Large Eddy Simulation of Vertical Structure and Size Density of Deep Layer Clouds

In a convective scheme featuring a discretized cloud size density, the assumed lateral mixing rate is inversely proportional to the exponential coefficient of plume size. This follows a typical assumption of-1, but it has unveiled inherent uncertainties, especially for deep layer clouds. Addressing this knowledge gap, we conducted comprehensive large eddy simulations and comparative analyses focused on terrestrial regions. Our investigation revealed that cloud formation adheres to the tenets of Bernoulli trials, illustrating power-law scaling that remains consistent regardless of the inherent deep layer cloud attributes existing between cloud size and the number of clouds. This scaling paradigm encompasses liquid, ice, and mixed phases in deep layer clouds. The exponent characterizing the interplay between cloud scale and number in the deep layer cloud, specifically for liquid, ice, or mixed-phase clouds, resembles that of shallow convection,but converges closely to zero. This convergence signifies a propensity for diminished cloud numbers and sizes within deep layer clouds. Notably, the infusion of abundant moisture and the release of latent heat by condensation within the lower atmospheric strata make substantial contributions. However, this role in ice phase formation is limited. The emergence of liquid and ice phases in deep layer clouds is facilitated by the latent heat and influenced by the wind shear inherent in the middle levels. These interrelationships hold potential applications in formulating parameterizations and post-processing model outcomes.

Effect of Mesoscale Land Use Change on Characteristics of Convective Boundary Layer:Semi-Idealized Large Eddy Simulations over Northwest China

Although large-scale topography and land use have been properly considered in weather and climate models, the effect of mesoscale and microscale heterogeneous land use on convective boundary layer(CBL) has not been fully understood yet. In this study, the influence of semi-idealized strip-like patches of oases and deserts, which resemble irrigated land use in Northwest China, on the CBL characteristics, is investigated based on the Weather Research and Forecasting(WRF)-large eddy simulation(LES) driven by observed land surface data. The influences of soil water content in oases on aloft CBL flow structure, stability, turbulent kinetic energy(TKE), and vertical fluxes are carefully examined through a group of sensitivity experiments. The results show that secondary circulation(SC)/turbulent organized structures(TOS) is the strongest/weakest when soil water content in oases is close to saturation(e.g.,when the oases are irrigated). With the decrease of soil water content in oases(i.e., after irrigation), SC(TOS) becomes weak(strong) in the lower and middle CBL, the flux induced by SC and TOS becomes small(large), which has a dramatic impact on point measurement of eddy covariance(EC) fluxes. The flux induced by SC and TOS has little influence on EC sensible heat flux, but great influence on EC latent heat flux. Under this circumstance, the area averaged heat flux cannot be represented by point measurement of flux by the EC method, especially just after irrigation in oases. Comparison of imbalance ratio(i.e., contribution of SC and TOS to the total flux) reveals that increased soil moisture in oases leads to a larger imbalance ratio as well as enhanced surface heterogeneity. Moreover,we found that the soil layer configuration at different depths has a negligible impact on the CBL flux properties.

Factors Influencing Diurnal Variations of Cloud and Precipitation in the Yushu Area of the Tibetan Plateau

Using the cloud radar,ground observations,and ECMWF Reanalysis v5(ERA5)data,we investigate the factors influencing nighttime precipitation during summer in the Yushu area of the Tibetan Plateau(TP).The cloud top height(CTH),cloud base height(CBH),and liquid water content(LWC)are compared between non-precipitation and precipitation days.The results show that the average CTH on precipitation days in Yushu is below 10 km above ground level(AGL)in the daytime,whereas it exceeds 10 km AGL at night,with the maximum at 2300 BT(Beijing Time).The CBH is in-phase with the dewpoint spread.The precipitation intensity and CTH are in-phase with the LWC.The hourly averaged precipitation intensity and convective available potential energy in ERA5 reach their maximums at2100 BT,which is 3 h ahead of their observed counterparts.There is descending motion in the mid day on non-precipitation days,whereas there is ascending motion at night on precipitation days.In addition,the horizontal wind direction in the lower level(below 5000 m)shows clockwise rotation from morning to night.Wind shear occurs in the mid level of the atmosphere,accompanied by a subtropical westerly jet in the upper level.The difference in horizontal wind speed between 200 and 500 hPa is positively related to the LWC,thereby contributing to the formation of upper-level cloud.

Assessing the Performance of Separate Bias Kalman Filter in Correcting the Model Bias for Estimation of Soil Moisture Profiles

The performance of separate bias Kalman filter (SepKF) in correcting the model bias for the improvement of soil moisture profiles is evaluated by assimilating the near-surface soil moisture observations into a land surface model (LSM). First, an observing system simulation experiment (OSSE) is carried out, where the true soil moisture is known, two types of model bias (i.e., constant and sinusoidal) are specified, and the bias error covariance matrix is assumed to be proportional to the model forecast error covariance matrix with a ratio λ. Second, a real assimilation experiment is carried out with measurements at a site over Northwest China. In the OSSE, the soil moisture estimation with the SepKF is improved compared with ensemble Kalman filter (EnKF) without the bias filter, because SepKF can properly correct the model bias, especially in the situation with a large model bias. However, the performance of SepKF becomes slightly worse if the constant model bias increases or temporal variability of the sinusoidal model bias becomes large. It is suggested that the ratio λ should be increased (decreased) in order to improve the soil moisture estimation if temporal variability of the sinusoidal model bias becomes high (low). Finally, the assimilation experiment with real observations also shows that SepKF can further improve the estimation of soil moisture profiles compared with EnKF without the bias correction.