Palfai Drought Index (PaDI) Easy method to analyze drought, tool for forecast, for early warning

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1 Palfai Drought Index (PaDI) Easy method to analyze drought, tool for forecast, for early warning DMCSEE Final meeting 14 th May 16 th May 2012, Ljubljana Arpad Herceg ATI-VIZIG, Szeged, Hungary

2 PaDI (Palfai Drought Index) Indicates strength of drought for one agricultural year with one data Proportional with crop decrease Uses results of meteorological measures, but the summer precipitation is more weighted characterization of water scarcity in agriculture Contains the most determinant factors Gives time series proper for trend analysis Suitable for correlation analysis (yield, pests, etc.)

PaDI (Palfai Drought Index) Based on Hungarian PAI - Theoretically the same, but less data demand - Calculating is more simple - Relates to local average conditions Calculation data

3 PaDI (Palfai Drought Index) Based on Hungarian PAI - Theoretically the same, but less data demand - Calculating is more simple - Relates to local average conditions Calculation data demand: - monthly mean temperature - monthly precipitation sum Possibility to preparing entire map of droughtness (PaDI 10% ) for larger regions (countries, Carpathian Basin, SEE, Europe)

4 PaDI (Palfai Drought Index) PaDI o PaDI = aug T i= apr = sept 10 PDI + i ( P ) i * wi i= oct 5*100 o * k1 * k 2* k 3 Month w i X 0.1 XI, XII 0.4 I,II,III,IV 0.5 V 0.8 VI 1.2 VII 1.6 VIII 0.9 IX 0.1 Σ= 7.5 k 1 k 2 = relation between summer average temperature and annual average = relation between summer min. monthly precipiation and annual average k 3 = relation between average precipiation of previous 36 month and annual average

5 PaDI (Palfai Drought Index) 1994 Evaluation of PaDI ( for a year) 4-6 mild drought 6-8 moderate drought 8-10 medium-weight drought serious drought very serious drought >30 extreme drought

PaDI (Palfai Drought Index) 1979 1993 1988 1990 1994 2000

6 PaDI (Palfai Drought Index) Evaluation of PaDI ( for a year) mild drought 6-8 moderate drought 8-10 medium-weight drought serious drought very serious drought >30 extreme drought

7 PaDI (Palfai Drought Index) Regional averages of PaDI in period

8 Regression between PaDI and PDSI PAI, C/100mm PAI, C/100mm Kecskemét Debrecen y = e x R 2 = y = e x R 2 = PDSIaug 0.00 PDSIaug in Hungary y = a * e bx ; R 2 avg >0,7

9 Regression between PaDI and scpdsi 20 PaDI 20 PaDI 18 y = 3,102e -0,1499x R 2 = 0, y = 3,3395e -0,1265x R 2 = 0, VARAZDIN (HR) 16 BJELOVAR (HR) 14 Expon. (VARAZDIN (HR)) 14 Expon. (BJELOVAR (HR)) scpdsi scpdsi Croatia y = a * e bx ; a avg = 4,05 b avg =-0,13 R 2 avg = 0,69

10 Regression between PaDI and scpdsi 20 PaDI 20 PaDI y = 15,679e -0,2129x R 2 = 0, y = 16,363e -0,1466x R 2 = 0, ATHEN (GR) 4 HELLINIKON (GR) 2 Expon. (ATHEN (GR)) 2 Expon. (HELLINIKON (GR)) scpdsi scpdsi Greece y = a * e bx ; a avg = 13,10 b avg =-0,13 R 2 avg = 0,69

11 Regression between PaDI and scpdsi 20 PaDI 20 PaDI y = 3,4503e -0,1206x R 2 = 0, y = 3,6544e -0,1733x R 2 = 0, NAGYKANIZSA (HU) Expon. (NAGYKANIZSA (HU)) 12 SZOMBATHELY (HU) Expon. (SZOMBATHELY (HU)) scpdsi scpdsi Hungary y = a * e bx ; a avg = 4,40 b avg =-0,14 R 2 avg = 0,71

12 Regression between PaDI and scpdsi 20 PaDI 20 PaDI y = 3,0637e -0,1459x R 2 = 0, y = 2,9552e -0,1741x R 2 = 0, LENDAVA (SI) VELIKI DOLENCI (SI) 12 Expon. (LENDAVA (SI)) 12 Expon. (VELIKI DOLENCI (SI)) scpdsi scpdsi Slovenia y = a * e bx ; a avg = 2,55 b avg =-0,14 R 2 avg = 0,72

13 Regression between PaDI and maize yield Maize annual average yield, t/ha ( ) in Hungary, R 2 =0,78 PaDI annual average, ºC/100mm ( )

14 Regression between PaDI and maize yield Maize annual average yield, t/ha ( ) Bács-Kiskun county, R 2 =0,95 PaDI annual average, ºC/100mm ( )

15 PaDI 10% (Palfai Drought Index - frequency) Drought frequency, map of droughtness: - 10% probability of occurrence (log-pearson Type III Distribution) of PaDI, given from long data queue - expresses the climatic factor (geographical characteristic) of region drought intensity and frequency,

16 PaDI 10% (Palfai Drought Index - frequency) The 10% probability of occurrence of PaDI for SEE region (PaDI 10% ) PaDI 10% Drougtness Drougtness Probability of impacts (Risk * Impacts = Vulnerability)

17 PaDI forecast (early warning) PaDI 2007

18 PaDI forecast (early warning) Drought forecast in May 2007 In case of dry weather In case of average weather

19 PaDI forecast (early warning) Drought forecast in June 2007 In case of dry weather In case of average weather

20 PaDI forecast (early warning) Drought index in 2007

21 PaDI forecast (early warning) Drought forecast in April 2012 In case of dry weather In case of average weather

22 PaDI forecast (early warning) Drought forecast in May 2012 In case of dry weather In case of average weather

23 PaDI (Palfai Drought Index) Conclusions, suggestions: - Calculation, data processing and understanding of PaDI is easy - Expresses well crop decrease - Correlation between scpdsi and PaDI is good (R 2 >0,7) - PaDI and SPI 3 (for spring or summer) together expresses strength and reason of drought - Useful for medium-term forecast of drought - Practical for multi-decade data series analysis and mapping, for the assessment of the possible climate change scenarios regarding drought.

24 PaDI (Palfai Drought Index) Thank you for your attention! Arpad Herceg ATI-VIZIG, Szeged, Hungary

Nolan Doesken Colorado Climate Center

Nolan Doesken Colorado Climate Center Presented to: Colorado Cattleman s s Association, Pueblo, CO, June 19, 2006 http://ccc.atmos.colostate.edu Prepared by Odie Bliss 1 Let s s Talk About Precipitation