Presentation on theme: "Understanding Potential Factors Influencing the ITF in the 21 st Century Tony Lee NASA Jet Propulsion Laboratory California Institute of Technology."— Presentation transcript:
Understanding Potential Factors Influencing the ITF in the 21 st Century Tony Lee NASA Jet Propulsion Laboratory California Institute of Technology
ITF: a great challenge to both observations and models Figure after Sprintall et al. (2014, Nature Geoscience)
The challenges In-situ systems: Difficulty to measure the inflow & outflow simultaneously Difficulty to measure the flow in the upper few tens of meters Satellite systems: Altimetry: need very good regional tidal corrections Salinity: contamination by land signals Models: Representation of the geometry/topography is a major issue, esp. for coarse- resolution climate models. Generally lack of tidal mixing. Questionable representation of the effect of the regional water cycle.
Changes of the ITF are more than just about total volume transport Transports of heat and freshwater are more relevant to climate. Vertical structure of velocity, temperature, and salinity are thus important.
What factors control the changes of the ITF Remote forcing from the Pacific and Indian Oceans. Local forcing in the Indonesian Seas/Maritime Continent (e.g., tidal mixing, freshwater input, local wind).
South Pacific wind and Godfrey’s “Island Rule” To the 1 st order, low-frequency change of ITF volume transport can be inferred from the Island Rule (Godfrey 1988, 1996) by integrating wind stress around the South Pacific and Australia (to be covered in the lecture by Prof. Mark Cane). Essentially because most of the northward Sverdrup transport through the South Pacific above the maximum sill depth of the Indonesian Sea has to go through the Indonesian Archipelago. The Island Rule has many limitations!
ITF variability is affected by equatorial Pacific & Indian Ocean winds via equatorial & coastal waves (e.g., Clarke and Liu 1994, Wijffels & Meyers 2004)
Illustration how equatorial Pacific zonal wind affects the ITF Lee et al. (2001) Lower SSH Higher SSH
Local forcing in the Maritime Continent region: freshwater effect, connection to regional water cycle, monsoon, and ENSO
0-20 m averaged T S ρ Northwest monsoon Southeast monsoon Freshwater from Java Sea restricts upper-layer ITF in Makassar St during NW monsoon. Caused subsurface maximum of ITF; lower volume transport weighted T. Cool Indonesian throughflow as a consequence of restricted surface layer flow Gordon et al. (2003)
South China Sea (SCS) waters continue down to Java Sea to restrict the upper ITF Qu et al. (2005), Tozuka et al. (2007), reaffirmed results of Gordon et al. (2003)
El Niño La Niña Strong Luzon throughflow Weak Luzon throughflow 40 m ~100m Mindanao surface layer leakage to ITF blocked upper ~100 m Mindanao surface layer leakage blocked only in upper ~40 m Mindanao Current Blocked: upper ~100m Blocked: upper ~40 m La Niña effect: Warmer ITF reaches into the Indian Ocean, potentially affecting regional sea surface temperature and climate??? Export of SCS buoyant surface layer into ITF Karimata transport response to local winds, slightly stronger in la nina Bouyancy recharge Effects of interannual variability of SCS water on the ITF: ENSO connection El Nino: more restrictive to the upper ITF La Nina: less restrictive to the upper ITF Gordon et al. (2012)
Local forcing in the Indonesian Seas: tidal mixing
Water mass transformation within the Indonesian Sea (e.g., inflow salinity maximum eroded) After Sprintall et al. (2014) T-S diagram Depth color codes
Tidal mixing in the Indonesia Seas responsible for water mass transformation Koch-Larrouy et al. (2010) No tidal mixing Twice the strength of tidal mixing as Koch-Larrouy et al. (2007) With 3D tidal mixing of Koch-Larrouy et al. (2007). Averaged Κ=1.5 cm 2 /s
Tidal mixing results in cooler and fresher ITF outflow at the thermocline Difference of T (a) and S (b) in the thermocline layer (depth≈100-200m) with and without tidal mixing Koch-Larrouy et al. (2010)
Tidal mixing also affects the coupled ocean-atmosphere system Graphics from Sprintall et al. (2010), based on results of Koch-Larrouy et al. (2010) Reduce SST by 2 o C inside Indonesia Seas Reduce precipitation by 20% Observation Control Run (no tidal mixing) With tidal mixing
What does it take to have reliable projections of the the ITF in the 21 st century by climate models? Reliable projection of Pacific and Indian Ocean wind Local monsoon wind Regional water cycle Realistic representation of Inflow characteristics (vertical structure of u, v, T, S) Regional ocean circulation Tidal mixing Geometry/topography
What are model projections of ITF changes in the 21 st century? Not documented. What are model projections of ITF-related forcing? The most systematic report is a consistent weakening of tropical atmospheric circulation in IPCC models (Vecchi and Soden 2007).
Projected weakening of the Walker Circulation in the 21 st century Vecchi and Soden (2007) The resultant changes of tropical wind (blue arrows below) are associated with El Niño-like condition in the Pacific and positive IOD-like condition in the Indian Ocean. Anomalous wind associated with a weaker Walker Circulation
The projected changes of the tropical Pacific (Indian) Ocean winds are expected to reduce (strengthen) the ITF Does the effect of the Pacific wind overcome that of the Indian Ocean wind? Need to be investigated. Wind change
Weakening of the Walker Circulation has been observed in the 20 th century and reproduced by IPCC models for the Pacific sector Vecchi et al. (2006, Nature) But wind changes in the Indian Ocean sector is not reproduced by models. Therefore, projected changes of Indian Ocean wind in the 21 st century are questionable.
Large bias of IO wind (too weak) would affect ITF simulation QuikSCAT obs CMIP3 QuikSCAT obs CMIP5 Large biases of equatorial zonal wind in CMIP models (CMIP3 & CMIP5, 1970-2005 climatology) Lee et al. (2013) Weller & Cai (2013) found that CMIP models greatly exaggerated IOD variability because of the weak IO wind caused too shallow a thermocline in the east IO, thus overly active thermocline feedback; cautioned against the projection of IOD-related changes by CMIP models.
Large biases of CMIP climatological zonal wind (thus wind stress curl) in the S. Pacific would also affect the simulated ITF (by Island Rule) Lee et al. (2013)
Other caveats of climate models that would affect ITF Uncertainty fidelity in representing regional ocean & atmospheric circulation and water cycle. Lack of representation of the effects of tidal mixing. Inadequate representation of geometry and topography. CMIP3/5 ocean models typically have 1 o resolution. Even ocean models with resolutions up to 1/4 o do not represent the ITF well.
ECCO2 INSTANT ECCO2 has a dominant semi-annual signal (like INSTANT). Other products have dominant annual cycle Importance of resolution in properly representing the ITF Comparison of seasonal (a) & non-seasonal (b) ITF transport anomalies between INSTANT observations and ocean state estimation products Color curves: 1/4°- 2° resolution products. Black curve: 18-km ECCO2. The better agreement between ECCO2 & INSTANT obs is attributed to the higher resolution and C-grid of ECCO2 that allow a better representation of flows through narrow channels (esp. deep signals from the IO, e.g., semi-annual signals) Lee et al (2010)
Why do coarser models do not resolve semi-annual signals well? Comparison of volume transports from ECCO-JPL (1 o x1/3 o ) & ECCO2 (18km) Top 100 m transports are similar, dominated by annual cycle due to Pacific wind Below 100 m, ECCO2 captures semi-annual signal due to Indian Ocean wind but ECCO-JPL does not Lee et al (2010)
Coarser models do not capture semi-annual signals from the IO due to poor representation of topography, esp. at depth (has implication to Indian Ocean Dipole signal as well) Lee et al (2010)
Grid scheme matters for coarse-resolution models too If the width of a strait is represented by only 1 grid, no flow through that grid! (MOM- or POP-type models) Lee et al (2010)
Grid scheme matters for coarse resolution models (e.g., CMIP) If the width of a strait is represented by only 1 grid, there is flow through that grid. But that flow can only represent the effect of along-strait pressure gradient, but cannot represent geostrophic flow that involves cross-strait pressure gradient (because it needs density grids to represent cross-strait pressure gradient. (MITgcm-type models)Lee et al (2010)
Summary Many factors influences the changes of the ITF Remote forcing from the Pacific & Indian Ocean Local forcing in the Maritime Continent/Indonesian Seas (monsoon wind, regional hydrological cycle and related freshwater effect, tidal mixing). Reliability of the projection of ITF changes in the 21 st century by climate models depends on the fidelity of the models in representing these processes (including proper representation of the complex topography). Climate models projected a weakening Walker Circulation in the Pacific sector in the 21 st century, corresponding to a weaker Pacific trade wind that may reduce the ITF volume transport. However, the projections of other factors (e.g., South Pacific wind, Indian Ocean wind, regional forcing) and other aspects of the ITF (e.g., heat and freshwater transports) are highly uncertainty.