• Attema, J. J., and G. Lenderink, 2014: The influence of the North Sea on coastal precipitation in the Netherlands in the present-day and future climate. Climate Dyn., 42, 505519, https://doi.org/10.1007/s00382-013-1665-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baas, P., S. R. de Roode, and G. Lenderink, 2008: The scaling behaviour of a turbulent kinetic energy closure model for stably stratified conditions. Bound.-Layer Meteor., 127, 1736, https://doi.org/10.1007/s10546-007-9253-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balsamo, G., P. Viterbo, A. Beljaars, B. J. J. M. van den Hurk, M. Hirschi, A. Betts, and K. Scipal, 2009: A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the Integrated Forecast System. J. Hydrometeor., 10, 623643, https://doi.org/10.1175/2008JHM1068.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beljaars, A. C. M., and F. C. Bosveld, 1997: Cabauw data for the validation of land surface parameterization schemes. J. Climate, 10, 11721193, https://doi.org/10.1175/1520-0442(1997)010<1172:CDFTVO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bennartz, R., and et al. , 2013: Greenland melt extent enhanced by low-level liquid clouds. Nature, 496, 8386, https://doi.org/10.1038/nature12002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boers, R., M. J. de Haij, W. M. F. Wauben, H. K. Baltink, L. H. van Ulft, M. Savenije, and C. N. Long, 2010: Optimized fractional cloudiness determination from five ground-based remote sensing techniques. J. Geophys. Res., 115, D24116, https://doi.org/10.1029/2010JD014661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boers, R., T. Brandsma, and A. P. Siebesma, 2017: Impact of aerosols and clouds on decadal trends in all-sky solar radiation over the Netherlands. Atmos. Chem. Phys., 17, 80818100, https://doi.org/10.5194/acp-17-8081-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlock, T. P., and V. Ramanathan, 1985: The albedo field and cloud radiative forcing produced by a general circulation model with internally generated cloud optics. J. Atmos. Sci., 42, 14081429, https://doi.org/10.1175/1520-0469(1985)042<1408:TAFACR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clough, S. A., M. W. Shephard, E. J. Mlawer, J. S. Delamere, M. J. 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, 233244, https://doi.org/10.1016/j.jqsrt.2004.05.058.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cronin, M., N. A. Bond, C. W. Fairall, and R. A. Weller, 2006: Surface cloud forcing in the east Pacific stratus deck/cold tongue/ITCZ complex. J. Climate, 19, 392409, https://doi.org/10.1175/JCLI3620.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and et al. , 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., and G. G. Mace, 2003: Arctic stratus cloud properties and radiative forcing derived from ground-based data collected at Barrow, Alaska. J. Climate, 16, 445461, https://doi.org/10.1175/1520-0442(2003)016<0445:ASCPAR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., B. Xi, and P. Minnis, 2006: A climatology of midlatitude continental clouds from the ARM SGP Central Facility: Part II: Cloud fraction and surface radiative forcing. J. Climate, 19, 17651783, https://doi.org/10.1175/JCLI3710.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., B. Xi, K. Crosby, C. N. Long, R. S. Stone, and M. D. Shupe, 2010: A 10 year climatology of Arctic cloud fraction and radiative forcing at Barrow, Alaska. J. Geophys. Res., 115, D17212, https://doi.org/10.1029/2009JD013489.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dürr, B., and R. Philipona, 2004: Automatic cloud amount detection by surface longwave downward radiation measurements. J. Geophys. Res., 109, D05201, https://doi.org/10.1029/2003JD004182.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • ECMWF-IFS, 2009: IFS documentation-Cy33r1—Part IV: Physical processes. ECMWF Rep., 62 pp., http://www.ecmwf.int/sites/default/files/elibrary/2009/9227-part-iv-physical-processes.pdf.

  • Fairall, C. W., T. Uttal, D. Hazen, J. Hare, M. Cronin, N. Bond, and D. Veron, 2008: Observations of cloud, radiation, and surface forcing in the equatorial eastern Pacific. J. Climate, 21, 655673, https://doi.org/10.1175/2007JCLI1757.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ghate, V. P., B. A. Albrecht, C. W. Fairall, and R. A. Weller, 2009: Climatology of surface meteorology, surface fluxes, cloud fraction, and radiative forcing over the southeast Pacific from buoy observations. J. Climate, 22, 55275540, https://doi.org/10.1175/2009JCLI2961.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Illingworth, A. J., and et al. , 2007: Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations. Bull. Amer. Meteor. Soc., 88, 883898, https://doi.org/10.1175/BAMS-88-6-883.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Intrieri, J. M., C. W. Fairall, M. D. Shupe, P. O. G. Persson, E. L. Andreas, P. S. Guest, and R. E. Moritz, 2002: An annual cycle of Arctic surface cloud forcing at SHEBA. J. Geophys. Res., 107, 8039, https://doi.org/10.1029/2000JC000439.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IPCC, 2014: Climate Change 2014: Synthesis Report. R. K. Pachauri and L.A. Meyer, Eds., IPCC, 151 pp.

  • Kalisch, J., and A. Macke, 2012: Radiative budget and cloud radiative effect over the Atlantic from ship-based observations. Atmos. Meas. Tech., 5, 23912401, https://doi.org/10.5194/amt-5-2391-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulmala, M., and et al. , 2011: General overview: European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI)—Integrating aerosol research from nano to global scales. Atmos. Chem. Phys., 11, 13 06113 143, https://doi.org/10.5194/acp-11-13061-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • L’Ecuyer, T. S. and G. L. Stephens, 2003: The tropical oceanic energy budget from the TRMM perspective. Part I: Algorithm and uncertainties. J. Climate, 16, 19671985, https://doi.org/10.1175/1520-0442(2003)016<1967:TTOEBF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenderink, G., and A. A. M. Holtslag, 2004: An updated length-scale formulation for turbulent mixing in clear and cloudy boundary layers. Quart. J. Roy. Meteor. Soc., 130, 34053427, https://doi.org/10.1256/qj.03.117.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, M., Y. Jiang, and C. Coimbra, 2017: On the determination of atmospheric longwave irradiance under all-sky conditions. Sol. Energy, 144, 4048, https://doi.org/10.1016/j.solener.2017.01.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Long, C. N., and T. P. Ackerman, 2000: Identification of clear skies from broadband pyranometers measurements and calculation of downwelling shortwave cloud effects. J. Geophys. Res., 105, 15 60915 626, https://doi.org/10.1029/2000JD900077.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Long, C. N., and D. D. Turner, 2008: A method for continuous estimation of clear-sky downwelling longwave radiative flux developed using ARM surface measurements. J. Geophys. Res., 113, D18206, https://doi.org/10.1029/2008JD009936.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Long, C. N., T. P. Ackerman, K. L. Gaustad, and J. N. S. Cole, 2006: Estimation of fractional sky cover from broadband shortwave radiometer measurements. J. Geophys. Res., 111, D11204, https://doi.org/10.1029/2005JD006475.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mace, G. G., Q. Zhang, M. Vaughan, R. Marchand, G. Stephens, C. Trepte, and D. Winker, 2009: Description of hydrometeor layer occurrence statistics derived from the first year of merged CloudSat and CALIPSO data. J. Geophys. Res., 114, D00A26, https://doi.org/10.1029/2007JD009755.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marty, Ch., R. Philippona, C. Frolich, and A. Ohmura, 2002: Altitude dependence of surface radiative fluxes and cloud forcing in the Alps: Results from the Alpine Surface Radiation Budget Network. Theor. Appl. Climatol., 72, 137155, https://doi.org/10.1007/s007040200019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mateos, D., M. Antón, A. Valenzuela, A. Cazorla, F. J. Olmo, and L. Alados-Arboledas, 2013: Short-wave radiative forcing at the surface for cloudy systems at a midlatitude site. Tellus, 65B, 21069, https://doi.org/10.3402/tellusb.v65i0.21069.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • May, P. T., C. N. Long, and A. Protat, 2012: The diurnal cycle of the boundary layer, convection, clouds, and surface radiation in a coastal monsoon environment (Darwin, Australia). J. Climate, 25, 53095326, https://doi.org/10.1175/JCLI-D-11-00538.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McFarlane, S., C. N. Long, and J. Flaherty, 2013: A climatology of surface cloud radiative effects at the ARM tropical western Pacific sites. J. Appl. Meteor. Climatol., 52, 9961013, https://doi.org/10.1175/JAMC-D-12-0189.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miller, M. A., V. P. Ghate, and R. K. Zahn, 2012: The radiation budget of the West African Sahel and its controls: A perspective from observations and global climate models. J. Climate, 25, 59765996, https://doi.org/10.1175/JCLI-D-11-00072.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miller, N. B., M. D. Shupe, C. G. Cox, V. P. Walden, D. D. Turner, and K. S. Steffen, 2015: Cloud radiative forcing at Summit, Greenland. J. Climate, 28, 62676280, https://doi.org/10.1175/JCLI-D-15-0076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 66316 682, https://doi.org/10.1029/97JD00237.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Monna, W. and F. Bosveld, 2013: In higher spheres: 40 years of observations at the Cabauw site. KNMI Publication 232, 55 pp., http://publicaties.minienm.nl/documenten/in-higher-spheres-40-years-of-observations-at-the-cabauw-site.

  • Morcrette, J., H. W. Barker, J. N. Cole, M. J. Iacono, and R. Pincus, 2008: Impact of a new radiation package, McRad, in the ECMWF Integrated Forecasting System. Mon. Wea. Rev., 136, 47734798, https://doi.org/10.1175/2008MWR2363.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prata, A. J., 1996: A new long-wave formula for estimating downward clear-sky radiation at the surface. Quart. J. Roy. Meteor. Soc., 122, 11271151, https://doi.org/10.1002/qj.49712253306.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Protat, A., E. Schulz, L. Rikus, Z. Sun, Y. Xiao, and M. Keywood, 2017: Shipborne observations of the radiative effect of Southern Ocean clouds. J. Geophys. Res., 122, 318328, https://doi.org/10.1002/2016JD026061.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, Y.-J., X.-Q. Dong, B.-K. Xi, and Z.-H. Wang, 2013: Effects of clouds and aerosols on surface radiation budget inferred from DOE AMF at Shouxian, China. Atmos. Oceanic Sci. Lett., 6, 3943, https://doi.org/10.1080/16742834.2013.11447049.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salgueiro, V., M. J. Costa, A. M. Silva, and D. Bortoli, 2014: Variability of the daily-mean shortwave cloud radiative forcing at the surface at a midlatitude site in southwestern Europe. J. Climate, 27, 77697780, https://doi.org/10.1175/JCLI-D-13-00696.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shi, Y., and C. N. Long, 2002: Techniques and methods used to determine the best estimate of radiation fluxes at SGP central facility. Proc. 12th ARM Science Team Meeting, St. Petersburg, FL, U.S. Dept. of Energy, 12 pp., https://www.arm.gov/publications/proceedings/conf12/extended_abs/shi-y.pdf?id=52.

  • Shupe, M. D., and J. M. Intrieri, 2004: Cloud radiative forcing of the Arctic surface: The influence of cloud properties, surface albedo, and solar zenith angle. J. Climate, 17, 616628, https://doi.org/10.1175/1520-0442(2004)017<0616:CRFOTA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Siebesma, A. P., P. M. M. Soares, and J. A. Teixeira, 2007: Combined eddy-diffusivity mass-flux approach for the convective boundary layer. J. Atmos. Sci., 64, 12301248, https://doi.org/10.1175/JAS3888.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., 2005: Cloud feedbacks in the climate system: A critical review. J. Climate, 18, 237273, https://doi.org/10.1175/JCLI-3243.1.

  • Stephens, G. L., P. J. Webster, R. H. Johnson, R. Engelen, and T. L’Ecuyer, 2004: Observational evidence for the mutual regulation of the tropical hydrological cycle and tropical sea surface temperatures. J. Climate, 17, 22132224, https://doi.org/10.1175/1520-0442(2004)017<2213:OEFTMR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and et al. , 2012a: An update on Earth’s energy balance in light of the latest global observations. Nat. Geosci., 5, 691696, https://doi.org/10.1038/ngeo1580.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., M. Wild, P. W. Stackhouse Jr., T. L’Ecuyer, S. Kato, and D. Henderson, 2012b: The global character of the flux of downward longwave radiation. J. Climate, 25, 23292340, https://doi.org/10.1175/JCLI-D-11-00262.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791799, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1993: Representation of clouds in large-scale models. Mon. Wea. Rev., 121, 30403061, https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tompkins, A. M., K. Gierens, and G. Rädel, 2007: Ice supersaturation in the ECMWF Integrated Forecast System. Quart. J. Roy. Meteor. Soc., 133, 5363, https://doi.org/10.1002/qj.14.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Meijgaard, E., L. H. van Ulft, G. Lenderink, S. R. de Roode, L. Wipfler, R. Boers, and R. M. A. Timmermans, 2012: Refinement and application of a regional atmospheric model for climate scenario calculations of Western Europe. KvR Rep. 054/12, 44 pp., http://climexp.knmi.nl/publications/FinalReport_KvR-CS06.pdf.

  • Walsh, J. E., W. L. Chapman, and D. Portis, 2009: Arctic cloud fraction and radiative fluxes in atmospheric reanalyses. J. Climate, 22, 23162334, https://doi.org/10.1175/2008JCLI2213.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, P., W. H. Knap, P. Kuipers Munneke, and P. Stammes, 2009: Clear-sky shortwave radiative closure for the Cabauw Baseline Surface Radiation Network site, Netherlands. J. Geophys. Res., 114, D14206, https://doi.org/10.1029/2009JD011978.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, X., and J. R. Key, 2003: Recent trends in Arctic surface, cloud, and radiation properties from space. Science, 299, 17251728, https://doi.org/10.1126/science.1078065.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 103 103 15
PDF Downloads 54 54 7

Observing and Modelling the Surface Radiative Budget and Cloud Radiative Forcing at the Cabauw Experimental Site for Atmospheric Research (CESAR), the Netherlands, 2009–17

View More View Less
  • 1 Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
© Get Permissions
Restricted access

Abstract

A dataset of 9 years in duration (2009–17) of clouds and radiation was obtained at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Cloud radiative forcings (CRF) were derived from the dataset and related to cloud cover and temperature. Also, the data were compared with RCM output. Results indicate that there is a seasonal cycle (i.e., winter, spring, summer, and autumn) in longwave (CRF-LW: 48.3, 34.4, 30.8, and 38.7 W m−2) and shortwave (CRF-SW: −23.6, −60.9, −67.8, and −32.9 W m−2) forcings at CESAR. Total CRF is positive in winter and negative in summer. The RCM has a cold bias with respect to the observations, but the model CRF-LW corresponds well to the observed CRF-LW as a result of compensating errors in the difference function that makes up the CRF-LW. The absolute value of model CRF-SW is smaller than the observed CRF-SW in summer, mostly because of albedo differences. The majority of clouds from above 2 km are present at the same time as low clouds, so the higher clouds have only a small impact on CRF whereas low clouds dominate their values. CRF-LW is a function of fractional cloudiness. CRF-SW is also a function of fractional cloudiness, if the values are normalized by the cosine of solar zenith angle. Expressions for CRF-LW and CRF-SW were derived as functions of temperature, fractional cloudiness, and solar zenith angle, indicating that CRF is the largest when fractional cloudiness is the highest but is also large for low temperature and high sun angle.

ORCID: 0000-0003-4894-8434.

ORCID: 0000-0001-7004-5405.

ORCID: 0000-0003-0616-3145.

ORCID: 0000-0002-6479-0916.

ORCID: 0000-0003-4657-2904.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0828.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fred Bosveld, fred.bosveld@knmi.nl

Abstract

A dataset of 9 years in duration (2009–17) of clouds and radiation was obtained at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Cloud radiative forcings (CRF) were derived from the dataset and related to cloud cover and temperature. Also, the data were compared with RCM output. Results indicate that there is a seasonal cycle (i.e., winter, spring, summer, and autumn) in longwave (CRF-LW: 48.3, 34.4, 30.8, and 38.7 W m−2) and shortwave (CRF-SW: −23.6, −60.9, −67.8, and −32.9 W m−2) forcings at CESAR. Total CRF is positive in winter and negative in summer. The RCM has a cold bias with respect to the observations, but the model CRF-LW corresponds well to the observed CRF-LW as a result of compensating errors in the difference function that makes up the CRF-LW. The absolute value of model CRF-SW is smaller than the observed CRF-SW in summer, mostly because of albedo differences. The majority of clouds from above 2 km are present at the same time as low clouds, so the higher clouds have only a small impact on CRF whereas low clouds dominate their values. CRF-LW is a function of fractional cloudiness. CRF-SW is also a function of fractional cloudiness, if the values are normalized by the cosine of solar zenith angle. Expressions for CRF-LW and CRF-SW were derived as functions of temperature, fractional cloudiness, and solar zenith angle, indicating that CRF is the largest when fractional cloudiness is the highest but is also large for low temperature and high sun angle.

ORCID: 0000-0003-4894-8434.

ORCID: 0000-0001-7004-5405.

ORCID: 0000-0003-0616-3145.

ORCID: 0000-0002-6479-0916.

ORCID: 0000-0003-4657-2904.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0828.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fred Bosveld, fred.bosveld@knmi.nl

Supplementary Materials

    • Supplemental Materials (PDF 937.56 KB)
Save