Influence of the Atlantic Multidecadal Oscillation and North Atlantic Oscillation Indices on Terrestrial Hydrology across the Continental United States using NCA-LDAS

Terrestrial hydrologic systems are affected by numerous factors ranging from local weather impacted by altitude, relief, soil, and vegetation to global scale climate regulated by seasonally varying coupled atmosphere and ocean patterns. This presentation evaluates the relationship of land surface water stores and fluxes across the continental United States (CONUS) to the Atlantic Multidecadal Oscillation index (AMO) and the North Atlantic Oscillation index (NAO) at regional and local scales using the hydrologic time series generated within the National Climate Assessment Land Data Assimilation System (NCA-LDAS) for the period 1980-2016. Important land hydrology state variables include multi-layer soil moisture and temperature, snow depth and water equivalent, and groundwater, while fluxes include precipitation, runoff, infiltration, evapotranspiration and sensible heat. NCA-LDAS employs the Noah-MP land surface model in assimilating satellite observations of several modeled variables including soil moisture, snow water equivalent and depth, groundwater, and Leaf Area Index over the 36-year period, using the NASA Land Information System. NCA-LDAS hydrology time series variables were developed for both data assimilation and non-data assimilation (open-loop) simulations, and each related to the AMO and NAO indices at various lags to understand regional and temporal scales of variability. Specific goals are i) to understand the extent to which the NAO and AMO relate to the hydrologic quantities including soil moisture, precipitation, snow, temperature, evapotranspiration, LAI, and runoff for different regions across CONUS at monthly lags, ii) to evaluate the impact of satellite data assimilation on the magnitude of those relationships and assess the ability of satellite observations to improve the capture of those relations, including extreme event periods, and iii) to evaluate their impact on the previously published 36-year hydrologic trend. The presentation will provide time series CONUS maps demonstrating the lagged relations that evolve for the various states and fluxes.