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NAWDEX Overview Paper

  • Schäfler, A., G. Craig, H. Wernli, P. Arbogast, J.D. Doyle, R. McTaggart-Cowan, J. Methven, G. Rivière, F. Ament, M. Boettcher, M. Bramberger, Q. Cazenave, R. Cotton, S. Crewell, J. Delanoë, A. Dörnbrack, A. Ehrlich, F. Ewald, A. Fix, C.M. Grams, S.L. Gray, H. Grob, S. Groß, M. Hagen, B. Harvey, L. Hirsch, M. Jacob, T. Kölling, H. Konow, C. Lemmerz, O. Lux, L. Magnusson, B. Mayer, M. Mech, R. Moore, J. Pelon, J. Quinting, S. Rahm, M. Rapp, M. Rautenhaus, O. Reitebuch, C.A. Reynolds, H. Sodemann, T. Spengler, G. Vaughan, M. Wendisch, M. Wirth, B. Witschas, K. Wolf, and T. Zinner, 2018: The North Atlantic Waveguide and Downstream Impact Experiment. Bull. Amer. Meteor. Soc., 99, 1607‐1637, https://doi.org/10.1175/BAMS-D-17-0003.1

Papers on dynamics and predictability

  • Baumgart, M., and M. Riemer, 2019: Processes governing the amplification of ensemble spread in a medium‐range forecast with large forecast uncertainty. Quart. J. Roy. Meteor. Soc., 145, 3252-3270, https://doi.org/10.1002/qj.3617.
  • Binder, H., G. Rivière, P. Arbogast, K. Maynard, P. Bosser, B. Joly, and C. Labadie, 2021: Dynamics of forecast-error growth along cut-off S a n c h e z and its consequence for the prediction of a high-impact weather event over southern France. Quart. J. Roy. Meteor. Soc., 147, 3263-3285, https://doi.org/10.1002/qj.4127.
  • Blanchard, N., F. Pantillon, J.-P, Chaboureau, and J. Delanoë, 2021: Mid-level convection in a warm conveyor belt accelerates the jet stream, Weather Clim. Dynam., 2, 37-53, https://doi.org/10.5194/wcd-2-37-2021.
  • Blanchard, N., F. Pantillon, J.-P, Chaboureau, and J. Delanoë, 2020: Organization of convective ascents in a warm conveyor belt, Weather Clim. Dynam., 1, 617-634, https//doi.org/10.5194/wcd-1-617-2020.
  • Bland, J., S. Gray, J. Methven, J., R. and Forbes, 2021: Characterising extratropical near-tropopause analysis humidity biases and their radiative effects on temperature forecasts. Quart. J. Roy. Meteor. Soc., 147, 3878-3898, https://doi.org/10.1002/qj.4150.
  • Euler, C., M. Riemer, T. Kremer, and E. Schömer, 2019: Lagrangian Description of Air Masses Associated with Latent Heat Release in Tropical Storm Karl (2016) during Extratropical Transition. Mon. Wea. Rev., 147, 2656-2676, https://doi.org/10.1175/MWR-D-18-0422.1.
  • Flack, D. L. A., G. Rivière, I. Musat, R. Roehrig, S. Bony, J. Delanoë, Q. Cazenave, and J. Pelon, 2021: How Well do Models Represent the Development of Extra-Tropical Cyclones? Evaluation of Two General Circulation Models Against NAWDEX IOP 6 Observations, Weather Clim. Dynam., https://doi.org/10.5194/wcd-2-233-2021.
  • Harvey, B., J. Methven, C. Sanchez, and A. Schäfler, 2020: Diabatic generation of negative potential vorticity and its impact on the North Atlantic jet stream. Quart. J. Roy. Meteor. Soc., 146, 1477-1497, https://doi.org/10.1002/qj.3747.
  • Keil, C., L. Chabert, O. Nuissier, and L. Raynaud, 2021: Dependence of predictability of precipitation in the northwestern Mediterranean coastal region on the strength of synoptic control., Atmos. Chem. Phys., 20, 15851-15865, https://doi.org/10.5194/acp-20-15851-2020.
  • Kremer, T., E. Schömer, C. Euler, and M. Riemer, 2020: Cluster Analysis Tailored to Structure Change of Tropical Cyclones Using a Very Large Number of Trajectories, Mon. Wea. Rev., 148, 4209-4229, https://doi.org/10.1175/MWR-D-19-0408.1.
  • Krüger, K., A. Schäfler, M. Wirth, M. Weissmann, and G. C. and Craig, 2022. Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes. Atmos. Chem. Phys., 22, 15559-15577, https://doi.org/10.5194/acp-22-15559-2022.
  • Maddison, J.W., S.L. Gray, O. Martínez-Alvarado, and K.D. Williams, 2019: Upstream Cyclone Influence on the Predictability of Block Onsets over the Euro-Atlantic Region. Mon. Wea. Rev., 147, 1277‐1296, https://doi.org/10.1175/MWR-D-18-0226.1.
  • Maddison, J. W., S. L.Gray, O. Martínez-Alvarado, and K. D. Williams, 2020: Impact of model upgrades on diabatic processes in extratropical cyclones and downstream forecast evolution. Quart. J. Roy. Meteor. Soc., 146, 1322-1350, https://doi.org/10.1002/qj.3739.
  • Martínez-Alvarado, O., and C. Sanchez, 2020: Examining model error in potential temperature and potential vorticity weather forecasts at different lead times. Quart. J. Roy. Meteor. Soc., 146, 1264-1280, https://doi.org/10.1002/qj.3736.
  • Mazoyer, M., D. Ricard, G. Rivière, J. Delanë, S. Riette, C. Augros, M. Borderies, and B. Vié, 2023: Impact of Mixed-Phase Cloud Parameterization on Warm Conveyor Belts and Upper-Tropospheric Dynamics. Mon. Wea. Rev., 151, 1073-1091, https://doi.org/10.1175/MWR-D-22-0045.1.
  • Mazoyer M., D. Ricard, G. Rivière, J. Delanoë, P. Arbogast, B. Vié, C. Lac, Q. Cazenave, and J. Pelon. 2021: Microphysics Impacts on the Warm Conveyor Belt and Ridge Building of the NAWDEX IOP6 Cyclone. Mon. Wea. Rev., 149, 3961-3980, https://doi.org/10.1175/MWR-D-21-0061.1.
  • Oertel, A., M. Boettcher, H. Joos, M. Sprenger, H. Konow, M. Hagen, and H. Wernli: 2019: Convective activity in an extratropical cyclone and its warm conveyor belt a case study combining observations and a convection-permitting model simulation. Quart. J. Roy. Meteor. Soc. 145, 1406‐1426, doi:10.1002/qj.3500 .
  • Oertel, A., M. Boettcher, H. Joos, M. Sprenger, and H. Wernli, 2020: Potential vorticity structure of embedded convection in a warm conveyor belt and its relevance for large-scale dynamics. Weather Clim. Dynam., 1, 127-153, https://doi.org/10.5194/wcd-1-127-2146020.
  • Oertel, A., M. Sprenger, H. Joos, M. Boettcher, H. Konow, M. Hagen, and H. Wernli, 2021: Observations and simulations of intense convection embedded in a warm conveyor belt - how ambient vertical wind shear determines the dynamical impact. Weather Clim. Dynam., 2, 89-110, https://doi.org/10.5194/wcd-2-89-2021.
  • Oertel, A., and S. Schemm, 2021: Quantifying the circulation induced by convective clouds in kilometer-scale simulations. Quart. J. Roy. Meteor. Soc., 1752 1766, https://doi.org/10.1002/qj.3992.
  • Rivière, G., M. Wimmer, P. Arbogast, J.-M. Piriou, J. Delanoë, C. Labadie, Q. Cazenave, and J. Pelon, 2021: The impact of deep convection representation in a global atmospheric model on the warm conveyor belt and jet stream during NAWDEX IOP6. Weather Clim. Dynam., 2, 1011-1031, https://doi.org/10.5194/wcd-2-1011-2021
  • Saffin, L., J. Methven, J. Bland, B. Harvey, and C. Sanchez, 2021: Circulation conservation in the outflow of warm conveyor belts and consequences for Rossby wave evolution. Quart. J. Roy. Meteor. Soc., 147, 3587-3610, https://doi.org/10.1002/qj.4143.
  • Sanchez, C., J. Methven, S. Gray, M. Cullen, 2020: Linking rapid forecast error growth to diabatic processes, Q. J. R. Meteorol. Soc., 146, 3548-3569,https://doi.org/10.1002/qj.3861.
  • Schäfler, A., B. Harvey, J. Methven, J.D. Doyle, S. Rahm, O. Reitebuch, F. Weiler, and B. Witschas, 2020: Observation of jet stream winds during NAWDEX and characterization of systematic meteorological analysis errors. Mon. Wea. Rev., 148, 2889-2907, https://doi.org/10.1175/MWR-D-19-0229.1
  • Schäfler, A., F. Ewald, and M. Rautenhaus, 2020: Die Vermessung von Zyklonen, promet, 103, 25-32, https://www.dwd.de/DE/leistungen/pbfb_verlag_promet/archiv/archiv_promet.htm.
  • Schindler, M., M. Weissmann, A. Schäfler, and G. Radnoti, 2020: The Impact of Dropsonde and Extra Radiosonde Observations during NAWDEX in Autumn 2016. Mon. Wea. Rev. , 148, 809-824, https://doi.org/10.1175/MWR-D-19-0126.1.
  • Steinfeld, D., M. Boettcher, R. Forbes, and S. Pfahl, 2020: The sensitivity of atmospheric blocking to upstream latent heating numerical experiments, Weather Clim. Dynam., 1, 405-426, https://doi.org/10.5194/wcd-1-405-2020.
  • Wimmer, M., G. Rivière, P. Arbogast, J.-M. Piriou, J. Delanë,C. Labadie, Q. Cazenave, and J. Pelon, 2022: Diabatic processes modulating the vertical structure of the jet stream above the cold front of an extratropical cyclone: sensitivity to deep convection schemes. Weather Clim. Dynam., 3, 863-882, https://doi.org/10.5194/wcd-3-863-2022.
  • Wolf, K., A. Ehrlich, M. Mech, R. J. Hogan, and M. Wendisch, 2020: Evaluation of ECMWF Radiation Scheme Using Aircraft Observations of Spectral Irradiance above Clouds. J. Atmos. Sci., 77, 2665-2685, https://doi.org/10.1175/JAS-D-19-0333.1.

Data oriented papers and other topics

  • Bosser, P. and O. Bock, 2021: IWV retrieval from ground GNSS receivers during NAWDEX, Adv. Geosci., 55, 1322, https://doi.org/10.5194/adgeo-55-13-2021.
  • Bramberger, M., A. Dörnbrack, H. Wilms, F. Ewald, and R. Sharman, 2020: Mountain-Wave Turbulence Encounter of the Research Aircraft HALO above Iceland. J. Appl. Meteor. Climatol., 59, 567588, https://doi.org/10.1175/JAMC-D-19-0079.1.
  • Ewald, F., S. Groß, M. Wirth, J. Delanoë, S. Fox, and B. Mayer, 2021: Why we need radar, lidar, and solar radiance observations to constrain ice cloud microphysics. Atmos. Meas. Tech., 14, 5029-5047, https://doi.org/10.5194/amt-14-5029-2021.
  • Konow, H., M. Jacob, F. Ament, S. Crewell, F. Ewald, M. Hagen, L. Hirsch, F. Jansen, M. Mech, and B. Stevens, 2018: A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP), Earth Syst. Sci. Data, 11, 921-934, https://www.earth-syst-sci-data.net/11/921/2019/.
  • Mech, M., M. Maahn, S. Kneifel, D. Ori, E. Orlandi, P. Kollias, V. Schemann, and S. Crewell, 2020: PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere, Geosci. Model Dev., 13, 4229-4251, https://doi.org/10.5194/gmd-13-4229-2020.
  • Lux, O., C. Lemmerz, F. Weiler, U. Marksteiner, B. Witschas, S. Rahm, A. Schäfler, A., and O. Reitebuch, 2018: Airborne wind lidar observations over the North Atlantic in 2016 for the pre-launch validation of the satellite mission Aeolus, Atmos. Meas. Tech., 11, 3297-3322, https://doi.org/10.5194/amt-11-3297-2018.
  • Schumann, U., 2019: The Horizontal Spectrum of Vertical Velocities near the Tropopause from Global to Gravity Wave Scales. J. Atmos. Sci., 76, 3847-3862, https://doi.org/10.1175/JAS-D-19-0160.1.
  • Wilms, H., M. Bramberger, and A. Dörnbrack, 2020: Observation and simulation of mountain wave turbulence above Iceland: Turbulence intensification due to wave interference. Q. J. R. Meteorol. Soc., 146, 3326-3346. https://doi.org/10.1002/qj.3848..
  • Witschas, B., C. Lemmerz, O. Lux, U. Marksteiner, O. Reitebuch, and A. Schäfler, 2021: Airborne temperature profiling in the troposphere during daytime by lidar utilizing Rayleigh-Brillouin scattering., Opt. Lett., 46, 4132-4135,https://doi.org/10.1364/OL.431350.

Visualization research

  • Kern, M., T. Hewson, F. Sadlo, R. Westermann and M. Rautenhaus, 2018: Robust Detection and Visualization of Jet-Stream Core Lines in Atmospheric Flow. IEEE Transactions on Visualization and Computer Graphics, 24, pp. 893-902, doi: 10.1109/TVCG.2017.2743989.
  • Kern, M., T. Hewson, A. Schäfler, R. Westermann and M. Rautenhaus, 2018: Interactive 3D Visual Analysis of Atmospheric Fronts IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2018.2864806.
  • Kumpf, A., B. Tost, M. Baumgart, M. Riemer, R. Westermann and M. Rautenhaus, 2018: Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses, IEEE Transactions on Visualization and Computer Graphics, 24, pp. 109-119, Jan. 2018. doi: 10.1109/TVCG.2017.2745178 .
  • Kumpf, A., M. Rautenhaus, M. Riemer and R. Westermann, 2018: Visual Analysis of the Temporal Evolution of Ensemble Forecast Sensitivities. IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2018.2864901.

Related Articles

  • Boettcher, M., A. Schäfler, M. Sprenger, H. Sodemann, S. Kaufmann, C. Voigt, H. Schlager, D. Summa, P. Di Girolamo, D. Nerini, U. Germann, and H. Wernli, 2021: Lagrangian matches between observations from aircraft, lidar and radar in a warm conveyor belt crossing orography. Atmos. Chem. Phys., 21, 5477-5498, https://doi.org/10.5194/acp-21-5477-2021>.
  • Fox, S., 2021: An Evaluation of Radiative Transfer Simulations of Cloudy Scenes from a Numerical Weather Prediction Model at Sub-Millimetre Frequencies Using Airborne Observations. Remote Sens., 12(17):2758, https://doi.org/10.3390/rs12172758>.
  • Craig, G. C., A. H. Fink, C. Hoose, T. Janjic, P. Knippertz, A. Laurian, S. Lerch, B. Mayer, A. Miltenberger, R. Redl, M. Riemer, K. I. Tempest, and V. Wirth, 2021. Waves to Weather: Exploring the limits of predictability of weather, Bull. Amer. Meteor. Soc., 1102, E2151-E2164, https://doi.org/10.1175/BAMS-D-20-0035.1.
  • Stevens, B., F. Ament, S. Bony, S. Crewell, F. Ewald, S. Gross, A. Hansen, L. Hirsch, M. Jacob, T. Kölling, H. Konow, B. Mayer, M. Wendisch, M. Wirth, K. Wolf, S. Bakan, M. Bauer-Pfundstein, M. Brueck, J. Delanoë, A. Ehrlich, D. Farrell, M. Forde, F. Gödde, H. Grob, M. Hagen, E. Jäkel, F. Jansen, C. Klepp, M. Klingebiel, M. Mech, G. Peters, M. Rapp, A.A. Wing, and T. Zinner, 2019: A High-Altitude Long-Range Aircraft Configured as a Cloud Observatory: The NARVAL Expeditions. Bull. Amer. Meteor. Soc., 100, 1061-1077, https://doi.org/10.1175/BAMS-D-18-0198.1.
  • Wick, G. A., J. P. Dunion, P. G. Black, J. R. Walker, R. D. Torn, A. C. Kren, A. Aksoy, H. Christophersen, L. Cucurull, B. Dahl, J. M. English, K. Friedman, T. R. Peevey, K. Sellwood, J. A. Sippel, V. Tallapragada, J. Taylor, H. Wang, R. E. Hood, and P. Hall, 0: NOAA'S SENSING HAZARDS WITH OPERATIONAL UNMANNED TECHNOLOGY (SHOUT) EXPERIMENT: Observations and Forecast Impacts. Bull. Amer. Meteor. Soc., 0, https://doi.org/10.1175/BAMS-D-18-0257.1.
  • Witschas, B., C. Lemmerz, A. Geiß, O. Lux, U. Marksteiner, S. Rahm, O. Reitebuch, and F. Weiler, 2021: First validation of Aeolus wind observations by airborne Doppler wind lidar measurements. Atmos. Meas. Tech., 13, 2381-2396, https://doi.org/10.5194/amt-13-2381-2020.

Miscellaneous

© 2015 by Institute for Atmospheric and Climate Science, ETH Zurich