Farm Planning
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Author(s):  
Fleur J. F. Maseyk ◽  
Estelle J. Dominati ◽  
Russell G. Death ◽  
Alec D. Mackay

Author(s):  
Simon Stokes ◽  
Katrina A. Macintosh ◽  
Richard W. McDowell
Keyword(s):  

2020 ◽  
Vol 5 (1) ◽  
pp. 285-308
Author(s):  
Erik Quaeghebeur ◽  
Michiel B. Zaaijer

Abstract. We present an analysis of three datasets of 10 min metocean measurement statistics and our resulting recommendations to both producers and users of such datasets. Many of our recommendations are more generally of interest to all numerical measurement data producers. The datasets analyzed originate from offshore meteorological masts installed to support offshore wind farm planning and design: the Dutch OWEZ and MMIJ and the German FINO1. Our analysis shows that such datasets contain issues that users should look out for and whose prevalence can be reduced by producers. We also present expressions to derive uncertainty and bias values for the statistics from information typically available about sample uncertainty. We also observe that the format in which the data are disseminated is sub-optimal from the users' perspective and discuss how producers can create more immediately useful dataset files. Effectively, we advocate using an established binary format (HDF5 or netCDF4) instead of the typical text-based one (comma-separated values), as this allows for the inclusion of relevant metadata and the creation of significantly smaller directly accessible dataset files. Next to informing producers of the advantages of these formats, we also provide concrete pointers to their effective use. Our conclusion is that datasets such as the ones we analyzed can be improved substantially in usefulness and convenience with limited effort.


2020 ◽  
Vol 116 (1/2) ◽  
Author(s):  
Bright Chisadza ◽  
Abbyssinia Mushunje ◽  
Kenneth Nhundu ◽  
Ethel E. Phiri

The ability of smallholder farmers to utilise seasonal climate forecast (SCF) information in farm planning to reflect anticipated climate is a precursor to improved farm management. However, the integration of SCF by smallholder farmers into farm planning has been poor, partly because of the lack of forecast skill, lack of communication and inability to see the relevance of the SCFs for specific farming decisions. The relevance of seasonal climate forecasting in farming decisions can be enhanced through improved understanding of SCF from the smallholder farmers’ perspective. Studies that have been done of how smallholder farmers understand SCF and how the available SCFs influence smallholder farmers’ decisions are limited. Therefore, the objective of this paper was to review how smallholder farmers make decisions on farming practices based on SCFs and the challenges and opportunities thereof. The review shows that the majority of smallholder farmers in Africa make use of either scientific or indigenous knowledge climate forecasts and, in some cases, a combination of both. There are mixed results in the area of evaluating benefits of SCFs in decision-making and farm production. In some cases, the outcomes are positive, whereas in others they are difficult to quantify. Thus, the integration of SCFs into smallholder farmers’ decision-making is still a challenge. We recommend that significant work must be done to improve climate forecasts in terms of format, and spatial and temporal context in order for them to be more useful in influencing decision-making by smallholder farmers.


2019 ◽  
Vol 20 ◽  
pp. e00703
Author(s):  
Inka Veltheim ◽  
Simon Cook ◽  
Grant C. Palmer ◽  
F.A. Richard Hill ◽  
Michael A. McCarthy
Keyword(s):  

2019 ◽  
Author(s):  
Erik Quaeghebeur ◽  
Michiel B. Zaaijer

Abstract. We present an analysis of three metocean datasets of 10-minute statistics and our resulting recommendations to both producers and users of such datasets. Many of our recommendations are more generally of interest to all numerical measurement data producers. The datasets analyzed originate from offshore meteorological masts installed to support offshore wind farm planning and design: the Dutch OWEZ and MMIJ, and the German FINO 1. Our analysis shows that such datasets contain issues that users should look out for and whose prevalence can be reduced by producers. We also present expressions to derive uncertainty and bias values for the statistics from information typically available about sample uncertainty. We also observe that the format in which the data is disseminated is sub-optimal from the users' perspective and discuss how producers can create more immediately useful dataset files. Effectively, we advocate using an established binary format (HDF5 or netCDF4) instead of the typical text-based one (comma-separated values), as this allows for the inclusion of relevant metadata and the creation of significantly smaller directly accessible dataset files. Next to informing producers of the advantages of these formats, we also provide concrete pointers to their effective use. Our conclusion is that datasets such as the ones we analyzed can be improved substantially in usefulness and convenience with limited effort.


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