Abstract

Abstract. The objective of this paper is to present the multi-orbit (MO) surface soil moisture (SM) and angle-binned brightness temperature (TB) products for the SMOS (Soil Moisture and Ocean Salinity) mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS) makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD) compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD) using multi-angular dual-polarisation TB from MO. A subsidiary angle-binned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive) TB. The Level 3 SM V300 product is compared to the single-orbit (SO) retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM) are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an open licence and free of charge using a web application (https://www.catds.fr/sipad/). The RE04 products, versions 300 and 310, used in this paper are also available at ftp://ext-catds-cpdc:catds2010@ftp.ifremer.fr/Land_products/GRIDDED/L3SM/RE04/.

Highlights

  • Surface soil moisture (SM) is a control physical parameter for many hydrological processes like infiltration, runoff, precipitation and evaporation (Koster et al, 2004)

  • The level 3 daily maps of soil moisture and brightness temperatures are presented in this paper

  • The L3 angle-binned TB product is compared to Soil Moisture Active Passive (SMAP) brightness temperature maps at 40◦

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Summary

Introduction

Surface soil moisture (SM) is a control physical parameter for many hydrological processes like infiltration, runoff, precipitation and evaporation (Koster et al, 2004). Estimates of SM are needed for many applications concerned with monitoring droughts (Keyantash and Dracup, 2002), floods (Brocca et al, 2010; Lievens et al, 2015), weather forecast (Drusch, 2007; de Rosnay et al, 2013), climate (Jung et al, 2010) and agriculture (Guérif and Duke, 2000). It is identified among the 50 Essential Climate Variables (ECVs) for the Global Climate Observing System (GCOS). The SMOS Level 2 (L2) SM retrieval algorithm (Kerr et al, 2012) minimizes the squared differences between L-MEB (Wigneron et al, 2007) forward simulations of multi-angular dual-polarisation TB and corresponding SMOS measurements using the Levenberg– Marquardt optimisation algorithm to retrieve physical parameters, mainly SM and VOD

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