Unstable modes of non-axisymmetric gaseous discs

We present a perturbation theory for studying the instabilities of non-axisymmetric gaseous discs. We perturb the dynamical equations of self-gravitating fluids in the vicinity of a non-axisymmetric equilibrium, and expand the perturbed physical quantities in terms of a complete basis set and a small non-axisymmetry parameter ε. We then derive a linear eigenvalue problem in matrix form, and determine the pattern speed, growth rate and mode shapes of the first three unstable modes. In non-axisymmetric discs, the amplitude and the phase angle of travelling waves are functions of both the radius R and the azimuthal angle φ. This is due to the interaction of different wave components in the response spectrum. We demonstrate that wave interaction in unstable discs, with small initial asymmetries, can develop dense clumps during the phase of exponential growth. Local clumps, which occur on the major spiral arms, can constitute seeds of gas giant planets in accretion discs.     

Sensitivity and uncertainty analysis of mesoscale model downscaled hydro‐meteorological variables for discharge prediction

Precipitation and Reference Evapotranspiration (ETo) are the most important variables for rainfall–runoff modelling. However, it is not always possible to get access to them from ground‐based measurements, particularly in ungauged catchments. This study explores the performance of rainfall and ETo data from the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim reanalysis data for the discharge prediction. The Weather Research and Forecasting (WRF) mesoscale model coupled with the NOAH Land Surface Model is used for the retrieval of hydro‐meteorological variables by downscaling ECMWF datasets. The conceptual Probability Distribution Model (PDM) is chosen for this study for the discharge prediction. The input data and model parameter sensitivity analysis and uncertainty estimations are taken into account for the PDM calibration and prediction in the case study catchment in England following the Generalized Likelihood Uncertainty Estimation approach. The goodness of calibration and prediction uncertainty is judged on the basis of the p‐factor (observations bracketed by the prediction uncertainty) and the r‐factor (achievement of small uncertainty band). The overall analysis suggests that the uncertainty estimates using WRF downscaled ETo have slightly smaller p and r values (p= 0.65; r= 0.58) as compared to ground‐based observation datasets (p= 0.71; r= 0.65) during the validation and hence promising for discharge prediction. On the contrary, WRF precipitation has the worst performance, and further research is needed for its improvement (p= 0.04; r= 0.10). Copyright © 2013 John Wiley & Sons, Ltd.     

Error distribution modelling of satellite soil moisture measurements for hydrological applications

Satellite‐based soil moisture data accuracies are of important concerns by hydrologists because they could significantly influence hydrological modelling uncertainty. Without proper quantification of their uncertainties, it is difficult to optimize the hydrological modelling system and make robust decisions. Currently, the satellite soil moisture data uncertainty has been limited to summary statistics with the validations mainly from the in situ measurements. This study attempts to build the first error distribution model with additional higher‐order uncertainty modelling for satellite soil moisture observations. The methodology is demonstrated by a case study using the Soil Moisture and Ocean Salinity satellite soil moisture observations. The validation is based on soil moisture estimates from hydrological modelling, which is more relevant to the intended data use than the in situ measurements. Four probability distributions have been explored to find suitable error distribution curves using the statistical tests and bootstrapping resampling technique. General extreme value is identified as the most suitable one among all the curves. The error distribution model is still in its infant stage, which ignores spatial and temporal correlations, and nonstationarity. Further improvements should be carried out by the hydrological community by expanding the methodology to a wide range of satellite soil moisture data using different hydrological models. Copyright © 2016 John Wiley & Sons, Ltd.     

Probabilistic radar rainfall nowcasts using empirical and theoretical uncertainty models

Weather radar has a potential to provide accurate short‐term (0–3 h) forecasts of rainfall (i.e. radar nowcasts), which are of great importance in warnings and risk management for hydro‐meteorological events. However, radar nowcasts are affected by large uncertainties, which are not only linked to limitations in the forecast method but also because of errors in the radar rainfall measurement. The probabilistic quantitative precipitation nowcasting approach attempts to quantify these uncertainties by delivering the forecasts in a probabilistic form. This study implements two forms of probabilistic quantitative precipitation nowcasting for a hilly area in the south of Manchester, namely, the theoretically based scheme [ensemble rainfall forecasts (ERF)‐TN] and the empirically based scheme (ERF‐EM), and explores which one exhibits higher predictive skill. The ERF‐TN scheme generates ensemble forecasts of rainfall in which each ensemble member is determined by the stochastic realisation of a theoretical noise component. The so‐called ERF‐EM scheme proposed and applied for the first time in this study, aims to use an empirically based error model to measure and quantify the combined effect of all the error sources in the radar rainfall forecasts. The essence of the error model is formulated into an empirical relation between the radar rainfall forecasts and the corresponding ‘ground truth’ represented by the rainfall field from rain gauges measurements. The ensemble members generated by the two schemes have been compared with the rain gauge rainfall. The hit rate and the false alarm rate statistics have been computed and combined into relative operating characteristic curves. The comparison of the performance scores for the two schemes shows that the ERF‐EM achieves better performance than the ERF‐TN at 1‐h lead time. The predictive skills of both schemes are almost identical when the lead time increases to 2 h. In addition, the relation between uncertainty in the radar rainfall forecasts and lead time is also investigated by computing the dispersion of the generated ensemble members. Copyright © 2013 John Wiley & Sons, Ltd.     

Advanced performance in geotechnical engineering using tomography analysis

This paper presents the technique to demonstrate reliable two-dimensional (2-D) tomography of near-surface soil through multichannel analysis of surface wave (MASW) method. The MASW method is used as seismic method for determining the shear wave velocity profile of near-surface soil with better performance. Normally, this method represents one-dimensional (1-D) soil layer profile to delineate anomalous subsurface materials and detect soil characteristics in geotechnical investigations. Conventionally, the MASW method is able to represent depth corresponding shear wave velocity through 1-D representation. In this paper, this method is improved through representation of depth and distance versus shear wave velocity profile using 2-D tomography analysis in geotechnical investigations. The outcomes of the newly developed method are more reliable and informative in comparison to the outcome of the conventional MASW method. The significance of this research is incorporating advanced tomography technique with MASW method to obtain 2-D tomography of geotechnical characteristics with consistency.     

Social capital, community based management, and fishers’ livelihood in Bangladesh

This paper examines the impact of Community Based Fisheries Management (CBFM) on fishing households’ welfare in Bangladesh. It analyses how the various types of livelihood assets contribute to fishers’ household incomes. The study found that fishers in CBFM project areas have improved their access to different assets including social, human, physical, financial and natural capitals. The regression results show that social capital contributed significantly to household income, indicating that social factors play very important roles in poverty alleviation in Bangladesh. Future poverty alleviation policy options need to give priority to investments in human, physical and natural capital assets.     

Fuzzy logic based melting layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations

The advent of polarimetry makes it possible to categorize hydrometeor inferences more accurately by providing detailed information of the scattering properties. In light of this, the authors have developed a fuzzy logic based system for the recognition of melting layer in the atmosphere. The fuzzy system is based on characterizing melting layer scatterers from non-melting scatterers using five crisp inputs, namely, horizontal reflectivity (Z _H), differential reflectivity (Z _DR), co-polar correlation coefficient (ρ _HV), linear depolarization ratio (LDR) and height of radar measurements (H). For the implementation of melting layer recognition, the study employs the dual polarized signatures from the 3 GHz Chilbolton Advanced Meteorological Radar (CAMRA). Furthermore, a simple but effective averaging procedure for melting level estimation from a volume RHI scan is proposed. The proposed scheme has been evaluated with Weather Research and Forecasting (WRF) model simulated and radio soundings retrieved melting level height over a total of 84 RHI scan-based bright band cases. The results confirm that the estimated melting level heights from the proposed method are in good agreement with the WRF model and radio sounding observations. The 3 GHz radar melting level height estimates correspond with the R ² and RMSE values of 0.92 and 0.24 km, respectively, when compared to the radio soundings, and 0.93 and 0.21 km, respectively, when compared to the WRF model results. Moreover, the related R ² and RMSE values are reported as 0.93 and 0.22 km respectively between the WRF and radio soundings retrievals. This implies that the downscaled WRF modelled melting level height may also be used for operational or research needs.