[AAS02-P04] A strategy towards the Japan regional reanalysis to protect our lives, properties and the social infra-structure under the changing climate
Keywords:regional reanalysis, NWP, resilience, changing climate
Through our experiences of the recent successive extreme weather events, the importance of preparedness for the changing climate has been more recognized by the society. The preparation includes structural and non-structural measures, for both of which the regional reanalysis can play an important role.
The regional reanalysis can be carried out by running the regional 4DDA system assimilated with the observation data in the past under the global reanalysis framework. Since the regional reanalysis requires substantial computing/human resources, we need to consider how large the benefit of the regional reanalysis can be for our society.
For structural measures, such as flood levies, ocean wave barriers, climate modelling community has already been contributing to them, through the future simulation of extreme events using the huge ensemble model outputs such as d4PDF (Mizuta et al. 2017). Under the adaptation policy for the climate changes, outputs of d4PDF are also used by experts in various fields such as agriculture, hydrology and risk management. The users of the climate models have been actively working on the use of the simulated outputs and apply for their decision in future planning. For the structural measures, requiring huge costs and long-term commitment, we need to confirm the reliability of the information. One way to reconfirm the reliability of the climate simulation is to compare the recent climate changes between the simulation and the observed nature. For the regional climate changes, which are crucial for the regional action plans, the regional reanalysis rather than the global reanalysis plays an important role for such comparison.
The role of the regional reanalysis is important not only for the climate change detection but also for strengthening our risk management and resilience. The regional reanalysis provides scenario for past extreme events in detail on fact bases. The analysis also provides us the initial condition for the prediction by the regional model, which is called “reforecast”. The frequency of weather-related disasters is normally very rare in the specific local area. To prepare for the extreme events in the local area such as municipal government area, we need to learn from the historical events using reanalysis and reforecast. If we use the “state-of-the-art” NWP system for the reanalysis and reforecast, our knowledge about the past events directly support our decision at the coming extreme events forecasted by the NWP system, since we may have the better knowledge about the reliability of the forecast for the extreme events. To make the decision in the various fields, it is extremely important to know the reliability of the forecast, which always includes the error to some extent.
Thus, we can recognize two important roles in the regional reanalysis, one is to detect or confirm the actual regional climate changes, and the other is to learn from the past extreme events to prepare for the next event. For the former role, we may choose the approach proposed by Fukui et al. (2018), while for the latter role, we may utilize the advanced observation and the NWP system close to the operational one, producing reanalysis and reforecast products. Renewable energy fields as well as disaster management fields are considered to be the major users of the regional reanalysis/reforecast.
The benefits to society from the regional reanalysis will be larger if we can activate the interaction with user communities and other fields of specialty such as oceanography, hydrology/snow, energy, and atmospheric chemistry. One of the keys for the success is to utilize the user network developed in the activities of d4PDF.
Finally, I would like to point out the importance of the international collaboration. For the first step, we may exchange or share the past observation data with neighboring countries in East Asia, which may contribute to the individual reanalysis project in each country. The intercomparison of the regional reanalysis results for the common region may be beneficial among these countries.
Reference
Fukui, S, T. Iwasaki, K. Saito, H. Seko and M. Kunii 2018: A feasibility study of the high-resolution regional reanalysis over Japan assimilating only conventional observations as an alternative to the dynamical downscaling. J. Meteor. Soc. Japan 2018, 565-585
Mizuta, R et al., 2017: Over 5000 years of ensemble future climate simulations by 60 km global and 20 km regional atmospheric models. Bull. Amer. Meteor. Soc. July 2017, 1383-1398
The regional reanalysis can be carried out by running the regional 4DDA system assimilated with the observation data in the past under the global reanalysis framework. Since the regional reanalysis requires substantial computing/human resources, we need to consider how large the benefit of the regional reanalysis can be for our society.
For structural measures, such as flood levies, ocean wave barriers, climate modelling community has already been contributing to them, through the future simulation of extreme events using the huge ensemble model outputs such as d4PDF (Mizuta et al. 2017). Under the adaptation policy for the climate changes, outputs of d4PDF are also used by experts in various fields such as agriculture, hydrology and risk management. The users of the climate models have been actively working on the use of the simulated outputs and apply for their decision in future planning. For the structural measures, requiring huge costs and long-term commitment, we need to confirm the reliability of the information. One way to reconfirm the reliability of the climate simulation is to compare the recent climate changes between the simulation and the observed nature. For the regional climate changes, which are crucial for the regional action plans, the regional reanalysis rather than the global reanalysis plays an important role for such comparison.
The role of the regional reanalysis is important not only for the climate change detection but also for strengthening our risk management and resilience. The regional reanalysis provides scenario for past extreme events in detail on fact bases. The analysis also provides us the initial condition for the prediction by the regional model, which is called “reforecast”. The frequency of weather-related disasters is normally very rare in the specific local area. To prepare for the extreme events in the local area such as municipal government area, we need to learn from the historical events using reanalysis and reforecast. If we use the “state-of-the-art” NWP system for the reanalysis and reforecast, our knowledge about the past events directly support our decision at the coming extreme events forecasted by the NWP system, since we may have the better knowledge about the reliability of the forecast for the extreme events. To make the decision in the various fields, it is extremely important to know the reliability of the forecast, which always includes the error to some extent.
Thus, we can recognize two important roles in the regional reanalysis, one is to detect or confirm the actual regional climate changes, and the other is to learn from the past extreme events to prepare for the next event. For the former role, we may choose the approach proposed by Fukui et al. (2018), while for the latter role, we may utilize the advanced observation and the NWP system close to the operational one, producing reanalysis and reforecast products. Renewable energy fields as well as disaster management fields are considered to be the major users of the regional reanalysis/reforecast.
The benefits to society from the regional reanalysis will be larger if we can activate the interaction with user communities and other fields of specialty such as oceanography, hydrology/snow, energy, and atmospheric chemistry. One of the keys for the success is to utilize the user network developed in the activities of d4PDF.
Finally, I would like to point out the importance of the international collaboration. For the first step, we may exchange or share the past observation data with neighboring countries in East Asia, which may contribute to the individual reanalysis project in each country. The intercomparison of the regional reanalysis results for the common region may be beneficial among these countries.
Reference
Fukui, S, T. Iwasaki, K. Saito, H. Seko and M. Kunii 2018: A feasibility study of the high-resolution regional reanalysis over Japan assimilating only conventional observations as an alternative to the dynamical downscaling. J. Meteor. Soc. Japan 2018, 565-585
Mizuta, R et al., 2017: Over 5000 years of ensemble future climate simulations by 60 km global and 20 km regional atmospheric models. Bull. Amer. Meteor. Soc. July 2017, 1383-1398