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Based on the CMA tropical cyclone (TC) best track data as well as the reanalysis datasets from the NCEP/NCAR and NOAA, the variation characteristics of TC number from 1949 to 2013 over the western North Pacific (including the South China Sea) are examined. Notably, the time series of TC number exhibits a significant abrupt change from more to less around 1995. Comparative analysis indicates that the environmental factors necessary to TC formation also change significantly around the mid-1990s. After 1995, accompanying with anomalous warm sea surface temperature (SST) in western equatorial Pacific, a La Niña-like pattern in tropical Pacific appears obviously. However, compared with the period before 1995, the vertical upward movement decreases, vertical shear of tropospheric zonal wind increases, and sea level pressure (SLP) rises, all of which are unfavorable to TC formation and work together to make TC number reduce markedly after 1995. Furthermore, when the typical interannual more and less TCs years are selected in the two separate stages before and after 1995, the relative importance of oceanic and atmospheric environments in interannual TC generation is also investigated respectively. The results imply that the SST over the tropical Pacific exerts relatively important influence on TC formation before 1995 whereas the atmospheric circulation plays a more prominent role in the generation of TC after 1995. [ABSTRACT FROM AUTHOR]

ABSTRACT This study examines the landfalling tropical cyclones ( TCs) over China using state-of-the-art data mining methods (i.e. Finite Mixture Model ( FMM) based cluster algorithm and the Classification and Regression Tree ( CART)). Using the 1951-2012 TC best track dataset released by the Shanghai Typhoon Institute of the Chinese Meteorological Administration, the tracks of TCs landfalling over the Chinese coast were classified into three clusters through an FMM. Several climate indices were analysed using the CART algorithm for the three clusters. The prediction model built by CART for summer track frequency was based on a random sampling of the data for 46 years (about 75% of the total years) as the training set with a training accuracy of 100% (Cluster-1), 89.96% (Cluster-2) and 100% (Cluster-3). Data for the remaining 16 years (about 25%) were used for testing with a prediction accuracy of 87.5% (Cluster-1), 62.5% (Cluster-2) and 68.75% (Cluster-3). This study focuses on Cluster-1 of summer TCs landfalling over China for its high frequency, strong intensity, severe impacts and long lifespan. Furthermore, it suggests that the FMM algorithm is effective for track classification of TCs landing over China. In addition, the CART algorithm, which was used to build the prediction model of Cluster-1 for the classification of track frequency, showed high accuracy and its results can be explained and understood easily. It provides a novel framework for forecasting the frequency of TCs landfalling over China. [ABSTRACT FROM AUTHOR]

The Varsha, a spectral hydrostatic general circulation model, is run regularly at an eight-processor Flosolver machine at Gauhati University (26°10′ N, 91°45′ E), with the aims to predicting track of cyclones generated in the Bay of Bengal and forecasting precipitation occurrence and intensity over the north-eastern part (NE) of India, induced by such events. The initial conditions of the model are prepared from FNL dataset of National Centre for Environmental Prediction (NCEP), available at 1°×1° resolutions. The predicted tracks of a few cyclonic events as SIDR (Nov, 2007), Aila (May, 2009) and Laila (May, 2010) are presented along with their contribution to precipitation in the NE. Each prediction, when assessed through observations obtained from satellite-based measurements of Tropical Rainfall Measuring Mission (TRMM) and National Oceanic and Atmospheric Administration (NOAA), and also from India Meteorological Department (IMD), shows that the model-generated zonal wind is a good precursor parameter in track determination of a cyclone. The reliability of the model-projected precipitation features over the NE, contributed by such storms, is also highlighted. [ABSTRACT FROM PUBLISHER]

Polar lows are intense high-latitude mesocyclones that form during the cold season over open sea. Their relatively small-scale and short life span lead to a rather poor representation in model outputs and meteorological reanalyses. In this paper, the ability of the Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) to represent polar lows over the Norwegian and Barents Sea is assessed, and a comparison with the 40-yr ECMWF Re-Analysis (ERA-40) is provided for three cold seasons (1999-2000 until 2001-02). A better representation in ERA-Interim is found, with 13 systems captured out of the 29 observed, against 6 in the case of ERA-40. Reasons for the lack of representation are identified. Unexpectedly, the representation of different polar low sizes does not appear to be linked to the resolution. Rather, it is the representation of synoptic conditions that appears to be essential. In a second part, a downscaling is conducted using the mesoscale model Méso-NH. For each observed polar low, a pair of simulations is performed: one initialized by ERA-Interim and the other one by ERA-40. An improvement is noted with 22 polar lows represented when ERA-Interim is used. Through a model-to-satellite approach, it is shown that even if polar lows are simulated, convective processes remain insufficiently represented. Wind speeds, which were underestimated in reanalyses, are nevertheless more realistic in the Méso-NH simulations. These results are supported by a spectral analysis of reanalyses and Méso-NH fields. [ABSTRACT FROM AUTHOR]

A significant challenge for tropical cyclone ensemble data assimilation is that storm-scale observations tend to make analyses that are more asymmetric than the prior forecasts. Compromised structure and intensity, such as an increase of amplitude across the azimuthal Fourier spectrum, are a routine property of ensemble-based analyses, even with accurate position observations and frequent assimilation. Storm dynamics in subsequent forecasts evolve these states toward axisymmetry, creating difficulty in distinguishing between model-induced and actual storm asymmetries for predictability studies and forecasting. To address this issue, a novel algorithm using a storm-centered approach is proposed. The method is designed for use with existing ensemble filters with little or no modification, facilitating its adoption and maintenance. The algorithm consists of 1) an analysis of the environment using conventional coordinates, 2) a storm-centered analysis using storm-relative coordinates, and 3) a merged analysis that combines the large-scale and storm-scale fields together at an updated storm location. This algorithm is evaluated in two sets of observing system simulation experiments (OSSEs): first, no-cycling tests of the update step for idealized three-dimensional storms in radiative-convective equilibrium; second, full cycling tests of data assimilation applied to a shallow-water model for a field of interacting vortices. Results are compared against a control experiment based on a conventional ensemble Kalman filter (EnKF) scheme as well as an alternative EnKF scheme proposed by Lawson and Hansen. The storm-relative method yields vortices that are more symmetric and exhibit finer inner-core structure than either approach, with errors reduced by an order of magnitude over a control case with prior spread consistent with the National Hurricane Center (NHC)'s mean 5-yr forecast track error at 12 h. Azimuthal Fourier error spectra exhibit much-reduced noise associated with data assimilation as compared to both the control and the Lawson and Hansen approach. An assessment of free-surface height tendency of model forecasts after the merge step reveals a balanced trend between the storm-centered and conventional approaches, with storm-centered values more closely resembling the reference state. [ABSTRACT FROM AUTHOR]

To efficiently and effectively prioritize resources, adaptive observations can be targeted by using some objective criteria to estimate the potential impact an initial condition perturbation (or analysis increment) in a specific region would have on the future forecast. Several objective targeting guidance techniques have been developed, including total-energy singular vectors (TESV), adjoint-derived sensitivity steering vectors (ADSSV), and the ensemble transform Kalman filter (ETKF), all of which were tested during the 2008 The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Office of Naval Research Tropical Cyclone Structure-2008 (TCS-08) field experiments. An intercomparison between these techniques is performed in order to find underlying physical mechanisms in the respective guidance products, based on four tropical cyclone (TC) cases from the T-PARC/TCS-08 field campaigns. It is found that the TESV energy norm and the ADSSV response function are largely indirect measures of the TC track divergence that can be produced by an initial condition perturbation, explaining the strong correlation between these products. The downstream targets routinely chosen by the ETKF guidance system are often not found in the TESV and ADSSV guidance products, and it is found that downstream perturbations can affect the steering of a TC through the development of a Rossby wave in the subtropics that modulates the strength of the nearby subtropical ridge. It is hypothesized that the ubiquitousness of these downstream targets in the ETKF is largely due to the existence of large uncertainties downstream of the TC that are not taken into consideration by either the TESV or ADSSV techniques. [ABSTRACT FROM AUTHOR]

A regional hybrid variational-ensemble data assimilation system (HVEDAS), the maximum likelihood ensemble filter (MLEF), is applied to the 2011 version of the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model to evaluate the impact of direct assimilation of cloud-affected Advanced Microwave Sounding Unit-A (AMSU-A) radiances in tropical cyclone (TC) core areas. The forward components of both the gridpoint statistical interpolation (GSI) analysis system and the Community Radiative Transfer Model (CRTM) are utilized to process and simulate satellite radiances. The central strategies to allow the use of cloud-affected radiances are (i) to augment the control variables to include clouds and (ii) to add the model cloud representations in the observation forward models to simulate the microwave radiances. The cloudy AMSU-A radiance assimilation in Hurricane Danielle's (2010) core area has produced encouraging results with respect to the operational cloud-cleared radiance preprocessing procedures used in this study. Through the use of the HVEDAS, ensemble covariance statistics for a pseudo-AMSU-A observation in Danielle's core area show physically meaningful error covariances and statistical couplings with hydrometeor variables (i.e., the total-column condensate in Ferrier microphysics). The cloudy radiance assimilation in the TC core region (i.e., ASR experiment) consistently reduced the root-mean-square errors of the background departures, and also generally improved the forecasts of Danielle's intensity as well as the quantitative cloud analysis and prediction. It is also indicated that an entropy-based information content quantification process provides a useful metric for evaluating the utility of satellite observations in hybrid data assimilation. [ABSTRACT FROM AUTHOR]

The predictability of explosive cyclones over the northwestern Pacific region is investigated using an ensemble reanalysis dataset. Explosive cyclones are categorized into two types according to whether the region of the most rapid development is in the Sea of Okhotsk or Sea of Japan (OJ) or in the northwestern Pacific Ocean (PO). Cyclone-relative composite analyses are performed for analysis increments (the differences between the analysis and the 6-h forecast) and ensemble spreads (the standard deviations of ensemble members of the analysis or first guess) at the time of the maximum deepening rate. The increment composite shows that the OJ explosive cyclone center is forecast too far north compared to the analyzed center, whereas the PO explosive cyclone is forecast shallower than the analyzed center. To understand the cause of these biases, a diagnosis of the increment using the Zwack-Okossi (Z-O) development equation is conducted. The results suggest that the increment characteristics of both the OJ and PO explosive cyclones are associated with the most important cyclone development mechanisms. The OJ explosive cyclone forecast error is related to a deeper upper trough, whereas the PO explosive cyclone error is related to weaker latent heat release in the model. A diagnosis of the spread utilizing the Z-O development equation clarifies the mechanism underlying the uncertainty in the modeled sea level pressure. For OJ explosive cyclones, the spread of adiabatic warming causes substantial sea level pressure spreading southwest of the center of the cyclones. For PO explosive cyclones, the latent heat release causes substantial sea level pressure spreading around the cyclone center. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the design and performance characteristics of a new type cyclone separator. The design of this cyclone is based on the idea of improving cyclone efficiency by increasing the vortex length. This cyclone differs from a classical cyclone with the separation space. Instead of conical part, the separation space of this cyclone consists of an outer cylinder and a vortex limiter. A model of this cyclone has been manufactured and tested. Collection efficiency and pressure drop of this cyclone were measured under different operational conditions. Experimental results were compared with the conventional cyclones. The effects of the position of the vortex limiter on the cyclone performance were also investigated. [Copyright &y& Elsevier]

Skillful predictions of the seasonal tropical cyclone (TC) activity are important in mitigating the potential destruction from the TC approach/landfall in many coastal regions. In this study, a novel approach for the prediction of the seasonal TC activity over the western North Pacific is developed to provide useful probabilistic information on the seasonal characteristics of the TC tracks and vulnerable areas. The developed model, which is termed the 'track-pattern-based model,' is characterized by two features: 1) a hybrid statistical-dynamical prediction of the seasonal activity of seven track patterns obtained by fuzzy c-means clustering of historical TC tracks and 2) a technique that enables researchers to construct a forecasting map of the spatial probability of the seasonal TC track density over the entire basin. The hybrid statistical-dynamical prediction for each pattern is based on the statistical relationship between the seasonal TC frequency of the pattern and the seasonal mean key predictors dynamically forecast by the National Centers for Environmental Prediction Climate Forecast System in May. The leave-one-out cross validation shows good prediction skill, with the correlation coefficients between the hindcasts and the observations ranging from 0.71 to 0.81. Using the predicted frequency and the climatological probability for each pattern, the authors obtain the forecasting map of the seasonal TC track density by combining the TC track densities of the seven patterns. The hindcasts of the basinwide seasonal TC track density exhibit good skill in reproducing the observed pattern. The El Niño-/La Niña-related years, in particular, tend to show a better skill than the neutral years. [ABSTRACT FROM AUTHOR]

High-amplitude convectively coupled equatorial atmospheric Kelvin waves (CCKWs) are explored over the tropical Atlantic during the boreal summer (1989-2009). Focus is given to the atmospheric environmental conditions that are important for tropical cyclogenesis. CCKWs are characterized by deep westerly vertical wind shear to the east of its convectively active phase and easterly vertical wind shear to the west of it. This dynamical signature increases vertical wind shear over the western tropical Atlantic ahead of the convectively active phase, and reduces vertical wind shear after its passage. The opposite is true over the eastern tropical Atlantic where the climatological vertical wind shear is easterly. Positive total column water vapor (TCWV) anomalies progress eastward with the convectively active phase of the CCKW, whereas negative TCWV anomalies progress eastward with the convectively suppressed phase. During the passage of the convectively active phase of the CCKW, a zonally oriented strip of low-level cyclonic relative vorticity is generated over the tropical Atlantic. Two days later, this strip becomes more wavelike and moves back toward the west. This signature resembles a train of westward-moving easterly waves and suggests CCKWs may influence such events. Strong CCKWs over the tropical Atlantic tend to occur during the decay of the active convection associated with the Madden-Julian oscillation over the Pacific. This relationship could be used to provide better long-range forecasts of tropical convective patterns and Atlantic tropical cyclogenesis. [ABSTRACT FROM AUTHOR]

The article focuses on climate science and seasonal forecasting of hurricane and tropical cyclone (TC) activity. It comments on the use of statistical and dynamical general circulation models in prediction seasonal TC activity in the Atlantic and Pacific oceans. It mentions the failure of forecasts for the 2013 Atlantic hurricane season which had far fewer storms than predicted and contrasts that to the successful forecast of the active 2010 season.