Group seminar on 20. December, 14:15 CET

Comparison of temperature and wind observations in the tropics in a perfect-model, global EnKF data assimilation system

Lanqian Li

 Flow-dependent errors in tropical analyses and short-range forecasts are analysed using the global observing system simulation experiments assimilating only temperature, only winds, and both data types by the ensemble Kalman filter (EnKF) data assimilation with a perfect model. The idealised, homogeneous observation network provides profiles of wind and temperature data from the nature run for January 2018 using the NCAR CESM model forced by the observed sea surface temperature.

In all experiments, the largest errors are found in the regions of the strong vertical and longitudinal gradients in the background wind, especially in the upper troposphere and lower stratosphere over the Indian ocean and Maritime continent. The tropical horizontal correlation scales are on average short throughout the troposphere, just several hundred km. For the wind variables, the correlations have twice shorter horizontal scales in the precipitating than in the non-precipitating regions. The correlations are elongated vertically in precipitating regions, especially for the wind variables. Strong positive correlations between temperature and specific humidity in the precipitating regions are explained using the Clausius-Clapeyron equation.

The key result is that the assimilation of abundant wind observations in a perfect model makes the temperature data in the tropics largely uninformative. Furthermore, the assimilation of wind data reduces the background errors in specific humidity twice as much as the assimilation of temperature observations.