Trends in daily rainfall erosivity in relation with NAO, MO and WeMO for NE Spain, during the period 1955-2006.Marta Angul...
Outline  Introduction:       - What’s rainfall erosivity?       - How to measure it       - Database creation       - Stud...
The rainfall erosivity factor in soil erosion (EI)Measures the rainfall energy or the ability of rainfall to erode soil.Cl...
Measuring and modelling rainfall erosivity                                                                                ...
Measuring rainfall kinetic energy er and splash      Workshop “Non-stationary extreme value modelling in climatology” Febr...
Relationships between kinetic energy (er) and intensity Logarithmic functions      Ek = a + b log I Power-law functions   ...
Daily Rainfall Erosivity Model   1 n j             m                                                                      ...
Daily Rainfall Erosivity databases spatial distribution       Workshop “Non-stationary extreme value modelling in climatol...
Daily Rainfall Erosivity vs. Rainfall (month by month)      Workshop “Non-stationary extreme value modelling in climatolog...
Trends in rainfall erosivity in relation with NAO, MO &WeMOStudy case:Trends in rainfall erosivity at NE Spainduring the p...
Rainfall erosivity trends at annual scale       Workshop “Non-stationary extreme value modelling in climatology” February ...
Rainfall erosivity trends at seasonal scale      Workshop “Non-stationary extreme value modelling in climatology” February...
Rainfall erosivity trends at seasonal scale      Workshop “Non-stationary extreme value modelling in climatology” February...
Temporal evolution of rainfall erosivity quintileoccurrence       Workshop “Non-stationary extreme value modelling in clim...
Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events.       Workshop “Non...
Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events.       Workshop “Non...
Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events.       Workshop “Non...
Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events.       Workshop “Non...
Could be these trends related with atmospheric mechanisms and teleconnection patterns evolution?The characteristics of the...
Main atmospheric teleconnection patterns affecting theclimate of the study area      Workshop “Non-stationary extreme valu...
Teleconnection indices circulation patterns in positive       (above) and negative (beneath) phaseNAO+                    ...
Are teleconnection indices phases influencing daily  rainfall erosivity? Differences in daily rainfall erosivity, negative...
NAO influencing daily rainfall erosivityRelative difference of average daily rainfall erosivity of negative NAO days with ...
MO influencing rainfall erosivityRelative difference of average daily rainfall erosivity of negative MO days with respect ...
WeMO influencing rainfall erosivityRelative difference of average daily rainfall erosivity of negative WeMO days with resp...
Analysis of the probability of occurrence of extreme dailyrainfall erosivity records associated to negative and positivete...
Temporal evolution of atmospheric teleconnectionindices and of rainfall erosivity quintile occurrence       Workshop “Non-...
Conclusions  Rainfall erosivity has decreased in the NE of the Iberian  peninsula during the last 55 years  Decrease occur...
Contact details:Estación Experimental Aula Dei – CSIC, Zaragoza (ESPAÑA)/Departamento de Suelo yAguaMarta Angulo-MartinezP...
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Trends in daily rainfall erosivity in relation with NAO, MO and WeMO for Spain, 1955-2006

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Trends in daily rainfall erosivity in relation with NAO, MO and WeMO for Spain, 1955-2006

  1. 1. Trends in daily rainfall erosivity in relation with NAO, MO and WeMO for NE Spain, during the period 1955-2006.Marta Angulo-MartinezPhD studentEstación Experimental Aula Dei-CSIC,Zaragoza, EspañaWorkshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012
  2. 2. Outline Introduction: - What’s rainfall erosivity? - How to measure it - Database creation - Study area Trends in rainfall erosivity at NE Spain, 1955-2006 Analysis of the relationship between some teleconnection patterns and rainfall erosivity Influence of the atmospheric teleconnection patterns evolution in explaining rainfall erosivity trends Conclusions Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  3. 3. The rainfall erosivity factor in soil erosion (EI)Measures the rainfall energy or the ability of rainfall to erode soil.Climate dynamics andrainfall genetic mechanisms Splash erosion & runoff erosion Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  4. 4. Measuring and modelling rainfall erosivity Where:Empirical models: vr = Rainfall volume;Universal Equation for Soil Erosion (R)USLE I30 = Maximum intensity in 30 min; er = Unit rainfall energy. m 1 n j  o R = ∑∑ ( EI 30 ) k EI = EI 30 =  ∑ er vr  I 30 Empirically estimated with n j =1 k =1  r =1  data from US er = 0.29 [1 − 0.72 exp( −0.05ir )]Limitations:- High resolution temporal data (15’) Other empirical equations- Empiricism Cerro et al. (1998); Barcelona, Spain Depends on the physics of rainfall and er ( Cr ) = 0.384 [1 − 0.538 exp( −0.029ir )] climate dynamics. Depends on the physico-chemical characteristics of the soil Van Dijk et al. (2002); Universal er (VD ) = 0.283 [1 − 0.52 exp( −0.042ir )] Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  5. 5. Measuring rainfall kinetic energy er and splash Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  6. 6. Relationships between kinetic energy (er) and intensity Logarithmic functions Ek = a + b log I Power-law functions Ek = a I b Exponential functionsEK = emax [1 − a exp (−b I )]USLE proposaler = 0.29 [1 − 0.72 exp( −0.05ir )] Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  7. 7. Daily Rainfall Erosivity Model 1 n j m DatabasesR = ∑∑( EI 30 ) k n j =1 k =1 110 rainfall series 15’ time resolution  o EI = EI 30 =  ∑ er vr  I 30 EI m = am P bm + ε Period 1997-2006  r =1  156 rainfall serieser = 0.29 [1 − 0.72 exp( −0.05ir )] Daily time resolution Period 1955-2006 R factor estimated MJ mm ha-1h-1 y-1 R factor observed MJ mm ha-1h-1 y-1 Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  8. 8. Daily Rainfall Erosivity databases spatial distribution Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  9. 9. Daily Rainfall Erosivity vs. Rainfall (month by month) Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  10. 10. Trends in rainfall erosivity in relation with NAO, MO &WeMOStudy case:Trends in rainfall erosivity at NE Spainduring the period 1955-2006 in relationwith NAO, MO & WeMO Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  11. 11. Rainfall erosivity trends at annual scale Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  12. 12. Rainfall erosivity trends at seasonal scale Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  13. 13. Rainfall erosivity trends at seasonal scale Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  14. 14. Temporal evolution of rainfall erosivity quintileoccurrence Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  15. 15. Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  16. 16. Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  17. 17. Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  18. 18. Rainfall erosivity trends at daily scale; evolution of theoccurrence in low (Q1) and high (Q5) events. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  19. 19. Could be these trends related with atmospheric mechanisms and teleconnection patterns evolution?The characteristics of the rainfall erosivity events—Drop Size Distribution, KineticEnergy, Intensity and Duration—depend on the type of rainfall event (Van Dijket al. 2002), and in the meteorological and climatic characteristics involved in thegeneration of the type of rainfall event: The leading atmospheric circulation patterns Sea level pressure fields Temperature contrasts between high and low atmospheric layers Humidity percentage in the air masses Wind flows Geographical factors Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  20. 20. Main atmospheric teleconnection patterns affecting theclimate of the study area Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  21. 21. Teleconnection indices circulation patterns in positive (above) and negative (beneath) phaseNAO+ MO+ WeMO+NAO- MO- WeMO- Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  22. 22. Are teleconnection indices phases influencing daily rainfall erosivity? Differences in daily rainfall erosivity, negative and positive atmospheric teleconnection indices phases Positive events = daily indices > 0.5 sd Negative events = daily indices < -0.5 sd Relative difference of average daily rainfall erosivity of negative NAO days with respect to positive NAO days. EIdif = (EINAO- - EINAO+) / EINAO+ where EINAO- (EINAO+) is the average daily rainfall erosivity of negative (positive) NAO daysStatistical significance checked by the Wilcoxon-Mann-Whitney testmonth by month. Significance level α=0.05 Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  23. 23. NAO influencing daily rainfall erosivityRelative difference of average daily rainfall erosivity of negative NAO days with respect to positive NAO days (MJ mm ha-1 h-1 y-1 (MJ mm ha-1 h-1 y-1)-1). Shaded areas indicate not significant difference between positive and negative NAO phases. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  24. 24. MO influencing rainfall erosivityRelative difference of average daily rainfall erosivity of negative MO days with respect to positive MO days (MJ mm ha-1 h-1 y-1 (MJ mm ha-1 h-1 y-1)-1). Shaded areas indicate not significant difference between positive and negative MO phases. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  25. 25. WeMO influencing rainfall erosivityRelative difference of average daily rainfall erosivity of negative WeMO days with respect to positive WeMOdays (MJ mm ha-1 h-1 y-1 (MJ mm ha-1 h-1 y-1)-1). Shaded areas indicate not significant difference betweenpositive and negative WeMO phases. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  26. 26. Analysis of the probability of occurrence of extreme dailyrainfall erosivity records associated to negative and positiveteleconnection indices phase Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  27. 27. Temporal evolution of atmospheric teleconnectionindices and of rainfall erosivity quintile occurrence Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  28. 28. Conclusions Rainfall erosivity has decreased in the NE of the Iberian peninsula during the last 55 years Decrease occurs at annual and seasonal scale, though little increase occurs at summer and autumn Decrease is explained by a reduction in the high and extreme rainfall erosivity events occurrence , whilst low events have increased. This evolution seems related with positive trends in the atmospheric teleconnection indices: NAO, MO and WeMO. Workshop “Non-stationary extreme value modelling in climatology” February 15-17, 2012; Technical University of Liberec
  29. 29. Contact details:Estación Experimental Aula Dei – CSIC, Zaragoza (ESPAÑA)/Departamento de Suelo yAguaMarta Angulo-MartinezPhD StudentEmail: mangulo@eead.csic.es Thanks!

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