Work Package 1
Operational and New measurements & Characterization
Participant : CNRS, Thales, DWD, DLR
WP leader : CNRS
Start month : 01 – End month : 46
Main contact: firstname.lastname@example.org
Re-evaluate the degree of supersaturation using high temporal measurements (5-10 minutes) combining simultaneous Lidar measurements of humidity and cirrus profiles.
Analyze the high-resolution water vapor data from Lidar, radiosonde, and aircraft to obtain the statistical variability that can be used in numerical simulations to represent the sub-grid variability.
Compile and harmonize the commercial aircraft water humidity and temperature measurements to allow their assimilation in numerical weather models.
Compare the different measurements in this WP with the existing satellite instruments to identify the missing information and the required resolution for future space platforms.
Description of work:
T1.1 Provide collocated water vapor/ice cloud Lidar from different sites
Systematic Lidar observations optimized for the upper troposphere and the lower stratosphere have been initiated within the NDACC network in France (44°N): Observatory of Haute-Provence, Sirta observatory at Palaiseau and Observatory at Clermont Ferrand and in a Tropical area (21°S): OPAR observatory at La Réunion.
Based on these observations, this task aims to provide collocated water vapour and ice cloud Lidar by:
- Consolidating Lidar instrumentation for systematic operations.
- Launching Flash sondes in collocation with Lidar
- Operating Lidar
- Implementing common Lidar retrieval algorithms.
- Identifying contrails and provide air-mass history through back-trajectories for temperature issues.
- Calculating the degree of supersaturation.
T1.2 Provide water vapor and temperature from AMDAR for assimilation
This tasks aims to provide the water vapour and temperature from AMDAR measurements for assimilation in WP2 by:
- Assessing AMDAR capabilities, in particular, when low absolute humidity < 30 ppmv and low temperature are concerned.
- Formulating measures to adapt AMDAR for cruise humidity measurements.
- Providing AMDAR or other appropriate data for assimilation.
T1.3 Provide full-sky ground-based images
This task aims to collect full-sky ground-based images to validate the contrail modelling by:
- Collecting images from observation sites.
- Preparing the data to formulate a database to be used by WP3 for validating the contrail modelling.
- Providing a link to the database to validate model contrail simulations.
T1.4 Analyze and compare humidity variability and contrail occurrence at cruise altitude from the different data sets, including space measurements
This task aims to identify the humidity variability associated to different measurements, which is necessary for WP3 in selecting the appropriate datasets for AI algorithm training. The task follows two steps by:
- Comparing the measured humidity with collocated IASI, Lidar/Calipso, GOES, and Modis observations.
- Providing statistics of the water vapor variability on a finer scale than numerical model grids.