scholarly journals Seasonal Forecast Climate Data and Hydropower Production in the Douro Basin, in Portugal

2020 ◽  
Vol 2 (1) ◽  
pp. 71
Author(s):  
Paulo Alexandre Diogo ◽  
Pedro Beça ◽  
Sofia Simões ◽  
Filipa Amorim ◽  
Babar Mujtaba
Keyword(s):  
Power Systems ◽  
Rainfall Runoff ◽  
Climate Data ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Hydropower Production ◽  
Climate Service ◽  
Daily Scale ◽  
Douro River

The project CLIM2POWER aims at developing a climate service including state-of-the art seasonal climate forecasts in the planning of the operation of the power systems. This work presents part of the project, addressing the forecasting of the hydropower generation in a case study area, the Portuguese part of the transboundary Douro River basin. Rainfall-runoff modelling was performed on a daily scale using three ensemble members of seasonal climate data (six months) for Portuguese territory crossed with three daily inflow scenarios from Spanish territory defined according to historical observed data. The obtained results reflect the fact that seasonal climate forecast present a wide variation of scenarios and also the fact that hydropower production in Portuguese territory is highly dependent on transboundary inflows. On the other hand, the implemented approach successfully produced consistent runoff and hydropower production results although improvements on the identification of the most probable scenarios are yet required.

Value of seasonal climate forecasts in reducing economic losses for grazing enterprises: Charters Towers case study

2019 ◽  
Vol 41 (3) ◽  
pp. 165
Author(s):  
Duc-Anh An-Vo ◽  
Kate Reardon-Smith ◽  
Shahbaz Mushtaq ◽  
David Cobon ◽  
Shreevatsa Kodur ◽  
...  
Keyword(s):  
Decision Making ◽  
Economic Value ◽  
Simulation Software ◽  
Economic Losses ◽  
Economic Modelling ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Net Profit ◽  
Seasonal Climate Forecasts

Seasonal climate forecasts (SCFs) have the potential to improve productivity and profitability in agricultural industries, but are often underutilised due to insufficient evidence of the economic value of forecasts and uncertainty about their reliability. In this study we developed a bio-economic model of forecast use, explicitly incorporating forecast uncertainty. Using agricultural systems (ag-systems) production simulation software calibrated with case study information, we simulated pasture growth, herd dynamics and annual economic returns under different climatic conditions. We then employed a regret and value function approach to quantify the potential economic value of using SCFs (at both current and improved accuracy levels) in decision making for a grazing enterprise in north-eastern Queensland, Australia – a region subject to significant seasonal and intra-decadal climate variability. Applying an expected utility economic modelling approach, we show that skilled SCF systems can contribute considerable value to farm level decision making. At the current SCF skill of 62% (derived by correlating the El Niño Southern Oscillation (ENSO) signal and historical climate data) at Charters Towers, an average annual forecast value of AU$4420 (4.25%) was realised for the case study average annual net profit of AU$104000, while a perfect (no regret) forecast system could result in an increased return of AU$13475 per annum (13% of the case study average annual net profit). Continued improvements in the skill and reliability of SCFs is likely to both increase the value of SCFs to agriculture and drive wider uptake of climate forecasts in on-farm decision making. We also anticipate that an integrated framework, such as that developed in this study, may provide a pathway for better communication with end users to support improved understanding and use of forecasts in agricultural decision making and enhanced sustainability of agricultural enterprises.

scholarly journals Downscaling and Evaluation of Seasonal Climate Data for the European Power Sector

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 304
Author(s):  
Jennifer Ostermöller ◽  
Philip Lorenz ◽  
Kristina Fröhlich ◽  
Frank Kreienkamp ◽  
Barbara Früh
Keyword(s):  
Spatial Resolution ◽  
Empirical Method ◽  
Added Value ◽  
Climate Data ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Four Seasons ◽  
Hydropower Production ◽  
Climate Service ◽  
Technical Details

Within the Clim2Power project, two case studies focus on seasonal variations of the hydropower production in the river basins of the Danube (Germany/Austria) and the Douro (Portugal). To deliver spatially highly resolved climate data as an input for the hydrological models, the forecasts of the German Climate Forecast System (GCFS2.0) need to be downscaled. The statistical-empirical method EPISODES is used in this approach. It is adapted to the seasonal data, which consists of ensemble hindcasts and forecasts. Beside this, the two case study regions need specific configurations of the statistical model, providing appropriate predictors for the meteorological variables. This paper describes the technical details of the adaptation of the EPISODES method for the needs of Clim2Power. We analyse the hindcast skill of the downscaled hindcasts of all four seasons for the two variables near-surface (2 m) temperature and precipitation, and conclude that on the average the skill is conserved compared to the global model. This means that the seasonal information is available at a higher spatial resolution without losing skill. Furthermore, the output of the statistical downscaling is nearly bias-free, which is, beside the higher spatial resolution, an added value for the climate service.

What methods of interaction with users have proved to better perform for advanced co-development of climate services in the water sector?

2020 ◽  
Author(s):  
María José Polo ◽  
Rafael Pimentel ◽  
María José Pérez-Palazón ◽  
Pedro Torralbo ◽  
Little Lorna ◽  
...  
Keyword(s):  
Climate Scenarios ◽  
Climate Data ◽  
Water Sector ◽  
Online Surveys ◽  
Climate Services ◽  
Climate Service ◽  
Development Approach ◽  
Adequate Communication ◽  
Key Questions

<p>A wide offer of climate data sources/services is currently available dealing with future climate scenarios and projections. A huge effort has been done at European scale to promote and share openly this information. However, their use is not extensive and their potential is frequently underexploited. There is usually a significant gap between the complexity of climate metadata and the users’ capability of exploiting them. Furthermore, this gap is also found between the expertise of climate data providers and the every-day operation of the different potentially interested end-users. Additionally, in some sectors users are not aware of climate service capabilities which prevent them from valuing and then demanding such services.</p><p>In this context, co-development improves and fosters climate services’ usability and uptake when compared to a traditional one-side development approach, since it best meets users’ needs and demands. However, co-development can be time-consuming for both sides and less effective than expected if an adequate communication design is missing. In this context, what methods of interaction with users have proved to better perform for advanced co-development of climate services? And, what factors have best motivated users to interact? are key questions to provide guidelines and profit from the on-going initiatives.</p><p>Three different approaches with users (mainly in the water sector) were tested: guided online surveys (anonymous users); focus groups (users known to different partners in the project); case study clients (users regularly interact with project partners). Indicators and metrics were used to evaluate and value the contribution from each group in the context of co-development of climate services that give future projections of water availability. The results of this comparison provide a conceptual framework to design and apply co-development strategies for climate services oriented to different groups within the water sector.</p><p>This work was funded by the project AQUACLEW, which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Commission [Grant 690462].</p>

scholarly journals Taking into Consideration the Inclusion of Wind Generation in Hybrid Microgrids: A Methodology and a Case Study

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4082
Author(s):  
Luis Arribas ◽  
Natalia Bitenc ◽  
Andreo Benech
Keyword(s):  
Power Systems ◽  
Design Process ◽  
Research Community ◽  
Wind Generation ◽  
Generation System ◽  
Economic Barriers ◽  
Wind Generation System

During the last decades, there has been great interest in the research community with respect to PV-Wind systems but figures show that, in practice, only PV-Diesel Power Systems (PVDPS) are being implemented. There are some barriers for the inclusion of wind generation in hybrid microgrids and some of them are economic barriers while others are technical barriers. This paper is focused on some of the identified technical barriers and presents a methodology to facilitate the inclusion of wind generation system in the design process in an affordable manner. An example of the application of this methodology and its results is shown through a case study. The case study is an existing PVDPS where there is an interest to incorporate wind generation in order to cope with a foreseen increase in the demand.

Constraints and Suggestions in Adopting Seasonal Climate Forecasts by Farmers in South India

2011 ◽  
Vol 17 (2) ◽  
pp. 153-163 ◽  
Author(s):  
K. Ravi Shankar ◽  
K. Nagasree ◽  
B. Venkateswarlu ◽  
Pochaiah Maraty
Keyword(s):  
South India ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Seasonal Climate Forecasts

Encouraging use of seasonal climate forecasts by farmers

2005 ◽  
Vol 25 (8) ◽  
pp. 1127-1137 ◽  
Author(s):  
Rod McCrea ◽  
Len Dalgleish ◽  
Will Coventry
Keyword(s):  
Seasonal Climate ◽  
Climate Forecasts ◽  
Seasonal Climate Forecasts

Characterization of Oscillations in Developing Power Systems: The Nigerian Case Study

2021 ◽  
Author(s):  
Nnaemeka Sunday Ugwuanyi ◽  
Uma Uzubi Uma ◽  
Arthur Obiora Ekwue
Keyword(s):  
Power Systems

Regional biogeographical model of vegetation zones in doctoral programme Regional Biography in Olomouc (Case study for Norway spruce)

2020 ◽  
Author(s):  
Ivo Machar ◽  
Marián Halás ◽  
Zdeněk Opršal
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Climate Data ◽  
Ecological Data ◽  
The Czech Republic ◽  
Climate Conditions ◽  
Vegetation Zones ◽  
Landscape Research

Regional climate changes impacts induce vegetation zones shift to higher altitudes in temperate landscape. This paper deals with applying of regional biogeography model of climate conditions for vegetation zones in Czechia to doctoral programme Regional Geography in Palacky University Olomouc. The model is based on general knowledge of landscape vegetation zonation. Climate data for model come from predicted validated climate database under RCP8.5 scenario since 2100. Ecological data are included in the Biogeography Register database (geobiocoenological data related to landscape for cadastral areas of the Czech Republic). Mathematical principles of modelling are based on set of software solutions with GIS. Students use the model in the frame of the course “Special Approaches to Landscape Research” not only for regional scenarios climate change impacts in landscape scale, but also for assessment of climate conditions for growing capability of agricultural crops or forest trees under climate change on regional level.

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