Title: Saroja Polavarapu
1Greenhouse gas simulation with GEM The story of
mass conservation
- Saroja Polavarapu
- Climate Research Division, Environment Canada
CRD Michael Neish, Douglas Chan, Shuzhan
Ren MRD Monique Tanguay, Claude Girard, Michel
Roch AQRD Jean de Grandpré, Sylvie Gravel
RPN seminar, 6 Feb. 2015
2OUTLINE
- What are we trying to do and why?
- The mass conservation story of GEM for CO2
- Ensemble Kalman Filtering
31. The FLUX ESTIMATION PROBLEM
4The Global Carbon Cycle
http//www.scidacreview.org/0703/html/biopilot.htm
l
1 Pg 1 Gt 1015 g
Net surface to atmosphere flux for biosphere or
ocean is a small difference between two very
large numbers
Earths crust 100,000
- The natural carbon cycle involves CO2 exchange
between the terrestrial biosphere, oceans/lakes
and the atmosphere. - Fossil fuel combustion and anthropogenic land use
are additional sources of CO2 to the atmosphere.
5Net perturbations to global carbon budget
LeQuere et al. (2013, ESSDD)
- Based on 2002-2012
- 50 of emissions remain in atmosphere
- 25 is taken up by terrestrial biosphere
- 25 is taken up by oceans
6Interannual variability
http//www.carboscope.eu/?qco2_budget
25 uptake by land
50 to atmosphere
25 uptake by ocean
- The uncertainty and interannual variability in
the global CO2 uptake is mainly attributed to the
terrestrial biosphere - Thus, we must first learn more about biospheric
sources/sinks
7But what is the spatial distribution of the
fluxes and how is it changing?
Mean XCO2 Aug. 2009 GOSAT Greenhouse Gas
Observing Satellite
v2.0 averaged at 0.9x0.9
Figure courtesy of Ray Nassar, CCMR
Figure courtesy of Elton Chan, CCMR
With the increased coverage from new satellite
data, can we get flux estimates at higher spatial
resolution?
OCO-2 launch July 2014
http//oco.jpl.nasa.gov/
8Atmospheric observations give feedback on model
forecasts
- If forecast does not match observation,
difference could be due to errors in CO2 initial
conditions, meteorological analyses, prescribed
fluxes, model formulation, representativeness, or
observation errors.
CO2 forecast
Fluxes
Forecast model
Model error
Meteorology analysis
CO2 analysis
9The inverse problem for Carbon Flux estimation
- In flux inversions, if one solves for fluxes
only, the transport model is needed to relate the
flux to the observation model is a strong
constraint - Exact mass conservation in transport model over
years of simulation is needed to attribute
model-data mismatch to fluxes. - Techniques used to solve inverse problem 4D-Var,
EnsKF, Bayesian Inversion, Markov Chain Monte
Carlo (MCMC) - Perfect model assumption since forecast model is
used as a strong constraint - No allowance for imperfect meteorological
analyses - Extension for imperfect tracer initial conditions
is not hard
flux
conc obs
Prior flux
Forecast model
Spatial interpolation
10Conventional inverse problem setup
11Inversions using surface network
Peylin et al. (2013)
- Inversion methods differ in
- Methodology
- Observations
- Sfc 100 flask continuous
- A priori fluxes
- Transport models
- Interannual variability is similar and due to
land
1 5-6 2 7-8 3 9 4 10 11
12The changing observing system
Mean XCO2 Aug. 2009 GOSAT Greenhouse Gas
Observing Satellite
v2.0 averaged at 0.9x0.9
GOSAT figure courtesy of Ray Nassar, EC
- 100 highly accurate surface stations with weekly
or hourly data - Regular aircraft obs over Pacific
- Satellites GOSAT (2009), OCO-2 (2014)
13Environment Canada Carbon Assimilation System
(EC-CAS)
- An advanced, state-of-the-art assimilation system
which will use ensemble forecasts to directly
simulate various sources of model error.
Comparable to systems in development for Japan,
US, etc. - Will be run routinely but behind real time since
it takes time for flux to reach measurement
locations - Forward model global operational air quality
model 0.9 x 0.9 - Statistical method Ensemble Kalman Smoother
(ext. of oper.) - Observations GAW global surface-based in-situ
and remote sensing stations, satellite, aircraft,
Total Carbon Column Observing Network (TCCON) - Emissions biosphere (Canadian Terrestrial
Ecosystem Model from CCCma), ocean, fossil fuel,
biomass burning
13
14EC-CAS Carbon Assimilation System
Flask, continuous, aircraft, satellite
Perturb initial conc., met fields, fluxes
Perturb obs
15The future vision Comprehensive Carbon Data
Assimilation System
GEO Carbon Strategy Report (2010)
- Comprehensive carbon assimilation systems are
being built by NASA, NOAA, agency-consortiums in
Europe, Japan and EC.
16EC-CAS team
- Saroja Polavarapu (lead) data assimilation
- Mike Neish system development
- Ray Nassar satellite observations, modeling
anthropogenic and other emissions - Douglas Chan carbon cycle science and modeling
- Bakr Badawy biospheric modeling
- University collaborators
- Prof. Dylan Jones (U Toronto), Feng Deng
- Prof. John Lin (U Waterloo), Myung Kim (U
Waterloo)
172. MASS CONSERVATION WITH Gem
18Operational model forecasts
- 10-day forecasts from the current operational
model (experiment K4H1RA2B Strato2B final cycle)
also show a steady drop in global mean surface
pressure - About 0.1 hPa is lost in 10 days
19Why do we need mass conservation?
- When we assimilate greenhouse gas observations,
mass conservation will not be possible. So no
need for this if we want to estimate the CO2 or
CH4 state only. - However, we need mass conservation for
- Accurate forward simulations of CO2/CH4. With a
good initial state and good source/sink inputs,
can match observations. - Estimation of sources/sinks of CO2/CH4 with
inverse methods. Such methods will serve as a
benchmark for the non-traditional EnKF state/flux
estimation scheme.
20Greenhouse gas simulation with GEM-MACH
- Need good simulation of GHG with exact mass
conservation - Priorities (1) CO2 global (2) CH4 global (3)
CO2, CH4 regional - CH4 chemistry (D.Chan, CCMR)
- stratosphere LINOZ (de Grandpré, McLinden,
AQRD), - troposphere
- OH climatology from CMAM (D. Plummer, CCCma)
- Start with global CO2 simulation
21Model validation experiment setup
- How well can GEM-MACH simulate Carbon?
- Simulation for January 1 December 31, 2009
- Initial condition from CarbonTracker for Jan. 1,
2009 - Meteorology surface fields (archived surface
analyses), 3D winds, archived analyses from
4D-Var - Set up series of 24h forecasts, no CO2
assimilation - Emissions
- Every 3 hours (area type) though GEM-MACH set up
for monthly fields with diurnal variation - biosphere (CarbonTracker a posteriori)
- ocean (CarbonTracker a posteriori)
- Fossil Fuel (CarbonTracker but based on CDIAC)
- Biomass burning (GFED v3)
- Idea With CarbonTracker emissions and initial
conditions, simulation should match CarbonTracker
if transport is similar
22Lack of global mass conservation
- Because of emissions, large gradients near the
surface are created. The semi-Lagrangian
advection scheme does not conserve mass. - The poor vertical mixing of CO2 from the surface
exacerbates the non-conservation issues.
10
20
50
Increasing KTmin reduces increase in global CO2
Petagrams C
Time
23Hypothesis
- Hypothesis Adding fluxes at the surface creates
large horizontal gradients. Without sufficient
vertical mixing in the boundary layer, these
unrealistically large gradients are smoothed by
the semi-Lagrangian advection scheme
(nonconservative flavour). With fast vertical
mixing, horizontal gradients are reduced before
the SL scheme can act. - To prove this Check global mass before and after
advection and before and after diffusion - Mass change due to diffusion is machine precision
- Mass changes due to advection!
24Further proof Turn off advection
control
4.5 Pg C 2.1 ppm too much
Annual growth is 7.7 Pg but should be 4
Petagrams C
No advection
Time
25How did we accumulate so much CO2?
Mass change due to advection over 24 h
- The mass change due to advection over 24h is
shown - 7.7 Pg C per year is 0.0004 Pg C per time step
for monotonic changes. - For global CO2 of 818 Pg C only 0.00006 Pg C can
be represented with 32-bits. - The error we are looking for is only 6.7 times
machine epsilon
Mass change (Pg C)
0.028 Pg C
Hour
26Mass conservation Semi-Lagrangian advection
Houweling et al. (2010, ACP)
- ECMWF IFS (red) shows spurious increase of 1 ppm
(Recall GEM spurious increase of 2.1 ppm in one
year) - South Pole (or Darwin) shows background CO2
values best and better illustrates annual trend
Simulated and observed XCO2
1 ppm
IFS LMDZ TM3 TM5 obs
Pg C
27EC-CAS version GEM v4.6.0-rc8
- Factors found to reduce spurious mass gain
- Reducing time step
- Adding horizontal diffusion to tracers consistent
with meteorological fields - Including convective transport of tracers
(Zhang-McFarlane scheme) - Adding tracer mass conservation scheme with
global mass fixer (Bermejo-Conde)
Without tracer mass conservation scheme
With Bermejo-CondeILMC scheme
Petagrams C
Time
28Global mass of water vapour in GEM analyses
during 2009
The total mass of the atmosphere varies mainly
due to water vapour loading.
- Trenberth and Smith (2005, J.Clim.)
- The mass of dry air is constant
- Water vapour cycle amplitude is 0.36 hPa or
0.00037 rel. to dry air - Here amplitude is 1900/5E60.00038
Petagrams
Time
29Next puzzle
- Why dont we get exact mass conservation even
after we (Monique Tanguay) implemented a tracer
mass conservation scheme? - Tracer variable in model
- Presently a pseudo moist mixing ratio (mass
CO2/mass moist air). (Mixing ratio is NOT
adjusted whenever water vapour changes, e.g.
after physics step.) - Tracer mixing ratios defined w.r.t. dry air is
another way - Observations are of mixing ratio w.r.t. dry air
(mass CO2/mass dry air) - Lets check global mass of CO2, air and water
vapour at various points in the model time step.
30Terminology used here
Mass change due to advection actually includes
any changes anywhere in the dynamics or physics
steps.
31GEM does not conserve global moist air mass
without use of switch PSADJ
Global moist air mass
- About 2500 Pg of moist air is lost in 10 days.
- This is a relative loss of 0.0005
PSADJon
PSADJoff
Petagrams
Day in January 2009
32Impact of switch PSADJ
Mass change due to dynamicsphysics steps
- Turning PSADJ on removed the H2O signal from
moist air mass
2 0 -2 -4 -6 -8 -10
10 5 0 -5 -10 -15 -20
PSADJon PSADJoff
PSADJon PSADJoff
PSADJ seems to remove water! Air mass include H2O
signal
Petagrams
Ideally red curve should look like this
Moist air
Water vapour
1 3 5 7 9
1 3 5 7 9
January 2009
January 2009
33A missing source of mass for Ps
- Claude Girard (RPN-A) determined that the changes
in global water vapour due to physics impact
GEMs thermodynamic equation but the flux of
water across the Earths surface was not properly
accounted for. - We need to use the surface pressure to compute
the total air mass and we assume that the water
vapour mass is accounted for when computing
tracer mass. If the surface pressure does not
reflect the current mass of water vapour, global
tracer mass calculations will not be accurate. - Claude devised a means of adding this source of
mass to surface pressure at the end of the
physics time step (see his Note from August 19,
2014). http//iweb.cmc.ec.gc.ca/armasmp/docs/mass
-cons/Total_mass_variation_iin_GEM_girard.pdf - Monique Tanguay (RPN-A) implemented this in GEM
v4.7.0 and v4.6.0-rc8
34Impact of new mass source of Ps
Mass change due to dynamicsphysics steps
- With adw_source_psTrue, moist air mass change
from one time step to the next resembles water
vapour mass change, as hoped
Adw_source_psTrue
Adw_source_psFalse
Moist air
Water vapour
Hours from May 1, 2009 0UTC
Hours from May 1, 2009 0UTC
35Impact of ps_source on air mass
Air mass evolution over 10 days
- PSADJ acts on moist air
- We actually need PSADJ to act on dry air
PS_source on PS_source off
PS_source on PS_source off
Petagrams
Moist air mass
Dry air mass
Hours from Jan. 1, 2009 00Z
Hours from Jan. 1, 2009 00Z
36New ps_source term will impact meteorological
forecasts
Expt by Monique Tanguay
2 day forecast valid 3 Jan 2009 Difference in
surface pressure due to new Ps mass source
- Differences are largest in the tropics and in
synoptic scale systems over the ocean - Max differences are about 3 hPa!
- There may be an impact on meteo forecasts
37Forecast impact of ps_source NH summer/winter
(neg/neutral)
Expts by Michel Roch
GYY15 96h
SH
NH
Tropic
Control Ps_source
Summer
Winter
38Another new flag PSADJ-dry
- For both experiments PS_source is on
- Good conservation in first 24 hours
PSADJ on moist air PSADJ on dry air
Spurious increase in dry air mass
10 day change is 100/5.1E62E-5
Petagrams
10 day change is 10/5.1E62E-6
Better but not perfect conservation of dry air
Dry air mass
Hours from Jan. 1, 2009 00Z
39Impact of ps_dry Neutral
Expts by Michel Roch
GYY15 96h
SH
NH
Tropic
Summer
Winter
40Need a dry mixing ratio for tracers
Change in CO2 mass
- No tracer mass conservation. Keep PSADJ-dryon,
PS_sourceon. - Define CO2 mixing ratio as ????CO2/??dry-air
instead of ????CO2/??air - Dry mixing ratio removes water signal, and CO2 is
more constant but still need to add tracer mass
conservation scheme for this variable. - This was done by Monique Tanguay
CO2 mixing ratio w.r.t. moist air CO2 mixing
ratio w.r.t. dry air
- Spin-up problem
- CO2 change is 0.0001 Pg C
- Diffusion error is lt0.0000005 PgC
Petagrams
Hours from Jan. 1, 2009 00Z
41CO2 global mass with a dry tracer mixing ratio
Dry tracer mixing ratio
- With a tracer mixing ratio w.r.t. dry air, mass
conservation is good until October then drifts - Accounting for local changes in air mass (surface
pressure) when analyses are inserted every 24h
yields exact conservation! But CO2 fields are
terribleso the story is not over...
Petagrams C
Local offset scheme Dry tracer mixing ratio
normalized Expected mass
Time
42Good agreement with surface obs
Dry tracer mixing ratio, global offset scheme
Without assimilation, CT fluxes
Obs GEM
Alert
Sable Island
Toronto
43CO2 transport with GEM compared to chemistry
transport models
Column mean CO2 for 2009
The model runs use the same initial state and
fluxes
GEM
GEOS-CHEM (US academia)
CarbonTracker (NOAA)
44Relevance of greenhouse gas modeling work to GEM
- Feedback to GEM-MACH
- https//wiki.cmc.ec.gc.ca/wiki/EC-CAS_Technology_T
ransfer - Vertical diffusion equation
- Emissions coding error
- Assessing vertical diffusion equation in dry
mixing ratio - Feedback to GEM
- Helping to test tracer conservation schemes
- Illustrated a missing source of mass for surface
pressure - Involved in redesign of global mean surface
pressure fix - Helping to convert tracer equation to dry mixing
ratio
453. Ensemble kalman filter
46Ensemble Kalman Filter first look
- No tracer assimilation, only passive advection
- Testing with 64 ensemble members, 0.9 grid
spacing - Start on 28 Dec 2008. Run for 4 weeks to 23 Jan
2009 - All members have same initial CO2 and same
fluxes. Spread is due to spread in winds only. - Winds differ among ensemble members due to
differences in model parameters (convection
scheme, parameters involved in PBL model,
diffusion of potential temperature, etc. ),
observation error perturbations - How does uncertainty in winds affect CO2 spread?
47Evolution of ensemble spread
Animation of column mean CO2
Dec. 28, 2008 to Jan. 23, 2009
Ensemble mean
Ensemble spread
48Other coupled meteorology/tracer forecast systems
- ECMWF
- Real time operational 5-day CO2 forecasts since
2013. No assimilation of CO2 obs. Updated
initial conditions from flux inversions every
Jan. 1. Plans Near-real time assimilation of
surface obs of CO2 with coupled
meteorological/tracer assimilation - NASA/Goddard GEOS5
- Coupled CO and CO2 assimilation to meteorological
assimilation. Weakly couple ocean and land data
assimilation systems to atmospheric assimilation
system. - Provide boundary conditions for regional
modelling and flux inversions. - Improve modelling of radiative transfer,
evapotranspiration - Feedback on modeling of boundary layer,
convection, advection - Provide a prioris for satellite retrievals of CO2
and CH4
49Future work
- EnKF development (Polavarapu/Neish)
- compare to obs without CO2 assimilation
- Extend EnKF for tracer assimilation
- Global methane simulations (D.Chan)
- Tropospheric chemistry uses CMAM OH climatology
(D.Plummer) - Stratospheric chemistry from Jean deGrandpré
(LINOZ) - OCO-2 OSSE work (Ray Nassar)
- Regional greenhouse gas simulations to support
inverted Lagrangian trajectory work - supports measurement network interpretation work
of Elton Chan and Douglas Chan - Coupling with CTEM (CCCma ecosystem model) (Bakr
Badawy) - Evaluate CTEM with GEM meteorology
50 51Interannual variability 1870-2013
LeQueré et al. (ESSD, 2014)
Atmospheric accumulation has strong variability
due to land uptake. This is due to climate
variability.
Ocean uptake is not as variable.
52Wet and dry air components of GEM analyses during
2009
This peak is due to water vapour
- Removing the water vapour from the air mass
reduces the peak variation from 3000 to 1500 - However, long time scale variations still exist
53Kalman Filter for coupled system
- System equations (truth)
- Equations for all 3 uncertainties also evolved,
but not shown here
Weather forecast model
Meteorology CO2 tracers Sources (Fluxes)
Transport model
Flux evolution model
54Kalman Filter for coupled system
- System equations (truth)
- Model errors separated into meteorology,
transport, flux - Model errors can be explicitly modelled and
accounted for in actual forecast step (from
analysis)
Weather forecast model error
Meteorology CO2 tracers Sources (Fluxes)
Transport model error
Flux evolution model error
55Kalman Filter for coupled system
- Analysis step
- Meteorology and tracer analysis steps decoupled,
initially - CO2 obs used to update CO2 and flux estimates
- Analysis step includes observation and
representativeness errors - Equations for uncertainties not shown
Meteorology step already done operationally CO2
tracers Sources (Fluxes)
GHG obs
Weight matrix based on error models
56EC-CAS mass conservation progress in the past
year
Polavarapu, Neish, deGrandpre, Gravel
May 2013 July 2013 Nov 2013 Jan 2014 July 2014
- Latest run has
- Surface fields from archives with Liebman
filtering - Physics recycling
- Half time step 900s
- Hor diffusion of tracers
- Bermejo-CondeILMC
GEM 4.5.0-a10 (7.2)
GEM 4.5.0-b7 (5.5)
GEM 4.5.0 (4.8)
(3.7)
GEM 4.5.0mass cons
GEM 4.6.0-rc8 (3.3)
Expected mass (3.3)
By the end of one year, the mass gain is exactly
right!
57Change in global mass due to advection
24h run of GEM-MACH
- Even with the flux boundary condition the global
mass changes during 24 h - The mass change due to advection is shown here
ExperimentfluxBCtry2
58Change in global mass due to diffusion
24h run of GEM-MACH
- The mass change due to the diffusion step is
isolated here - The maximum error of 0.0008 Pg C is 13 times
machine epsilon - The typical error of 0.0002 Pg C is 3.3 times
machine epsilon - This plot reflects only the precision of the
diagnostic calculation. No conclusions about
model behaviour can be drawn.
Jump of machine epsilon
ExperimentfluxBCtry2
59Impact of greenhouse gas modeling work on GEM-MACH
- Using a model in a different way often leads to
insights/feedback on the model - GEM-MACH was designed for air quality forecasts
regional scale up to 2 days, or global scale up
to 10 days. - But we used it for greenhouse gas simulations.
Unlike the air quality problem, (1) we have no
reactive chemistry to hide behind, and (2) we are
looking at long time scales. - We saw problems because of this different focus
and we were able to provide feedback to GEM-MACH - https//wiki.cmc.ec.gc.ca/wiki/EC-CAS_Technology_T
ransfer - Vertical diffusion equation
- Emissions coding error
- Assessing vertical diffusion equation in dry
mixing ratio (in progress)