It is well known that moisture data from aircrafts are extremely important for Numerical Weather Prediction (NWP). This work is carry out under the CCG Search and Rescue New Initiative Funds (SAR NIF).

The purpose of this study is to examine the impact of moisture data from aircrafts into the NWP system at the Canadian Meteorological Centre (CMC).

The data are collected from aircrafts participating in the Great Lakes Fleet Experiment (GLFE), equipped with Tropospheric Airborne Meteorological Data Report (TAMDAR) instruments measuring relative humidity, and from the UPS AMDAR and European Lufthansa aircrafts, equipped with the second generation water vapor sensing system (WVSSII). The moisture variables that we use are the dew point depression and the logarithm of the specific humidity. The latter is the control variable in the CMC analysis program. The monitoring procedure consists on the statistics of observation minus first guess for moisture observations and includes the possibility of evaluating the quality of all data as well as of individual aircraft.

A set of observing system experiments were run to measure the impact of aircraft moisture data in the global and regional data assimilation cycles. The impact has been assessed in both winter and summer periods. The results presented here show a slight advantage using moisture data from both types of sensors.

We would like to acknowledge the financial support of the Government of Canada for this initiative through the CCG Search and Rescue NEW Initiatives Funds and AirDat campany for providing TAMDAR data.