An overview of recent activities at the Global Modeling ... · J.+Climate+ QBO&‘reboot’&of&2016&in&MERRA2& Out-of-phase easterlies disrupt the westerly phase in a broad layer

National Aeronautics and Space Administration

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Global Modeling and Assimilation Office

An overview of recent activities at the Global Modeling and Assimilation Office

with focus on the stratosphere K. Wargan, L. Coy, S. Pawson, A. Molod, R. Gelaro,

R. Todling, L. Takacs, C. Orbe, A. El Akkraoui, G. Partyka &

The GMAO team


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Outline

•  Status of MERRA-2 validation •  QBO ‘reboot’ in 2016 •  Towards full stratospheric chemistry •  Replay and downscaling experiments •  AMIP simulations •  Transition to 4D-EnVar!!! •  Other ongoing developments

This talk focuses on the stratosphere. There is much more going on at GMAO: weather, tropospheric chemistry, land, ocean…


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Status of MERRA-2 validation: core publications

MERRA-2 overview paper Gelaro et al. 2016: The Modern-Era Retrospective Analysis for Research and Applications, Version-2 (MERRA-2); to be submitted to J. Clim. This week MERRA-2 ozone validation paper Wargan et al., 2016: Evaluation of the Ozone Fields in NASA's MERRA-2 Reanalysis, submitted to J. Clim. MERRA-2 QBO paper Coy et al., 2016: Structure and dynamics of the quasi-biennial oscillation as seen in MERRA-2, J. Clim Tech memos Bosilovich, M. G., et al. 2015: MERRA-2: Initial evaluation of the climate, NASA Tech. Rep. series on global modeling and data assimilation, NASA/TM-2015-104606, vol. 39, 136 pp., NASA. [Available at http://gmao.gsfc.nasa.gov/pubs/tm/docs/Bosilovich803.pdf.] McCarty et al. 2016: MERRA-2 Input Observations: Summary and Assessment, NASA/TM–2016-104606/Vol. 46 . Finished and ready for processing


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Status of MERRA-2 validation: the stratosphere & mesosphere

MERRA-2 Global Temperature Anomalies

1980 1985 1990 1995 2000 2005 2010 20151000

100

10

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Pres

sure

(hPa

)

Averaging Period

-4.5 -4 -3.5 -3 -2.5 -2 -1.5 -1 -0.5 0.5 1 1.5 2 2.5 3 3.5 4 4.5}T (K) Gelaro et al., 2016

AMSU-‐A MLS

Pressure [h

Pa]

Some cooling, no obvious discontinuities in the lower stratosphere El Chichon and Mt. Pinatubo signal The largest impact of the observing system changes: in the upper stratosphere and mesosphere •  Introduction of ATOVS AMSU-A •  Introduction of MLS (p<5 hPa)

El Chichon Mt. Pinatubo


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Gelaro et al., 2016

Evolution of polar temperatures during the 2005-2006 Northern Hemisphere winter •  Disappearance of the warm polar

stratopause during the major SSW •  Reformation at a higher altitude and

slow descent These features are captured more realistically in MERRA-2 compared to MERRA that did not use MLS


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Globally averaged temperature at 10 hPa

MERRA-2 uses CRTM to assimilate SSU; cell pressure leaks are taken into account. The two reanalyses converge once more data become assimilated: AMSU, AIRS


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MEAN 30°N-‐60°N

DIFFERENCE St. Dev.

MIPAS MERRA MERRA-‐2

DJF MAM JJA SON

MIPAS - MERRA-2 correlations. Bold line: 0.7

MERRA did not assimilate Aura data Seasonal cycle at 40 hPa captured by both MERRA and MERRA-2 but MERRA-2 has smaller bias Large improvement in the MERRA-2 – MIPAS st. deviations during the Aura period

Aura period SBUV period

Status of MERRA-2 validation: ozone pp

mv

ppm

v


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MERRA-2 is in better agreement with the radiosondes at 50 hPa. Note that the sonde data are assimilated in both reanalyses

Sondes (gray shading) MERRA MERRA-‐2

Zonal wind at Singapore

Coy et al., 2016: J. Clim.

Status of MERRA-2 validation: the QBO


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Coy et al., 2016

Nairobi sondes MERRA MERRA-‐2

MERRA minus sondes MERRA-‐2 minus sondes

SBUV assimilated

MLS assimilated

SBUV period

Aura period

In the Aura period tropical ozone is •  Consistent with the zonal wind •  In agreement with ozonesondes Large vertical smoothing errors in SBUV obscure the phase propagation [Kramarova et al., 2013]

In the Aura period in MERRA-2 the QBO signal in ozone shows more realistic phase propagation

Status of MERRA-2 validation: the QBO


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MERRA-2a

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2015 2016

Composite StDev x SQRT(2)d

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-50 -45 -40 -35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35 40 45 50}U (ms-1)

What Happened

Expected EvoluIon

Coy et al. submiLed to J. Climate

QBO ‘reboot’ of 2016 in MERRA-‐2

Out-of-phase easterlies disrupt the westerly phase in a broad layer centered around 40 hPa

Unprecedented Oddball Disrupted Unexpected Anomalous Rebooted Hiccup dip into the gravitational field of a black hole

Reported by Newman et al., 2016, GRL

Osprey et al., 2016, Science


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-60 -40 -20 0 20 40 60Latitude

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d

Horizontal Momentum Flux (February)

Normalized by the Standard DeviaIon (mean removed)

Momentum Heat 2016

1998

2014

2011

40 Large (+9) 40 hPa and Large (+3) upper troposphere momentum flux.

Coy et al. submiLed to J. Climate



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2015 2016 2017 2018

a

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}U (ms-1)

Seasonal Forecasts Zonal Mean Zonal Wind 10oS-‐10oN

MERRA-‐2 1 Jul Fcst

2018 100

4

Forecast calls for descent of verIcal shear zones

Forecast erroneously called for descent of early Jan verIcal shear zones

Normal

Disrupted

2015 2016 2017

MERRA-‐2 1 Jan Fcst

(Low Horizontal ResoluIon)



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Adding the STRATCHEM chemistry model to GEOS-DAS; Research & Development stage

•  STRATCHEM replaces a simplified parameterized chemistry scheme used in GMAO’s operational data assimilation experiments to date

•  34 transported and 17 derived species •  124 gas-phase and 39 photolysis reactions •  Includes a PSC scheme and heterogeneous reactions •  Reaction rates follow the recommendations in JPL 2010

We plan to assess its viability for use in future products


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STRATCHEM: Towards ozone forecasts

Ozone hole area Ozone hole area

Ozone mass deficit

Ozone mass deficit

With parameterized chem. With STRATCHEM

At present, the model is not suited for running ozone forecasts beyond a few hours With full chemistry we have a good ozone hole forecast skill out to at least 10 days

Analysis 5-day forecast 10-day forecast


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Chemical tendency

Sunlit fraction of the vortex Temperature at the pole Time-

integrated tendency

Chemical ozone loss •  Late December to mid-March after the vortex broke apart •  Maxima in early and late February correspond to vortex displacements (minor

and final warmings) exposing larger portions of the vortex to sunlight •  Maximum cumulative loss of ~2.1 at 480 K (~18-20 km)

STRATCHEM: polar processing in 2015/2016

~20 km


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MERRA-2 AMIP simulations Ensemble of 10 model runs using the MERRA-2 GCM, at the same resolution, with the same boundary conditions and covering the same period. Purpose: Determine how the model climate compares with the reanalysis (and other atmospheric models), identify errors •  For the stratosphere we will be interested in derived diagnostics, e.g. B-D circulation, age of air •  Note that ozone and water vapor are constrained by climatologies – probably less interesting

than dynamics and transport •  Currently in production; 5 ensemble members finished •  The output will be made publicly available

This is work in progress. We haven’t looked at the stratosphere yet


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Replay and downscaling Assimilation

Generate the analysis state, ANA INCREMENT = ANA-BKG

Force the GCM with INCREMENT Run GCM, generate new BKG

Replay Use ANA from an existing analysis

INCREMENT = ANA-BKG Force the GCM with INCREMENT

Run GCM, generate new BKG

•  Faster (the analysis step is already done) •  Can be run with a different model and/or at different resolution •  Analysis increments can be applied selectively

GMAO has produced a 12.5 km resolution replay of MERRA-2 (2000-2015) •  Weather: tropical cyclones better resolved, differences in

precipitation •  Stratosphere: gravity waves resolved better than in MERRA-2

Omega [Pa/s]

MERRA-‐2

12.5 km replay


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Transport in the model, analysis and replay There exist systematic differences in transport between analysis, CTM, and replay: The use of instantaneous analysis fields leads to systematic errors in transport

These issues are being investigated

Replay minus analysis N2O at 480 K, 1 March 2015

%

Realistic age of air in MERA-2 driven CTM Too young in replay Improved with time-averaged analysis forcing

Replay produces faster descent inside the polar vortex leading to lower N2O mixing ratio


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Transition to 4D-EnVar

•  A version of 4D data assimilation in which –  Ensemble forecasts are used to estimate

background error covariances –  The ensemble eliminates the need for a

tangent linear and adjoint model integration

•  In this implementation the background error covariance matrix is a combination of a static and an ensemble component

•  32 ensemble members •  Incremental analysis update •  Now run in parallel to the operational forward

processing; it will become the next operational stream

Pressure [h

Pa]

StaIc B Ensemble B

Ensemble & static component weights


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Other ongoing developments

•  Vertical resolution: 72 layers à 132 layers; ~0.5 km in the stratosphere •  Seasonal forecasts (contributing to the North American Multi-Model

Ensemble): upgrade to a more recent model configuration in progress •  Tropospheric chemistry: inclusion of a new tropospheric chemistry model

(GEOS-Chem), carbon data assimilation, work towards multispecies data assimilation

Plans for new reanalyses •  MERRA-2 based full chemistry reanalysis (in replay mode) •  Coupled atmosphere-ocean-land-ice 1980 onwards •  High resolution atmospheric reanalysis 2000s


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Summary of GMAO developments •  GMAO validation of MERRA-2 and research

–  Stratosphere: a section in Gelaro et al., QBO paper (Coy et al. 2016a); anomalous 2016 QBO: Newman et al., 2016, Coy et al. 2016b; polar TIL and SSWs (Wargan & Coy 2016)

–  Ozone: Wargan et al., ozone validation paper submitted to J. Clim. •  Introduction of full stratospheric chemistry •  MERRA-2 AMIP and downscaling experiments •  Ongoing research on stratospheric transport in analyses, models

and replay •  Transition to 4D-EnVAR •  Lots and lots of work on the troposphere, land and ocean…

Note: production of MERRA was discontinued; final date: 29 February 2016


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Technical note: Incremental Analysis Update; ‘ANA’ vs. ‘ASM’ output

Each predictor step, e.g. 15 min: xi+1 = xi+Δx(xi) In the corrector step: xi+1 = xi+Δx(xi)+ΔANA

Nonlinearity sits here: the tendency depends on state, which depends on the analysis increment

‘ANA’ = background state + analysis increment

‘ANA’ : the analyzed states, the closest to the observations, 6-hourly, only assimilated fields ‘ASM’: the IAU state, consistency between fields and tendencies (dynamical, radiative,…), 3-hourly, larger set of fields (e.g. EPV). Use ‘ASM’ for most applications

Diagram by Bill Putman ASM


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backup


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Wargan et al., 2016

Tropopause – 50 hPa

MERRA MERRA-‐2

Difference St. Dev.

Improvement.

Correla[ons

Lower stratospheric ozone between 30°N and 60°N in ozonesondes, MERRA and MERRA-2 •  Error standard deviation 11.2% (8.1 % in the

Aura period) •  Very high correlation MERRA-2 performs significantly better than MERRA when Aura data are assimilated

Status of MERRA-2 validation: ozone


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0 20 40 60 80 100 120 140Analysis times

0

0.5

1

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3MLS global statistics for March 2016

MERRA-2 O-FSTRATCHEM O-FMERRA-2 O-ASTRATCHEM O-A

Pena

lty fu

nc[o

n STRATCHEM: Impact on the GEOS-DAS

performance

Large reduction in the MLS ozone term of the penalty function indicates much better agreement between the model and MLS and a healthier data assimilation system.

MERRA-2 GEOS- STRATCHEM


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Note on MLS ozone data versions

We replaced MLS v2.2 with v4.2 on 1 June 2015 We turned off the 261 hPa level on 1 May 2016 because of high bias

Pressure [h

Pa]

Pressure [h

Pa]

Version 2.2

Version 4.2

V 2.2 Oct 2004-May 2015

V4.4 w/ 261 hPa level June 2015 – May 2016

V4.4, 261 hPa turned off Since June 2016

Documents

An overview of recent activities at the Global Modeling ... · J.+Climate+ QBO&‘reboot’&of&2016&in&MERRA2& Out-of-phase easterlies disrupt the westerly phase in a broad layer