The most viable solution for PAG-ASA is a comprehensive modernization of its weather forecasting capabilities. First and foremost, it should start installing basic devices such as the Doppler Radar which is very useful in predicting amount of rainfall. However, the underlying principle PAG-ASA must consider is that to be able to provide accurate and timely weather information, it must continuously upgrade its capabilities in both hardware (workstations, servers, telecommunication lines and terminals, specialized radars, satellites and other specialized atmospheric data reader) and software aspects (program codes, models, compilers, data translators, etc.)
PAG-ASA is claiming that it uses the most advanced weather prediction model in MM5, but actually there were already newer model versions developed that succeeded MM5. If PAG-ASA does not allot effort and resources to upgrade its hardware facilities as well as learn these newer models, then we cannot take advantage of the benefits that IT advancement is currently offering. For example, MM5 resolution ranges from 20 km to 60 km but with the newer model, it can even scale from up to several meters to thousand of kilometers.
NCAR in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and other meteorological agencies and weather forecasting laboratories worldwide recently introduced the Weather Research and Forecasting (WRF) Model which is the next-generation mesoscale numerical weather prediction system. WRF like the MM5 is developed through an open source approach, but unlike the MM5, WRF is the first model to have both operational forecasting capabilities and simulation features for research needs. It offers flexible and efficient computations for operational weather forecasting that considers physics and numerics while on the other hand can also conduct simulations using actual or idealized data for research purposes. The software architecture of the WRF supports computational parallelism, system extensibility, multiple dynamic cores and 3-dimensional variational data assimilation system. WRF also incorporates data from satellites, radars, and a wide range of other tools with greater ease than earlier models, thus the model outperformed its predecessors in more than 70% of the situations.
WRF is also freely provided by the NCAR. If PAG-ASA is not been able to capitalize on this latest IT enhancement, then it is foregoing the opportunity to have an efficient and flexible operation forecasting model with research capabilities. Of course there will be resources and efforts needed in order for PAG-ASA to shift from its existing forecasting models to the newer ones. Amongst them are:
(a) Upgrading hardware that will support the new forecast modeling software system
(b) Technical skills and know-how in running the program codes of the new model
(c) Trainings and workshops for PAG-ASA employees in relation to using the new model
(d) New set of license needed in operating the model
However, most probable than not that the gain from modernization of PAG-ASA’s IT capabilities can surely outweigh the costs associated in implementing new model and installing new set of hardware and programs.
International meteorological agencies such as the National Center for Atmospheric Research are important organization that PAG-ASA must create good alliance with. NCAR has the technology, knowledge and capabilities in developing state-of-the art weather forecasting models that PAG-ASA cannot do on its own. NCAR also has a wide range of experience in collaborating efforts with established weather agencies and laboratories worldwide in the development and continuous improvement of technology-based forecasting models such as the WRF. Amongst NCAR’s partners in developing WRF are the National Oceanic and Atmospheric Administration (the National Centers for Environmental Prediction (NCEP) and the Forecast Systems Laboratory (FSL), the Air Force Weather Agency (AFWA), the Naval Research Laboratory, the University of Oklahoma, and the Federal Aviation Administration (FAA). In addition, program codes contributed by the community of users are also considered in developing and improving models. This open source approach will make it easier for PAG-ASA to be kept updated. Furthermore, workshops, tutorials, supports and program code updates are also provided to users by NCAR and therefore we don’t see any major problem that will arise should PAG-ASA opt to be one of the 4,000 registered users of WRF in 77 countries.
(Sources and related links: http://www.wrf-model.org/index.php; http://www.inergizedigital.com/news/WDTPressRelease-January-27-2009.pdf)
PAG-ASA is claiming that it uses the most advanced weather prediction model in MM5, but actually there were already newer model versions developed that succeeded MM5. If PAG-ASA does not allot effort and resources to upgrade its hardware facilities as well as learn these newer models, then we cannot take advantage of the benefits that IT advancement is currently offering. For example, MM5 resolution ranges from 20 km to 60 km but with the newer model, it can even scale from up to several meters to thousand of kilometers.
NCAR in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and other meteorological agencies and weather forecasting laboratories worldwide recently introduced the Weather Research and Forecasting (WRF) Model which is the next-generation mesoscale numerical weather prediction system. WRF like the MM5 is developed through an open source approach, but unlike the MM5, WRF is the first model to have both operational forecasting capabilities and simulation features for research needs. It offers flexible and efficient computations for operational weather forecasting that considers physics and numerics while on the other hand can also conduct simulations using actual or idealized data for research purposes. The software architecture of the WRF supports computational parallelism, system extensibility, multiple dynamic cores and 3-dimensional variational data assimilation system. WRF also incorporates data from satellites, radars, and a wide range of other tools with greater ease than earlier models, thus the model outperformed its predecessors in more than 70% of the situations.
WRF is also freely provided by the NCAR. If PAG-ASA is not been able to capitalize on this latest IT enhancement, then it is foregoing the opportunity to have an efficient and flexible operation forecasting model with research capabilities. Of course there will be resources and efforts needed in order for PAG-ASA to shift from its existing forecasting models to the newer ones. Amongst them are:
(a) Upgrading hardware that will support the new forecast modeling software system
(b) Technical skills and know-how in running the program codes of the new model
(c) Trainings and workshops for PAG-ASA employees in relation to using the new model
(d) New set of license needed in operating the model
However, most probable than not that the gain from modernization of PAG-ASA’s IT capabilities can surely outweigh the costs associated in implementing new model and installing new set of hardware and programs.
International meteorological agencies such as the National Center for Atmospheric Research are important organization that PAG-ASA must create good alliance with. NCAR has the technology, knowledge and capabilities in developing state-of-the art weather forecasting models that PAG-ASA cannot do on its own. NCAR also has a wide range of experience in collaborating efforts with established weather agencies and laboratories worldwide in the development and continuous improvement of technology-based forecasting models such as the WRF. Amongst NCAR’s partners in developing WRF are the National Oceanic and Atmospheric Administration (the National Centers for Environmental Prediction (NCEP) and the Forecast Systems Laboratory (FSL), the Air Force Weather Agency (AFWA), the Naval Research Laboratory, the University of Oklahoma, and the Federal Aviation Administration (FAA). In addition, program codes contributed by the community of users are also considered in developing and improving models. This open source approach will make it easier for PAG-ASA to be kept updated. Furthermore, workshops, tutorials, supports and program code updates are also provided to users by NCAR and therefore we don’t see any major problem that will arise should PAG-ASA opt to be one of the 4,000 registered users of WRF in 77 countries.
(Sources and related links: http://www.wrf-model.org/index.php; http://www.inergizedigital.com/news/WDTPressRelease-January-27-2009.pdf)
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