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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                External references

                1. Bayr, T., D. Dommenget, T. Martin, and S. B. Power (2014), The eastward shift of the Walker Circulation in response to global warming and its relationship to ENSO variability, Climate Dynamics, 43(9), 2747–2763, doi:10.1007/s00382-014-2091-y.
                2. Bony, S., G. Bellon, D. Klocke, S. Sherwood, S. Fermepin, and S. Denvil (2013), Robust direct effect of carbon dioxide on tropical circulation and regional precipitation, Nature Geosci., 6(6), 447–451, doi:10.1038/NGEO1799.
                3. Cai, W., S. Borlace, M. Lengaigne, P. van Rensch, M. Collins, G. Vecchi, A. Timmermann, A. Santoso, M. J. McPhaden, L. Wu, M. H. England, G. Wang, E. Guilyardi, and F.-F. Jin (2014), Increasing frequency of extreme El Niño events due to greenhouse warming, Nature Clim. Change, 4, 111–116, doi:10.1038/NCLIMATE2100.
                4. Dessler, A. E. (2010), A Determination of the Cloud Feedback from Climate Variations over the Past Decade, Science, 330(6010), 1523–1527, doi:10.1126/science.1192546.
                5. Dessler, A. E. and S. M. Davis (2010), Trends in tropospheric humidity from reanalysis systems, J. Geophys. Res., 115, D19127, doi:10.1029/2010JD014192.
                6. Engels, A. (2016), Anthropogenic climate change: how to understand the weak links between scientific evidence, public perception, and low-carbon practices, Energy Emiss. Control Technol., 4, 17–26, doi:10.2147/EECT.S63005.
                7. Frieler, K., M. Meinshausen, T. Schneider von Deimling, T. Andrews, and P. Forster (2011), Changes in global-mean precipitation in response to warming, greenhouse gas forcing and black carbon, Geophys. Res. Lett., 38, L04702, doi:10.1029/2010GL045953.
                8. Gregory, J. M. and P. M. Forster (2008), Transient climate response estimated from radiative forcing and observed temperature change, J. Geophys. Res., 113(D23), doi:10.1029/2008JD010405.
                9. Immler, F. J., J. Dykema, T. Gardiner, D. N. Whiteman, P. W. Thorne, and H. Vömel (2010), Reference Quality Upper-Air Measurements: guidance for developing GRUAN data products, Atmos. Meas. Tech., 3, 1217–1231, doi:10.5194/amt-3-1217-2010.
                10. Kleidon, A. and M. Renner (2013), A simple explanation for the sensitivity of the hydrologic cycle to surface temperature and solar radiation and its implications for global climate change, Earth Syst. Dynamics, 4, 455–465, doi:10.5194/esd-4-455-2013.
                11. Kriener, M. (2015), Die Erde im Schwitzkasten, Zeit, 48.
                12. Norris, J. R., R. J. Allen, A. T. Evan, M. D. Zelinka, C. W. O'Dell, and S. A. Klein (2016), Evidence for climate change in the satellite cloud record, Nature, doi:10.1038/nature18273.
                13. Penner, J. E. (2004), Climate change: The cloud conundrum, Nature, 432(7020), 962–963, doi:10.1038/432962a.
                14. Philipona, R., A. Kräuchi, and E. Brocard (2012), Solar and thermal radiation profiles and radiative forcing measured through the atmosphere, Geophys. Res. Lett., 39(13), 1–6, doi:10.1029/2012GL052087.
                15. Popke, D., B. Stevens, and A. Voigt (2013), Climate and climate change in a radiative-convective equilibrium version of ECHAM6, J. Adv. Model. Earth Syst., 5(1), 1–14, doi:10.1029/2012MS000191.
                16. Ren, L., P. Arkin, T. M. Smith, and S. S. P. Shen (2013), Global precipitation trends in 1900–2015 from a reconstruction and coupled model simulations, J. Geophys. Res., 118(4), 1679–1689, doi:10.1002/jgrd.50212.
                17. Schneider, T., P. A. O'Gorman, and X. J. Levine (2010), Water vapor and the dynamics of climate changes, Rev. Geophys., 48, RG3001, doi:10.1029/2009RG000302.
                18. Sherwood, S. and Q. Fu (2014), A Drier Future?, Science, 343(6172), 737–739, doi:10.1126/science.1247620.
                19. Sherwood, S. (2015), The Sun and the rain, Nature, 528(7581), 200–201, doi:10.1038/528200a.
                20. Singh, M. S. and P. A. O'Gorman (2012), Upward Shift of the Atmospheric General Circulation under Global Warming: Theory and Simulations, J. Climate, 25, 8259–8276, doi:10.1175/JCLI-D-11-00699.1.
                21. Stevens, B., S. C. Sherwood, S. Bony, and M. J. Webb (2016), Prospects for narrowing bounds on Earth's equilibrium climate sensitivity, Earth's Fut., 4(11), 512–522, doi:10.1002/2016EF000376.
                22. 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.
                23. Thompson, D. W. J., J. M. Wallace, P. D. Jones, and J. J. Kennedy (2009), Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights, J. Climate, 22(22), 6120–6141, doi:10.1175/2009JCLI3089.1.
                24. Vallis, G. K., P. Zurita-Gotor, C. Cairns, and J. Kidston (2015), Response of the large-scale structure of the atmosphere to global warming, Q. J. R. Meteorol. Soc., 141(690), 1479–1501, doi:10.1002/qj.2456.
                25. Wentz, F. J., L. Ricciardulli, K. Hilburn, and C. Mears (2007), How Much More Rain Will Gobal Warming Bring?, Science, 317(5835), 233–235, doi:10.1126/science.1140746.
                26. 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.