Evaluation of ECMWF water vapour fields by airborne differential absorption lidar measurements: a case study between Brazil and Europe

Three extended airborne Differential Absorption Lidar (DIAL) sections of tropospheric water vapour across the tropical and sub-tropical Atlantic in March 2004 are com- pared to short-term forecasts of the European Centre for Medium Range Weather Forecasts (ECMWF). The humidity fields between 28 S and 36 N exhibit large inter air-mass gradients and reflect typical transport patterns of low- and mid-latitudes like convection (e.g. Hadley circulation), sub- sidence and baroclinic development with stratospheric intru- sion. These processes re-distribute water vapour vertically such that locations with extraordinary dry/moist air-masses are observed in the lower/upper troposphere, respectively. The mixing ratios range over 3 orders of magnitude. Back- trajectories are used to trace and characterize the observed air-masses. Overall, the observed water vapour distributions are largely reproduced by the short-term forecasts at 0.25 reso- lution (T799/L91), the correlation ranges from 0.69 to 0.92. Locally, large differences occur due to comparably small spa- tial shifts in presence of strong gradients. Systematic de- viations are found associated with specific atmospheric do- mains. The planetary boundary layer in the forecast is too moist and to shallow. Convective transport of humidity to the middle and upper troposphere tends to be overestimated. Potential impacts arising from data assimilation and model physics are considered. The matching of air-mass bound- aries (transport) is discussed with repect to scales and the rep- resentativity of the 2-D sections for the 3-D humidity field. The normalized bias of the model with respect to the obser- vations is 6%, 11% and 0% (moist model biases) for the three along-flight sections, whereby however the lowest levels are excluded.

[1]  D. Althausen,et al.  Correction Method for RS80-A Humicap Humidity Profiles and Their Validation by Lidar Backscattering Profiles in Tropical Cirrus Clouds , 2005 .

[2]  David W. Keith,et al.  The effect of climate change on ozone depletion through changes in stratospheric water vapour , 1999, Nature.

[3]  A. Benedetti,et al.  Validation of ECMWF global forecast model parameters using GLAS atmospheric channel measurements , 2005 .

[4]  Mark Lawrence,et al.  The chemical weather , 2005 .

[5]  Lawrence P. Giver,et al.  Visible and near-infrared H216O line intensity corrections for HITRAN-96 , 2000 .

[6]  C. Kiemle,et al.  Airborne all-solid-state DIAL for water vapour measurements in the tropopause region: system description and assessment of accuracy , 2002 .

[7]  K. Trenberth,et al.  Earth's annual global mean energy budget , 1997 .

[8]  Piers M. Forster,et al.  Radiative forcing and temperature trends from stratospheric ozone changes , 1997 .

[9]  P. V. Velthoven,et al.  Comparison of Water Vapor Measurements with Data Retrieved from ECMWF Analyses during the POLINAT Experiment , 1997 .

[10]  S. Solomon,et al.  On the composition and optical extinction of particles in the tropopause region , 1999 .

[11]  Franz Rohrer,et al.  Strong correlation between levels of tropospheric hydroxyl radicals and solar ultraviolet radiation , 2006, Nature.

[12]  Heini Wernli,et al.  A Lagrangian‐based analysis of extratropical cyclones. I: The method and some applications , 1997 .

[13]  Heini Wernli,et al.  An intercomparison of results from three trajectory models , 2001 .

[14]  Klaus Gierens,et al.  Ice supersaturation in the ECMWF integrated forecast system , 2007 .

[15]  S. Hagemann,et al.  Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA40 , 2004 .

[16]  P. Forster,et al.  Radiation balance of the tropical tropopause layer , 2004 .

[17]  Moustafa T. Chahine,et al.  The hydrological cycle and its influence on climate , 1992, Nature.

[18]  Gerhard Ehret,et al.  Low stratospheric water vapor measured by an airborne DIAL , 1999 .

[19]  B. Luo,et al.  Water activity as the determinant for homogeneous ice nucleation in aqueous solutions , 2000, Nature.

[20]  Gerhard Ehret,et al.  Low stratospheric water vapor measured by an airborne DIAL , 1999, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[21]  Jean-Noël Thépaut,et al.  Analysis and forecast impact of the main humidity observing systems , 2007 .

[22]  Keith P. Shine,et al.  Sensitivity of the Earth's climate to height-dependent changes in the water vapour mixing ratio , 1991, Nature.

[23]  M. Wirth,et al.  Water vapor heterogeneity related to tropopause folds over the North Atlantic revealed by airborne water vapor differential absorption lidar , 2005 .

[24]  P. Bauer,et al.  SSM/I Radiance Assimilation at ECMWF , 2003 .

[25]  Syukuro Manabe,et al.  Thermal Equilibrium of the Atmosphere with a Given Distribution of Relative Humidity , 1967 .

[26]  J. Klett,et al.  Microphysics of Clouds and Precipitation , 1978, Nature.

[27]  P. Bauer,et al.  Variational retrieval of temperature and humidity profiles using rain rates versus microwave brightness temperatures , 2004 .