Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Satellite Radiance Assimilation in the JMA Operational Mesoscale 4DVAR System

View through CrossRef
Abstract The direct radiance assimilation scheme used in the Japan Meteorological Agency (JMA) global analysis system is applied to the JMA mesoscale four-dimensional variational data assimilation (4DVAR) system with two modifications. First, the data-thinning distance is shortened, and, second, the atmospheric profiles are extrapolated from the mesoscale model top to the radiative transfer model top using the U.S. Standard Atmosphere lapse rate. Although the variational bias correction method is widely used in many numerical weather prediction centers for global radiance assimilations, a radiance bias correction method for regional models has not been established because of difficulties in estimating the biases within limited regions and times. This paper examined the use of the bias correction coefficients estimated in the global system for the mesoscale system when the radiance data were introduced instead of the retrievals. It was found that the profile extrapolation was necessary to reduce the biases. Moreover, the use of common bias coefficients enables the use of the radiance data in the same way as the global system. The radiance data assimilation experiments in the mesoscale system demonstrated considerable improvements to the tropospheric geopotential height forecasts and precipitation forecasts. The improvements resulted from the introduction of radiance data from multiple satellites into data-sparse regions and times. However, the major effect of the radiance assimilation on the precipitation forecasts was limited to weak precipitation areas over oceans; the effects on deep convective areas and over land were relatively small.
American Meteorological Society
Title: Satellite Radiance Assimilation in the JMA Operational Mesoscale 4DVAR System
Description:
Abstract The direct radiance assimilation scheme used in the Japan Meteorological Agency (JMA) global analysis system is applied to the JMA mesoscale four-dimensional variational data assimilation (4DVAR) system with two modifications.
First, the data-thinning distance is shortened, and, second, the atmospheric profiles are extrapolated from the mesoscale model top to the radiative transfer model top using the U.
S.
Standard Atmosphere lapse rate.
Although the variational bias correction method is widely used in many numerical weather prediction centers for global radiance assimilations, a radiance bias correction method for regional models has not been established because of difficulties in estimating the biases within limited regions and times.
This paper examined the use of the bias correction coefficients estimated in the global system for the mesoscale system when the radiance data were introduced instead of the retrievals.
It was found that the profile extrapolation was necessary to reduce the biases.
Moreover, the use of common bias coefficients enables the use of the radiance data in the same way as the global system.
The radiance data assimilation experiments in the mesoscale system demonstrated considerable improvements to the tropospheric geopotential height forecasts and precipitation forecasts.
The improvements resulted from the introduction of radiance data from multiple satellites into data-sparse regions and times.
However, the major effect of the radiance assimilation on the precipitation forecasts was limited to weak precipitation areas over oceans; the effects on deep convective areas and over land were relatively small.

Related Results

Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
In recent years, the development of artificial intelligence has led to rapid advances in data-driven weather forecasting models, some of which rival or even surpass traditional met...
Study of weak constraint 4dvar with model error forcing control variable
Study of weak constraint 4dvar with model error forcing control variable
In the traditional implementations of four-dimensional variational data assimilation (4dvar for short), it is assumed that the model used is perfect. However the model error in the...
Satellite Radiance Data Assimilation within the Hourly Updated Rapid Refresh
Satellite Radiance Data Assimilation within the Hourly Updated Rapid Refresh
Abstract Assimilation of satellite radiance data in limited-area, rapidly updating weather model/assimilation systems poses unique challenges compared to those for g...
Transmittance and Radiance Computations for Rocket Engine Plume Environments
Transmittance and Radiance Computations for Rocket Engine Plume Environments
Rocket engine exhaust plume is generally thermal in character arising from changes in the internal energy of constituent molecules. Radiation from the plume is attenuated in its pa...
Development of Profile Assimilation Methods for Data-Driven Large Eddy Simulations
Development of Profile Assimilation Methods for Data-Driven Large Eddy Simulations
Abstract Mesoscale-to-microscale coupling (MMC) extends the capability of large-eddy simulations by introducing spatially and temporally varying mesoscale condition...
Spontaneous near-inertial wave generation from mesoscale eddy: Energy transformation
Spontaneous near-inertial wave generation from mesoscale eddy: Energy transformation
The energy transformation between inertial oscillations (IOs), near-inertial waves (NIWs), and mesoscale eddies during spontaneous NIW generation is analyzed by the kinetic energy ...
Impact of AMSU-A and MHS radiances assimilation on Typhoon Megi (2016) forecasting
Impact of AMSU-A and MHS radiances assimilation on Typhoon Megi (2016) forecasting
Abstract To better understand the assimilation contribution and influence mechanism of different satellite platforms and different microwave instruments, the radianc...

Back to Top