1. Cold wave of February 2018 above Europe observed by rotational Raman lidar
Alexandre Baron, Patrick Chazette, Julien Totems
LSCE – IPSL, Gif-sur-Yvette, France

2. Presentation plan The Weather and Aerosol LIdar (WALI)
Observations in February 2018
Its calibration against radiosonde
Origins of the air masses
Associated weather situations
Comparison with:
Model reanalyses
Spaceborne observations

3. WALI, its characteristics and assets
Fig. 1: WALI
60 cm
130 cm
Fig. 2: The Mobile Atmospheric Station (MAS)
Eye safe lidar operating at 355 nm
Compact (Fig. 1) and transportable (Fig. 2)
Aerosols, WVMR, Temperature
Short overlap function (~ 200 m)
Temporal resolution 30 min
Vertical resolution 100 m
T uncertainty < 1 K
T profile up to 6 km / 2 km
Nigh / Day
Using lens, it is compact, as shown in this picture
It is also easily transportable in an instrumented truck named MAS for « mobile atmospheric station » represented here
WALI measures aerosols optical properties, water vapor mixing ratio and atmospheric temperature with a short overlap function, full overlap at about 2 hundred meters
For temperature measurements, error is below 1 k up to 5 km of altittude for profiles averaged 30min with a spatial resolution of 100m
This system has proven its worth in different campaigns where you can find more specifications on this lidar system especially for the Aerosol and the WVMR
Involvement in former field studies: HyMeX and ChArMEx (P.Chazette et al, 2014; AMT), PARCS (J.Totems et al, 2019; QJRMS) …

4. WALI, its temperature measurements in February 2018
Cold air
Free troposphere
Warm air
PBL Top
Cold air advection
PBL
Temperature in color in the interval -20 to 5 Celsius degree, in function of altitude from the 21 Feb to the 27 Feb 2018
In the PBL = diurnal cycle with thermal inertia of atmosphere
Two air masses stand out: a warm one on the 24 Feb and a very cold one on the 26 and 27 of Feb

5. Calibration of the Rotational Raman channel
𝑄 𝑇,𝑧 = 𝑆 𝑅𝑅2 𝑇,𝑧 𝑆 𝑅𝑅1 𝑇,𝑧 =𝑓(𝑇)
Night time radiosondings:
Meteo-France site of Trappes ~15 km from the lidar
[1]
20deg smoothed
RMSN Z < 6 km = 0.96 K
RMSD Z < 3 km = 1.14 K
[1] A. Behrendt, “Temperature measurement with Lidar,” in Lidar Range-Resolved Optical Remote Sensing of the Atmosphere (C. Weitkamp, 2005), Ch. 10.

6. Origins of the air masses and synoptic weather situation
Backward Ensemble mode:
Every 6h from 26/ UTC to 28/ UTC
Every 250m from 1250m to 2750m
77 runs ; 5 days calculation H
Lagrangian model HYSPLIT from NOAA H L L L
Backward Ensemble mode:
24/02 at 0000, 0600 and 1200 UTC
Starting altitude: 2000 m (AGL)
3 days calculation
Blocked weather situation with an high above Scandinavia = polar air from Siberia guided through Europe to a low off the coast of Portugal

7. Consistency with modeling
Noter quelques differences et faire seulement 2 à trois profiles max
ECMWF ERA5 reanalysis (hourly, 33 pressure levels)

8. Lidar – Model differences
(unbiased)
PBL Top issue
Correlation > 0.92
Max(Cor) > 0.99 around Z = 2 km
Mean bias = K
Root Mean Square
Deviation (unbiased) ~ 1 K

9. Consistency with modelingP1 P2
Noter quelques differences et faire seulement 2 à trois profiles max

10. Comparison of lidar, ERA5 and AIRS profiles
AIRS/AQUA transit  AIRS Level 3 daily Temperature product
Daily average of Lidar and ERA5 data
Weighting function
of AIRS is peaked above 1 km agl
AIRS does not observed the slope discontinuity of T(z) (P1)
Good agreement of the 3 datasets, for a ~constant T gradient (P2)
Profile journalier plutot que horaire

11. Conclusions & Perspectives
Successful calibration with RS (RMS ~1 K). Differences induced by Lidar and RS not co-located  can be improved using ultra-light aircraft and/or UAV to calibrate the RR channel right on site
Complementarity with spaceborne measurements (e.g. AIRS, IASI B&C) especially where spaceborne spectrometers failed, in the low troposphere (PBL)
Suitable tool for validation of next generation of spaceborne spectrometers (e.g. IASI NG)
Reliable performances for model assimilation of lidar network into meteorological model
Unmanned aerial vehicul