# Presentation: 451784

## Intensification of Summer Rainfall Variability in the 

**Southeastern United States in Recent Decades**

**Hui Wang****1,2****, Wenhong Li****1****, and Rong Fu****1,3**
*1**Georgia Institute of Technology*
*2**NOAA Climate Prediction Center*
*3**University of Texas at Austin*

- NOAA’s 33rd Climate Diagnostics and Prediction Workshop
-  and CLIVAR Drought Workshop
- October 20–24, 2008, Lincoln, Nebraska

**Notes:**
The map shows the region of our focus, 7 SE states.

## 			Highlights:

** ****Intensified SE rainfall variability in recent 3 decades.**
** ****Consistent with the shift of rainfall PDF.**
** ****Closely tired to the Atlantic SST variability.**
** ****Certain predictability based on tropical SST.**

**Notes:**
These are the messages that this presentation wants to deliver.

## Background:

**Lake Lanier **
**– ****main water source for Atlanta**

***2007 ******Southeast drought***
*** ******– ******Worst in 100****** years***

**Background:**
- Summer droughts repeatedly struck the Southeast in recent decades.

**Questions:**
-  Has the rainfall variability been intensified in recent decades?
-  What might cause the intensification?

## Previous works:

- Stahle & Cleaveland 1992: decade-long spring rainfall extremes have been a prominent feature of SE US over the past 1000 yrs.
- Mo & Schemn 2008: model simulations show seasonally varying ENSO forcing on SE US;
- Seager et al. 2008: model simulations show weak connection with SSTA, thus low predictability

## 			    Data

**Precipitation**** **
**     ****CPC U.S. Unified Precipitation (1948–1998, 0.25****o ****x 0.25****o****)**
**     ****CPC realtime U.S. Daily Precipitation Analysis (1999–2007)**
**SST**
-      **NOAA Extended Reconstructed SST (ERSST v3, 2****o**** x 2****o****)**
**Wind and height**
-      **NCEP/NCAR Reanalysis (850 and 200 hPa, 2.5****o**** x 2.5****o****)**
**Period**
-      **JJA 1948–2007, 60 years**

## Part 1

**Data: 1984–2007**
**CPC**

**JJA Rainfall **
**& Variability**

**Southeast:**
**Large mean rainfall**
**High variability**

**Part 1**

**Notes:**
The importance of the SE summer precipitation to the continental-scale warm season rainfall.

## Change in SE Rainfall Variability

- Normalized JJA Precipitation Anomaly

- Year

- 1 stdv=0.64 mm/day

|  | 1st 30 years
1948–1977 | 2nd 30 years
1978–2007 |
| --- | --- | --- |
| Wet and Dry
(> 1 Stdv) | 4 | 11 |
| Contribution to Precipitation Variance | 32% | 68% |

**Change in SE Rainfall Variability**

**Notes:**
Color bars are those exceeding one standard deviation (0.64 mm/day).
Year 2007 is less than one standard deviation because the rainfall index is the average of rainfall over an area larger than the drought region, and also the drought was due to deficit of accumulated rainfall, not the single JJA season rainfall anomaly (also see next slide, longer time scale SPI in 2007).

## Standardized Precipitation Index:

**SE SPI (3-month)**

**SE SPI (3-month)**

**SE SPI (9-month)**

**SE SPI (9-month)**

**Standardized Precipitation Index:**

**4 : 11**

**Moderately to extremely wet/dry**

**5 : 14**

**1 : 3**

**1 : 7**

**Moderately to extremely wet/dry**

**Severely to extremely wet/dry**

**Severely to extremely wet/dry**

- 1st 30 yrs

- 2nd 30 yrs

**Notes:**
Upper: SPI 3-month, Low: SPI 9-month  (how do you define moderately <=1 severe: 1.5 in SPI?)
Left: SPI>1 or SPI<-1, Right: SPI>1.5 or SPI<-1.5
Changes in rainfall variability are also seen in SPI of different time scales and categories. 

## Shift of Rainfall PDF

**60 yrs****	****	****1st 30 yrs****	****2nd 30 yrs**
**Climatology****	****Wet (5)****	****	****Wet (5)**
**	****	****Dry (5)****	****	****Dry (5)**

**Shift of Rainfall PDF**

**2****nd**** 1****st**** clm 1****st**** 2****nd**

**2****nd**** 1****st**** clm 1****st**** 2****nd**

**2****nd**** 1****st**** clm 1****st**** 2****nd**

**Frequency**

**Intensity**

**	****2nd 30 years:**
**Decrease of frequency and intensity in dry summers.**
**Increase of frequency and intensity in wet summers.**

**5**

**1**

**8**

**12**

**15**

**11**

**Difference at 11% **
**significance level**

**Difference at  5% **
**significance level**

- Bootstrap test

## Warm Season Rainfall

***Midwest floods***

**Warm Season Rainfall**

**Southeast and Midwest: out of phase**

**Notes:**
June 2008 Midwest floods
This is just an example showing the typical warm season rainfall pattern, Southeast and Midwest rainfall anomalies are out of phase.

## Composite: 

**Composite: **
**Drought-related **
**Large-scale **
**Circulation**
**Regression vs. SE  precip index**
**JJA 1948–2007 **

**Contour: u200**
**Shading: z200**

**Shading: prcp**
**Vector: wind 850**
**Contour: div 925**

***LLJ***

**Notes:**
The southeast rainfall is a part of continental-scale warm season rainfall variability.
Large scale circulation features (related to SE drought):
Lower level: anticyclonic circulation, less moisture from the Gulf, enhanced Great Plains LLJ, lower-level divergence in the South and convergence to the North
Upper level: positive height anomaly dominant the central US, weakened jet-level zonal wind to the south.
The circulation is consistent with dry condition in the south and wet to the north.

## Change in Zonal Wind Variability at the Jet-Steam Level

**1st 30 yrs**

**2nd 30 yrs**

**Change in Zonal Wind Variability at the Jet-Steam Level**

**Notes:**
Circulation variability also experienced significant change between the two 30-year periods.

## Part 2

**ENSO**

**ATL Zonal Mode**

**Warming Trend**

**Co-variability of SE Rainfall with SST**
**Homogeneous correlation map**

**PCF SST**
**SVD Mode 1**

**ATL SST**
**SVD Mode 2**

**ATL SST **
**SVD Mode 1**

**Part 2**

**Notes:**
Atl sST has strongest loading in SE US, whereas Pacific and linear warming tend to influence midwest US and s. central US.

The boxes are the SST domains used in SVD analyses.
2 SVD analysis: Pacific SST vs. US precipitation and Atlantic SST vs. US precipitation
Each SVD mode has some loadings in the SE.
Bottom panel: Although only Atlantic SST was used in the SVD analysis, the western Pacific warm pool and Indian Ocean also show high loadings. This is the region where global warming signal is strong.

## 200-hPa Zonal Wind Variance: 1st 30 yrs vs. 2nd 30 yrs

**200-hPa Zonal Wind Variance: 1st 30 yrs vs. 2nd 30 yrs**

**1st 30yrs**

**2nd 30yrs**

**ENSO SST**
**ATL Zonal Mode**
**Warming Trend**

**Notes:**
The results are based on reconstructed 200-hPa zonal wind using multilinear regression of 200-hPa height vs. SVD SST time series. Associated with tropical SST, there is an increase jet-stream level zonal wind variability. But ATL SST primarily contributes to the shift of region of larger zonal wind variability to the south shown previously in observations.
10% of the total variance of the 200 hPa u’

## SVD Time Series

**SST****              ****US precip**

**R****  ****= 0.58**

**R****  ****= 0.60**

**R****  ****= 0.63**

| 
ENSO | 1st 30yrs | 2nd 30yrs |
| --- | --- | --- |
| SST | 51% | 49% |
| US P | 35% | 65% |

| Zonal mode | 1st 30yrs | 2nd 30yrs |
| --- | --- | --- |
| SST | 39% | 61% |
| US P | 37% | 63% |

| Warm-ing | 1st 30yrs | 2nd 30yrs |
| --- | --- | --- |
| SST | 35% | 65% |
| US P | 39% | 61% |

- Variance

- Variance

- Variance

**ENSO**

**ATL zonal Mode**

**Warming**

**SVD Time Series**

**Notes:**
R is the correlation between the two SVD time series (SST and US precipitation).
ENSO change cannot explain the increase in variance of USP, however, the decadal changes of Atlantic zonal mode and warming can explain the USP.

Since Atlantic SST also increase the SST variability in the second 30 years, it is a possible cause for the change in the SE rainfall variability.

## Reconstruction of SE Precipitation Index

**Total (R=0.92)**
**ATL ZM (R=0.87)**
**Warming (0.63)**
**ENSO (R=0.39)**

**ENSO dominant**

- Multilinear regression
- based on SVD precipitation time series.

- Correlation
- with OBS

**Notes:**
This slide shows the contribution of co-variability of rainfall with the ENSO, global warming and Atlantic zonal mode to the SE rainfall variability. Out of 15 extremely wet and dry summers (green and orange bars), one (1993) was dominated by ENSO and 14 were dominated by Atlantic zonal mode. Note that the reconstructed SST for 2007 is not good. The warming tends to increase rainfall anomaly in that year.

## Part 3

**1. Project SST (OBS or FCST) onto the SVD SST pattern**
**                ****SST projection coefficient**
**2. Based on SVD SST – US precipitation relationship, **
**	****   ****precipitation projection coefficient**
**3. Based on SVD precipitation pattern,              **
**                ****forecast of precipitation anomaly**

**Part 3**

**Cross-Validation**
**Anomaly Correlation: Hindcast vs. OBS**

- Hindcasts: JJA 1948–2007 rainfall based on observed SST

**ENSO**

**2 ATL modes**

## Dry

**Based on **_***Observed***_** SST**

**“****Forecast”**

**Observation**

**Dry**

**Dry**

**Wet**

**Wet**

**Notes:**
This is just an exercise. The forecast for the coast regions are not good.

## 			Summary

** ****SE summer precipitation exhibits higher interannual variability in recent 30 years.**
** ****The shift of rainfall variability is linked to tropical Atlantic SST variability, suggesting certain predictability of SE summer rainfall based on tropical SST.**