1. The summer 2017 seen by LMDZOR and two French instrumented sites
Yanfeng ZHAO, Frederique CHERUY
Guylaine CANUT, William MAUREL and Jean-charles DUPONT
Labex: LP2: Understanding climate variations since the early 20th century (LMD, LATMOS, METIS, LOCEAN,LSCE)
Approach: Construct and use climate reconstruction starting in the mid of the 20thcentury and produced with the same model as the one used for the climate projections (IPSL-CM6)

2. Model (zoomed and nudged):
Observation:
SIRTA 1 hour mean data (surface temperature, air temperature, shortwave radiation, soil moisture content, soil temperature and relative humidity)
Toulouse meteopole-flux data
Atmospheric soundings from Wyoming weather web ( for Trappes ( 48.76N/2.00E, 2003 and 2017) and Voronez (51.65N/39.25E, 2010)
Model (zoomed and nudged):
CMIP6_V6010v3, zoomed and nudged, COSY project (June-August, 2017)
CMIP6_V6012 ( Mega Heatwaves : 2003 and 2010) (Nudged, regular grid, L. Mellul)
Heatwave:
Abstract:
Real-time simulations on France carried out as part of the COZY project were used to evaluate the representation of the heat waves that raged in France and Europe last summer.
We show that LMDZOR simulates the heat wave, that these extremes of temperature are accompanied in the observations and in the model of a soil drying in surface, modest to the SIRTA, very pronounced on the metropole.
On the other hand, at SIRTA the agreement between observations and simulations is rather poor for sensitive flows, which seem to be largely overestimated by the model whereas the agreement for latent flows is more satisfactory. Several tracks remain to be explored to explain this disagreement. One can think of problems of unrepresentativeness of the measuring point compared to the mesh of the model. Imperfect treatment of the surface layer by the model can also be invoked: in the case of intense heat waves, the surface layer could be heated as a whole, which would weaken the temperature gradient between the surface and the atmosphere and decrease the sensible flow.
The SIRTA is equipped with a mast that measures the temperature between 2m, 5m, 10m and 20m and 30m. We use these observations to evaluate the daytime and nighttime temperature profile in the surface layer and on the first layers of the boundary layer.
Pre_heatwave
Heatwave
2003
23 July — 1 August
4-13 August
2010
1-10 July
1-10 August
2017
12-17 June
18-23 June
Miralles, Diego G., et al. "Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation." Nature geoscience 7.5 (2014): 345.

3. Zoomed over France
«COSY»: Near real time, env.50km, nudged with analysis/forecast ECMWF (wind, SST forced)
SIRTA (48.7N, 2.2E)
Toulouse(43.6N, 21.4E)

4. SIMULATIONS TEMPS REEL (dites COSY)
ANALYSE
ECMWF
JJ-2
ANALYSE
ECMWF
JJ-1
PREVISION ECMWF
JJ JJ JJ+2 JJ+3 JJ+4
Guidage u, v
JOUR J
LMDZOR
1 jour
Simulation LMDZOR zoomée guidée sur le site
Conditions initiales
sol et atmosphère
Chaine mise en place sur Climserv (Polytechnique, IPSL)
Rapatriement journalier automatique des analyses et prévisions (N. Poulet)
Lancement automatique journalier et surveillance (N. Poulet)

5. Part 1: Summer representation Part 2: Heatwave period representation Summary

6. Part 1: Summer representation

7. Air Temperature (2 m) (SIRTA and TOULOUSE)
LMDZOR simulates the observed heat wave (intensity and duration)
But a warm bias is present
SIRTA
Toulouse
OBS
V6010v3

8. Air Temperature (0-60 m) SIRTA mast
NIGHT
DAY
Warm bias and less gradient at lower layer
Night-time, too warm and not enough decoupling at surface
Day-time, too much mixing at the lower layer
Sample standard
deviation
Observation at surface, 2m, 5m, 10m, 20m and 30m AGT

9. Soil Moisture and Soil Temperature (SIRTA )
Lower soil moisture than the OBS at upper depths
Warm bias at the upper layers, it is consistent with the warm bias at atmosphere
JJA AVE 00Z
Soil Moisture
Soil Temperature
Sechiba SIRTA
Observation SIRTA
Sample standard
deviation

10. Soil Moisture and Soil Temperature (Toulouse)
Lower soil moisture than the OBS around 10cm depths, and moister at other depths
Warm bias above 1m depth, it is also consistent with the warm bias at atmosphere (2m)
Soil Moisture
Soil Temperature
Sechiba
Observation
Sample standard
deviation

11. Soil moisture
Lower soil moisture than the observations at SIRTA for 10 cm, 30 cm and 50 cm depths
At SIRTA, LMDZ and OBS time series are well correlated at 10 cm and 20 cm
Soil moisture at Toulouse close to the wilting point (0.1 m3/ m3) in model
10 cm
30 cm
20 cm
50 cm

12. Relative Humidity (2 m) SIRTA
Lower relative humidity than the observations at SIRTA for the heatwave period (daytime)

13. Sensible heat flux Latent heat flux
SIRTA
Preliminary new processing (ACTRIS)
Strongly over-estimate the sensible heat flux.
Under-estimated the latent heat flux in most cases.

14. Sensible heat flux Latent heat flux
Toulouse
Preliminary new processing (ACTRIS)
Strongly over-estimated the sensible heat flux;
Under-estimated the latent heat flux, and less evaporation for soil in model.

15. Short wave radiation (SIRTA)
Lower albedo in model with less variability.
Higher downward radiation in most cases.
Albedo
Downward

16. Short wave radiation (Toulouse)
Higher albedo in model with less variability.
Higher downward radiation in most cases.
Albedo
Downward

17. Part 2: Heatwave period representation

18. Mega-heatwave of 2003
00Z
12Z
Model: CM6012
Pre_HW
Nudging method improved the heatwave simulation very well.
Cold bias for the heatwave period.
Regular grid identical to CM6-LR (L-Mellul) HW
Two representation days were selected.

19. Mega-heatwave of 2010
00Z
12Z
Model: CM6012
Pre_HW
Nudging method improved the heatwave simulation very well, especially for the atmospheric boundary layer.
Regular grid identical to CM6-LR (L-Mellul) HW
Two representation days were selected.

20. Air Temperature (0-60 m) SIRTA
Not enough gradient at lower layer (below 10m)
Warm bias for LMDZOR outputs, except the surface temperature at day-time
Heatwave 2017
00Z
12Z
Observation Black: Pre_HW Red: HW
LMDZOR
Summer average

21. Summary
The model (V6010v3) can simulate the heatwave in 2017 (intensity and duration), and nudging method in the new version (V6012) improved the heatwave simulation (2003, 2010) very well.
There are warm bias for summer and heatwave period.
Drying of the soil moisture is well phased with observation, and stronger where the heatwave is more intensity.
Model outputs yielded higher potential temperature, and haven’t enough gradient for air temperature at lower layer.
Model strongly over-estimated the sensible heat flux and under-estimated the latent heat flux.
On the other hand, at SIRTA the agreement between observations and simulations is rather poor for sensitive flows, which seem to be largely overestimated by the model whereas the agreement for latent flows is more satisfactory. Several tracks remain to be explored to explain this disagreement. One can think of problems of unrepresentativeness of the measuring point compared to the mesh of the model. Imperfect treatment of the surface layer by the model can also be invoked: in the case of intense heat waves, the surface layer could be heated as a whole, which would weaken the temperature gradient between the surface and the atmosphere and decrease the sensible flow.

22. Thank you!