Abstract

Dual-Doppler, polarimetric radar observations and precipitation efficiency (PE) calculations are used to analyze subtropical heavy rainfall events that occurred in southern Taiwan from 14 to 17 June 2008 during the Southwest Monsoon Experiment/Terrain-Influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX) field campaign. Two different periods of distinct precipitation systems with diverse kinematic and microphysical characteristics were investigated: 1) prefrontal squall line (PFSL) and 2) southwesterly monsoon mesoscale convective system (SWMCS). The PFSL was accompanied by a low-level front-to-rear inflow and pronounced vertical wind shear. In contrast, the SWMCS had a low-level southwesterly rear-to-front flow with a uniform vertical wind field. The PFSL (SWMCS) contained high (low) lightning frequency associated with strong (moderate) updrafts and intense graupel–rain/graupel–small hail mixing (more snow and less graupel water content) above the freezing level. It is postulated that the reduced vertical wind shear and enhanced accretional growth of rain by high liquid water content at low levels in the SWMCS helped produce rainfall more efficiently (53.1%). On the contrary, the deeper convection of the PFSL had lower PE (45.0%) associated with the evaporative loss of rain and the upstream transport of liquid water to form larger stratiform regions. By studying these two events, the dependence of PE on the environmental and microphysical factors of subtropical heavy precipitation systems are investigated by observational data for the first time. Overall, the PE of the convective precipitation region (47.9%) from 14 to 17 June is similar to past studies of convective precipitation in tropical regions.

Abstract

In this study, a regional rainfall event (RRE) is defined by observed rainfall at multiple, well-distributed stations in a given area. Meanwhile, a regional rainfall coefficient (RRC), which could be used to classify local rain (LR) and regional rain (RR) in the given area, is defined to quantify the spatiotemporal variation of rainfall events. As a key parameter describing the spread of rainfall, RRC, together with duration and intensity, presents an effort to explore more complete spatiotemporal organization and evolution of RREs. Preliminary analyses of RREs over the Beijing plain reveal new, interesting characteristics of rainfall. The RRC of RRE increases with longer duration and stronger intensity. Most of the RREs with maximum peak rainfall intensity below 2 mm h⁻¹ or duration shorter than 3 h have RRC less than 0.4, indicating that these events are not uniformly spread over the region. Thus, they are reasonably classified into LR. RREs with RRC above 0.5 could be classified into RR, which usually lasts longer than 4 h and has primary peak rainfall occurring from 1700 to 0600 LST. For most of the intense long-duration RR, evolutions of RRC and rainfall intensity are not consistent. The RRC reaches a maximum a few hours after the peak intensity was reached. The results of this study enrich the understanding of rainfall processes and provide new insight into understanding and quantifying the space–time characteristics of rainfall. These findings have great potential to further evaluate cloud and precipitation physics as well as their parameterizations in numerical models.

Abstract

The capability of the Canadian land surface external modeling system known as the Global Environmental Multiscale Surface (GEM-SURF) system with respect to surface wind predictions is evaluated. Based on the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme, and an exponential power law adjusted to the local stability conditions for the prediction of surface winds, the system allows decoupling of surface processes from those of the free atmosphere and enables high resolutions at the surface as dictated by the small-scale heterogeneities of the surface boundary. The simulations are driven by downscaled forecasts from the Regional Deterministic Prediction System, the 15-km Canadian regional operational modeling system. High-resolution, satellite-derived datasets of orography, vegetation, and soil cover are used to depict the surface boundary. The integration domains cover Canada’s eastern provinces at resolutions ranging from that of the driving model to resolutions similar to those of the geophysical datasets. The GEM-SURF predictions outperform those of the driving operational model. Reduction of the standard error and improvement of the model skill is seen as resolution increases, for all wind speeds. Further, the bias error is reduced in association with a rise in the corresponding value of the roughness length. For all examined resolutions GEM-SURF’s predictions are shown to be superior to those obtained through a simple statistical downscaling. In the prospect of the future development of a multicomponent system that provides wind forecasts at levels of wind energy generation, GEM-SURF’s potential for improved scores at the surface and its limited requirements in computer resources make it a suitable surface component of such a system.

Abstract

Atmospheric intraseasonal variability in the tropical Atlantic is analyzed using satellite winds, outgoing longwave radiation (OLR), and reanalysis products during 2000–08. The analyses focus on assessing the effects of dominant intraseasonal atmospheric convective processes, the Madden–Julian oscillation (MJO), and Rossby waves on surface wind and convection of the tropical Atlantic Ocean and African monsoon area. The results show that contribution from each process varies in different regions. In general, the MJO events dominate the westward-propagating Rossby waves in affecting strong convection in the African monsoon region. The Rossby waves, however, have larger contributions to convection in the western Atlantic Ocean. Both the westward- and eastward-propagating signals contribute approximately equally in the central Atlantic basin. The effects of intraseasonal signals have evident seasonality. Both convection amplitude and the number of strong convective events associated with the MJO are larger during November–April than during May–October in all regions. Convection associated with Rossby wave events is stronger during November–April for all regions, and the numbers of Rossby wave events are higher during November–April than during May–October in the African monsoon region, and are comparable for the two seasons in the western and central Atlantic basins. Of particular interest is that the MJOs originating from the Indo-Pacific Ocean can be enhanced over the tropical Atlantic Ocean while they propagate eastward, amplifying their impacts on the African monsoon. On the other hand, Rossby waves can originate either in the eastern equatorial Atlantic or West African monsoon region, and some can strengthen while they propagate westward, affecting surface winds and convection in the western Atlantic and Central American regions.

Abstract

A new statistical–dynamical downscaling procedure is developed and then applied to high-resolution (regional) time series generation and wind resource assessment. The statistical module of the new procedure uses empirical orthogonal function (EOF) analysis for the generation of large-scale atmospheric component patterns. The dominant atmospheric patterns (associated with the EOF modes explaining most of the statistical variance) are then dynamically downscaled or adjusted to high-resolution terrain and surface roughness by using the Global Environmental Multiscale–Limited Area Model (GEM-LAM). Regional time series are constructed using the model outputs. The new method is applied to the Gaspé region of Québec in Canada. The dataset used is the NCEP–NCAR reanalysis of wind, temperature, humidity, and geopotential height during the period 1958–2004. Regional time series of wind speed and temperature are constructed, and a numerical wind atlas of the Gaspé region is generated. The generated time series and the numerical wind atlas are compared with observations at different masts located in the Gaspé Peninsula and are also compared with a numerical wind atlas for the same region generated in Yu et al. The results suggest that the newly developed procedure can be useful to generate regional time series and reasonably accurate numerical wind atlases using large-scale data with much less computational effort than previous techniques.

Abstract

An incremental analysis update (IAU) scheme is successfully implemented into a WRF/WRFDA-based hourly cycling data assimilation system with the goal to reduce the imbalance introduced by the high-frequency intermittent data assimilation, especially when radar data is included. With the application of IAU, the analysis increment is smoothly introduced into the model integration over a time window centered at the analysis time. As in digital filter initialization (DFI), the IAU scheme is able to limit large shocks in the early part of a model forecast. Compared to DFI, IAU does better in hydrometeor spin-up and produces more continuous precipitation forecasts from cycle to cycle. The run with IAU is shown to improve the precipitation forecast skills (10+% for CSI scores) compared to the regular cycling forecasts without IAU. The data assimilation system with IAU is also able to accept more observations due to balanced first-guess fields. Comparable results are obtained in IAU tests when the time-varying weights are used versus constant weights. Because of its better property, the IAU with the time-varying weights is implemented in the operational system.

Abstract

This research combines an advanced multiple-Doppler radar synthesis technique with the thermodynamic retrieval method, originally proposed by Gal-Chen, and a moisture/temperature adjustment scheme, and formulates a sequential procedure. The focus is on applying this procedure to improve the model quantitative precipitation nowcasting (QPN) skill in the convective scale up to 3 hours. A series of (observing system simulation experiment) OSSE-type tests and a real case study are conducted to investigate the performance of this algorithm under different conditions.

It is shown that by using the retrieved three-dimensional wind, thermodynamic, and microphysical parameters to reinitialize a fine-resolution numerical model, its QPN skill can be significantly improved. Since the Gal-Chen method requires the horizontal average properties of the weather system at each altitude, utilization of in situ radiosonde(s) to obtain this additional information for the retrieval is tested. When sounding data are not available, it is demonstrated that using the model results to replace the role played by observing devices is also a feasible choice. The moisture field is obtained through a simple, but effective, adjusting scheme and is found to be beneficial to the rainfall forecast within the first hour after the reinitialization of the model.

Since this algorithm retrieves the unobserved state variables instantaneously from the wind measurements and directly uses them to reinitialize the model, fewer radar data and a shorter model spinup time are needed to correct the rainfall forecasts, in comparison with other data assimilation techniques such as four-dimensional variational data assimilation (4DVAR) or ensemble Kalman filter (EnKF) methods.

Abstract

To implement continuous and reliable rainfall retrieval, based on the satellite retrieval algorithm of 10-min rain rate, this study proposes an immediate tracking and continuous accumulation technique (ITCAT) of half-hour rainfall retrieval by further combining the cross-correlation method. The ITCAT includes two steps. 1) The cross-correlation method is applied to track cloud-motion currents and establish 10-min-interval image sequences. 2) A continuous retrieval of 10-min rain rates is conducted with the image sequences, and finally a total half-hour rainfall is determined by accumulations. The satellite retrieval tests on the typical precipitation processes in the summer of 2008 show that, compared with the previous direct rainfall retrieval for half-hour to one-hour, this rainfall retrieval technique significantly improves the retrieval accuracy of rainfall scope and rainfall intensity ranging from slight rain to rainstorm for both real-time monitoring or nowcasting processes. This technique is more effective than the previous algorithm, and the fundamental reason lies in its consideration of the movement of cloud clusters. On this basis, coverage duration of rainfall clouds can be reliably estimated. It is of significance to the retrieval of deep convective cloud rainfall with rapid movement speed and drastic intensity variation. This technique also provides a feasible idea for improving the accuracy of rainfall nowcasting.

Abstract

Wind retrieval algorithms are required for Doppler weather radars. In this article, a new wind retrieval algorithm of single-Doppler radar with a support vector machine (SVM) is analyzed and compared with the original algorithm with the least squares technique. Through an analysis of coefficient matrices of equations corresponding to the optimization problems for the two algorithms, the new algorithm, which contains a proper penalization parameter, is found to effectively reduce the condition numbers of the matrices and thus has the ability to acquire accurate results, and the smaller the analysis volume is, the smaller the condition number of the matrix. This characteristic makes the new algorithm suitable to retrieve mesoscale and small-scale and high-resolution wind fields. Afterward, the two algorithms are applied to retrieval experiments to implement a comparison and a discussion. The results show that the penalization parameter cannot be too small, otherwise it may cause a large condition number; it cannot be too large either, otherwise it may change the properties of equations, leading to retrieved wind direction along the radial direction. Compared with the original algorithm, the new algorithm has definite superiority with the appropriate penalization parameters for small analysis volumes. When the suggested small analysis volume dimensions and penalization parameter values are adopted, the retrieval accuracy can be improved by 10 times more than the traditional method. As a result, the new algorithm has the capability to analyze the dynamical structures of severe weather, which needs high-resolution retrieval, and the potential for quantitative applications such as the assimilation in numerical models, but the retrieval accuracy needs to be further improved in the future.

Abstract

The drop size distribution (DSD) and drop shape relation (DSR) characteristics that were observed by a ground-based 2D video disdrometer and retrieved from a C-band polarimetric radar in the typhoon systems during landfall in the western Pacific, near northern Taiwan, were analyzed. The evolution of the DSD and its relation with the vertical development of the reflectivity of two rainband cases are fully illustrated. Three different types of precipitation systems were classified—weak stratiform, stratiform, and convective—according to characteristics of the mass-weighted diameter D_m , the maximum diameter, and the vertical structure of reflectivity. Further study of the relationship between the height H of the 15-dBZ contour of the vertical reflectivity profile, surface reflectivity Z, and the mass-weighted diameter D_m showed that D_m increased with a corresponding increase in the system depth H and reflectivity Z.

An analysis of DSDs retrieved from the National Central University (NCU) C-band polarimetric radar and disdrometer in typhoon cases indicates that the DSDs from the typhoon systems on the ocean were mainly a maritime convective type. However, the DSDs collected over land tended to uniquely locate in between the continental and maritime clusters. The average mass-weighted diameter D_m was about 2 mm and the average logarithmic normalized intercept N_w was about 3.8 log₁₀ mm⁻¹ m⁻³ in typhoon cases. The unique terrain-influenced deep convective systems embedded in typhoons in northern Taiwan might be the reason for these characteristics.

The “effective DSR” of typhoon systems had an axis ratio similar to that found by E. A. Brandes et al. when the raindrops were less than 1.5 mm. Nevertheless, the axis ratio tended to be more spherical with drops greater than 1.5 mm and under higher horizontal winds (maximum wind speed less than 8 m s⁻¹). A fourth-order fitting DSR was derived for typhoon systems and the value was also very close to the estimated DSR from the polarimetric measurements in Typhoon Saomai (2006).