The following articles are based upon work from COST Action TOPROF (ES1303), supported by COST (European Cooperation in Science and Technology):

 

2017

  1. Bernet, L., F. Nava-Guzmán, N. Kampfer: The efect of cloud liquid water on tropospheric temperature retrievals from microwave measurements, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2017-153, 2017. Online.
  2. De Angelis, F., Cimini, D., Löhnert, U., Caumont, O., Haefele, A., Pospichal, B., Martinet, P., Navas-Guzmán, F., Klein-Baltink, H., Dupont, J.-C., and Hocking, J.: Long term Observations minus Background monitoring of ground-based microwave radiometer network. Part 1: Brightness Temperatures, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2017-112, in review, 2017. Online.
  3. Martinet, P., Cimini, D., De Angelis, F., Canut, G., Unger, V., Guillot, R., Tzanos, D., and Paci, A.: Combining ground-based microwave radiometer and the AROME convective scale model through 1DVAR retrievals in complex terrain: an Alpine Valley case study, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-144, accepted, 2017. Online.
  4. Tuononen, M., O’Connor, E.J., Sinclair, V.A., and Vakkari,V.: Low-level jets over Utö, Finland, based on Doppler lidar observations. J. Appl. Meteor. Climatol., https://doi.org/10.1175/JAMC-D-16-0411.1, accepted, 2017.
  5. Bravo-Aranda, J. A., de Arruda Moreira, G., Navas-Guzmán, F., Granados-Muñoz, M. J., Guerrero-Rascado, J. L., Pozo-Vázquez, D., Arbizu-Barrena, C., Olmo Reyes, F. J., Mallet, M., and Alados Arboledas, L.: A new methodology for PBL height estimations based on lidar depolarization measurements: analysis and comparison against MWR and WRF model-based results, Atmos. Chem. Phys., 17, 6839-6851, 2017. Online.
  6. Pattantyús-Ábrahám, M., I. Mattis, R. Begbie, J. A. Bravo-Aranda, M. Brettle, J. Cermak, M.-A. Drouin, A. Geiß, U. Görsdorf, A. Haefele, M. Haeffelin, M. Hervo, K. Komínková, R. Leinweber, C. Münkel, K. Pönitz, J. Vande Hey, F. Wagner, and M. Wiegner: The Dataset of the CeiLinEx 2015 Ceilometer-Inter-comparison Experiment, Version v001, doi:10.5676/DWD/CEILINEX2015, 2017. Online dataset.
  7. Rottner, L., Baehr, C., Dabas, A., Hammoud, L., Stochastic Method for Turbulence Estimation from Doppler Lidar Measurements, Journal of Applied Remote Sensing, accepted, 2017.

 

2016

  1. Navas-Guzmán, F., Kämpfer, N., and Haefele, A.: Validation of brightness and physical temperature from two scanning microwave radiometers in the 60 GHz O2 band using radiosonde measurements, Atmos. Meas. Tech., 9, 4587-4600, doi:10.5194/amt-9-4587-2016, 2016. Online
  2. Görsdorf et al., The ceilometer inter-comparison campaign CeiLinEx2015 - Cloud detection and cloud base height, Technical Conference on Meteorological and Environmental Instruments and Methods of Observation (TECO), 27-30 September 2016, MADRID, Extended Abstract
  3. Caumont O., D. Cimini, U. Löhnert, L. Alados-Arboledas, R. Bleisch, F. Buffa, M. E. Ferrario, A. Haefele, T. Huet, F. Madonna, G. Pace, 2016:  Assimilation of humidity and temperature observations retrieved from ground-based microwave radiometers into a convective-scale model, Quart. Jour. Roy. Met. Soc. Online.
  4. De Angelis, F., Cimini, D., Hocking, J., Martinet, P., and Kneifel, S.: RTTOV-gb – adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations, Geosci. Model Dev., 9, 2721-2739, doi:10.5194/gmd-9-2721-2016, 2016. Online
  5. Gryning S.E., Floors R., Peña A., Batchvarova E., and Brümmer B., 2016: Weibull wind-speed distribution parameters derived from a combination of wind-lidar and tall-mast measurements over land, coastal and marine sites, Boundary-Layer Meteorol. 159, 329–348, doi:10.1007/s10546-015-0113-x Online
  6. Haeffelin M., Laffineur Q., Bravo-Aranda J.-A., Drouin M.-A., Casquero-Vera J.-A., Dupont J.-C., and De Backer H., 2016: Radiation fog formation alerts using attenuated backscatter power from automatic lidars and ceilometers, Atmos. Meas. Tech., doi:10.5194/amt-9-5347-2016, 2016. Online
  7. Hervo, M., Poltera, Y., and Haefele, A.: An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers, Atmos. Meas. Tech., 9, 2947-2959, doi:10.5194/amt-9-2947-2016, 2016. Online
  8. Kotthaus, S., O'Connor, E., Münkel, C., Charlton-Perez, C., Gabey, A. M., and Grimmond, C. S. B.: Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 Ceilometers, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-87, in review, 2016. Online
  9. Lotteraner C. & Piringer M., 2016: Mixing-height time series from operational ceilometer aerosol-layer heights. Boundary-Layer Meteorology, doi:10.1007/s10546-016-0169-2 Online
  10. Thobois L., O’Connor E, Preissler J., Petersen G., Investigation of the capabilities and benefits of Doppler lidars in an operational European observation network: the TOPROF European Action, Technical Conference on Meteorological and Environmental Instruments and Methods of Observation (TECO), Madrid, 27-30 September 2016, Online

2015

  1. Cimini, D., Nelson, M., Güldner, J., and Ware, R.: Forecast indices from a ground-based microwave radiometer for operational meteorology, Atmos. Meas. Tech., 8, 315-333, doi:10.5194/amt-8-315-2015, 2015. Online 
  2. Illingworth, A., D. Cimini, C. Gaffard, M. Haeffelin, V. Lehmann, U. Loehnert, E. O'Connor, D. Ruffieux, Exploiting Existing Ground-Based Remote Sensing Networks To Improve High Resolution Weather Forecasts, Bull. Amer. Meteor. Soc. doi: 10.1175/BAMS-D-13-00283.1, February, 2015. Online