%0 Conference Paper %1 Steele2018Using %A Steele, Edward %A Neal, Robert %A Dankers, Rutger %A Fournier, Nicolas %A Mylne, Kenneth %A Newell, Paul %A Saulter, Andrew %A Skea, Alasdair %A Upton, Jon %B Offshore Technology Conference %D 2018 %I Offshore Technology Conference %K MySeclifirmWTwork circulation colleagues economicvalue energy marine monthly nwp renewables weathertypes %R 10.4043/28784-ms %T Using Weather Pattern Typology to Identify Calm Weather Windows for Local Marine Operations %U http://dx.doi.org/10.4043/28784-ms %X The cost and complexity of offshore operations, combined with the vulnerability of equipment to prevailing conditions, requires weather-sensitive decisions to be made to ensure the continued accessibility and availability of marine assets. In the current economic context, this is especially important since the robust (timely) identification of calm weather windows has the potential to save many thousands of dollars per day in unplanned downtime and vessel contracting, allowing large efficiencies in sequencing, mobilisation and demobilisation costs if decisions are taken at the earliest possible opportunity. As forecasts extend weeks to months ahead, it is well known that predictability limits make the direct characterisation of small-scale weather events all but impossible, but there still remains a considerable amount of useful information contained within the large-scale weather circulation types. These circulation types, termed 'weather patterns', have a strong influence on the variability of marine wind and wave fields. Here, we present a new method for the tracking of calm weather windows out to several weeks ahead. Using a 34-year hindcast to elicit the daily maximum significant wave height experienced at the location of interest – and an analysis of the associated weather pattern under which they occurred – the circulation types are linked to the viability of offshore operations on a local scale. When subsequently applied in forecast mode, this method can enable earlier decision-making than is typically done at present. As weather patterns are more predictable than the actual weather itself at long lead-times, knowledge of the corresponding historic wave heights can enable identification of expected conditions within a probabilistic weather pattern forecasting system. In addition, the approach facilitates contingency planning; further supporting improved decision-making and reduced operational costs for the offshore oil and gas and marine renewable energy sector.

@inproceedings{Steele2018Using, abstract = {The cost and complexity of offshore operations, combined with the vulnerability of equipment to prevailing conditions, requires weather-sensitive decisions to be made to ensure the continued accessibility and availability of marine assets. In the current economic context, this is especially important since the robust (timely) identification of calm weather windows has the potential to save many thousands of dollars per day in unplanned downtime and vessel contracting, allowing large efficiencies in sequencing, mobilisation and demobilisation costs if decisions are taken at the earliest possible opportunity. As forecasts extend weeks to months ahead, it is well known that predictability limits make the direct characterisation of small-scale weather events all but impossible, but there still remains a considerable amount of useful information contained within the large-scale weather circulation types. These circulation types, termed 'weather patterns', have a strong influence on the variability of marine wind and wave fields. Here, we present a new method for the tracking of calm weather windows out to several weeks ahead. Using a 34-year hindcast to elicit the daily maximum significant wave height experienced at the location of interest – and an analysis of the associated weather pattern under which they occurred – the circulation types are linked to the viability of offshore operations on a local scale. When subsequently applied in forecast mode, this method can enable earlier decision-making than is typically done at present. As weather patterns are more predictable than the actual weather itself at long lead-times, knowledge of the corresponding historic wave heights can enable identification of expected conditions within a probabilistic weather pattern forecasting system. In addition, the approach facilitates contingency planning; further supporting improved decision-making and reduced operational costs for the offshore oil and gas and marine renewable energy sector.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Steele, Edward and Neal, Robert and Dankers, Rutger and Fournier, Nicolas and Mylne, Kenneth and Newell, Paul and Saulter, Andrew and Skea, Alasdair and Upton, Jon}, biburl = {https://www.bibsonomy.org/bibtex/27bcb3351a6f5dfa3270f6a3d9eb6cc89/pbett}, booktitle = {Offshore Technology Conference}, citeulike-article-id = {14579985}, citeulike-attachment-1 = {steele_etal_2018_otc_S1.pdf; /pdf/user/pbett/article/14579985/1135868/steele_etal_2018_otc_S1.pdf; 4e6b27da10ae397f2f804ef3162e5d79dc70ad65}, citeulike-linkout-0 = {http://dx.doi.org/10.4043/28784-ms}, comment = {(private-note)Cites me. Preprint attached.}, day = 24, doi = {10.4043/28784-ms}, file = {steele_etal_2018_otc_S1.pdf}, interhash = {0041424bcf0210a1e520f7a526191bd3}, intrahash = {7bcb3351a6f5dfa3270f6a3d9eb6cc89}, keywords = {MySeclifirmWTwork circulation colleagues economicvalue energy marine monthly nwp renewables weathertypes}, location = {Houston, Texas, USA}, month = apr, posted-at = {2018-05-02 18:19:58}, priority = {2}, publisher = {Offshore Technology Conference}, timestamp = {2019-08-14T12:56:31.000+0200}, title = {Using Weather Pattern Typology to Identify Calm Weather Windows for Local Marine Operations}, url = {http://dx.doi.org/10.4043/28784-ms}, year = 2018 }