1. Estimating Future Changes in Drought Risk in New Zealand by Statistical Downscaling from Global Climate Models
Brett Mullan1, Alan Porteous1, David Wratt1, Andy Reisinger2, Howard Larson2, Gerald Rys3
1 National Institute of Water & Atmospheric Research, Wellington, NZ
2 Ministry for the Environment, Wellington, New Zealand
3 Ministry of Agriculture and Forestry, Wellington. New Zealand

2. Outline NZ drought risk under current climate
Potential Evapotranspiration Deficit (PED) as a drought index
Downscaling from global climate model runs to obtain future rainfall, PET projections
Using these to produce PED scenarios
Projected changes in drought frequency: 2030s, 2080s
Assumptions
Implications
In spoken introduction, explain that water-related matters (too much - ie changes in floods; too little, ie drought) are shaping up to be one of the key climate change impacts issues for New Zealand. This paper outlines work to develop some quantatative estimates of how drought risk may change under various future cimate change scenarios - a topic od considerable importance for New Zealand agriculture
Note: Focus of this paper is on soil moisture - not river flows

3. NZ drought risk under current climate
Main areas of drought risk are in east and north
Main factor in rainfall patterns is mountain backbone across predominant westerly flow
Periods of enhanced westerly or southwesterly flow tend to be dryer than usual in east
El Niño typically gives enhanced SW flow over NZ, and increases drought risk in the east
PED: The amount of water that would need to be added to a crop over a year to prevent loss of production due to water shortage

4. Accumulated Potential Evapotranspiration Deficit (PED) as a drought index
Run a daily soil moisture balance
Field capacity water storage taken to be Available Water Capacity (AWC). For this study we used 150mm
Rainfall in excess of field capacity was assumed lost as runoff + drainage
If Sd>½(AWC) then ETd = PETd If Sd<½(AWC) then ETd = 0
Potential evapotranspiration deficit PED = PETd - ETd
Accumulate on a daily basis, beginning July 1 (NZ is in Southern Hemisphere) PEDd = PEDd-1 + (PETd-ETd)
The moisture balance is run using a “bucket” model for soil moisture
Explanation of terms: S = water storage; P = precipitation; PET = potential evapotranspiration; RO = surface runoff;
D = drainage loss through percolation; d = number of days from 1st July
ET = actual evapotranspiration (sometimes called soil water-restricted evapotranspiration RET)
PET is calculated for pasture, using daily values of appropriate climate parameters. Use …. (get from Alan)
Accumulated PED is essentially the amount of water that would need to be added to a crop over a year to prevent loss of production due to water shortage

5. PED is closely related to “days of deficit”
PED is closely related to “days of deficit”. It does well at identifying past dry years
Lincoln, July-June years, 1881/2 to 2003/4
Fraction of NZ gridpoints (0.05° grid) with July-June PED exceeding shown thresholds
(72/3, 77/78, 97/98 were big El Niño years)

6. What will happen later this century ?
We selected PED as our “drought index” partly because we can estimate future values on a 0.05° grid covering New Zealand by downscaling from global climate model runs for various future climate scenarios
This requires downscaling to obtain grid-point estimates of rainfall and of potential evapotranspiration (as anomalies from present monthly means) for (the “2030s”) and for (the “2080s”).
For this study we used global projections from the CSIRO Mark2 model, and from the UK MetOffice HadCM2 model.
We used two sets of projections from each climate model - adjusted to correspond to global temperatures changes approximately 25% and 75% of the way between the lower and upper bounds of the SRES range
Temperature change °C
IPCC TAR Projections using SRES scenarios

7. Downscaling from global models to obtain grid-point rainfall estimates for 2080s
Rainfall : For each grid point (0.05° grid) use historical data to develop multiple linear regression for monthly rainfall anomaly (cf ).
Predictors: Monthly anomaly of rainfall averaged 160°E to 170°W at latitude of grid point. Monthly Z1, M1 pressure index anomalies. Use NCEP-NCAR reanalyses.
Apply the resulting regression equation to output from climate model to get monthly rainfall projections for 2030s, 2080s
Projected change in spring rainfall cf 2080s (%)
(Z1 anomalous pressure diff Auckland - Christchurch)
(M1 anomalous pressure diff Hobart - Chathams)

8. Downscaling from global models to obtain grid-point PET estimates for 2080s
PET: For each grid point use historical data to develop multiple linear regression.
Predictors: Grid-point values of monthly rainfall and temperature anomalies. Monthly Z1, M1 pressure index anomalies from NCEP-NCAR (All anomalies cf )
For grid point monthly T anomalies use similar approach to rainfall (previous slide)
Apply the resulting regression equation to output from climate model to get monthly PET projections for 2030s, 2080s
Would like to use temperature, wind speed and solar radiation as predictors, but the last two are not available or satisfactorily downscalable.
So use rainfall as a proxy for solar radiation, Z1 and M1 anomalies as these indicate wind flow over NZ.
Satisfying that explained variance is highest (and very significant statistically) in eastern drought-prone regions.

9. Producing future PED scenarios
Previous steps provide monthly average changes of rain, PET at each grid point
Estimate daily time series of past rainfall Pi at each grid point from based on daily climate observations
Produce hypothetical daily grid point rainfall time series for 2080s by multiplying Pis by ratio of projected future grid point rainfall for that month to observed average rainfall for that month from historical time series
For daily future grid point values of PET use projected average for the month
Feed these daily rainfall and PET projections into daily soil moisture balance to calculate and accumulate PED
Time series approach for rainfall, monthly average/30 every day for PET.
Cover different models (Hadley, CSIRO), use of central portion of SRES scenarios.

10. Projected changes in drought risk, 2080s, based on downscaled PED estimates
“Low-medium” scenario
“Medium-high” scenario

11. Caveats and Cautions Uncertainties in regional climate projections
Scenarios spanned only central portion (~25% to 75%) of IPCC SRES range
Rainfall time series assumed proportional change in amount of rain each wet day, but not change in number of rain days compared to present
Assumed increase in leaf stomatal resistance to evapotranspiration due to increased CO2 is offset by increase in leaf area
Picture:
FACE, AgResearch

12. Some implications for New Zealand
Drought risk is expected to increase this century in already drought-prone areas
For “low-medium” scenario, by 2080s severe droughts are projected to occur at least twice as often as at present in many eastern areas (& even more often for the “medium-high” scenario)
For the “medium-high” 2080s scenario, drying of pasture in Spring is projected to advance by about a month in dry eastern regions, relative to the present.