Abstract
Abstract. Vegetation optical depth (VOD) retrievals from passive microwave sensors provide analog estimates of above-ground canopy biomass. This study presents the development and analysis of assimilating VOD retrievals from X-, C-, and L-band passive microwave instruments within the Noah-MP land surface model over the Continental U.S. The results from this study demonstrate that the assimilation of VOD retrievals have a significant beneficial impact on the simulation of evapotranspiration and GPP, particularly over the agricultural areas of the U.S. The improvements in the water and carbon fluxes from the assimilation of VOD from X- and C-band sensors are found to be comparable to those obtained from the assimilation of vegetation indices from optical sensors. The study also quantifies the relative and joint impacts of assimilating surface soil moisture and VOD from the Soil Moisture Active Passive (SMAP) mission. The utility of soil moisture assimilation for improving evapotranspiration (ET) is more significant over water-limited regions, whereas VOD DA is more impactful over areas where soil moisture is not the primary controlling factor on ET. The results also indicate that the information on moisture and vegetation states from SMAP can be simultaneously exploited through the joint assimilation of surface soil moisture and VOD. Since passive microwave-based VOD retrievals are available in nearly all weather conditions, their use within data assimilation systems offers the ability to extend and improve the utility obtained from the use of optical/infrared-based vegetation retrievals.
Highlights
Remote sensing estimates of vegetation are typically developed by exploiting the relationship between the stomatal stress and the spectral reflectance of leaves and canopies (Knipling, 1970)
Since soil moisture is typically considered the primary retrieval from microwave remote sensing, we evaluate the relative benefits of assimilating both Soil Moisture Active Passive (SMAP) surface soil moisture and Vegetation optical depth (VOD) retrievals
The impact of assimilating VOD retrievals on the simulated ET estimates is shown in Fig. 3, which shows the change in RMSE and correlation (R) of ET in the DA simulation relative to the OL
Summary
Remote sensing estimates of vegetation are typically developed by exploiting the relationship between the stomatal stress and the spectral reflectance of leaves and canopies (Knipling, 1970). Most studies to date have focused on the assimilation of LAI retrievals to improve the characterization of vegetation biomass, evapotranspiration, root zone soil moisture, and CO2 fluxes within land surface models (Sabater et al, 2008; Barbu et al, 2011, 2014; Albergel et al, 2017, 2018; Fox et al, 2018). As the use of all-weather VOD measurements from microwave sensors provides the opportunity to extend the spatial and temporal coverage of vegetation observations into overcast and clouded conditions, here we examine the influence of assimilating VOD retrievals from microwave radiometry. The L-band measurements provide more sensitivity to deeper soil moisture and canopy layers To our knowledge, this is one of the first reported studies of continental-scale assimilation of VOD retrievals within.
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