Quantification of large-scale hydroclimatic patterns from observational data

(hydrosphere) water balances, land-atmosphere interactions, and hydroclimatic hazards. Such essential co-variation patterns still remain largely unknown over large scales and in different climates around the world. To contribute to bridging this large-scale knowledge gap, we synthesize and decipher different data time series over the period 1980-2010 for 6405 hydrological catchments around the world. From observation-based data, we identify dominant large-scale co-variation patterns between main freshwater fluxes and soil moisture (SM) for different world parts and climates.

These co-variation patterns are also compared with those obtained from reanalysis products and Earth System Models (ESMs). The observation-based datasets robustly show the strongest large-scale hydrological co-variation relationship to be that between SM and runoff (R), consistently across the study catchments and their different climate characteristics. The predominantly strongest large-scale SM-R co-variation relationship, however, is also the most misrepresented by ESMs and reanalysis products, followed by that between precipitation and R. Comparison between corresponding observation-based and ESM results also shows that an ESM may perform well for individual hydrological variables, but still fail in representing the patterns of large-scale co-variations between variables.

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Taxonomy

• Modeling
• Hydrological Modelling
• Analytics & Modeling
• Hydrological modelling of climate change

1 Comment

1. This study is aimed at: (1) creating a deeper understanding of large-scale interconnections and relationships between key hydroclimatic variables based on observational data and (2) encouraging hydrologists to collaborate more closely with the earth system model (ESM) developers to enhance hydrological representations of ESMs. 
   
   Here are the main highlights from this study:

   - Soil moisture-runoff (along with precipitation-runoff) is the most strongly correlated variables while also being the most misrepresented in reanalysis and #ESMs
   - The closest large-scale co-variations of studied freshwater fluxes and storages in different climates are between soil moisture and runoff
   - Commonly expected blue-water precipitation-runoff and green-water precipitation-evapotranspiration co-variations are overall weaker
   - Models can perform well in simulating individual variables but fail to simulate co-variations between the same variables with considerable errors