– Track recovery of the ozone layer

– Understand aspects of how composition affects climate

– Quantify aspects of pollution in the upper troposphere

EOS MLS Overall Objectives

AuraAura

MLS

The EOS MLS Instrument Advanced follow-on to UARS MLS launched in 1991

radiometers in 5 broad bands between 118 GHz, 2.5 THz455 kg, 535 W , 100 kb/s data, 28 spectrometers

Pioneers satellite measurements over full submillimeterwavelength region (0.1 - 3 mm)

enabled by new technology, mostly developed by JPL

Flight instrument

1.6 m GHz

antennaspectro-meters,

digitizers,and data

handling

telemetry

GHz caltargets

THz caltarget

space view

atmo-sphericsignals

and space views

GHz switching

mirror and

optical multi-plexer

190 GHz

240 GHz

640 GHz

2.5 THz

118 GHz

0.25 m THz scan

mirror

THz telescope

Signal Flow Block Diagram

MLS Atmospheric Measurements

Solid lines indicate useful individual profile measurements are generally obtained.Dashed lines indicate that averages are generally needed for useful precision.

MLS Measurement of Cloud Ice in Upper Troposphere Will improve global circulation models (GCMs) used for weather and climate forecasts and help quantify the upper tropospheric (UT) hydrological cycle, including water vapor feedbacks on climate change

Aura MLS: Jan 2005 mean

ECMWF analyses: Jan 2005 mean

UCLA-Liou GCM: 5-year Jan mean

GFDL-RAS GCM: 18-year Jan mean

NCAR CAM3 GCM: 10-year Jan mean

GFDL-Donner GCM:20-year Jan mean

UT cloud ice from MLS, ECMWF analyses, and various GCMs

Li et al., GRL 32, L14826, 2005

Cloud ice increase with sea surface temperature >300 K leads to convective moistening of UT, and H2O feedback ~3x above that implied solely by thermodynamics

Su et al., GRL 33, L05709, 2006 sea surface temperature (K)

300K

UT H2Oconvective cloud ice

300K 300K

greenhouse parameter

MLS Measurement of CO in Upper Troposphere CO from biofuels and from biomass burning is lofted by convection, with a major pathway over Tibet into the stratosphere Detection of CO pollution lofted to the upper troposphere and temporarily ‘trapped’ in anticyclone over south Asia

Filipiak et al., GRL 32, L14825, 2005Li et al., GRL 32, L14826, 2005

Quantifying convective transport over the Tibetan plateau – and discovering it is a ‘short circuit’ to the global stratosphere

Uses data primarily from MLS, but also from MODIS, AIRS and TRMMFu et al., Proc. Nat. Acad. Sci., April 2006

Detection of ‘CO tape recorder’ in lower stratosphere, and linking it to seasonal changes in biomass burning

Reproduced by GMI chemical transport modelSchoeberl et al., GRL, in review

MLS 150 hPa CO: 25 Aug – 6 Sep 04

orange is ~120 ppbvgreen is ~60 ppbv

frequency of >80 ppbv CO abundances at 100 hPa

MLS (day 0)

back trajectories-5 days -20 days

CO deviation from mean vs. time and height

MLS Upper Troposphere Weekly Mean Maps for 9-15 Apr 2006 at 100 hPaWhite contours: GMAO PV = 3.5 (10-6Km2kg-1s-1) indicative of dynamical tropopause

Black contours: GMAO OLR = 240 W/m2 for IWC map and IWC = 0.3 mg/m3 for other maps indicative of deep convection

MLS Cloud Ice (mg/m3)

-3.5

-3.5

240 240

240

240240

240240

240240

240

0.0 0.1 0.3 0.4 0.5 0.7 0.8

MLS Relative Humidity (%)

-3.5

0 8 17 25 33 42 50 58 67 75 83 92 100

MLS H2O (ppmv)

-3.5

3.7 4.0 4.2 4.5 4.8 5.1 5.4 5.6 5.9

cloud-filtered MLS CO (ppbv)

-3.5

10 20 30 40 50 60 70 80

cloud-filtered MLS O3 (ppbv)

-3.5

16 31 47 63 78 94 109 125

MLS Temperature (K)

-3.5

180 186 193 199 205 211 218 224 230

GEOS4-CHEM NRT CO (ppbv)

-3.5

10 20 30 40 50 60 70 80

GEOS4-CHEM NRT O3 (ppbv)

-3.5

9 19 28 38 47 56 66 75

GMAO GEOS-4 FLK H2O (ppmv)

-3.5

1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0

Produced by Jonathan Jiang of the MLS team at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA, from EOS MLS, GEOS-CHEM and GMAO GEOS-4 data. JPL Clearance CL#05-3903

MLS Upper Troposphere Weekly Mean Maps for 9-15 Apr 2006 at 147 hPaWhite contours: GMAO PV = 3.5 (10-6Km2kg-1s-1) indicative of dynamical tropopause

Black contours: GMAO OLR = 240 W/m2 for IWC map and IWC = 1 mg/m3 for other maps indicative of deep convection

MLS Cloud Ice (mg/m3)

-3.5 -3.5

240 240

240

240240

240240

240240

240

0.0 0.4 0.8 1.1 1.5 1.9 2.2 2.6 3.0

MLS Relative Humidity (%)

-3.5 -3.5

111 1

1

0 8 17 25 33 42 50 58 67 75 83 92 100

MLS H2O (ppmv)

-3.5 -3.5

111 1

1

3.6 7.2 10.8 14.4 18.0

cloud-filtered MLS CO (ppbv)

-3.5 -3.5

111 1

1

11 27 43 60 76 92 108 125

cloud-filtered MLS O3 (ppbv)

-3.5 -3.5

111 1

1

10 26 42 57 73 89 104 120

MLS Temperature (K)

-3.5 -3.5

111 1

1

190 195 200 205 210 215 220 225 230

GEOS4-CHEM NRT CO (ppbv)

-3.5 -3.5

111 1

1

11 23 34 45 56 68 79 90

GEOS4-CHEM NRT O3 (ppbv)

-3.5 -3.5

111 1

1

9 19 28 38 47 56 66 75

GMAO GEOS-4 FLK H2O (ppmv)

-3.5 -3.5

111 1

1

3.6 7.2 10.8 14.4 18.0

Produced by Jonathan Jiang of the MLS team at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA, from EOS MLS, GEOS-CHEM and GMAO GEOS-4 data. JPL Clearance CL#05-3903

MLS Upper Troposphere Weekly Mean Maps for 9-15 Apr 2006 at 215 hPaWhite contours: GMAO PV = 3.5 (10-6Km2kg-1s-1) indicative of dynamical tropopause

Black contours: GMAO OLR = 240 W/m2 for IWC map and IWC = 3 mg/m3 for other maps indicative of deep convection

MLS Cloud Ice (mg/m3)

-3.5 -3.5240 240

240

240240

240240

240240

240

0.0 1.2 2.3 3.5 4.7 5.8 7.0

MLS Relative Humidity (%)

-3.5 -3.5

33

3

3 3

0 8 17 25 33 42 50 58 67 75 83 92 100

MLS H2O (ppmv)

-3.5 -3.5

33

3

3 3

17.5 35.0 52.5 70.0 87.5 105.0 122.5 140.0

cloud-filtered MLS CO (ppbv)

-3.5 -3.5

33

3

3 3

17 42 67 92 117 142 167 192

cloud-filtered MLS O3 (ppbv)

-3.5 -3.5

33

3

3 3

10 26 42 57 73 89 104 120

MLS Temperature (K)

-3.5 -3.5

33

3

3 3

195 199 203 206 210 214 218 221 225

GEOS4-CHEM NRT CO (ppbv)

-3.5 -3.5

33

3

3 3

11 23 34 45 56 68 79 90

GEOS4-CHEM NRT O3 (ppbv)

-3.5 -3.5

33

3

3 3

9 19 28 38 47 56 66 75

GMAO GEOS-4 FLK H2O (ppmv)

-3.5 -3.5

33

3

3 3

17.5 35.0 52.5 70.0 87.5 105.0 122.5 140.0

Produced by Jonathan Jiang of the MLS team at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA, from EOS MLS, GEOS-CHEM and GMAO GEOS-4 data. JPL Clearance CL#05-3903

MLS Upper Troposphere Weekly Mean Maps for 9-15 Apr 2006 at 316 hPaWhite contours: GMAO PV = 3.5 (10-6Km2kg-1s-1) indicative of dynamical tropopause

Black contours: GMAO OLR = 240 W/m2 for IWC map and IWC = 3 mg/m3 for other maps indicative of deep convection

MLS Cloud Ice (mg/m3)

-3.5 -3.5-3.5

-3.5240 240

240

240240

240240

240240

240

0.0 1.2 2.3 3.5 4.7 5.8 7.0

MLS Relative Humidity (%)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

0 10 20 30 40 50 60 70 80 90 100 110 120

MLS H2O (ppmv)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

33

33

75.0 150.0 225.0 300.0 375.0 450.0 525.0 600.0

cloud-filtered MLS CO (ppbv)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

-5 31 67 103 140 176 212 248

cloud-filtered MLS O3 (ppbv)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

-51 -23 6 35 64 93 121 150

MLS Temperature (K)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

205 210 215 220 225 230 235 240 245

GEOS4-CHEM NRT CO (ppbv)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

12 23 35 47 58 70 81 93

GEOS4-CHEM NRT O3 (ppbv)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

9 19 28 38 47 56 66 75

GMAO GEOS-4 FLK H2O (ppmv)

-3.5 -3.5-3.5

-3.5

3

33

33

3

3

333 3 3

3

3

33

75.0 150.0 225.0 300.0 375.0 450.0 525.0 600.0

Produced by Jonathan Jiang of the MLS team at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA, from EOS MLS, GEOS-CHEM and GMAO GEOS-4 data. JPL Clearance CL#05-3903