CN-122018047-A - All-weather satellite microwave humidity data assimilation method based on ARMS

CN122018047ACN 122018047 ACN122018047 ACN 122018047ACN-122018047-A

Abstract

The application relates to an all-weather assimilation method for satellite microwave humidity data based on ARMS, which comprises the following steps of collecting YH4DVAR global background field data, calculating the effective particle radius of a hydraulic condensate, establishing a symmetrical error model aiming at ARMS scattering characteristics for the forecast deviation of cloud and precipitation intensity and space position, expanding the observation error into a sectional function of cloud quantity or precipitation in the mode and observation, distributing assimilation weight for the microwave observation data under all-weather conditions, and assimilating and forecasting the all-weather satellite microwave humidity data by using the model. The application has good all-weather microwave radiation simulation capability, provides a new observation operator for all-weather assimilation of YH4DVAR, and has wide application prospect in the field of satellite microwave data assimilation.

Inventors

ZHANG WEIMIN
Luo Tengling
MA SHUO
YU YI
ZHAO YANLAI
LI SHAOYING
LIU BAINIAN
NI WEICHENG
ZHANG ZHONGYU

Assignees

中国人民解放军国防科技大学

Dates

Publication Date: 20260512
Application Date: 20260409

Claims (7)

1. The all-weather satellite microwave humidity data assimilation method based on ARMS is characterized by comprising the following steps of: collecting YH4DVAR global background field data; Calculating the effective particle radius of the hydrogel; Establishing a symmetrical error model aiming at ARMS scattering characteristics for the forecast deviation of cloud and precipitation intensity and space position, wherein the symmetrical error model expands the observation error into a model and a sectional function of cloud quantity or precipitation quantity in observation, and distributes assimilation weights for microwave observation data under all-weather conditions; and assimilating and forecasting all-weather satellite microwave humidity data by using the model.
2. The all-weather assimilation method for ARMS-based satellite microwave humidity data according to claim 1, wherein the effective particle radius is Expressed as: ; where r is the radius of the particle, Is the particle spectrum distribution with radius as a variable, Is a parameter of the shape of the article, Is the mixing ratio of the hydraulic condensate x, Is the density of the hydrogel material and, Is the density of air, N is the particle number concentration, Is a gamma function; Mixing ratio of hydraulic condensate The definition is as follows: ; Wherein, the Is the density of the hydrogel material and, Is the density of the air and is the air density, The cloud particle spectrum distribution is represented, In order to be able to carry out the intercept parameters, Is the diameter of the cloud particles, Representing a slope parameter; the air density is expressed as: ; Wherein the method comprises the steps of 、、 Respectively representing the air pressure, specific humidity and temperature on the level layer; Slope of The method comprises the following steps: 。
3. the all-weather assimilation method for ARMS-based satellite microwave humidity data according to claim 2, wherein the effective particle radius of water clouds in the water condensate on land and sea is And The method comprises the following steps of: ; ; wherein the land water cloud particle number concentration Concentration of marine cloud particles , Is the density of the water cloud, and the water cloud density, Is the water cloud mixing ratio.
4. The all-weather assimilation method for satellite microwave humidity data based on ARMS according to claim 2, wherein the effective particle radius formula of the ice cloud in the condensate is: ; wherein the ice cloud density , Is the concentration of the ice cloud particles, Is the ice cloud content.
5. The all-weather assimilation method for ARMS-based satellite microwave humidity data according to claim 2, wherein the effective particle radius of rain particles in the condensate is The calculation formula is as follows: ; where a and b are coefficients, respectively, for rain particles a=pi/6, b=3.0, And Respectively the coefficients, for rain particles =0.22, =2.2。
6. The all-weather assimilation method for satellite microwave humidity data based on ARMS according to claim 2, wherein the effective particle radius of snow particles in the hydrogel is The calculation formula is that ; Wherein, the Is the temperature of the freezing point, The temperature of the air is set to be the atmospheric temperature, Is the mixing ratio of the snow particles, a and b are coefficients, respectively, and b=2.0 for the snow particles a=0.069.
7. The all-weather assimilation method for satellite microwave humidity data based on ARMS according to claim 1, wherein the symmetrical error model is represented by the following formula: ; In the formula, For the symmetric cloud predictor, the method comprises the steps of, 、、、 The method comprises the steps of observing errors under a clear sky condition, observing errors under a cloud and rain condition and minimum and maximum values of a symmetric cloud predictor.

Description

All-weather satellite microwave humidity data assimilation method based on ARMS Technical Field The invention belongs to the technical field of weather forecast, and particularly relates to an all-weather assimilation method for satellite microwave humidity data based on ARMS. Background Typhoons are strong cyclone vortex systems formed in tropical ocean atmospheres, and are usually accompanied by disastrous weather phenomena such as strong winds, strong precipitation and the like, and are one of the most threatening natural disasters for human activities. An accurate numerical weather forecast (Numerical Weather Prediction, NWP) can provide accurate predictions of path and intensity development for extreme weather events such as typhoons. The satellite microwave detection data is an important observation data source for Numerical Weather Prediction (NWP), and researches show that the microwave detector can penetrate through non-precipitation cloud, provide temperature and humidity profile information for a numerical weather prediction mode, and greatly improve the accuracy of short-term and medium-term weather prediction and typhoon prediction. The fast radiation transmission mode is a bridge erected in the mode space and the satellite observation space, and is a key technology for realizing all-weather assimilation technology of microwave data. In all-weather conditions, radiation transmission simulation requires, in addition to the mode conventional variables (temperature, air pressure, humidity, wind), the scattering properties of various hydraulic condensate (water cloud, ice cloud, rain, snow, aragonite, hail) to be additionally considered, which makes radiation transmission calculation under scattering conditions quite complex. In the existing all-weather microwave data assimilation scheme, a scattering module RTTOV _ SCATT in a rapid radiation transmission mode RTTOV is generally used as an observation operator to simulate microwave radiation data under the cloud water condition. In terms of the shape of the hydrogel particles, the hydrogel particles of water cloud, ice cloud, rain and snow are generally assumed to be spherical particles, and the corresponding optical characteristics (attenuation coefficient, single scattering albedo and asymmetry are accordingly) are calculated in advance and stored in a Mie-table, so that the hydrogel particles are convenient to quickly call during calculation. In terms of radiation transmission solution, the multiple scatter solution scheme RTTOV-SCATT uses an Aiton approximation, which is essentially a spherical harmonic solution scheme of a two-stream approximation. ARMS (ADVANCED RADIATIVE TRANSFER Modeling System) is a fast radiation transmission mode developed by the China weather department. In the cloud and precipitation scattering module, ARMS constructs an aspheric ice phase particle scattering lookup table (LUT) facing the microwave frequency range, wherein liquid particles (cloud water and rain) are still processed based on Mie sphere theory, ice phase particles (cloud ice, snow and aragonite) uniformly adopt a roughened six-bullet flower beam aggregate model, and single particle optical properties are calculated by using Discrete Dipole Approximation (DDA). In the aspect of radiation transmission solution, ACCELERATED DISCRETE Ordinate Method (ADOM) is introduced into ARMS to improve multi-layer multi-scattering calculation efficiency, ADOM is a multi-stream radiation transmission solution scheme, the atmosphere can be distinguished according to scattering/non-scattering characteristics, and the matrix dimension and calculation cost can be greatly reduced. It should be noted that, when the ARMS scattering module is called, the user is required to input the effective particle radii of various hydraulic condensate, and the user is required to calculate the corresponding effective particle radii based on the cloud micro-physical parameterization scheme of the user mode, so that the ARMS is adapted to various cloud micro-physical parameterization schemes, and the use difficulty of the ARMS is increased. Disclosure of Invention The application is based on YH4DVAR assimilation system developed by national defense science and technology university, uses domestic rapid radiation transmission mode ARMS as an observation operator, and realizes MetOp-C MHS all-weather assimilation. Firstly, calculating the effective particle radius of the condensate according to the characteristics of a cloud micro-physical parameterization scheme in YH4DVAR, secondly, establishing a symmetrical error model aiming at ARMS scattering characteristics, and finally, carrying out a forecast test by taking typhoon 'Capricorn' as an example, and evaluating the assimilation effect and forecast performance of the ARMS by a system through comparative analysis with RTTOV. Experimental results show that (1) under all-weather conditions, the O-B (observed bright temperature radiation minus t