Bodo Bookhagen. Deciphering Climatic Extreme events with Complex Networks in South America

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1 Deciphering Climatic Extreme events with Complex Networks in South America Bodo Bookhagen Geography Department and Earth Research Institute UC Santa Barbara

2 Climatic Extreme Events in South America 1. Climate of South America and the South American Monsoon System 2. Linkages between Climate and Erosion Exploring the impact of a steep rainfall-gradient on sediment-transport processes Understanding and quantifying spatial variations in erosion rates

3 Topography and Mean Annual Rainfall

4 Mean Daily Rainfall (TRMM 3B42 V7, ) Bookhagen and Strecker, 2010; Bookhagen (in review); Boers et al. (in review)

5 Mean Daily Rainfall (TRMM 3B42 V7, ) Bookhagen and Strecker, 2010; Bookhagen (in review)

6 Mean Daily Rainfall (TRMM 3B42 V7, ) 90 th percentile 90 th percentile Bookhagen and Strecker, 2010; Bookhagen (in review)

7 90 th / 50 th Percentile for Daily Rainfall Ratio of 90 th /50 th percentile for each pixels. 15 years of data Low ratios indicate a narrow rainfall distribution High ratios indicate a heavy-tail rainfall distribution Bookhagen (in review)

8 General Extreme Value Distribution: Shape Parameter Fitting of the General Extreme Value (GEV) distribution for each individual pixel. Shape (k) parameters describes tail of the distribution. Higher k values indicate heavier tails Bookhagen (in review)

9 90 th and 95 th percentile Daily Rainfall (TRMM 3B42 V7, ) Bookhagen and Strecker, 2010; Boers et al., 2013

10 Complex Network Measures: Building the network 1 define events for a rainfall time series at the each grid point (e.g., at the 90 th percentile) calculate event synchronizati on matrix Q ij and delay direction matrix q ij. Malik et al. (2011)

11 Complex Network Measures: Building the network 2 define events for a rainfall time series at the each grid point (e.g., at the 90 th percentile) calculate event synchronizati on matrix Q ij and delay direction matrix q ij. Malik et al. (2011)

12 Complex Network Measure: Degree Centrality Degree centrality for the rainy season (DJF) from TRMM3B42 (V7) for rainfall events above the 90 th Percentile. At each grid point, we count the number of synchronous links: high values indicate locations where rainfall occurs simultaneously with many other locations within τ max = 7 days (or other delays). Boers et al., 2013

13 Complex Network Measure: Betweenness Centrality (BC) Using concept of shortest geodesic paths in the CN, which are the shortest sequences of links leading from one grid point to another. For given grid points i, j, and k we first calculate the ratio of the number of shortest CN paths between j and k, which pass i, and the total number of shortest CN paths between j and k. BC at grid point i is then defined as the sum of these ratios over all j and k. If a grid point lies on many shortest paths between any pairs of grid points, its BC will be high and we interpret it to be important for the propagation of extreme rainfall events, in particular over large spatial distances. Boers et al.,2013

14 Complex Network Measure: Mean Geographical Distance (MD) mean geographical distance (MD) of the connections at a grid point We use this measure to estimate the spatial scales at which a grid point is connected to other regions. Areas with high MD are thus likely to be part of teleconnection patterns. Boers et al.,2013

15 Complex Network Measure: Mean Geographical Distance (MD) mean geographical distance (MD) of the connections at a grid point We use this measure to estimate the spatial scales at which a grid point is connected to other regions. Areas with high MD are thus likely to be part of teleconnection patterns. Boers et al.,2013

16 Complex Network Measure: Clustering Coefficient (CC) clustering coefficient (CC) is defined as the relative frequency of pairs of CN neighbors of this grid point that are CN neighbors themselves A region with high CC is interpreted to exhibit rather large spatial coherence. High CC serves as an indicator for MCS activity. Boers et al.,2013

17 Complex Network Measure: Long Ranged Directedness (LD) 1 LD: calculating the normalized ranks of BC (NRBC), MD (NRMD) and CC (NRCC), we put LD = ½ NRBC + ½ NRMD NRCC. Low values indicate areas where extreme rainfall occurs regionally coherently as e.g. in MCS, while high values indicate areas where extreme rainfall prop- agates on narrow transport routes over large spatial distances, as e.g. along the eastern Andes slopes. Boers et al.,2013

18 Complex Network Measure: Long Ranged Directedness (LD) 2 LD of events >95 th compared to >90 th percentile: Increase of 95 th LD (red) along the eastern Andean slopes, in the SACZ, and at the outlet of the Amazon R. Decrease of 95 th LD (blue) in the La Plata Basin, in eastern Paraguay Atmospheric Interpretation synchronizations along different moisture pathways: The main pathway for the large-scale moisture transport from the Amazon Basin along the eastern Andes slopes towards the subtropics is substantially less pronounced for events above the 95th percentile, while the role of the SACZ is strongly enhanced Boers et al.,2013

19 Complex Network Measure: Directed Networks and source regions Number of links from any other gridpoint into the internally drained Alitplano and Puna de Atacama Plateaus We interpret the spatial distribution of this link intensity as an indicator for the source regions. Boers et al.,2013

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