Development of an “end-to-end” altimeter mission simulator

Alix Lombard - Juliette Lambin (CNES)Laurent Roblou – Julien Lamouroux (NOVELTIS)

Context

Debates on future altimetry constellation design need for continuity and complementarity between missions variety of applications (climate, meso-scale, operational,…) but all need multi-mission orbit : sun-synchronous or not, cycle/repetitivity, existing tracks or not, … payload : bi-frequency or not, radiometer or not, platform stability (roll for wide-swath altimeter), … data : sampling, latency/availability, …

Need for a decision-making tool :”End-to-end” mission simulator (R&D CNES funding)

objective : examine the merits of various observing configurations / discriminate among them need for a simple, flexible, evolutive tool

Analyzer

(assimilation)

Sampler

(pseudo-observations)

Multi-missions obs. systems

Storm surges(model)

Altimetryconfigurationperformances

Status : end-to-end altimeter mission simulator for storm surge observations

• Possibility of studying multi-missions altimetry configurations, easy tuning of orbit configurations parameters

Framework of Observing-Systems Simulation Experiments (OSSEs, Arnold and

Dey, 1986) : designed to evaluate the impact of observing system data in numerical analysis.

“Ensemble Twin Experiments” method (Mourre et al., 2004) : pseudo-observations generated from a “control” simulation (oceanic model) then assimilated in a “free” simulation

The performance of the system is estimated in terms of model error (=ensemble variance) reduction performed via a data assimilation system.

Methodology

Model configuration : MOG-2D / T-UGO 2D (F. Lyard) barotropic, non linear, finite element zone : well known / studied and representative / varied (open ocean, shelf and coastal seas) time period : 15 days, typical / varied winter storm surges conditions (16/11 to 01/12/1999) atmospheric forcing: surf. pressure / 10m-wind (ARPEGE) tidal forcing

Nadir Wide swath

Generation of pseudo-observations Altimetry configuration set up by user (specify orbit parameters) pseudo-obs. (Sea Level Anomaly) extracted from the model reference simulation (non-perturbed run), at the space-time altimetry positions then noise-added (gaussian noise of 0-mean and standard deviation specified by instrument noise level)

Model errors computation (prior requirement for data assimilation) estimated from a 100 Ensemble simulations of the model in response to atmospheric forcing errors (surf. pressure and 10m-wind perturbed) [Lamouroux, 2006] error statistics thus estimated by the ensemble variance of the model at each analysis time step (daily) – errors variable in time and space

11 cm²

0 cm²

20/11

Data assimilation / Performance analysis method s-EnROOI (simplified Ensemble Reduced Order Optimal Interpolation) configuration

“simplified” : no sequential control of the model (ensemble error reduction only estimated at analysis time, not propagated in time via the model) → quick execution / results obtained

Possibility to implement EnROOI, ROEnKF, EnKF (higher performance but longer computational time)… but idea to keep a simple / quick decision-making tool to discriminate between various observing scenario

SEQUOIA + MANTA codes used (De Mey, 2005)

Methodology

Model reference simulation

Ensemble variance reduction estimation at each analysis time step

Perturbed simulations

Validation

“Ideal” observing system regularly spaced grid pseudo-obs / analysis daily

11 cm² 11 cm²

0 cm² 0 cm²

Results for Ta = 20/11/1999 (analysis time representative of model errors over the whole period)

Ensemble variance of the model

(before correction)

Ensemble variance after pseudo-obs.

assimilation

Strong and uniform reduction of variance, especially in the English Channel (gain Ta ~ 94%)

100 %

50

80

% of ensemble variance reduction

over the period

Time-averaged result

Over the whole period (synthetic gain ~ 78%), methodology validated

Performance of various altimetry configuration

SWOT on a JASON orbit

100

70

40

JASON-1

Efficient tool to estimate the performances of various altimetry configuration and to discriminate among them.

Allow to design orbit and assess performances of multi-satellite altimetry systems

NB: the higher the percentage of variance reduction, the more the altimeter mission will provide helpful information to storm surges models

Lamouroux et al, OSTST meeting, Hobart, 2007

Various performance diagnostics at each analysis time step, mapped synthetic over the period, space averaged …

Reduction of ensemble variance time-averaged over the period

Evolution : end-to-end altimeter mission simulator for the study of tide aliasing question

AnalyzerSampler

Multi-missions obs. systems

Tides

Storm surges

Oceanic

circulation

Tides aliasing

diagnostics

Altimetry

configuration

performances

Existing module

Context of possible sun-synchronous orbit configurations (SWOT, Jason-3, Sentinel-3, …) → tide aliasing problem

Extension work in progress

Evolution : end-to-end altimeter mission simulator for the study of tide aliasing question

Same methodology but some evolutions needed → some work done, some in progress

Generation of pseudo-observations : ocean tide model reference simulation (non-perturbed run) → high frequency (HF) lower frequency (LF) ocean circulation simulation (daily reanalysis from PSY2V2 global ocean model computed by MERCATOR-Ocean) pseudo-obs. extracted from the sum of both simulations (ocean tide HF + ocean circulation LF), at the space-time altimetry positions → take into account the coupling HF aliased by altimetry sampling at LF / LF circulation

Ocean tide model configuration : T-UGO 2D 28 ocean tide components, model validated through comparisons with FES2004 / GOT00b larger zone (long wave dynamics of ocean tides) 1-year simulation model dissipation parameters : topography, bottom friction coefficient, transfer coefficient towards barocline modes

Model errors computation : estimated from ensemble simulations of the model in response to perturbed model dissipation parameters work in progress

Conclusions and perspectives

Work in progress for tidal analysis (end of R&D funding + SWOT PASO study) ensemble model error statistics (ensemble variance) computation implementation of specific tide aliasing diagnostics more realistic observation errors to be defined (especially for wide-swath altimeter) case studies (inferred from PASO SWOT instrument study)

First prototype of the simulator (storm-surge model) efficient tool to estimate the performances of various altimetry configuration and

discriminate among them simple, highly flexible and evolutive, first version of a powerful tool for designing orbit for multi-satellite altimetry systems (Jason-3, SWOT, Sentinel-3 …)

Work plan / Perspectives further tests of altimetry configurations : case studies, ≠ realistic mission scenario tests implement other oceanic processes : ocean circulation, waves, … implement more complex data assimilation scheme : e.g. for refined studies