Case Of Convection Research Articles

A general Physics-Informed Neural Network approach for deriving fluid flow fields from temperature distribution

One attractive application of Physics-Informed Neural Network (PINN) is deriving fluid flow information such as velocity and pressure from temperature field. However, this requires developing a suitable loss function for a given flow condition. In this paper we implemented a general loss function in PINN to directly obtain fluid velocity and pressure from temperature information. We first validated this method through cases of natural convection in a square cavity, flow around a cylinder in a square cavity, and two-dimensional channel flow. Additionally, we examined forced convection heat transfer around a cylinder in depth. Results show that different Reynolds numbers (2, 10, 40, and 140) can all be effectively resolved using temperature data. Furthermore, super-resolution predictions of temperature, velocity and pressure are achievable even far outside the training area, suggesting that the proposed PINN method could be used to measure fluid flow within confined spaces via finite visualization windows without tracers.

Can Satellite or Reanalysis Precipitation Products Depict the Location and Intensity of Rainfall at Flash Flood Scale Over the Eastern Mountainous Area of the Tibetan Plateau?

AbstractThis study conducted evaluation and analysis on various precipitation products over the eastern Tibetan Plateau (ETP), including four sets of satellite precipitation data (i.e., IMERG_Uncal, IMERG_Cal, GSMaP_MVK, GSMaP_Gauge) and one set of model reanalysis data (i.e., ERA5‐land, hereafter ERA5‐L). We evaluated the spatial‐temporal distribution of their quality at an hourly temporal scale and 0.1° spatial scale, with a special focus on capturing different types of precipitation. The results show that: (a) GSMaP_Gauge exhibits the highest correlation with ground‐based gauges, while IMERG_Uncal and IMERG_Cal perform best in the estimation of the amount of precipitation. Satellite products generally perform better during summer while ERA5‐L sometimes outperforms satellite products in spring and autumn. (b) The evaluation results for different precipitation types reveal that all the QPE products face significant challenges in accurately describing convective precipitation. They tend to underestimate convective precipitation and fail to properly capture the intensity and location of heavy precipitation. (c) In heavy convective precipitation cases, the evaluated QPE products show various issues in accurately capturing the intensity and spatiotemporal variation of precipitation. Almost all QPE products underestimate maximum precipitation (both hourly precipitation and accumulated precipitation) and small‐scale (about 50 km or less) spatial variability of precipitation. IMERG_Uncal, IMERG_Cal, and GSMaP_MVK perform better than other products in heavy convective precipitation cases. This study provides new insights into the quality of QPE products in different types of precipitation. The analysis of the quality of these QPE products serves as a valuable indicator of their potential applications, particularly in flash flood simulations, while also underscoring the critical need for improving precipitation product quality.

Assessing Turbulence Model Performance in OpenFOAM for Natural Convection Simulations

Abstract Natural convection processes are pivotal in various engineering applications, necessitating accurate and reliable computational fluid dynamics (CFD) models for their simulation. This study evaluates the efficacy of different turbulence models implemented in OpenFOAM for a natural convection scenario, aiming to identify the most suitable model for capturing complex thermal and fluid dynamic behaviors. We compared several turbulence models, including the k − ε, k − ω, and k − ω SST, using a benchmark thermal convection case. Our methodology involved setting up the simulations to reflect realistic thermal gradients and boundary conditions, followed by a rigorous analysis of temperature distribution, vertical velocity profiles, and computational efficiency. The results indicate that the k − ω SST achieved the lowest averaged root mean square error (RMSE) values for temperature (0.076) and vertical velocity (0.03) while also requiring the fewest convergence iterations (314) compared to k − ε (411) and k − ω (1474). These findings demonstrate that the k − ω SST model is a suitable compromise between accuracy and computational cost for engineering applications. This study underscores the importance of selecting an appropriate turbulence model in OpenFOAM to enhance the accuracy of natural convection simulations, which can significantly influence design and safety considerations in engineering systems.

A Comparative Study of Cloud Microphysics Schemes in Simulating a Quasi-Linear Convective Thunderstorm Case

An investigation is undertaken to explore a sudden quasi-linear precipitation and gale event that transpired in the afternoon of 30 May 2024 over Beijing. It was situated at the southwestern periphery of a double-center low-vortex system, where a moisture-rich belt efficiently channeled abundant warm, humid air northward from the south. The interplay between dynamical lifting, convergent airflow-induced uplift, and the amplifying effects of the northern mountainous terrain’s topography creates favorable conditions that support the development and persistence of quasi-linear convective precipitation, accompanied by gale-force winds at the surface. The study also analyzes the impacts of five microphysics schemes (Lin, WSM6, Goddard, Morrison, and WDM6) employed in a weather research and forecasting (WRF) numerical model, with which the simulated rainfall and radar reflectivity are compared against ground-based rain gauge network and weather radar observations, respectively. Simulations with the five microphysics schemes demonstrate commendable skills in replicating the macroscopic quasi-linear pattern of the event. Among the schemes assessed, the WSM6 scheme exhibits its superior agreement with radar observations. The Morrison scheme demonstrates superior performance in predicting cumulative rainfall. Nevertheless, five microphysics schemes exhibit limitations in predicting the rainfall amount, the rainfall duration, and the rainfall area, with a discernible lag of approximately 30 min in predicting precipitation onset, indicating a tendency to forecast peak rainfall events slightly posterior to their true occurrence. Furthermore, substantial disparities emerge in the simulation of the vertical distribution of hydrometeors, underscoring the intricacies of microphysical processes.

Evolution Characteristics of Convective Clouds With Relatively Small Scales Over South China

AbstractAs a crucial element in the Earth's system, development of convective clouds is still insufficiently understood and simulated in both weather and climate models, particularly for small‐scale regional convective clouds. In this study, a series of convective clouds cases with relatively small scales are selected over south China, and the evolution characteristics of those convective clouds are investigated using high spatiotemporal resolution geostationary satellite data. Statistical results show that the shorter the life cycle or the smaller the area, the higher the proportion of convective clouds. Notably, approximately 79.23% of convective clouds have a life cycle of less than 3 hr, and 63.81% have an area of less than 500 km2 for selected cases. In addition, there are significant differences in the cloud characteristics and meteorological parameters during various convective cloud stages and durations. Nevertheless, the relative proportions of convective clouds at three identified stages remain relatively constant with almost no dependence on duration of convective clouds, which are 33.50%, 23.92%, and 42.58% for the developing, mature, and dissipation stages, respectively. In addition, we find that the cloud‐top cooling rate during the developing stage also affects the characteristics of the later stage of convective clouds. Quantitatively, the average cloud area and duration changed by 157.03 km2 and 0.17 hr when the cloud‐top cooling rate varies by 15 K/h.

Development of Multiscale EnKF within GSI and Its Applications to Multiple Convective Storm Cases with Radar Reflectivity Data Assimilation Using the FV3 Limited-Area Model

Abstract To improve the representation of all relevant scales in initial conditions for large-domain convection-allowing models, a new multiscale ensemble Kalman filter (MEnKF) algorithm is developed and implemented within the Gridpoint Statistical Interpolation analysis system (GSI) data assimilation framework coupled with the Finite-Volume Cubed-Sphere Dynamical Core (FV3) limited-area model. The algorithm utilizes ensemble background error covariances filtered to match the observations assimilated. This is realized in a sequential manner. 1) When assimilating coarse-resolution observations such as radiosondes, ensemble background perturbations are filtered to remove scales smaller than those the observations can represent, along with relatively large horizontal localization radii to ensure low-noise and balanced analysis increments. 2) The resulting ensemble analyses from the first step then serve as the background to assimilate denser observations such as radar data with smaller localization radii. Several passes can be taken to assimilate all observations. In this paper, vertically increasing horizontal filter scales are used when assimilating rawinsonde and surface observations together, while radar data are assimilated in the second step. The algorithm is evaluated through six convective storm cases during May 2021, with cycled assimilation of either conventional data only or with additional radar reflectivity followed by 24-h ensemble forecasts. Overall, positive impacts of the MEnKF on forecasts are obtained regardless of reflectivity data; its advantage over the single-scale EnKF is most significant in surface humidity and temperature forecasts up to at least 12 h. More accurate hourly precipitation forecasts with MEnKF can last up to 24 h for light rain. Furthermore, MEnKF forecasts higher ensemble probabilities for the observed hazardous events.

Deep Entry of Low‐Energy Ions Into Mercury’s Magnetosphere: BepiColombo Mio’s Third Flyby Observations

AbstractAlthough solar wind‐driven convection is expected to dominate magnetospheric circulation at Mercury, its exact pattern remains poorly characterized by observations. Here we present BepiColombo Mio observations during the third Mercury flyby indicative of convection‐driven transport of low‐energy dense ions into the deep magnetosphere. During the flyby, Mio observed an energy‐dispersed ion population from the duskside magnetopause to the deep region of the midnight magnetosphere. A comparison of the observations with backward test particle simulations suggests that the observed energy dispersion structure can be explained in terms of energy‐selective transport by convection from the duskside tail magnetopause. We also discuss the properties and origins of more energetic ions observed in the more dipole‐like field regions of the magnetosphere in comparison to previously reported populations of the plasma sheet horn and ring current ions. Additionally, forward test particle simulations predict that most of the observed ions on the nightside will precipitate onto relatively low‐latitude regions of the nightside surface of Mercury for a typical convection case. The presented observations and simulation results reveal the critical role of magnetospheric convection in determining the structure of Mercury's magnetospheric plasma. The upstream driver dependence of magnetospheric convection and its effects on other magnetospheric processes and plasma‐surface interactions should be further investigated by in‐orbit BepiColombo observations.

Evaluating synthetic aperture radar surface winds for convective squalls in the Gulf of Mexico

AbstractThe detection and quantification of strong sea surface winds, reaching up to 25 m·s−1, whether associated with deep convection aloft or not, have been extensively discussed in previous studies. This method involves the combined observation of the same event from both low‐orbit altitude and geostationary (GEO) satellites. Strong surface winds observed by the Sentinel‐1 C‐band synthetic aperture radar (SAR) are robustly associated with deep convective clouds detected by GEO infrared sensors. The current paper aims to generalize the previous assessment of several convective wind events by collecting a larger dataset and comparing these data to in‐situ wind observations. To achieve this, we evaluated wind speeds retrieved from Sentinel‐1 SAR images against corresponding in‐situ wind measurements from all active buoys/stations in the Gulf of Mexico. Significant agreement between satellite‐based winds and in‐situ data was achieved, particularly for wind speeds exceeding 3 m·s−1, with even better agreement for wind speeds over 10 m·s−1. From this dataset, three specific convective cases were extracted to illustrate various stages of convective squall events: before, during, and after the occurrence of a squall peak. In each case, comparison with in‐situ measurements showed that SAR‐estimated wind speeds closely matched observed speeds, including the peak convective winds, which were estimated at 18.90 m·s−1 and measured at 20.69 m·s−1. Furthermore, combining these findings with GOES‐16 sequential images illustrates the temporal and spatial similarity between deep convection areas, estimated strong sea surface wind patterns, and measured wind speeds.

The performance of a variable‐resolution 300‐m ensemble for forecasting convection over London

AbstractWhen using sub‐km models to forecast convection, it is important to have a large enough domain to allow convection to fully spin‐up from the lateral boundaries. However, running large domains is computationally expensive and while it may be feasible for research purposes it is not yet feasible for routinely run models, such as the Met Office 300‐m London model. To try and mitigate the spin‐up issues in the London model, a variable‐resolution 300‐m London Model (the ‘LMV’) has been developed, which allows the boundaries of the London model to be further away from areas of interest (e.g., London Heathrow) at lower computational cost. Results from several cases of summertime convection show that the convective storms in the variable‐resolution model are more like those in a large fixed‐resolution 300‐m model than those in the much smaller London model. This implies variable resolution is a viable option for increasing the size of the London model domain without increasing the computational costs too much. Extended evaluation of the LMV was conducted during summer 2022, running as an ensemble nested inside the Met Office's operational UK ensemble (MOGREPS‐UK). Overall, the LMV looks promising for high‐impact convective events as it is better able to represent the organisation of convection into lines or larger storms whereas MOGREPS‐UK tends to simulate isolated, circular storms. This often leads to more reliable probabilities of heavy rainfall in the LMV ensemble compared to MOGREPS‐UK. However, there is an issue with the LMV producing too many small precipitating showers in situations where there should only be shallow clouds. This is thought to be a result of shallow clouds getting too deep in the model and precipitating erroneously.

Convective Initiation Nowcasting in South China Using Physics‐Augmented Random Forest Models and Geostationary Satellites

AbstractConvective initiation (CI) nowcasting in subtropical regions often faces challenges, such as complex physical processes and imbalanced samples of CI events, resulting in a high false alarm ratio (FAR). In this paper, we propose a Storm Warning System with Physics‐Augmentation (SWASP) based on the random forest algorithm and cloud physical conditions, using Himawari‐8 Advanced Himawari Imager data from April to September 2019 in South China. The cloud physical conditions (e.g., cloud‐top cooling rates) were investigated to establish regional thresholds for convection occurrence. Ancillary information, including elevation, satellite zenith angle, and latitude, was also incorporated into the SWASP model. Compared to conventional methods, the SWASP model exhibits an improved probability of detection by 0.11 and 0.08 and a decreased FAR by 0.38 and 0.44 for daytime and nighttime forecasts. Moreover, the SWASP model enables the detection of local convective storm systems about 30 min to 1 hr ahead of radar detection in typical convective storm cases. This study contributes to further advancements of the SWASP model by incorporating physical conditions and emphasizes the potential application of geostationary satellites in convective early warnings.

On the impact of true polar wander on heat flux patterns at the core–mantle boundary

Abstract. The heat flux across the core–mantle boundary (CMB) is a fundamental variable for Earth evolution and internal dynamics. Seismic tomography provides access to seismic heterogeneities in the lower mantle, which can be related to present-day thermal heterogeneities. Alternatively, mantle convection models can be used to either infer past CMB heat flux or to produce statistically realistic CMB heat flux patterns in self-consistent models. Mantle dynamics modifies the inertia tensor of the Earth, which implies a rotation of the Earth with respect to its spin axis, a phenomenon called true polar wander (TPW). This rotation must be taken into account to link the dynamics of the mantle to the dynamics of the core. In this study, we explore the impact of TPW on the CMB heat flux over long timescales (∼1 Gyr) using two recently published mantle convection models: one model driven by a plate reconstruction and a second that self-consistently produces a plate-like behaviour. We compute the geoid in both models to correct for TPW. In the plate-driven model, we compute a total geoid and a geoid in which lateral variations of viscosity and density are suppressed above 350 km depth. An alternative to TPW correction is used for the plate-driven model by simply repositioning the model in the original paleomagnetic reference frame of the plate reconstruction. The average TPW rates range between 0.4 and 1.8° Myr−1, but peaks up to 10° Myr−1 are observed. We find that in the plate-driven mantle convection model used in this study, the maximum inertia axis produced by the model does not show a long-term consistency with the position of the magnetic dipole inferred from paleomagnetism. TPW plays an important role in redistributing the CMB heat flux, notably at short timescales (≤10 Myr). Those rapid variations modify the latitudinal distribution of the CMB heat flux, which is known to affect the stability of the magnetic dipole in geodynamo simulations. A principal component analysis (PCA) is computed to obtain the dominant CMB heat flux pattern in the different cases. These heat flux patterns are representative of the mantle convection cases studied here and can be used as boundary conditions for geodynamo models.

Large-eddy simulation of axial, radial and mixed centrifugal convection in a closed rotating cavity

Large-eddy simulations (LES) of centrifugal convection in a closed rotating cavity with different thermal boundary conditions are presented for Rayleigh numbers (Ra) 107∼109. Previous results for radial convection with a positive radial temperature gradient and for axial convection with low Ra are confirmed. For axial convection, turbulence develops in the core flow at Ra=109, but is considerably weaker than the turbulence for the radial and mixed convection. In mixed convection, the mean core temperature shows little radial variation as in radial convection, but has a significant axial temperature gradient as in axial convection. Compared to the radial and axial convection cases, both shroud and disc heat transfer are increased in mixed convection. Changes in disc heat transfer from the axial convection case are particularly strong. In all the conditions, laminar kinematic Ekman layers occur on the discs, but the disc thermal boundary layers for axial and mixed convection are considerably thicker.

A-priori evaluation of data-driven models for large-eddy simulations in Rayleigh–Bénard convection

Natural convection is a commonly occurring heat-transfer problem in many industrial flows and its prediction with conventional large eddy simulations (LES) at higher Rayleigh numbers using progressively coarser grids leads to increasingly inaccurate estimates of important performance indicators, such as Nusselt number (Nu). Thus, to improve the heat transfer predictions, we utilize Gene Expression Programming (GEP) to develop sub-grid scale (SGS) stress and SGS heat-flux models simultaneously for LES. The models’ development is performed using reference direct numerical simulation data of a typical natural convection case, i.e. the Rayleigh–Bénard convection (RBC). The training frameworks are built by using alignment as the evaluation metrics of the basis functions when comparing to the Gaussian-filtered SGS stress and SGS heat-flux. The trained models in isotropic form, by utilizing the L2 norm of the grid cell ΔL2 as the length scale, demonstrate good performance in the bulk region, but less improved performance in the near wall region. It is shown, that for LES of wall-bounded flow, the GEP models in anisotropic form, i.e. using different grid length scale for the different spatial directions, are required to obtain generalized models suitable for different regions. Consequently, the a-priori results demonstrate a significant improvement in the prediction of both instantaneous and mean quantities for a wide range of filter widths.

A New Comprehensive Cloud Macrophysics Scheme With a Prognostic Dual‐Triangular PDF

AbstractTo improve cloud simulation in a general circulation model, we develop a new cloud macrophysics scheme that treats detrained cumulus generated by convective detrainment process separately from pure stratus; prognoses two symmetric triangular probability density functions of total specific humidity for each detrained cumulus and pure stratus; and diagnoses both cloud fraction and cloud condensate in all liquid, ice, and mixed‐phases in a consistent and unified way without any adjustment to remove empty or very dense cloud. Supersaturation is allowed within ice cloud. The new scheme (“NEW”) is compared with the previous model (“OLD”) using single‐column simulations for subtropical marine stratocumulus (DYCOMS2) and continental deep convection (ARM97) cases. In DYCOMS2, both NEW and OLD produce vertical profiles of grid‐mean cloud condensate similar to large‐eddy simulation. In ARM97, compared with OLD, NEW simulates less sporadic vertical profiles of in‐cloud condensates, due to consistent diagnosis of cloud fraction and cloud condensate; more continuously‐varying detrained cumulus with time, due to prognostic treatment of detrained cumulus; and ice cloud fraction and ice condensate similar to those of OLD, in spite of completely different treatment of ice cloud processes. The global performance of NEW is similar to OLD with improved relative humidity. Compared to OLD, NEW simulates more and improved cloud condensate, but less and degraded cloud fraction, particularly, in the lower troposphere. Detrained cumulus is moister and colder and has a larger moisture variance than pure stratus. Overall, NEW simulates stronger condensation‐deposition rates than OLD, due in part to the separate treatment of detrained cumulus and pure stratus.

Lagrangian Stochastic Modeling of Stratified Atmospheric Boundary Layer

A single-column turbulence model for stratified atmospheric boundary layer (ABL), which solves the transport equations of turbulence probability density function (PDF) using a Lagrangian stochastic modeling (LSM) approach, is proposed in this study. This study adopts previously developed stochastic differential equations (SDEs) for particle velocity and temperature and extends the LSM to simulate inhomogeneous turbulence. The proposed LSM is tested for its ability to fully simulate statistics of inhomogeneous stratified turbulence. In the model, particles evolve by SDEs, and turbulence statistics are calculated by averaging the properties of particles. The model provides a full representation of turbulence PDF and simulates turbulent transport without any modeling assumption. The model performance is evaluated against large-eddy simulation (LES) results in the simulations of convective and stable ABL cases. For the convective ABL, LSM realistically simulates the entrainment process with the temperature and heat flux profiles that closely match with LES. The joint PDF simulated by LSM reproduces a curved and highly skewed shape, and some distinct features, like the asymmetric distribution of vertical velocity and the separation of the PDF in the entrainment zone, are simulated. LSM also reproduces the entrainment enhancement by wind shear in the simulation of sheared convective ABL. The LSM simulation of stable ABL predicts realistic turbulence intensity and mean field profiles, where Gaussian-like PDFs are simulated both in LSM and LES.

The effect of peristalsis on dispersion in Casson fluid flow

The present study examines the peristaltic flow of a non-Newtonian (Casson) fluid and solute transport through a flexible tube. Using the long-wavelength approximation, an analytical solution for the Casson fluid velocity is obtained in the axial and radial directions. Then, a numerical solution to the solute concentration is computed using the standard Galerkin finite element method (FEM) for the case of solutal convection-diffusion and the Discontinuous Galerkin FEM for the pure convection case. Graphical results are presented for the axial and local solute concentrations, and the influence of peristaltic wave amplitude, volumetric flow rate, modified Péclet number, time, yield stress, and pertinent initial condition parameters were investigated.

Analytical solution model of heat transfer for energy soldier piles during excavation to backfilling

This paper presents a two-dimensional heat transfer model for energy soldier piles during excavation and after backfilling. Based on Green's function and separation of variables method, this model considers the heat transfer process from various angles during excavation and after backfilling, deriving a series of analytical solutions for the heat transfer processes. It is more suitable for solving the heat transfer problem of energy soldier piles. The accuracy of the analytical solution was verified by numerical simulation and classical analytical solutions. Then, the effects of air convection coefficient and backfill materials' thermal diffusivity on heat transfer are analyzed. The results show that the temperature rise of both the soil and the pile in the non-excavated case (ordinary energy pile) is lower than that of the various convective coefficient cases, and the convective heat transfer contributes to the heat transfer capacity of energy soldier piles. After backfilling, materials with higher thermal diffusivity have smaller temperature rise. Conversely, materials with lower thermal diffusivity have higher temperature rise. Under the long-term operation strategy, the heat flux within the soil and backfill is higher and favorable for heat transfer by selecting the backfill with lower thermal diffusivity.

How do operational meteorologists perceive model performance for elevated convection?

AbstractOperational Meteorologists (OMs) in the Met Office have a perception that elevated convection is not well represented in kilometre‐scale models, which are generally associated with an improved representation of convection. Here, we consider why there may be a problem with representing elevated convection and consider how OMs judge the model to be poor so often. Three OMs have subjectively scored and classified observed elevated convection cases over the UK from 2017 to 2020. Continental plumes (warm, moist, air coming from the near continent or Africa) account for 73% of the cases. The most frequent errors are associated with (i) location, (ii) organisation, (iii) timing and (iv) intensity of the convection. Thus, OMs perceive that the biggest problem with predicting elevated convection is constraining the location of the convective events. The location errors are particularly prevalent for events coming to the UK from the near continent. The location errors are most frequently identified for flow regimes coming from the near continent in weakly forced synoptic conditions. The identification of this problem enables the specific targeting of research into continental plumes (for UK elevated convection) but also raises questions around the role of lateral boundary conditions in the forecasts of elevated convection.

Unsteady Numerical Investigation Strategy of Natural Convection in an Isosceles Superimposed Triangular Enclosure

In energy applications, convection plays a dominant role in the transport of energy for the proper design in order to achieve higher heat transfer rates. Where the fluid motion is simply induced by density gradients. This study is concerned with transient natural convection in an isosceles-superimposed triangular enclosure. The inclination of the inclined partitions walls was θ =45°. Critical Rayleigh numbers have been obtained: Ra=106, especially for the fluid crushed between the two triangles where we can visualize the critical convection transaction between the air and water. The results in quantitative measurement of average Nusselt number change and qualitative visualization of streamline and isotherms are examined. The air and water streamlines and the temperature fields were obtained for the Rayleigh numbers 103 ≤ Ra ≤ 108 for both cases studied. Besides, the highest heat transfer performance is observed during the natural convection case of the water fluid, and the lowest heat is transferred when the fluid is dilatant. The triangular shape can greatly enhance the heat transfer from the bottom to the top at first in a smooth and harmonious manner, and then it turns into a more complex and disorderly shape when the water reaches high temperatures.

Comparison and Synthesis of Precipitation Data from CloudSat CPR and GPM KaPR

Employing different bands of radar to detect precipitation information in identical regions enables the acquisition of a more comprehensive precipitation cloud structure, thereby refining the continuity and completeness of precipitation measurements. This study first compared the coincident data from CloudSat W-band cloud profiling radar (CPR) and Global Precipitation Measurement Mission (GPM) Ka-band precipitation radar (KaPR) from 2014 to 2017, and then a synthesis of the radar reflectivity from CPR and KaPR was attempted to obtain a complete cloud and precipitation structure. The findings of the reflectivity comparisons indicated that the echo-top height identified by CPR is on average 3.6 to 4.2 km higher than that from KaPR, due to the higher sensitivity. Because of strong attenuation of CPR by liquid-phase particles, the reflectivity below the height of the melting layer usually shows an opposite gradient to KaPR with decreasing altitude. The difference in the near-surface rain rates of CPR and KaPR was found to be related to reflectivity gradients in the vertical direction, and the larger the reflectivity gradients, the greater the differences in near-surface rain rates. For better representing the complete vertical structure of precipitation clouds and improving the consistency of the reflectivity and precipitation rate, the radar reflectivity was weighted, synthesized from CPR and KaPR based on the gradient difference of the reflectivity from the two radars. We presented the synthesis results for a stratiform cloud and a deep convective case, and Spearman’s rank correlation coefficient (rs) between the GPM combined radiometer precipitation rate and the radar reflectivity was utilized to analyze the performance of the synthesis. The consistency between synthesized reflectivity and precipitation rate in the non-liquid phase was improved compared with KaPR, and the rs of the ice and mixed phases was increased by about 12% and 10%, respectively.