Land surface temperature retrieval from Sentinel 2 and 3 Missions

In this work we explore the synergistic use of future MSI instrument on board Sentinel-2 platform and OLCI/SLSTR instruments on board Sentinel-3 platform in order to improve LST products currently derived from the single AATSR instrument on board the ENVI- SAT satellite. For this purpose, the high spatial resolu- tion data from Setinel2/MSI will be used for a good characterization of the land surface sub-pixel heteroge- neity, in particular for a precise parameterization of surface emissivity using a land cover map and spectral mixture techniques. On the other hand, the high spectral resolution of OLCI instrument, suitable for a better characterization of the atmosphere, along with the dual- view available in the SLTSR instrument, will allow a better atmospheric correction through improved aero- sol/water vapor content retrievals and the implementa- tion of novel cloud screening procedures. Effective emissivity and atmospheric corrections will allow accu- rate LST retrievals using the SLSTR thermal bands by developing a synergistic split-window/dual-angle algo- rithm. ENVISAT MERIS and AATSR instruments and different high spatial resolution data (Landsat/TM, Proba/CHRIS, Terra/ASTER) will be used as bench- mark for the future OLCI, SLSTR and MSI instruments. Results will be validated using ground data collected in the framework of different field campaigns organized by ESA.

Seasonal surface urban energy balance and wintertime stability simulated using three land-surface models in the high-latitude city Helsinki

The performance of three urban land surface models, run in offline mode, with their default external parameters, is evaluated for two distinctly different sites in Helsinki: Torni and Kumpula. The former is a dense city centre site with 22% vegetation, while the latter is a suburban site with over 50% vegetation. At both locations the models are compared against sensible and latent heat fluxes measured using the eddy covariance technique, along with snow depth observations. The cold climate experienced by the city causes strong seasonal variations that include snow cover and stable atmospheric conditions. Most of the time the three models are able to account for the differences between the study areas as well as the seasonal and diurnal variability of the energy balance components. However, the performances are not systematic across the modelled components, season and surface type. The net all-wave radiation is well simulated, with the greatest uncertainties related to snowmelt timing, when the fraction of snow cover has a key role, particularly in determining the surface albedo. For the turbulent fluxes, more variation between the models is seen which can partly be explained by the different methods in their calculation and partly by surface parameter values. For the sensible heat flux, simulation of wintertime values was the main problem, which also leads to issues in predicting near-surface stabilities particularly at the dense city centre site. All models have the most difficulties in simulating latent heat flux. This study particularly emphasizes that improvements are needed in the parameterization of anthropogenic heat flux and thermal parameters in winter, snow cover in spring and evapotranspiration in order to improve the surface energy balance modelling in cold climate cities.

The BALTIMOS (BALTEX Integrated Model System) fi eld experiments: A comprehensive atmospheric boundary layer data set for model validation over the open and ice- covered Baltic Sea

A comprehensive atmospheric boundary layer (ABL) data set was collected in eight fi eld experiments (two during each season) over open water and sea ice in the Baltic Sea during 1998–2001 with the primary objective to validate the coupled atmospheric- ice-ocean-land surface model BALTIMOS (BALTEX Integrated Model System). Measurements were taken by aircraft, ships and surface stations and cover the mean and turbulent structure of the ABL including turbulent fl uxes, radiation fl uxes, and cloud conditions. Measurement examples of the spatial variability of the ABL over the ice edge zone and of the stable ABL over open water demonstrate the wide range of ABL conditions collected and the strength of the data set which can also be used to validate other regional models.

Modelo OLAM (ocean-land-atmosphere-model): descrição, aplicações, e perspectivas

O modelo OLAM foi desenvolvido com objetivo de estender a capacidade de representar os fenômenos de escala global e regional simultaneamente. Este modelo apresenta inovações quanto aos processos dinâmicos, configuração de grade, estrutura de memória e técnicas de solução numérica das equações prognósticas. As equações de Navier-Stokes são resolvidas através da técnica de volumes finitos que conservam massa, momento e energia. No presente trabalho, apresenta-se uma descrição sucinta do OLAM e alguns resultados de sua aplicação em simulações climáticas da precipitação mensal para a região norte da América do Sul, bem como em rodadas para previsão numérica de tempo regional. Os resultados mostram que o modelo consegue representar bem os aspectos meteorológicos de grande escala. Em geral, seu desempenho melhora quando são adotadas grades de maior resolução espacial, nas quais se verificam melhorias significativas tanto na estimativa da precipitação mensal regional, quanto na previsão numérica de tempo.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

The impact of different surface parameterizations and vertical resolutions on the simulation of seabreeze episodes at the island of Fuerteventura

[EN] On 8-10 April 2007, several episodes of intense sea-breeze fronts were registered at the island of Fuerteventura (Canary Islands). The sea-breeze circulation was primary driven by daytime heating contrasts between land and the Atlantic Ocean during a period of weak trade winds. Numerical simulations of these events were carried out using the 3.1.1 version of the Weather Research and Forecasting (WRF) Model. Two different domains with 6.6-km and 2.2-km horizontal grid spacing and two sets with 27 and 51 vertical sigma levels were defined. The simulation was performed using two-way interactive nesting between the first and the second domain, using different land surface model parameterizations (Thermal diffusion, Noah LSM and RUC) for comparison. Initial conditions were provided by the NCAR Dataset analysis from April 2007, which were improved using surface and upper-air observations. The poster is focused on the 9 April episode.

Multitemporal analysis of satellite imagery: implementation of a land evolution model in ALCS (ATSR LAND CLASSIFICATION SYSTEM)

In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

Use of Land Surface Temperature to Estimate Surface Energy Fluxes: Contributions of Wilfried Brutsaert and Collaborators

Land surface temperature (LST) plays a key role in governing the land surface energy budget, and measurements or estimates of LST are an integral part of many land surface models and methods to estimate land surface sensible heat (H) and latent heat fluxes. In particular, the LST anchors the potential temperature profile in Monin-Obukhov similarity theory, from which H can be derived. Brutsaert has made important contributions to our understanding the nature of surface temperature measurements as well as the practical but theoretically sound use of LST in this framework. His work has coincided with the wide-spread availability of remotely sensed LST measurements. Use of remotely sensed LST estimates inevitably involves complicating factors, such as: varying spatial and temporal scales in measurements, theory, and models; spatial variability of LST and H; the relationship between measurements of LST and the temperature felt by the atmosphere; and the need to correct satellite-based radiometric LST measurements for the radiative effects of the atmosphere. This paper reviews the progress made in research in these areas by tracing and commenting on Brutsaert's contributions.