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The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of ~ 50 km. However, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution SM information. In order to overcome this spatial mismatch, a disaggregation algorithm called Disaggregation based on Physical And Theoretical scale Change (DISPATCH) combines higher-resolution data from optical/thermal sensors with the SM retrieved from microwave sensors like SMOS, producing higher-resolution SM as the output. A DISPATCH-based processor has been implemented for the whole globe (emerged lands) in the Centre Aval de Traitement des Données SMOS (CATDS), the French data processing center for SMOS Level 3 products. This new CATDS Level-4 Disaggregation processor (C4DIS) generates SM maps at 1 km resolution. This paper provides an overview of the C4DIS architecture, algorithms and output products. Differences with the original DISPATCH prototype are explained and major processing parameters are presented. The C4DIS SM product is compared against L3 and in situ SM data during a one year period over the Murrumbidgee catchment and the Yanco area (Australia), and during a four and a half year period over the Little Washita and the Walnut Gulch watersheds (USA). The four validation areas represent highly contrasting climate regions with different landscape properties. According to this analysis, the C4DIS SM product improves the spatio-temporal correlation with in situ measurements in the semi-arid regions with substantial SM spatial variability mainly driven by precipitation and irrigation. In sub-humid regions like the Little Washita watershed, the performance of the algorithm is poor except for summer, as result of the weak moisture-evaporation coupling. Disaggregated products do not succeed to have and additional benefit in the Walnut Gulch watershed, which is also semi-arid but with well-drained soils that are likely to cancel the spatial contrast needed by DISPATCH. Although further validation studies are still needed to better assess the performance of DISPATCH in a range of surface and atmospheric conditions, the new C4DIS product is expected to provide satisfying results over regions having medium to high SM spatial variability. [ABSTRACT FROM AUTHOR]

The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on vegetation, in particular plant available water and water content in a canopy, drought index and flood risks, surface ocean winds in storms, freeze/thaw state and sea ice and its effect on ocean–atmosphere heat fluxes and dynamics affecting large-scale processes of the Earth's climate system. Significant progress has been made over the course of the now 6-year life time of the SMOS mission in improving the ESA provided level 1 brightness temperature and level 2 soil moisture and sea surface salinity data products. The main emphasis of this paper is to review the status of the mission and provide an overview and performance assessment of SMOS data products, in particular with a view towards operational applications, and using SMOS products in data assimilation. SMOS is in excellent technical condition with no limiting factors for operations beyond 2017. The instrument performance fulfils the requirements. The radio-frequency interference (RFI) contamination originates from man-made emitters on ground, operating in the protected L-band and adding signal to the natural radiation emitted by the Earth. RFI has been detected worldwide and has been significantly reduced in Europe and the Americas but remains a constraint in Asia and the Middle East. The mission's scientific objectives have been reached over land and are approaching the mission objectives over ocean. This review paper aims to provide an introduction and synthesis to the papers published in this RSE special issue on SMOS. [ABSTRACT FROM AUTHOR]

European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission is perturbed by Radio Frequency Interference (RFI) that jeopardizes part of its scientific retrieval in certain areas of the world. Areas affected by RFI might experience data loss or underestimation of soil moisture and ocean salinity retrieval values. To alleviate this situation, the SMOS team has put several strategies into place that help improve the RFI situation, filter the SMOS data from RFI perturbed measurements and bring awareness to the RFI problem. [ABSTRACT FROM AUTHOR]

The main objectives of this study were to provide a proxy “validation” of the Soil Moisture and Ocean Salinity (SMOS) mission's vegetation optical depth product ( τ SMOS ) on a global scale, to give a first indication of the potential of τ SMOS to capture large-scale vegetation dynamics, and to contribute towards investigations into the possible use of optical vegetation indices (VI's) for the estimation of τ . The analyses were performed by comparing the spatial and temporal behaviour of τ SMOS relative to four MODIS-based VI's, with that of the vegetation optical depth from a similar sensor, AMSR-E ( τ AMSR-E ). 16-day and annual average values of the passive microwave optical depth ( τ ) for the year 2010 were obtained from SMOS (1.4 GHz) and AMSR-E (6.9 GHz) observations. The VI's chosen for this study were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI) and Normalized Difference Water Index (NDWI). The highest global-scale, annual correlation was found between τ SMOS and τ AMSR-E from ascending orbits (Spearman's R = 0.80). On global, annual scales, τ SMOS showed higher correlations with τ AMSR-E than with the VI's, while τ AMSR-E was more highly correlated with VI's than with τ SMOS . Timeseries of both τ and the VI's were made per landcover class, for the northern hemisphere, tropics and southern hemisphere. Although the large-scale spatial and spatio-temporal behaviour of τ SMOS and τ AMSR-E is generally similar, the results highlight some notable differences in observing vegetation with optical vs . passive microwave sensors, and certain crucial differences between the two passive microwave sensors themselves. Overall, the results found in this study give a good first confidence in the SMOS L3 τ product and its potential use in vegetation studies. These results provide an essential general reference for future (global-scale) vegetation monitoring with passive microwaves, for the future inclusion of τ SMOS in long-term, multi-sensor datasets, and for passive microwave algorithm development. [ABSTRACT FROM AUTHOR]

The Soil Moisture Ocean Salinity (SMOS) satellite mission routinely provides global multiangular observations of brightness temperature TB at both horizontal and vertical polarization with a 3-day repeat period. The assimilation of such data into a land surface model (LSM) may improve the skill of operational flood forecasts through an improved estimation of soil moisture SM. To accommodate for the direct assimilation of the SMOS TB data, the LSM needs to be coupled with a radiative transfer model (RTM), serving as a forward operator for the simulation of multiangular and multipolarization top of the atmosphere TBs. This study investigates the use of the Variable Infiltration Capacity model coupled with the Community Microwave Emission Modelling Platform for simulating SMOS TB observations over the upper Mississippi basin, United States. For a period of 2 years (2010-11), a comparison between SMOS TBs and simulations with literature-based RTM parameters reveals a basin-averaged bias of 30 K. Therefore, time series of SMOS TB observations are used to investigate ways for mitigating these large biases. Specifically, the study demonstrates the impact of the LSM soil moisture climatology in the magnitude of TB biases. After cumulative distribution function matching the SM climatology of the LSM to SMOS retrievals, the average bias decreases from 30 K to less than 5 K. Further improvements can be made through calibration of RTM parameters related to the modeling of surface roughness and vegetation. Consequently, it can be concluded that SM rescaling and RTM optimization are efficient means for mitigating biases and form a necessary preparatory step for data assimilation. [ABSTRACT FROM AUTHOR]

Abstract: Global Level-3 surface soil moisture (SM) maps derived from the passive microwave SMOS (Soil Moisture and Ocean Salinity) observations at L-band have recently been released. In this study, a comparative analysis of this Level 3 product (referred to as SMOSL3) along with another Surface SM (SSM) product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) at C-band is presented (this latter product is referred to as AMSRM). SM-DAS-2, a SSM product produced by the European Centre for Medium Range Weather Forecasts (ECMWF) Land Data Assimilation System (LDAS) was used to monitor both SMOSL3 and AMSRM qualities. The present study was carried out from 03/2010 to 09/2011, a period during which both SMOS and AMSR-E products were available at global scale. Three statistical metrics were used for the evaluation; the correlation coefficient (R), the Root Mean Squared Difference (RMSD), and the bias. Results were analysed using maps of biomes and Leaf Area Index (LAI). It is shown that both SMOSL3 and AMSRM captured well the spatio-temporal variability of SM-DAS-2 for most of the biomes. In terms of correlation values, the SMOSL3 product was found to better capture the SSM temporal dynamics in highly vegetated biomes (“tropical humid”, “temperate humid”, etc.) while best results for AMSRM were obtained over arid and semi-arid biomes (“desert temperate”, “desert tropical”, etc.). Finally, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (marginally better) SSM products correlated well with the SM-DAS-2 product over regions with sparse vegetation for values of LAI ≤1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 showed better correlations with SM-DAS-2 than AMSRM: SMOSL3 had a consistent performance up to LAI=6, whereas the AMSRM performance deteriorated with increasing values of LAI. This study reveals that SMOS and AMSR-E complement one another in monitoring SSM over a wide range in conditions of vegetation density and that there are valuable satellite observed SSM data records over more than 10years, which can be used to study land–atmosphere processes. [Copyright &y& Elsevier]

This paper reports on a new soil moisture disaggregation scheme based on topography and soil depth information. It is designed for low resolution remote sensing data assimilation into hydrological modelling. The scheme makes use of a simple Soil Vegetation Atmosphere Transfer model coupled to the TOPMODEL formalism. Water and energy balance are computed at the catchment scale, taking lateral flows due to topography into account. Lumped values of near-surface and deep soil water content are then disaggregated at local scale using simple relationship between mean quantities, local topography and soil depth information. Results for a small water catchment in South-eastern Australia show satisfactory reproduction of the local soil moisture patterns using a combination of topography and soil depth information. Due to subgrid variability and differences between the simulation and observation scale (the Digital Elevation Model pixel versus the point measurement), the point-to-point comparison between observations and simulations shows a poor correlation. Rescaling shows that a good correlation is obtained when averaging the simulated and observed soil moisture over a length of 100 m. [Copyright &y& Elsevier]

This paper presents a community effort to develop good practice guidelines for the validation of global coarse-scale satellite soil moisture products. We provide theoretical background, a review of state-of-the-art methodologies for estimating errors in soil moisture data sets, practical recommendations on data pre-processing and presentation of statistical results, and a recommended validation protocol that is supplemented with an example validation exercise focused on microwave-based surface soil moisture products. We conclude by identifying research gaps that should be addressed in the near future. • Satellite soil moisture validation methods are reviewed • Community-agreed validation good practice guidelines are presented • A standardized satellite soil moisture validation protocol is provided [ABSTRACT FROM AUTHOR]

A data-driven approach insensitive to the initial conditions was developed to extract governing equations for the concentration of CO 2 in the Altamira cave (Spain) and its two main drivers: the outside temperature and the soil moisture. This model was then reformulated in order to use satellite observations and meteorological predictions, as a forcing. The concentration of CO 2 inside the cave was then investigated from 1950 to 2100 under various scenarios. It is found that extreme levels of CO 2 were reached during the period 1950-1972 due to the massive affluence of visitors. It is demonstrated that it is possible to monitor the CO 2 in the cave in real time using satellite information as an external forcing. For the future, it is shown that the maximum values of CO 2 will exceed the levels reached during the 1980s and the 1990s when the CO 2 introduced by the touristic visits, although intentionally reduced, still enhanced considerably the micro corrosion of walls and pigments., (© 2024. The Author(s).)

The US Centers for Disease Control and Prevention (CDC) supports international partners in introducing vaccines, including those against SARS-CoV-2 virus. CDC contributes to the development of global technical tools, guidance, and policy for COVID-19 vaccination and has established its COVID-19 International Vaccine Implementation and Evaluation (CIVIE) program. CIVIE supports ministries of health and their partner organizations in developing or strengthening their national capacities for the planning, implementation, and evaluation of COVID-19 vaccination programs. CIVIE's 7 priority areas for country-specific technical assistance are vaccine policy development, program planning, vaccine confidence and demand, data management and use, workforce development, vaccine safety, and evaluation. We discuss CDC's work on global COVID-19 vaccine implementation, including priorities, challenges, opportunities, and applicable lessons learned from prior experiences with Ebola, influenza, and meningococcal serogroup A conjugate vaccine introductions.

Background: Gay, bisexual and other men who have sex with men (GBMSM) are at far greater risk of experiencing poor mental health (MH) than wider society. This disparity was exacerbated by additional 'unique to sexual minority status' COVID-19 stressors. Objective: This sequential, mixed-methods study examined remote MH help-seeking among GBMSM in the U.K. and Ireland during the first COVID-19 lockdown. Methods and Results: Quantitative survey data ( n  = 1368), analysed with logistic regression, suggested GBMSM experiencing moderate-to-severe anxiety and those with a past MH diagnosis were most likely to seek MH support. Thematic analysis of qualitative interview ( n  = 18) data identified multiple barriers and enablers to GBMSM seeking remote MH help, with the help primarily sought from GBMSM-facing organisations and generic online resources. Finally, the behaviour change wheel was used to generate theoretically informed recommendations to promote MH help-seeking among GBMSM in Scotland. Implications: We discuss how applying these recommendations in the short, medium and long term will begin to address GBMSM's MH needs, post COVID-19., Competing Interests: No potential conflict of interest was reported by the author(s)., (© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)

Background: The initial response to COVID-19 in the UK involved a rapid contraction of face-to-face sexual and reproductive health (SRH) services and widespread use of remote workarounds. This study sought to illuminate young people's experiences of accessing and using condoms and contraception in the early months of the pandemic., Methods: We analysed data, including open-text responses, from an online survey conducted in June-July 2020 with a convenience sample of 2005 16-24-year-olds living in Scotland., Results: Among those who used condoms and contraception, one quarter reported that COVID-19 mitigation measures had made a difference to their access or use. Open-text responses revealed a landscape of disrupted prevention , including changes to sexual risk-taking and preventive practices, unwanted contraceptive pathways, unmet need for sexually transmitted infection (STI) testing, and switches from freely provided to commercially sold condoms and contraception. Pandemic-related barriers to accessing free condoms and contraception included: (1) uncertainty about the legitimacy of accessing SRH care and self-censorship of need; (2) confusion about differences between SRH care and advice received from healthcare professionals during the pandemic compared with routine practice; and (3) exacerbation of existing access barriers, alongside reduced social support and resources to navigate SRH care., Conclusions: Emerging barriers to STI and pregnancy prevention within the context of COVID-19 have the potential to undermine positive SRH practices, and widen inequalities, among young people. As SRH services are restored amid evolving pandemic restrictions, messaging to support navigation of condom and contraception services should be co-created with young people., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Microwave radiometry has provided valuable spaceborne observations of Earth's geophysical properties for decades. The recent SMOS, Aquarius, and SMAP satellites have demonstrated the value of measurements at 1400 MHz for observing surface soil moisture, sea surface salinity, sea ice thickness, soil freeze/thaw state, and other geophysical variables. However, the information obtained is limited by penetration through the subsurface at 1400 MHz and by a reduced sensitivity to surface salinity in cold or wind-roughened waters. Recent airborne experiments have shown the potential of brightness temperature measurements from 500-1400 MHz to address these limitations by enabling sensing of soil moisture and sea ice thickness to greater depths, sensing of temperature deep within ice sheets, improved sensing of sea salinity in cold waters, and enhanced sensitivity to soil moisture under vegetation canopies. However, the absence of significant spectrum reserved for passive microwave measurements in the 500-1400 MHz band requires both an opportunistic sensing strategy and systems for reducing the impact of radio-frequency interference. Here, we summarize the potential advantages and applications of 500-1400 MHz microwave radiometry for Earth observation and review recent experiments and demonstrations of these concepts. We also describe the remaining questions and challenges to be addressed in advancing to future spaceborne operation of this technology along with recommendations for future research activities.

While predicting the course of an epidemic is difficult, predicting the course of a pandemic from an emerging virus is even more so. The validity of most predictive models relies on numerous parameters, involving biological and social characteristics often unknown or highly uncertain. Data of the COVID-19 epidemics in China, Japan, South Korea and Italy were used to build up deterministic models without strong assumptions. These models were then applied to other countries to identify the closest scenarios in order to foresee their coming behaviour. The models enabled to predict situations that were confirmed little by little, proving that these tools can be efficient and useful for decision making in a quickly evolving operational context.

Changes in terrestrial tropical carbon stocks have an important role in the global carbon budget. However, current observational tools do not allow accurate and large-scale monitoring of the spatial distribution and dynamics of carbon stocks 1 . Here, we used low-frequency L-band passive microwave observations to compute a direct and spatially explicit quantification of annual aboveground carbon (AGC) fluxes and show that the tropical net AGC budget was approximately in balance during 2010 to 2017, the net budget being composed of gross losses of -2.86 PgC yr -1 offset by gross gains of -2.97 PgC yr -1 between continents. Large interannual and spatial fluctuations of tropical AGC were quantified during the wet 2011 La Niña year and throughout the extreme dry and warm 2015-2016 El Niño episode. These interannual fluctuations, controlled predominantly by semiarid biomes, were shown to be closely related to independent global atmospheric CO 2 growth-rate anomalies (Pearson's r = 0.86), highlighting the pivotal role of tropical AGC in the global carbon budget.

Sexual and relationship education should be part of educational curriculum in early teenage years. The young people should be provided with evidence based education to reduce the risks of untimed pregnancies and sexually transmitted infections., (Crown Copyright © 2019. Published by Elsevier B.V. All rights reserved.)

Plant water storage is fundamental to the functioning of terrestrial ecosystems by participating in plant metabolism, nutrient and sugar transport, and maintenance of the integrity of the hydraulic system of the plant. However, a global view of the size and dynamics of the water pools stored in plant tissues is still lacking. Here, we report global patterns of seasonal variations in ecosystem-scale plant water storage and their relationship with leaf phenology, based on space-borne measurements of L-band vegetation optical depth. We find that seasonal variations in plant water storage are highly synchronous with leaf phenology for the boreal and temperate forests, but asynchronous for the tropical woodlands, where the seasonal development of plant water storage lags behind leaf area by up to 180 days. Contrasting patterns of the time lag between plant water storage and terrestrial groundwater storage are also evident in these ecosystems. A comparison of the water cycle components in seasonally dry tropical woodlands highlights the buffering effect of plant water storage on the seasonal dynamics of water supply and demand. Our results offer insights into ecosystem-scale plant water relations globally and provide a basis for an improved parameterization of eco-hydrological and Earth system models.

The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was -0.05 petagrams of C per year (Pg C yr -1 ) associated with drying trends, and a net change of -0.02 Pg C yr -1 was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, -0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area.

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial and time scales in surface soil moisture (SM) within the satellite footprint (~50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at time scales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per time-scale basis by comparison to large-spatial scale datasets (the in situ spatial average, SMOS, AMSR2 and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), the percentage of correlated areas (CArea) and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the time scale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings and TC is suitable for week and month scales but not for other scales where datasets cross-correlations are found low. In contrast, WCor and CArea give consistent results at all time-scales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (1 station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones. Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAP/Sentinel-1 Active-Passive Soil Moisture Product in April 2017. This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (T A ) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated T A data then go through various correction/calibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (LiC_TB_E). The LiC_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 - October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m 3 /m 3 unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized T B channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.

In 1988, the by the World Health Assembly established the Global Polio Eradication Initiative, which consisted of a partnership among the World Health Organization (WHO), Rotary International, the Centers for Disease Control and Prevention (CDC), and the United Nations Children's Fund. By 2016, the annual incidence of polio had decreased by >99.9%, compared with 1988, and at the time of writing, only 3 countries in which wild poliovirus circulation has never been interrupted remain: Afghanistan, Nigeria, and Pakistan. A key strategy for polio eradication has been the development of a skilled and deployable workforce to implement eradication activities across the globe. In 1999, the Stop Transmission of Polio (STOP) program was developed and initiated by the CDC, in collaboration with the WHO, to train and mobilize additional human resources to provide technical assistance to polio-endemic countries. STOP has also informed the development of other public health workforce capacity to support polio eradication efforts, including national STOP programs. In addition, the program has diversified to address measles and rubella elimination, data management and quality, and strengthening routine immunization programs. This article describes the STOP program and how it has contributed to polio eradication by building global public health workforce capacity., (© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.)

The "Cooperative Airborne Radiometer for Ocean and Land Studies" (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer-STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity.

We present a physical model describing the radiance acquired by an infrared sensor over a rugged heterogeneous surface. This model predicts the radiance seen over complex landscapes like urban areas and provides an accurate analysis of the signal, as each component is available at ground and sensor level. Plus, it allows data comparison from different instruments. Two representative cases (natural and urban) are analysed to show the composition and the construction of the sensor signal and to highlight the importance of having a 3D model, especially for rugged surfaces where environment weights in the overall spectral domain.

A physical algorithm is developed to solve the radiative transfer problem in the solar reflective spectral domain. This new code, Advanced Modeling of the Atmospheric Radiative Transfer for Inhomogeneous Surfaces (AMARTIS), takes into account the relief, the spatial heterogeneity, and the bidirectional reflectances of ground surfaces. The resolution method consists of first identifying the irradiance and radiance components at ground and sensor levels and then modeling these components separately, the rationale being to find the optimal trade off between accuracy and computation times. The validity of the various assumptions introduced in the AMARTIS model are checked through comparisons with a reference Monte Carlo radiative transfer code for various ground scenes: flat ground with two surface types, a linear sand dune landscape, and an extreme mountainous configuration. The results show a divergence of less than 2% between the AMARTIS code and the Monte Carlo reference code for the total signals received at satellite level. In particular, it is demonstrated that the environmental and topographic effects are properly assessed by the AMARTIS model even for situations in which the effects become dominant.

An algorithm based on the Monte Carlo method is developed to solve the radiative transfer equation in the reflective domain (0.4-4 microm) of the solar spectrum over rugged terrain. This algorithm takes into account relief, spatial heterogeneity, and ground bidirectional reflectance. The method permits the computation of irradiance components at ground level and radiance terms reaching an airborne or satelliteborne sensor. The Monte Carlo method consists of statistically simulating the paths of photons inside the Earth-atmosphere system to reproduce physical phenomena while introducing neither analytical modeling nor assumption. The potentialities of the code are then depicted over different types of landscape, including a seashore, a desert region, and a steep mountainous valley.