ to Extratropical Thermal Forcing: Idealized Slab-Ocean Experiments with a GCM, J. Climate, 21(14), 3521–3532, doi:10.1175/2007JCLI2146.1.
            29. Kristjánsson, J. E., J. M. Edwards, and D. L. Mitchell (2000), Impact of a new scheme for optical properties of ice crystals on climates of two GCMs, J. Geophys. Res., 105(D8), 10063–10079, doi:10.1029/2000JD900015.
            30. Kristjánsson, J. E., J. M. Edwards, and D. L. Mitchell (1999), A new parameterization scheme for the optical properties of ice crystals for use in general circulation models of the atmosphere, Phys. Chem. Earth, 24, 231–236.
            31. Kumar, V. V., C. Jakob, A. Protat, P. T. May, and L. Davies (2013), The four cumulus cloud models and their progression during rainfall events: A C-band polarimetric radar perspective, J. Geophys. Res., 118(15), 8375–8389, doi:10.1002/jgrd.50640.
            32. Li, H., J. Sheffield, and E. F. Wood (2010), Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching, J. Geophys. Res., 115, D10101, doi:10.1029/2009JD012882.
            33. Liu, G. (1998), A Fast and Accurate Model for Microwave Radiance Calculations, J. Meteorol. Soc. Jpn., 76(2), 335–343.
            34. Lohmann, U. and B. Kaecher (2002), First interactive simulations of cirrus clouds formed by homogeneous freezing in the ECHAM GCM, J. Geophys. Res., 107, doi:10.1029/2001JD000767.
            35. Lohmann, U., B. Kärcher, and C. Timmreck (2003), Impact of the Mount Pinatubo eruption on cirrus clouds formed by homogeneous freezing in the ECHAM4 GCM, J. Geophys. Res., 108(D18), doi:10.1029/2002JD003185.
            36. Lohmann, U., B. Kärcher, and C. Timmreck (2004), Impact of the Mount Pinatubo Eruption on Cirrus Clouds Formed by Homogeneous Freezing in the ECHAM GCM, J. Geophys. Res., 109, doi:10.1029/2002JD003185.
            37. Lohmann, U., B. Kärcher, and J. Hendricks (2004), Sensitivity studies of cirrus clouds formed by heterogeneous freezing in the ECHAM GCM, J. Geophys. Res., 108, doi:10.1029/2003JD004443.
            38. Lohmann, U., P. Stier, C. Hoose, S. Ferrachat, E. Roeckner, and J. Zhang (2007), Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5–HAM, Atmos. Chem. Phys., 7, 3719–3761, doi:10.5194/acp-7-3425-2007.
            39. Lohmann, U. and E. Roeckner (1996), Design and performance of a new microphysics schemen developed for the ECHAM general circulation model, Climate Dynamics, 12, 557–572.
            40. Masunaga, H., T. Matsui, W. K. Tao, A. Y. Hou, C. D. Kummerow, T. Nakajima, P. Bauer, W. S. Olson, M. Sekiguchi, and T.Y. Nakajima (2010), Satellite Data Simulator Unit (SDSU): A multi-sensor, multi-spectral satellite simulator, Bull. Amer. Met. Soc.
            41. Matteo, N. A. and Y. T. Morton (2011), Comparison of IGRF model prediction and satellite measurements 1991–2010, Radio Sci., 46, RS4003, doi:10.1029/2010RS004529.
            42. Mattioli, V., P. Basili, S. Bonafoni, P. Ciotti, and E. R. Westwater (2009), Analysis and improvements of cloud models for propagation studies, Radio Sci., 44, RS2005, doi:10.1029/2008RS003876.
            43. Mauritsen, T. and B. Stevens (2015), Missing iris effect as a possible cause of muted hydrological change and high climate sensitivity in models, Nature Geosci., 8, 346–351, doi:10.1038/ngeo2414.
            44. Mayer, B. and A. Kylling (2005), Technical note: The libRadtran software package for radiative transfer calculations - description and examples of use, Atmos. Chem. Phys., 5, 1855–1877, doi:10.5194/acp-5-1855-2005.
            45. Mitchell, J. L., R. T. Pierrehumbert, D. M. W. Frierson, and R. Caballero (2006), The Dynamics behind Titan's Methane Clouds, Proc. Nat. Aca. Sci., 103(49), 18421–18426, doi:10.1073/pnas.0605074103.
            46. Nolte-Holube, R., U. Karstens, D. Lohmann, B. Rockel, and R. Stuhlmann (1996), Regional scale atmospheric and hydrological modelling: Results and validation for the Baltic Sea and Weser catchments, Institute fuer Athmosphaerenphysik, GKSS-Forschungszentrum.
            47. Pierce, D. W., T. P. Barnett, E. J. Fetzer, and P. J. Gleckler (2006), Three-dimensional tropospheric water vapor in coupled climate models compared with observations from the AIRS satellite system, Geophys. Res. Lett., 33, L21701, doi:10.1029/2006GL027060.
            48. Pierrehumbert, R. T. (2011), A palette of climates for Gliese581g, Astrophys. J. Lett., 786(L8), doi:10.1088/2041-8205/726/1/L8.
            49. Pincus, R. and B. Stevens (2013), Paths to accuracy for radiation parametrizations in atmospheric models, J. Adv. Model. Earth Syst., 5(2), 225–233, doi:10.1002/jame.20027.
            50. Pulvirenti, L., N. Pierdicca, and F. S. Marzano (2005), Simulating Brightness Temperatures in Cloudy Conditions Over the Mediterranean Sea, In: Proceedings of the XXIXth General Assembly of International Union of Radio Science (URSI), New Delhi.
            51. Quaas, J., B. Stevens, P. Stier, and U. Lohmann (2010), Interpreting the cloud cover — Aerosol optical depth relationship found in satellite data using a general circulation model, Atmos. Chem. Phys., 10, 6129–6135, doi:10.5194/acp-10-6129-2010.
            52. Rädel, G. and K. P. Shine (2010), Validating ECMWF forecasts for the occurrence of ice supersaturation using visual observations of persistent contrails and radiosonde measurements over England, Q. J. R. Meteorol. Soc., doi:10.1002/qj.670.
            53. Randall, D. A., R. A. Wood, S. Bony, R. Colman, T. Fichefet, J. Fyfe, V. Kattsov, A. Pitman, J. Shukla, J. Srinivasan, R. J. Stouffer, A. Sumi, and K. E. Taylor (2007), Climate models and their evaluation, In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Edited by Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H. L. Biller, Cambridge University Press.
            54. Richardson, M., K. Cowtan, E. Hawkins, and M. B. Stolpe (2016), Reconciled climate response estimates from climate models and the energy budget of Earth, Nature Clim. Change, doi:10.1038/NCLIMATE3066.
            55. Rodrigo, R., E. G. Alvarez, and M. J. Lopez (1990), A Nonsteady One-Dimensional Theoretical Model of Mars Neutral Atmospheric Composition Between 30 and 200 km, Geophys. Res. Lett., 95, 14795–14810.
            56. Roeckner, E., et al. (2003), The atmospheric general circulation model ECHAM5. Part I: model description. 127pp., MPI Hamburg.
            57. Ross, R. J., W. P. Elliot, and D. J. Seidel (2002), Lower-Tropospheric Humidity-Temperature Relationships in Radiosonde Observations and Atmospheric General Circulation Models, Journal of Hydrometerology, 3, 26–38.
            58. Schaller, N., I. Mahlstein, J. Cermak, and R. Knutti (2011), Analyzing precipitation projections: A comparison of different approaches to climate model evaluation, J. Geophys. Res., 116, D10118, doi:10.1029/2010JD014963.
            59. Slingo, A., K. I. Hodges, and G. J. Robinson (2004), Simulation of the diurnal cycle in a climate model and its evaluation using data from Meteosat 7, Q. J. R. Meteorol. Soc., 130, 1449–1467, doi:10.1256/qj.03.165.
            60. Smith, E. A., P. Bauer, F. S. Marzano, C. D. Kummerow, D. McKague, A. Mugnai, and G. Panegrossi (2002), Intercomparison of Microwave Radiative Transfer Models for Precipitating Clouds, IEEE Geosci. Remote Sens., 40(3), 541–549.
            61. Soden, B. J. and I. M. Held (2006), An assessment of climate feedbacks in coupled ocean-atmosphere models, J. Climate, 19(14), 3354–3360, doi:10.1175/JCLI3799.1.
            62. Spangenberg, D. A., G. G. Mace, T. P. Ackerman, N. L. Seaman, and B. J. Soden (1997), Evaluation of model-simulated upper troposphere humidity using 6.7 μm satellite observations, J. Geophys. Res., 102(D22), 25737–25749.
            63. Stamnes, K., S.-C. Tsay, and I. Laszlo (2000), DISORT, a General-Purpose Fortran Program for Discrete-Ordinate-Method Radiative Transfer in Scattering and Emitting Layered Media: Documentation of Methodology, Dept. of Physics and Engineering Physics Stevens Institute of Technology,NASA Goggard Space Flight Center, Department of Meteorology University of Maryland.
            64. Stevens, B. and S. Bony (2013), What are Climate Models Missing, Science, 340(6136), 1053–1054, doi:10.1126/science.1237554.
            65. Su, H., J. H. Jiang, C. Zhai, T. J. Shen, J. D. Neelin, G. L. Stephens, and Y. L. Yung (2014), Weakening and strengthening structures in the Hadley Circulation change under global warming and implications for cloud response and climate sensitivity, J. Geophys. Res., 119(10), 5787–5805, doi:10.1002/2014JD021642.
            66. Trenberth, K. E. and J. T. Fasullo (2010), Simulation of Present-Day and Twenty-First-Century Energy Budgets of the Southern Oceans, J. Climate, 23(2), 1272–1282, doi:10.1175/2009JCLI3152.1.
            67. Turner, D. D., S. Kneifel, and M. P. Cadeddu (2016), An Improved Liquid Water Absorption Model at Microwave Frequencies for Supercooled Liquid Water Clouds, J. Atmos. Oceanic Technol., 33(1), 33–44, doi:10.1175/JTECH-D-15-0074.1.
            68. Vial, J., J.-L. Defrusne, and S. Bony (2013), On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates, Climate Dynamics, 41(11), 3339–3362, doi:10.1007/s00382-013-1725-9.
            69. Watterson, I. G., M. R. Dix, and R. A. Colman (1999), A comparison of present and doubled CO2 climates and feedbacks simulated by three general circulation models, J. Geophys. Res., 104(D2), 1943–1956.
            70. Webb, M. J., T. Andrews, A. Bodas-Salcedo, S. Bony, C. S. Bretherton, R. Chadwick, H. Chepfer, H. Douville, P. Good, J. E. Kay, S. A. Klein, R. Marchand, B. Medeiros, A. Pier Siebesma, C. B. Skinner, B. Stevens, G. Tselioudis, Y. Tsushima, and M. Watanabe (2016), The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6, Geosci. Model Dev. Discuss., 2016, 1–27, doi:10.5194/gmd-2016-70.
            71. Woods, C. P., D. E. Waliser, J.-L. Li, R. T. Austin, G. L. Stephens, and D. G. Vane (2008), Evaluating CloudSat ice water content retrievals using a cloud- resolving model: Sensitivities to frozen particle properties, J. Geophys. Res., 113, D00A11, doi:10.1029/2008JD009941.
            72. Wyant, M. C., C. S. Bretherton, J. T. Bacmeister, J. T. Kiehl, I. M. Held, M. Zhao, S. A. Klein, and B. J. Soden (2006), A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity, Climate Dynamics, 27, 261–279, doi:10.1007/s00382-006-0138-4.
            73. Zängl, G., D. Reinert, P. Rípodas, and M. Baldauf (2015), The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. R. Meteorol. Soc., 141(687), 563–579, doi:10.1002/qj.2378.
            74. Zelinka, M. D. and D. L. Hartmann (2010), Why is longwave cloud feedback positive?, J. Geophys. Res.: Atm., 115(D16), D16117, doi:10.1029/2010JD013817,.
            75. Zelinka, M. D., S. A. Klein, K. E. Taylor, T. Andrews, M. J. Webb, J. M. Gregory, and P. M. Forster (2013), Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5, J. Climate, 26(14), 5007–5027, doi:10.1175/JCLI-D-12-00555.1.