Understanding the impact of vegetation dynamics on the water cycle in the Noah-MP model

Abstract

The impact of extreme climate events, especially prolonged drought, on ecosystem response, can influence the land-atmosphere interactions and modify local and regional weather and climate. To investigate the impact of vegetation dynamics on the simulation of energy, water, and carbon exchange at the land surface and streamflow, especially during drought conditions, we compared the performance of multiple versions of the Noah- multiparameterization (MP) land surface model (both Noah-MP LSM, version 3.6 and 4.0.1) with default configurations as well as various vegetation physics options, including the dynamic or input leaf area index (LAI) and the fractional vegetated area (FVEG). At the site level, simulated water and energy fluxes from each version were compared to eddy covariance (EC) flux tower measurements and remote sensing data from Moderate-Resolution Imaging Spectroradiometer (MODIS) at well-characterized natural grassland sites in Kansas from 2008 to 2018. The ability of each version to reproduce annual mean river flows was compared to gauged observations at United States Geological Survey (USGS) stations over 11 years (2008–2018). Model performance in replicating spatial patterns during extreme events was assessed by comparing simulated soil moisture (SM) percentiles over the state of Kansas to the U.S. Drought Monitor (USDM). Results from these comparisons indicate that (a) even though there were differences in the latent heat (LE) components (i.e., transpiration, canopy evaporation, and soil evaporation), the total LE is mostly insensitive to variations in LAI across all model versions. This indicates that the incoming net radiation limits the total evaporation, as the presence of adequate soil moisture allows for higher soil evaporation when LAI limits transpiration; (b) regardless of the model version, the force of the precipitation largely dictates the accuracy of evapotranspiration (ET) simulation; (c) Overestimation of LE resulted in underestimation of streamflow, particularly over the land surface type dominated by a combination of grasses and cropland in the western and central part of the state; (d) all of the tested Noah-MP 4.0.1 vegetation physics produced spatial patterns of drought that more closely matched the USDM as compared to version 3.6. These findings have important relevance for applications of large-scale ecosystem-atmosphere feedbacks in water, carbon, and energy exchange.

Implementation of global soil databases in NOAH-MP model and the effects on simulated mean and extreme soil hydrothermal changes

“…Due to its simplicity in selecting and combining multi-physics options, the model has been widely used for different applications, including natural hazards, drought and wildfire monitoring, land-atmosphere interactions, sensitivity and uncertainty quantification, biogeochemical processes, water dynamics, dynamic crop growth modeling, and soil hydrothermal processes. (Zhuo et al, 2019;Kumar et al, 2020;Chang et al, 2022;Hosseini et al, 2022;Nie et al, 2022;Warrach-Sagi et al, 2022;Hu et al, 2023).…”

“…However, accurate descriptions of soil properties in LSMs are difficult to obtain due to the limited availability of high resolution global-scale soil texture measurements or lack of regionally specific measured soil properties (e.g. Kishné et al 2017;Dennis and Berbery, 2021;2022). This represents a key limitation and is a source of model uncertainty in current LSMs (Li et al, 2018), and consequently weather and climate models.…”

“…As an alternative approach, new state-of-the-art global soil information datasets are being explored to constrain and improve the representation of soil processes within LSMs (e.g. de Lannoy et al, 2014;Shangguan et al, 2014;Hengl et al, 2017;Looy et al, 2017;Dennis and Berbery, 2021;2022;Xu et al, 2023). For some LSMs, soil hydrothermal properties can be estimated from a set of equations known as PedoTransfer Functions (PTFs) that require information on soil composition such as sand, silt and clay composition and organic matter (Looy et al, 2017;Dai et al, 2019a,b).…”

“…Clearly, the existing PTFs vary in complexity. Thus, the choice of PTFs partly depends on the availability of inputs (Weihermüller et al 2021) and has been reported to impact soil moisture simulations, with consequent effects on the surface energy and water fluxes, land-atmosphere coupling, atmospheric moisture budget, boundary layer evolution and regional climate (Dennis and Berbery, 2021;2022;Weihermüller et al 2021;Xu et al, 2023;Zhang et al, 2023). Moreover, as soil moisture affects land-atmosphere interactions largely through its control on the evaporative fraction (e.g.…”

“…albedo, surface roughness length, etc.) and meteorological forcing (Arsenault et al, 2018;Hosseini et al, 2022). The first effort to implement SoilGrids in NOAH-MP LSM was recently evaluated over Southern Africa (Zhang et al, 2023).…”