Surface moisture and temperature trends anticipate drought conditions linked to wildfire activity in the Iberian Peninsula

17 pages, 5 figuresIn this study, drought conditions involving risk of fires are detected applying SMOS-derived soil moisture data and land surface temperature models. Moisture-temperature (SM-LST) patterns studied between 2010 and 2014 were linked to main fire regimes in the Iberian Peninsula. Most wildfires burned in warm and dry soils, but the analysis of pre-fire conditions differed among seasons. Absolute values of SM-LST were useful to detect prone-to-fire conditions during summer and early autumn. Complementarily, SM-LST anomalies were related to droughts and high fire activity in October 2011 and February-March 2012. These episodes were coincident with abnormally anticyclonic atmospheric conditions. Results show that combined trends of new soil moisture space-borne data and temperature models could enhance fire risk assessment capabilities. This contribution should be helpful to face the expected increase of wildfire activity derived from climate changeThis study was funded by the Spanish government through the project PROMISES: Productos y servicios innovadores con sensores de microondas, SMOS y Sentinels para tierra (ESP2015-67549-C3-1-R), and the pre-doctoral grant Ayudas para contratos predoctorales para la Formación de Doctores, with reference BES-2013-066240. This work was also supported by the European Regional Development Fund (ERDF). Additional funding came to the second author from Fundación BBVAPeer Reviewe

A new empirical model of sea surface microwave emissivity for salinity remote sensing

SMOS (Soil Moisture and Ocean Salinity) is a European Space Agency mission that aims at generating global ocean salinity maps with an accuracy of 0.1 psu, at spatial and temporal resolution suitable for climatic studies. The satellite sensor is an L-band (1400-1427 MHz) aperture synthesis interferometric radiometer. Sea surface salinity (SSS) can be retrieved since the brightness temperature of sea water is dependent on the frequency, angle of observation, dielectric constant of sea water, sea surface temperature and sea surface state. This paper presents a new empirical sea water emissivity model at L-band in which surface roughness effects are parameterized in terms of wind speed and significant wave height. For the SMOS mission these parameters can be obtained from external measurements and model diagnostics. An analysis has been done on the effect on SSS retrieval of different sources for this auxiliary information. Copyright 2004 by the American Geophysical UnionThis study was funded by ESA-ESTEC under WISE (14188/00/NL/DC) and EuroSTARRS (15950/02/NL/SF) contracts, and by the Spanish National Program on Space Research under grant ESP2001-4523-PEPeer Reviewe

Impact of day/night time land surface temperature in soil moisture disaggregation algorithms

18 pages, 5 figures, 1 tableSince its launch in 2009, the ESA’s SMOS mission is providing global soil moisture (SM) maps at ~40 km, using the first L-band microwave radiometer on space. Its spatial resolution meets the needs of global applications, but prevents the use of the data in regional or local applications, which require higher spatial resolutions (~1-10 km). SM disaggregation algorithms based generally on the land surface temperature (LST) and vegetation indices have been developed to bridge this gap. This study analyzes the SM-LST relationship at a variety of LST acquisition times and its influence on SM disaggregation algorithms. Two years of in situ and satellite data over the central part of the river Duero basin and the Iberian Peninsula are used. In situ results show a strong anticorrelation of SM to daily maximum LST (R≈0.5 to -0.8). This is confirmed with SMOS SM and MODIS LST Terra/Aqua at day time-overpasses (R≈-0.4 to -0.7). Better statistics are obtained when using MODIS LST day (R≈0.55 to 0.85; ubRMSD≈0.04 to 0.06 m/m) than LST night (R≈0.45 to 0.80; ubRMSD≈0.04 to 0.07 m/m) in the SM disaggregation. An averaged ensemble of day and night MODIS LST Terra/Aqua disaggregated SM estimates also leads to robust statistics (R≈0.55 to 0.85; ubRMSD≈0.04 to 0.07 m/m) with a coverage improvement of~10-20 %This work was supported by the Spanish Ministry of Economy and Competitiveness, through a Formación Personal Investigador (FPI) grant BES-2011-043322, the project PROMISES: ESP2015-67549-C3, ERDF (European Regional Development Fund) and the BBVA foundationPeer Reviewe

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 1 pageSoil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA’s Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth’s surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona’s fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide ’memory’ in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to droughtPeer Reviewe

La Misión de oportunidad SMOS de la serie Earth Explorer. Radiometría por síntesis de apertura para la medida de la humedad del suelo y la salinidad del océano

Desde medi ados de los años 80, di versas Agencias Espaciales han prestado una atención a los ll amados radiómetros interferométricos por síntesis de apertura. Estos in strumentos ofrecen por primera vez un salto cuantitativo importante en resolución espac ial como para permitir monitorizar la superfi cie terrestre a frecuencias bajas de microondas (banda L). En esta banda de frecuencias (1.4 GHz) existe la máxima sensibilidad de la temperatura de brillo tanto a la humedad del terreno, como a la salinidad del océano. En los radiómetros clásicos, la resolución espacial viene dada por el ancho de haz de la antena que, al ser escaneada, forma la imagen de temperatura de brillo. Por ello, para alcanzar la resolución espacial deseada (30-50 km como máximo, 10-20 km ideal) 'desde un satélite en órbita baja, las antenas requeridas tienen unas dimensiones inaceptablemente grandes: entre 10 y 20 metros de diámetro. Durante los años 90, la Agencia Europea del Espacio (ESA) llevó a cabo una serie de estudios tecnológicos con vistas a desarrollar un radiómetro por síntesis de apertura bidimensional en banda L. A este proyecto se le llamó MIRAS (Microwave Imaging Radiometer by Aperture Synthesis). En Noviembre de 1998, la mi sión SMOS (Soil Moisture and Ocean Salinity) basada en el concepto derivado de los estudios del proyecto MIRAS, fue propuesta como respuesta a un anuncio de «Misiones de Oportunidad Earth Exploren) lanzado por la ESA [1). En Mayo de 1999, después de un proceso de selección de 27 propuestas, la ESA aprobó la mi sión SMOS en segundo lugar para una fase A extendida. Este artículo describe brevemente la moti vación de esta misión , los principios de funcionamiento de dicho in strumento y las actividades en las que ha participado y participa un grupo de profesores del Departament de Teoria del Senyal i Comunicacions, de la Universitat Politecnica de Catalunya.Peer Reviewe

Remote Sensing as a Tool for Agricultural Drought Alert Over the South Region of Brazil

In this study the estimative of the Combined Drought Index (CDI) to identify agricultural drought over Southern Brazil is introduced. This combined drought index is based on a combination of three indicators: Standardized Precipitation Index (SPI), Soil Moisture Anomalies (SMA) and Vegetation Health Index (VHI). The proposed CDI has four levels, watch, warning, alert I and alert II, thus benefiting an increasing degrees of severity. This CDI was applied during the first 6 months of 2020 to different study sites over Southern Brasil, representative of the crop areas. The performance of the CDI levels was assessed by comparison with risk areas. Observations show a good match between these areas and the CDI. Important crop drought events in 2020 were correctly predicted by the proposed CDI in all areas

De campañas de medidas a productos de salinidad: un tributo a las contribuciones de Jordi Font a la mision SMOS

This article summarizes some of the activities in which Jordi Font, research professor and head of the Department of Physical and Technological Oceanography, Institut de Ciències del Mar (CSIC, Spanish National Research Council) in Barcelona, has been involved as co-Principal Investigator for Ocean Salinity of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Mission from the perspective of the Remote Sensing Lab at the Universitat Politècnica de Catalunya. We have probably left out some of his many contributions to salinity remote sensing, but we hope that this review will give an idea of the importance of his work. We focus on the following issues: 1) the new accurate measurements of the sea water dielectric constant, 2) the WISE and EuroSTARRS field experiments that helped to define the geophysical model function relating brightness temperature to sea state, 3) the FROG 2003 field experiment that helped to understand the emission of sea foam, 4) GNSS-R techniques for improving sea surface salinity retrieval, 5) instrument characterization campaigns, and 6) the operational implementation of the Processing Centre of Levels 3 and 4 at the SMOS Barcelona Expert Centre.Este artículo resume algunas de las actividades en las que Jordi Font, profesor de investigación y jefe del Departamento de Física y Tecnología Oceanográfica, del Institut de Ciències del Mar (CSIC) en Barcelona, ha estado desarrollando como co-Investigador Principal de la parte de la misión SMOS de la ESA, una misión Earth Explorer, desde la perspectiva del Remote Sensing Lab, de la Universitat Politècnica de Catalunya. Seguramente, estamos olvidando algunas de sus muchas contribuciones a la teledetección de la salinidad, pero esperamos que esta revisión dé una idea de la importancia de su trabajo. Este artículo se focaliza en los siguientes puntos: 1) las medidas de alta calidad de la constante dieléctrica del agua marina, 2) las campañas de medidas WISE y EuroSTARRS que ayudaron a la definición del modelo geofísico relacionando la temperatura de brillo con el estado del mar, 3) la campaña de medidas FROG 2003 que ayudó a entender la emisión de la espuma marina 4) presentación de las técnicas de GNSS-R para la mejora de la recuperación de la salinidad superficial 5) campañas para la caracterización del instrumento y 6) la implantación del centro de procesado operacional de niveles 3 y 4 en el SMOS Barcelona Expert Centre

Sensitivity of L-band vegetation optical depth to carbon stocks in tropical forests: a comparison to higher frequencies and optical indices

Supplementary data to this article can be found online at https://doi.org/10.1016/j.rse.2019.111303.Monitoring vegetation carbon in tropical regions is essential to the global carbon assessment and to evaluate the actions oriented to the reduction of forest degradation. Mainly, satellite optical vegetation indices and LiDAR data have been used to this purpose. These two techniques are limited by cloud cover and are sensitive only to the top of vegetation. In addition, the vegetation attenuation to the soil microwave emission, represented by the vegetation optical depth (VOD), has been applied for biomass estimation using frequencies ranging from 4 to 30¿GHz (C- to K-bands). Atmosphere is transparent to microwaves and their sensitivity to canopy layers depends on the frequency, with lower frequencies having greater penetration depths. In this regard, L-band VOD (1.4¿GHz) is expected to enhance the ability to estimate carbon stocks. This study compares the sensitivity of different VOD products (from L, C, and X-bands) and an optical vegetation index (EVI) to the above-ground carbon density (ACD). It quantifies the contribution of ACD and forest cover proportion to the VOD/EVI signals. The study is conducted in Peru, southern Colombia and Panama, where ACD maps have been derived from airborne LiDAR. Results confirm the enhanced sensitivity of L-band VOD to ACD when compared to higher frequency bands, and show that the sensitivity of all VOD bands decreases in the densest forests. ACD explains 34% and forest cover 30% of L-band VOD variance, and these proportions gradually decrease for EVI, C-, and X-band VOD, respectively. Results are consistent through different categories of altitude and carbon density. This pattern is found in most of the studied regions and in flooded forests. Results also show that C-, X-band VOD and EVI provide complementary information to L-band VOD, especially in flooded forests and in mountains, indicating that synergistic approaches could lead to improved retrievals in these regions. Although the assessment of vegetation carbon in the densest forests requires further research, results from this study support the use of new L-band VOD estimates for mapping the carbon of tropical forests.Peer ReviewedPostprint (author's final draft