Consequences of Using Different Altimeter Products on the Interpretation of the Sea Level Change 1993-2001

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Alfred Wegener Institute for Polar and Marine Research

Consequences of Using Different Altimeter Products on the Interpretation of the Sea Level Change 1993-2001

M. Wenzel and J. Schr¨oter

Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany

Introduction

1993 1994 1995 1996 1997 1998 1999 2000 2001

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cm

CCAR OSU

GSFC GfZ

global mean SSHA

Fig. 1: Evolution of the global mean sea level during 1993-2001 as estimated by four different groups processing the TOPEX/Poseidon altimeter measurements.

Data provided by

CCAR: Colorado Center for Astrodynamics Research (Eric Leuliette) OSU : Ohio State University (Chung-Yen Kuo)

GSFC: NASA/GSFC Ocean Pathfinder Project (ftp server) GfZ : Geoforschungszentrum Potsdam (Saskia Esselborn)

In principle sea level changes can be measured accurately by satellite altimetry, but the processing of the data includes many corrections.

At this step the choise of the algorithms and the additional correction data is free to subjective preferences to a certain extent. For sure each choise has its own justification, but this finally leads to differences in the products that are delivered to the end user. As an example Fig.1 shows the temporal evolution of the global mean sea level as estimated by four different groups.

From the end users point of view it is interesting to see what are the consequences of using different products e.g. in ocean state esti- mation. For that reason we performed two assimilation experiments utilizing the sea level anomaly maps from the NASA/GSFC Ocean Pathfinder Project (NASA/GSFC) and from the Geoforschungszen- trum Potsdam (GfZ) respectively covering the years 1993 to 2001.

assimilation

experiment SSHA data source

BRIO2C NASA/GSFC B2ntp GfZ Potsdam

Both assimilation experiments, BRIO2C and B2ntp, start from the same first guess. Thus they differ only in the sea surface height anomalies used!

Method

The OGCM that is used to study the impact of the different sea level anomaly products on the ocean state is based on the Hamburg Large Scale Geostrophic model LSG. The main improvement of the model is the ability to estimate the single contributions to sea level change, the steric (thermosteric, halosteric) and the non-steric effects (local freshwater balance, mass redistribution) seperately.

The model has a 2^o × 2^o horizontal resolution, 23 vertical layers and a ten day timestep. Nine years (1993-2001) of respective TO- PEX/Poseidon (T/P) sea surface height anomalies are assimilated in- to the model. In addition the SHOM98.2 mean sea surface relative to the GRACE geoid (GfZ) as well as sea surface temperatures and ice cover information from Reynolds (2002) are assimilated into the model. Furthermore background information from the Levitus WOA98 is used.

To adjust the model to the data the adjoint method is employed. The control parameters of this optimization are the models initial temperature and salinity state as well as the forcing fields (windstress, air temperature and surface freshwater flux). The forcing is optimized via an empirical orthogonal function (EOF) decomposition, with the first guess taken from the NCEP reanalysis.

Comparing TOPEX Data Products: GfZ vs. NASA/GSFC

1993 1994 1995 1996 1997 1998 1999 2000 2001 -2.0

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regional mean

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global mean

Atlantic Pacific Indic

deviation from global global

regional mean / difference / GfZ - NASA/GSFC

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GfZ vs. NASA/GSFC

cm

1993-2001

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sea surface height anomaly

temporal rms of local difference

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0.902 area mean:

1993-2001

c.i. 0.05

sea surface height anomaly correlation

Fig. 2: (left) Temporal evolution of area mean differences between the NASA/GSFC and the GfZ dataset. For the single oceans only the excess to the global difference is shown! (center) Temporal RMS of the local differences and (right) the local correlation

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NASA/GSFC

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1993-2001

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sea surface height anomaly local linear trend

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0.244 area mean:

GfZ

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1993-2001

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0.087 area mean:

cm/year

1993-2001

difference local linear trend

Fig. 3: Local sea level trend as derived from the NASA/GSFC dataset (left) and from the GfZ dataset (center) as well as the difference in these trends (right)

It is not the purpose of this presentation to compare or even judge the single correction steps applied to the TOPEX data by the different groups. Therefore we on- ly give a short comparison of the finally resulting pro- ducts used in the assimilation experiments.

Although the datasets from the NASA/GSFC and from the GfZ respectively, are hightly correlated in time (Fig.2 right), especially in the northern hemispere, one finds differences in the temporal evolution of the global mean, which range up to ±2cm (Fig.2 left).

Even for the area mean of the single ocean basins one finds additional deviations exceeding the global up to ±1.5cm. Nevertheless the temporal RMS of the differences show up fairly constant at a 1cm level (Fig.2 center) with maximum values (up to 3cm) found in regions with hight oceanic variability like in the Kuroshio, at the Falkland/Malvinas Plateau or in the Gulf Stream area.

The local linear trend of the NASA/GSFC (Fig.3 left) and the GfZ dataset (Fig.3 center) exhibit essential- ly the same spatial structure but with an 0.087cm/year global mean offset. The positive differences in the trend range up to 0.3cm/year locally, e.g. in the North Pacific, but especially in the region south of 30^oS one finds also negative differences up to –0.2cm/year (Fig.3 right).

Comparing Model Sea Surface Height to Data

Figure 4 shows that the optimized models repro- duce their corresponding global mean sea level data well. This is true especially for the interannual variabilty, while the amplitude of the annual cycle is underestimated by the models. The latter appears to be a general deficit of the OGCM used and leads to the maxima in the temporal RMS dif- ferences shown in Fig.5. The spatial distribution of the RMS is very simular for both experiments and reaches values of up to 7cm especially in the tropics and in the western boundary currents. Al- so their global mean RMS values, which are the measure of success in the assimilation, appear to be comparable (2.83cm and 2.81cm respectively).

The same good correspondence between the two experiments one also finds for the differences between the modeled temporal mean sea level and the SHOM98.2 sea level (Fig.6). In most of the world ocean the differences are below 10cm. Larger vau- es are found only in the circum polar belt, where the model produces a much broader Circum Po- lar current than expected from the data. The same holds for the western boundary currents, while the strong deviations near the Indoneasian Through- flow and in the Carribic may be explained by de-

ficits in the geoid. The spatial RMS value of these difference fields are again comparable (10.58cm and 10.84cm respectively)

The strong similarity in the fit of the model to the data encourages to look at the effect of the difference in the data on the ocean state.

1993 1994 1995 1996 1997 1998 1999 2000 2001

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cm

GSFC BRIO2C

GfZ B2ntp

data model

global mean sea level

Fig. 4: Global mean sea level anomaly from the two assimilation expe- riments, BRIO2C and B2ntp, as compared to the corresponding data

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BRIO2C vs. T/P(NASA/GSFC)

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1993-2001

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temporal RMS difference

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2.806 area RMS:

B2ntp vs. T/P(GfZ)

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1993-2001

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temporal RMS difference

Fig. 5: Local temporal RMS of the modeled SSHA difference between model and corresponding data, for experiment BRIO2C (top) and B2ntp (bottom).

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1993-2001

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mean sea level difference

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B2ntp vs. SHOM98

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c.i. 10 cm

mean sea level difference

Fig. 6: Temporal mean sea level for the assimilation experiments BRIO2C (top) and B2ntp (bottom) compared to the SHOM98.2 mean sea surface height referenced to the GRACE geoid

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Comparing Model Sea Surface Height

For both experiments, BRIO2C and B2ntp respec- tively, the main contribution to global sea level rise is given by the linear trend of the (thermo-)steric com- ponent, which is slightly higher using the GfZ data (experiment B2ntp) than in the results obtained when utilizing the NASA/GSFC data. The main differences in the mean sea level is explained by the non-steric component, which reflects the annual to interannual variability (Fig.7a).

Only about 60% of the thermosteric sea level rise ori- ginates from the upper 512m of the ocean. Thus the thermal trend in the deeper layers contribute an essen- tial part (Fig.7b).

Figure 8a shows the local sea level trends resulting from the two models BRIO2C and B2ntp that should

be compared to the corresponding data shown in Fig.3.

Decomposing the sea level trends into its thermoste- ric, halosteric and non-steric components (Fig.8b-d) shows that even on local scale the main contribution to sea level change is given by the thermosteric part.

But the halosteric one cannot be neglegted! There are large regions where it is of the same size as the thermosteric.

Differences between the models appear mainly in the non-steric part of the trends. In contrast to the diffe- rences in the corresponding data trends Fig.3 right these differences are of opposite sign in the North and the South Pacific. In the thermosteric as well as in the halosteric part differences are found mainly in the At- lantic and in the circumpolar belt.

1993 1994 1995 1996 1997 1998 1999 2000 2001

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cm

BRIO2C BRIO2C

B2ntp B2ntp

steric non-steric

global mean sea level

Fig. 7a: Decomposition of the temporal evolution of global mean sea level into steric and non-steric part for the model solutions BRIO2C and B2ntp.

1993 1994 1995 1996 1997 1998 1999 2000 2001

-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 10²³ J

total top middle bottom

dashed: BRIO2C straight: B2ntp

global ocean heat content anomaly

Fig. 7b: Corresponding global ocean heat content anoma- ly for the depth ranges: total=[ζ-bottom], top=[ζ-512m], middle=[512m-2250m] and bottom=[2250m-bottom]

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1993-2001

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0.241 area mean:

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1993-2001

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Fig. 8a: Local sea level trend of the model solutions BRIO2C (upper row) and B2ntp (lower row). REMARK: The area mean values are given for the data covered area (see e.g. Fig.3)

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1993-2001

thermosteric component local linear trend

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0.239 area mean:

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1993-2001

thermosteric component local linear trend

Fig. 8b: same as Fig. 8a: but for the thermosteric component

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1993-2001

halosteric component local linear trend

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halosteric component local linear trend

Fig. 8c: same as Fig. 8a: but for the halosteric component

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1993-2001

non-steric component local linear trend

Fig. 8d: same as Fig. 8a: but for the non-steric component

Pacific Circulation

1993 1994 1995 1996 1997 1998 1999 2000 2001

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Sv

BRIO2C B2ntp surface - 500m

Pacific top layer inflow at 32S

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BRIO2C B2ntp

Pacific total transport at 32S

Fig. 9: Pacific mass transport across 32^oS for the depth ranges (topmost to undermost): [ζ-500m], [500m-1300m], [1300m- bottom] and [ζ-bottom]

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6 8

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0 meridional streamfunction Pacific

Fig. 10: Temporal mean Pacific meridional overturning circulati- on for experiment BRIO2C. The general structure appears to be the same in B2ntp (not shown) although the strength of the mean cells differ.

1993 1994 1995 1996 1997 1998 1999 2000 2001

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Sv

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North Pacific Overturning Cell

Fig. 11: Temporal variations in the strength of the North Pacific overturning cell for both experiments, BRIO2C and B2ntp.

The differences in the sea level variations influence the oceanic circulation as demonstrated here by the Pacific overturning. Although the total transport across 32^oS (Fig.9) appears to be nearly the same for both expe- riments, BRIO2C and B2ntp respectively, one finds differences of up to two Sverdrup especially in the deep inflow and in the mid-depth outflow which are re- ciprocally compensating.

This difference is not that pronounced in the general structure of the overturning (Fig.10) but in its strength.

As an example Fig.11 compares the strength of the northern cell centered at about 50^oN and 500m depth.

This overturning cell shows nearly the same temporal behaviour for BRIO2C and B2ntp on short timesca- les, but it also exhibits different trends especially after the 1997 El Ni˜no event.

Indo-Pacific Heat Transport

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BRIO2C Indo-Pacific heat transport

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Indo-Pacific heat transport

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temporal mean

Fig. 12: Meridional heat transport in the Indo-Pacific Ocean for experiments BRIO2C (top) and the difference between the two model results, B2ntp minus BRIO2C (below).

The meridional heat transport in the two model solutions, BRIO2C and B2ntp respec- tively, differ mainly in the equatorial belt between 5^oS and 15^oN. Only the transport in the Indo-Pacific is shown here, but this holds for all of the global ocean. The differences mainly appear in the amplitude of the annual cycle which is altered by about 0.5PW, while the temporal means, given in the right graphs of Fig.12, stay approximately the same.

Outside the equatorial band the differences stay well below 0.04PW as indicated by the additional dashed lines in the lower left plot.

Summary

• The sea level anomalies, as derived by different groups from the TO- PEX/Poseidon altimeter measurements exhibit strong differences related to the respective correction algorithms / data chosen.

• The ocean model can be fitted to the different datasets with equal quality

• The assimilated model solutions exhibit equal steric contributions to sea level change. The differences in the datasets are mainly reflected in the non-steric part.

• Nevertheless the differences in the sea level datasets project into the oceanic cir- culation. This can be seen especially in the mass transports, while for the heat transports essential differces are found only in the equatorial belt (5

^o

S - 15

^o

N) in the amplitude of the annual cycle.

Corresponding e-mail adresses:

mwenzel@awi-bremerhaven.de jschroeter@awi-bremerhaven.de