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Morris L. Weisman, Christopher Davis, Wei Wang, Kevin W. Manning, and Joseph B. Klemp

Abstract

Herein, a summary of the authors’ experiences with 36-h real-time explicit (4 km) convective forecasts with the Advanced Research Weather Research and Forecasting Model (WRF-ARW) during the 2003–05 spring and summer seasons is presented. These forecasts are compared to guidance obtained from the 12-km operational Eta Model, which employed convective parameterization (e.g., Betts–Miller–Janjić). The results suggest significant value added for the high-resolution forecasts in representing the convective system mode (e.g., for squall lines, bow echoes, mesoscale convective vortices) as well as in representing the diurnal convective cycle. However, no improvement could be documented in the overall guidance as to the timing and location of significant convective outbreaks. Perhaps the most notable result is the overall strong correspondence between the Eta and WRF-ARW guidance, for both good and bad forecasts, suggesting the overriding influence of larger scales of forcing on convective development in the 24–36-h time frame. Sensitivities to PBL, land surface, microphysics, and resolution failed to account for the more significant forecast errors (e.g., completely missing or erroneous convective systems), suggesting that further research is needed to document the source of such errors at these time scales. A systematic bias is also noted with the Yonsei University (YSU) PBL scheme, emphasizing the continuing need to refine and improve physics packages for application to these forecast problems.

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Jianqiong Zhan, Wenyuan Chang, Wei Li, Yanming Wang, Liqi Chen, and Jinpei Yan

Abstract

Fujian Province in southeastern coastal China is a relatively clean region with low emissions, as its high altitude isolates it from the rest of the country. However, the region experienced haze episodes on 3–14 December 2013. The authors performed simulations using the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) to examine the impacts of meteorological conditions, aerosol radiative feedbacks (ARFs; including aerosol direct and nearly first indirect effect), and internal and external emissions reduction scenarios on particulate matter smaller than 2.5 μm (PM2.5) concentrations. To the best of the authors’ knowledge, this is the first time the WRF-Chem model has been used to study air quality in this region. The model reasonably reproduced the meteorological conditions and PM2.5 concentrations. The analysis demonstrated that the highest-PM2.5 event was associated with a cold surge that promoted the impingement of northern pollutants on the region, and PM2.5 concentrations were sensitive to the emissions from the Yangtze River delta (16.6%) and the North China Plain (12.1%). This suggests that efforts toward coastal air quality improvement require regional cooperation to reduce emissions. Noticeably, ARFs were unlikely to increase PM2.5 concentrations in the coastal region, which was in contrast to the case in northern China. ARFs induced strong clean wind anomalies in the coastal region and also lowered the inland planetary boundary layer, which enhanced the blocking of northern pollutants crossing the high terrain in the north of Fujian Province. This indicates that ARFs tend to weaken the haze intensity in the southeastern coastal region.

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George Tai-Jen Chen, Chung-Chieh Wang, and David Ta-Wei Lin

Abstract

The present study investigates the characteristics of low-level jets (LLJs) (≥12.5 m s−1) below 600 hPa over northern Taiwan in the mei-yu season and their relationship to heavy rainfall events (≥50 mm in 24 h) through the use of 12-h sounding data, weather maps at 850 and 700 hPa, and hourly rainfall data at six surface stations during the period of May–June 1985–94. All LLJs are classified based on their height, appearance (single jet or double jet), and movement (migratory and nonmigratory). The frequency, vertical structure, and spatial and temporal distribution of LLJs relative to the onset of heavy precipitation are discussed.

Results on the general characteristics of LLJs suggest that they occurred about 15% of the time in northern Taiwan, with a top speed below 40 m s−1. The level of maximum wind appeared mostly between 850 and 700 hPa, with highest frequency at 825–850 hPa. A single jet was observed more often (76%) than a double jet (24%), while in the latter case a barrier jet usually existed at 900–925 hPa as the lower branch.

Migratory and nonmigratory LLJs each constituted about half of all cases, and there existed no apparent relationship between their appearance and movement. Migratory LLJs tended to be larger in size, stronger over a thicker layer, more persistent, and were much more closely linked to heavy rainfall than nonmigratory jets. They often formed over southern China between 20° and 30°N and moved toward Taiwan presumably along with the mei-yu frontal system.

Before and near the onset of the more severe heavy rain events (≥100 mm in 24 h) in northern Taiwan, there was a 94% chance that an LLJ would be present over an adjacent region at 850 hPa, and 88% at 700 hPa, in agreement with earlier studies. Occurrence frequencies of LLJs for less severe events (50–100 mm in 24 h) were considerably lower, and the difference in accumulative rainfall amount was seemingly also affected by the morphology of the LLJs, including their strength, depth, elevation of maximum wind, persistence, proximity to northern Taiwan, source region of moisture, and their relative timing of arrival before rainfall. During the data period, about 40% of all migratory LLJs at 850 or 700 hPa passing over northern Taiwan were associated with heavy rainfall within the next 24 h. The figure, however, was much lower compared to earlier studies, and some possible reasons are offered to account for this deficit.

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Chunpeng Wang, Zhengzhao Johnny Luo, Xiuhong Chen, Xiping Zeng, Wei-Kuo Tao, and Xianglei Huang

Abstract

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

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Tae-Kwon Wee, Ying-Hwa Kuo, Dong-Kyou Lee, Zhiquan Liu, Wei Wang, and Shu-Ya Chen

Abstract

The authors have discovered two sizeable biases in the Weather Research and Forecasting (WRF) model: a negative bias in geopotential and a warm bias in temperature, appearing both in the initial condition and the forecast. The biases increase with height and thus manifest themselves at the upper part of the model domain. Both biases stem from a common root, which is that vertical structures of specific volume and potential temperature are convex functions. The geopotential bias is caused by the particular discrete hydrostatic equation used in WRF and is proportional to the square of the thickness of model layers. For the vertical levels used in this study, the bias far exceeds the gross 1-day forecast bias combining all other sources. The bias is fixed by revising the discrete hydrostatic equation. WRF interpolates potential temperature from the grids of an external dataset to the WRF grids in generating the initial condition. Associated with the Exner function, this leads to the marked bias in temperature. By interpolating temperature to the WRF grids and then computing potential temperature, the bias is removed. The bias corrections developed in this study are expected to reduce the disparity between the forecast and observations, and eventually to improve the quality of analysis and forecast in the subsequent data assimilation. The bias corrections might be especially beneficial to assimilating height-based observations (e.g., radio occultation data).

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Chun-Chieh Wu, Tzu-Hsiung Yen, Ying-Hwa Kuo, and Wei Wang

Abstract

In this study, a series of numerical experiments are performed to examine the ability of a high-resolution mesoscale model to predict the track, intensity change, and detailed mesoscale precipitation distributions associated with Typhoon Herb (1996), which made landfall over Taiwan. The fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), with a 2.2-km horizontal grid spacing, successfully simulates the mesoscale rainfall distribution associated with Herb, and the predicted maximum 24-h rainfall of 1199 mm accounts for about 70% of the observed amount of 1736 mm at Mount A-Li. It is shown that, with an accurate track simulation, the ability of the model to simulate successfully the observed rainfall is dependent on two factors: the model's horizontal grid spacing and its ability to describe the Taiwan terrain. The existence of the Central Mountain Range has only a minor impact on the storm track, but it plays a key role in substantially increasing the total rainfall amounts over Taiwan. The analysis presented here shows that the model and terrain resolutions play a nearly equivalent role in the heavy precipitation over Mount A-Li. The presence of maximum vertical motion and heating rate in the lower troposphere, above the upslope mountainous region, is a significant feature of forced lifting associated with the interaction of the typhoon's circulation and Taiwan's mountainous terrain. Overall, Typhoon Herb is a case in point to indicate the intimate relation between Taiwan's topography and the rainfall distribution associated with a typhoon at landfall.

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Ji-Qin Zhong, Bing Lu, Wei Wang, Cheng-Cheng Huang, and Yang Yang

Abstract

In this study, the causes of the underestimated diurnal 2-m temperature range and the overestimated 2-m specific humidity in the winter of northern China in the Rapid-Refresh Multiscale Analysis and Prediction System–Short Term (RMAPS-ST) are investigated. Three simulations based on RMAPS-ST are conducted from 1 November 2016 to 28 February 2017. Further analyses show that the partitioning of surface upward sensible heat fluxes and downward ground heat fluxes might be the main contributing factor to the 2-m temperature forecast bias. In this study, two simulations are conducted to examine the effect of soil moisture initialization and soil hydraulic property on the 2-m temperature and 2-m specific humidity forecasts. First, the High-Resolution Land Data Assimilation System (HRLDAS) is used to provide an alternative soil moisture initialization. The results show that the drier soil moisture could lead to noticeable change in energy partitioning at the land surface, which in turn results in improved prediction of the diurnal 2-m temperature range, although it also enlarges the 2-m specific humidity bias in some parts of the domain. Second, a soil texture dataset developed by Beijing Normal University and the revised hydraulic parameters are applied to provide a more detailed description of soil properties, which could further improve the 2-m specific humidity bias. In summary, the combination of using optimized soil moisture initialization, an updated soil map, and revised soil hydraulic parameters can help improve the 2-m temperature and 2-m specific humidity prediction in RMAPS-ST.

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BINGTIAN LI, ZEXUN WEI, YONGGANG WANG, XINYU GUO, TENGFEI XU, and XIANQING LV

Abstract

An enhanced harmonic analysis (S_TIDE) approach is adopted to examine the seasonal variations of internal tidal amplitudes in the northern South China Sea (SCS). Results of idealized experiments reveal that the seasonality can be captured by S_TIDE. By applying S_TIDE to mooring data, observed seasonality of internal tidal amplitudes in the northern SCS are explored. Not diurnal and semidiurnal internal tides (ITs), but overtides and long-period constituents of ITs exhibit clear seasonal cycles. However, differences between amplitudes of the eastward velocity and the northward counterpart are evident for K1, M2 and MK3, which may be caused by the intensification of background currents. Amplitudes of those ITs are stronger at intersection time between spring and summer in the eastward direction, but weaker in the northward direction. EOF analysis reveals that modes of diurnal ITs are higher than those of seimidiurnal ITs, which induces relatively more complicated seasonal variations. In addition to intensification of background currents, influences of surface tides and stratification will also induce variations of internal tidal amplitudes, introducing tremendous difficulty in predicting variation trends of internal tidal amplitudes, which greatly reduces predictability of ITs.

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Steven M. Cavallo, Ryan D. Torn, Chris Snyder, Christopher Davis, Wei Wang, and James Done

Abstract

Real-time analyses and forecasts using an ensemble Kalman filter (EnKF) and the Advanced Hurricane Weather Research and Forecasting Model (AHW) are evaluated from the 2009 North Atlantic hurricane season. This data assimilation system involved cycling observations that included conventional in situ data, tropical cyclone (TC) position, and minimum SLP and synoptic dropsondes each 6 h using a 96-member ensemble on a 36-km domain for three months. Similar to past studies, observation assimilation systematically reduces the TC position and minimum SLP errors, except for strong TCs, which are characterized by large biases due to grid resolution. At 48 different initialization times, an AHW forecast on 12-, 4-, and 1.33-km grids is produced with initial conditions drawn from a single analysis member. Whereas TC track analyses and forecasts exhibit a pronounced northward bias, intensity forecast errors are similar to (lower than) the NWS Hurricane Weather Research Model (HWRF) and GFDL forecasts for forecast lead times ≤60 h (>60 h), with the largest track errors associated with the weakest systems, such as Tropical Storm (TS) Erika. Several shortcomings of the data assimilation system are addressed through postseason sensitivity tests, including using the maximum 800-hPa circulation to identify the TC position during assimilation and turning off the quality control for the TC minimum SLP observation when the initial intensity is far too weak. In addition, the improved forecast of TS Erika relative to HWRF is shown to be related to having initial conditions that are more representative of a sheared TC and not using a cumulus parameterization.

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Chao Wang, Liguang Wu, Jun Lu, Qingyuan Liu, Haikun Zhao, Wei Tian, and Jian Cao

Abstract

Understanding variations in tropical cyclone (TC) translation speed (TCS) is of great importance for islands and coastal regions since it is an important factor in determining TC-induced local damages. Investigating the long-term change in TCS was usually subject to substantial limitations in the quality of historical TC records, but here we investigated the interannual variability in TCS over the western North Pacific (WNP) Ocean by using reliable satellite TC records. It was found that both temporal changes in large-scale steering flow and TC track greatly contributed to interannual variability in the WNP TCS. In the peak season (July–September), TCS changes were closely related to temporal variations in large-scale steering flow, which was linked to the intensity of the western North Pacific subtropical high. However, for the late season (October–December), changes in TC track played a vital role in interannual variability in TCS while the impacts of temporal variations in large-scale steering were weak. The changes in TC track were mainly contributed by the El Niño–Southern Oscillation (ENSO)-induced zonal migrations in TC genesis locations, which make more or fewer TCs move to the subtropical WNP, thus leading to notable changes in the basinwide TCS because of the much greater large-scale steering in the subtropical WNP. The increased influence of TC track change on TCS in the late season was linked to the greater contrast between the subtropical and the tropical large-scale steering in the late season. These results have important implications for understanding current and future variations in TCS.

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