Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales
Abstract
:1. Introduction
2. Data
2.1. Streamflow Data
2.2. Climate Indices
3. Methods
3.1. PC-Wavelet
3.2. Wave-Clust
Wavelet Analysis
3.3. Diagnostic Analysis of the Role of Low Frequency Climate Variation
3.3.1. Correlation Analysis
3.3.2. Linear Regression with Regularization and Variable Selection
3.3.3. Non-Linear Regression
4. Results
4.1. Diagnosis of Low Frequency Variations and Space-Time Signatures for the ORB
4.2. Diagnosis of Relations with Climate Indices
4.2.1. Correlation Analysis
4.2.2. Linear Regression
4.2.3. Non-Linear Regression
5. Summary
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
References
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Amonkar, Y.; Doss-Gollin, J.; Lall, U. Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales. Hydrology 2023, 10, 67. https://doi.org/10.3390/hydrology10030067
Amonkar Y, Doss-Gollin J, Lall U. Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales. Hydrology. 2023; 10(3):67. https://doi.org/10.3390/hydrology10030067
Chicago/Turabian StyleAmonkar, Yash, James Doss-Gollin, and Upmanu Lall. 2023. "Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales" Hydrology 10, no. 3: 67. https://doi.org/10.3390/hydrology10030067
APA StyleAmonkar, Y., Doss-Gollin, J., & Lall, U. (2023). Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales. Hydrology, 10(3), 67. https://doi.org/10.3390/hydrology10030067