# Presentation: 375510

## A TRMM-based analysis on tropical  dryness and clouds over tropical Indian Ocean

_**G.L.Liberti**_**1****,F.Cheruy****2**
**	****	****1 ISAC-CNR, Roma, Italy ****g.liberti@isac.cnr.it**
**	****	****2 LMD-CNRS, Paris, France.**

**Brown & Zang ’97**
**Soundings+GMS**

**Liberti & al ’94**
**SSM/I+GMS**

**Mote & Frey ’06**
**MODIS**

**Notes:**

I’m going to present some preliminary results on the characterization of clouds observed during the occurrence of anomalously dry atmospheres over the Indian Ocean.
First of all let me explain what are we looking for and why.
In 1994-95 I was merging GMS IR data with SSM/I ones for a precipitation-sort of study on the TOGA-COARE dataset when I observed that the driest SSM/I pixels would not correspond to clear sky ones according with the GMS IR data. 
That was quite weird to me: if you don’t have moisture why should you waste it to make clouds? I misinterpreted this observation as downdraft from single convective systems. This plus few others errors and a very bad English made my paper been rejected and was the end of the story.
Since then several papers have been published on the water vapor anomalous distribution over the TOGA-COARE area due to the intrusion of extra-tropical dry air in the tropics. Such a phenomenon, often referred as dry tongues,  is of particular interest because  the temporary un-availability of atmospheric moisture, influences the convective activity. So for climate and weather modelers it is important to characterize spatial and temporal scales of such anomaly in order to be able to reproduce it. On the other hand, as the same level, numerical models must be able not only to reproduce the anomaly onset but also the recovery to the normal status at the right time and space scales. Intuitively the recovery mechanism is going to be a mixture of dynamical, cloud and radiative processes.
Now going back to my observation, if radiation play a role the presence of a cloud and the knowledge of cloud properties is important to correctly reproduce the phenomenon. But, in the published studies, because based mostly on SSM/I and radiosounding data very few information were given on clouds.

## TRMM data pre-processing

**DRY**

**CIRRUS**

**TMI  – VIRS Merging**
**Box Definition**
**Thresholds Definition**

**VIRS 1B01 + TMI Daily TPWV Remote Sensing Systems**

**DRY & CLOUDY**

**CLOUDY**

**>250K**

**<302K**

**T****98%**

**T****moda**

**<T****dry****>**

**TRMM-VIRS March 1999**

## March’99

**Dry&Cloudy/Dry**

**Ex:**
**.75**

## March’99

**Dry&Cloudy/Dry**
**Dry&Cirrus/Dry**

**Ex:**
**.75****/****.50**

## March’99

**Dry&Cloudy/Dry**
**Dry&Cirrus/Dry**

**Ex:**
**.75****/****.50**

## March’99

**Dry&Cloudy/Dry**
**Dry&Cirrus/Dry**

**Ex:**
**.75****/****.50**

## March’99

**Dry&Cloudy/Dry**
**Dry&Cirrus/Dry**

**Ex:**
**.75****/****.50**

## January 1999

- March 1999

## HOW OFTEN WHEN A DRY LAYER OCCURS CIRRUS OCCURS TOO ?

## VIRS T4-T5 vs T4 SCATTERPLOTS FOR 16 ‘RANDOMLY’ 

**VIRS T4-T5 vs T4 SCATTERPLOTS FOR 16 ‘RANDOMLY’ **
**SELECTED DRY CASES ACCORDING WITH THE **
**RADIOSOUNDING AT SEYCHELLES**

## SO WHAT?

## P(dry)*P(cir)-P(cir&dry)

- P(dry)*P(cir)

- P(cir)<10%

**-1**

**0**

**+1**

**>0  Dry → ****- Cirrus**** **
**=0 events are uncorrelated**
** **
**<0 Dry → ****+ Cirrus**** **

## Possible explanations

- Cirrus are always there but if the atmosphere is dry they can be more easily detected with the split window test

-  Ratio of  the number of  pixels, within each box, classified as cirrus for 1kg/m2 TPWV width class out of the total population of the class. Ratio range (y-axis): 0-1. TPWV range (x-axis): 20-70 Kg/m2.
- Bars are** red **(**blue**) if the corresponding TPWV class is below (above) the 50% percentile of the TPWV distribution within the box.**  **

- March 1999.

## Possible explanations

- Cirrus are always there but if the atmosphere is dry they can be more easily detected with the split window test
- A combination of physical mechanisms link the occurrence of dry air below the cirrus with increased lifetime of the cirrus

## Slide 17

## Average profiles, for the month of March over the Seychelles
               all soundings (dashed-dotted line)
               subset of soundings where the dry inversion is detected at 575 hPa 
As a reference a thin horizontal line is plotted at 575 hPa (top of the inversion layer) 

-                all soundings (dashed-dotted line)
-                subset of soundings where the dry inversion is detected at 575 hPa
- As a reference a thin horizontal line is plotted at 575 hPa (top of the inversion layer)

## Conclusions & future work

- Cloudiness associated with dry events is partly due to cirrus
- The relationship between cirrus and dry columns has different sign and geographycal distribution
- Keep extending the analysed TRMM dataset  (400GByte/yr!!!)
- Find a collaboration with cloud/cirrus modeling group to test the 2nd proposed hypothesis
- Part of the results shown has been published as:
- Liberti G.L., & F.Cheruy,  2006. *Tropospheric dryness and clouds over tropical Indian Ocean.* Atmos. Res.. 82, 276-293.
- 					Contact:  _g.liberti@isac.cnr.it_

## More...

## Portion of soundings with TPWV below the percentile reported in the abscissa, that do not present a dry inversion (see text for the definition) in the water vapour mixing ratio as a function of the percentile value. Results are shown in form of skill score index False Alarm Ratio (FAR).

- Statistics computed using 7733 radio-soundings from the Seychelles (4.66°S, 55.5°E) site.
- Average water vapour mixing ratio profile,
- Standard deviation of the average mixing ratio.
- c)Portion of total precipitable water content, for the average profile (a), below a particular pressure level.** **

## Average portion of TPWV below a pressure level. About 50% within the 900-400 hPa pressure range.

**>0K**

**<5K**

**TRMM-VIRS March 1999**

**Δ****T45**

**Δ****T45****DRY**

## WHAT IS A DRY INTRUSION ?

- Can we get more informations about the characteristics of such cirrus?

## RETRIEVAL OF CIRRUS OPTICAL PROPERTIES(Wu 1981 , Parol et al. 1991, Prabhakara et al. 1993)

**Tau**

**Height**

**Size Distribution**

- small

- LARGE

## RETRIEVAL OF CIRRUS OPTICAL PROPERTIES: 

**             ****RETRIEVAL RESULTS:  Cloud top height ****~****11km => ****~****250 hPa**
**	****	****                ****Particles modal radius ****~****14********m,**** **
**                                                       ****Cirrus mean optical thickness ****~**** 0.8**

## RETRIEVAL OF CIRRUS OPTICAL PROPERTIES: PRELIMINARY RESULTS

**Summary of 2-DC Tropical Anvils S.D. measurements (2270 SD)**
**[McFarquhar &Heymfield 1996]**

**Developing**
**Mature**
**Dissipating**

## Cirro giovaneParticelle grandi

**Size Distribution**

- small

- LARGE

- time

- Gravita’
- Evaporazione

- Cirro *anziano*Particelle piccole

- Time

## Slide 31

## METEOSAT5 IR 

**METEOSAT5 IR **
**METEOSAT5 –WV**** ****260**** ****250**** ****240**

**METEOSAT5**** ****WV **
**METEOSAT5 –WV**** ****260**** ****250**** ****240**

**METEOSAT5 IR**
**METEOSAT5 –WV**** ****260**** ****250**** ****240**

- TMI-TPWV

**METEOSAT5 IR**
**METEOSAT5 –WV**** ****260**** ****250**** ****240**

- VIRS-CLOUD

## CIRRUS&DRY

- CIRRUS
- CLOUDY
- CLOUDY&VERY MOIST

**≈ ****1000 Km**

## T0-T+12 [K]

- T0
- T+12

##   MECHANISM #2

- 200-300 hPa

- 300-400 hPa

-   **MECHANISM #2**
- 	Wind Shear induced turbolence

## METEOSAT5 IR

**METEOSAT5 IR**
**METEOSAT5 –WV**** ****260**** ****250**** ****240**

- TMI-TPWV

**METEOSAT5 IR**
**METEOSAT5 –WV**** ****260**** ****250**** ****240**

- VIRS-CLOUD