eskes, tropomi workshop, mar 2008 air quality forecasting in europe henk eskes european ensemble...

Eskes, TROPOMI workshop, Mar 2008

Air Quality Forecasting in Europe

Henk Eskes

• European ensemble forecasts: GEMS and PROMOTE

• Air Quality forecasts for the Netherlands


GMES

http://www.gmes.info/


GMES and atmospheric composition / air quality

GMES Atmospheric projects: PROMOTE (ESA) and GEMS (EU)

MACC (2009 onward)Follow-up of GEMS and

GMES Atmosphere ServiceCore service:

Atmospheric composition on global and European scale


OMI and PROMOTE http://www.gse-promote.org


Greenhouse Gases (GHG)

Global Reactive Gases (GRG)

Aerosols (AER)

Regional Air Quality (RAQ)

Validation (VAL) Production (PRO)

GHG

GRG

AER

RAQ

GEMS subprojects


GEMS subproject: Regional Air Quality RAQ

• Production of regional forecasts of chemical species and air quality indices based on an ensemble of air-quality models on the European scale

AERGRGGHG

GEMS

global system

European Center of Medium Range Weather Forecasts

regionalair qualityarchives

GEMS web site

FRIUUK, Germany

SMHISweden

MetOffice, UK

CNRS,INERIS, France

FMI, Finland

FMI, Finland

DMI, Denmark

NKUA, Greece

ISAC, Italy

met.no, Norway

MeteoFrance, France

EURAD

MATCH

UMAQ

CHIMERE

SILAM

MATCH

CAC

UAM-V

BOLCHEM

EMEP

MOCAGE

European partner institutes

AERGRGGHG

GEMS

global system

AERGRGGHG

AERGRGGHG

GEMS

global system

European Center of Medium Range Weather Forecasts

regionalair qualityarchives

GEMS web siteGEMS web site

FRIUUK, Germany

SMHISweden

MetOffice, UK

CNRS,INERIS, France

FMI, Finland

FMI, Finland

DMI, Denmark

NKUA, Greece

ISAC, Italy

met.no, Norway

MeteoFrance, France

EURAD

MATCH

UMAQ

CHIMERE

SILAM

MATCH

CAC

UAM-V

BOLCHEM

EMEP

MOCAGE


FRIUUK, Germany

SMHISweden

MetOffice, UK

CNRS,INERIS, France

FMI, Finland

FMI, Finland

DMI, Denmark

NKUA, Greece

ISAC, Italy

met.no, Norway

MeteoFrance, France

EURAD

MATCH

UMAQ

CHIMERE

SILAM

MATCH

CAC

UAM-V

BOLCHEM

EMEP

MOCAGE



GEMS subproject: Regional Air Quality RAQ


Satellite

Surface network

Assimilation

Air qualityprediction

Model

Data assimilation


• In NWP uncertainties in the initial state will diverge.

• In atmospheric chemistry (regional scale) the uncertainty is mainly related to uncertainty in model input data, physical parameterizations, or from gaps in our knowledge of the chemistry and physics of the atmosphere and its interaction with the surface. Impact of initial state rapidly decreases with increasing forecast period.

-> In NWP the assimilation should first of all optimise the initial state

-> In atmospheric chemistry the assimilation should target the model processes, e.g. optimise the emissions, boundary conditions, deposition ..

Advanced assimilation approaches needed:Ensemble Kalman filter and 4D-Var approaches most popular

Assimilation: NWP vs. Atmospheric Chemistry


Assimilation: NWP vs. Atmospheric Chemistry

Courtesy: Hendrik Elbern, Köln

ForecastAnalysis

Initial-state

Initial-state + EmissionEmission


Dutch SmogProg project, User Support Programme, NIVR, 2007-2008

• Aim: To replace the (simple) statistical AQ forecast now issued by RIVM• Collaboration of three Dutch institutes

RIVM, KNMI, TNO• Based on Dutch LOTOS-EUROS model, and French CHIMERE model• Region covering the Netherlands and surroundings (about 10 km resol)

Use high-resolution meteorological input, i.e. KNMI - HIRLAM • Assimilation of surface and satellite data

NO2 from OMI on EOS-Aura• First focus on ozone and precursors

• Project started beginning 2007l

Air quality forecasts for the Netherlands


• Two-day ozone forecast available on the web (demo service)

http://www.lml.rivm.nl.nl

Air quality forecasts for the Netherlands

• Plan: become operational in May 2008

- ozone forecasts during summer.nl


Daily variation in ozone: Chimère vs surface

4 Aug 2007 5 Aug 2007 6 Aug 2007


OMI near-real time NO2, 13-16 October 2005


Chimere @ OMI overpass time, 13-16 Oct 2005


• LOTOS-EUROS + Ensemble Kalman FilterDeveloped at TNO / RIVM

• Interface between LE / Kalman,surface data and OMI-NO2 data available

• First experiments have started

Assimilation of satellite and surface data


Wang et al, GRL 2007

Pepijn Veefkind

Is OMI NO2 related to concentrations at surface ?


Cities of the size >100,000 habitantsCities of the size >100,000 habitants


• In a few years there will be operational systems in place for tropospheric composition and air quality forecasting / monitoring / reanalyses, similar to what is in place now for NWP

Europe: GMES Atmosphere Service

• These systems rely on high-quality observational data on especially the troposphere and boundary layer composition:

both in-situ (surface networks, aircraft, ..) and from satellites

• Sustainability preferred: operational satellites (such as sentinels 4 and 5)development of assimilation is long-term investment

• High spatial resolution important especially for regional AQModel resolution on European domain will be around 10 km or betteremission distribution very irregular (points, lines), chemistry non-linear

• Multiple observations/day and (near) global coverage of importance fordiurnal cycle of air pollution, daily monitoring, major events (dust/fire/transport)

TROPOMI measures key compounds (O3, NO2, CO, CH4, HCHO, SO2, ..)A TROPOMI - post EnviSat / Aura - would be major component of the GAS

Conclusions


That's all

eskes, tropomi workshop, mar 2008 air quality forecasting in europe henk eskes european ensemble...

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