# Presentation: 047246

## Global Occurrences of Extreme Precipitation and the Madden-Julian Oscillation: Observations and Predictability

**Charles Jones, Duane E. Waliser, K. M. Lau and William Stern**

**How does the MJO modulate weather predictability in the tropics and extratropics?**
**How does the MJO modulate the occurrence of extreme events and their predictability?**

## The MJO and Extreme Precipitation: Observations

**Barlow et al. (2004)**

**Mo and Higgins (1998) Higgins et al (2000) Jones (2000) Bond and Vecchi (2003)**

**Carvalho et al. (2004) Liebmann et al. (2004)**

**Wheeler and Hendon (2004)**

## The MJO and Extreme Precipitation: Observations

**The MJO and Extreme Precipitation: Observations**

## Extreme precipitation events

## Test statistic Zk

_**North America**_** (Mo and Higgins 1998; Higgins et al 2000; Jones 2000; Bond and Vecchi 2003), **_**South America**_** (Carvalho et al. 2004), **_**Southwest Asia (Afghanistan)**_**  (Barlow et al. 2004)**

**Test statistic Z****k**

- Only positive values plotted
- Zk > 1.645 (90% level) Zk > 1.960 (95% level)
- Extremes more frequent in MJO phase than in inactive MJO

## Average, min and max P1k and P2 over gridpoints with statistically significant differences

**Average, min and max P1****k**** and P2 over gridpoints with statistically significant differences**

## The MJO and Extreme Precipitation: Predictability

- _Modeling Approach_
- NASA/GLA model (Kalnay et al. 1983)
- Very good performance of MJO representation in AMIP study (Slingo et al. 1996; Sperber et al. 1996)
- Ten year control run with climatological SST (Waliser et al. 2003; Jones et al. 2004)

## Extreme precipitation events in the NASA/GLA model

_**Extreme precipitation events in the NASA/GLA model**_

- GLA 10-yr control run – NH winter

-  Extremes: above 75th percentile

## Model MJO

_**Model MJO**_
- identification of MJO events in 10-yr control run: EEOF of 30-90 day rainfall anomalies
- Candidate MJO events and Null cases: amplitudes of EEOF modes 1 and 2 and ISI index

*Jones et al. (2004a)*

## Null

** ****15 Events Selected **
**        ****From Each Type**
** ****2 Perturbations**
**      ****Run for Each Event**
** ****Model Integrated for 90 days**
**  ****Perturbations Added**
**  ****Were ~ < 5% of **
**  ****Day-to-Day Variability**

**Mode 1 > 0**
**Mode 1 < 0**
**Mode 2 > 0**
**Mode 2 < 0**
**Null**

**Predictability Experiments: Initial Condition Selection**

**Notes:**
Statistical Models: Show some skill out to 10-20 days.
   (e.g. Waliser et al. 1999; Hendon et al. 2000; Wheeler et al.2000)
Dynamical Models:  For the most part only forecast
  skill studies with models that have poor ISO representation
    (e.g., Chen and Alpert, 198x; Lau and Chang 1996; 
       Jones et al. 2000; Hendon et al 2000)

Few/No MJO predictability studies with “good” MJO models.  

Thus the question remains?

## MJO modulation on potential predictability of extreme precipitation 

**MJO modulation on potential predictability of extreme precipitation **

**IC**

**14 Days lead time**

## Test statistic Zk

**Test statistic Z****k**

- Only positive values plotted Zk > 1.645 (90%) Zk > 1.960 (95%)
- Higher frequency of correct forecasts in MJO phase than in inactive MJO

*Jones et al. (2004b)*

## Average, min and max P1k and P2 over gridpoints with statistically significant differences

**Average, min and max P1****k**** and P2 over gridpoints with statistically significant differences**

**~**

**~**

*Jones et al. (2004b)*

## Conclusions

_**Observations**_
- Higher frequency of extremes during active MJO phases
- On a global scale, extreme events during active MJO are about 40% higher than in quiescent phases in locations of statistically significant signals
_**Model Experiments**_
- Overall, the GLA model has a realistic representation of extremes in tropical convective regions associated with the MJO but shortcomings are also present.
- Predictability experiments indicate higher success in the prediction of extremes during active MJO than in quiescent situations
- Overall, the predictability experiments indicate the mean number of correct forecasts of extremes during active MJO periods to be nearly twice the correct number of extremes during quiescent phases in locations of statistically significant signals
- Jones, C., D. E. Waliser, K. M. Lau, and W. Stern, 2004a: The Madden-Julian Oscillation and its Impact on Northern Hemisphere Weather Predictability. Mon. Wea. Rev., 132, 1462-1471
- Jones, C., D. E. Waliser, K. M. Lau, and W. Stern, 2004b: Global occurrences of extreme precipitation events and the Madden-Julian Oscillation: observations and predictability. J. Climate (in press)