Operational climate service Carlo Buontempo With contributions - - PowerPoint PPT Presentation

Operational climate service

Climate Change

Carlo Buontempo

With contributions from: Jean-Noël Thepaut, Dick Dee, Anca Brookshaw, Cedric Bergeron ECMWF

@carlo_tuitter ; Carlo.Buontempo@ecmwf.int

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Fake

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Operational

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Climate Data Store – CDS

The CDS is designed as a distributed system, providing improved access to existing datasets through a unifjed web interface. It is ALL* free and unrestricted

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Climate projections

Service: Providing users with timely access to climate change scenarios produced with state-of-the-art climate models (CMIP, CORDEX)

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Aim: to generate seasonal forecast products based on the best information available, to an operational schedule, and make them publicly available. C3S seasonal forecasts - Introduction

• Issued every month on the 13th

(likely to be moved closer to the 10th)

• Large ensembles

(members: ~50 forecast, ~25 hindcast)

• Common reference period (1993-2016)

Output

• on common horizontal resolution (1*1 degree)
• ~30 single-level variables (every 6h or 24h)
• 5 variables in pressure levels (every 12h)

(11 levels from 925hPa to 10hPa)

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Climate reanalysis: ERA5

• Atmosphere/land/wave parameters
• 31 km global resolution, 137 levels
• Hourly output from 1979 onward
• Using 2016 ECMWF forecast system
• Using improved input observations
• Ensemble data assimilation method
• Uncertainty estimates for all ECVs
• Atmosphere/land/wave parameters
• 31 km global resolution, 137 levels
• Hourly output from 1979 onward
• Using 2016 ECMWF forecast system
• Using improved input observations
• Ensemble data assimilation method
• Uncertainty estimates for all ECVs

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Essential Climate Variables

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E v a l u a t i o n a n d Q u a l i t y C o n t r o l

Quality of data

• Assessments
• User guidance
• Gaps and limitations

Quality of tools

• Fitness for purpose
• Best practices

Quality of service

• Speed,

responsiveness

• System availability,

…

d a ta q u a lity

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Climate Data Store - implementation

• Ongoing physical implementation:

– On-Premises Private Cloud :

• CloudFerro

– 34 compute servers x 2 cpu x 12 cores@ 2.2 GHz and 192 GB RAM per server – 4 compute server x 2 CPUs x 8 cores @ 2.6 Ghz and 64 GB RAM per server – 100 TB SSD and 900 TB HDD

Phase I

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T raceability of simple applications

Fractions of time the wind speed is less than 6 m/s and the significant wave height is less than 1.5 m in ERA5 hourly record for 2012

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State of the climate

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Data is not information without users and context: co-design in practice …

Irrigation in Italy Freshwater supply in Spain Brewing beer in the Netherlands Sweden Flooding in Slovakia Lake water quality Sweden

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http://ecem.wemcouncil.org/

Integrating climate and energy scenarios to learn how well prepared our infrastructure is to cope with the climate of the future. Will the renewable dominated energy mix of the future able to cope with the expected change in the energy demand profile? Using a combination of historical data, reanalysis, seasonal predictions and climate projections the SIS contracts demonstrated how will be possible to address some of these questions through the CDS. Contract led by A. Troccoli UEA

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I n d i c a t o r s , g l o b a l a g r i c u l t u r e c o n t r a c t

• Biologically Efgective Degree Days, Growing Season Length, Maximum number of

consecutive dry days, Maximum number of consecutive frost days (Cold spell), Cold Spell Duration Index , Maximum number of consecutive summer days (Hot spell), Maximum number of consecutive wet days (Wet spell), Mean of diurnal temperature range, Frost Days, Ice Days, Heavy precipitation days, Very heavy precipitation days, Precipitation sum, Wet Days, Simple Daily Intensity Index (Mean precipitation per wet day), Sumer Days, Mean of daily mean temperature, Mean of daily minimum temperature, Minimum value of the daily minimum temperature, Maximum value of the daily minimum temperature, Tropical nights, Mean of daily maximum temperature, Minimum value of daily maximum temperature, Maximum value of daily maximum temperature, Warm Spell Duration Index, Warm and wet days, AgERA5 wind speed, AgERA5 dewpoint temperature, AgERA5 air temperature, AgERA5 precipitation type, AgERA5 relative humidity, AgERA5 snow, AgERA5 solar radiation, AgERA5 cloud cover, AgERA5 precipitation, AgERA5 vapour pressure, Soybean development stage, Soybean T

• tal above-ground production, Soybean T
• tal weight storage organs (yield),

Wheat development stage, Wheat T

• tal above-ground production, Wheat T
• tal weight

storage organs (yield), Rice development stage, Rice T

• tal above-ground production,

Rice T

• tal weight storage organs, (yield), Maize development stage, Maize T
• tal above-

ground production, Maize T

• tal weight storage organs (yield), evapotranspiration

1 7

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Operational Phase Operational Phase

CDS / T

• olbox

launched Previous C3S GA March 2017

201 6 201 7 201 8 201 9 202 202 1

Present

Agriclass Agriclass SWICCA SWICCA EDGE EDGE ECEM ECEM Clim4Energy Clim4Energy WISC WISC

C3S Water (SMHI) C3S Water (SMHI) C3S Energy (WEMC) C3S Energy (WEMC) C3S Wind Storms (KNMI) C3S Wind Storms (KNMI)

Proof of concept Proof of concept UrbanSIS UrbanSIS

U R B A N

POC migration POC migration

POC to Operations

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Operational Phase Operational Phase

CDS / T

• olbox

launched Previous C3S GA March 2017

201 6 201 7 201 8 201 9 202 202 1

Present

Agriclass Agriclass

Global Agriculture (WenR) Global Agriculture (WenR)

Proof of concept Proof of concept Global Impacts (SMHI) Global Impacts (SMHI) Global Shipping (OSM) Global Shipping (OSM) European T

• urism

(TEC) European T

• urism

(TEC) European Health (VITO) European Health (VITO)

European Storm Surges (Deltares) European Storm Surges (Deltares)

FISHERIES

European Fisheries (PML) European Fisheries (PML)

Global Services European Services

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Conclusions

• The scale of the climate challenge requires a step change in the way we produce

and deal with climate information.

• C3S has developed an operational infrastructure that makes simple for users to

freely access an unprecedented amount of quality controlled climate data.

• The climate data store come with a computational layer that allows users to

define and run their climate-relevant product –or at least part thereteof- in the cloud, significantly reducing the need of downloading a large volume of data.

• A series of exemplar applications which show how the infrastructure could be

used to address specific issues are about to become publicly available. Yours could be next if you want…

• It is (almost…) irrelevant whether it will be C3S or another programme but we MUST

find a way to operationalise the development and delivery of climate services.

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climate.copernicus.eu

For more info:

copernicus-support@ecmwf.int

Carlo.Buontempo@ecmwf.int Twitter: @carlo_tuitter

Questions?