Adjoint Matching Condition for Parameterized Discontinuities－A Derivation Using Lagrangian-form Costfunction

The generalized adjoint property and adjoint matching condition for systems that contain discontinuous on / off switches are derived by a perturbation analysis of the Lagranging-form costfunction     

A New Algorithm for Sea Fog／Stratus Detection Using GMS-5 IR Data

A new algorithm for the detection of fog/stratus over the ocean from the GMS-5 infrared (IR) channel data is presented. The new algorithm uses a clear-sky radiance composite map (CSCM) to compare the hourly observations of the IR radiance. The feasibility of the simple comparison is justified by the theoretical simulations of the fog effect on the measured radiance using a radiative transfer model. The simulation results show that the presence of fog can be detected provided the visibility is worse than 1 km and the background clear-sky radiances are accurate enough with known uncertainties. For the current study, an accurate CSCM is constructed using a modified spatial and temporal coherence method, which takes advantage of the high temporal resolution of the GMS-5 observations. The new algorithm is applied for the period of 10-12 May 1999, when heavy sea fog formed near the southwest coast of the Korean Peninsula. Comparisons of the fog/stratus index, defined as the difference between the measured and clear-sky brightness temperature, from the new algorithm to the results from other methods, such as the dual channel difference of NOAA/AVHRR and the earth albedo method, show a good agreement. The fog/stratus index also compares favorably with the ground observations of visibility and relative humidity. The general characteristics of the fog/stratus index and visibility are relatively well matched, although the relationship among the absolute values, the fog/stratus index, visibility, and relative humidity, varies with time. This variation is thought to be due to the variation of the atmospheric conditions and the characteristics of fog/stratus, which affect the derived fog/stratus index.     

A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes——A Pilot Study

Extreme Mei-yu rainfall(MYR) can cause catastrophic impacts to the economic development and societal welfare in China. While significant improvements have been made in climate models, they often struggle to simulate local-to-regional extreme rainfall(e.g., MYR). Yet, large-scale climate modes(LSCMs) are relatively well represented in climate models.Since there exists a close relationship between MYR and various LSCMs, it might be possible to develop causality-guided statistical models for MYR pr...     

A Heavy Rainfall Event in Autumn over Beijing—Atmospheric Circulation Background and Hindcast Simulation Using WRF

Heavy rainfall events often occur in Beijing during summer but rarely in autumn. However, during 3–5 September 2015, an exceptionally heavy rainfall event occurred in Beijing. Based on the reanalysis data and the Weather Research and Forecasting (WRF) model simulations, the main contributing factors and the predictability of this heavy rainfall event were examined through comprehensive analyses of vorticity advection and water vapor transport/ budget. The results indicate that a “high-in-the-east–low-in-the-west” pattern of 500-hPa geopotential height over the Beijing area played an important role. The 850-hPa low-level jet (LLJ) provided a mechanism for rising motion and transported abundant water vapor into the Beijing area. Two-way nested hindcast experiments using WRF well reproduced the atmospheric circulation and LLJ. Quantitative analysis indicates that the WRF model with the rapid update cycle (RUC) land surface scheme and the single-moment 6-class (WSM6) microphysics scheme exhibited the best skill, and the model performance improved with a higher resolution. Further analysis indicates that the bias in the precipitation forecast was caused by the bias in water vapor transport.     

Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method——A Case Study of a Mesoscale Convective System

Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of nowcasting and short-term forecasting. Physical initialization combined with the three-dimensional variational data assimilation method(PI3 DVar_rh) is used in this study to assimilate two kinds of observation data simultaneously, in which radar data are dominant and lightning data are introduced as constraint conditions. In this way, the advantages of dual observations are adopted. To verify the effect of assimilating radar and lightning data using the PI3 DVar_rh method, a severe convective activity that occurred on 5 June 2009 is utilized, and five assimilation experiments are designed based on the Weather Research and Forecasting(WRF) model. The assimilation of radar and lightning data results in moister conditions below cloud top, where severe convection occurs; thus, wet forecasts are generated in this study.The results show that the control experiment has poor prediction accuracy. Radar data assimilation using the PI3 DVar_rh method improves the location prediction of reflectivity and precipitation, especially in the last 3-h prediction, although the reflectivity and precipitation are notably overestimated. The introduction of lightning data effectively thins the radar data, reduces the overestimates in radar data assimilation, and results in better spatial pattern and intensity predictions. The predicted graupel mixing ratio is closer to the distribution of the observed lightning,which can provide more accurate lightning warning information.     

A new Building Energy Model coupled with an Urban Canopy Parameterization for urban climate simulations—part II. Validation with one dimension off-line simulations

Recent studies show that the fluxes exchanged between buildings and the atmosphere play an important role in the urban climate. These fluxes are taken into account in mesoscale models considering new and more complex Urban Canopy Parameterizations (UCP). A standard methodology to test an UCP is to use one-dimensional (1D) off-line simulations. In this contribution, an UCP with and without a Building Energy Model (BEM) is run 1D off-line and the results are compared against the experimental data obtained in the BUBBLE measuring campaign over Basel (Switzerland) in 2002. The advantage of BEM is that it computes the evolution of the indoor building temperature as a function of energy production and consumption in the building, the radiation coming through the windows, and the fluxes of heat exchanged through the walls and roofs as well as the impact of the air conditioning system. This evaluation exercise is particularly significant since, for the period simulated, indoor temperatures were recorded. Different statistical parameters have been calculated over the entire simulated episode in order to compare the two versions of the UCP against measurements. In conclusion, with this work, we want to study the effect of BEM on the different turbulent fluxes and exploit the new possibilities that the UCP–BEM offers us, like the impact of the air conditioning systems and the evaluation of their energy consumption.     

A new building energy model coupled with an urban canopy parameterization for urban climate simulations—part I. formulation, verification, and sensitivity analysis of the model

The generation of heat in buildings, and the way this heat is exchanged with the exterior, plays an important role in urban climate. To analyze the impact on urban climate of a change in the urban structure, it is necessary to build and use a model capable of accounting for all the urban heat fluxes. In this contribution, a new building energy model (BEM) is developed and implemented in an urban canopy parameterization (UCP) for mesoscale models. The new model accounts for: the diffusion of heat through walls, roofs, and floors; natural ventilation; the radiation exchanged between indoor surfaces; the generation of heat due to occupants and equipments; and the consumption of energy due to air conditioning systems. The behavior of BEM is compared to other models used in the thermal analysis of buildings (CBS-MASS, BLAST, and TARP) and with another box-building model. Eventually, a sensitivity analysis of different parameters, as well as a study of the impact of BEM on the UCP is carried out. The validations indicate that BEM provides good estimates of the physical behavior of buildings and it is a step towards a modeling tool that can be an important support to urban planners.     

Heterogeneity-Induced Heat-Flux Patterns in the Convective Boundary Layer: Can they be Detected from Observations and is There a Blending Height?—A Large-Eddy Simulation Study for the LITFASS-2003 Experiment

An understanding of how the convective boundary layer (CBL) is mixed under heterogeneous surface forcing is crucial for the interpretation of area-averaged turbulence measurements. To determine the height and degree to which a complex heterogeneous surface affects the CBL, large-eddy simulations (LES) for two days of the LITFASS-2003 experiment representing two different wind regimes were undertaken. Spatially-lagged correlation analysis revealed the turbulent heat fluxes to be dependent on the prescribed surface flux pattern throughout the entire CBL including the entrainment layer. These findings prompted the question of whether signals induced by surface heterogeneity can be measured by airborne systems. To examine this question, an ensemble of virtual flights was conducted using LES, according to Helipod flight measurements made during LITFASS-2003. The resulting ensemble-averaged heat fluxes indicated a clear dependence on the underlying surface up to the top of the CBL. However, a large scatter between the flux measurements in different ensemble runs was observed, which was the result of insufficient sampling of the largest turbulent eddies. The random and systematic errors based on the integral length scale did not indicate such a large scatter. For the given flight leg lengths, at least 10–15 statistically independent flight measurements were necessary to give a significant estimate of heterogeneity-induced signals in the CBL. The need for ensemble averaging suggests that the observed blending of heterogeneity-induced signals in the CBL can be partly attributed to insufficient averaging.