scholarly journals Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing

2021 ◽  
Author(s):  
Ivan Vorobevskii ◽  
Thi Thanh Luong ◽  
Rico Kronenberg ◽  
Thomas Grünwald ◽  
Christian Bernhofer
Keyword(s):  
Goodness Of Fit ◽  
Meteorological Data ◽  
Model Performance ◽  
Correct Process ◽  
Process Representation ◽  
Uncertainty Model ◽  
Physically Based ◽  
Terrestrial Water

Abstract. Observation and estimation of evaporation is a challenging task. Evaporation occurs on each surface and is driven by different energy sources. Thus the correct process approximation in modelling of the terrestrial water balance plays a crucial part. Here, we use a physically-based 1D lumped soil-plant-atmosphere model (BROOK90) to study the role of parameter selection and meteorological input for modelled evaporation on the point scale. Then, with the integration of the model into global, regional and local frameworks, we made cross-combinations out of their parameterization and forcing schemes to analyse the associated model uncertainty. Five sites with different land uses (grassland, cropland, deciduous broadleaf forest, two evergreen needleleaf forests) located in Saxony, Germany were selected for the study. All combinations of the model setups were validated using FLUXNET data and various goodness of fit criteria. The output from a calibrated model with in-situ meteorological measurements served as a benchmark. We focused on the analysis of the model performance with regard to different time-scales (daily, monthly, and annual). Additionally, components of evaporation are addressed, including their representation in BROOK90. Finally, all results are discussed in the context of different sources of uncertainty: model process representation, input meteorological data and evaporation measurements themselves.

scholarly journals Relative performance of empirical and physical models in assessing the seasonal and annual glacier surface mass balance of Saint-Sorlin Glacier (French Alps)

2018 ◽  
Vol 12 (4) ◽  
pp. 1367-1386 ◽  
Author(s):  
Marion Réveillet ◽  
Delphine Six ◽  
Christian Vincent ◽  
Antoine Rabatel ◽  
Marie Dumont ◽  
...  
Keyword(s):  
Energy Balance ◽  
Mass Balance ◽  
Meteorological Data ◽  
Model Performance ◽  
Surface Mass Balance ◽  
Glacier Surface ◽  
Meteorological Forcing ◽  
Surface Mass ◽  
French Alps

Abstract. This study focuses on simulations of the seasonal and annual surface mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the period 1996–2015 using the detailed SURFEX/ISBA-Crocus snowpack model. The model is forced by SAFRAN meteorological reanalysis data, adjusted with automatic weather station (AWS) measurements to ensure that simulations of all the energy balance components, in particular turbulent fluxes, are accurately represented with respect to the measured energy balance. Results indicate good model performance for the simulation of summer SMB when using meteorological forcing adjusted with in situ measurements. Model performance however strongly decreases without in situ meteorological measurements. The sensitivity of the model to meteorological forcing indicates a strong sensitivity to wind speed, higher than the sensitivity to ice albedo. Compared to an empirical approach, the model exhibited better performance for simulations of snow and firn melting in the accumulation area and similar performance in the ablation area when forced with meteorological data adjusted with nearby AWS measurements. When such measurements were not available close to the glacier, the empirical model performed better. Our results suggest that simulations of the evolution of future mass balance using an energy balance model require very accurate meteorological data. Given the uncertainties in the temporal evolution of the relevant meteorological variables and glacier surface properties in the future, empirical approaches based on temperature and precipitation could be more appropriate for simulations of glaciers in the future.

scholarly journals Relative performance of empirical and physical models in assessing seasonal and annual glacier surface mass balance in the French Alps

2017 ◽  
Author(s):  
Marion Réveillet ◽  
Delphine Six ◽  
Christian Vincent ◽  
Antoine Rabatel ◽  
Marie Dumont ◽  
...  
Keyword(s):  
Energy Balance ◽  
Mass Balance ◽  
Meteorological Data ◽  
Model Performance ◽  
Surface Mass Balance ◽  
Glacier Surface ◽  
Meteorological Forcing ◽  
Surface Mass ◽  
The Future

Abstract. This study focuses on simulations of the seasonal and annual surface mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the period 1996-2015 using the detailed SURFEX/ISBA-Crocus snowpack model. The model is forced by SAFRAN meteorological reanalysis data, adjusted with AWS measurements to ensure that simulations of all the energy balance components, in particular turbulent fluxes, are accurately represented with respect to the measured energy balance. Results indicate good model performance for the simulation of summer SMB when using meteorological forcing adjusted with in-situ measurements. Model performance however strongly decreases without in-situ meteorological measurements. The sensitivity of the model to meteorological forcing indicates a strong sensitivity to wind speed, higher than the sensitivity to ice albedo. Compared to an empirical approach, the model exhibited better performance for simulations of snow and firn melting in the accumulation area and similar performance in the ablation area when forced with meteorological data adjusted with nearby AWS measurements. When such measurements were not available close to the glacier, the empirical model performed better. Our results suggest that simulations of the evolution of mass balance in the future using energy balance model required very accurate meteorological data which are not reliable from the climatic scenarios. With the current status of knowledge on meteorological variables and glacier surface roughness in the future, empirical approaches based on temperature and precipitation could be more appropriate for simulations of glaciers in the future.

scholarly journals The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms

2016 ◽  
Vol 20 (2) ◽  
pp. 803-822 ◽  
Author(s):  
D. Michel ◽  
C. Jiménez ◽  
D. G. Miralles ◽  
M. Jung ◽  
M. Hirschi ◽  
...  
Keyword(s):  
Water Cycle ◽  
Meteorological Data ◽  
Model Performance ◽  
Set Covering ◽  
Laboratory Model ◽  
Data Sets ◽  
Data Set ◽  
Balance System ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2  =  0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2  =  0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global estimates) confirmed the original findings.

scholarly journals The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote sensing-based evapotranspiration algorithms

2015 ◽  
Vol 12 (10) ◽  
pp. 10739-10787 ◽  
Author(s):  
D. Michel ◽  
C. Jiménez ◽  
D. G. Miralles ◽  
M. Jung ◽  
M. Hirschi ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Model Performance ◽  
Set Covering ◽  
Laboratory Model ◽  
Data Sets ◽  
Data Set ◽  
Balance System ◽  
Absolute Agreement ◽  
Wet Climate

Abstract. The WACMOS-ET project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run 4 established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODIS evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in-situ meteorological data from 24 FLUXNET towers was used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed across several time scales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement to the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2 = 0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2 = 0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs re-sampled to a common grid to facilitate global estimates) confirmed the original findings.

scholarly journals A 18-yr long (1993–2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.) for driving and evaluating snowpack models

2012 ◽  
Vol 5 (1) ◽  
pp. 29-45 ◽  
Author(s):  
S. Morin ◽  
Y. Lejeune ◽  
B. Lesaffre ◽  
J.-M. Panel ◽  
D. Poncet ◽  
...  
Keyword(s):  
Snow Depth ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Model Performance ◽  
Short Wave ◽  
Wave Radiation ◽  
Density Profiles ◽  
The Public ◽  
Snow Water

Abstract. A quality-controlled snow and meteorological dataset spanning the period 1 August 1993–31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist in measurements of air temperature, relative humidity, wind speed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow- and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gap-free record. Evaluation data are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information are provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free "settling" disks. This dataset has been partially used in the past to assist in developing snowpack model and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (http://doi.pangaea.de/10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.

A first look at ERA5 for physically based water balance modelling of the Devoll Catchment, Albania

2020 ◽  
Author(s):  
María Herminia Pesci ◽  
Fenja Voges ◽  
Nils Rüther ◽  
Kristian Förster
Keyword(s):  
Water Balance ◽  
Meteorological Data ◽  
Model Performance ◽  
Data Availability ◽  
Capital City ◽  
High Temporal Resolution ◽  
Time Step ◽  
Reanalysis Dataset ◽  
River Catchment ◽  
Physically Based

<p>The need for effective water resources management has turned into a major challenge, especially in the face of climate change. Meteorological data is not always readily available and thus the task of predicting the response of hydrological systems becomes complicated. For this reason, climate reanalysis datasets are used as a viable alternative. They combine models with data from satellites and ground sensors and provide consistent long-term meteorological conditions with high temporal resolution. The ERA5 reanalysis dataset was produced and is continuously updated by the European Centre for Medium-Range Weather Forecasts (ECMWF). Within this framework, the ERA5 reanalysis dataset has been applied to predict the hydrological response of the Devoll River catchment in Albania. Due to its location, Albania belongs to the Mediterranean climatic belt, which is characterized by hot dry summers and mild rainy winters. The Devoll River catchment is situated south from the capital city Tirana and covers a surface of around 3140 km<sup>2</sup>. The flow regime of this catchment consists mainly of snowmelt in the upstream mountainous part, whereas precipitation dominates the lower regions. The simulation of the different flow components was carried out with the latest version of the Water Balance and Simulation Model (WaSiM) on a daily time step. The performance of the simulation was evaluated with the Nash-Sutcliffe (NSE) and the Kling-Gupta (KGE) efficiencies, yielding values of 0.66 and 0.80, respectively. Although the model performance suggests some deficiencies, it is considered satisfactory given that ERA5 is a reanalysis dataset with modelled precipitation fields. From the resulting hydrographs, it is possible to infer that observed and simulated runoff follow the same dynamics and a close correspondence between flow peaks can be achieved. These results finally reinforce the idea of applying ERA5 datasets in cases where meteorological input data availability is low or even absent.</p>

{10-12} Twinning Mechanism During In Situ Micro-Tensile Loading of Pure Mg: Role of Basal Slip and Twin-Twin Boundary Interaction

2020 ◽  
Author(s):  
Nicolò Maria della Ventura ◽  
Szilvia Kalácska ◽  
Daniele Casari ◽  
Thomas Edward James Edwards ◽  
Johann Michler ◽  
...  
Keyword(s):  
Twin Boundary ◽  
Basal Slip ◽  
Tensile Loading ◽  
Boundary Interaction

The role of (bio)surfactant sorption in promoting the bioavailability of nutrients localized at the solid-water interface

1999 ◽  
Vol 39 (7) ◽  
pp. 91-98 ◽  
Author(s):  
Ryan N. Jordan ◽  
Eric P. Nichols ◽  
Alfred B. Cunningham
Keyword(s):  
Mass Transfer ◽  
Cell Membrane ◽  
Substrate Concentration ◽  
Water Interface ◽  
Industrial Systems ◽  
Solid Liquid Interface ◽  
Solid Liquid ◽  
Surfactant Sorption

Bioavailability is herein defined as the accessibility of a substrate by a microorganism. Further, bioavailability is governed by (1) the substrate concentration that the cell membrane “sees,” (i.e., the “directly bioavailable” pool) as well as (2) the rate of mass transfer from potentially bioavailable (e.g., nonaqueous) phases to the directly bioavailable (e.g., aqueous) phase. Mechanisms by which sorbed (bio)surfactants influence these two processes are discussed. We propose the hypothesis that the sorption of (bio)surfactants at the solid-liquid interface is partially responsible for the increased bioavailability of surface-bound nutrients, and offer this as a basis for suggesting the development of engineered in-situ bioremediation technologies that take advantage of low (bio)surfactant concentrations. In addition, other industrial systems where bioavailability phenomena should be considered are addressed.

THE ROLE OF BACTERIAL COMMUNITIES ON IN-SITU ARSENIC AND IRON CYCLING IN RIVERBANKS ALONG THE MEGHNA RIVER, BANGLADESH

2020 ◽  
Author(s):  
Kimberly D. Myers ◽  
◽  
Katrina Lee Jewell ◽  
P.S.K. Knappett ◽  
Mehtaz M. Lipsi ◽  
...  
Keyword(s):  
Bacterial Communities ◽  
Iron Cycling
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