1. EQUATORIAL WAVES EXCITED BY THE TIEDTKE CONVECTIVE SCHEME STUDIED WITH WACCM
Lucrezia Ricciardulli
Remote Sensing Systems, Santa Rosa, California
Rolando R. Garcia
National Center for Atmospheric Research, Boulder, Colorado
Acknowledgements: Byron Boville, Marco Giorgetta (MPI, Hamburg), Jim Hack, Phil Rasch, Fabrizio Sassi, John Truesdale, Stacy Walters
This work was supported by NSF grant ATM

2. The Model WACCM3: Whole Atmosphere Community Climate Model, v.3
Surface to 140 km (CCSM up to 40 km)
Standard Resolution: ~ 1.9o x 2.5o or 4o x 5o horizontal
1.5 – 3 km vertical (66 levels)
Finite volume dynamical core
Interactive chemistry disabled in our experiments

3. Convective variability at short time scales and wave excitation
Equatorial waves excited by convection transport energy and momentum in the middle atmosphere and they affect tropical dynamics. Phenomena like the Quasi-Biennial Oscilation (QBO) and Semi Annual Oscillations (SAO) in the winds are driven by momentum deposition by these waves on the mean flow.
LOCAL FORCING  GLOBAL EFFECT
QBO
From Baldwin et al, Rev. Geophys, 2001

4. SHORT-TERM VARIABILITY OF CONVECTIVE HEATING RATE
We analyzed 3 convective schemes already available for this model, and looked at variability at short time scales (less than 2 days, necessary for wave excitation)
TROPOSPHERIC CONVECTIVE HEATING RATE 20°N-20°S
(K/day)2
GCI
ISCCP
SATELLITE
(estimate from DCC)
WACCM
CONTROL
(Zhang-McFarlane + Hack)
(Hack only)
RAS
(Relaxed Arakawa Schubert)
Variance
>10 days
2.1
2.0
14.7
2.7
2-10 days
4.5
1.1
17.0
1.8
< 2 days
11.7
0.5
1.5
WE start from 3-hourly convective heating rates, integrate over the troposphere. Then analyze the variance about the mean. This table represent the average in the tropics (20N-20S) for a 128-time period (in winter, but the season doesn’t make much of a difference).
The problem: Models with these convective schemes underestimate temporal variability of convection at short periods and, consequently, underestimate wave excitation and propagation in the middle-upper atmosphere

5. OUR APPROACH: THE TIEDTKE CONVECTIVE SCHEME
We implemented the Tiedtke (1989) parameterization from ECHAM into WACCM because ECHAM shows good wave excitation (and produces a QBO when run at sufficiently high vertical resolution).
Tiedtke is a mass flux scheme based on moisture convergence.
We had serious problems with excessive low clouds (global low cloud fraction ~ 65% versus 42% in control case) and TOA balance (off by 30 W/m2)
After making sure this was not a BUG, we fixed this problem by calling the Hack scheme after the Tiedtke scheme, as is done in standard WACCM, which uses Zhang McFarlane + Hack.
Apparently this is necessary because the Tiedtke scheme can support only ONE type of convection for an atmospheric column at each time step (deep, mid-level OR shallow). Tiedtke alone was not efficient at removing instability at lower levels (~900 mb).

6. SOME 5-YR DIAGNOSTICS: PRECIPITATION RATE
No double ITCZ, improved N. Pacific storm track,
better seasonal cycle, but too intense, “spotty”
precipitation areas in warm pool.
SEASONAL CYCLE
WACCM
TIEDTKE
WACCM
CONTROL
Major changes in simulated climate are expected when changing a convective scheme in a climate model. Therefore, before focusing on the wave analysis, we made sure the WACCM+Tiedtke model produced a realistic average climate by running the diagnostic package on a 5-yr low-resolution simulation. Overall, the comparison of a 5-yr WACCM+Tiedtke test with a control run showed some significant differences and highlighted the need for more tuning, but the results are very promising. Here we briefly summarize the main differences compared to the control simulations.
Overall, the precipitation rate increases a little at the global scale, but the distribution is reasonable, more blotchy than control because more variability than CAM. Less double ITCZ. The seasonal cycle of PREC in Tiedtke is much higher than control, but seems to be in sync with Xie-Arkin dataset (max prec in JJA, northern tropics).
The max intensity in Tiedtke could be improved with some tuning parameters.
I did not spend too much time on that because our priority was the VARIABILITY rather than the mean
XIE-ARKIN

7. OTHER VARIABLES:MOST STATIC ENERGY PROFILE
One interesting change we noticed with CAM is that the vertical profile of the moist static energy greatly improves over the ocean with Tiedtke. (But it degrades significantly over certain continental locations, e.g., the Great Plains –not shown) .
Marshall Islands
Midway Island
OBS
CONTROL
TIEDTKE

8. Changes in other variables:
Some change in TOA radiative balance, same magnitude as control (~4 W m-2) but different sign.
Small changes in clouds, precipitable water and latent heat flux
Improvement in annual surface winds
CONCERNS: increase in SW cloud forcing, significant increase in cloud liquid water, Land temperature too warm, land diurnal cycle in precipitation small, ocean heat transport degenerated, large changes in SLP in winter extratropics.
In the control runs, the TOA was unbalanced by 4-5 W/m2; the Tiedtke implementation did alter the radiative balance of the model, changing its sign but staying in the same range. On a global average, there were small changes in the clouds, mainly a small increase of low clouds and a small decrease of high clouds. The Tiedtke scheme also generated an increase in precipitable water and in latent heat flux, but with a pattern more similar to observations than in the control run. The mean zonal wind also seems improved. We observed also an overall improvement of the annual surface winds, except for equatorial winds in winter, which are much stronger than in the observations especially in the western pacific. The Tiedtke simulation also showed a minor improvement in the annual mean zonal temperature profile in the middle atmosphere and the South Pole, compared to observations. Major improvement was however evident in the winter (DJF). The tropical tropopause is a little bit cooler, but is probably a negligible difference.
Some changes in the Tiedtke simulation compared to control (or observations) might be of concern: a) There was a significant increase in the amplitude of surface shortwave cloud forcing, all over the tropics (with global averages from –56 W/m2 in control reaching –66 W/m2 in Tiedtke); b) The grid-box cloud liquid water content significantly increased over the oceans (by about 35%); c) The moist static energy profile which greatly improved over the tropics degenerated over the US northern plains; d) The Tiedtke simulation shows a much warmer land in some areas in South America and Asia (by 2-5 K) compared to control; e) The ocean heat transport degenerated, in particular over the Indian Ocean; f) The surface level pressure in the winter extra tropics departed from the control run and the observations. These changes require a closer look and more tests to identify the reasons behind them.
These changes require a closer look and more tests to identify
the reasons behind them. But this was beyond the scope of our project.

9. VARIABILITY AT SHORT TIME SCALES (from 6 hr to monthly)
TIEDTKE
CONTROL
From now on we focus on VARIABILITY. Here we see the variance maps for convective heating broken down in three bands: low frequency (T > 10 days), medium (2 to 10 days) and high frequency (6 hrs to 2 days). tropics, for the Tiedtke low-resolution (left) In the control run,all the variability at scales shorter than 2 days is due to the continental diurnal cycle.
The Tiedtke simulation shows variance distributed all over the ocean, similar to the GCI satellite
observations (not shown).

10. CONVECTIVE HEATING RATE (K/day) ~ precipitation
Tiedtke scheme implemented in low and high horizontal resolution WACCM
GCI
SATELLITE
(estimated)
WACCM
4x5
CONTROL
4X5 TIEDTKE
1.9X2.5
TIEDTKE
Variance
>10 days
2.1
0.7
4.7
5.2
2-10 days
4.5
0.4
3.3
8.2
< 2 days
11.7
0.9
6.2
5.5
Total variance
18.2
2.0
14.3
18.9
The Tiedtke convective scheme was implemented in a low and high horizontal resolution versions of the
model, and compared to the control run (Zhang-McFarlane scheme).
The table shows the convective heating variance for the three simulations compared to the one
derived from satellite (20NS). The Tiedtke scheme added variability at all time scales. In particular, at short time
scales the variance increased almost by an order of magnitude.

11. Wave activity flux (EP flux)
Using an analytical model (Ricciardulli and Garcia 2000) we calculated the momentum flux that would be associated with vertically propagating waves excited by OBS or MODEL (just above forcing, 12 km). The EP flux is expressed in units of 10-2 m2 s-2.
Westward waves
GCI
SATELLITE
WACCM
4x5
CONTROL
TIEDTKE
1.9x2.5
Rossby
1.75
0.32
2.22
2.17
Rossby-gravity
0.09
0.02
0.20
Gravity
0.83
0.06
0.21
0.39
Eastward waves
Kelvin
-0.34
-0.07
-0.40
-0.38
Rossby-gravity
-0.13
-0.01
-0.05
Gravity
-0.32
-0.20
-0.26

12. COMPARISON WITH SPECTRA FROM SABER SATELLITE DATA: Temperature (2003) for zonal wavenumber =1
W E
SABER
model
30 mb
1 mb
0.01 mb
Waves excited in WACCM are in good agreement with analyses of large-scale waves observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the NASA TIMED satellite (Garcia et al, 2005) for the eastward propagating waves; westward-propagating waves tend to have smaller amplitude than observed.
We plan to perform more comparisons with observations. HIRDLS data are also available now.

13. SIMULATED ZONAL WIND PROFILE (EQUATOR)
CONTROL
4° RES
2° RES
Z (km) 50
100
150
U(z,t)
Generation of WESTERLY LAYER
due to Kelvin waves
time
time
time
NO QBO
Still NO QBO 20
-20 10
-10
U (m/s)
U(t), lower stratosphere
Here we show the temporal evolution of the mean zonal winds at the equator int the model, for 5 years with the control (left), Tiedtke low-res (middle), and Tiedtke HIgh-res (right, on-going simulation). The bottom plots show the timeseries at some selected levels in the lower stratosphere
In the Tiedtke low-resolution run the momentum carried by the Kelvin waves affects the lower stratosphere by generating an eastward wind layer around Km Because of the lack of gravity waves (which can carry both eastward and westward momentum) in the lower-resolution run, an alternation of QBO-like westward and eastward winds is not found, as expected. A shorter run (3-yr) at high resolution shows a modification of the winds in the lower stratosphere. For a successful simulation of the QBO, likely more modifications needed (I.e., higher vertical resolution in order to allow propagation of eq waves which have a small vertical wavelength in the stratosphere).
time
time
time Km

14. CONCLUSIONS
We showed how critical it is for climate models to represent the convective variability at time scales < 2 days for exciting vertically-propagating equatorial waves
The Tiedtke convective parameterization was implemented in WACCM and resulted in a greatly improved equatorial wave excitation
Simulated waves in the middle atmosphere can be compared to satellite observations
The excited waves impact stratospheric dynamics. In order to be able to simulate the QBO, we will likely need to use a high horizontal resolution model at increased vertical resolution to allow propagation in the stratosphere of gravity waves with small vertical wavelengths

15. FUTURE WORK Increase vertical resolution and try to simulate the QBO
Compare model waves with satellite observations
Improve Tiedtke average climatology
We are not funded anymore for this project
Any student/postdoc who likes to contribute?
Anyone interested in looking at the 5-yr diagnostics and point out areas of concern or improvement?
Please contact Lucrezia at