GFDLs Coupled and Earth System Model Developments Highresolution

GFDL’s Coupled and Earth System Model Developments • High-resolution Atmosphere and Oceans horizontal (capturing regional, other fine-scale details), vertical (capturing the stratosphere) • Climate Models graduating onto Earth Systems Model, including interactive Atmospheric Chemistry (capturing Climate – Air Quality nexus) and Biogeochemistry (capturing Carbon. Climate feedbacks) • Need for comprehensiveness and realism in representation of processes

Model development strategy within GFDL: 2 pipelines developed in tandem push atmospheric and oceanic climate models to higher resolution, while developing and utilizing lower resolution Earth System Models Precip in 25 km model Resolution pipeline Surface NOX in AM 3 (200 km) Earth system/ comprehensiveness pipeline Merge in future

Winter mean precipitation in Western U. S. in 50 km model 200 km res. 50 km res. Observations 1/2 deg. Annual mean precipitation in Europe 200 km 50 km

GFDL Model rainfall Current generation To resolve societally and physically relevant scales: High-res. atmosphere, ocean, coupled models being developed at GFDL Observed SST and Wind Developing generation Model data: S. J. Lin, I. Held, M. Zhao From Vecchi, Xie and Fischer (2004, J. Clim)

High resolution simulation of Southern Ocean (Hallberg and Gnanadesikan, JPO, 2006) Small vortices affect oceanic carbon uptake heat, transport of heat towards Antarctic continent, marine ecology of Southern Ocean

Development Pathway: Coupled Model for AR 5 2008 CM 3 = AM 3 + LM 3 + CM 2. 1 ICE/OCEAN ESM 2. 1 = CM 2. 1 + LM 3 V + OBGC 5 yr/day on 500 PEs 2400 CPUhr/yr CM 2 M = CM 2. 1 with MOM+ ESM 2 M CM 2 G = CM 2. 1 with GOLD ESM 2 G 10 yr/day on 120 PEs 300 CPUhr/yr 8 yr/day on 140 PEs 425 CPUhr/yr

Why two ocean models? z-coordinate better in weakly stratified regions -coordinate better on sloping bottom Role of ocean in transient climate change?

LM 2 -> LM 3 Land Model Dynamic vegetation Subgrid land-use heterogeneity Distinct treatment of ground, vegetation, & canopy air Soil water dynamics (liquid & frozen) Multilayer snow pack River network with capacity for tracers and temperature

Decadal Predictability Research • Ongoing studies with CM 2 model to develop improved understanding of a) mechanisms of decadal variability b) decadal scale predictability arising from internal variability • Development and use of higher resolution coupled models. Want this to be focus of variability and predictability research • New coupled assimilation system

North Atlantic Temperature Atlantic Meridional Overturning Circulation (AMOC) What will the next decade or two bring? Warm North Atlantic linked to … Drought More intense hurricanes More rain over Sahel and western India Two important aspects: a. Decadal-multidecadal fluctuations b. Long-term trend

Simulated North Atlantic AMOC Index All forcings Aerosol only forcing Greenhouse gas only forcing

Projected Atlantic SST Change (relative to 1991 -2004 mean) Can we predict which trajectory the real climate system will follow? Results from GFDL CM 2. 1 Global Climate Model

Decadal Predictability • Decadal prediction/projection is a mixture of boundary forced and initial value problem • Changing radiative forcing (esp. aerosols) will be a key ingredient • Some basis for decadal predictability of internal variability, probably originating in ocean • Some of predictability will arise from unrealized climate change already in the system • Substantial challenge for models, observations, assimilation systems, and theoretical understanding

Earth System Modeling • What proportion of Fossil Fuel CO 2 emissions will stay in the atmosphere, and for how long? • What are the ecological impacts of increased CO 2 and ocean acidification? • What are the ecological impacts of climate change? • What is the role of land use on carbon cycling? • How effective can proposed CO 2 sequestration approaches be (e. g. iron fertilization, deep ocean CO 2 injection, forest preservation)?

GFDL’s earth system model (ESM) for coupled carbon-climate Atmospheric circulation and radiation Climate Model Earth System Model Sea Ice Ocean circulation Land Ice Land physics and hydrology Atmospheric circulation and radiation Chemistry – CO 2, NOx, SO 4, aerosols, etc Sea Ice Ocean ecology and Biogeochemistry Ocean circulation Land Ice Plant ecology and land use Land physics and hydrology

IPCC AR 4 WG 1 Chapter 10

Ocean processes represented in GFDL’s current ESM • Coupled C, N, P, Fe, Si, Alkalinity, O 2 and clay cycles • Phytoplankton functional groups – Small (cyanobacteria) / Large (diatoms/eukaryotes) – Calcifiers and N 2 fixers • Herbivory - microbial loop / mesozooplankton (filter feeders) • Variable Chl: C: N: P: Si: Fe stoichiometry • Carbon chemistry/ocean acidification • Atmospheric gas exchange deposition and river fluxes • Water column denitrification • Sediment N, Fe, Ca. CO 3, clay interactions

Current land processes represented in GFDL’s current ESM in collaboration with PU, UNH and USGS (Schevliakova et al. , subm GBC; Malyshev et al. , in prep) • Plant growth – Photosynthesis and respiration – f(CO 2, H 2 O, light, temperature) – Carbon allocation to leaves, soft/hard wood, coarse/fine roots, storage • Plant functional diversity – Tropical evergreen/coniferous/deciduous trees, warm/cold grasses • Dynamic vegetation distribution – Competition between plant functional types – Natural fire disturbance – f(drought, biomass) • Land use – Cropland, pastures, natural and secondary lands – Conversion of natural and secondary lands and abandonment – Agricultural and wood harvesting and resultant fluxes

Work in progress: repeating these runs with a comprehensive ecosystem model Nutrients Phytoplankton Deposition (N, Fe) Runoff Remineralization/ (Ca. CO 3, N) dissolution NO 3 NH 4 Small plankton Si Dissolved components Oxygen DOP, DON Burial (Ca. CO 3, Fe) Ca. CO 3 Zooplankton (parameterized) PO 4 Large Plankton Sinking particles Fe Remineralization/ dissolution Denitrification N fixation Dunne et al. , in prep. Diazotrophs DOP, DON Oxygen (POM, Ca. CO 3, Opal, Fe)

PO 4 NO 3 Log(Chl) Observations Model

Moving towards the future of Earth System Modeling (ESM 3 and beyond) • Coupling with atmospheric chemistry • Coupling with river biogeochemistry • Integrated elemental cycles beyond carbon – N, P, Fe, CH 4 • Seasonal fire dynamics • Coastal and estuarine interactions • Ecological prediction of hypoxia, harmful algal blooms and fisheries capacity variability

Future Model Applications: Ecological Prediction Example Land-use and ecology Nitrogen runoff Harmful algal blooms Atmospheric chemistry River Routing Hypoxia events

Doubles every ≥ 2 years 10 x every ≥ 7 years

FY 2007 Project Summary Project % of R&D HPCS (Princeton) CPU-hours per year Climate Scenario Analysis 10 3, 800, 000 Climate Scenario Generation 20 7, 600, 000 Software Infrastructure Development 5 1, 900, 000 Next Generation Ocean Model R&D 15 5, 700, 000 Long-term Climate Model R&D 40 15, 300, 000 Seasonal Climate Modeling R&D 10 3, 800, 000 100 38, 100, 000 TOTAL

DEC-CEN Computing Gaps • Computing gaps are associated primarily with requirements for – Increased resolution • To meet demands for information on water resources, extreme events, and ecosystems at regional scales. • CM 2. 4, the target model for GFDL’s Decadal Prediction research, is 25 x more expensive to run than CM 2. 1, one of its AR 4 -class models – Additional comprehensiveness • Fully interactive cycles of many chemical species in the atmosphere, land, rivers, and ocean • Direct and indirect aerosol effects • Ice sheets (eventually) • ESM 2. 1 is ≤ 2 x more expensive to run than CM 2. 1 • CM 3 is 5 x more expensive to run than ESM 2. 1 – Ensemble members • Using different initial conditions • Increasing number of assessments – Technology will provide about 6 -8 x between AR 4 and AR 5 • State-of-the-art computing is crucial for recruiting and retaining topnotch scientific talent

The Challenges Critical Resources § Increasing the realism, capturing the complexities and addressing the key uncertainties § Coupling of the components Climate, Earth System Models § Performing high-resolution simulations § Increased ensemble member integrations § Meeting timelines (e. g. , for major assessments) § Computational (“Computer-ware”) § Scientific talent (“Brainware”) Global Climate Model

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