Remote Sensing of Environment 120 (2012) 84–90

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Remote Sensing of Environment

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ESA's sentinel missions in support of Earth system science

Michael Berger a,⁎, Jose Moreno b, Johnny A. Johannessen c,d, Pieternel F. Levelt e,f, Ramon F. Hanssen f

a ESA-ESRIN, EOP-SA, Caselle Postale 64, 00044 Frascati (RM), Italyb University of Valencia, Dept. of Earth Physics and Thermodynamics, Faculty of Physics C. Dr. Moliner 50, 46100 Burjassot (Valencia), Spainc Nansen Environmental & Remote Sensing Center (NERSC), Thormohlensgate 47, 5006 Bergen, Norwayd Geophysical Institute, University of Bergen, Allegaten 70, Bergen, Norwaye KNMI, University of Technology Delft, The Netherlandsf Delft University of Technology, Kluyverweg 1, 2629 HS Delft, The Netherlands

⁎ Corresponding author. Tel.: +39 06 941 80597.E-mail address: Michael.Berger@esa.int (M. Berger).

0034-4257/$ – see front matter © 2012 Elsevier Inc. Alldoi:10.1016/j.rse.2011.07.023

a b s t r a c t

a r t i c l e i n f o

Article history:Received 20 December 2010Received in revised form 5 July 2011Accepted 7 July 2011Available online 23 February 2012

Keywords:SentinelESAEarth system scienceGlobal Monitoring for Environment andSecurity (GMES)

The spatial and temporal characteristics of the new Sentinel missions, primarily designed to provide routinemultidisciplinary observations for operational services, are also very suitable for addressing some of the chal-lenges associated with advancing Earth System sciences. The Sentinels are ensuring long-term observationalcommitment and will operate a range of instruments with different spectral bands and spatial resolutionswith global coverage and high revisit times.The complexity of Earth System models has been increasing gradually and most simulations of future climateand Earth system evolution are based on coupled models that include aspects of physics, bio/geo-chemistry,anthropogenic impacts and even recently some elements of socioeconomic factors. Sentinels will provideunique observations to describe such coupled atmosphere, oceans, land and cryosphere and the exchangesamong them into Earth System models.This paper emphasizes the indispensable value of the data provided by the family of Sentinel constellations inthe context of the urgent need for improved process understanding of the Earth system.

© 2012 Elsevier Inc. All rights reserved.

1. Introduction

In the coming decades mankind is faced with an urgent need to bet-ter understand and predict how the environment and resources on theEarth are affected by global warming as well as the correspondingsocio-economic implications of such warming. This is indisputably de-manding significant advances in our quantitative knowledge of Earthsystem processes and mutual feedback mechanisms on a wide span oftemporal and spatial scales. In turn, improved modelling system andpredictive skills can be expected to deliver better operational servicesas well as climate change predictions.

Earth-observation (EO) satellites provide one source of informa-tion needed to address some of the ‘grand challenges’ of Earth systemscience as elaborated in a consultative process by the InternationalCouncil for Science (ICSU) and the International Social Science Coun-cil (ISSC). Satellite observations support developing strategies to re-spond to ongoing global change while at the same time meetingsocietal development goals and help deepen knowledge of the func-tioning of the Earth system and its critical thresholds (Reid et al.,2010). In particular, they respond to the need to develop, enhance,and integrate monitoring and prediction systems to manage global

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and regional environmental change, and the determination of howto anticipate, avoid, and manage disruptive environmental changes.

Most models describe in a similar manner the fundamental basicprocesses, such as the planetary radiation balance. But as more com-plex processes are incorporated into the models, the knowledge ofthe processes and their feedback mechanisms, together with themathematical formulations and parameterizations, lead to largemodel discrepancies and even inconsistencies (Friedlingstein, 2006).

The current uncertainty in climate sensitivity (defined by the tem-perature change associated with a doubling of the atmospheric CO2

concentration) as stated in the Fourth Assessment Report of the Inter-governmental Panel on Climate Change (IPCC, 2007) ranges between2 and 4.5°, with the best estimate value of about 3°. Although the con-fidence level has increased it should be noted that about the samelevel of uncertainty was already reported in 1979 by the NationalAcademy of Science (see e.g. Kerr, 2004). Hence one may ask whatthe gain in Earth system knowledge is over the last few decades. Infact there are currently new findings coming along which are basedon Earth system models, and by confronting the models with consis-tent long-term data which are now becoming available to the sciencecommunity. This includes e.g. the elevated photosynthetic rate due todiffuse radiation e.g. caused by aerosols and clouds (Mercado et al.,2009) or the decline of the global evapotranspiration due to limitedmoisture supply during the last decade (Jung et al., 2010). Further ad-vances are expected by developing sophisticated data integration

85M. Berger et al. / Remote Sensing of Environment 120 (2012) 84–90

systems such as assimilation schemes which together with re-analysis tools will lead to an enhanced process understanding. Thiswas also emphasized in a commentary by Morel (2007) where hestated that ‘the sad fact is that few climate modellers devote muchtime to overcoming the very real difficulty of combining “modeldata” with real world observations’. New integrated data processingsystems are needed together with a model validation frameworkmaking use of data from climate proxies, in-situ measurement net-works and satellites. Satellite observations, with adequate temporaland spatial coverage, are considered particularly suitable for this un-dertaking, provided long-term continuity is ensured.

Earth observation science missions, such as ESA's Earth Explorers,with a typical lifetime of 3–5 years are suitable for addressing partic-ular aspects of the Earth system by providing new insight into domi-nant processes and feedback mechanisms. However, some of themost fundamental questions cannot be tackled with less than half adecade of data (Heimann, 2009). If we want to understand theinter-annual variations and their tele-connections to climate oscilla-tions with often decadal or longer periods, continuous monitoringprogrammes over timescales of decades are needed. In this regard,scientific ‘piggy backing’ on existing operational systems with long-term commitments like the family of Sentinel constellations, is offer-ing a true opportunity for the science community.

ESA is currently implementing, in coordination with the EuropeanUnion, a set of operational Earth observation missions with a long-term operational commitment (Aschbacher and Milagro-Perez,2012-this issue). These Sentinel missions are primarily designed toprovide routine observations for operational GMES services and en-sure data continuity of ERS, Envisat and SPOT/Landsat like observa-tions with improved observational capabilities (see Table 1: keymission characteristics of the Sentinels; for details see the Sentinelmission papers in this RSE issue, Torres et al., 2012-this issue, GMESSentinel-1 Mission, Drusch et al., 2012-this issue, GMES Sentinel-2,this RSE issue, Donlon et al., 2012-this issue, GMES Sentinel-3, thisRSE issue, Ingmann et al., 2012-this issue and Veefkind et al., 2012-this issue, GMES Sentinels 4, 5, and 5p, this RSE issue).

The manifold instrumentations with different spectral and spatialresolutions, the global coverage with high revisit times, and the long-term operational commitments of the Sentinel missions are support-ing data harmonisation and new science products which are very rel-evant for studying and monitoring of Earth system processes andinteractions. Furthermore, data quality and validity range will bemonitored continuously within the operational context which isvery beneficial for the scientific exploitation e.g. by ingesting thedata stream into assimilation schemes. As such the Mission Perfor-mance Centres (MPCs) for each Sentinel will be established to main-tain regular monitoring about:

• Calibration — to update on-board and on-ground configuration byanalysing the calibration data acquired by the instruments or thecalibration data processed in the vicarious calibration programme.

• Validation — to assess, by independent means, the quality of thedata products derived from the system outputs for eventual algo-rithm evolution and processor upgrades.

• Quality Control — to monitor the status of the spacecraft (payloadand platform) and to check if the derived products meet the qualityrequirements along mission life-time.

• Data processors (prototypes) and Quality Control tools for correctiveand evolutive maintenance — to manage the updates of the proces-sors and auxiliary files in order to ensure the overall quality targets.

• End-to-end system performance assessment — to detect anomalies atsystem-level and provide high-level performance figures on theoverall mission performance.

Through adequate availability and accessibility of the data and thederived products, complemented with an ‘open’ data policy, this will

stimulate the scientific exploitation of the Sentinel data streams(for details see: Aschbacher and Milagro-Perez, 2012-this issue).

2. A roadmap to address scientific challenges

The broad science community has outlined the scientific chal-lenges in various strategy documents (ESA, 2006). The role of sciencein the development of the Global Earth Observing System and its in-terrelationship with the societal benefit areas are emphasized bythe GEO Science and Technology Committee of the Group of Earth Ob-servation (GEO Science Technology Committee, 2008). With regard toclimate modelling, GCOS published recently an update on the Imple-mentation Plan of the Global Observing System for climate in supportof the UNFCCC (GCOS, 2010), and in particular the supplementary de-tails on Systematic Observation Requirements for Satellite-BasedProducts for Climate (2011 Satellite Supplement), and the UK RoyalSociety released a summary of the current scientific evidence on cli-mate change and its drivers (The Royal, 2010).The document listsmain aspects of climate change that are not yet well understood.

The derived Earth observation requirements are currently beingassessed with respect to the Sentinel missions by a dedicated ESAstudy (Malenovsky et al., 2012-this issue) and was discussed for theland, solid Earth, cryosphere and ocean community at a workshopin March 2011. A summary report of the workshop is provided onlineat http://www.sen4sci.org. A similar workshop addressing scientificproduct requirements for atmospheric sciences is under preparation.

In summary these strategic documents emphasize a range of highlevel requirements needed to make progress. Concerning satellite ob-servations these needs include:

• Improved observational capabilities including the development ofnew observation and measurement techniques by making use ofadvanced technologies;

• Provision of physically consistent data products together with a de-tailed description on their validity range and product confidencelimits supported by long-term validation and calibration frame-works, together with product inter-comparison activities aimingat the development of common methodologies;

• Development of more efficient tools for data analysis and dissemi-nation allowing both, observational and model-created informationto be extracted, combined and used in an efficient way;

• Adaptation of current Earth Systemmodels to ingest Earth Observa-tion data and the development of new models with increased pro-cess understanding in order to enhance forecast capabilities,

• Provision of long-term data records allowing assessing climate var-iability and trend analysis.

Considering these high-level requirements, ESA's scientific EarthExplorer missions (see e.g. http://www.esa.int/esaLP/LPearthexp.html) together with the operational Sentinel missions are well suitedto tackle these issues. Their data exploitation strategies and prepara-tory activities are therefore focussed on:

• Activities fostering interdisciplinary research by linking experimentalscientists, Earth System modelling communities and Earth observa-tion specialists of different disciplines in order to get a mutual un-derstanding of the different requirements and their priorities. Thisincludes increasing awareness of Earth observation data and theircapabilities with focus on common product definition, the organisa-tion and support of requirement assessment and consolidationworkshops, the support of smaller brainstorming discussion forumsand working groups focussing on specific topics as well as a contin-uous consultation of the science community for assessing short-comings and possible issues of priorities which could be assessedwith dedicated new Earth Explorer missions.

In this regard ESA draws on the experience of international re-search initiatives such as the projects of the Earth System Science

Table 1Most striking Sentinel mission/instrument characteristics (for further details and acronyms please see dedicated mission papers in this RSE issue).

Sentinel-1 Sentinel-2 Sentinel-3 Sentinel-5p Sentinel-4 Sentinel-5

Launch A-unit/B-unit

2013/18 months afterA-unit

2013/18 monthsafter A-unit

2013/18 months after A-unit 2014 2019 — embarkedon MTG-S1 andMTG-S2

2020+ —

embarked onMetop-SG

Design lifetimeper unit

7.25 yrs (consumablesfor 12 yrs)

7.25 yrs(consumables for12 yrs)

7.5 yrs (consumables for 12 yrs) 7 yrs

Orbit Sun-sync, 693 km/incl.98.18/LTAN 18:00

Sun-sync, 786 km/LTDN: 10:30

Sun-sync, 814.5 km, LTDN: 10:00 Sun-sync, 824 km,LTDN: 13:30

GEO Sun-sync —

under definitionInstrument C-band SAR MSI (multi-

spectral-instrument)

OLCI (ocean andland colourinstrument)

SLSTR (sea andland surfacetemperatureradiometer)

SRAL (Sentinel-3 Ku/Cradar altimeter)

MWR(microwaveradiometer)

POD (preciseorbitdetermination)

TROPOMI (UV–VIS–NIR–SWIR (UVNS)pushbroomspectrometer — intandem withNPOESS-VIIRS forcloud screening)

UVN+utilisation ofthe infraredsounder IRS onMTG-S and imagerdata from the MTG-I platforms forcloud screening

UVNS+utilisation ofTIR data from IRsounder andimagery data forcloud screeningon Metop-SG

Coverage Global/20 min per orbit All land surfacesand coastal waters+full med. seabetween: −56and +84° latitude,40 min imagingper orbit

Global Global Global Global Global Global Europe Global

Revisit 12 days (6 days for A- andB-units)

10 days (5 days forA- and B-units)

b4 days (b2 daysfor A- and B-units)

b4 days (b2 daysfor A- and B-units)

27 days Daily 60 min (goal:30 min)

Spatial resolution/swath width

Strip mode: 5×5m/80 kminterferometric wide-swathmode: 5×20m/250 km(standard mode) extra-wide-swath mode:20×40 m/400 km wavemode: 5×5m/20×20 km

Depending onspectral band 10–20–60 m/290 km

300 m/1270 km(with 5 westwardtilted cameras toavoid sun-glint,fully within SLSTRnadir and obliqueswath)

500 m (VIS, SWIR)1 km (MWIR,TIR)/1675 km(nadir)/750 km(backwards),nadir and 55°backwardsviewing

>2 km (centred nadirand within OLCI andSLST swath)

20 km(centred nadirand fullycollocatedwith SRAL)

7 km/~2100 km 8 km/N/S FOV:3.65°

Spectral coverage/resolution

5.405 GHz— VV+VH, HH+HV

13 spectral bands:443 nm–2190 nm(incl. 3 bands at60 m for atmos.corr.)

21 spectralbands:400 nm– 1020 nm

9 bands: (0.55–12 μm — newbands at 1.3 and2.2 μm)

Ku/C-band altimeter 23.8/36.5 GHz GPS, LRR andDORIS

270–495 nm 710–775 nm 2314–2382 nm/0.25 nmto 1.1 nm(depending on theband)

305–400 nm 400–500 nm 750–775 nm/0.12 nm to0.5 nm (dependingon the band)

Radiometricresolution/accuracy

1 dB (3 s) 12 bit/ b5% 2% absolute TIR NEdT: 50 mK Total range error:3 cm

3 K absolute(0.6 K relative)

3 cm finalaccuracy

/2%

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Partnership (ESSP), the challenges of the Living Planet Programme:The Changing Earth and on the scientific challenges as outlined bythe Group of Earth Observation's Communities of Practises, as wellas on the cooperation with the International Space Science Institute(ISSI) (http://www.issibern.ch) as a facilitator of interdisciplinary re-search. As one example of a research network linking remote sensingspecialists with the ecosystem modelling community, the EC fundedCOST action ‘Terrabites’ is named which aims at a cross-disciplinaryassessment of our current understanding of the terrestrial biospherefrom an Earth system perspective to improve the reliability of futureEarth system projections in coupled climate–biosphere simulations(Brovkin, Reick, & van Bodegom, 2010).

• Provision of data supporting initiatives aiming at the generation offundamental climate data records (FDCRs) and essential climatevariables (ECVs) as outlined by GCOS and the generation of new sci-ence products which is believed to lead to an increased process un-derstanding. This includes the provision of reference data sets anddedicated data handling toolboxes as well as sophisticated proces-sing environments (e.g. based on cloud/grid processing). Develop-ment activities for new science products by, in particular,accounting for the synergies provided by the different instruments,the demonstration of their impact within the model environment,and the development of novel data ingestion methods will be sup-ported. A series of preparatory activities were already launched byESA's Support To Science Element (STSE — see: http://wfaa-dat.esrin.esa.int/stse/) and ESA's Climate Change Initiative (CCI) is aim-ing to do this for selected ECVs based on archived data sets (for de-tails see: http://earth.eo.esa.int/workshops/esa_cci/). A rigorouserror assessment provided by on-board and vicarious calibrationactivities is foreseen within the operational context of the Sentinelmissions. Product consistency within their associated uncertaintiesand validity limitations will be assessed through specific validationby a detailed assessment of all uncertainties including those provid-ed by auxiliary information within the processing chain, includingalso internal consistence tests, cross-comparison between relatedproducts and dedicated validation campaigns. In this regard the sci-ence community will benefit from the functionality of the previous-ly mentioned Mission Performance Centres which are currentlybeing implemented within the operational context. Furthermore,novel data processing techniques by making use of community ra-diative transfer models and data assimilation techniques, allowingintegrating data from different missions by providing consistentdata products at the same time, will be fostered (see e.g. Lewiset al., 2012-this issue). As continuously more and more long-termdata records will become available, it is planned to encourage thescience community in utilizing these data streams and performingre-analysis activities.

These activities will ultimately lead to an increased process under-standing, a better model parameterisation and a subsequent modelimprovement, and thus to an overall increased understanding of theEarth system and its forecast capability. This is more substantiatedin the following chapters.

3. Improved process understanding and model parameterisation

The Sentinel missions will provide a global view of environmentalparameters of prime importance for climate and environmental re-search. These measurements will cover the atmosphere, the ocean,the cryosphere, the land surface and the solid Earth. The accuracy andhigh spatial resolution of the data will play a crucial role in order to bet-ter represent physical, chemical and biological processes in the modelsand develop more precise parameterizations of these processes and oftheir complex interactions and mutual feedback. Thus, the suite ofdata has an enormous potential for improving the predictive skills of

climate models including, for instance, the simulation of the carboncycle, the water cycle and of the atmospheric composition changes.

The science community will benefit from the advances in com-bined retrievals and inverse modelling and data assimilation tech-niques to incorporate remote observations into global climatemodels. Inverse modelling of the Sentinel global observations, sup-ported by high revisit times, will for instance directly allow determin-ing with a better accuracy bio-geophysical variables and thus fluxesand interactions between the surface and the atmosphere, with ex-plicit improvements in the representation of the carbon and water cy-cles in global models. The high temporal sampling also supports themonitoring of surface deformation with mm-precision enabling thesolid Earth sciences to start modelling inter-seismic strain accumula-tion, leading to improved understanding of global earthquake dy-namics (Walters et al., 2011), and the detection and monitoring oflandslides (Hilley et al., 2004). The same deformation measurementswill lead to an increased reliability in the prediction of volcanic erup-tions (Poland et al., 2006; Sigmundsson et al., 2010), which are inturn significant drivers for climatic anomalies (Fischer et al., 2007).

Improved understanding of the interactions between air qualityand climate forcing are also highly needed, since short-lived tracegases and aerosols play a double role. For example, the necessarymeasures to improve air quality may counteract climate mitigationpolicies. Strategies that take into account the complex chemical feed-back mechanisms between air pollutants and climate forcing need tobe sought (Shindell et al., 2009). Similar complex climate-couplingsexist with respect to stratospheric ozone and climate forcing, see forexample the climate forcing prevented by the Montreal Protocol(Velders et al., 2007) and the anticipated interactions between cli-mate change and ozone recovery in the 21st century.

The atmospheric Sentinel data are further needed to improve our un-derstanding of the physical and chemical processes concerning climatechange, air quality, and ozone layer. Improvements in the Earth Systemmodelling combining climate and atmospheric chemistry are for a largepart dependent on availability and improvement of long-term atmo-spheric composition data records in terms of timeliness (daily or even di-urnal observations), accuracy, spatial resolution, vertical resolution, andglobal coverage. The data of Sentinels 4 and 5, including the Sentinel-5Precursor mission, can be used for emission source identification andquantification using inverse modelling techniques. This information willimprove the boundary conditions for the climate and air quality models,as well as better constrain current emission data bases. Currently climateand air quality models use bottom-up estimates (i.e. a calculation of theatmospheric emissions based on certain assumptions) and are thus notbased on direct measurements of emission sources.

Research projects assimilating atmospheric Sentinel data in semi-operational models will prepare for a Global Atmospheric CompositionService using the data in operational forecasting systems for e.g. UV andair quality and aviation warning systems after volcanic eruptions.

In addition to their use in global climate models, the Sentinel mea-surements through harmonised data streams will also be extremelyvaluable for improving numerical weather prediction. In particular,atmospheric trace gas and aerosol measurements have the potentialto improve weather forecasting. Tropospheric ozone and aerosols at-tenuate atmospheric radiation, thereby modifying the temperatureprofile and directly influencing weather. Aerosols act as cloud con-densation nuclei and have a strong impact on the hydrological cycle.Gradients in trace gas concentrations contain dynamical informationrelevant for weather forecasting, such as the wind speed and direc-tion, strength of convection, and the amplitude of wave activity.

The case of Land Surface parameterizations in Earth Systemmodels is another good example on how Sentinels can contribute.Two critical issues in such models are the adequate parameterizationof heterogeneity and the prescription of temporal changes, also dif-ferentiating from changes in composition and structure (i.e., landcover change) or changes in and functioning (i.e., seasonal vegetation

88 M. Berger et al. / Remote Sensing of Environment 120 (2012) 84–90

dynamics). With Sentinel data, systematic global information will beavailable at high spatial resolution (up to 10 m), while the high tem-poral repetition of measurements will also allow to monitor changesat scales of days or weeks. Even though it is unlikely that globalmodels at such high spatial resolution will be developed in a shorttime, current models at lower resolution still need to parameterizethe within-cell variability, but such data are currently missing at theadequate spatial scales. The prescription of temporal changes is cur-rently quite empirical, even for smooth changes as seasonal dynam-ics, and very poor parameterizations exist for abrupt changes instructure (Jonsson & Eklundh, 2002; Verbesselt et al., 2010), whichleads to a simplistic treatment of such processes in Earth Systemmodels. Even though the Sentinel series represents a continuityover current systems (i.e., Landsat, SPOT, MERIS, etc.) it will be thesystematic availability of the data simultaneously at rather high spa-tial resolution and with good temporal sampling (something neveravailable before) that will make the Sentinel data especially attractivefor this purpose. Examples include the rapid changes in biomass cov-erage in countries such as Brazil, where the economic value of bio-renewable is increasing exponentially.

Studies of mesoscale upper ocean dynamics, air–sea interactionand coupled bio-physical processes are highly needed to advancethe understanding of the role of the ocean in the Earth system. Thedevelopment of weather and climate on Earth is the integral resultof how the sun's energy penetrates and is transformed at the bound-aries between atmosphere, land and cryosphere, and at the highly dy-namic and wavy atmosphere–ocean boundary. Although circulationmodels include interactive air–sea processes they are not adequatelyparameterized. This equally applies to global and regional forecastsystems as well as coupled bio-physical models. Nearly 50% of thetotal primary production on Earth occurs within the thin ocean-mixed layer by the tiny phytoplankton organisms, which can occurat concentrations that alter penetration of the sun's radiation andmodify the vertical structure of heat content through the upperocean. Moreover, phytoplankton has the potential to change the seawater viscosity and turbulent fluxes, and, in turn, influence the verti-cal distribution of plankton. These critical coupled physical and ma-rine biosphere processes have hitherto not been considered inconcert and most climate models are not including any biologicalfeedbacks. The important long-term provision of ocean surface data(SST, surface current, sea surface height, Chlorophyll-a, wave fieldand high resolution wind field) from the Sentinels is thereforeexpected to stimulate and trigger advances in process understandingas well as development of more reliable models.

Although satellite observations have revealed significant changestaking place in the cryosphere, the attribution of these changes to ei-ther anthropogenic or natural causes remains unclear. Hence the na-ture of cryosphere interaction with the oceans, atmosphere andterrestrial systems, and the understanding of the role of the cryo-sphere for the Earth system remain incomplete. The major challengesare connected with adequate knowledge of the freshwater balance,seasonal to decadal changes in sea ice volume, sea ice deformation,rapid ice sheet dynamics along the margins, and their feedbacks tothe ocean and atmosphere. As a result, we are not yet fully capableof assessing the current and potential future cryosphere (includingfloating ice shelves) impact on sea level, ocean circulation andwater cycle. Moreover, the current and potential impact of the cryo-sphere on energy, moisture and trace gas fluxes between the land, at-mosphere and ocean needs to be evaluated. Frozen ground andpermafrost act to constrain physical and biogeochemical processesand remain largely untreated in present-day climate models. As a re-sult, fluxes of trace gases from northern ecosystems, along with hy-drological and energy flux changes represent highly uncertaincomponents of future global change. With the regular long-term pro-vision of Sentinel data the scientific community has therefore theprospect of contributing to improve the parameterisation of a range

of cryospheric processes in coupled ice–ocean–atmosphere models.This, in turn, may lead to more accurate prediction of the role of thecryosphere in climate change, as well as its impact on regionalwater resources, biosphere and natural hazards.

4. Long-term data record

The data continuity ensured by the Sentinelswill significantly contrib-ute to the growth of the data records and the reliability of trend estimates,thus increasing the value of several of the essential climate variables spec-ified by (GCOS, 2010). As the length of these data records increases, insome cases now at around 20–30 years, and as they gradually becomeof better quality and accuracy, adequate validation and adaptation to bet-ter initialization of climate models is becoming feasible. As such they willbe of fundamental importance for Earth system science. For instance, pre-dicting decadal climate variations over the next 10–30 years is criticallydependent on both knowing the current state of the Earth system aswell as monitoring how it evolves in order to keep climate models ontrack. The space-borne data continuity and systematic availability aretherefore a critical issue in order to develop adequate methods to assim-ilate the data streams into coupled Earth System models. This is a majorchallenge in climate research, in which quality control of themodel fieldsis performed through regular and consistent validation and inter-comparison against independent long term data records. Moreover, con-struction and implementation of realistic initial conditions using long-term observation data are also recognized to be essential for reducingthe uncertainty in predictions up to 30 years (Cox & Stephenson, 2007).If therefore we wish to reduce the uncertainty in climate predictionsover a period of 10–30 years, now considered extremely important byIPCC and UNFCC (IPCC, 2007), the primary need is for more, better andlonger observation records of key essential climate variables. Conse-quently, the Sentinel missions, with their additional capacity to providesimultaneous multidisciplinary observations, will be an essential tool forclimate change research in the coming years.

5. Integrated processing

Running global coupled models would need integration of atmo-spheric, oceanic, cryospheric and land surface data, plus inputs comingfrom multiple sources describing dynamical processes, accounting forspatial and temporal scales from metres and hours up to hundreds ofkilometres and decades. This is definitely a huge challenge, not onlyfrom the point of viewof the amount of data to copewith or the comput-er resources to run the whole data assimilation system, but also for thedevelopment of such advancedmodelling scheme.While such objectiveseems reachable only in the far future, it will be a difficult and long pro-cess. The timeliness of all Sentinels, providing all data in a coordinatedmanner, is a key element supporting an integratedprocessing in coupledEarth System models. While models used initially may be limited in itscapability to assimilate such data streams coming from Sentinels, thesystematic data availably will furthermore support long-term trendanalysis including their teleconnections which may eventually lead tonew insights in our process understanding, and thus systematic im-provements in the modelling tools and more advanced mathematicaldata assimilation strategies. Key is a good physical understanding ofthe processes and their interactions in an integrativemodelling environ-ment coupled with a sophisticated data ingestion system which allowsconfronting the virtual world of models with real data. As process vari-ables are interlinked and as some variables are observed by differentsystems and thus at different local times, synergistic retrieval ap-proaches and novel assimilation schemes to cover the temporal differ-ences need to be developed. This integrative model environmentallows assessing the model validity and supports subsequent model im-provement through long term consistent data series of global satelliteobservations like the ones provided by Sentinels.

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In this context, the definite specific role for Sentinels in combina-tion with the whole network of already existing satellite systems (likethe geostationary meteorological satellites, Earth Explorer systems,constellation of very high resolution observations, or long time seriesin the past from Landsat or other satellites) must be emphasized.What is really new in Sentinels is that the whole information is pro-vided simultaneously in a systematic manner. For instance, it isclear that having global observations from Sentinel-2 in such spatialresolution cannot be handled by current models, but the improvedparameterization of subgrid heterogeneity coming from such datawill improve the representation of land–atmosphere and land–ocean exchanges, thus contributing to improve the whole Earth Sys-tem model. It is not the direct ingestion of the whole dataset thatcould improve the models, but an intelligent strategy on how theavailable information is properly exploited. It is true that trying to in-tegrate all data together in a huge complex model may seem unreal-istic, but the approach of using smaller models to get a betterparameterisation, and then use the learned strategies in the globalmodel is a proper approach. It is well known that representing pro-cesses in models depend on the identified inputs, and it will takesome time until models are adapted to ingest the input data comingfrom Sentinels, but such long-term perspective is needed and shouldbe focused on what Sentinels in particular can do, given the identifieddata streams for the coming decades.

Amultidisciplinary integrated data processing approach can only beimplemented if all the necessary inputs are provided in a timely man-ner, with adequate spatial and temporal sampling, and providing valueswith a given accuracy and their associated uncertainties and cross-correlation of uncertainties among information derived from the samedata sources. This is essential in the case of using Earth Observationdata in climate models as different spatial and temporal variabilityhave different impacts. Sentinel data products should be designed keep-ing inmind such climatemonitoring requirements and the capability toprovide consistent inputs to themodels properly accounting for the un-certainties associated to each one of the Sentinel products.

The capability of re-analysis of long time series should enable im-proved real-time data assimilation, while at the same time the predic-tive capability of the models is continuously being improved. Theopportunity to have consistent long-term series of global data withhigh spatial resolution from Sentinels will provide the necessary ele-ments to have a really consistent provision of inputs for local/regionalprocesses into global models. The future Earth observing systembased on Sentinels should be designed and implemented with afocus on deriving, disseminating and using the information contentof multi-disciplinary observations and not just the observationsthemselves. In fact, while Sentinels are only the space component,the overall GMES programme aims at integrating space observations,ground networks of observations and the necessary models and toolsto address the scientific challenges and associated applications.

The demanding technology and infrastructures that need to be inplace to handle such huge amounts of data, as provided by the Senti-nel family of satellites are currently being developed and implemen-ted. In the long term, it will be possible to run global models wherethe different physical, chemical and biological processes, with thecorresponding links and feedbacks, are properly accounted for in aglobal integrated data processing system at the relevant spatial andtemporal scales (see e.g. Lewis et al., 2012-this issue). The familiesof the Sentinel missions will make this possible not only for the atmo-sphere, the oceans and the cryosphere, but also for the land compo-nent, providing a high spatial resolution dynamic framework(continuously updated) where all inputs can be assimilated throughintegrated processing, with continuous systematic access to globaldata in a way never available before.

The long term commitment of guaranteed consistent data provisionover decades (>20 years) will motivate modellers and the scientificcommunity in general to develop the necessary tools. While the

scientific knowledge and capabilities, and the required technologies,are mostly already available, the motivation to develop such advancedEarth System Models and the corresponding Data Assimilation Tech-niques will only come if the data streams are identified, and the roleof Sentinel data in such approach is probably unique in the current en-visaged long-term Earth Observation capabilities at the internationallevel.

6. Summary and outlook

Data streams from various Earth observing satellite systems includ-ing ESA's ERS-1, ERS-2, and Envisat mission have gradually becomeopen and freely available in the last decade with a significant benefitto the multidisciplinary Earth science community. The correspondinggrowing exploitation of these data is well documented in the scientificliterature as well as in the increasing number of operational services.

Recently, a new era in the ESA Earth Observation programmeemerged with the implementation of the Earth Explorer missions,the continuity of well-established meteorological missions and thedevelopment of the Sentinel space component for GMES. These mis-sions will provide the science community an unprecedented observa-tion capacity in addressing the challenges outlined in the ESA's LivingPlanet Program (ESA, 2006) and the objectives outlined by the majorinternational scientific initiatives.

The Sentinel missions will provide systematic continuity of dataalready widely used within the science and application communitiesand specifically ensure long-term operational commitment and dataconsistency. Furthermore, the high temporal revisits, well-matchedfor capturing rapid changes, are supporting process understanding,model validations and development, and moreover fostering an inte-grated data analysis based on sophisticated assimilation schemes. TheSentinels have been designed with “extra” capabilities to guaranteesuch data consistency and harmonisation. For instance, Sentinel-2and Sentinel-3 have dedicated additional spectral bands used just toprovide better cloud screening and better compensation of atmo-spheric effects, decoupling the surface and atmospheric changes intemporal series of data. This is rather new and innovative in satellitesystems primarily intended for operational services, but such guaran-teed generation of consistent products and overall data harmonisa-tion are a prerequisite for establishing fundamental climate datarecords. Climate prediction will certainly benefit from this develop-ment as long time series (>20–30 years) will become available forthe extension of fundamental climate data records and multi-parameter trend analyses.

The first three Sentinel constellations will be operational simulta-neously frommid 2015 and will complement a range of science specificmissions such as the Earth Explorers, offering synergies starting fromthe provision of auxiliary information to substantial inputs for addres-sing scientific challenges. The timeliness furthermore fosters and callsfor multidisciplinary integrated data exploitation strategies which areconsidered of paramount importance for the development of a holisticEarth system approach. The integrated data analysis shall be furtherstimulated by dedicated theme oriented exploitation initiatives, tai-lored to advancing the understanding of themultidisciplinary Earth sys-tem coordinated with international science communities.

It is obvious that this can only be achieved if the data streams fromthe Sentinel missions are readily available to the science community.It will commence a new and exciting period of integrated EO science.

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