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Rui Salgado

Bio: Rui Salgado is an academic researcher from University of Évora. The author has contributed to research in topics: Numerical weather prediction & Aerosol. The author has an hindex of 15, co-authored 64 publications receiving 1187 citations.


Papers
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Journal ArticleDOI
TL;DR: SURFEX as mentioned in this paper is an externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean.
Abstract: . SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

573 citations

Journal ArticleDOI
23 Feb 2012-Tellus A
TL;DR: The impact of lakes in numerical weather prediction is investigated in a set of global simulations performed with the ECMWF Integrated Forecasting System (IFS) in this article, where a Fresh shallow-water Lake model (FLake) is introduced allowing the coupling of both resolved and subgrid lakes (those that occupy less than 50% of a grid-box) to the IFS atmospheric model.
Abstract: The impact of lakes in numerical weather prediction is investigated in a set of global simulations performed with the ECMWF Integrated Forecasting System (IFS). A Fresh shallow-water Lake model (FLake) is introduced allowing the coupling of both resolved and subgrid lakes (those that occupy less than 50% of a grid-box) to the IFS atmospheric model. Global fields for the lake ancillary conditions (namely lake cover and lake depth), as well as initial conditions for the lake physical state, have been derived to initialise the forecast experiments. The procedure for initialising the lake variables is described and verified with particular emphasis on the importance of surface water temperature and freezing conditions. The response of short-range near surface temperature to the representation of lakes is examined in a set of forecast experiments covering one full year. It is shown that the impact of subgrid lakes is beneficial, reducing forecast error over the Northern territories of Canada and over Scandinavia particularly in spring and summer seasons. This is mainly attributed to the lake thermal effect, which delays the temperature response to seasonal radiation forcing. Keywords: lakes impact in NWP; global lake simulations; lake-temperature; lake-ice (Published: 23 February 2012) Citation: Tellus A 2012, 64 , 15829, DOI: 10.3402/tellusa.v64i0.15829

116 citations

01 Jan 2010
TL;DR: In this paper, a validation of the coupled system Surfex-FLake based on measurements carried out on the Alqueva reservoir in southern Portugal is presented, showing how the use of FLake in the Surfex system improves surface temperature and turbulent fluxes at the water-mosphere interface.
Abstract: The FLake model parameterizes the local-scale energy exchanges between lake surfaces and the atmosphere. FLake simulates the temperature profile as well as the budgets of heat and turbulent kinetic energy in water. Its implementation into the Surfex system, the externalized surface scheme devoted to research and operational forecasts, is presented here. The paper describes a validation of the coupled system Surfex-FLake based on measurements carried out on the Alqueva reservoir in southern Portugal. This paper shows how the use of FLake in the Surfex system improves surface temperature and turbulent fluxes at the water– atmosphere interface and explains the minor changes made in the computation of the shape function in order to adapt the FLake model to warm lakes, like the one used for this study.

70 citations

Journal ArticleDOI
TL;DR: In this paper, the quality of short-term (24 h) forecasts from a global Numerical Weather Prediction (NWP) model regarding the GHI and DNI components for solar energy applications is assessed.

58 citations

Journal ArticleDOI
TL;DR: In this article, a validation study of the satellite derived water leaving spectral reflectance is presented, using data taken during three field campaigns carried out during 2010 and early 2011, and an empirical algorithm to estimate lake water surface turbidity from the combination of in situ and satellite measurements is proposed.
Abstract: The quality control and monitoring of surface freshwaters is crucial, since some of these water masses constitute essential renewable water resources for a variety of purposes. In addition, changes in the surface water composition may affect the physical properties of lake water, such as temperature, which in turn may impact the interactions of the water surface with the lower atmosphere. The use of satellite remote sensing to estimate the water turbidity of Alqueva reservoir, located in the south of Portugal, is explored. A validation study of the satellite derived water leaving spectral reflectance is firstly presented, using data taken during three field campaigns carried out during 2010 and early 2011. Secondly, an empirical algorithm to estimate lake water surface turbidity from the combination of in situ and satellite measurements is proposed. Finally, the importance of water turbidity on the surface energy balance is tested in the form of a study of the sensitivity of a lake model to the extinction coefficient of water (estimated from turbidity), showing that this is an important parameter that affects the lake surface temperature.

50 citations


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01 Jan 1989
TL;DR: In this article, a two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea.
Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

3,813 citations

Journal ArticleDOI
TL;DR: A geo-statistical model is developed to estimate the volume of global lakes with a surface area of at least 10 ha based on the surrounding terrain information and calculates mean and median hydraulic residence times for all lakes to be 1,834 days and 456 days, respectively.
Abstract: Lakes are key components of biogeochemical and ecological processes, thus knowledge about their distribution, volume and residence time is crucial in understanding their properties and interactions within the Earth system. However, global information is scarce and inconsistent across spatial scales and regions. Here we develop a geo-statistical model to estimate the volume of global lakes with a surface area of at least 10 ha based on the surrounding terrain information. Our spatially resolved database shows 1.42 million individual polygons of natural lakes with a total surface area of 2.67 × 106 km2 (1.8% of global land area), a total shoreline length of 7.2 × 106 km (about four times longer than the world’s ocean coastline) and a total volume of 181.9 × 103 km3 (0.8% of total global non-frozen terrestrial water stocks). We also compute mean and median hydraulic residence times for all lakes to be 1,834 days and 456 days, respectively. Lakes play a key role in our ecosystems and thus it is vital to understand their distribution and volume. Here, the authors present a new global lake database (HydroLAKES) and develop a new geo-statistical model to show global lake area, shoreline length, water volume and hydraulic residence times.

729 citations

Journal ArticleDOI
TL;DR: The ERA5-Land dataset as mentioned in this paper is an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5Land.
Abstract: . Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly ( Munoz-Sabater , 2019 a ) and monthly ( Munoz-Sabater , 2019 b ) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30 , respectively.

704 citations