Numerical Simulations of a Florida Sea Breeze and Its Interactions with Associated Convection:Effects of Geophysical Representation and Model Resolution

The Florida peninsula in the USA has a frequent occurrence of sea breeze(SB)thunderstorms.In this study,the numerical simulation of a Florida SB and its associated convective initiation(CI)is simulated using the mesoscale community Weather Research and Forecasting(WRF)model in one-way nested domains at different horizontal resolutions.Results are compared with observations to examine the accuracy of model-simulated SB convection and factors that influence SB CI within the simulation.It is found that the WRF model can realistically reproduce the observed SB CI.Differences are found in the timing,location,and intensity of the convective cells at different domains with various spatial resolutions.With increasing spatial resolution,the simulation improvements are manifested mainly in the timing of CI and the orientation of the convection after the sea breeze front(SBF)merger into the squall line over the peninsula.Diagnoses indicate that accurate representation of geophysical variables(e.g.,coastline and bay shape,small lakes measuring 10-30 km2),better resolved by the high resolution,play a significant role in improving the simulations.The geophysical variables,together with the high resolution,impact the location and timing of SB CI due to changes in low-level atmospheric convergence and surface sensible heating.More importantly,they enable Florida lakes(30 km2 and larger)to produce noticeable lake breezes(LBs)that collide with the SBFs to produce CI.Furthermore,they also help the model reproduce a stronger convective squall line caused by merging SBs,leading to more accurate locations of postfrontal convective systems.

Numerical Simulation of the Rapid Intensification of Hurricane Katrina(2005):Sensitivity to Boundary Layer Parameterization Schemes

Accurate forecasting of the intensity changes of hurricanes is an important yet challenging problem in numerical weather prediction. The rapid intensification of Hurricane Katrina（2005） before its landfall in the southern US is studied with the Advanced Research version of the WRF（Weather Research and Forecasting） model. The sensitivity of numerical simulations to two popular planetary boundary layer（PBL） schemes, the Mellor–Yamada–Janjic（MYJ） and the Yonsei University（YSU） schemes, is investigated. It is found that, compared with the YSU simulation, the simulation with the MYJ scheme produces better track and intensity evolution, better vortex structure, and more accurate landfall time and location. Large discrepancies（e.g.,over 10 hPa in simulated minimum sea level pressure） are found between the two simulations during the rapid intensification period. Further diagnosis indicates that stronger surface fluxes and vertical mixing in the PBL from the simulation with the MYJ scheme lead to enhanced air–sea interaction, which helps generate more realistic simulations of the rapid intensification process. Overall, the results from this study suggest that improved representation of surface fluxes and vertical mixing in the PBL is essential for accurate prediction of hurricane intensity changes.

Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, en- semble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition （also called phase transition） and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

Numerical Simulations of an Advection Fog Event over Shanghai Pudong International Airport with the WRF Model

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Forecasting （WRF） model. Using the current operational settings at the Meteorological Center of East China Air Traffic Manage- ment Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are per- formed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation （both longwave and shortwave） processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, sug- gesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi- cal processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

Evaluation of the Forecast Accuracy of Near-Surface Temperature and Wind in Northwest China Based on the WRF Model

This study investigated the performance of the mesoscale Weather Research and Forecasting(WRF) model in predicting near-surface atmospheric temperature and wind for a complex underlying surface in Northwest China in June and December 2015. The spatial distribution of the monthly average bias errors in the forecasts of 2-m temperature and 10-m wind speed is analyzed first. It is found that the forecast errors for 2-m temperature and 10-m wind speed in June are strongly correlated with the terrain distribution. However, this type of correlation is not apparent in December, perhaps due to the inaccurate specification of the surface albedo and freezing-thawing process of frozen soil in winter in Northwest China in the WRF model. In addition, the WRF model is able to reproduce the diurnal variation in 2-m temperature and 10-m wind speed, although with weakened magnitude. Elevations and land-use types have strong influences on the forecast of near-surface variables with seasonal variations. The overall results imply that accurate specification of the complex underlying surface and seasonal changes in land cover is necessary for improving near-surface forecasts over Northwest China.

Impacts of Soil Moisture on the Numerical Simulation of a Post-Landfall Storm

Surface heat and moisture fluxes are important to the evolution of a tropical storm after its landfall. Soil moisture is one of the essential components that influence surface heating and moisture fluxes. In this study, the impact of soil moisture on a pre-landfall numerical simulation of Tropical Storm Bill(2015), which had a much longer lifespan over land, is investigated by using the research version of the NCEP Hurricane Weather Research and Forecasting(HWRF) model. It is found that increased soil moisture with SLAB scheme before storm's landfall tends to produce a weaker storm after landfall and has negative impacts on storm track simulation. Further diagnoses with different land surface schemes and sensitivity experiments indicate that the increase in soil moisture inside the storm corresponds to a strengthened vertical mixing within the storm boundary layer, which is conducive to the decay of storm and has negative impacts on storm evolution. In addition, surface diabatic heating effects over the storm environment are also found to be an important positive contribution to the storm evolution over land, but their impacts are not so substantial as boundary layer vertical mixing inside the storm. The overall results highlight the importance and uncertainty of soil moisture in numerical model simulations of landfalling hurricanes and their further evolution over land.

Impacts of Land-Use Data on the Simulation of Surface Air Temperature in Northwest China

This study examines the impacts of land-use data on the simulation of surface air temperature in Northwest China by the Weather Research and Forecasting(WRF) model. International Geosphere–Biosphere Program(IGBP) landuse data with 500-m spatial resolution are generated from Moderate Resolution Imaging Spectroradiometer(MODIS)satellite products. These data are used to replace the default U.S. Geological Survey(USGS) land-use data in the WRF model. Based on the data recorded by national basic meteorological observing stations in Northwest China, results are compared and evaluated. It is found that replacing the default USGS land-use data in the WRF model with the IGBP data improves the ability of the model to simulate surface air temperature in Northwest China in July and December 2015. Errors in the simulated daytime surface air temperature are reduced, while the results vary between seasons. There is some variation in the degree and range of impacts of land-use data on surface air temperature among seasons. Using the IGBP data, the simulated daytime surface air temperature in July 2015 improves at a relatively small number of stations, but to a relatively large degree; whereas the simulation of daytime surface air temperature in December 2015 improves at almost all stations, but only to a relatively small degree(within 1°C). Mitigation of daytime surface air temperature overestimation in July 2015 is influenced mainly by the change in ground heat flux. The modification of underestimated temperature comes mainly from the improvement of simulated net radiation in December 2015.

EVALUATION OF TROPICAL CYCLONE GENESIS PRECURSORS WITH REI ATIVE OPER ATING CHARACTERISTICS(ROC)IN HIGH-RESOLUTION ENSEMBLE FORECASTS:HURRICANE ERNESTO

Identifying the environmental conditions that control tropical cyclone(TC)genesis is a challenging problem.This study examines a new method to evaluate the precursors of TC genesis using high-resolution ensemble forecasts and relative operating characteristic(ROC)diagrams.With an advanced research version of the Weather Research and Forecasting(WRF)model,high-resolution ensemble forecasts(at 5 km horizontal resolution)are conducted in various configurations using a bred vector method to form a set of 140 ensemble members for predicting Hurricane Ernesto’s genesis.Basic evaluation shows that high-resolution ensemble forecasts are able to predict well-developed TCs,whereas the NCEP Global Ensemble Forecast System(GEFS)fails to do so.This set of 140 ensemble members is employed to study the precursors of Hurricane Ernesto’s genesis by contrasting the genesis and nongenesis cases.Specifically,ROC curves,composite figures for genesis and nongenesis cases,and Kolmogorov-Smirnov tests are applied to characterize the relationship between important environmental parameters near the beginning of the simulation and genesis likelihood 15-18 h later.It is found that moist conditions at 850 hPa,vertical wind shear,the strength of the 850 hPa pre existing wave,and upper-level warming play notable roles in Ernesto’s genesis.

The Representativeness of Air Quality Monitoring Sites in the Urban Areas of a Mountainous City

Lanzhou is a typical mountainous city with severe air pollution in northwestern China. This study uses hourly observational data of air pollutants at five air quality monitoring sites in Lanzhou from July to December 2015 to discuss data quality control and the representativeness of the monitoring sites(four urban sites and one suburban site). A fuzzy matrix is applied to study primary air pollutants. The results show that of the six routinely monitored pollutants,the primary pollutant is PM_10 during the study period. Based on lag correlation analysis and one-way analysis of variance, it is concluded that there are redundant observations at the four urban sites for the timely diffusion and transport of air pollutants from the same general area. The coefficient of divergence(COD) method is then used to evaluate the spatial distribution differences, and the primary air pollutant PM_10 shows differences at each site. COD can be used as a positive indicator to describe site representativeness. To evaluate the overall air pollution in the valley, correlation analysis is performed between the PM_10 concentration retrieved from aerosol optical depth satellite data and the concentration from the four urban monitoring sites. Among these, the correlation between the workers' hospital site data and the retrieval data is the highest, passing the 90% confidence level. A new representative evaluation model for air quality monitoring sites, R_s = 0.77 COD + 0.23R_(retrieval), is established by using COD and correlation coefficients between routine observations and satellite retrieval products. From this model, it can be concluded that the biological products institute site in Lanzhou is the most representative site for the evaluation of air pollution out of the four urban air quality monitoring sites from July to December 2015.

Combining Monte Carlo and Ensemble Probabilities in Tropical Cyclone Forecasts near Landfall

The Monte Carlo probability(MCP)model,which has been used for official tropical cyclone(TC)warnings to the public by the United States’National Hurricane Center(NHC),can estimate the probability of wind speed in the vicinity of a TC during the forecast period.It has been successful in the operational environment for many years.However,due to its strong dependence on a given forecast track(e.g.,forecast from the NCEP Global Forecast System),the MCP model may generate a poor probability map for TCs near landfall.In this study,we proposed and tested a modified MCP method for TC forecasts near landfall.We first adjusted the MCP model by adding limits to the direction angle and motion distance to deal with the substantial change in TC moving direction and the low wind speeds during landfall.Then,we combined ensemble probability maps generated from ECMWF,United Kingdom Met Office(UKMO),and NCEP ensemble forecasts,obtained from The International Grand Global Ensemble(TIGGE),into the MCP model to configure a modified MCP model.Wind speed probability maps for the 0-120-h forecast from both the original and modified MCP models are compared.It is found that the modified MCP model can provide a better wind speed probability map during landfall,especially at wind speeds of 20-64 kt near TC landfall.The results from this study prove the benefits of combining the MCP model with ensemble forecasting in potential applications for improved TC forecasts.

CHAR ACTERISTICS OF TROPICAL CYCLONE GENESIS FORECASTS AND UNDERDISPERSION IN HIGH-RESOLUTION ENSEMBLE FORECASTING WITH A STOCHASTIC KINETIC ENERGY BACKSCATTER SCHEME

This study evaluates ensemble forecasts with a stochastic kinetic energy backscatter scheme(SKEBS)to predict tropical cyclone(TC)genesis and also to characterize the related ensemble underdispersion.Several sets of ensemble forecasts are generated using an advanced research version of the Weather Research and Forecasting model at 5 km horizontal resolution to predict the genesis of Hurricane Ernesto(2006)and Typhoon Nuri(2008).Ensemble forecasts with SKEBS are compared against a control ensemble forecast with the WRF model using downscaled initial conditions derived from the NCEP Global Ensemble Forecasting System.It is found that ensemble forecasts with SKEBS are able to generate probabilistic forecasts for TC genesis and also capable of indicating the forecast uncertainties.Compared with the deterministic forecast that fails to predict the genesis of Typhoon Nuri,the ensemble forecast with SKEBS is able to produce the genesis forecast.However,the underdispersion of ensemble forecasts with SKEBS is also present in all cases in terms of the simulation period and over the whole model domain,TC environment,and inner core regions,although it is reduced near the TC inner core region.In addition,the initial perturbation–based ensemble forecasts shows slightly less underdispersion compared with the SKEBS ensembles.

Effects of Updated RegCM4 Land Use Data on Near-Surface Temperature Simulation in China

Biogeophysical effects of land use and land cover （LULC） changes play a significant role in modulating climate on various spatial scales. In this study, a set of recent LULC products with a spatial resolution of 500 m was developed in China for update in RegCM4 （regional climate model version 4）. Two sets of comparative numerical experiments were conducted to study the effects of LULC changes on near-surface temperature simulation. The results show that after LULC changes, areas of crops and mixed woodlands as well as urban areas increase over entire China, accom- panied with greatly expanded mixed farming and forests/field mosaics in southern China, and reduced areas of 1） ir- rigated crops and short grasses in northern China and the Tibetan Plateau, and 2） semi-desert and desert in northwest-em China. Improvements in the LULC data clearly result in more accurate simulations of the near-surface temperat-ure. Specifically, increasing latent heat and longwave albedo due to enhanced LULC in certain areas lead to reduc-tion in land surface temperature （LST）, while changes in shortwave albedo and sensible heat also exert a great influ- ence on the LST. Overall, these parameter adjustments reduce the biases in near-surface temperature simulation.