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A High-Resolution Tropical Mesoscale Convective System Reanalysis Product

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DataCite Commons2021-12-07 更新2024-07-13 收录
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The advent of modern global reanalysis products has greatly accelerated meteorological research into synoptic to planetary-scale phenomena. However, their usage in studying tropical mesoscale convective systems (MCSs) is mostly limited to supplying initial and boundary conditions to MCS-resolving simulations and providing information about the tropical MCSs’ large-scale environments. These limitations are due to the global products’ difficulties in resolving tropical MCS dynamics, and the fact that tropical MCSs often occur over ill-observed regions. In this work, a Tropical MCS-resolving Reanalysis product (TMeCSR) was created over a region spanning the tropical Indian Ocean, tropical continental Asia, the Maritime Continent, and the Western Pacific. Tropical MCSs frequently occur in these regions. The TMeCSR is produced by assimilating all-sky infrared radiances from geostationary satellites and other conventional observations, into an MCS-resolving regional model using the Ensemble Kalman Filter (EnKF). The resulting observation-constrained high-resolution (9-km grid spacing) dataset is currently available at every hour for the three boreal summer months (June-August) of 2017. Comparisons of the TMeCSR and ERA5 datasets against independent satellite-retrieved outgoing longwave radiation and rainfall data indicate that the TMeCSR’s multiscale cloud and rain fields are better than the ERA5’s. Furthermore, the TMeCSR better captured the diurnal variability of rainfall. Forecasts initialized from the TMeCSR also produced more accurate rain and cloud forecasts than those initialized from ERA5. The TMeCSR and ERA5 datasets had similar performances with respect to sounding and surface observations. These results indicate that the TMeCSR might be a promising MCS-resolving dataset for future tropical MCS studies.
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Penn State Data Commons
创建时间:
2021-12-07
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