SÖRENSSON A. , P. SPENNEMANN, M. SALVIA, R. RUSCICA, F. GRINGS, H.

KARSZENBAUM

Spatio-temporal analysis of the coupling between soil moisture and surface climate in the La Plata Basin: combining results from

regional climate models and satellites

ICRC-CORDEX 2016 17th – 20th May 2016 Stockholm

New collaboration between remote sensing group and RCM group at the University of Buenos Aires

Institute of astronomy and space physics (IAFE). quantitative remote sensing: ¡  Mercedes Salvia

¡  Francisco Grings ¡  Haydee Karszenbaum

  Active/passive microwaves   Soil moisture,

evapotranspiration, flood monitoring

Center for Sea and Atmosphere Research (CIMA): ¡  Romina Ruscica ¡  Pablo Spennemann ¡  Anna Sörensson

  Regional Climate Models   Interaction between land

surface and atmosphere

0

200

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1960 1970 1980 1990 2000 2010 LA PLATA BASIN

ARGENTINE PAMPAS

Annual precipitation Puán 1960-2010, values between 300 and 900 mm.

•  The Argentine Pampas is an extremely flat region that extends over 600.000 km2. •  Mostly covered by annual crops and ranching.

•  Annual mean of precipitation: 300mm in the west and 1200mm in the east, but the interannual variability is very high.

Non-periodic floods and droughts extending over several months / seasons

Coupling between soil moisture and atmosphere

COUPLING: How much of the atmospheric

variability depends on soil moisture variability?

• The memory of the soil moisture is longer than the memory of the atmosphere.

• Soil moisture influences on the atmosphere through the partitioning of energy into latent and sensible heat flux

• Soil moisture could therefore be a low frequency modulator of the atmosphere in some regions.

• This can improve predictions on weekly-seasonal scales.

Ruscica et al. 2015

How to measure the coupling: Example

HSTempTempI .*βHSSTD=

Sensitivity of temperature to soil moisture.

Variability of soil moisture

SM’

T’

STD

β

In regions with coupling, the soil moisture anomalies are anticorrelated with the surface temperature anomalies. ( +SM → +ET → -T) β <0 is a necessary conditions for a casual influence of soil moisture on

temperature.

Dirmeyer, 2011 SM SM

Coupling between soil moisture and evapotranspiration for austral summer

Notaro, 2008

Zeng et al., 2010

Koster et al., 2004

I= STD * β

Dirmeyer, 2011

Indices

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Rus

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Sör

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201

1

Multiple sources, indices temporal scales show robust signal of coupling for the Pampas region.

Nevertheless these studies have several limitations related to model assumptions and vegetation parameterizations, as well as the lack of observational data for the evaluation of models performance. Can satellite data be used to validate the results?

Meanwhile we got a visit from IAFE…

Soil moisture products from different satellite systems report different patterns over la Pampa. These products discrepancy was also observed for other areas around the world. All products claim some form of validation (in situ validation in some densely instrumented sites – not available in our region). Therefore, since: (1) product quality in the area cannot be guaranteed by global validation and (2) direct in situ validation is not possible, Alternative validation schemes become relevant.

Can soil moisture – atmosphere coupling be used to calibrate satellite product over the Pampa?

Soil moisture – surface fluxes coupling: starting point of the interaction between the IAFE and CIMA

REMOTE SENSING GROUP MODELLING GROUP

1. COUPLING

3. ??

2. ?

Evaluation of coupling Evaluation of soil moisture product

Satellite data to calculate coupling

  Infrared derived Temperature ¡  MODIS level-3

(MOD11A2) ¡  8-days-means ¡  1km

  Microwave derived Soil Moisture product ¡  AMSRE / LPRM ¡  Daily ¡  0.25˚ (25km)

June 2002 – October 2011 (AMSR-E)

Interpolated to a 1 degree grid, temporal resolution 8 days

Coupling between soil moisture and evapotranspiration for austral summer

MODIS (T) - AMSRE (SM)

HSTempTempI .*βHSSTD=Satellite products give similar signal of coupling in the Pampas region.

Coupling during extreme contidions

Second step: Does the coupling change under extremely dry / wet conditions? Does the model and the satelite give the same results?

DJF seasonal mean anomalies from AMSRE

DJF seasonal mean anomalies from RCA4

(different periods)

Coupling during wet and dry summers

Weak coupling Strong coupling

MO

DIS

/AM

SR-E

R

CA4

Both sources show stronger coupling for dry conditions.

Future Plans

Analyze coupling with complementary satellite products. Integrate available information about biogeophysical variables. Can we constrain satellite products with model dynamics? Is it possible to integrate soil moisture satellite products in the regional climate models?

Tack så mycket!

References

Sörensson AA y Menéndez CG. 2011. Summer soil-precipitation coupling in South America. Tellus Ser. A: Dyn. Meteorol. Oceanogr. 63: 56–68, DOI: 10.1111/j.1600- 0870.2010.00468.x.

Ruscica, R. C., Sörensson, A. A. and Menéndez, C. G.. 2015. Pathways between soil moisture and precipitation in southeastern South America. Atmosph. Sci. Lett., 16: 267–272. doi: 10.1002/asl2.552

Ruscica, R. C., Menéndez, C. G. and Sörensson, A. A. 2016. Land surface–atmosphere interaction in future South American climate using a multi-model ensemble. Atmosph. Sci. Lett., 17: 141–147. doi: 10.1002/asl.635

Spennemann, P. C. and Saulo, A. C. 2015: An estimation of the land-atmosphere coupling strength in South America using the Global Land Data Assimilation System. Int. J. Climatol.. doi: 10.1002/joc.4274

sorensson@cima.fcen.uba.ar