4:10 PM - 4:30 PM
[MTT38-03] Multi-sensing for monitoring and forecasting extreme weather
★Invited Papers
Keywords:extreme weather, multi-sensing, cloud radar, Doppler lidar, microwave radiometer, Lightning Mapping Array
According to recent research on climate change, it is highly likely that the frequency of heavy rain will increase in the future. In fact, the frequency of short-time heavy rain has been increasing in recent years, and the damage from flooding and sediment disasters has also become more severe and frequent. In this situation, in order to strengthen the resilience of society against extreme weather such as heavy rain, it is necessary to improve observation and prediction technologies related to extreme weather and wind and water damage, and to use the results to generate information products that lead to the optimization of disaster response.
At the National Research Institute for Earth Science and Disaster Resilience (NIED), we have focused on the fact that many extreme weather events are caused by cumulonimbus clouds, and have been working on early detection and prediction of cumulonimbus clouds. Until now, most observations of cumulonimbus clouds have relied on meteorological radar, but ordinary meteorological radar cannot observe clouds before they form rain. Therefore, in addition to the conventional X-band weather radar, we have introduced a cloud radar that can observe cumulus clouds before they form rain, a Doppler lidar that can observe air flow in clear areas, a microwave radiometer that can estimate vertical profiles of water vapor and air temperature, and a Lightning Mapping Array (LMA) that can observe the path of lightning discharges in three dimensions, and have developed a research multi-sensing system that can seamlessly observe cumulonimbus clouds from before they form to when they fade. We are also developing a method for predicting cumulonimbus clouds early by capturing the signs of cumulus and cumulonimbus cloud formation through these observations and assimilating them into a cloud-resolving numerical model. In this presentation, we will introduce examples of these observations and forecasts. We will also introduce new observation methods that have been developed in recent years and discuss how to utilize the data.
At the National Research Institute for Earth Science and Disaster Resilience (NIED), we have focused on the fact that many extreme weather events are caused by cumulonimbus clouds, and have been working on early detection and prediction of cumulonimbus clouds. Until now, most observations of cumulonimbus clouds have relied on meteorological radar, but ordinary meteorological radar cannot observe clouds before they form rain. Therefore, in addition to the conventional X-band weather radar, we have introduced a cloud radar that can observe cumulus clouds before they form rain, a Doppler lidar that can observe air flow in clear areas, a microwave radiometer that can estimate vertical profiles of water vapor and air temperature, and a Lightning Mapping Array (LMA) that can observe the path of lightning discharges in three dimensions, and have developed a research multi-sensing system that can seamlessly observe cumulonimbus clouds from before they form to when they fade. We are also developing a method for predicting cumulonimbus clouds early by capturing the signs of cumulus and cumulonimbus cloud formation through these observations and assimilating them into a cloud-resolving numerical model. In this presentation, we will introduce examples of these observations and forecasts. We will also introduce new observation methods that have been developed in recent years and discuss how to utilize the data.