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