# Presentation: 796584

## Impact of common SST anomalies on global drought and pluvial frequency

- Kirsten Findell and Tom Delworth
- Geophysical Fluid Dynamics Laboratory
- Princeton, NJ
- 33rd Climate Diagnostics and Prediction Workshop/CLIVAR Drought Workshop (CDPW)
- October 2008

## SST forcing patterns used for Clivar Drought Working Group Study

- Climatology derived from Hadley Centre Monthly SST data, 1901 to 2004 (HADISST1, Rayner et al 2003)
- Rotated EOF analysis: first three modes:
- Linear trend pattern (27.2%), scaled by 1
- Pacific pattern (20.5%), scaled by 2
- North Atlantic pattern (5.8%), scaled by 2

## SST forcing patterns used for Clivar Drought Working Group Study

- REOF 1

- REOF 3

- REOF 2

- All runs: fixed SSTs, 50 years long
- Control run: Climatological SSTs

## Outline

- SST forcing patterns
- Drought index used: SDDI
- Extensive look at Cold Pacific experiment
- GFDL model to demonstrate the methodology
- Multi-model analysis (GFDL, NSIPP, CAM)
- The three models tend to yield similar results in terms of drought/pluvial frequency and intensity
- Pac/Atl combination experiments, Multi-model means
- Positive/negative forcings tend to yield opposite results
- Trend and Trend/Pac/Atl combinations
- What do they tell us about the relative strengths of these different forcings in the present day?
- Trend impacts are generally overwhelmed by Pac/Atl impacts
- Additional experiments to look at future scenarios
- Trend impacts should not be overwhelmed by Pac/Atl impacts in the future
- Conclusions

## Supply-Demand Drought Index (SDDI)

- From Rind et al. (JGR, 1990)
- Difference between moisture supply (precip) and demand (potential evap)
- Similar in construct to PDSI:
- dSDDI = P – Ep – (P – Ep)clim
- ZSDDI = d/
- Y(i) = 0.897 Y(i-1) + Z(i)
- (P – Ep)clim,: seasonal cycle (monthly values) determined from Control run
- Benefits:
- Tied to soil moisture (through evaporative demand), but since soil moisture is very model dependent (e.g., depth saved) this index is good to use when looking at multiple models
- No grid-specific empirical coefficients to estimate (might these change if climate changes?)

## Cold Pacific: Changes in Mean SDDI

- GFDL model:
- Annual mean SDDI differences,
- where significantly different from control
- (95% level, modified t-test)

## Cold Pacific: Drought Frequency

- GFDL model: differences in mean

- Average number of months/year in drought
- (SDDI < -2.0)

## Cold Pacific: Changes in Drought Frequency

- GFDL model: differences in mean

- Difference from Ctl, months/year in drought
- (SDDI < -2.0)

- Locations with reductions in mean SDDI also show increased drought frequency.
- There are some additional locations with minor increases in drought frequency,
- despite a lack of significant change in the mean SDDI (Central Asia, Central Africa).

## Cold Pacific: Pluvial Frequency

- GFDL model: differences in mean

- Average number of months/year with
- SDDI > 2.0

- Locations with increased mean SDDI also show increased pluvial frequency.
- There are some additional locations with minor increases in pluvial frequency,
- despite a lack of significant change in the mean SDDI (high latitudes).

## Cold Pacific: Drought Frequency

- Multi-model
- mean

## Cold Pacific: Drought Intensity

- Multi-model
- mean

## Cold Pacific: Pluvial Frequency

- Multi-model
- mean

## Cold Pacific: Pluvial Intensity

- Multi-model
- mean

## Model agreement in Cold Pacific run

- Drought is:
- Much more frequent in Continental US and southern South America
- Slightly more frequent in eastern Canada, from 35-50°N in Europe and Asia, and along the east coast of Asia
- Pluvials are:
- Much more frequent in Central America, northern South America, and Oceania
- Somewhat more frequent in Arabia and Australia

## Model differences in Cold Pacific run

- CAM is much more sensitive than GFDL and NSIPP throughout Africa (greater tendency towards pluvials in this run)
- African pluvial pattern in CAM run extends into Mediterranean region, pushes European drought region further north
- GFDL model more sensitive in high latitudes (more pluvials in this run)
- The three models differ in the central location and intensity of the drought response in the US

- Drought Frequency, MMM, Pac/Atl runs

- Cold Pacific

- Cold Atlantic

- Warm Atlantic

- Warm Pacific

- Pluvial Frequency, MMM, Pac/Atl runs

- Cold Pacific

- Cold Atlantic

- Warm Atlantic

- Warm Pacific

## SDDI time series in Central US – Pac/Atl combinations; GFDL model

## SDDI time series in Central US – Do we see linearity in the responses?

- GFDL model

## SDDI time series in Central US – Do we see linearity in the responses?

- GFDL model

## Warm Linear Trend: Drought Frequency

- Multi-model
- mean

## Warm Linear Trend: Pluvial Frequency

- Multi-model
- mean

## Model agreement in Warm Trend run

- Modest increases in drought frequency:
- ~30-45°N in North America (Central US) and
- ~35-50°N in Europe and Asia (Mediterranean region and extending eastward)
- Central and Southern Africa
- Modest increases in pluvial frequency:
- North of ~55°N, particularly in Asia
- Central America and NE coast of South America
- Eastern Australia

## Drought in Trend, Pac, Atl combinations

- Cold Trend, Cold Pac, Warm Atl

- Cold Trend, Warm Pac, Cold Atl

- Cold Trend

- GFDL model

- Warm Trend, Warm Pac, Cold Atl

- Warm Trend

- Warm Trend, Cold Pac, Warm Atl

## Pluvials in Trend, Pac, Atl combinations

- Cold Trend, Cold Pac, Warm Atl

- Cold Trend, Warm Pac, Cold Atl

- Cold Trend

- GFDL model

- Warm Trend, Warm Pac, Cold Atl

- Warm Trend

- Warm Trend, Cold Pac, Warm Atl

## Trend/Pac/Atl combinations

- Impacts of Trend are overwhelmed by Pacific/Atlantic impacts
- Since these standard runs had the Trend EOF multiplied by 1, and Pac/Atl multiplied by 2, this result is in part due to the experimental design
- Present-day runs: composites of the three EOFs all multiplied by 1
- Should indicate if Trend impacts are overwhelmed by ENSO/NAO in current world
- Future-scenario runs: composites of the Pac/Atl EOFs multiplied by 1, Trend by 2
- Should indicate if Trend impacts will be overwhelmed by ENSO/NAO in the future, assuming that ENSO/NAO don’t change much in the future

## Droughts and pluvials in the present

- Warm 1 Trend, Cold 1 Pac, Warm 1 Atl

- Warm 1 Trend

- GFDL model

- Warm 1 Trend, Warm 1 Pac, Cold 1 Atl

- Pluvial increases – bottom row

- Drought increases – top row

## Present-day scenario results

- Drought/pluvial frequency is a strong function of Pacific and Atlantic condition
- Exceptions:
- Central Africa has frequent droughts
- Southern India and SE Australia have frequent pluvials
- Calls into question the validity of fixed SST experiments for the Indian Ocean

## Droughts and pluvials in the future

- Warm 2 Trend, Cold 1 Pac, Warm 1 Atl

- Warm 2 Trend

- GFDL model

- Warm 2 Trend, Warm 1 Pac, Cold 1 Atl

- Pluvial increases – bottom row

- Drought increases – top row

## Future scenario results

- Droughts become more frequent in the future, independent of ENSO/NAO:
- Mediterranean Sea region and east past Caspian Sea (~30-50°N in Africa, Europe, and Asia)
- Central Africa
- Pluvials become more frequent in the future:
- North of 50°N (esp. in Europe and Asia)
- Coastal Asia
- India and Australia (esp. SE)
- Caveat: experimental validity in Indian Ocean region?
- Drought/pluvial frequency remains a strong function of Pacific and Atlantic condition:
- Continental US
- Southern and Northern South America

## Conclusions

- The three models (GFDL, NSIPP, CAM) generally yield similar drought/pluvial results:
- Cold Pacific:
- Increased drought in US, southern SAm., (S Europe, SE coast Asia)
- Increased pluvials in Cent. Am., northern SAm., Oceania, (Arabia, Australia)
- Warm Pacific:
- In general, opposite of Cold Pacific
- Cold Atlantic:
- Increased droughts in Cent. Am., northern SAm., Central Africa, (Oceania)
- Increased pluvials in cent. SAm., (cent. US)
- Warm Atlantic:
- In general, opposite of Cold Atlantic
- Warm Trend:
- Modest changes that are overwhelmed by Pac/Atl impacts in combination runs

## Conclusions (cont.)

- Areas with an increase (decrease) in the mean SDDI tend to also show an increase (decrease) in the frequency of extreme SDDI values
- Areas with more frequent extremes also tend to show higher intensity extremes
- Present day experiments suggest:
- The impact of the background warming trend is generally overwhelmed by the ENSO and NAO signals
- Questionable use of fixed SST models in Indian Ocean Basin
- Future experiments suggest:
- The impact of the trend will be more dominant than the ENSO and NAO signals in many areas of the globe when the magnitude of the trend has doubled, assuming ENSO and NAO characteristics remain relatively stable.