Review of “The Multi-Assumption Architecture and Testbed (MAAT v1.0): Code for ensembles with dynamic model structure including a unified model of leaf-scale C3 photosynthesis” by Walker et al. for Geoscientific Model Development

2018 ◽  
Author(s):  
Nicholas Smith
Author(s):  
Moritz Buchholz ◽  
Johannes Haus ◽  
Fritz Polt ◽  
Swantje Pietsch ◽  
Michael Schönherr ◽  
...  

2021 ◽  
Author(s):  
Markus Hrachowitz ◽  
Petra Hulsman ◽  
Hubert Savenije

<p>Hydrological models are often calibrated with respect to flow observations at the basin outlet. As a result, flow predictions may seem reliable but this is not necessarily the case for the spatiotemporal variability of system-internal processes, especially in large river basins. Satellite observations contain valuable information not only for poorly gauged basins with limited ground observations and spatiotemporal model calibration, but also for stepwise model development. This study explored the value of satellite observations to improve our understanding of hydrological processes through stepwise model structure adaption and to calibrate models both temporally and spatially. More specifically, satellite-based evaporation and total water storage anomaly observations were used to diagnose model deficiencies and to subsequently improve the hydrological model structure and the selection of feasible parameter sets. A distributed, process based hydrological model was developed for the Luangwa river basin in Zambia and calibrated with respect to discharge as benchmark. This model was modified stepwise by testing five alternative hypotheses related to the process of upwelling groundwater in wetlands, which was assumed to be negligible in the benchmark model, and the spatial discretization of the groundwater reservoir. Each model hypothesis was calibrated with respect to 1) discharge and 2) multiple variables simultaneously including discharge and the spatiotemporal variability in the evaporation and total water storage anomalies. The benchmark model calibrated with respect to discharge reproduced this variable well, as also the basin-averaged evaporation and total water storage anomalies. However, the evaporation in wetland dominated areas and the spatial variability in the evaporation and total water storage anomalies were poorly modelled. The model improved the most when introducing upwelling groundwater flow from a distributed groundwater reservoir and calibrating it with respect to multiple variables simultaneously. This study showed satellite-based evaporation and total water storage anomaly observations provide valuable information for improved understanding of hydrological processes through stepwise model development and spatiotemporal model calibration.</p>


2018 ◽  
Vol 11 (9) ◽  
pp. 3647-3657 ◽  
Author(s):  
Nathan Luke Abraham ◽  
Alexander T. Archibald ◽  
Paul Cresswell ◽  
Sam Cusworth ◽  
Mohit Dalvi ◽  
...  

Abstract. The Met Office Unified Model (UM) is a state-of-the-art weather and climate model that is used operationally worldwide. UKCA is the chemistry and aerosol sub model of the UM that enables interactive composition and physical atmosphere interactions, but which adds an additional 120 000 lines of code to the model. Ensuring that the UM code and UM-UKCA (the UM running with interactive chemistry and aerosols) is well tested is thus essential. While a comprehensive test harness is in place at the Met Office and partner sites to aid in development, this is not available to many UM users. Recently, the Met Office have made available a virtual machine environment that can be used to run the UM on a desktop or laptop PC. Here we describe the development of a UM-UKCA configuration that is able to run within this virtual machine while only needing 6 GB of memory, before discussing the applications of this system for model development, testing, and training.


2018 ◽  
Vol 9 (3) ◽  
pp. 48-57
Author(s):  
Abdel Karim M. Baareh

Temperature study and model development related to estimation is an essential and important task not only for a human life but also for animal life, agriculture, tourism, water reservation and evaporation, and many other fields. Regression is considered a dominant prediction model which is heavily used in forecasting in spite of the difficulties related to the number of available measurements, the order of the model and the nonlinearity of the data. In this article, the purpose is to use a nonlinear model structure to forecast the temperature at the airport of Mumbai city in India using the fuzzy logic technique. The datasets were collected for twelve months period starting from 1st of January 2009 to 31st of December at a weather underground in India. The datasets were divided into two parts, 288 days (80%) of the data for training and the remaining 72 days (20%) for testing. The results obtained and the error calculated using the fuzzy logic model were satisfactory.


2011 ◽  
Vol 6 (1) ◽  
Author(s):  
Glen Hay ◽  
John Nighswander

A project team was given the task of evaluating various technology options for design of a small-scale gas-to-liquids (GTL) process operated remotely at or near an individual gas source. For this study, small-scale plants were considered those producing between 100 and 500 barrels per day of liquid fuels. In addition, being remote enforced limitations on utility sources available to the plant site such as water and grid power. A secondary goal was development of a dynamic model of the plant to use in operator training. To accomplish these objectives, the authors investigated the suitability of a process-simulation application. The conceptual design of the GTL unit included many different possibilities, such as front-end design, back-end design, heat integration, and recycling of materials. Complications associated with plant start-up and shutdown, utilities, process reliability, and economics were included in the decision-making process. The authors present selective results from a steady-state model and sensitivity studies. Considerations for the development of the dynamic model included both a fully rigorous dynamic model and a pseudo-dynamic steady-state-based model; results of the latter model are provided. The study concluded that an industrial steady-state simulation tool provided sufficient flexibility to complete the material and energy-balance calculations, sensitivity analyses, and pseudo-dynamic modeling. This study yielded significant insights into the importance of model assumptions and their impact on the overall process viability. The pseudo-dynamic model also provided insight for improving the process control design. During the work completed the authors determined that the object-oriented structure adopted for the model enabled an efficient, rapid model development.


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