Memorandum of Understanding:

Forward models and metrics for model evaluation.

Achievements:

• WG1 has investigated the impact of ALC network observations on improving weather forecast. Preliminary studies have been made at ECMWF of assimilating ALC data on smoke from Canadian forest fires: http://www.toprof.imaa.cnr.it/images/toprof/short_term_scientific_mission/STSM_Scientific_Report_Hervo.pdf
• WG2 has investigated the use of DWL measurements for evaluation of wind-speed prediction by numerical weather prediction models: http://www.toprof.imaa.cnr.it/images/toprof/short_term_scientific_mission/STSM_Scientific_Report_EkaterinaBatchvarova.pdf
• WG3 developed a fast forward model suitable for the direct assimilation of ground-based MWR, RTTOVgb: https://doi.org/10.5194/gmd-9-2721-2016
• WG3 has shown an analysis of the MWR DA potential impact for improving the forecasts of heavy rainfall events in the Mediterranean: http://onlinelibrary.wiley.com/doi/10.1002/qj.2860/pdf

Memorandum of Understanding:

Standardised retrieval algorithms for ceilometers, Doppler lidars and MWRs so that key atmospheric properties (clouds, humidity, temperature, aerosol, and winds) can be derived together with their errors.

Achievements:

• WG1 developed a fog forecasting technique. Trials at Paris, Munich and Vienna airports are on-going: http://www.lmd.polytechnique.fr/~madrouin/parafog/
• WG1 organized an ALC intercomparison campaign and dataset (http://ceilinex2015.de/). This unprecedented dataset is used for investigations concerning calibration, uncertainty estimates, cloud detection, and aerosol retrievals.
• WG2 has developed DWL algorithms for characterising boundary layer winds, low level jets, turbulence, wind gustiness, and distorted airflow around isolated islands. FMI (Finnish Meteorological Institute) is studying their application for improving forecasts in an operational environment, and other stations have implemented these algorithms to display products in real-time, e.g. http://macehead.nuigalway.ie/rt/lidar.html
• WG3 has developed two standardised retrieval processing: a multivariate regression (available through mwr_pro at ftp://gop.meteo.unikoeln.de/pub/loehnert/mwr_data_flow/) and a 1DVAR optimal estimation (https://github.com/PaulineMartinet/SAF1DVARgb_GIT)

Memorandum of Understanding:

Standardised formats and data protocols, so that observations can be exchanged in near real time between the various NMHSs across Europe.

Achievements:

• WG1 developed software for ALC standardised format (RAW2L1). RAW2L1 can be accessed from: https://sourcesup.renater.fr/projects/sirta-raw2l1/
• WG2 developed DWL standardised formats and data protocols. E-PROFILE is distributing data from a few DWLs in Germany on an experimental basis; in 2018 this will be extended and become operational.
• WG3 developed an harmonized MWR data processing chain (mwr_pro), providing quality-controlled level 1 and level 2. mwr_pro is available at: ftp://gop.meteo.unikoeln.de/pub/loehnert/mwr_data_flow/
• WG3 has submitted a proposal to EUMETNET for the inclusion of MWR into the next phase of E-PROFILE project.