Modeling evaporation from northern waterbodies, the case of an 85-km2 reservoir

Author(s):  
Habiba Kallel ◽  
Murray Mackay ◽  
Antoine Thiboult ◽  
Daniel Nadeau ◽  
François Anctil

<p>Freshwater bodies represent 9% of Canada’s total land area, with more than half of these having a surface area smaller than 100 km<sup>2</sup>. Taking into account the interactions between lakes and the atmosphere in meteorological models is crucial, considering the marked differences with the surrounding land masses (low albedo, unlimited source of water, high thermal capacity, etc.). Open water evaporation, in particular, is often a challenge because of its intangible nature and the scarcity of direct observations. This project focuses on the modeling of the surface energy budget of a reservoir located in the boreal biome of eastern Canada, with an emphasis on the evaporation. Observations are available for the 85-km<sup>2</sup> La Romaine 2 hydroelectric reservoir (50.7°N, 63.2°W), where two micrometeorological towers were deployed: one operated yearlong on the shore and one operated on a floating deck during ice-free conditions. Modeling resorts to the Canadian Small Lake Model (CSLM), a one-dimensional land surface model designed to integrate the lake-atmosphere fluxes into meteorological models. The model also simulates the thermal regime of the water body, including ice formation. Lastly, the model can be used for climate and weather prediction, which may be a useful for reservoir management. Comparison of field observations and simulations confirms the CSLM ability to reproduce the turbulent fluxes and the temperature behavior of the reservoir except for some specific periods, in particular the ice breakups and freeze-ups. The model somehow underestimates the water temperature resulting in a premature depletion of the lake heat storage in autumn. It also overreacts to high wind episodes.</p>

2014 ◽  
Vol 5 (2) ◽  
pp. 441-469 ◽  
Author(s):  
L. Wang-Erlandsson ◽  
R. J. van der Ent ◽  
L. J. Gordon ◽  
H. H. G. Savenije

Abstract. Moisture recycling, the contribution of terrestrial evaporation to precipitation, has important implications for both water and land management. Although terrestrial evaporation consists of different fluxes (i.e. transpiration, vegetation interception, floor interception, soil moisture evaporation, and open-water evaporation), moisture recycling (terrestrial evaporation–precipitation feedback) studies have up to now only analysed their combined total. This paper constitutes the first of two companion papers that investigate the characteristics and roles of different evaporation fluxes for land–atmosphere interactions. Here, we investigate the temporal characteristics of partitioned evaporation on land and present STEAM (Simple Terrestrial Evaporation to Atmosphere Model) – a hydrological land-surface model developed to provide inputs to moisture tracking. STEAM estimates a mean global terrestrial evaporation of 73 900 km3 year-1, of which 59% is transpiration. Despite a relatively simple model structure, validation shows that STEAM produces realistic evaporative partitioning and hydrological fluxes that compare well with other global estimates over different locations, seasons, and land-use types. Using STEAM output, we show that the terrestrial residence timescale of transpiration (days to months) has larger inter-seasonal variation and is substantially longer than that of interception (hours). Most transpiration occurs several hours or days after a rain event, whereas interception is immediate. In agreement with previous research, our simulations suggest that the vegetation's ability to transpire by retaining and accessing soil moisture at greater depth is critical for sustained evaporation during the dry season. We conclude that the differences in temporal characteristics between evaporation fluxes are substantial and reasonably can cause differences in moisture recycling, which is investigated more in the companion paper (van der Ent et al., 2014, hereafter Part 2).


2012 ◽  
Vol 13 (3) ◽  
pp. 1119-1130 ◽  
Author(s):  
M. Jahanzeb Malik ◽  
Rogier van der Velde ◽  
Zoltan Vekerdy ◽  
Zhongbo Su

Abstract This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado) that are part of the 2002/03 Cold Land Processes Field Experiment (CLPX). The assimilated snow albedo products are 1) the standard Moderate Resolution Imaging Spectrometer (MODIS) product (MOD10A1) and 2) retrievals from MODIS observations with the recently developed Pattern-Based Semiempirical (PASS) approach. The performance of the Noah simulations, with and without assimilation, is evaluated using the in situ measurements of snow albedo, upward shortwave radiation, and snow depth. The results show that simulations with albedo assimilation agree better with the measurements. However, because of the limited impact of snow albedo updates after subsequent snowfall, the mean (or seasonal) error statistics decrease significantly for only two of the three CLPX sites. Though the simulated snow depth and duration for the snow season benefit from the assimilation, the greatest improvements are found in the simulated upward shortwave radiation, with root mean squared errors reduced by about 30%. As such, this study demonstrates that assimilation of satellite-observed snow albedo can improve LSM simulations, which may positively affect the representation of hydrological and surface energy budget processes in runoff and numerical weather prediction models.


2021 ◽  
Author(s):  
Gianpaolo Balsamo ◽  
Souhail Boussetta

<p>The ECMWF operational land surface model, based on the Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) is the baseline for global weather, climate and environmental applications at ECMWF. In order to expedite its progress and benefit from international collaboration, an ECLand platform has been designed to host advanced and modular schemes. ECLand is paving the way toward a land model that could support a wider range of modelling applications, facilitating global kilometer scales testing as envisaged in the Copernicus and Destination Earth programmes. This presentation introduces the CHTESSEL and its recent new developments that aims at hosting new research applications.</p><p>These new improvements touch upon different components of the model: (i) vegetation, (ii) snow, (iii) soil hydrology, (iv) open water/lakes (v) rivers and (vi) urban areas. The developments are evaluated separately with either offline simulations or coupled experiments, depending on their level of operational readiness, illustrating the benchmarking criteria for assessing process fidelity with regards to land surface fluxes and reservoirs involved in water-energy-carbon exchange, and within the Earth system prediction framework, as foreseen to enter upcoming ECMWF operational cycles.</p><p>Reference: Souhail Boussetta, Gianpaolo Balsamo*, Anna Agustì-Panareda, Gabriele Arduini, Anton Beljaars, Emanuel Dutra, Glenn Carver, Margarita Choulga, Ioan Hadade, Cinzia Mazzetti, Joaquìn Munõz-Sabater, Joe McNorton, Christel Prudhomme, Patricia De Rosnay, Irina Sandu, Nils Wedi, Dai Yamazaki, Ervin Zsoter, 2021: ECLand: an ECMWF land surface modelling platform, MDPI Atmosphere, (in prep).</p>


2014 ◽  
Vol 7 (1) ◽  
pp. 361-386 ◽  
Author(s):  
D. N. Walters ◽  
K. D. Williams ◽  
I. A. Boutle ◽  
A. C. Bushell ◽  
J. M. Edwards ◽  
...  

Abstract. We describe Global Atmosphere 4.0 (GA4.0) and Global Land 4.0 (GL4.0): configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) community land surface model developed for use in global and regional climate research and weather prediction activities. GA4.0 and GL4.0 are based on the previous GA3.0 and GL3.0 configurations, with the inclusion of developments made by the Met Office and its collaborators during its annual development cycle. This paper provides a comprehensive technical and scientific description of GA4.0 and GL4.0 as well as details of how these differ from their predecessors. We also present the results of some initial evaluations of their performance. Overall, performance is comparable with that of GA3.0/GL3.0; the updated configurations include improvements to the science of several parametrisation schemes, however, and will form a baseline for further ongoing development.


2018 ◽  
Vol 19 (12) ◽  
pp. 1917-1933 ◽  
Author(s):  
Li Fang ◽  
Xiwu Zhan ◽  
Christopher R. Hain ◽  
Jifu Yin ◽  
Jicheng Liu

Abstract Green vegetation fraction (GVF) plays a crucial role in the atmosphere–land water and energy exchanges. It is one of the essential parameters in the Noah land surface model (LSM) that serves as the land component of a number of operational numerical weather prediction models at the National Centers for Environmental Prediction (NCEP) of NOAA. The satellite GVF products used in NCEP models are derived from a simple linear conversion of either the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) currently or the enhanced vegetation index (EVI) from the Visible Infrared Imaging Radiometer Suite (VIIRS) planned for the near future. Since the NDVI or EVI is a simple spectral index of vegetation cover, GVFs derived from them may lack the biophysical meaning required in the Noah LSM. Moreover, the NDVI- or EVI-based GVF data products may be systematically biased over densely vegetated regions resulting from the saturation issue associated with spectral vegetation indices. On the other hand, the GVF is physically related to the leaf area index (LAI), and thus it could be beneficial to derive GVF from LAI data products. In this paper, the EVI-based and the LAI-based GVF derivation methods are mathematically analyzed and are found to be significantly different from each other. Impacts of GVF differences on the Noah LSM simulations and on weather forecasts of the Weather Research and Forecasting (WRF) Model are further assessed. Results indicate that LAI-based GVF outperforms the EVI-based one when used in both the offline Noah LSM and WRF Model.


Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 815
Author(s):  
Marcelo Somos-Valenzuela ◽  
Francisco Manquehual-Cheuque

The use of numerical weather prediction (NWP) model to dynamically downscale coarse climate reanalysis data allows for the capture of processes that are influenced by land cover and topographic features. Climate reanalysis downscaling is useful for hydrology modeling, where catchment processes happen on a spatial scale that is not represented in reanalysis models. Selecting proper parameterization in the NWP for downscaling is crucial to downscale the climate variables of interest. In this work, we are interested in identifying at least one combination of physics in the Weather Research Forecast (WRF) model that performs well in our area of study that covers the Baker River Basin and the Northern Patagonian Icecap (NPI) in the south of Chile. We used ERA-Interim reanalysis data to run WRF in twenty-four different combinations of physics for three years in a nested domain of 22.5 and 4.5 km with 34 vertical levels. From more to less confident, we found that, for the planetary boundary layer (PBL), the best option is to use YSU; for the land surface model (LSM), the best option is the five-Layer Thermal, RRTM for longwave, Dudhia for short wave radiation, and Thompson for the microphysics. In general, the model did well for temperature (average, minimum, maximum) for most of the observation points and configurations. Precipitation was good, but just a few configurations stood out (i.e., conf-9 and conf-10). Surface pressure and Relative Humidity results were not good or bad, and it depends on the statistics with which we evaluate the time series (i.e., KGE or NSE). The results for wind speed were inferior; there was a warm bias in all of the stations. Once we identify the best configuration in our experiment, we run WRF for one year using ERA5 and FNL0832 climate reanalysis. Our results indicate that Era-interim provided better results for precipitation. In the case of temperature, FNL0832 gave better results; however, all of the models’ performances were good. Therefore, working with ERA-Interim seems the best option in this region with the physics selected. We did not experiment with changes in resolution, which may have improved results with ERA5 that has a better spatial and temporal resolution.


2017 ◽  
Vol 10 (4) ◽  
pp. 1487-1520 ◽  
Author(s):  
David Walters ◽  
Ian Boutle ◽  
Malcolm Brooks ◽  
Thomas Melvin ◽  
Rachel Stratton ◽  
...  

Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.


2013 ◽  
Vol 6 (2) ◽  
pp. 2813-2881 ◽  
Author(s):  
D. N. Walters ◽  
K. D. Williams ◽  
I. A. Boutle ◽  
A. C. Bushell ◽  
J. M. Edwards ◽  
...  

Abstract. We describe Global Atmosphere 4.0 (GA4.0) and Global Land 4.0 (GL4.0): configurations of the Met Office Unified Model and JULES community land surface model developed for use in global and regional climate research and weather prediction activities. GA4.0 and GL4.0 are based on the previous GA3.0 and GL3.0 configurations, with the inclusion of developments made by the Met Office and its collaborators during its annual development cycle. This paper provides a comprehensive technical and scientific description of GA4.0 and GL4.0 as well as details of how these differ from their predecessors. We also present the results of some initial evaluations of their performance. These show that, overall, performance is comparable with that of GA3.0/GL3.0; the updated configurations do, however, include improvements to the science of several parametrization schemes and will form a baseline for further ongoing development.


2021 ◽  
Author(s):  
John Edwards

<p>The parametrization of land-atmosphere interactions in numerical weather prediction and climate models is a topic of active and growing interest, especially in connection with extreme events such as heat waves and droughts. Semiarid regions are sensitive to drought and are currently expanding, but they are often poorly represented in numerical models. On forecasting timescales, comparisons of simulated land surface temperature against retrievals from satellites often show significant cold biases around noon, whilst, on climate timescales, land surface models often fail to represent droughts realistically. Inadequate treatment of the land surface, and particularly of soil properties and soil moisture, is likely to contribute to such errors.</p> <p>Efforts to develop improved parametrizations of soil processes in the JULES land surface model for application in weather prediction and climate simulations are underway. Whilst processes at the soil surface are a central part of this, to obtain acceptable performance it is also important to consider the surface flux budget as a whole, including the treatment of the plant canopy. Here, we shall describe the current status of developments aimed at improving the representation of evapotranspiration and ground heat fluxes in the model, noting the major issues encountered. The importance of accurately representing the impact of soil moisture on thermal properties will be stressed. Results from initial studies will be presented and we shall offer a perspective on future developments.<br /><br /></p>


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