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ATMO 529 Class Project Presentation Seshadri Rajagopal

Causes for Persistence in Inter Annual Variability of 3 Layer Soil Moisture Estimates in the Colorado River Basin. ATMO 529 Class Project Presentation Seshadri Rajagopal. Motivation. Soil moisture plays an important role in land- atmosphere interactions at a variety of time scales

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ATMO 529 Class Project Presentation Seshadri Rajagopal

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  1. Causes for Persistence in Inter Annual Variability of 3 Layer Soil Moisture Estimates in the Colorado River Basin ATMO 529 Class Project Presentation Seshadri Rajagopal ATMO 529

  2. Motivation • Soil moisture plays an important role in land- atmosphere interactions at a variety of time scales • Similar to SST it is a slow changing variable. In other words there is a persistence in SM • Distributed observations of soil moisture are rare to find • Most of the analysis is performed on GCM based assimilated values or from Hydrologic models ATMO 529

  3. Background • VIC is a hydrologic model that solves for full water and energy balance • Takes basic atmospheric variables such as temperature, precipitation, wind speed etc as inputs • Apart from other output it generates, for current purpose I use the soil moisture values ATMO 529

  4. Perform correlation analysis Perform SVD analysis on the soil moisture data to identify dominant modes of variability Perform REOF analysis to identify regionalized patterns Testable Hypothesis Layer 1 soil moisture will show variability similar to the ENSO index, whereas in the deeper layers (2, 3) due to persistence will correlate better to the PDO signal The spatial patterns of will indicate a higher dominance of PDO in the upper basin, and higher dominance of ENSO in the lower basin Tasks ATMO 529

  5. Correlation Analysis – Layer 1SM and Nino3 ATMO 529

  6. Correlation Analysis – Layer 1SM and PDO ATMO 529

  7. Correlation Analysis – Layer 2SM and Nino3 ATMO 529

  8. Correlation Analysis – Layer 2SM and PDO ATMO 529

  9. Correlation Analysis – Layer 3SM and Nino3 ATMO 529

  10. Correlation Analysis – Layer 3SM and PDO ATMO 529

  11. Layer 1 SM PC1 and Nino3 Var Explained = 47% ATMO 529

  12. PC1 time-series and Nino3 R = 0.47 R = 0.31 R = 0.19 ATMO 529

  13. Layer 1 SM PC1 and PDO ATMO 529

  14. Layer 1 SM REOF 1 & 2 and Nino3 ATMO 529

  15. Layer 3 SM PC1 and PDO Var Explained = 33% ATMO 529

  16. PC1 time-series and PDO R = 0.52 R = 0.57 R = 0.52 ATMO 529

  17. Layer 3 REOF 1 & 2 and PDO ATMO 529

  18. Summary • Nino3 is more influential on layer 1 soil moisture • This make intuitive sense as the top layer soil moisture will follow an annual cycle (similar to the precipitation cycle) • Layer 3 soil moisture follows similar cycles as the PDO • This indicates that there is more hydrologic memory in the deep layer soil moisture. ATMO 529

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