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Status of ECCO v4r3 extension and ice-shelf melt-rate optimization
UT Austin: PATRICK HEIMBACH
MIT: GAEL FORGET
AER: RUI PONTE
© 2018. All rights reserved.
Ou Wang, Ichiro Fukumori, and Ian Fenty
Estimating the Circulation and Climate of the Ocean
Part I: V4r3 extension
Part II: Ice-shelf melt rate optimization
jpl.nasa.gov
Release 1 Release 2
2014 2016
Timeline of ECCO Version 42017
J F M A M J J A S O N D J F M A M J J A S O
Release 3Updating forcing and new observations.
Extension iterations
2018
Part I: V4r3 extension
jpl.nasa.gov
• Optimization first conducted for 2014-2017 when the
majority of new observations are added:
• Turning on time-anomaly data costs only;
• Adjusting time-variable atmospheric controls;
• Using V4r3’s other control adjustments;
• ~50 iterations conducted for 2014-2017;
• Conducting iterations for the whole 26-year of 1992-
2017 with everything turned on.
V4r3 being extended thru 2017
Variable R3 Ext. Comments
cg2dTargetResWunit 1e-12 N/ANow using non-dimensional
convergence criteria
SEAICEadvScheme 30 33From 3rd-order direct space
& time to flux-limited 3rd-DST (suggested by Martin Losch)
• Improve accuracy of the 2D conjugate-gradient solver (CG2D) by applying non-dimensional convergence criteria;
• Revised sea-ice time-stepping scheme.
Model:
ECCO V4 Release 3 Ext. (what’s different)
~5000W/m2 oceQnet caused by SEAICEadvScheme=30
Maps for March 2014 from runs over 2014-2017
5000W/m2
SEAICEadvScheme = 33(3-DST flux limited);Similar results if using SEAICEadvScheme=77 (Non-linear flux limited).
SEAICEadvScheme = 30(3rd Order Direct Space & Time).The adv. scheme generated large unphysical negative HEFF that needs ~5000W/m2 to the ocean to make HEFF non-negative.This large heat flux causes >10m increase of sea-ice at a neighboringgrid point in one month.
AmundsenSea
12m
+ is downward
Updated forcing and observation:
AERMIT
UT
JPLSIO
ITP, GOSHIP (S. Escher)
CTD, XBT, GLD, APB/Seals, MRB, sea-ice (I. Fenty);SSH, SST (O. Wang);Forcing (H. Zhang).
GRACE, Aquarius, GMSL, GMBP, MDT (R. Ponte)
Argo (G. Forget)
MEOP/Seals, TAO (D. Trossman)
ECCO V4 Release 3 Ext. (what’s different)
‘92 ‘00 ‘05 ‘10 ‘15 ‘17SSHSSTSIOBPSSSGMSLGMBP
Data CoverageRed = R3, Blue = extension
SI: Sea-ice concentration
In situ T Coverage Red = R3, Blue = extension
‘92 ‘00 ‘05 ‘10 ‘15 ‘17ArgoXBTCTDITPCLIMODESealsGliderGOSHIPBeaufort GyreDavis Str.TAO/other moorings
In situ S Coverage: Red = R3, Blue = extension‘92 ‘00 ‘05 ‘10 ‘15 ‘17
ArgoCTDITPCLIMODE
SealsGliderGOSHIPBeaufort GyreDavis Str.Bering Str.
Fram Str.TAO/other moorings
Number of T profiles vs. dataset:Red = R3, Blue = Ext., Black = Ext./R3
ext./
v4r3
Num
ber (
in m
illion
s)
Argo CTDXBT APB (marine mammals)
ITP
Novel profiles:Red = R3/Extension, Blue = Extension only
APB (marine mammals)
Glider
ITP
Novel mooring data:Red = R3/Extension, Blue = Extension only
Moorings
1. Convert to MITprof profile format2. Map data to model grid3. Add corresponding monthly climatology4. Map data to geodesic grids
• Supports mean and anomaly profile cost formulation
5. Add spatially-varying weights6. Convert in-situ T to potential T (when
necessary)7. Change weights to zero for bad or
missing data8. Multiply weights by relative grid-cell
area factor (γ)• γ = A(i)/max(A)
9. Remove profiles with zero weights
In situ Data Processing Sequence
Ten tests to zero out in-situ data weights
1. Inherited weight = 02. Nonzero QC flag3. Missing value4. T or S value identically zero5. T or S value outside physical range6. No corresponding climatology value7. Invalid date or time8. Invalid location9. Average average cost of entire profile
vs. climatology exceeds threshold10. Average cost of individual
observation vs. climatology exceeds threshold
update_zero_weight_points_on_prepared_profiles.m
Processing code:https://github.com/ECCO-GROUP/OBS_DATA_PROCESSING
jpl.nasa.gov
COST REDUCTION AND NORMALIZED COST VS. Ext. ITER0
% COST REDUCTION
NORMALIZED COST(COST PER DATUM)
1
2
3
-0.6
-0.4
0
-0.2
-0.8
0.2
-
+
fc
OBP
Prof
mn
T
prof
mn
S
For 2014-2017; black: iter0; magenta to red: iter10 to 52.
Fit to GRACE (Normalized Cost)
Iter52Iter0
2014-2107
Profile T and S:Uncertainty normalized model-data before and after novel APB data
Pre-new APB
Post-new APB
300-m, 2014-2017
T S
Large-scale SSH: Variance through time (cm2)
2000 2005 2010 20151995
model data
residual
0
20
40
60
AMOC: Rapid vs. Model (in Sv)
V4r3 extensiondata
2004 2006 2008 2010 2012 2014 2016 2018
10
20
30
26.5 N
• Configuration based on v4r3;• Updated bathymetry in Antarctic;• Data: Rignot et al. (2013) estimate of mean melt rate;• Code: Merged shelf-ice & ice-front packages (I. Fenty);• Control: ice-ocean heat transfer coefficient
• 3-d varying, but temporally invariant;• Initial guess is constant.
One-year (2010) experimental runsConfiguration:
Part II: Antarctic ice-shelf melt rate optimization
land
ice-shelfX
Y
ice-frontZ
Ice-shelf vs. ice-front:
Area-wise, ice-shelf >> ice-front in Antarctic.
ocean
T,S,& FW (q)
Thermodynamics of ice-ocean interactions:3 equations and 3 unknowns
TB = aSB + b+ cpB
Ice-shelf (Tice, Sice)
Unknowns: ice-ocean boundary layer TB and SB, and melt-rate q
Ocean (T, S)
ice-ocean boundary layer (TB, SB)
heat conservation
salt conservation
Linearized version of sea-water freezing point
Holland & Jenkins (1999)
q
Assumptions: • Ice-shelf and ice-front are
infinite reservoirs;• Heat and salt transfer
coefficients (m/s) are linearly related
• …
Sea-floor depth: v4 vs. IBCSO
v4
IBCSO
0-3000-6000
10000-1000
IBCSO-v4
(in meters)
Sea-floor depth vs. ice-shelf thickness (m):
Ice-shelf thickness (BEDMAP-2)
0
-4000
-2000
0
4000
2000
Sea-floor depth
Ice shelf cavity thickness (m):
0
500
200
100
300
400
Melt rate estimate (m/yr):
Rignot et al. (2013)
Melt rate (m/yr)Rignot et al. (2013)
Fractional cost vs. iterations
iteration 0
iteration 27
0.2
0.4
0.6
0.8
1
0 10 205 15 25
758Gt/yr, 16%
1156Gt/yr, 100%681Gt/yr
Data constraint: mean melt rate;Control: ice-ocean heat transfer coefficient(3d varying)
Freshwater flux
m/yr
ERA-interim precipitation2300 Gt/yr
River runoff in v42205 Gt/yr
Melt rate 682 Gt/yr
Rignot et al. (2013)Fekete et al. (2002)
jpl.nasa.gov
Summary• V4r3 being extending thru 2017 with
extended datasets;• Experimental ice-shelf melt rate
optimization working;• Adding ice-shelf melt to model requiring
modification of v4 runoff.
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