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Global Validation of GRACE Gravity Measurements by in-situ and modelled Ocean Bottom Pressure

PIES Deployment in Southern Ocean, RV Polarstern, 2006. Global Validation of GRACE Gravity Measurements by in-situ and modelled Ocean Bottom Pressure. C. Böning , A. Macrander, R. Timmermann, O. Boebel, J. Schröter AWI Bremerhaven. GSTM/SPP 1257 Potsdam, 15.10.2007.

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Global Validation of GRACE Gravity Measurements by in-situ and modelled Ocean Bottom Pressure

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  1. PIES Deployment in Southern Ocean, RV Polarstern, 2006 Global Validation of GRACE Gravity Measurements by in-situ and modelled Ocean Bottom Pressure C. Böning, A. Macrander, R. Timmermann, O. Boebel, J. Schröter AWI Bremerhaven GSTM/SPP 1257 Potsdam, 15.10.2007

  2. GRACE: monthly variability [RMS / dbar] 0.15 AWI NOAA 0.10 RAPID MOVE 0.05 POL/CNES/ IFREMER AWI POL 0 GFZ RL04 GSM+GAD [RMS] Ground-truth validation of GRACE with OBP • GRACE measures mass variability on Earth • large hydrological cycle over continents • much smaller signal over oceans (0.01 … 0.05 dbar) • Does GRACE capture real oceanic variability? • Here: Global comparison with in-situ and modelled data of Ocean Bottom Pressure (OBP) GRACE GFZ RL04 GSM+GAD RMS variability [dbar of water equivalent]. GRACE: do2-50, 750 km Gauss filter.  OBP ground truth sites

  3. OBP [dbar] at 45°S 7°E: unfiltered data, 7 days LP – 4677 dbar – 4676 dbar Ocean Bottom Pressure (OBP) p = ∫ g  dz Vertical integral of oceanic + atmospheric mass • In-situ observations by instruments deployed at the sea floor • Short term variability ≤ O(1 dbar) tides, planetary waves may cause aliasing in GRACE data, corrected by GAC/GAD model • Monthly variability (0.01 to 0.05 dbar) water mass changes, geostrophic ocean currents Ocean Bottom Pressure OBP timeseries in AWI ACC array (PIES ANT 7-1) .

  4. GRACE: monthly variability [RMS / dbar] 0.15 AWI NOAA 0.10 RAPID MOVE 0.05 POL/CNES/ IFREMER AWI POL 0 GFZ RL04 GSM+GAD [RMS] Validation of GRACE with OBP Data used in this study: I. GRACE • different data centres: CSR, GFZ, JPL, GRGS, ITG • different releases RL01 to RL04 • different products: GSM monthly geoid + GAC/D monthly average of de-aliasing model • spatial smoothing: degree/order 2 – 50, 750 km Gauss filter ornewly developed patch filtering GRACE GFZ RL04 GSM+GAD RMS variability [dbar of water equivalent]. GRACE: do2-50, 750 km Gauss filter.  OBP ground truth sites

  5. GRACE: monthly variability [RMS / dbar] 0.15 AWI NOAA 0.10 RAPID MOVE 0.05 POL/CNES/ IFREMER AWI POL 0 GFZ RL04 GSM+GAD [RMS] Validation of GRACE with OBP Data used in this study: II. in-situ OBP data Global OBP database at AWI contains: • dedicated GRACE-arrays: ACC (AWI), MOVE (IFM-GEOMAR/SIO) • oceanographic OBP-sections: Drake Passage (POL/CNES),Kerguelen (POL/IFREMER), Framstrait (AWI), RAPID (NOC) • tsunami warning system: DART (NOAA) … further contributions appreciated GRACE GFZ RL04 GSM+GAD RMS variability [dbar of water equivalent]. GRACE: do2-50, 750 km Gauss filter.  OBP ground truth sites

  6. Validation of GRACE with OBP • Data used in this study: • III. FESOM • Finite Element Sea Ice Ocean Model • hydrostatic primitive equation OGCM with sea ice coupling • 1.5° horizontal resolution • 26 z-levels • atmospheric forcing: usually NCEP/NCAR daily reanalysis 1958-2005 • no restoring • OBP variability of about ± 0.03 dbar • OBP anomalies strongly related to barotropic • velocity anomalies • High pressure anomalies → anticyclonic currents • Low pressure anomalies → cyclonic currents

  7. Framstrait at 79°N 300 km from Greenland Ice Shield • PIES data from AWI since 2003 • Monthly OBP variability O(0.05 dbar) • GRACE captures real oceanic variability: → correlation improvements by recent releases, e.g. GFZ: RL03 GSM+GAC r = 0.55 RL04 GSM+GAC r = 0.71 RL04 GSM+GAD r = 0.76 → best agreement of all GRACE products: GRGS (10day time axis; r = 0.80) → GAC, GAD de-aliasing models alone do not show observed variability, actual GRACE measurements (GSM) necessary GRACE vs. in-situ OBP: Framstrait 79°N Arctic Blue: In-situ data: Framstrait PIES F8 – 1-3 [A. Beszczynska-Möller, AWI] Other colours: GRACE do2-50, 750 km Gauss filter

  8. GRACE vs. in-situ OBP: MOVE, Tropical Atlantic Tropical Atlantic at 16°N • in-situ OBP variability small O(0.02 dbar) • GRACE strongly overestimates variability • unrealistic annual cycle in all GRACE products [GFZ, CSR, GRGS, ITG, JPL] → see also: Poster of U. Neumann et al. this afternoon Blue: In-situ data: MOVE PIES V404 1-5 [J. Karstensen, IFM-GEOMAR] Other colours: GRACE do2-50, 750 km Gauss filter

  9. Filtering GRACE data • Issues of Gaussian filtering methods due to • symmetrie of Gauss function: • adds land signal to oceanic data • ignores ocean circulation pattern • FESOM simulations indicate that OBP anomalies are • coherent over a certain area which corresponds to • bottom topography

  10. Spatial coherence of OBP • OBP anomalies of 2002-2005 from 50-yr FESOM simulation • 4-months high pass filter to subtract dominant seasonal cycle • Cross-correlation of time series at one point with time series at all other points • Cut-off at correlation <0.7 and radius 20º • filter data by weighting with correlation coefficients ANT 7 ANT 11

  11. OBP cross-validation FESOM/PIES/GRACE AWI ACC array: PIES ANT 7, ANT 11 (more to come) PIES: in-situ data 2002-2005 FESOM: simulations 2002-2005, patch filtered GRACE: GFZ RL04, d/o 2-50, patch filtered • increase in correlation of 0.1-0.2 • FESOM reproduces seasonal cycle

  12. Comparison of Gauss and coherence-patch filtered data Correlations GFZ RL04 (750 km Gauss)/in situ OBP AWI • Correlation of • GRACE and in situ • data indicates an • improvement due to • the new filtering • method • At many locations • correlation increases • by 0.1-0.2 • Improvement at • POL Array in Drake • Passage, but • correlation still • negative GFZ RL04 GSM+GAD NOAA RAPID MOVE AWI POL/CNES/ IFREMER POL Correlations GFZ RL04 (patch filtered)/in situ AWI GFZ RL04 GSM+GAD NOAA RAPID MOVE AWI POL/CNES/ IFREMER POL

  13. Recent GRACE releases capture real oceanic OBP variability with r = 0.8 … 0.9 at some locations (all at high latitudes) • Improvements by recent GAC, GAD de-aliasing models, but actual GRACE measurements (GSM fields) necessary to capture real variability • Improvements RL03→RL04 and GAC→GAD • Improvements by using the patch filtering method • OBP database at AWI now available upon request Contact: Carmen.Boening@awi.de, Andreas.Macrander@awi.de Conclusions

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