Future extreme precipitation events in the Southwestern US: climate change and natural modes of variability

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1 Future extreme precipitation events in the Southwestern US: climate change and natural modes of variability Francina Dominguez Erick Rivera Fernandez Hsin-I Chang Christopher Castro AGU 2010 Fall Meeting

2 The goal of this work is to investigate how climate change will affect the intensity of precipitation in the western US. Regions where disproportionate changes in heavy and very heavy precipitation during the past decades were documented as either an increase (+) or decrese (-) compared to the change in the annual and/or seasonal precipitation (updated from Groisman et al, 2005), taken from Trenberth et al. (2007) Recent work has shown that the intensity of extreme precipitation events in the NH has increased. This has many important implications for many areas including urban infrastructure.

3 We use a regional climate modeling framework to address issues of non-stationarity and capture the physical mechanisms of extreme rainfall events. GCM data Regional Climate Model (WRF) Test how the RCM performs using ideal boundary conditions. Historical (Reanalysis) Physically based - Regional Scale Future Projections (IPCC) Future climate projections using different models/emission scenarios. We use a 112-year continuous simulation using WRF forced at it s lateral boundaries with HadCM3 A2 data.

4 From this WRF-HadCM3 112-year simulation we will present two analyses: 1. Analysis of extreme precipitation events 2. ENSO relationship to precipitation in the SW

5 We use a Poisson GP model to characterize the statistical distribution of extreme events. (Katz et al. 1999, 2002, 2010). We don t use GEV theory because it is limited to block maxima, and we would loose information. Katz, Climatic Change 2010 Consists of a Poisson process to model the occurrence of an exceedance of a high threshold and a generalized Pareto (GP) distribution to model the excess over the threshold.

6 WRF-downscaling shows a realistic characterization of the climatology of precipitation and of the intense events. Observed Precipitation WRF-Reanalysis II Precipitation WRF-UKMO HadCM3 Precipitation The spatial pattern of precipitation and the magnitude is realistically captured for both winter and summer. WRF-downscaled rainfall seems to be biased high in both Reanalysis and UKMO-HadCM3

7 WRF-Reanalysis II shows an impressive ability to capture individual cool-season events. Summer season convective storms are much more difficult to capture, and show decreased skill.

8 In the future, we see a generalized increase in the intensity of extreme events in the winter season. Pattern is very heterogeneous, with distinct regions of significant increases.

9 WRF-HadCM3 SST 3-month anomalies are used to calculate the model ENSO-index (shown for ) Feb 73 Jun 81 Oct 89 Feb 98 Monthly SST temperature (HADcm3) Regional average Monthly climatology (currently ) Calculate 3-month SST anomaly (DJF, JFM, etc). Identify the SST anomalies into El Nino (>0.5 C), La Nina (<0.5 C) and Neutral. Following Trenberth 1997 and CPC website.

10 HADcm3 SST 3 month anom ( ), calculation following Trenberth 1997, and CPC website (blue: La Nina; red: El Nino; black: Neutral) NDJ DJF JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND

11 Correlations between WRF-HadCM3 SST anomalies vs. monthly precipitation anomalies in the Salt-Verde show positive winter negative summer relations ( ) month SST anom vs 1-month precip (monthly) Corr. coef OND NDJ DJF JFM FMA MAM AMJ MJJ JJA JAS ASO SON Salt Verde This has been shown in the literature using observed data (Castro et al. 2001).

12 Daily precipitation Salt River Basin shows a future increase in very intense events associated to climate change. Nino Nina Neutral Non-parametric significance test shows that the in the period, El Nino events are associated with the higher values of rain (99% significant) and La Nina with lower (99%).

13 In Conclusion - Model Validation 1 WRF Downscaled HadCM3 data show a realistic climatology when compared to observations. The model is biased high. 2 Extreme events for the Salt-Verde basins are captured by the WRF- Reanalysis II simulations for all but the summer season

14 In Conclusion Future Projections 3 We see a generalized increase in extreme events throughout the region, and the patterns are closely tied to topography. 4 The model shows that extreme events in the future will have a higher probability of occurrence during ENSO years.

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