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)

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 (http://weather.uwyo.edu/upperair/sounding.html) 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.

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)

SIMULATIONS TEMPS REEL (dites COSY) ANALYSE ECMWF JJ-2 ANALYSE ECMWF JJ-1 PREVISION ECMWF JJ JJ+1 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)

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

Part 1: Summer representation

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

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

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

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

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

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

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.

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.

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

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

Part 2: Heatwave period representation

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.

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.

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

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.

Thank you!