Transcript Long-Term Trends in the Tropical Cold Point Tropopause

Long-Term Evolution of the
Tropical Cold Point Tropopause
Simulation Results and Attribution Analysis
Thomas Reichler, U. of Utah, Salt Lake City, USA
John Austin, UCAR-NOAA-GFDL, Princeton, USA
Motivation
• Tropical tropopause is closely related to climate change
• Examples:
– Tropopause controls stratospheric water vapor
– Tropopause is controlled by tropical upwelling, QBO, tropospheric and stratospheric temperature changes
• Exact cause-and-effect relationship between climate
change and tropopause change is unclear
• Outline
– Simulations with coupled chemistry climate model
– Past and future evolution of tropical tropopause
– Identify factors for change:
1. regression analysis
2. conceptual model
Methodology
• GFDL-AMTRAC: stratosphere resolving coupled
chemistry climate model (2.5x2.5, L48)
• Simulation: 1960-2100, 3 members
– PAST: 1960-1990, historical forcings (SST, GHG, ODS)
– FUTURE: 1990-2100, IPCC-A1B and WMO (2003)
forcings, SSTs from GFDL-CM2.1
• Cold point tropopause
– Interpolation after Reichler et al. (2003)
– Lapse rate definition: 0 K/km
– Zonal averages (22S-22N) and annual means
Tropical Tropopause Evolution
• Heights
– PAST: Increase
– FUTURE: Increase
– 1960-2100: ca. 1 km or
ca. 10%
• Temperatures
– Climatologically
important transition
– PAST: Cooling
– FUTURE: warming
Decadal Trends
Tropics
Height [m/dec.]
Global
PAST
FUTURE
1980-2004
OBS
70
64
123
64
0.25
-0.27
-0.41
Temperature [K/dec.] -0.13
1. Linear Regression Model
Fit tropical tropopause parameters (temperature,
pressure, height) to a linear regression model using
the following four factors:
AER
SST
O3
UPW
Aerosols (60 hPa at equator)
Tropical SSTs (22S-22N)
Total ozone (globally averaged)
Tropical mass upwelling (77 hPa), BDC
These factors represent major processes known to
influence the tropopause.
Regression Parameters Evolution
Regression Analysis: Heights
Plots are decadally smoothed
• Contribution of each term to tropopause height
1. UPW - most important
2. SST - comes second
Regression Analysis: Temperatures
Plots are decadally smoothed
1.
2.
3.
4.
O3 - dominates PAST
SST - dominates FUTURE
UPW - probably strongly related to SST
AER - small impact
2. Conceptual Tropopause Model
• Shepherd (2002):
Constant lapse rates
above (γs) and below (γt)
tropopause
• Explain tropopause
change by temperature
change below (ΔTt) and
above (ΔTs )
1. ΔTt > 0: height ↑ temperature ↑
2. ΔTs < 0: height ↑ temperature ↓
• Staten and Reichler (2008) show:
and
Testing the Simple Model
• Test impact of simulated temperature trends above ΔTs (0,
LS) and below ΔTt (0, LT, UT) on tropopause itself
PAST
LS (and UT)
FUTURE (LS and) UT
PAST
FUTURE
γs = -4 K/km, γt = 6 K/km
Cause and Effect Analysis
Change per
century
ΔZtrop ΔTtrop ΔTUT ΔTLS
PAST
700
FUTURE 640
-1.3
2.5
2.5
5
-5
0
O3 UPW GHG
↓↓ ↑↑ ↑
↑
↑ ↑↑
ΔZtrop • Tropopause increases mostly due to LS cooling
(PAST) and UT warming (FUTURE)
ΔTtrop • Similar
• PAST: LS cooling dominates
• FUTURE: UT warming dominates
PAST
ΔTLS O3, UPW, GHG
FUTURE ΔTUT GHG
Conceptual vs. Regression Model
Conceptual
PAST
FUTURE
ΔT↓
ΔZ↑
ΔT↑
ΔZ↑
O3 + UPW + GHG
GHG (SSTs)
Regression
O3
UPW
SST + O3
UPW
• In the PAST, ozone depletion was most important for
cooling and lifting the tropopause
• In the FUTURE, greenhouse gas increase will be most
responsible for warming and lifting the tropopause
Thank You
More info: Austin and Reichler (2008, JGR)
Trend Analysis