ccmval overview: the extra-tropical utls in chemistry-climate models

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UTLS Workshop Boulder 2009 CCMVal overview: The extra-tropical UTLS in chemistry-climate models Michaela I. Hegglin & Andrew Gettelman Seok-Woo Son, Masatomo Fujiwara, Simone Tilmes, Laura Pan, Peter Hoor, Huikyo Lee, Gloria Manney, Thomas Birner, Gabriele Stiller, Markus Rex, Stefanie Kremser, Don Wuebbles

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CCMVal overview: The extra-tropical UTLS in chemistry-climate models Michaela I. Hegglin & Andrew Gettelman Seok-Woo Son, Masatomo Fujiwara, Simone Tilmes, Laura Pan, Peter Hoor, Huikyo Lee, Gloria Manney, Thomas Birner, Gabriele Stiller, Markus Rex, Stefanie Kremser, Don Wuebbles. - PowerPoint PPT Presentation

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Page 1: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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CCMVal overview:

The extra-tropical UTLS in chemistry-climate

models

Michaela I. Hegglin & Andrew Gettelman

Seok-Woo Son, Masatomo Fujiwara, Simone Tilmes, Laura Pan, Peter Hoor, Huikyo Lee, Gloria Manney, Thomas Birner, Gabriele Stiller, Markus Rex,

Stefanie Kremser, Don Wuebbles

Page 2: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Chemistry Climate Model Validation (CCMVal)

• Present a multi-model comparison of coupled chemistry-climate models (CCMs) in the UTLS using process-oriented diagnostics.

• Comparison is part of a report on CCMs by the CCMVal (Chemistry-Climate Model Validation) SPARC project and will be used for the WMO ozone assessment.

• The different diagnostics test the representation of dynamics, chemistry, transport, radiation, and microphysics and are derived from robust relations seen in observations.

• 17 international models are participating in this round of CCMVal(-2).

• CCMVal-2 included for the first time the comprehensive validation of CCM performance in the UTLS.

• Major efforts were needed in order to

find and process suitable observations for comparison, establish robust diagnostics for the CCMs (which operate in a

free-running mode and are multi-dimensional), turn the diagnostic into a quantitative grade.

Page 3: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

The global UTLS

Page 4: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Tropical diagnostics

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Well, we want to know where we come from, no?

Page 5: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Seasonal cycle in the CPT

The cold point temperature (CPT) determines the entry value of stratospheric water vapour.

• The amplitude of the seasonal cycle is generally well reproduced.

• The models exhibit a relatively wide range in the mean value. (Note that due to the non-linearity of the Clausius-Clapeyron equation regulating H2O saturation mixing ratios, the annual cycle is more important than the mean.)

Page 6: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

In conjunction with the cold point temperature, the water vapor concentration above the CPT is the dominant term in the total hydrogen budget of the stratosphere.

Seasonal cycle in H2O @ 80 hPa

• More difficulties are seen in reproducing the H2O seasonal cycle.

• Model means, phase, and amplitude of the seasonal cycle exhibit a wide range.

Page 7: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

O3 is important radiatively, and thus important for getting the thermal structure correct. O3 is influenced by both transport and chemistry (e.g. lightning NOx).

Seasonal cycle in O3 @ 100 hPa

• The diagnostic is generally well reproduced.

• Many models have less NH summertime tropical ozone than observations.

• Some models exhibit the wrong annual cycle, and one shows an excessive amplitude during summer.

Page 8: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Extra-tropical diagnostics

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Page 9: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Zonal mean zonal wind @ 200 hPa

The Taylor diagram yields a statistical summary of the model performance in terms of correlation and amplitude.

Used to test the models’ realism in representing the meridional gradients of the thermal structure.

Most models perform very well.

Page 10: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Zonally-averaged N2 as a function of latitudes and log-p height in tropopause based coordinates

(Contour intervals are 0.5x10-4 s-1, and values ≥ 5.5x10-4 s-1 are shaded.)

The tropopause inversion layer

The tropopause inversion layer (TIL) is a distinctive feature of the thermal structure just above the tropopause, which reflects the balance between radiative and dynamical processes.

GPS

GPS: Model Resolution

Model Composite

Page 11: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

We need to better understand how features depend on the resolution of both models and observations and how this can bias the evaluations.

Multi-model comparison of individual N2 vertical profiles:

• The maxima in modeled N2 are comparable to or larger than those derived from degraded, but weaker than those computed from full-level GPS data.

• The location of maximum N2 in the CCMVal-2 models is always higher.

Page 12: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

The LMS mass can be seen as an integrated measure for the extra-tropical tropopause and therefore tests the basic dynamical state of the atmosphere.

The mass of the lowermost stratosphere

Page 13: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Total grade for the LMS mass:

• In the NH, most models exhibit a high skill, i.e. realistic amplitude and phase of the seasonal cycle.

• There are, however, major discrepancies in the model means.

• Overall scores are generally higher in the NH than in the SH.

The total grade includes the skill obtained from the Taylor diagram plus the assessment of the mean. We use mean=1 - 1/ng * | μmod - μobs | / σobs

Page 14: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Test of the models’ representation of the relative strength in quasi-horizontal, meridional mixing between the tropics and the extra-tropics and the transport of aged stratospheric air through the large-scale Brewer-Dobson circulation.

Seasonal cycles in tracers @ 100 hPa NH

Page 15: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

The shift to lower amplitudes at this lower level in the UTLS indicates too much mixing across the subtropical jet region.

Seasonal cycles in tracers @ 200 hPa NH

Page 16: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Validates the strength of tropospheric influence on the lowermost stratospheric background composition. The tropospheric fraction of CO* is determined by

CO* = (CO-COstrat)/(COtrop-COstrat).

• We are interested in both, the background value at higher altitudes, as well as the gradient across the tropopause.

• The models perform well given their rather low vertical and horizontal resolution, except for the models with semi-Lagrangian transport schemes.

CO vertical profiles in dθ/dz_tp

Page 17: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

This diagnostic is used to validate the mixing and transport characteristics of the models in the tropopause region.

ExTL width and center

• Generally very poor performance in this metric, which might be at least partly attributable to the limited vertical resolution of the models.

• Recent satellite observations from the ACE-FTS, which have a resolution closer to the CCMs (around 1 km), show indeed a behaviour similar to some models.

Page 18: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

GLOBAL UTLS METRICS TABLE

Despite the relatively low resolution of the models, they represent the UTLS dynamical and chemical features surprisingly well.

Page 19: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Trends in tropopause pressure

Simulations show good historical fidelity with observed tropical tropopause pressure trends, and projected decreases in tropical tropopause pressure in the 21st century.

REF-B1

REF-B2

SH NH

Page 20: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Trends in tropopause pressure

Future Trends are different between hemispheres due to the effects of ozone depletion and recovery in the SH.

Page 21: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

Trends in UTLS O3 and H2O

H2O exhibits strong positive changes in the UT.

Changes in the LMS are in part caused by the upward tropopause trend, and therefore more moderate in TP coordinates.

In the tropical LS, O3 trends are negative in conventional, but positive in tropopause (tp) coordinates.

In the extra-tropics, substantial O3 increases are seen at and above the tp.

Page 22: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

•A wide range of tropical LS H2O values were found. This is likely due to the

tropical tropopause pressure and CPT which exhibit significant biases between models, although the seasonal cycles are generally reasonable.

•LMS mass (which is an indicator of the extra-tropical tropopause pressure) shows a wide range of skill. The performance is generally better in the NH than in the SH. Comparison with other reanalyses is needed in order to gain confidence in the observational reference of the SH.

•The seasonal cycle of O3 in both the tropics and the extra-tropics is for most

models quite good, though a few models do perform very poorly.

•The skill in representing the seasonal cycle in H2O is rather bad: The reasons for

this finding at the 100 hPa level are not so clear, but at 200 hPa it seems to arise from too much tropospheric influence. (H2O is more sensitive to tropospheric in-

mixing than O3).

•The structure of tracer gradients across the extra-tropical tropopause, both vertical and meridional, is perhaps surprisingly good given the comparatively low horizontal resolution of most CCMs. The outliers tend to be models which use a semi-Lagrangian transport scheme.

SUMMARY

Page 23: CCMVal overview: The extra-tropical UTLS in chemistry-climate models

UTLS

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October 2009Hegglin&GettelmanThe UTLS in CCMs

• The UTLS is still relatively sparsely sampled by observations. This unfortunately limits confidence in the quantitative evaluation of model performance in the UTLS. New observations are needed especially for O3 and H2O with a vertical resolution better than 1 km and a horizontal resolution better than 100 km, especially in the SH and the tropics.

• In this round of CCMVal, our main focus was on evaluating the representation of dynamics, and transport and mixing in the UTLS.

However, testing chemistry should be part of future model validation efforts, including tropospheric CCMs used for the IPCC. Future model development is needed that brings together tropospheric and stratospheric chemistry climate models.

ISSUES AND RECOMMENDATIONS

CCMVal data will become available for the wider community early next year. (Respect data policy!)

A diagnostic-package using NCL is available for easier comparison between model fields and observations. (Talk to Andrew Gettelman for more info)