A parameterization method for wet atmospheric topography gravity waves

Abstract

The present invention discloses a method for parameterizing wet atmospheric terrain gravity waves, comprising the following steps: calculating the dry adiabatic buoyancy frequency and total density in unsaturated wet air, taking into account the effects of water vapor, liquid water, and solid water; calculating the surface stress of wet atmospheric terrain gravity waves; calculating the wet atmospheric buoyancy frequency parameters during the vertical propagation of terrain gravity waves, taking into account both dry and wet adiabatic processes; calculating the wet atmospheric buoyancy frequency parameters, gravity wave amplitude, and local Richardson number layer by layer during the upward propagation of terrain gravity wave stress; determining whether the terrain gravity wave layer has reached saturation; and numerically simulating heavy rainfall events to analyze the impact of water vapor on rainfall. The present invention addresses the dry air assumption in the numerical model for terrain gravity wave parameterization, better characterizing the gravity wave surface stress and the vertical propagation process of the stress, and improving the performance of the numerical model.

Description

Technical Field

[0001] The present invention belongs to the technical field of numerical weather forecasting, and in particular relates to a parameterization method for wet atmosphere terrain gravity waves. Background Art

[0002] The impact of topography on the atmosphere has long been a complex and fascinating research topic in fluid dynamics. As air flows over the Earth's surface, topography can cause atmospheric obstructions or disturbances. These disturbances create friction and drag on the airflow, influencing the evolution of various weather systems. Numerical weather prediction (NWP) models are currently the primary method for weather forecasting. They employ a deductive reasoning process, using numerical integration to solve the state of the Earth system on a grid-by-grid basis. However, numerical models can only account for topographic effects above the grid scale and are unable to describe the influence of sub-grid topography on atmospheric circulation.

[0003] Under certain atmospheric conditions, small-scale subgrid topography can excite gravity waves that propagate vertically upward, increasing in amplitude and breaking when they become unstable. This can have significant nonlocal effects on large-scale circulation in the stratosphere and mesosphere. Accounting for the effects of topographic gravity waves plays an important role in accurately representing the state of the stratosphere, which is crucial for medium-term weather forecasts, seasonal forecasts, and climate predictions. Gravity wave breaking can cause clear-air turbulence, which can affect aircraft flight safety. In the lower troposphere, gravity wave breaking can also produce severe downslope storms. However, small-scale subgrid topography has a significant impact on atmospheric circulation, and therefore, parameterization of small-scale subgrid topographic processes is necessary to account for subgrid effects.

[0004] As early as the 1980s, the effects of gravity waves excited by subgrid-scale topography were described in NWP models based on early mountain wave theory. However, these were limited to two-dimensional single-wave parameterizations and had certain assumptions (e.g., stable stratified airflow, neglect of the Earth's rotation, inviscidity, static equilibrium, and dry air assumptions). Lott & Miller (later known as LM97) proposed a new orographic gravity wave drag (OGWD) parameterization scheme to address the nonlinear low-level mountain drag that was not considered in previous schemes, taking into account the airflow blocking effect caused by subgrid-scale topography. Subsequently, this OGWD parameterization scheme was applied to multiple NWP models, including ECMWF's IFS, Met Office's UM, JMA's GSM2003, DWD's ICON, and Météo-France's ARPEGE. OGWD parameterization schemes play an important role in reducing tropospheric and stratospheric model errors and improving NWP model performance. However, due to the lack of observational and theoretical constraints on tropospheric and stratospheric topographic drag, parameterization schemes are generally based on many assumptions and empirical formulas, resulting in large uncertainties and poor constraints. This makes the parameterization schemes themselves a source of error in NWP models. To date, representing unresolved topographic processes in numerical models remains a major challenge. Therefore, topographic gravity wave parameterization schemes continue to require further de-assumption and de-approximation to become more complete.

[0005] The current OGWD parameterization scheme still retains a key assumption: the dry air approximation. The real atmosphere contains water vapor, which has a significant impact on atmospheric conditions and is a key factor influencing climate change. Water vapor is arguably central to all key atmospheric processes. Water vapor also plays a crucial role in atmospheric stability during the propagation of orographic gravity waves. When an air parcel containing water vapor experiences an upward disturbance, if the water vapor condenses and releases latent heat, this heat can partially compensate for the cooling of the air parcel due to adiabatic expansion, making the density difference between the moist air parcel and the surroundings smaller than that between the moist air parcel and the dry air parcel, reducing the buoyancy of the air parcel. For air parcels experiencing small downward disturbances, the absorption of latent heat by evaporation also produces a similar reduction in buoyancy, resulting in a lower oscillation frequency for moist air than for dry air. Researchers have studied the impact of water vapor on leeward waves trapped in mountainous regions and found that variations in water vapor can produce different wave responses in different environments and at different altitudes. It can be seen that ignoring the influence of water vapor in the existing technology brings errors to the numerical weather forecast model. Therefore, it is necessary to accurately consider the influence of water vapor in the terrain gravity wave parameterization scheme to improve the accuracy of the model. Summary of the Invention

[0006] In light of this, this paper removes the dry air assumption from the orographic gravity wave parameterization scheme. Starting from the original governing equations of atmospheric motion, the paper considers the effects of water vapor, liquid water, and solid water, and utilizes linear gravity wave theory to derive and calculate the surface stress of wet atmospheric orographic gravity waves. During the vertical propagation of gravity waves, the wet atmospheric buoyancy frequency parameter, which comprehensively considers both dry and wet adiabatic processes, is applied to determine the vertical distribution of gravity wave stress. This allows for a more accurate description of subgrid topographic effects and improves the simulation and forecasting capabilities of numerical models in complex terrain areas.

[0007] To achieve the above-mentioned purpose, the wet atmosphere topography gravity wave parameterization method disclosed in this application includes the following steps:

[0008] Collect site rainfall observation data;

[0009] The dry air assumption is removed from the topographic gravity wave parameterization scheme, and the unsaturated moist air buoyancy frequency including humidity effect is calculated in the near-surface moist atmosphere. and total air density

[0010] Calculate the surface stress of wet atmospheric topographic gravity waves based on linear gravity wave theory ;

[0011] Calculate the buoyancy frequency parameters of the moist atmosphere during vertical propagation of topographic gravity waves by comprehensively considering the dry adiabatic process and the wet adiabatic process;

[0012] During the upward propagation of topographic gravity wave stress, the following steps are performed: the buoyancy frequency parameters of the moist atmosphere are calculated layer by layer; the gravity wave amplitude and the local Richardson number are calculated layer by layer; if the local Richardson number is less than the critical value, the gravity wave amplitude at which the gravity wave breaks and the gravity wave stress of the layer are calculated; if the local Richardson number is still greater than the critical value, the topographic gravity wave stress of the layer continues to propagate upward;

[0013] Based on the numerical weather forecast model, the orographic gravity wave parameterization method considering the moist atmosphere is applied to numerically simulate heavy rainfall events and analyze the impact of orographic gravity wave parameterization considering water vapor on rainfall.

[0014] Preferably, during the process of the topographic gravity wave stress propagating upward layer by layer, the following steps are performed:

[0015] a. Horizontal wind field based on the kth layer in the numerical model , wet atmosphere buoyancy frequency , total density of moist air and the gravity wave stress of the next layer Calculate the gravity wave amplitude of this layer ;

[0016] b. Topographic gravity wave amplitude based on the layer and moist atmospheric buoyancy frequency , calculate the local Richardson number ;

[0017] c. According to the local Richardson number Compare with the critical value to determine whether the terrain gravity wave is broken and calculate the terrain gravity wave of this layer ;

[0018] d. Repeat steps a, b, and c until you reach the top of the pattern layer.

[0019] Preferably, the dry air assumption is removed from the topographic gravity wave parameterization scheme, and the total air density of water vapor, liquid water and solid water is included in the governing equations of the wet atmosphere. and the dry adiabatic buoyancy frequency of unsaturated moist air , total air density The calculation is as follows:

[0020] ;

[0021] Where P is the air mass pressure, 、 denote the dry air pressure and dry air specific gas constant, respectively. 、 denote the moist air pressure and moist air specific gas constant, respectively. is the density of liquid water, is the density of solid water, T is the temperature of the air mass, represents the water vapor mixing ratio, represents the total mixing ratio, It represents the ratio of the dry air gas constant to the wet air gas constant;

[0022] Dry adiabatic buoyancy frequency of unsaturated moist air The calculation is as follows:

[0023] ;

[0024] in, represents the specific heat capacity, is the acceleration due to gravity.

[0025] Preferably, the surface stress of wet atmospheric terrain gravity waves is calculated based on the linear gravity wave theory. :

[0026] ;

[0027] in, is the effective mountain height obtained by subtracting the airflow blockage height from the subgrid mountain height, is a function of the sharpness of the elliptical mountain range, and is the anisotropy function of the elliptical mountain range, and represent the components parallel and perpendicular to the wind direction, respectively. It is the angle between the mountain azimuth and the wind direction.

[0028] Preferably, the dry adiabatic process and the wet adiabatic process in the wet atmosphere are comprehensively considered during the vertical propagation of the wet atmospheric topographic gravity wave, and the wet atmospheric buoyancy frequency The calculation is as follows:

[0029] ;

[0030] Where T is the temperature of the air mass, g is the acceleration due to gravity, is the dry adiabatic lapse rate, is the moist adiabatic lapse rate, represents the saturated mixing ratio, represents the total mixing ratio, represents the latent heat of vaporization, represents the dry air specific gas constant, Indicates height, and are the dry coefficient and the wet coefficient, which are determined by the following formula:

[0031] ;

[0032] in is the specific humidity, is the saturated specific humidity, Indicates the saturation regulation coefficient.

[0033] Preferably, during the vertical propagation of wet atmospheric topographic gravity waves, the gravity wave amplitude is calculated as follows:

[0034] ;

[0035] in represents the gravity wave stress of the k+1th layer, represents the air density of the kth layer, represents the buoyancy frequency of moist air in the kth layer, represents the wind speed at the kth layer.

[0036] Preferably, during the vertical propagation of wet atmospheric topographic gravity waves, the local Richardson number The calculation is as follows:

[0037] ;

[0038] in is the average Richardson number of the airflow, is the Froude number of the airflow.

[0039] Preferably, the determining of the vertical distribution of gravity wave stress comprises calculating the first Layer stress:

[0040] ;

[0041] in is the amplitude of the gravity wave when it breaks, It represents the critical Richardson value, which is iteratively propagated upward gradually to determine the vertical distribution of gravity wave stress.

[0042] The present invention removes the "dry air" assumption and, starting from the original set of atmospheric motion control equations, considers the influence of water vapor and develops a new wet atmosphere OGWD scheme that can more accurately describe the sub-grid terrain effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A framework diagram of the present invention;

[0044] Figure 2 The buoyancy frequency (a), local Richardson number (b), and vertical distribution of topographic gravity wave stress (c) during the vertical propagation of topographic gravity waves. The solid line represents the dry atmosphere topographic gravity wave parameterization scheme, the long dashed line represents the wet atmosphere topographic gravity wave parameterization scheme, and the short dashed line represents the difference between the two. DETAILED DESCRIPTION

[0045] The following is a further explanation of the present invention using the extreme rainfall event in a certain place and its surrounding areas from July 19 to July 21, 2021 as an example and in combination with the accompanying drawings, but the present invention is not limited in any way. Any changes or replacements made based on the teachings of the present invention are within the scope of protection of the present invention.

[0046] In one embodiment, reference Figure 1 The wet atmosphere topography gravity wave parameterization method disclosed in this application comprises the following steps:

[0047] Collect site rainfall observation data;

[0048] The dry air assumption is removed from the topographic gravity wave parameterization scheme, and the buoyancy frequency of unsaturated moist air in the near-surface moist atmosphere, which includes the effects of water vapor, liquid water, and solid water, is calculated. and total air density

[0049] Calculate the surface stress of wet atmospheric topographic gravity waves based on linear gravity wave theory ;

[0050] Comprehensively consider the dry adiabatic process and the wet adiabatic process in the wet atmosphere to calculate the buoyancy frequency of the wet atmosphere ;

[0051] During the upward propagation of topographic gravity wave stress, the following steps are performed: the buoyancy frequency parameters of the moist atmosphere are calculated layer by layer; the gravity wave amplitude and the local Richardson number are calculated layer by layer; if the local Richardson number is less than the critical value, the gravity wave amplitude at which the gravity wave breaks and the gravity wave stress of the layer are calculated; if the local Richardson number is still greater than the critical value, the topographic gravity wave stress of the layer continues to propagate upward;

[0052] Based on the numerical weather forecast model, the new moist atmospheric topographic gravity wave parameterization method is applied to numerically simulate heavy rainfall events and analyze the impact of water vapor on rainfall.

[0053] In one embodiment, during the process of topographic gravity wave stress propagating upward layer by layer, the following steps are specifically performed:

[0054] a. Horizontal wind field based on the kth layer in the numerical model , wet atmosphere buoyancy frequency , total density of moist air and the gravity wave stress of the next layer Calculate the gravity wave amplitude of this layer ;

[0055] b. Topographic gravity wave amplitude based on the layer and moist atmospheric buoyancy frequency , calculate the local Richardson number ;

[0056] c. According to the local Richardson number Compare with the critical value to determine whether the terrain gravity wave is broken and calculate the terrain gravity wave of this layer ;

[0057] d. Repeat steps a, b, and c until you reach the top of the pattern layer.

[0058] In one embodiment, the dry air assumption is removed from the terrain gravity wave parameterization scheme, and the total air density including water vapor, liquid water and solid water is calculated in the governing equations of the wet atmosphere. and the dry adiabatic buoyancy frequency of unsaturated moist air , total air density The calculation is as follows:

[0059] ;

[0060] Where P is the air mass pressure, 、 denote the dry air pressure and dry air specific gas constant, respectively. 、 denote the moist air pressure and moist air specific gas constant, respectively. is the density of liquid water, is the density of solid water, T is the temperature of the air mass, represents the water vapor mixing ratio, represents the total mixing ratio, It represents the ratio of the dry air gas constant to the wet air gas constant;

[0061] Dry adiabatic buoyancy frequency of unsaturated moist air The calculation is as follows:

[0062] ;

[0063] in, represents the specific heat capacity, is the acceleration due to gravity.

[0064] In one embodiment, the surface stress of wet atmospheric terrain gravity waves is calculated based on linear gravity wave theory. :

[0065] ;

[0066] in, is the effective mountain height obtained by subtracting the airflow blockage height from the subgrid mountain height, is a function of the sharpness of the elliptical mountain range, and is the anisotropy function of the elliptical mountain range, and represent the components parallel and perpendicular to the wind direction, respectively. It is the angle between the mountain azimuth and the wind direction.

[0067] In one embodiment, the dry adiabatic process and the wet adiabatic process in the wet atmosphere are comprehensively considered during the vertical propagation of the wet atmospheric terrain gravity wave. The calculation is as follows:

[0068] ;

[0069] Where T is the temperature of the air mass, g is the acceleration due to gravity, is the dry adiabatic lapse rate, is the moist adiabatic lapse rate, represents the saturated mixing ratio, represents the total mixing ratio, represents the latent heat of vaporization, represents the dry air specific gas constant, Indicates height, and are the dry coefficient and the wet coefficient, which are determined by the following formula:

[0070] ;

[0071] in is the specific humidity, is the saturated specific humidity, Indicates the saturation regulation coefficient.

[0072] In one embodiment, during the vertical propagation of moist atmospheric topographic gravity waves, the gravity wave amplitude is calculated as follows:

[0073] ;

[0074] in represents the gravity wave stress of the k+1th layer, represents the air density of the kth layer, represents the buoyancy frequency of moist air in the kth layer, represents the wind speed at the kth layer.

[0075] In one embodiment, during the vertical propagation of moist atmospheric topographic gravity waves, the local Richardson number The calculation is as follows:

[0076] ;

[0077] in is the average Richardson number of the airflow, is the Froude number of the airflow.

[0078] In one embodiment, determining the vertical distribution of gravity wave stress includes calculating Layer stress:

[0079] ;

[0080] in is the amplitude of the gravity wave when it breaks, It represents the critical Richardson value, which is iteratively propagated upward gradually to determine the vertical distribution of gravity wave stress.

[0081] In this application, the Galaxy Global Spectrum Model (YHGSM) developed by the National University of Defense Technology is used for numerical weather prediction. Two sets of numerical experiments (EXP_LM97 and EXP_NEW) are conducted using the LM97 scheme based on the "dry air" assumption and the newly proposed moist atmosphere topographic gravity wave parameterization scheme, respectively, to numerically simulate the extreme rainfall event in a certain place from July 19 to 21, 2021.

[0082] First, the numerical model is run. Reanalysis data with a resolution of TL1279, obtained from the ensemble four-dimensional variational data assimilation system, are used as the initial conditions for the numerical model and initialized at 12:00 UTC on July 18, 2021. The model runs for five days, covering the entire extreme rainfall period.

[0083] Then, the terrain gravity wave surface stress is calculated. The terrain gravity wave parameterization scheme is called in each integration step of the numerical model to calculate the surface terrain gravity wave stress by calculating the buoyancy frequency of unsaturated moist air near the surface and the total air density. The average terrain gravity wave surface stress during the extreme rainfall period is then obtained by averaging. The surface stress in the wet atmosphere topography gravity wave parameterization scheme is greater than that in the dry atmosphere topography gravity wave parameterization scheme.

[0084] Secondly, the vertical distribution of terrain gravity wave stress is calculated. In the process of gravity wave propagation upward, the first step is to comprehensively consider the dry adiabatic process and the wet adiabatic process in the moist atmosphere and calculate the key parameters of the buoyancy frequency of each layer of moist atmosphere. ,like Figure 2 The difference between the buoyancy frequency of the wet atmosphere and the buoyancy frequency of the dry atmosphere is mainly reflected in the middle and lower layers of the troposphere, and the wet buoyancy frequency is generally smaller than the dry buoyancy frequency during the vertical propagation of gravity waves. The second step is to calculate the local Richardson number. ,like Figure 2 b. Local Richardson number in moist atmosphere Less than the local Richardson number in dry atmosphere According to the local Richardson number Determine whether the gravity wave is broken, and use the key parameters to calculate the gravity wave stress of each layer and determine the vertical distribution of gravity wave stress, such as Figure 2 c. The topographic gravity wave stress in the wet scenario is greater than that in the dry scenario, with the difference primarily occurring in the middle and lower troposphere. The attenuation rate of the topographic gravity wave stress with height in the wet scenario is also greater than that in the dry scenario, indicating that the wet scenario produces stronger topographic gravity wave drag.

[0085] Finally, the numerical simulation results of the moist atmosphere topography gravity wave parameterization scheme are analyzed. The numerical simulation is performed on the average daily rainfall during the extreme rainfall period in a certain place and its surrounding areas from July 19 to July 21, 2021. The moist atmosphere topography gravity wave parameterization scheme increases the intensity of the rainfall center and significantly improves the negative deviation of the rainfall center and the positive deviation northwest of the rainfall center. The moist atmosphere topography gravity wave parameterization scheme changes the water vapor transport by increasing the drag on the circulation, resulting in an increase of about 33% in the net water vapor balance in the heavy rainfall area, a decrease of 14.59% in the average daily rainfall, and a region with improved daily average rainfall of 74.99%, effectively improving the simulation capability of extreme rainfall events.

[0086] In recent years, extreme weather has occurred frequently. Accurate numerical simulation of extreme rainfall events is an important way to prevent disasters and reduce social impacts, but this is still a challenge. Compared with the existing technology, the present invention shows that water vapor has an important influence on the OGWD parameterization in the numerical model, and it will become one of the important error sources of the NWP model based on the "dry air" assumption. By considering the influence of water vapor in the OGWD scheme, the present invention processes the dry air assumption of the terrain gravity wave in the numerical model, which can better characterize the surface stress and vertical propagation process of the gravity wave excited by the sub-grid terrain by moist air in the actual atmosphere, which helps to improve the numerical simulation of extreme rainfall and improve the simulation of atmospheric circulation, improve the numerical simulation of heavy rainfall and atmospheric circulation, and improve the performance of the numerical weather forecast model.

[0087] As used herein, the word "preferred" is intended to serve as an example, instance, or illustration. Any aspect or design described herein as "preferred" is not necessarily to be construed as advantageous over other aspects or designs. Rather, the use of the word "preferred" is intended to present concepts in a concrete manner. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from the context, "X employs A or B" is intended to mean any of the naturally inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then "X employs A or B" is satisfied in any of the foregoing examples.

[0088] Moreover, although the present disclosure has been shown and described with respect to one or implementation, those skilled in the art will think of equivalent variations and modifications based on reading and understanding of this specification and the accompanying drawings. The present disclosure includes all such modifications and variations and is limited only by the scope of the appended claims. In particular, with respect to the various functions performed by the above-mentioned components (such as elements, etc.), the terms used to describe such components are intended to correspond to any component (unless otherwise indicated) that performs the specified function of the component (such as it is functionally equivalent), even if structurally different from the disclosed structure that performs the function in the exemplary implementation of the present disclosure shown herein. In addition, although the specific features of the present disclosure have been disclosed with respect to only one of several implementations, such features can be combined with one or other features of other implementations that can be desired and advantageous for a given or specific application. Moreover, insofar as the terms "including", "having", "containing" or their variations are used in specific embodiments or claims, such terms are intended to be included in a manner similar to the term "comprising".

[0089] The functional units in the embodiments of the present invention may be integrated into a single processing module, or each unit may exist physically separately, or multiple or more units may be integrated into a single module. The aforementioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. The aforementioned storage medium may be a read-only memory, a magnetic disk, or an optical disk, etc. The aforementioned devices or systems may execute the storage method in the corresponding method embodiment.

[0090] In summary, the above embodiment is one implementation method of the present invention, but the implementation method of the present invention is not limited to the described embodiment. Any other changes, modifications, substitutions, combinations, and simplifications that deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A method for parameterizing wet atmospheric topography gravity waves, characterized in that: The following steps are involved: Collect site rainfall observation data; The dry air assumption is removed from the topographic gravity wave parameterization scheme, and the unsaturated moist air buoyancy frequency including humidity effect is calculated in the near-surface moist atmosphere. and total air density Calculate the surface stress of wet atmospheric topographic gravity waves based on linear gravity wave theory ; Calculate the buoyancy frequency parameters of the moist atmosphere during vertical propagation of topographic gravity waves by comprehensively considering the dry adiabatic process and the wet adiabatic process; During the upward propagation of topographic gravity wave stress, the following steps are performed: the buoyancy frequency parameters of the moist atmosphere are calculated layer by layer; the gravity wave amplitude and the local Richardson number are calculated layer by layer; if the local Richardson number is less than the critical value, the gravity wave amplitude at which the gravity wave breaks and the gravity wave stress of the layer are calculated; if the local Richardson number is still greater than the critical value, the topographic gravity wave stress of the layer continues to propagate upward; Based on the numerical weather forecast model, the orographic gravity wave parameterization method considering the moist atmosphere is applied to numerically simulate heavy rainfall events and analyze the impact of orographic gravity wave parameterization considering water vapor on rainfall.

2. The wet atmosphere topography gravity wave parameterization method according to claim 1, characterized in that: During the process of topographic gravity wave stress propagating upward layer by layer, the following steps are specifically performed: a. Horizontal wind field based on the kth layer in the numerical model , wet atmosphere buoyancy frequency , total density of moist air and the gravity wave stress of the next layer Calculate the gravity wave amplitude of this layer ; b. Topographic gravity wave amplitude based on the layer and moist atmospheric buoyancy frequency , calculate the local Richardson number ; c. According to the local Richardson number Compare with the critical value to determine whether the terrain gravity wave is broken and calculate the terrain gravity wave of this layer ; d. Repeat steps a, b, and c until you reach the top of the pattern layer.

3. The wet atmosphere topography gravity wave parameterization method according to claim 2, characterized in that: Remove the dry air assumption in the topographic gravity wave parameterization scheme and calculate the total air density including water vapor, liquid water and solid water in the governing equations of moist atmospheric motion and the dry adiabatic buoyancy frequency of unsaturated moist air , total air density The calculation is as follows: ； Where P is the air mass pressure, 、 denote the dry air pressure and dry air specific gas constant, respectively. 、 denote the moist air pressure and moist air specific gas constant, respectively. is the density of liquid water, is the density of solid water, T is the temperature of the air mass, represents the water vapor mixing ratio, represents the total mixing ratio, It represents the ratio of the dry air gas constant to the wet air gas constant; Dry adiabatic buoyancy frequency of unsaturated moist air The calculation is as follows: ； in, represents the specific heat capacity, is the acceleration due to gravity.

4. The wet atmosphere topography gravity wave parameterization method according to claim 3, characterized in that: Calculate the surface stress of wet atmospheric topographic gravity waves based on linear gravity wave theory : ； in, is the effective mountain height obtained by subtracting the airflow blockage height from the subgrid mountain height, is a function of the sharpness of the elliptical mountain range, and is the anisotropy function of the elliptical mountain range, and represent the components parallel and perpendicular to the wind direction, respectively. It is the angle between the mountain azimuth and the wind direction.

5. The wet atmosphere topography gravity wave parameterization method according to claim 4, characterized in that: In the vertical propagation process of wet atmospheric topographic gravity waves, the dry adiabatic process and the wet adiabatic process in the wet atmosphere are comprehensively considered. The calculation is as follows: ； Where T is the temperature of the air mass, g is the acceleration due to gravity, is the dry adiabatic lapse rate, is the moist adiabatic lapse rate, represents the saturated mixing ratio, represents the total mixing ratio, represents the latent heat of vaporization, represents the dry air specific gas constant, Indicates height, and are the dry coefficient and the wet coefficient, which are determined by the following formula: ； in is the specific humidity, is the saturated specific humidity, Indicates the saturation regulation coefficient.

6. The wet atmosphere topography gravity wave parameterization method according to claim 5, characterized in that: During the vertical propagation of wet atmospheric topographic gravity waves, the gravity wave amplitude is calculated as follows: ； in represents the gravity wave stress of the k+1th layer, represents the air density of the kth layer, represents the buoyancy frequency of moist air in the kth layer, represents the wind speed at the kth layer.

7. The wet atmosphere topography gravity wave parameterization method according to claim 6, characterized in that: During the vertical propagation of moist atmospheric topographic gravity waves, the local Richardson number The calculation is as follows: ； in is the average Richardson number of the airflow, is the Froude number of the airflow.

8. The wet atmosphere topography gravity wave parameterization method according to claim 7, characterized in that: Determine the vertical distribution of gravity wave stress, including the calculation of the Layer stress: ； in is the amplitude of the gravity wave when it breaks, It represents the critical Richardson value, which is iteratively propagated upward gradually to determine the vertical distribution of gravity wave stress.

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