Global-scale analysis of satellite-derived time series of naturally inundated areas as a basis for floodplain modeling

Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993–2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges

Diagnostiquer la proximité perçue en vente directe de produits alimentaires

Assessing the perceived proximity in direct selling of food products In line with the Editorial of Décisions Marketing "Is proximity a new marketing trend?", the aim of this article is to question the managerial relevance of the concept of proximity within the context of direct selling of food products. Through empirical studies in three supply chains - French CSA (AMAP), farm shops and direct selling on markets- we show the interest of assessing perceived proximity since it has a positive influence on consumers trust towards the studied supply chains and allows to discriminate them. The relevance of the concept of proximity being supported, recommendations are then emphasized on two points: which kinds of proximity to encourage and how to enhance proximity in food direct selling.Dans le prolongement de l'éditorial de Décisions Marketing : " La proximité est-elle une nouvelle mode du marketing ? ", cet article interroge la pertinence managériale du concept de proximité en vente directe de produits alimentaires. Via des études empiriques menées dans trois circuits - l'AMAP, le Point de Vente Collectif et le marché - nous montrons qu'il est pertinent de diagnostiquer la proximité perçue par les consommateurs car elle influence positivement la confiance à l'égard des circuits étudiés et permet de les discriminer. Une fois l'intérêt du concept démontré, des recommandations sont formulées autour de deux interrogations : quels types de proximité encourager et comment développer la proximité perçue en vente directe

Impact of Surface Roughness and Soil Texture on Mineral Dust Emission Fluxes Modeling

Dust production models (DPM) used to estimate vertical fluxes of mineral dust aerosols over arid regions need accurate data on soil and surface properties. The Laboratoire Inter-Universitaire des Systemes Atmospheriques (LISA) data set was developed for Northern Africa, the Middle East, and East Asia. This regional data set was built through dedicated field campaigns and include, among others, the aerodynamic roughness length, the smooth roughness length of the erodible fraction of the surface, and the dry (undisturbed) soil size distribution. Recently, satellite-derived roughness length and high-resolution soil texture data sets at the global scale have emerged and provide the opportunity for the use of advanced schemes in global models. This paper analyzes the behavior of the ERS satellite-derived global roughness length and the State Soil Geographic data base-Food and Agriculture Organization of the United Nations (STATSGO-FAO) soil texture data set (based on wet techniques) using an advanced DPM in comparison to the LISA data set over Northern Africa and the Middle East. We explore the sensitivity of the drag partition scheme (a critical component of the DPM) and of the dust vertical fluxes (intensity and spatial patterns) to the roughness length and soil texture data sets. We also compare the use of the drag partition scheme to a widely used preferential source approach in global models. Idealized experiments with prescribed wind speeds show that the ERS and STATSGO-FAO data sets provide realistic spatial patterns of dust emission and friction velocity thresholds in the region. Finally, we evaluate a dust transport model for the period of March to July 2011 with observed aerosol optical depths from Aerosol Robotic Network sites. Results show that ERS and STATSGO-FAO provide realistic simulations in the region

Ground subsidence effects on simulating dynamic high-latitude surface inundation under permafrost thaw using CLM5

Simulating surface inundation is particularly challenging for the high-latitude permafrost regions. Ice-rich permafrost thaw can create expanding thermokarst lakes as well as shrinking large wetlands. Such processes can have major biogeochemical implications and feedbacks to the climate system by altering the pathways and rates of permafrost carbon release. However, the processes associated with it havenot yet been properly represented in Earth system models. We show a new model parameterization that allows direct representation of surface water dynamics in CLM (Community Land Model), the land surface model of several Earth System Models. Specifically, we coupled permafrost-thaw-induced ground subsidence and surface microtopography distribution to represent surface water dynamics in the high latitudes. Our results show increased surface water fractions around western Siberian plains and northeastern territories of Canada. Additionally, localized drainage events correspond well to severe ground subsidence events. Our parameterization is one of the first steps towards a process-oriented repre-sentation of surface hydrology, which is crucial to assess the biogeochemical feedbacks between land and the atmosphere under changing climat

Frequency and Angular Variations of Land Surface Microwave Emissivities: Can we Estimate SSM/T and AMSU Emissivities from SSM/I Emissivities?

To retrieve temperature and humidity profiles from SSM/T and AMSU, it is important to quantify the contribution of the Earth surface emission. So far, no global estimates of the land surface emissivities are available at SSM/T and AMSU frequencies and scanning conditions. The land surface emissivities have been previously calculated for the globe from the SSM/I conical scanner between 19 and 85 GHz. To analyze the feasibility of deriving SSM/T and AMSU land surface emissivities from SSM/I emissivities, the spectral and angular variations of the emissivities are studied, with the help of ground-based measurements, models and satellite estimates. Up to 100 GHz, for snow and ice free areas, the SSM/T and AMSU emissivities can be derived with useful accuracy from the SSM/I emissivities- The emissivities can be linearly interpolated in frequency. Based on ground-based emissivity measurements of various surface types, a simple model is proposed to estimate SSM/T and AMSU emissivities for all zenith angles knowing only the emissivities for the vertical and horizontal polarizations at 53 deg zenith angle. The method is tested on the SSM/T-2 91.655 GHz channels. The mean difference between the SSM/T-2 and SSM/I-derived emissivities is less than or equal to 0.01 for all zenith angles with an r.m.s. difference of approx. = 0.02. Above 100 GHz, preliminary results are presented at 150 GHz, based on SSM/T-2 observations and are compared with the very few estimations available in the literature

Interannual variations of the terrestrial water storage in the Lower Ob' Basin from a multisatellite approach

International audienceTemporal variations of surface water volume over inundated areas of the Lower Ob' Basin in Siberia, one of the largest contributor of freshwater to the Arctic Ocean, are estimated using combined observations from a multisatellite inundation dataset and water levels over rivers and floodplains derived from the TOPEX/POSEIDON (T/P) radar altimetry. We computed time-series of monthly maps of surface water volume over the common period of available T/P and multisatellite data (1993–2004). The results exhibit interannual variabilities similar to precipitation estimates and river discharge observations. This study also presents monthly estimates of groundwater and permafrost mass anomalies during 2003–2004 based on a synergistic analysis of multisatellite observations and hydrological models. Water stored in the soil is isolated from the total water storage measured by GRACE when removing the contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the snow estimated by inversion of GRACE measurements. The time variations of groundwater and permafrost are then obtained when removing the water content of the root zone reservoir simulated by hydrological models

Modeling Holocene Peatland Carbon Accumulation in North America

Peatlands are a large carbon reservoir. Yet the quantification of their carbon stock still has a large uncertainty due to lacking observational data and well‐tested peatland biogeochemistry models. Here, a process‐based peatland model was calibrated using long‐term peat carbon accumulation data at multiple sites in North America. The model was then applied to quantify the peat carbon accumulation rates and stocks within North America over the last 12,000 years. We estimated that 85–174 Pg carbon was accumulated in North American peatlands over the study period including 0.37–0.76 Pg carbon in subtropical peatlands. During the period from 10,000 to 8,000 years ago, the warmer and wetter conditions might have played an important role in stimulating peat carbon accumulation by enhancing plant photosynthesis. Enhanced peat decomposition due to warming slowed the carbon accumulation through the rest of the Holocene. While recent modeling studies indicate that the northern peatlands will continue to act as a carbon sink in this century, our studies suggest that future enhanced peat decomposition accompanied by peatland areal changes induced by permafrost degradation and other disturbances shall confound the sink and source analysis

Toward systems biology in brown algae to explore acclimation and adaptation to the shore environment.

International audienceBrown algae belong to a phylogenetic lineage distantly related to land plants and animals. They are almost exclusively found in the intertidal zone, a harsh and frequently changing environment where organisms are submitted to marine and terrestrial constraints. In relation with their unique evolutionary history and their habitat, they feature several peculiarities, including at the level of their primary and secondary metabolism. The establishment of Ectocarpus siliculosus as a model organism for brown algae has represented a framework in which several omics techniques have been developed, in particular, to study the response of these organisms to abiotic stresses. With the recent publication of medium to high throughput profiling data, it is now possible to envision integrating observations at the cellular scale to apply systems biology approaches. As a first step, we propose a protocol focusing on integrating heterogeneous knowledge gained on brown algal metabolism. The resulting abstraction of the system will then help understanding how brown algae cope with changes in abiotic parameters within their unique habitat, and to decipher some of the mechanisms underlying their (1) acclimation and (2) adaptation, respectively consequences of (1) the behavior or (2) the topology of the system resulting from the integrative approach

Sea surface temperature in global analyses: gains from the copernicus imaging microwave radiometer

Sea surface temperatures (SSTs) derived from passive microwave (PMW) observations benefit global ocean and SST analyses because of their near-all-weather availability. Present PMW SSTs have a real aperture-limited spatial resolution in excess of 50 km, limiting the spatial fidelity with which SST features, reflecting ocean dynamics, can be captured. This contrasts with the target resolution of global analyses of 5 to 10 km. The Copernicus Imaging Microwave Radiometer (CIMR) is a mission concept under consideration as a high-priority candidate mission for the expansion of the Copernicus space programme. This instrument would be capable of real aperture resolution < 15 km with low total uncertainties in the range 0.4–0.8 K for channels between 1.4 and 36.5 GHz, and a dual-view arrangement that further reduces noise. This paper provides a comparative study of SST uncertainty and feature resolution with and without the availability of CIMR in the future SST-observing satellite constellation based on a detailed simulation of CIMR plus infrared observations and the processing of global SST analyses with 0.05◦ final grid resolution. Simulations of CIMR data including structured errors were added to an observing system consisting of the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and the Advanced Very High Resolution Radiometer (AVHRR) on MetOp-A. This resulted in a large improvement in the global root-mean-square error (RMSE) for SST from 0.37 K to 0.21 K for January and 0.40 K to 0.25 K for July. There was a particularly noticeable improvement in the performance of the analysis, as measured by the reduction in RMSE, for dynamical and persistently cloudy areas. Of these, the Aghulas Current showed an improvement of 43% in January and 48% in July, the Gulf Stream showed 70% and 44% improvements, the Southern Ocean showed 57% and 74% improvements, and the Maritime Continent showed 50% and 40% improvements, respectively

Estimation of Consistent Global Microwave Land Surface Emissivity from AMSR-E and AMSR2 Observations

Accurate estimation of passive microwave land surface emissivity (LSE) is crucial for numerical weather prediction model data assimilation, for microwave retrievals of land precipitation and atmospheric profiles, and for better understanding of land surface and sub-surface characteristics. In this study, global instantaneous LSE is estimated for the 9-year period from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and for the 5-year period from the Advanced Microwave Scanning Radiometer - 2 (AMSR2) sensors. Estimates of LSE from both sensors were obtained by using an updated algorithm that minimizes the discrepancy between the differences in penetration depths from microwave and infrared remote sensing observations. Concurrent ancillary data sets such as skin temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) and profiles of air temperature and humidity from the Atmospheric Infrared Sounder (AIRS) are used. The latest collection 6 of MODIS skin temperature is used for the LSE estimation, and the differences between collections 6 and 5 are also comprehensively assessed. Our analyses reveal that the differences between these two versions of infrared-based skin temperatures could lead up to 0.015 differences in passive microwave LSE values especially in arid regions. The comparison of global mean LSE features from the combined use of AMSR-E and AMSR2 against an independent product - Tool to Estimate Land-Surface Emissivities at Microwave frequencies (TELSEM2) shows spatial pattern correlations of the order 0.92 at all the frequencies. However, there are considerable differences in magnitude between these two LSE estimates possibly due to differences in incidence angles, frequencies, observation times, and ancillary data sets