Journal article

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

Flentje H, Doernbrack A, Fix A, Ehret G, Holm E ...see all

ATMOSPHERIC CHEMISTRY AND PHYSICS, vol. 7, issue 19 (2007) pp. 5033-5042

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Three extended airborne Differential Absorption Lidar (DIAL) sections of
tropospheric water vapour across the tropical and sub-tropical Atlantic
in March 2004 are compared to short-term forecasts of the European
Centre for Medium Range Weather Forecasts (ECMWF). The humidity fields
between 28 degrees S and 36 degrees N exhibit large inter air-mass
gradients and reflect typical transport patterns of low- and
mid-latitudes like convection (e. g. Hadley circulation), subsidence and
baroclinic development with stratospheric intrusion. 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. Backtrajectories 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 degrees resolution (T799/L91), the
correlation ranges from 0.69 to 0.92. Locally, large differences occur
due to comparably small spatial shifts in presence of strong gradients.
Systematic deviations are found associated with specific atmospheric
domains. 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 boundaries ( transport) is discussed with repect to scales and
the representativity of the 2-D sections for the 3-D humidity field. The
normalized bias of the model with respect to the observations is 6{%},
11{%} and 0{%} (moist model biases) for the three along-flight sections,
whereby however the lowest levels are excluded.

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  • H Flentje

  • A Doernbrack

  • A Fix

  • G Ehret

  • E Holm

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