Advanced predictive modelling of severe weather and weather emergencies Daniel Santos, Project Leader, National Meteorological Service, Spain

1. Advanced predictive modelling
of severe weather and weather
emergencies
Dr. Daniel Santos Muñoz
HIRLAM-C Project Leader for System
@DSantosMunoz
EENA CONFERENCE 2018 25-27 April 2018, Ljubljana, Slovenia

2. https://www.eea.europa.eu/data-and-maps/indicators/direct-losses-from-weather-disasters-3/assessment-1
Economic losses and fatalities caused by weather and climate-
related extremes in the EEA member countries 1980-2016
2

3. 2003 European heatwave:
35 000 heat-related deaths across Europe (WHO)
Mortality rate in France increased by 54 %
The financial loss due to crop failure is estimated at $12.3 billion
Forest fires in Portugal alone resulted in total damage costing $1.6 billion
3

4. 17 wind storms affected Europe
since 12 Sept 2017:
Maximum wind gust 274 km/h
74 deaths
More 2.748 billion € on damages.
4

5. 1904
Norwegian physicist and meteorologist Vilhelm F.K Bjerknes published
“The Problem of Weather Forecasting as a Problem in Mechanics and Physics”
Weather forecasting can be done using physics and numerical models
(and also human forecasters)
1922
English mathematician, physicist, meteorologist, psychologist and pacifist Lewis Fry
Richardson pubished “Weather Prediction by Numerical Process”
64.000 HPU (Human Processing Units) working in PARALELL for
making an accurate forecast . 5

6. 6

7. 1950
Charney, Fjørtoft y von Neumann made the
first 24 hours weather forecast using ENIAC
(Electronic Numerical Integrator And
Computer).
7

8. 8

9. The European Centre for Medium-Range
Weather Forecasts (ECMWF) is an independent
intergovernmental organisation supported by
34 states.
ECMWF is both a research institute and a 24/7
operational service, producing and
disseminating numerical weather predictions
to its Member States.
This data is fully available to the national
meteorological services in the Member States.
9

10. The Integrated Forecasting System (IFS) is Earth-system model
developed in the ECMWF in cooperation with Météo-France
The HRES provides a highly detailed description of future
weather and averaged over many forecasts it is the most
accurate forecast for a certain period, which is currently
estimated as 10 days for large scale properties of the
atmosphere
Forecast /
Analysis
Number of
members
Horizontal
resolution
Vertical
levels
Pressure
at model
top (hPa)
Perturbation
models
HRES
Atmospheric
Model high
resolution
Forecast
10 Days
1 Native:
01280 ~9km
Interpolated:
0.1° ~9km
137 0.01 hPa No
4DVAR
4-Dimensional
data
assimilation
Analysis 1 N128/N160/
N200 inner
loops
O1280 outer
loop
137 0.01 hPa No
10

11. July 2015 heatwave affected Europe
11

12. 12

13. Domain Cycle Grid DA forecast length/cycle
AEMET 40h1.1 2.5 km 65 lev 3DVar + surf ana 48h/8times
DMI 40h1.1 2.5 km 65 lev 3DVar + surf ana 60h/8 times
FMI 38h1.2 2.5 km 65 lev 3DVAR + Surf ana 54h/8times
KNMI 36h1.4.bf1 2.5 km 60 lev 3DVAR + Surf ana 48h/8 times
LHMS 37h1.2 2.5 km 60 lev blending + Surf ana 54h/4 times
MetEireann 37h1.1 2.5 km 65 lev blending + Surf ana 54h/4 times
MetCoOp
HarmonEPS
40h1.1 2.5 km 65 lev 3DVAR + Surf ana
66h at 00,06,12,18, 3h
at 03,09,15,21
VI-Iceland 38h1.2 2.5 km 65 lev blending + Surf ana 48h/4 times
HARMONIE-AROME
The non-hydrostatic convection-
permitting model is developed in a
code cooperation with Météo-France
and ALADIN.
Forecasts: 2.5 km 48-72 hours
13

14. Credit MetEireean
14

15. CHAOS THEORY AND WEATHER FORECAST
LORENZ (1963) published "Deterministic Nonperiodic Flow"
“Two states differing by imperceptible amounts may eventually evolve
into two considerably different states ... If, then, there is any error
whatever in observing the present state—and in any real system such
errors seem inevitable—an acceptable prediction of an instantaneous
state in the distant future may well be impossible....In view of the
inevitable inaccuracy and incompleteness of weather observations,
precise very-long-range forecasting would seem to be nonexistent”.
Probabilistic
forecast
PDF
best guess
15

16. Credit MetEireean
16

17. GOALS
A key target is to extend the probabilistic skill of ECMWF’s high-
impact weather forecasts by 3 to 6 days over the next decade.
This would enable skillful predictions of high-impact weather up to 2
weeks ahead.
Other goals include predicting large-scale patterns and regime
transitions up to four weeks ahead, and global-scale anomalies up to
a year ahead.
EPS
5 km grid spacing for ensemble forecasts by 2025, down from 18 km today.
Earth system modelling
Adequately representing the interactions between components of the Earth system that influence the
weather. In addition to the atmosphere, these components include the oceans, sea ice and the continental
land surfaces. 17

18. GOALS
Development of a high-resolution (1-2.5km) short-range HarmonEPS which the ensemble
generation, the data assimilation system and the forecast model are closely integrated.
The forecast skill of this system should be optimized towards the very short range(3-24h) and
to the accurate prediction of high-impact weather.
Prepare the model for operational use at increased resolution (~100 layers, 0.5-1.3km), and
explore model behavior at hectometric scales (500 m) and in the nowcasting (0-6h) range.
Develop the model towards a more complete earth system model, with a focus in the coming
years on sea and sea surface and atmospheric chemistry aspects.
Continue optimizing the use and impact of existing, and introduction of new, types of high-
resolution observations, in combination with advanced flow-dependent assimilation
techniques.
18

19. Andreas Schaffhauser
METEOALARM and the European
Civil Protection
Eric Sprokkereef,
The European Flood Awareness System
(EFAS) 19

20. Summary and future challenges
The NWP models are continuously increasing accuracy and resolution to detect
extreme weather phenomena.
During next years, and also nowadays, high resolution EPS (probabilistic
forecasts) will be the main source of information for decision making for severe
weather.
Models running in hectometric scales (500 m) and in the nowcasting (0-6h)
range several times per day (hourly) are or will be available.
New high-resolution observations (private networks, cars, werables …), in
combination with advanced flow-dependent assimilation techniques will
increase the accuracy of the NWP models.
20

21. Summary and future challenges
How to communicate the uncertainty in the
weather forecast and in severe weather
events?. For example, low probability
extreme phenomena but with a big potential
impacts.
Big data, artificial intelligence, smartcities,
werables … will play a new role in the severe
weather modelling
21

22. Summary and future challenges
Major impacts of climate change on human health
are likely to occur via changes in the magnitude
and frequency of extreme events which trigger a
natural disaster or emergency (IPCC )
22

23. Thanks for your
attention
23
Dr. Daniel Santos Muñoz
dsantosm@aemet.es
@DSantosMunoz