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Using longwave HIRS radiances to test climate models

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Abstract

A ‘model-to-radiance’ comparison of simulated brightness temperatures from the Hadley Centre Global Environmental Model 2 with measurements from the High Resolution Infrared Radiation Sounder/4 (HIRS/4) instrument onboard the MetOp-A satellite is presented. For the all-sky, the model overestimates brightness temperatures in the atmospheric window region with the greatest biases over areas associated with deep convective cloud. In contrast to many global climate models, much smaller clear-sky biases are found indicating that model clouds are the dominating source of error. Simulated values in upper atmospheric CO2 channels approximate observations better as a result of compensating cold biases at the poles and warm biases at lower latitudes, due to a poor representation of the Brewer Dobson circulation in the 38 level ‘low-top’ configuration of the model. Simulated all and clear-sky outgoing longwave radiation (OLR) evaluated against the Clouds and the Earth’s Radiant Energy System (CERES) and HIRS OLR products reveal good agreement, in part due to cancellation of positive and negative biases. Through physical arguments relating to the spectral energy balance within a cloud, it is suggested that broadband agreement could be the result of a balance between positive window biases and unseen negative biases originating from the water vapour rotational band in the far infrared (not sampled by HIRS).

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References

  • Allan R, Slingo A (2002) Can current climate model forcings explain the spatial and temporal signatures of decadal OLR variations? Geophys Res Lett 29(7):1141

    Article  Google Scholar 

  • Allan R, Ringer M, Slingo A (2003) Evaluation of moisture in the Hadley Centre climate model using simulations of HIRS water-vapour channel radiances. Q J Royal Meteorol Soc 129(595):3371–3389

    Article  Google Scholar 

  • Amorati R, Rizzi R (2002) Radiances simulated in the presence of clouds by use of a fast radiative transfer model and a multiple-scattering scheme. Appl Opt 41(9):1604–1614

    Article  Google Scholar 

  • Barker HW, Li Z, Blanchet JP (1994) Radiative characteristics of the Canadian climate centre second-generation general circulation model. J Clim 7(7):1070–1091

    Article  Google Scholar 

  • Barkstrom BR (1984) The earth radiation budget experiment (erbe). Bull Am Meteorol Soc 65(11):1170–1185

    Article  Google Scholar 

  • Bates J, Wu X, Jackson D (1996) Interannual variability of upper-troposphere water vapor band brightness temperature. J Clim 9(2):427–438

    Article  Google Scholar 

  • Bodas-Salcedo A, Webb M, Bony S, Chepfer H, Dufresne J, Klein S, Zhang Y, Marchand R, Haynes J, Pincus R et al (2011) COSP: satellite simulation software for model assessment. Bull Am Meteorol Soc 92:1023–1043

    Article  Google Scholar 

  • Bony S, Emanuel K (2001) A parameterization of the cloudiness associated with cumulus convection; evaluation using TOGA COARE data. J Atmos Sci 58(21):3158–3183

    Article  Google Scholar 

  • Budyko MI (1969) The effect of solar radiation variations on the climate of the earth. Tellus 21(5):611–619

    Article  Google Scholar 

  • Buriez J, Bonnel B, Fouquart Y, Geleyn J, Morcrette J (1988) Comparison of model-generated and satellite-derived cloud cover and radiation budget. J Geophys Res 93(D4):3705–3719

    Article  Google Scholar 

  • Cao C, Xu H, Sullivan J, McMillin L, Ciren P, Hou Y (2005) Intersatellite radiance biases for the high-resolution infrared radiation sounders (HIRS) on board NOAA-15,-16, and-17 from simultaneous nadir observations. J Atmos Ocean Technol 22(4):381–395

    Article  Google Scholar 

  • Cao C, Goldberg M, Wang L (2009) Spectral bias estimation of historical HIRS using IASI observations for improved fundamental climate data records. J Atmos Ocean Technol 26(7):1378–1387

    Article  Google Scholar 

  • Cess RD (1976) Climate change: An appraisal of atmospheric feedback mechanisms employing zonal climatology. J Atmos Sci 33:1831–1843

    Article  Google Scholar 

  • Charlton-Perez A, Baldwin M, Birner T, Black R, Butler A, Calvo N, Davis N, Gerber E, Gillett N, Hardiman S et al. (2013) On the lack of stratospheric dynamical variability in low-top versions of the CMIP5 models. J Geophys Res Atmos 118:2494–2505

    Google Scholar 

  • Chen R, Cao C (2012) Physical analysis and recalibration of MetOp HIRS using IASI for cloud studies. J Geophys Res 117(D3):D03,103

    Google Scholar 

  • Chen X, Huang X, Loeb NG, Wei H (2013) Comparisons of clear-sky outgoing far-ir flux inferred from satellite observations and computed from the three most recent reanalysis products. J Clim 26(2):478–494

    Article  Google Scholar 

  • Chevallier F, Kelly G (2002) Model clouds as seen from space: comparison with geostationary imagery in the 11-μm window channel. Mon Weather Rev 130(3):712–722

    Article  Google Scholar 

  • Chevallier F, Bauer P, Kelly G, Jakob C, McNally T (2001) Model clouds over oceans as seen from space: comparison with HIRS/2 and MSU radiances. J Clim 14(21):4216–4229

    Article  Google Scholar 

  • Chou MD, Lee KT, Tsay SC, Fu Q (1999) Parameterization for cloud longwave scattering for use in atmospheric models. J Clim 12(1):159–169

    Article  Google Scholar 

  • Chung E, Soden B, Sohn B, Schmetz J (2011) Model-simulated humidity bias in the upper troposphere and its relation to the large-scale circulation. J Geophys Res 116(D10):D10,110

    Article  Google Scholar 

  • Chung E, Soden B, Clement A (2012) Diagnosing climate feedbacks in coupled ocean–atmosphere models. Surv Geophys 116:1–12

    Google Scholar 

  • Collins W, Bellouin N, Doutriaux-Boucher M, Gedney N, Hinton T, Jones C, Liddicoat S, Martin G, O Connor F, Rae J et al. (2008) Evaluation of the HadGEM2 model, vol 74. Hadley Centre Technical Note, Exeter

  • Cordero E, Forster P et al. (2006) Stratospheric variability and trends in models used for the ipcc ar4. Atmos Chem Phys 6(12):5369–5380

    Article  Google Scholar 

  • Cusack S, Edwards J, Kershaw R (1999) Estimating the subgrid variance of saturation, and its parametrization for use in a GCM cloud scheme. Q J Royal Meteorol Soc 125(560):3057–3076

    Article  Google Scholar 

  • Dee D, Uppala S, Simmons A, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda M, Balsamo G, Bauer P et al. (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J Royal Meteorol Soc 137(656):553–597

    Article  Google Scholar 

  • Derbyshire S, Maidens A, Milton S, Stratton R, Willett M (2011) Adaptive detrainment in a convective parametrization. Q J Royal Meteorol Soc 137(660):1856–1871

    Article  Google Scholar 

  • Edwards J, Slingo A (1996) Studies with a flexible new radiation code. I: choosing a configuration for a large-scale model. Q J Royal Meteorol Soc 122(531):689–719

    Article  Google Scholar 

  • Ellingson RG, Lee HT, Yanuk DJ, Gruber A (1989) A technique for estimating outgoing longwave radiation from hirs radiance observations. J Atmos Ocean Technol 6:706–711

    Article  Google Scholar 

  • Ellis JS, Vander Haar TH (1976) Zonal average earth radiation budget measurements from satellites for climate studies. Department of Atmospheric Science, Colorado

    Google Scholar 

  • Gregory D, Rowntree P (1990) A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon Weather Rev 118(7):1483–1506

    Article  Google Scholar 

  • Gregory D, Wilson D, Bushell A (2002) Insights into cloud parametrization provided by a prognostic approach. Q J Royal Meteorol Soc 128(583):1485–1504

    Article  Google Scholar 

  • Gregory J (1999) Representation of the radiative effects of convective anvils. Hadley Centre Technical Note 7 Met Office: Exeter, UK

    Google Scholar 

  • Gregory J, Webb M (2008) Tropospheric adjustment induces a cloud component in CO2 forcing. J Clim 21(1):58–71

    Article  Google Scholar 

  • Gruber A (1977) Determination of the earth-atmosphere radiation budget from NOAA satellite data. Unknown 1

  • Gruber A, Winston J (1978) Earth-atmosphere radiative heating based on NOAA scanning radiometer measurements. Bull Am Meteorol Soc 59:1570–1573

    Article  Google Scholar 

  • Hardiman S, Butchart N, Hinton T, Osprey S, Gray L (2012) The effect of a well resolved stratosphere on surface climate: differences between CMIP5 simulations with high and low top versions of the met office climate model. J Clim 25:7083–7099

    Google Scholar 

  • Harries J, Carli B, Rizzi R, Serio C, Mlynczak M, Palchetti L, Maestri T, Brindley H, Masiello G (2008) The far-infrared earth. Rev Geophys 46(4):RG4004

    Article  Google Scholar 

  • Harries JE, Brindley HE, Sagoo PJ, Bantges RJ (2001) Increases in greenhouse forcing inferred from the outgoing longwave radiation spectra of the earth in 1970 and 1997. Nature 410(6826):355–357

    Article  Google Scholar 

  • Hartmann D, Ramanathan V, Berroir A, Hunt G (1986) Earth radiation budget data and climate research. Rev Geophys 24(2):439–468

    Article  Google Scholar 

  • Hess M, Koepke P, Schult I (1998) Optical properties of aerosols and clouds: the software package OPAC. Bull Am Meteorol Soc 79(5):831–844

    Article  Google Scholar 

  • Hewitt H, Copsey D, Culverwell I, Harris C, Hill R, Keen A, McLaren A, Hunke E (2011) Design and implementation of the infrastructure of HadGEM3: the next-generation met office climate modelling system. Geosci Model Dev 4:223–253

    Article  Google Scholar 

  • Huang X, Ramaswamy V, Schwarzkopf MD (2006) Quantification of the source of errors in AM2 simulated tropical clear-sky outgoing longwave radiation. J Geophys Res Atmos (1984–2012) 111:D14

  • Huang X, Loeb N, Yang W (2010) Spectrally resolved fluxes derived from collocated AIRS and CERES measurements and their application in model evaluation: 2. cloudy sky and band-by-band cloud radiative forcing over the tropical oceans. J Geophys Res 115(D21):D21,101

    Article  Google Scholar 

  • Huang X, Cole JN, He F, Potter GL, Oreopoulos L, Lee D, Suarez M, Loeb NG (2013) Longwave band-by-band cloud radiative effect and its application in GCM evaluation. J Clim 26(2):450–467

    Article  Google Scholar 

  • Huang Y, Ramaswamy V, Huang X, Fu Q, Bardeen C (2007a) A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations. Geophys Res Lett 34(24):L24,707

    Article  Google Scholar 

  • Huang Y, Ramaswamy V, Soden B (2007b) An investigation of the sensitivity of the clear-sky outgoing longwave radiation to atmospheric temperature and water vapor. J Geophys Res 112(D5):D05,104

    Article  Google Scholar 

  • Iacono M, Delamere J, Mlawer E, Clough S (2003) Evaluation of upper tropospheric water vapor in the NCAR community climate model (CCM3) using modeled and observed HIRS radiances. J Geophys Res 108(D2):4037

    Article  Google Scholar 

  • Jackson D, Wylie D, Bates J (2003) The HIRS pathfinder radiance data set (1979–2001). In: Preprints, 12th conference on satellite meteorology and oceanography, Long Beach, CA, Amer Meteor Soc P, vol 1

  • Jiang J, Su H, Zhai C, Perun V, Del Genio A, Nazarenko L, Donner L, Horowitz L, Seman C, Cole J et al. (2012) Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA A-train satellite observations. J Geophys Res 117(D14):D14,105

    Article  Google Scholar 

  • John V, Soden B (2007) Temperature and humidity biases in global climate models and their impact on climate feedbacks. Geophys Res Lett 34:L18,704

    Article  Google Scholar 

  • John V, Holl G, Allan R, Buehler S, Parker D, Soden B (2011) Clear-sky biases in satellite infrared estimates of upper tropospheric humidity and its trends. J Geophys Res 116(D14):D14,108

    Article  Google Scholar 

  • Kassianov E, Barnard J, Berg L, Long C, Flynn C (2011) Shortwave spectral radiative forcing of cumulus clouds from surface observations. Geophys Res Lett 38(7):L07,801

    Article  Google Scholar 

  • Kay J, Gettelman A, Eaton B, Boyle JJ, Marchand RR, Ackermann T (2012) Exposing global cloud biases in the community atmosphere model (CAM) using satellite observations and their corresponding instrument simulators. J Clim 25:5190–5207

    Article  Google Scholar 

  • Kiehl J, Ramanathan V (1990) Comparison of cloud forcing derived from the earth radiation budget experiment with that simulated by the NCAR community climate model. J Geophys Res Atmos (1984–2012) 95(D8):11,679–11,698

    Article  Google Scholar 

  • Kiehl J, Hack J, Briegleb B (1994) The simulated earth radiation budget of the national center for atmospheric research community climate model CCM2 and comparisons with the earth radiation budget experiment (ERBE). J Geophys Res Atmos (1984–2012) 99(D10):20,815–20,827

    Article  Google Scholar 

  • Klaes D, Ackermann J, Schraidt R, Patterson T, Schlüssel P, Phillips P, Arriaga A, Grandell J (2005) The ATOVS and AVHRR product processing facility of eps. Adv Space Res 36(5):996–1002

    Google Scholar 

  • Lee H, Gruber A, Ellingson R, Laszlo I (2007) Development of the HIRS outgoing longwave radiation climate dataset. J Atmos Ocean Technol 24(12):2029–2047

    Article  Google Scholar 

  • Lee HT, Ellingson RG (2013) HIRS OLR climate data record–production and validation updates. In: AIP conference proceedings, vol 1531, p 420

  • Leroy S, Anderson J, Dykema J, Goody R (2008) Testing climate models using thermal infrared spectra. J Clim 21(9):1863–1875

    Article  Google Scholar 

  • Li J, Wolf W, Menzel W, Zhang W, Huang H, Achtor T (2000) Global soundings of the atmosphere from ATOVS measurements: the algorithm and validation. J Appl Meteorol 39(8):1248–1268

    Article  Google Scholar 

  • Li JLF, Waliser DE, Stephens G, Lee S, L’Ecuyer T, Kato S, Loeb N, Ma HY (2013) Characterizing and understanding radiation budget biases in CMIP3/CMIP5 GCMs, contemporary GCM and reanalysis. J Geophys Res Atmos 118:8166–8184

    Google Scholar 

  • 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(3):748–766

    Article  Google Scholar 

  • MacKenzie I, Tett S, Lindfors A (2012) Climate model-simulated diurnal cycles in HIRS clear-sky brightness temperatures. J Clim 25:5845–5863

    Google Scholar 

  • Maestri T, Rizzi R (2003) A study of infrared diabatic forcing of ice clouds in the tropical atmosphere. J Geophys Res 108(D4):4139

    Article  Google Scholar 

  • Manabe S, Wetherald RT (1967) Thermal equilibrium of the atmosphere with a given distribution of relative humidity. J Atmos Sci 24:241–259

    Google Scholar 

  • Martin G, Bellouin N, Collins W, Culverwell I, Halloran P, Hardiman S, Hinton T, Jones C, McDonald R, McLaren A et al. (2011) The HadGEM2 family of met office unified model climate configurations. Geosci Model Dev 4(3):723–757

    Article  Google Scholar 

  • Matricardi M (2005) The inclusion of aerosols and clouds in RTIASI, the ECMWF fast radiative transfer model for the infrared atmospheric sounding interferometer. Eur Centre Medium Range Weather Forecast, ECMWF Technical Memorandum, vol 474

  • Mauritsen T, Stevens B, Roeckner E, Crueger T, Esch M, Giorgetta M, Haak H, Jungclaus J, Klocke D, Matei D, et al. (2012) Tuning the climate of a global model. J Adv Model Earth Syst 4(null):M00A01

    Google Scholar 

  • Meehl G, Covey C, Delworth T, Latif M, McAvaney B, Mitchell J, Stouffer R, Taylor K (2007) The wcrp cmip3 multi-model dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394

    Article  Google Scholar 

  • Mlynczak M, Johnson D, Latvakoski H, Jucks K, Watson M, Kratz D, Bingham G, Traub W, Wellard S, Hyde C et al. (2006) First light from the far-infrared spectroscopy of the troposphere (FIRST) instrument. Geophys Res Lett 33(7):L07,704

    Article  Google Scholar 

  • Morcrette J (1989) Comparison of satellite-derived and model-generated diurnal cycles of cloudiness and brightness temperatures. Adv Space Res 9:175–179

    Article  Google Scholar 

  • Morcrette J (1991) Evaluation of model-generated cloudiness: Satellite-observed and model-generated diurnal variability of brightness temperature. Month Weather Rev 119(5):1205–1224

    Article  Google Scholar 

  • Morcrette C, O’Connor E, Petch J (2012) Evaluation of two cloud parametrization schemes using ARM and cloud-net observations. Q J Royal Meteorol Soc 138:964–979

    Google Scholar 

  • NOAA (2006) KLM user’s guide Section 3.2.2 HIRS/4, http://www.ncdc.noaa.gov/oa/pod-guide/ncdc/docs/klm/html/c3/sec32-2.htm

  • Probst P, Rizzi R, Tosi E, Lucarini V, Maestri T (2012) Total cloud cover from satellite observations and climate models. Atmos Res 107:161–170

    Google Scholar 

  • Räisänen P (1998) Effective longwave cloud fraction and maximum-random overlap of clouds: a problem and a solution. Month Weather Rev 126(12):3336–3340

    Article  Google Scholar 

  • Ramanathan V (1987) The role of earth radiation budget studies in climate and general circulation research. J Geophys Res 92(D4):4075–4095

    Article  Google Scholar 

  • Randall D, Khairoutdinov M, Arakawa A, Grabowski W (2003) Breaking the cloud parameterization deadlock. Bull Am Meteorol Soc 84(11):1547–1564

    Article  Google Scholar 

  • Randall D, Wood R, Bony S, Colman R, Fichefet T, Fyfe J, Kattsov V, Pitman A, Shukla J, Srinivasan J, Stouffer R, Sumi A, Taylor K (2007) Climate models and their evaluation. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change, chap 8. Cambridge University Press, Cambridge

  • Rayner N, Parker D, Horton E, Folland C, Alexander L, Rowell D, Kent E, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14):4407

    Article  Google Scholar 

  • Righetti PL, Meixner H, Sancho F, Damiano A, Lazaro D (2007) Flight dynamics performances of the MetOp-A satellite during the first months of operations. International Symposium on Space Flight Dynamics. http://issfd.org/ISSFD_2007/1-2.pdf

  • Ringer M, Allan R (2004) Evaluating climate model simulations of tropical cloud. Tellus A 56(4):308–327

    Article  Google Scholar 

  • Rizzi R (1994) Raw HIRS/2 radiances and model simulations in the presence of clouds. ECMWF Tech Report No. 73:29

  • Rossow WB, Schiffer RA (1991) ISCCP cloud data products. Bull Am Meteorol Soc 72(1):2–20

    Article  Google Scholar 

  • Sassen K, Wang Z, Liu D (2008) Global distribution of cirrus clouds from CloudSat/cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO) measurements. J Geophys Res 113(D8):D00A12

    Google Scholar 

  • Saunders R et al. (2010) RTTOV-9 science and validation report. NWP SAF Report: EUMETSAT

  • Saunders R et al. (2011) RTTOV-10 science and validation report. NWP SAF Report: EUMETSAT

  • Shi L, Bates JJ (2011) Three decades of intersatellite-calibrated high-resolution infrared radiation sounder upper tropospheric water vapor. J Geophys Res Atmos 116:D04108

    Google Scholar 

  • Simmons A, Uppala S, Dee D, Kobayashi S (2007) Era-interim: new ecmwf reanalysis products from 1989 onwards. ECMWF Newslett 110(110):25–35

    Google Scholar 

  • Slingo JM (1982) A study of the earth’s radiation budget using a general circulation model. Q J Royal Meteorol Soc 108(456):379–405

    Article  Google Scholar 

  • Smith G, Mlynczak P, Rutan D, Wong T (2008) Comparison of the diurnal cycle of outgoing longwave radiation from a climate model with results from ERBE. J Appl Meteorol Climatol 47(12):3188–3201

    Article  Google Scholar 

  • Smith R (1990) A scheme for predicting layer clouds and their water content in a general circulation model. Q J Royal Meteorol Soc 116(492):435–460

    Article  Google Scholar 

  • Soden B, Held I (2006) An assessment of climate feedbacks in coupled ocean-atmosphere models. J Clim 19(14):3354–3360

    Article  Google Scholar 

  • Soden B, Jackson D, Ramaswamy V, Schwarzkopf M, Huang X (2005) The radiative signature of upper tropospheric moistening. Science 310(5749):841–844

    Article  Google Scholar 

  • Sohn B, Nakajima T, Satoh M, Jang H (2010) Impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing: NICAM simulation results. Atmos Chem Phys 10:11,641–11,646

    Article  Google Scholar 

  • Stephens G (2005) Cloud feedbacks in the climate system: a critical review. J Clim 18(2):237–273

    Article  Google Scholar 

  • Stephens G, Kummerow C (2007) The remote sensing of clouds and precipitation from space: a review. J Atmos Sci 64(11):3742–3765

    Article  Google Scholar 

  • Stephens G, Campbell G, Haar T (1981) Earth radiation budgets. J Geophys Res Ocean (1978–2012) 86(C10):9739–9760

    Article  Google Scholar 

  • Stephens GL, Vane DG, Boain RJ, Mace GG, Sassen K, Wang Z, Illingworth AJ, O’Connor EJ, Rossow WB, Durden SL, et al. (2002) The CloudSat mission and the A-Train: a new dimension of space-based observations of clouds and precipitation. Bull Am Meteorol Soc 83(12):1771–1790

    Article  Google Scholar 

  • Stephens GL, Li J, Wild M, Clayson CA, Loeb N, Kato S, L’Ecuyer T, Stackhouse Jr PW, Lebsock M, Andrews T (2012) An update on earth’s energy balance in light of the latest global observations. Nat Geosci 5:691–696

    Google Scholar 

  • Stratton R, Stirling A (2012) Improving the diurnal cycle of convection in GCMs. Q J Royal Meteorol Soc 138:1121–1134

    Google Scholar 

  • Taylor K, Stouffer R, Meehl G (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485

    Article  Google Scholar 

  • Vidot J, Guyot, Jourdan G, Sourdeval O, Brunel O, P Labonnote L, Brogniez G (2011) Evaluation of RTTOV ice cloud parameterization by comparison with infrared measurements from IIR/CALIPSO during the CIRCLE-2 experiment. Poster from 2011 EUMETSAT meteorological satellite conference, p 59

  • Wang H, Su W (2013) Evaluating and understanding top of the atmosphere cloud radiative effects in intergovernmental panel on climate change (IPCC) fifth assessment report (AR5) coupled model intercomparison project phase 5 (cmip5) models using satellite observations. J Geophys Res Atmos 118:683–699

    Google Scholar 

  • Wielicki B, Barkstrom B, Harrison E, Lee III R, Louis Smith G, Cooper J (1996) Clouds and the earth’s radiant energy system (CERES): an earth observing system experiment. Bull Am Meteorol Soc 77(5):853–868

    Article  Google Scholar 

  • Wilson D, Ballard S (1999) A microphysically based precipitation scheme for the UK meteorological office unified model. Q J Royal Meteorol Soc 125(557):1607–1636

    Article  Google Scholar 

  • Wilson D, Bushell A, Kerr-Munslow A, Price J, Morcrette C (2008) PC2: a prognostic cloud fraction and condensation scheme. i: scheme description. Q J Royal Meteorol Soc 134(637):2093–2107

    Article  Google Scholar 

  • Wylie D (2008) Diurnal cycles of clouds and how they affect polar-orbiting satellite data. J Clim 21(16):3989–3996

    Article  Google Scholar 

  • Wylie D, Menzel W, Woolf H, Strabala K (1994) Four years of global cirrus cloud statistics using HIRS. J Clim 7(12):1972–1986

    Article  Google Scholar 

  • Wylie D, Jackson D, Menzel W, Bates J (2005) Trends in global cloud cover in two decades of HIRS observations. J Clim 18(15):3021–3031

    Article  Google Scholar 

  • Wyser K, Yang P (1998) Average ice crystal size and bulk short-wave single-scattering properties of cirrus clouds. Atmos Res 49(4):315–335

    Article  Google Scholar 

  • Yang G, Slingo J (2001) The diurnal cycle in the tropics. Month Weather Rev 129(4):784–801

    Article  Google Scholar 

  • Zhou T, Yu R (2006) Twentieth-century surface air temperature over china and the globe simulated by coupled climate models. J Clim 19(22):5843–5858

    Article  Google Scholar 

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Acknowledgments

HIRS all-sky data was kindly provided by Viju John of the UK Met Office and processed clear-sky data was from Lei Shi of NOAA. ECMWF ERA-40 data used in this study have been obtained from the ECMWF Data Server. We thank Ian MacKenzie of the University of Edinburgh for providing UM data, Hai-Tien Lee of the University of Maryland for providing HIRS MetOp-A OLR data, Christopher Merchant of the University of Reading, UK for additional comments and Cyril Morcrette, James Hocking and Roger Saunders of the UK Met Office for valuable insights into the models. We also express our gratitude to two anonymous reviewers for their helpful comments. We thank the UK’s National Environmental Research Council for funding the project.

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  1. Grant Institute, School of Geosciences, University of Edinburgh, King’s Buildings, Edinburgh, EH9 3JW, Scotland, UK

    Emma C. Turner & Simon F. B. Tett

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Correspondence to Emma C. Turner.

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Turner, E.C., Tett, S.F.B. Using longwave HIRS radiances to test climate models. Clim Dyn 43, 1103–1127 (2014). https://doi.org/10.1007/s00382-013-1959-6

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