Can Adaptive Observations Improve Tropical Cyclone Intensity Forecasts?简

In order to investigate whether adaptive observations can improve tropical cyclone （TC） intensity forecasts,observing system simulation experiments （OSSEs） were conducted for 20 TC cases originating in the western North Pacific during the 2010 season according to the conditional nonlinear optimal perturbation （CNOP） sensitivity,using the fifth version of the PSU/NCAR mesoscale model （MM5） and its 3DVAR assimilation system.A new intensity index was defined as the sum of the number of grid points within an allocated square centered at the corresponding forecast TC central position,that satisfy constraints associated with the Sea Level Pressure （SLP）,near-surface horizontal wind speed,and accumulated convective precipitation.The higher the index value is,the more intense the TC is.The impacts of the CNOP sensitivity on the intensity forecast were then estimated.The OSSE results showed that for 15 of the 20 cases there were improvements,with reductions of forecast errors in the range of 0.12％-8.59％,which were much less than in track forecasts.The indication,therefore,is that the CNOP sensitivity has a generally positive effect on TC intensity forecasts,but only to a certain degree.We conclude that factors such as the use of a coupled model,or better initialization of the TC vortex,are more important for an accurate TC intensity forecast.

Can Adaptive Observations Improve Tropical Cyclone Intensity Forecasts？

In order to investigate whether adaptive observations can improve tropical cyclone (TC) intensity forecasts, observing system simulation experiments (OSSEs) were conducted for 20 TC cases originating in the western North Pacific during the 2010 season according to the conditional nonlinear optimal perturbation (CNOP) sensitivity, using the fifth version of the PSU/NCAR mesoscale model (MM5) and its 3DVAR assimilation system. A new intensity index was defined as the sum of the number of grid points within an allocated square centered at the corresponding forecast TC central position, that satisfy constraints associated with the Sea Level Pressure (SLP), near-surface horizontal wind speed, and accumulated convective precipitation. The higher the index value is, the more intense the TC is. The impacts of the CNOP sensitivity on the intensity forecast were then estimated. The OSSE results showed that for 15 of the 20 cases there were improvements, with reductions of forecast errors in the range of 0.12%–8.59%, which were much less than in track forecasts. The indication, therefore, is that the CNOP sensitivity has a generally positive effect on TC intensity forecasts, but only to a certain degree. We conclude that factors such as the use of a coupled model, or better initialization of the TC vortex, are more important for an accurate TC intensity forecast.