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Chengcheng Xu, Chen Wang, and Pan Liu

Abstract

The study presented in this paper investigated the combined effects of environmental factors and real-time traffic conditions on freeway crash risks. Traffic and weather data were collected from a 35-km freeway segment in the state of California, United States. The weather conditions were classified into five categories: clear, light rain, moderate/heavy rain, haze, and mist/fog. Logistic regression models using unmatched case-control data were developed to link the likelihood of crash occurrences to various traffic and environmental variables. The sample size requirements for case-control studies and the interaction between traffic and environmental variables were considered. The model estimation results showed that the light rain, moderate/heavy rain, and mist/fog significantly increase freeway crash risks. The interaction between light rain and upstream occupancy was also found to be statistically significant. Bootstrap analyses were conducted to quantify the interaction effect between these two variables. The crash risk model was compared to a reduced model in which environmental information was not included. It was found that the inclusion of environmental information improved both goodness of fit and prediction performance of the crash risk prediction model. The inclusion of environmental information in crash risk models improved the prediction accuracy of crash occurrences by 6.8% and reduced the false alarm rate by 1.3%. It was also found that the inclusion of environmental information had minor impacts on the prediction performance of the crash risk model in clear weather conditions.

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Shida Gao, Pan Liu, and Upmanu Lall

Abstract

Integrated atmospheric water vapor transport (IVT) is a determinant of global precipitation. In this paper, using the CERA-20C climate reanalysis dataset, we explore three questions in Northern Hemisphere precipitation for four seasons: 1) What is the covariability between the leading spatiotemporal modes of seasonal sea surface temperature (SST), the seasonal IVT, and the seasonal precipitation for the Northern Hemisphere? 2) How well can the leading spatial modes of seasonal precipitation be reconstructed from the leading modes of IVT and SST for the same season? 3) How well can the leading modes of precipitation for the next season be predicted from the leading modes of the current season’s SST and IVT? Wavelet analyses identify covariation in the leading modes of seasonal precipitation and those of IVT and SST in the 2–8-yr band, with the highest amplitude in the March–May (MAM) season, and provide a firm physical explanation for the potential predictability. We find that a subset of the 10 leading principal components of the seasonal IVT and SST fields has significant trends in connections with seasonal precipitation modes, and provides an accurate statistical concurrent reconstruction and one-season-ahead forecast of the leading seasonal precipitation modes, thus providing a pathway to improving the understanding and prediction of precipitation extremes in the context of climate change attribution, seasonal and longer prediction, and climate change scenarios. The same-season reconstruction model can explain 76% of the variance, and the next-season forecast model can explain 58% variance of hemispheric precipitation on average.

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Xiaolong Zong, Haidong Pan, Yongzhi Liu, and Xianqing Lv

Abstract

The spline interpolation method is applied to the inversion of the time-varying pollutant emission rate based on an ocean pollutant diffusion model with the adjoint method. A series of numerical experiments are performed to compare the spline interpolation with the Cressman interpolation. Experimental results show that the spline interpolation improves the inversion results in terms of the smoothness and accuracy. Furthermore, it is the advantages of spline interpolation—better resistance to the impact of errors and demand for fewer observations—that give rise to a better performance in practice.

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Zaitao Pan, Xiaodong Liu, Sanjiv Kumar, Zhiqiu Gao, and James Kinter

Abstract

Some parts of the United States, especially the southeastern and central portion, cooled by up to 2°C during the twentieth century, while the global mean temperature rose by 0.6°C (0.76°C from 1901 to 2006). Studies have suggested that the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO) may be responsible for this cooling, termed the “warming hole” (WH), while other works reported that regional-scale processes such as the low-level jet and evapotranspiration contribute to the abnormity. In phase 3 of the Coupled Model Intercomparison Project (CMIP3), only a few of the 53 simulations could reproduce the cooling. This study analyzes newly available simulations in experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 28 models, totaling 175 ensemble members. It was found that 1) only 19 out of 100 all-forcing historical ensemble members simulated negative temperature trend (cooling) over the southeast United States, with 99 members underpredicting the cooling rate in the region; 2) the missing of cooling in the models is likely due to the poor performance in simulating the spatial pattern of the cooling rather than the temporal variation, as indicated by a larger temporal correlation coefficient than spatial one between the observation and simulations; 3) the simulations with greenhouse gas (GHG) forcing only produced strong warming in the central United States that may have compensated the cooling; and 4) the all-forcing historical experiment compared with the natural-forcing-only experiment showed a well-defined WH in the central United States, suggesting that land surface processes, among others, could have contributed to the cooling in the twentieth century.

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Chen Pan, Bin Zhu, Chenwei Fang, Hanqing Kang, Zhiming Kang, Hao Chen, Duanyang Liu, and Xuewei Hou

Abstract

The studies of the climate effects of black carbon (BC) in East Asia are not abundant and remain uncertain. Using the Community Earth System Model version 1 (CESM1) with the Peking University’s emissions, the fast response of the atmospheric water cycle to anthropogenic BC during summer in East Asia is investigated in this study. Results show that the CESM1-simulated BC concentration and its direct effective radiative forcing are comparable to observations. With the combination of aerosol-radiation interaction (ARI) and non-aerosol-radiation interaction (including aerosol-cloud interaction and surface albedo effect), anthropogenic BC induces a “wetter south and drier north” pattern over East Asia during summer. Also, anthropogenic BC affects the summer precipitation primarily through changing moisture transport rather than altering local evaporation over East Asia. Using the self developed atmospheric water tracer method, the responses of dominant moisture sources (tropic Indian Ocean (TIO) and Northwest Pacific) to anthropogenic BC are investigated. Results show that the moisture originating from southwest monsoon-related sources (especially TIO) is more responsive to anthropogenic BC effects over East Asia. In particular, differing from total precipitation, TIO-supplied precipitation shows a significant response to the ARI of anthropogenic BC over East Asia. Process analyses show that anthropogenic BC affects the southwest monsoon-related moisture supplies primarily via advection, deep convection, and cloud-macrophysics. Interestingly, the anthropogenic BC-induced changes of TIO-supplied water vapour in these three processes are all dominated by the ARI over East Asia.

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C. H. Liu, G. Dester, S. J. Franke, J. Röttger, and C-J. Pan

Abstract

A novel extension of the spaced antenna method for VHF/UHF radar and wind profiler applications is introduced in this paper. It is proposed that instead of pointing the spaced antenna beams vertically, off-vertical oblique configuration should be used. It will be, shown that this technique can be used to obtain horizontal wind at independent “points” in the atmosphere without making assumptions about homogeneity or variation of the wind field between these points. Good experimental confirmations are achieved by comparing the results with those derived from the conventional spaced antenna method and the Doppler method. Applications of the proposed technique in measuring kinematic properties of the wind field such as divergence, vorticity, etc., in the atmosphere and the accuracy of these measurements are discussed.

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Yun Lin, Yuan Wang, Bowen Pan, Jiaxi Hu, Yangang Liu, and Renyi Zhang

Abstract

A continental cloud complex, consisting of shallow cumuli, a deep convective cloud (DCC), and stratus, is simulated by a cloud-resolving Weather Research and Forecasting Model to investigate the aerosol microphysical effect (AME) and aerosol radiative effect (ARE) on the various cloud regimes and their transitions during the Department of Energy Routine Atmospheric Radiation Measurement Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) campaign. Under an elevated aerosol loading with AME only, a reduced cloudiness for the shallow cumuli and stratus resulted from more droplet evaporation competing with suppressed precipitation, but an enhanced cloudiness for the DCC is attributed to more condensation. With the inclusion of ARE, the shallow cumuli are suppressed owing to the thermodynamic effects of light-absorbing aerosols. The responses of DCC and stratus to aerosols are monotonic with AME only but nonmonotonic with both AME and ARE. The DCC is invigorated because of favorable convection and moisture conditions at night induced by daytime ARE, via the so-called aerosol-enhanced conditional instability mechanism. The results reveal that the overall aerosol effects on the cloud complex are distinct from the individual cloud types, highlighting that the aerosol–cloud interactions for diverse cloud regimes and their transitions need to be evaluated to assess the regional and global climatic impacts.

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Jiayi Pan, Xiao-Hai Yan, Young-Heon Jo, Quanan Zheng, and W. Timothy Liu

Abstract

It has been difficult to estimate the sensible heat flux at the air–sea interface using satellite data because of the difficulty in remotely observing the sea level air temperature. In this study, a new method is developed for estimating the sensible heat flux using satellite observations under unstable conditions. The basic idea of the method is that the air–sea temperature difference is related to the atmospheric convergence. Employed data include the wind convergence, sea level humidity, and sea surface temperature. These parameters can be derived from the satellite wind vectors, Special Sensor Microwave Imager (SSM/I) precipitable water, and Advanced Very High Resolution Radiometer (AVHRR) observations, respectively. The authors selected a region east of Japan as the test area where the atmospheric convergence appears all year. Comparison between the heat fluxes derived from the satellite data and from the National Centers for Environmental Prediction (NCEP) data suggests that the rms difference between the two kinds of sensible heat fluxes has low values in the sea area east of Japan with a minimum of 10.0 W m−2. The time series of the two kinds of sensible heat fluxes at 10 locations in the area are in agreement, with rms difference ranging between 10.0 and 14.1 W m−2 and correlation coefficient being higher than 0.7. In addition, the National Aeronautics and Space Administration (NASA) Goddard Satellite- Based Surface Turbulent Flux (GSSTF) was used for a further comparison. The low-rms region with high correlation coefficient (>0.7) was also found in the region east of Japan with a minimum of 12.2 W m−2. Considering the nonlinearity in calculation of the sensible monthly means, the authors believe that the comparison with GSSTF is consistent with that with NCEP data.

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Lulin Xue, Amit Teller, Roy Rasmussen, Istvan Geresdi, Zaitao Pan, and Xiaodong Liu

Abstract

A detailed bin aerosol-microphysics scheme has been implemented into the Weather Research and Forecast Model to investigate the effects of aerosol solubility and regeneration on mixed-phase orographic clouds and precipitation. Two-dimensional simulations of idealized moist flow over two identical bell-shaped mountains were carried out using different combinations of aerosol regeneration, solubility, loading, ice nucleation parameterizations, and humidity. The results showed the following. 1) Pollution and regenerated aerosols suppress the riming process in mixed-phase clouds by narrowing the drop spectrum. In general, the lower the aerosol solubility, the broader the drop spectrum and thus the higher the riming rate. When the solubility of initial aerosol increases with an increasing size of aerosol particles, the modified solubility of regenerated aerosols reduces precipitation. 2) The qualitative effects of aerosol solubility and regeneration on mixed-phase orographic clouds and precipitation are not affected by different ice nucleation parameterizations. 3) The impacts of aerosol properties on rain are similar in both warm- and mixed-phase clouds. Aerosols exert weaker impact on snow and stronger impact on graupel compared to rain as graupel production is strongly affected by riming. 4) Precipitation of both warm- and mixed-phase clouds is most sensitive to aerosol regeneration, then to aerosol solubility, and last to modified solubility of regenerated aerosol; however, the precipitation amount is mainly controlled by humidity and aerosol loading.

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Fang Pan, Seiji Kato, Fred G. Rose, Alexander Radkevich, Xu Liu, and Xianglei Huang

Abstract

A linear inversion algorithm to derive changes of surface skin temperature and atmospheric temperature and specific humidity vertical profiles using spatially and temporally averaged spectral radiance differences is developed. The algorithm uses spectral radiative kernels, which is the top-of-atmosphere spectral radiance change caused by perturbations of skin temperature and air temperature and specific humidity in the atmosphere, and is an improved version of the algorithm used in earlier studies. Two improvements are the inclusion of the residual and cloud spectral kernels in the form of eigenvectors of principal components. Three and six eigenvectors are used for, respectively, the residual and cloud spectral kernels. An underlying assumption is that the spectral shape of the principal components is constant and their magnitude varies temporally and spatially. The algorithm is tested using synthetic spectral radiances with the spectral range of the Atmospheric Infrared Sounder averaged over 16 days and over a 10° × 10° grid box. Changes of skin temperature, air temperature, and specific humidity vertical profiles are derived from the difference of nadir-view all-sky spectral radiances. The root-mean-square difference of retrieved and true skin temperature differences is 0.59 K. The median of absolute errors in the air temperature change is less than 0.5 K above 925 hPa. The median of absolute errors in the relative specific humidity changes is less than 10% above 825 hPa.

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