Local control on precipitation in a fully coupled climate-hydrology model

Abstract

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.The critical importance of realistically representing the complex interactions and hydrological feedback loops between the atmosphere and the land surface in climate models is well documented 1 . The ability to adequately simulate precipitation systems is often related to the horizontal grid scales resolved by the models 2 and their ability to account for non-linearity and the associated variability 3,4 . Also, this is highly dependent on a proper land surface representation as soil moisture acts as a control on water and energy fluxes from land surfaces to the atmosphere while humidity, temperature, wind, radiation and precipitation provides the drivers and input for the land-surface and subsurface water fluxes. In particular, on local to regional scales the models' ability to represent a wide range of complex physical processes at a very high spatial and temporal resolution is crucial for describing the spatio-temporal variability of precipitation 1,5,6 . Some improvements in modelling approaches and improved confidence in precipitation projections have been seen recently. These improvements include: (I) higher resolution spatio-temporal model scales with grid resolutions down to e.g. 1.5 km 7 , (II) improved physical schemes and parameterizations (including dynamical vegetation schemes 8 ) in climate models and the development of earth system models (ESMs) 9 , (III) better quality of forcing and evaluation data like the increased availability of high quality gridded data sets 10,11 and (IV) a continuing growth of computational power. That said even state-of-the-art regional climate models (RCMs), which operate at scales down to a few kilometres, still generally suffer from deficiencies in fully representing the hydrological feedback to the atmosphere from the land surface and sub-surface 12,13 . Excluding g...

Role of Lateral Terrestrial Water Flow on the Regional Water Cycle in a Complex Terrain Region: Investigation With a Fully Coupled Model System

“…Several coupled atmospheric‐hydrological modeling studies have shown the potential role of surface and subsurface lateral water flow on precipitation (e.g., Anyah et al, ; Arnault et al, ; Larsen, Christensen, et al, , Larsen, Højmark Rasmussen, et al, ; Maxwell et al, ; Rahman et al, ; Senatore et al, ; Wagner et al, ). Indeed, lateral terrestrial water flow redistributes soil moisture, which then potentially affects surface fluxes, atmospheric boundary layer condition, and finally precipitation.…”

“…Corsmeier et al () further described convective initiation as a two‐way interaction from larger and longer scales (e.g., upper tropospheric processes) down to smaller and shorter scales (e.g., boundary layer and soil‐surface driven processes) and vice versa. Larsen, Christensen, et al () showed that an enhanced treatment of subsurface hydrological processes in a climate model, for example, 3‐D groundwater flow, potentially improves the representation of seasonal precipitation.…”

“…The improved representation of runoff mechanisms and the ability of lateral water flow in Parflow‐WRF led to a different spatial pattern of land surface fluxes and affected atmospheric variables with relevance to wind energy applications. A series of works by Fan et al (), Miguez‐Macho et al (), Anyah et al (), Leung et al (), Shrestha et al (), Rahman et al (), Larsen, Christensen, et al (), Larsen, Højmark Rasmussen, et al (), and Wagner et al () have also explored the issue of atmospheric coupling to groundwater. Specifically, Anyah et al () applied the coupled regional climate‐hydrologic modeling system RAMS‐Hydro over North America to investigate the impact of water table dynamics on evapotranspiration ET and precipitation.…”

Full Coupling Between the Atmosphere, Surface, and Subsurface for Integrated Hydrologic Simulation

“…The southern regions in the blues and purples are grouped toward the right and middle section of the figure (deeper groundwater tables with positive LE difference). The influence of water table depth on latent heat fluxes across the land surface has been previously noted by Maxwell and Kollet (); Larsen et al ().…”

A Joint Soil‐Vegetation‐Atmospheric Water Tagging Procedure With WRF‐Hydro: Implementation and Application to the Case of Precipitation Partitioning in the Upper Danube River Basin

“…Recent studies showed that considering the horizontal transport of terrestrial water in a climate model has an impact on precipitation (e.g., Arnault, Wagner, et al, ; Arnault et al, ; Kerandi et al, ; Larsen et al, ; Maxwell et al, ; Rahman et al, ; Rummler et al, ; Senatore et al, ; Wagner et al, ; Zhang et al ). Indeed, spatially redistributing soil moisture modifies surface fluxes, which potentially affects boundary layer dynamics, convection initiation and precipitation (e.g., Pielke, ).…”