AIM science results and their significance for PMC long

1 May 3 – 4, 2012 Russell - 2nd CAWSES WkShp

GATS

AIM science results and their significance for PMC long-term change studies

By

James M. Russell III and Pingping Rong 2nd CAWSES Workshop

LASP Science Building, Boulder, CO

May 3 - 4, 2012


GATS

AIM was launched from VAFB by a Pegasus XL rocket

  Launched April 25, 2007 at 1:26:03 PDT

  Near perfect 600 km orbit - 596 km perigee, 601 km apogee - Ascending node equatorial crossing time only 47 seconds off


GATS

  SOFIE: Solar Occultation for Ice Experiment

- A 16-band differential absorption radiometer (UV to IR) to simultaneously measure cloud properties, the PMC environment and cosmic smoke

  CIPS: Cloud Imaging and Particle Size Experiment

- Four CCD cameras; image PMCs at λ = 0.265 µm - 2000 x 2000 element array with 5km x 5km resolution

AIM has two operating instruments


GATS

Two questions are addressed in this presentation:

1.  What is the main driver of long-term bright PMC increases measured by SBUV? Is it temperature H2O, or other causes?

2.  Is the number of clouds increasing at low latitudes in the 40O to 60O range?


GATS

Albedo: DeLand et al. [2007] Frequency: Shettle et al. [2009]

PMC brightness and frequency increases over the last 27 years from SBUV data

Provided by Matt DeLand


GATS

What is the main driver of long-term increases in in bright PMCs measured by SBUV? Is it T, H2O or other causes?

Approach: Examine SOFIE T, H2O and PMC changes during the season

Use the Hervig et al. (2009) 0-D water/ice model to analyze changes


GATS

AIM SOFIE data show that T is in dominant control at the season start and end. H2O is in control during the season.

Northern Hemisphere Rong et al., 2011

PMC Workshop, Dec 2009 8

Log-

Pres

sure

Alti

tude

(km

)

WACCM Estmated Temperature and H2O trends Arctic (70°N, -90°) 2000-2050 (JJA)

Large trend in H2O, small trend in T near summer mesopause Rolando Garcia, December, 2009

PMC effect on H2O is not included

20

20

20

-2 -1 0 1 2 k/decade %/decade

-5 0 5 10 15

100

80

60

40

20

Alti

tude

(km

)

ΔT Δ H2O


GATS

Is there any temporal trend in the occurrence of low latitude PMCs?


GATS

Low latitude NLC observations All occurred during or after 1999

  US towns where NLCs were recently sighted:

- Bellingham, WA 46.8N - Glen Ullin, ND 46.8N - Portland, OR 45.5N - Twin Falls, ID 42.6N - Logan, UT 41.7N - Boulder, CO 40.2N - McGuire, NJ 40.1N

• • •

• • •

•

•

• •

All low latitude sightings occured in or after 1999

Orange

50N

60N


GATS

NLCs observed over Omaha, NE (410N) on July 14, 2009 Mike Hollingshead


GATS

AIM CIPS observed low latitude PMCs on July 15, 2009


GATS

Approach: Create clouds using the following:

- 0-D model by Hervig et al. (2009)

- SABER temperatures for 2002 to 2011 with an MLS H2O climatology for the

PMC season

- MLS temperatures and H2O for 2005 to 2011 Analyze the numbers and temporal changes in clouds as a function of latitude over the 10 year period from 2002 through 2011

Low latitude PMC data sets used and analysis approach


GATS

Two H2O fields are used in 0-D modeling - the MLS mean and maximum

Steps to obtain the H2O fields:

1.  5° latitude bands

2.  For each band calculate the mean or select the max

of all events for a given day and given year

3. Calculate the average for each band for each day for both the maximum and mean cases over the period 2005 - 2011

MLS H2O fields at 84 km


GATS

SABER Max H2O

Sharply defined by PSAT, not very sensitive to H2O


GATS

SABER Mean H2O

Sharply defined by PSAT, not very sensitive to H2O


GATS

SABER derived clouds show a robust upward trend

MLS derived clouds show similar changes

SABER 84km cloud number trends for max H2O

Lower lats


GATS

SABER derived clouds show a robust upward trend

For latitudes > 55N, both SABER and MLS derived clouds show no trend

SABER 84km cloud number trends for max H2O

Lower lats Higher lats Higher lats


GATS

SABER 84 km temperature trends for 2002 - 2011

Downward T trend drives cloud increases for 40 – 55N


GATS

SABER 84 km temperature trends for 2002 - 2011

In the saturated condition > 55N, T variation no longer controls cloud frequency, which is close to 100%.

Downward T trend drives cloud increases for 40 – 55N


GATS

Brightest PMCs, mice>60 ng/m3 MLS H2O trend

MLS 84 km H2O and bright PMCs trends for 2005 - 2011


GATS

All PMCs, mice>0.15 ng/m3 MLS H2O trend

MLS 84 km H2O and all PMCs trends for 2005 - 2011


GATS

Does 0-D model bright PMCs derived using MLS T, H2O agree with SBUV changes?

SBUV Long-term changes

[Shettle et al., 2009]


GATS

Brightest clouds, mice>60 ng/m3

Both 0-D model bright PMCs derived using MLS T and H2O and SBUV show upward trend




GATS

Brightest clouds, mice>60 ng/m3

Both 0-D model bright PMCs derived using MLS T and H2O and SBUV show upward trend



0-D model bright PMCs derived using SABER T, and MLS H2O climatology show no upward trend.


GATS

PMC long-term change analysis summary   Because Psat is near zero during the PMC season and PH2O is large, H2O is the main parameter governing LT change. WACCM ΔH2O and ΔT support this idea.

  Low latitude Psat gradient is sharp and PMCs form at this edge

  0-D model coupled with SABER T and MLS T and H2O, show that PMCs are occurring more often at low latitudes

  Downward T trend at low latitudes drives the PMC increases

  H2O and not T causes brightest PMCs to increase with time for >70N

  At >55N, same number of all clouds form each year, so there is no trend

  Both SBUV PMC changes and 0-D model derived changes using MLS, agree, providing some amount of validation of these results.


GATS

Backup


GATS

0-D water/ice model (Hervig et al., 2009)

PH2O=H2O vmr× P (hPa)

(hPa)

(ng/m3)

Assumes that ice exists in thermodynamic equilibrium with the local temperature and water vapor, i.e. “H2O vapor in excess of saturation gets assigned to the ice phase”.

Ignores: nucleation, sedimentation, horizontal transport, time depend- ence of growth and sublimation, and the Kelvin effect.


GATS

Qualitatively same as max H2O case; therefore cloud numbers are not very sensitive to H2O and trend in the low latitudes driven mostly by temperature

Lower lats Higher lats Higher lats

SABER 84 km cloud number trend for mean H2O


GATS

AIM CIPS NH June 21, 2007


GATS

SOFIE: Solar Occultation for Ice Experiment

  Operates over 0.3µm to 5.3 µm range

  T, NLCs, CO2, H2O, CH4, NO, O3, aerosols, cosmic smoke

  2 km vertical resolution

A 16-band differential absorption radiometer (UV to IR) to simultaneously measure cloud properties and the PMC environment


GATS

High SOFIE sensitivity allows subvisible ice to be measured up to about 90km

SOFIE: Solar Occultation for Ice Experiment


GATS

CIPS: Cloud Imaging and Particle Size Experiment

  λ = 0.265 µm; 1 X 2.5 km pixel size

  Cloud morphology and particle sizes


Four CCD cameras image PMCs at ~ 83 km


GATS


June 18, 2009

June 22, 2009

June 26, 2009

CIPS 2009 northern summer orbit strips

Four CCD cameras image PMCs at ~ 83 km


GATS

AIM CIPS NH June 22, 2007


GATS

Polar-region mice is completely controlled by H2O

SABER Mean H2O


GATS

Polar-region mice is completely controlled by H2O

SABER Max H2O

Documents

AIM science results and their significance for PMC long