Water vapor in the TTL and stratosphere Bill Randel Atmospheric Chemistry Division NCAR, Boulder, CO

Topics Why is H 2 O important? Measurements of TTL/stratospheric H 2 O Global variability and seasonal cycle Simulations of H 2 O: trajectories and global models Long-term variability and trends

Processes influencing the TTL eddy mixing by baroclinic eddies and monsoon circulations extratropical tropopause cold point tropopause Upward Brewer-Dobson circulation: TTL sets boundary condition for global stratosphere deep convection TTL: Sensitive coupling of circulation, convection, clouds, radiation (all involve water vapor)

wave forcing of mean tropical upwelling TTL structure and transport

What controls variability of the cold-point tropopause? Convection? Dynamically-forced upwelling? T(z) main convective outflow ~12 km cold point tropopause ~17 km height Lapse rate from radiative-convective equlibrium Mean upwelling Radiative balance

Quantifying climate feedbacks using radiative kernels Soden et al, J. Climate, 2006 Temperature kernel K T Water vapor kernel K w Radiation is most sensitive to temps and H 2 O in the tropical upper troposphere Importance of TTL water vapor for climate Stratospheric H 2 O also important for stratospheric temps and ozone

Measurements of TTL / stratosphere water vapor MLS satellite balloon CFH cryogenic frostpoint hygrometer JGR, 2009

JGR, 2011 balloon frostpoint hygrometer measurements at Boulder (40 o N) 1980 – present (~ 1 per month)

ACP, 2009aircraft measurements Australia Africa Brazil

Tropical balloon measurements HALOE satellite data JGR 2010

HALOE sampling for one year HALOE solar occultation Measurements Good vertical resolution ~2 km Limited space-time sampling Observations

MLS daily orbital data Aura Microwave Limb Sounder (MLS) Vertical resolution ~3 km Daily global sampling Observations 2004-present

QJRMS, 1949 The stratosphere is extremely dry because air is dehydrated passing the cold tropical tropopause

QJRMS, 1949 HALOE global climatology

Climatological tape recorder HALOE MLS cold point tropopause

Tropical tape recorder observed by MLS cold point tropopause Interannual variations in tropopause temperature reflected in H 2 O

Tropical dehydration zone is ~20 N-S Lower stratosphere horizontal tape recorder 390 K dehydration in Antarctic polar vortex

Climatology at Boulder (40 o N) Balloon HALOE tropopause Seasonal minimum due to transport from tropics

Trajectory simulation of transport on 400 K isentrope

Summertime lower stratosphere maxima linked to monsoons H H HALOE climatology Asian monsoon North American monsoon

monsoon circulation near 15 km water vapor near 10 km observed by AIRS moist air within monsoon anticyclone

Water vapor over Asian monsoon from Aura MLS MLS H2O (Jul-Aug) 100 hPa MLS H2O (Jul-Aug) 216 hPa max inside the anticyclone max over deep convection hPa 216 hPa Park et al 2009 JGR deep convection

Transport pathways over Asian monsoon CO surface emission (India and South China) convective transport (main outflow near 200 hPa) confinement by anticyclone transport to west of convection 23 Transport above 200 hPa by large-scale circulation References: Park et al, JGR, 2007; ACP, 2008; JGR, 2009 into stratosphere

Trajectory simulations of seasonal cycle * dehydration at Lagrangian cold point * Fueglistaler et al 2005 JGR also Liu, Fueglistaler, Haynes, JGR 2010 Brewer, 1949 model obs

25 MLS observations 100 hPa Trajectory simulation Note: small impact of convective moistening or overshooting convection in these calculations GRL, 2008

Wright et al 2011 JGR Trajectory simulation of dehydration in Asian monsoon Cold dehydration region

ACP, 2011 MLS trajectory model Forward trajectory model

When/where does dehydration occur? Combined analysis of MLS water vapor and GPS temperatures work with Aurélien Podglajen, Pierre and Marie Curie University - Paris GPS radio occultation temps: Daily data from CHAMP, COSMIC, others ~3000 obs/day for middle 2006-present High vertical resolution (~ 1 km), well-resolved cold point Saturation mixing ratios Q sat (RH=1.0) Daily overlapping data with MLS for

GPS measurements gridded data

GPS Temps MLS H 2 O 40 o N-S 80 o N-S Example for one day

100 hPa H2O GPS cold point SMR Boreal Winter 15 o N-S time

100 hPa H2O GPS cold point SMR Boreal Winter 15 o N-S time

100 hPa H2O GPS cold point SMR Boreal Winter 15 o N-S time

Fractional area of RH>1, for 20 o N-S and 100 and 83 hPa 2005 fraction Max during boreal winter

Winter (DJF) Summer (JJA) Fraction of RH > 1.0 at 100 hPa locations where dehydration may occur longitude latitude longitude Dehydration mainly over ~20 o N-S 40 N 40 S Africa Indonesia S. America

Winter (DJF) Fraction of RH > 1.0 at 100 hPa Schoeberl and Dessler 2011 Trajectory dehydration location longitude 40 N 40 S

Summer (JJA) Schoeberl and Dessler 2011 Trajectory dehydration location longitude Fraction of RH > 1.0 at 100 hPa 40 N 40 S

HALOE global mean, 82 hPa Interannual changes in stratospheric water vapor

deseasonalized decrease after 2001 Interannual changes in stratospheric water vapor HALOE global mean, 82 hPa

Extending the satellite record: HALOE + Aura MLS data HALOE MLS overlap during Variability tied to the QBO. What else?

Anomalies originate near the tropical tropopause, and propagate coherently with time Deseasonalized anomalies HALOE MLS

Rapid latitudinal propagation in lower stratosphere Deseasonalized anomalies

ppm HALOE MLS near-global measurements near Boulder (40 o N) Comparisons with the Boulder balloon record satellite balloons

Correlations with tropical tropopause temperatures 82 hPa water vapor cold point temperature anomalies r=0.76 lag=2 months HALOE MLS radiosondes GPS from a few high quality radiosonde stations

Winter-spring Summer-fall r=0.89 r=0.58 Very strong correlation during cold season H2OH2O temp r=0.76 Same data, 3-month averages Seasonal correlations

Fueglistaler and Haynes, 2005 JGR trajectory model (Lagrangian cold point) HALOE uncertainties with ERA40 temps Simulating interannual changes using trajectory models

Trajectory calculations based on different data sets Schoeberl et al 2012 ACP MLS obs. MERRA CFSR ERAinterim Details are sensitive to the meteorological data

Chemistry-climate model simulations from WACCM

HALOE WACCM HALOE vs. WACCM

Water vapor in a climate model (WACCM REF1) 86 hPa water vapor cold point temperature anomalies PEA r=.41 volcanoes

In the model, volcanoes dominate interannual variability EP

Observations: HALOE + MLS very different variability after 1992

Observations: HALOE + MLS very different variability after 1992

Key points: Stratospheric seasonal cycle is well understood. Tropical dehydration mainly during boreal winter (cold season). Tape recorder, rapid global transport in lower stratosphere, monsoons in UTLS during NH summer. Also Antarctic dehydration. Interannual changes for satellite record ( ) in good (quantitative) agreement with tropical cold point. Cold point controls stratospheric water vapor; what controls the cold point? Simulation of seasonal cycle in trajectory calculations and chemistry-climate models is reasonable. Interannual variability is less-well understood (uncertainties in reanalysis data).

Some additional science questions: How can the space-time variability of deep convection and effects on the TTL be better quantified from observations? What are the contrasting characteristics of oceanic vs. continental deep convection on the TTL? How is stratospheric H 2 O maintained within the summer monsoon circulations? How important is overshooting deep convection? What can we learn from high resolution ‘cloud-resolving’ models? Are small-scale processes important? What resolution is necessary to capture climate-relevant processes? How can data assimilation / reanalysis systems be improved for the TTL? Note that we are currently in a data-rich time period. Need to assure the availability of climate-quality data for the TTL into the future (note value of GRUAN).

Thank you

Extra slides

Stratospheric aerosols observed by CALIPSO 20 km 30 km 40 km

Africa Lidar cloud observations from CALIPSO

ACE-FTS summer climatology climatological deep convection

100 hPa heating rates from different data sources

Radiative influence on temperature (Fixed Dynamical Heating calculations) Water vapor differences Pre- vs. post 2001 Water vapor decreases associated with warming

Radiative influence on temperature (Fixed Dynamical Heating calculations) Water vapor differences Pre- vs. post 2001 Water vapor decreases causes warming Long-term temperature changes flat since ~1995

100 hPa H 2 O 83 hPa H 2 O Q sat at the cold point Q sat 15% driest area Zonal averages 15 o N-S ppmv

Distinct behavior of Asian, NA summer monsoon regions Similar H 2 O patterns over Asian, NA monsoons Very different  D

maxima tied to confinement in Asian monsoon anticyclone Park et al, JGR, 2006 carbon monoxide water vapor

Anticyclones in the UT anticyclones Convection (heating) ‘Gill-type’ Solution 67 theory observations Note that the anticyclone does not lie on top of the deep convection geopotential height and winds 100 hPa

Beware problems with historical radiosonde data satellite radiosonde change in radiosonde difference Common problem; many historical radiosonde data have similar jumps