deep learning for satellite precipitation estimation · deep learning for geoscience 2 deep...

IMPLEMENTED BY

Deep learning for

satellite precipitation

estimation

• A. Moraux, S. Dewitte, B. Cornelis & A. Munteanu

• Royal Meteorological Institute of Belgium & Vrije Universiteit Brussel

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Deep learning for geoscience

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Deep learning and process

understanding for data-driven Earth

system science. Nature, 2019

M. Reichstein et al.

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Deep learning for climatology

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Deep learning for multi-year ENSO forecasts. Nature, 2019

Y. G Ham, J. H. Kim, & J. J. Luo

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Importance of precipitation estimation

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Daily precipitation accumulationInstantaneous precipitation rate

Courtesy of M. Journée RMI belgian radars composite

Precipitation Nowcasting

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Different observation tools:

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3) Satellite radiometers

1) Rain gauges

2) Weather radar

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Rain gauges

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Radar

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Estimate precipitation from

electromagnetic pulse reflection

measurementsZ=aR𝑏

Z =

Reflectivity

R =

Precipitation rate

a, b =

empirical

coefficients

Courtesy of L. Delobbe

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Satellite radiometer

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Meteosat Second

Generation

Full disc imagery in 12

spectral channels

Visible and infrared

3 km spatial resolution

15 minutes temporal

resolution

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Satellite radiometer

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Cloud physical properties

Red: Optical depth

Green: Water phase

(water/ice) and particle

size

Blue: Temperature

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Multimodal and multiscale deep learning model for precipitation estimation

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Model training

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Rain gauges measurements

Satellite channels

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Data splitting

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Proper data splitting both in time and space is necessary for correct performance evaluation

➔Not randomly !

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Study case: winter rain

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Our DL model

Traditional

methods

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Study case: summer rain

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Our DL model

Traditional

methods

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Future studies

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Use radar, combined with satellite and rain gauges

➢ Further improve precipitation estimation and resolution

Develop a model with only satellite data as input

➢ Global coverage precipitation product

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Future Eumetnet workshop on Artificial Intelligence for weather and climate

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⚫ When: 26-27 February 2020

⚫ Where: Brussels

⚫ Inscription: https://events.spacepole.be/e/AI

⚫ For more information: steven@meteo.be

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Appendix: Performance scores

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1) Precipitation detection

2) Precipitation rate

estimation