European heat waves: the propagation of Mediterranean drought Fabio DAndrea With thanks to: Philippe Ciais, Christophe Cassou, Nathalie de Noblet-Ducoudret,,

European heat waves: the propagation of Mediterranean drought

Fabio D’Andrea

With thanks to: Philippe Ciais, Christophe Cassou, Nathalie de Noblet-Ducoudret,, Masa Kageyama,

Robert Vautard, Nicolas Viovy, Charlotte Vorms, Pascal Yiou, Matteo Zampieri.

Toulon 9.10.2007

(Grazzini et al 2003)

Outline

1. Motivation - the heatwave of summer 2003.2. The importance of soil moisture. Feedbacks.3. Mediterranean precursor. Observation.4. Mediterranean precursor. Modeling.

a, JJA temperature anomaly with respect to the 1961−90 mean. Colour shading shows temperature anomaly (°C), bold contours display anomalies normalized by the 30-yr standard deviation. b−e, Distribution of Swiss monthly and seasonal summer temperatures for 1864−2003. The fitted gaussian distribution is indicated in green. The values in the lower left corner of each panel list the standard deviation and the 2003 anomaly normalized by the 1864−2000 standard deviation (T‘’/sigma).

The 2003 heatwave in Europe(Schär et al 2004, Nature)

(Black et al 2004)

Synoptic aspect 2003

Prevailing anticyclonic conditions.

(Black and Sutton 2006 Clim Dyn)

Anomalous SST

“Horseshoe” pattern

Hot Indian and tropical Atlantic ocean

Hot Mediterranean

There are other mechanism that are be responsible for the high amplitude of temperature and precipitation anomalies. One of the main actors is SOIL MOISTURE.

Heatwaves have been observed to be preceeded by precipitation deficit (Huang and Van den Dool 1992 J. Clim.

Figure 1: a) Summertime (JJA) anomaly composites (°C) over the hottest 10 summers in the 1948-2004 period; b) same as a) but for JJA precipitation frequency (%). Stations where the anomaly is significant at the 90% level are marked by a black bullet;

precipitation deficit

Dry soil

Less evapotranspiration

Less latent Cooling.Less clouds

Hot soil

More sensibleHeat flux

Hot PBL

Soil moisture controls the energy balance between the earth surface and the atmosphere by modulating sensible and latent (evaporation) heat fluxes.

The Soil Moisture - Precipitation feedbackHigh amplitude temperature and moisture variation are maintained by a feedback between soil moisture and precipitation (Schär et al 1999, Fischer et al 2006).

Figure 1: a) Summertime (JJA) anomaly composites (°C) over the hottest 10 summers in the 1948-2004 period; b) same as a) but for JJA precipitation frequency (%). Stations where the anomaly is significant at the 90% level are marked by a black bullet;

Vautard et al 2007, GRL.

57 year dataset of station measurement in Europe for temperature and precipitation frequency.

The 10 hottest summers:

Vautard et al 2007. GRL

Hot summers:

1950

1952

1959

1964

1976

1983

1992

1994

1995

2003

Northward propagation of drought(Vautard et al 2007, GRL)

Figure: a) Average rainfall frequency anomaly (% of days) (January–April) for the 10 years containing the hottest summers listed in Table 1 of the Auxiliary Material. The color scale is as in Figure 1b. The figures that would obtain for the winter only (January-march, not shown) or from January to May are rather similar to this one; b) Same as a) for averages of the month of May only; c) Same as a) for June; d) Difference between the early summer (June and July) maximal hot-summer temperature anomalies when southerly wind occurs at the station and that obtained for northerly wind. At each station, days are classified into 2 classes according to the sign of the mean daily surface meridional wind field. The 58-year average maximal temperature is calculated and subtracted from the hot-summer average to obtain mean anomalies. Then the difference between “southerly” and “northerly” mean anomalies is shown in panel d). The figure shows that temperature anomalies, in the 10 hottest summers, are higher in southerly wind conditions than in northerly wind conditions. e) As in d) for rainfall frequency (% of days). Stations where the differences are significant at the 90% level are marked with a black bullet.

Figure 3: Detrended summertime (JJA) daily maximum temperature anomalies, averaged over European stations, as a function of year

(in black), together with the detrended anomaly of precipitation frequency averaged in the 42°N-46°N latitude band during preceding

winter and early spring (January to May), in red. Temperature anomalies are in °C while precipitation frequencies anomalies are in %. In order to assess the sensitivity to the chosen latitude band for

precipitation frequency, 2° northward and southward shifts are applied and results are also represented. Yellow bars indicate the

years selected in the hottest 10 summer years.

A predictor in the mediterranean region?

Spring precipitation at different band of latitude and summer temperature

Data from weather stations + a water budget model. Wilmott and Matsuura 2001.

Test of the drought propagation by mesoscale modeling(credit: Matteo Zampieri, LMD)

MM5 Integration details (credit: Matteo Zampieri, LMD)

Simulations domain: most of Europe (excluding the Northern part of the Scandinavian peninsula) and a large part of the Atlantic Ocean.

Forced by the ECMWF (ERA40) or NCAR-NCEP reanalyses with a 6-hour rate. Resolution: 36 km at the centre of the domain. 85x125 grid points and 23 vertical

levels.MM5 3.7.3 model versionReisner microphysics, Kain-Fritsch convection scheme, MRF PBL scheme CCM2 radiation scheme. NOAH land-surface 4-layer scheme.

twin simulation, starting on 1 June, for all the 10 hottest summers, differing only by their initial soil moisture south of 46N:

1) 'wet' simulation. Initial volumetric soil moisture content of 30% . 2) 'dry' simulation Initial volumetric soil moisture content of 15%. North of 46N initial soil moisture content is taken from the ERA40 ECMWF

reanalysis data, when possible, or the NCAR-NCEP reanalysis data.

Results from the twin (DRY and WET) simulations averaged over the 10 hottest summers:

a) difference between DRY and WET 15h UTC 2m temperature averaged over the month of July;

b) difference between the July and June DRY-WET 15h UT 2m temperature (June-July increment of the DRY-WET differences).

c) and d) show the standard deviation of the variables plotted in a) and b) , respectively

Heat wave propagation: 2m temperature

July Dry - Wet July - June, Dry - Wet

Heat wave propagation: 2m temperature

Time evolution of 2m temperature at 15UTC averaged between 46.5 and 50°N and for longitude < 6°E. In blue the mean between DRY and WET, in red the difference. The bold lines represent the average over the 10 summers, the dashed lines represents the corresponding standard deviations. The difference is multiplied by 10

Dry - Wet July Dry - Wet

Heat wave propagation: Precipitation

Averaged total precipitation over the 10 hottest summers, in cm. a) DRY - WET difference accumulated over the months of June and July; b) the same, but over the month of July

Time evolution of the DRY-WET differences of total accumulated precipitation for each summer, averaged over France. The red bold line represents the average among all the summers.

Heat wave propagation: Soil moisture

a) June-July increment of the DRY-WET differences of root layer (1 m) volumetric soil moisture content, in % of total volume. b) time evolution averaged over France

∑∑ΔΔ−=ji jiji jijiqqlatl , ,, ,, )46(

Drought length propagation length scale

a) June-July increment of the DRY-WET differences of total incoming radiation at 12h UT, in W m-2. b) same for surface latent heat flux. c) same for sensible heat flux. Colorscale in b) is inverted with respect to a) and c).

Heat wave propagation: Fluxes

Radiation Sensible heatLatent heat

a) total incoming radiation at the surface

b) Bowen ratio c) sensible heat flux d) latent heat flux.

Differences of

incoming radiation are multiplied by 10 for readability.

Heat wave propagation: Fluxes

Heat wave propagation: Synoptic effect

DRY-WET mean July anomaly of

a) mean sea level pressure, in mb

b) geopotential at 500 mb, in m,

c) boundary layer height at 15 UTC, in m and

d) lapse rate between 700 and 500 mb, in K km-1.

Is MM5 a good model for this study?

cold temperature bias

« dry » runs of the model: sensitivity to soil moisture

2m temperature Fluxes

Conclusions: heat and drought propagates north.

Dry soil:

1) favours higher sensible heat fluxes, and subsequent temperature increases (slow);

2) favours drier air with less and less extended clouds, thus enhancing solar radiation (fast);

3) favours less convection and an upper-air anticyclonic circulation.

Future plan: change model.

POSTDOC POSITION AVAILABLE

Fig.: The visualization displays TERRA MODIS (MODerate resolution Imaging Spectroradiometer) derived land surface temperature data of 1km spatial resolution. The difference in land surface temperature is calculated by subtracting the average of all cloud free data during 2000, 2001, 2002 and 2004 from the ones in measured in 2003, covering the date range of July 20 - August 20. (Cite this image as: Image by Reto St-böckli, Robert Simmon and David Herring, NASA Earth Observatory, based on data from the MODIS land team. Correspondance: [email protected]).

Thank you

Water balance on a layer of soil

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∂Qs

∂t= P − E − R − L

In a hot summer day, a mature tree can evaporate 2000 liters of water!

…water for one week…

At this point, we really need to study the dynamics of soil water, and its interaction with the atmosphere

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ρCpha

∂θa

∂t= Qs +εaεsσ TS

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ρha

∂qa

∂t= E − ρha

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ρwCpshs

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∂t= Frad − Qs − Le E −εsσTs

4

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ηρwhs

∂qs

∂t= P '−E − L(qs )

Free troposphere

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θe = θae

Le qa

c pθ a

Box model description (D’Andrea et al 2006 GRL)

Planetary Boundary Layer

Soil

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θe∗

E P

Qs

1000 m

0.5 m

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Fq

Leakage

divergence

Results from 1-d model

Equilibrium

Results from 1-d model

DAY 1

Results from 1-d model

DAY 30

Results from 1-d model

DAY 60

Results from 1-d model

DAY 90

Evaporation Rate

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E = EMax forqs ≥ q∗

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aSatMaxMax

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2.5106

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point Wilting18.0

point cHygroscopi14.0

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sq

E

(Laio et al 2001)

Evaporation Rate (can be used alternatively)

Penman Monteith formula (FAO 56), modified

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Le E =

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rsand : resistence parameters (aerodynamic and bulk)

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γ= 6 .65 Psychrometric constant (hPa per Kelvin)

Leakage

Sensible heat flux

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Qs = ρCpCD u (Ts −θa )

Precipitation Rate and Runoff (1)

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P = f1

dtΔ˜ q S

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L(qs) = Ks

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−1

ek(1 −q fc )

−1(Laio et al 2001)

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P '= P for P ≤q0 − qs

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if θe −θe∗ ≥ 0

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Δ ˜ θ a =θe −θe

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Δ˜ q a = qRe lδqsΔ ˜ θ a (drying)

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δqsat =∂qSat

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variation)(enthalpy ~~

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Precipitation Rate and Runoff (2)

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Not all the water that is lifted in the free troposphere by convection precipitates.

The fraction of precipitated water depends on the intensity of convection.

f is 0.9 for strong convection and 0.25 for weak convection

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ρha

Δ˜ q adt

(mm /day)

Equilibrium statesAs a function of initial soil moisture condition

Some parameter values:

atmosphere

free theof mperature te

equivalentConstant 300

humidity offlux Lateral 10.1

emissivity Soil 8.0

radiationSolar 380

e

8

2

K

sKg

KgF

m

WF

q

rad

οθ

ε

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=

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Hysteresis cycle obtained by varying Fq

Air temperature

Soil moisture

Dependence on the large scale flux convergence

Stochastically forced integration

Fq is perturbed stochastically every 5 days. Values varying between -1 and 3 mm/day. Flat distribution

Cool and moistregime

Dry and warmregime

Observed data

D’Odorico and Porporato 2003, PNAS

Conclusions

Two criteria are necessary for the occurrence of a heat and drought wave:1. The establishment and presistence of an anticyclonic regime.2. A condition of dry soil.When both criteria are met, the soil moisture - precipitation feedback can maintain

large amplitudes of anomaly.

Heat propagates northward from the Mediterranean region:1. By propagation of drought (over France)2. By propagation of anomalous cloudiness (over Germany)

The initial content in soil water at the beginning of the summer is the crucial parameter. It is more likely that one summer is either in one or the other state and stay there, rather than a transition occur during the season (counterexample: summer 2006).

Hypothesis: the dependence of precipitation efficiency on convection intensity can be at the base of the soil moisture - precipitation feedback.

Differential E-P in a meridionally well mixed atmosphere can explain the northward propagation of the drought anomaly. (Still very sensitive to the model parameters. It depends strongly on the stability properties of the two regimes.)