1. 23/09/2005 Thanh NGO-DUC Page 1 Modélisation des bilans hydrologiques continentaux: variabilité interannuelle et tendances. Comparaison aux observations Modeling the continental hydrologic cycle: interannual variability and trends. Comparison with observations Thanh NGO-DUC Ph.D. Defense

2. 23/09/2005 Thanh NGO-DUC Page 2 Introduction Our climate is changing, which direct consequences for the Earth. Variations in greenhouse gases, aerosols, and land use/cover force changes in climate… …but, most of consequences of climate change are realized through the water cycle : flood, drought, sea level rise, etc. Brésil, 1997 ©IRD/ photo Bernard Osès Bolivie, 1983 ©IRD photo Denis Wirrmann

3. 23/09/2005 Thanh NGO-DUC Page 3 Introduction This thesis aims to study the variability of continental hydrologic cycle by using numerical models and observations. Solar heat Precip. 387 water vapor Evaporation 427 Ocean Net mouvement of water by wind 40 Evaporation 71 water vapor surface water and ground water flow of water 40 Water cycle ×10 12 m 3 /yr Water exchanged volume estimated by Baumgartner et Reichel (1975) Precip. 111 ? GRACE model http://www.wilkes.edu

4. 23/09/2005 Thanh NGO-DUC Page 4 Introduction The ORCHIDEE land surface model (LSM) SECHIBA : surface energy and water balances STOMATE : surface biochemical processes LPJ: dynamical evolution of the vegetation and the carbon budget ORCHIDEE is the new land-surface scheme of the IPSL. It is composed of: ORCHIDEE: Organising Carbon and Hydrology in Dynamic EcosystEms SECHIBA: Schématisation des Echanges Hydriques à l’Interface entre la Biosphère et l’Atmosphère STOMATE: Saclay Toulouse Orsay Model for the Analysis of Terrestrial Ecosystems LPJ: Lund –Postdam-Jena Only SECHIBA is used. Inclusion of a routing scheme, which routes the water to the oceans through a cascade of linear reservoirs. 2 m river discharge

5. 23/09/2005 Thanh NGO-DUC Page 5 Plan Seasonal variations using GRACE, basin scale Thesis Seasonal/interannual variations using Topex/Posédion, continental scale off-line simulation 1987-1988 coupled simulation 1997-1998 Ngo-Duc et al. (JGR, 2005a) Applications land water & sea level Ngo-Duc et al. (GRL, 2005c ) Construction & validation Ngo-Duc et al. (JGR, 2005b) Decadal/interdecadal timescales, the NCC forcing data set, basin/continental scale (NCC:NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) Corrected by CRU (Climate Research Unit)

6. 23/09/2005 Thanh NGO-DUC Page 6 http://www.aviso.oceanobs.com  Radar altimeters transmit signals to Earth, and receive the echo from the sea surface.  Measuring the time span between sending and receiving of the pulses allows to determine the height of the satellite above sea-level.  The distance from the satellite to the mean earth ellipsoid is known. the height of the sea-level above the ellipsoid Principe of altimetry Launched: 10/08/1992 Orbit: quasi-circular, 66°, 1336 km of altitude Topex/Poséidon (T/P) I. Topex/Poséidon & ORCHIDEE

7. 23/09/2005 Thanh NGO-DUC Page 7 I. Topex/Poséidon & ORCHIDEE Causes of sea level variations: thermal expansion of the oceans (steric effect) water mass exchanged with other reservoirs NCEP/NCAR vapor T/P-steric-vapor Ishii stericT/P mean seasonal variations 1993-1998, expressed in sea level equivalent 8.0 4.0 0.0 - 4.0 - 8.0 mm NCEP/NCAR vapor T/P-steric-vapor Ishii stericT/P mean seasonal variations 1993-1998, expressed in sea level equivalent 8.0 4.0 0.0 - 4.0 - 8.0 mm

8. 23/09/2005 Thanh NGO-DUC Page 8 I. Topex/Poséidon & ORCHIDEE a) forced simulation for 1987 & 1988 ISLSCP-I (International Satellite Land-Surface Climatology Project, Initiative I) produced the atmospheric forcing over the continents for 1987 and 1988. The differences could be due to :  incompatibility of the compared periods  data/model uncertainties In the simulation, there are interannual variations between 1987 and 1988 next study: use GCM simulations, for 1997 and 1998 The model outputs are comparable to the observations (phase, amplitude) T/P derived value (T/P-steric-vapor) ORCHIDEE forced by ISLSCP-I continental water variations expressed in sea level equivalent (mm) 12.0 8.0 mean seasonal cycle for the period 1993-1998 4.0 0.0 - 4.0 - 8.0 - 12.0 1987 1988

9. 23/09/2005 Thanh NGO-DUC Page 9 I. Topex/Poséidon & ORCHIDEE b) coupled simulation for 1997 & 1998 AMIP Simulation LMD GCM, version 3.3 ; 96×72×19 ● Forced by SST form 1979 to 1999 Ngo-duc, T., K. Laval, J. Polcher and A. Cazenave (JGR, 2005a) AMIP: Atmospheric Model Intercomparison Project Contribution of continental water to sea level variations AMIP T/P derived value AMIP 19971998 mm

10. 23/09/2005 Thanh NGO-DUC Page 10 I. Topex/Poséidon & ORCHIDEE b) coupled simulation for 1997 & 1998 Our results don’t agree with the analysis of Chen et al. (2002) who attributed the contrast between 1997 and 1998 to a change in snow cover at high latitudes. A major part of the interannual variability of the continental water storage comes from the strong variability of precipitation on the tropical continents. Seasonal variations of tropical continental water expressed in terms of equivalent sea level - 4.0 - 2.0 0.0 2.0 4.0 mm

11. 23/09/2005 Thanh NGO-DUC Page 11 I. Topex/Poséidon & ORCHIDEE c) Limitations and perspectives  forced simulation: the period of the ISLSCP-I forcing data is incomparable with the Topex/Poséidon  coupled simulation: uncertainty of the precipitation fields, in particular when looking at geographical details. Limitations of this part next study: forced simulation over a long period

12. 23/09/2005 Thanh NGO-DUC Page 12 Plan Thesis Seasonal/interannual variations using Topex/Posédion, continental scale Seasonal variations using GRACE, basin scale off-line simulation 1987-1988 coupled simulation 1997-1998 Ngo-Duc et al. (JGR, 2005a) Applications land water & sea level Ngo-Duc et al. (GRL, 2005c ) Construction & validation Ngo-Duc et al. (JGR, 2005b) Decadal/interdecadal timescales, the NCC forcing data set, basin/continental scale

13. 23/09/2005 Thanh NGO-DUC Page 13 II. The NCC atmospheric forcing data a. Construction NCEP/NCAR Reanalysis NPRE CRU (Climate Research Unit) precipitation 0.5°×0.5°, 1901-2000 NCRU CRU temperature Specific humidity, pressure, precipitation NCEP Interpolation to the grid 1°×1°, differences in elevation between the grids were taken into account 6-hourly, ~1.875°, 1948-present (NCEP Corrected by CRU) NCC 6-hourly, 1°x1°, 1948-2000 Radiation : SRB (Surface Radiation Budget) http://dods.lmd.jussieu.fr/cgi-bin/nph-dods/Dods/NCC/ (~40GB) Ngo-duc, T., J. Polcher and K. Laval (JGR, 2005)

14. 23/09/2005 Thanh NGO-DUC Page 14 II. The NCC atmospheric forcing data b. Validation The world's 10 biggest rivers (by the estimated river mouth flow rate) Observed discharge  GRDC (Global Runoff Data Center)  Data at UCAR (the University Corporation for Atmospheric Research) Station Obidos 55.51°W, 1.95°S

15. 23/09/2005 Thanh NGO-DUC Page 15 OBS NCEP NCC NCEP OBS II. The NCC atmospheric forcing data b. Validation  quality of the NCC forcing data is improved compared to NCEP/NCAR  high flow in simulated mean seasonal signal is too early  the interannual signal is well described by the NCC experiment

16. 23/09/2005 Thanh NGO-DUC Page 16 II. The NCC atmospheric forcing data b. Validation Taylor diagram (Taylor, 2001) The quality of forcing data is improved after each adjustment. NCEP NPRE NCRU NCC 1. Amazon 2. Congo 3. Orinoco 4. Changjiang 5. Brahmaputra 6. Mississippi 7. Yenisey 8. Parana 9. Lena 10. Mekong Standard deviation OBS Precipitation: most important improvement Temperature: significant effect only at high latitudes Radiation: improves discharge amplitudes Precipitation: most important improvement Temperature: significant effect only at high latitudes Radiation: improves discharge amplitudes

17. 23/09/2005 Thanh NGO-DUC Page 17 II. The NCC atmospheric forcing data b. Validation Comparison between NCC and GSWP2 (Global Soil Wetness Project) Standard deviation OBS GSWP2 NCC 1. Amazon 2. Congo 3. Orinoco 4. Changjiang 5. Mississippi 6. Yenisey 7. Parana series mean seasonal signal anomaly Discharge is better simulated using NCC than GSWP2.

18. 23/09/2005 Thanh NGO-DUC Page 18 Over the past 50 yrs, the rate of global mean sea level rise was on the order of 1.8 mm/yr [Church et al., 2004], where: Thermal expansion contributes ~ 0.4 mm/yr [Lombard et al., 2005] Mountain glaciers melting accounts for ~ 0.4 mm/yr [Meier and Duygerov, 2002] Greenland & Antarctica melting provide ~ 0.5 mm/yr [Thomas et al., 2004] Effects of land water storage on global mean sea level over the past 50-yrs Ngo-Duc, T., K. Laval, J. Polcher, A. Lombard et A. Cazenave (GRL, 2005) What is the land water contribution? II.c. Applications of NCC Effects of land water storage on global mean sea level

19. 23/09/2005 Thanh NGO-DUC Page 19 5-yr moving average of water reservoirs changes expressed as equivalent global sea level anomalies. II.c. Applications of NCC Effects of land water storage on global mean sea level greatest variation is associated with ground water, followed by soil moisture no significant trend was detected strong decadal variability driven by precipitation, strong decrease in the beginning of 1970s agreement between ORCHIDEE and LaD. (Land Dynamics LSM of GFDL)

20. 23/09/2005 Thanh NGO-DUC Page 20 5-yr moving average time series of changes in land water storage for the six study regions during the past 50 yrs, the northern tropical Africa lost water to the benefit of the oceans the strong decrease of the global signal in the early 1970s is due to changes in the Amazon basin regions 2 and 3 seem to be anti- correlated (-0.78), suggesting a possible teleconnection mechanism II.c. Applications of NCC Effects of land water storage on global mean sea level

21. 23/09/2005 Thanh NGO-DUC Page 21 II.c. Applications of NCC Effects of land water storage on global mean sea level Relations between land water and thermosteric sea level fluctuations R=-0.84 oceans warmer continents wetter negative feedback to sea level These results do not confirm the suggestions of Gregory et al. [2004] that decadal fluctuations in ocean heat content are artifacts of the interpolation processes of raw hydrological data. + T océan + M continents - M océan - sea level rise + V océan + + E ocean, (P,E,R) land

22. 23/09/2005 Thanh NGO-DUC Page 22 Plan Thesis Seasonal/interannual variations using Topex/Posédion, continental scale Seasonal variations using GRACE, basin scale off-line simulation 1987-1988 coupled simulation 1997-1998 Ngo-Duc et al. (JGR, 2005a) Applications land water & sea level Ngo-Duc et al. (GRL, 2005c ) Construction & validation Ngo-Duc et al. (JGR, 2005b) Decadal/interdecadal timescales, the NCC forcing data set, basin/continental scale

23. 23/09/2005 Thanh NGO-DUC Page 23 III. GRACE & ORCHIDEE GRACE Mission (Gravity Recovery And Climate Experiment GRACE Mission (Gravity Recovery And Climate Experiment ) GRACE, twin satellites launched in March 2002, are making detailed measurements of Earth's gravity field. They study the movement of water over the surface of the Earth with a level of detail never before possible. © NASA

24. 23/09/2005 Thanh NGO-DUC Page 24 III. GRACE & ORCHIDEE Seasonal variations of continental water April/May - November 2002 GRACELaD model Figure provided by Ramillien, G., LEGOS How do ORCHIDEE results compare?

25. 23/09/2005 Thanh NGO-DUC Page 25 III. GRACE & ORCHIDEE Numerical experiments - Built a new atmospheric forcing from 2001 to 2003, named NCMAP (NCEP/NCAR-NCC-CMAP): constrained by monthly CMAP precipitation. - experiment ORCHIDEE-1: ORCHIDEE without routing scheme, forced by NCMAP - experiment ORCHIDEE-2: ORCHIDEE with routing scheme, forced by NCMAP CMAP: CPC (Climate Prediction Center) Merged Analysis of Precipitation

26. 23/09/2005 Thanh NGO-DUC Page 26 GRACEORCHIDEE with routing ORCHIDEE without routing Seasonal variations of continental water April/May – November 2002 III. GRACE & ORCHIDEE The routing scheme much improves the signals over tropical basins

27. 23/09/2005 Thanh NGO-DUC Page 27 GRACE ORCHIDEE with routing ORCHIDEE without routing III. GRACE & ORCHIDEE The routing scheme much improves the signals over tropical basins Variations of water stock over the 8 tropical basins

28. 23/09/2005 Thanh NGO-DUC Page 28 Conclusions ORCHIDEE is able to reproduce seasonal and interannual variations of continental water reservoirs The important role of the tropical regions in the variability of the climate was underlined The NCC data set was found to be reliable in the validations On studying the variability of land water storage, an hypothesis was proposed: when the oceans are warmer, the continents will be wetter, leading to a negative feedback on sea level changes The role of the routing scheme on simulating land water storage was shown

29. 23/09/2005 Thanh NGO-DUC Page 29 Future directions study the anti-correlation between South A M erica and north tropical Africa look at smaller scale: soil moistu R e (T. D’Orgeval) examine land water storage at interannual/d E cadal timescale using GRACE and other LSMs, forcing data sets Observations: Global soil moisture data bank [Robock et al., 2000] Soil moisture index comparison study the relations with climate C hange study anthropogenic impact : irr I gation, floodplains, dams, …