# Presentation: 691085

## Comparison of MLS with Models 

**Ju-Mee Ryoo, Darryn Waugh, Takeru Igusa**
- Johns Hopkins University
- Correspondence: _[jryoo1@jhu.edu](mailto:jryoo1@jhu.edu)_; _[waugh@jhu.edu](mailto:waugh@jhu.edu)_

**PDFs of Tropical Tropospheric Humidity: Measurements and Theory**

-  **PDFs of AIRS RH**

- Since water vapor is the main greenhouse gas, it is important to know its **spatial distribution and the processes behind this distribution.**
- Here we examine the PDFs of tropospheric relative humidity (RH) for measurements from MLS and AIRS, and show that the observed PDFs can be reproduced by a simple theoretical model.

** ****Introduction**

_**Aura MLS PDFs**_

**PDFs of ****daily 215 ****hPa RH ****for several subregions ****from**** Aura MLS ****data (symbol****)**

-  PDFs of RH show a large variation between different subregions.

***μ******R***

***σ******R***

***k***

**a**

**a**

**Aura MLS RH (Read et al. 2007), 215 hPa, 2005 – 2007, DJF**** **

**Generalized model parameters**

**AIRS RH **** ****250 hPa**

**Subtropics (15N-25N)**

**Tropics (5S-5N)**

**a**

**Theoretical Models**

-  Generalized model closely matches the observed PDFs and Cumulative Distribution Functions (CDFs).
-  The generalized model can fit the data for all subregions.
- Note that the generalized model can reproduce some important features such as the ***peak, range and skewness*** of the PDF at RH.

_**PDF**__**s**_

**(a)**** PDFs**** and (b) ****CDFs**** of 215 hPa RH in NH winter (DJF) for whole tropics (30S-30N) from Aura MLS data (symbol), fits by ****S06(dotted)**** and ****generalized (solid)**** models.**

**(a)**

**(b)**

**PDFs for Tropics  (5S-5N,120E-140E)**

**PDFs for subtropics   (15-25N,120E-140E)**

**Comparison of MLS with Models**

*t* : age (time) of Parcel since Last saturation

-  Moistening by random events
- Uniform subsidence (water is conserved)

_**Basic Assumptions**_

**Generalized version of S06 Model**

**Sherwood et al. (2006) Model (S06 Model)**

- Generalized PDFs of RH reduces to the original S06 distributions when *k*=1

- Time since last saturation is modeled as time between _random moistening events_

- Eliminate t from above equations, yields the PDFs of RH as

- Given _uniform subsidence_, RH can be approximated as

- Eliminate t from above equations, yields the generalized PDFs of RH as

-          is the uniform drying time by subsidence
-       is the time between remoistening events.

- where,

- where,

- : Gamma function

***r*****: ratio of drying time (       ) to moistening time (         )**
***k*****: measure of randomness of remoistening events**

- Time since last saturation is now modeled as _random moistening events_ but includes randomness of these events (*k*).

- • Variations in *r* and *k* characterize variations in the moistening processes.
-  The maps of *μ**R* and *σ**R* show a strong resemblance to those of *r* and *k*, respectively, i.e., there is **large *****μ******R*** where ***r***** is large** and **large *****σ******R*** where ***k***** is small**.

***r***** ~ *****μ******R***
***k ~ 1/ *****(*****σ******R*****) ****2**

**Longitudinal variation (a, c) *****r*****, and (b, d) *****k *****for generalized model fit to Aura MLS, UARS MLS****,**** and AIRS**** ****measurements. **

_** **_

-  Good agreement between different data sets ***except ******the tropical convective regions***** ***(5S-5N, 120E-140E)**** ***where the PDFs from MLS are much broader than those from AIRS.

-  Good agreement between different data sets in terms of *r* and *k*.

** ****Small *****r (r<1) *****and large *****k*** in dry regions in subtropics and tropical eastern Pacific.
-   **Large *****r****** (r>1) and small k****** ***in tropical convective regions.

-  In tropical dry non-convective regions,  the range of PDFs are similar, but the peak values are slightly different.

-  Largest disagreement of *k* occurs in tropical convective regions.

-  The general tendency of variation of *k* is that the *k* is larger from AIRS than MLS.

**PDFs for 3 subregions in the ****(a) ****subtropics (15*****◦*****N-25*****◦*****N) and (b) tropics (5*****◦*****S-5*****◦*****N)**** ****for ****different data set in DJF.**

** ****UARS MLS RH (Read et al. 2001), 215 hPa, 1992-1994, DJF**
** ****Aura MLS RH (Read et al. 2007),  215 hPa, 2005-2007, DJF**

-  **Data can be well fit** by a two parameter generalization of the Sherwood et al. (2006) model.
-  The parameter *r* and *k* not only provide a simple way to **characterize the RH distributions**, but also provide insight into the **processes controlling** on the RH distributions.

_**Acknowledgement**_

_**References**_

- Fetzer, E., and Coauthors, 2003: Validation of AIRS/AMSU/HSB core products for Data Release Version 3.0, JPL D-26538.
- Read, W. G., and Coauthors, 2001: UARS Microwave Limb Sounder upper tropospheric humidity measurement: Method and validation, *J. Geophys. Res.*, **106**, 32,207-32,258.
- Read, W. G., and Coauthors, 2007: Aura Microwave Limb Sounder upper tropospheric and lower stratospheric H2O and relative humidity with respect to ice validation, *J. Geophys. Res.*, **112**, D24S35, doi:10.1029/2007JD008752.
- Ryoo, J.-M., T. Igusa, and D. W. Waugh, 2008: PDFs of Tropical Tropospheric Humidity: Measurements and Theory, *Submitted to J. Climate (in review)*.
- Sherwood, S. C., E. R. Kursinski, W. G. Read, 2006: A distribution law for free tropospheric relative humidity, *J. Climate*, **19**, 6267-6277.

-   This work was supported by grants from NASA and NSF. We thank Andrew Gettelman for providing the gridded AIRS data, and Eric Fetzer, Annmarie Eldering, Bill Read, and Steve Sherwood for helpful conversations and advice.

**Large *****r*****, small *****k*** in tropical convective regions
-              rapid, random vertical mixing
**Small *****r*****, large *****k*** in dry regions
-             slow, more regular lateral mixing

-  A more quantitative link between the different physical processes and the parameters *r* and *k* is needed. This would be performed by trajectory-based water vapor simulations.

**Comparison between MLS and AIRS**

**Spatial variation in *****r***** and *****k***

- : subtropics

- : tropics

**a**

**b**

**c**

**f**

**e**

**d**

**east Asia (40E-60E)**

**east Asia (40E-60E)**

**western Pacific (120E-140E)**

**western Pacific (120E-140E)**

**eastern Pacific (260E-280E)**

**eastern Pacific (260E-280E)**

**    **_**Non-convective Region**_
**Small *****r*****:  **slow remoistening
**Large *****k*****: **less randomness

**         **_**Convective Region**_
**Large *****r*****:  **rapid remoistening
**Small *****k*****: **more randomness

***μ******R***

***σ******R***

***r***

***k***

**Generalized model parameters**

**A****ura MLS**** RH **** ****2****15**** hPa**

**Conclusions **

** ****PDFs for Tropics  (5S-5N,120E-140E) from AIRS**

**PDFs for whole Tropics  (30S-30N,0E-360E) from AIRS**

**In the whole tropics and tropical convective region, AIRS PDFs show better match with model.**

**Cf)**

**Subtropics (15N-25N)**

**Tropics (5S-5N)**