Search

The authors analyze the mesoscale structure accompanying two multiday periods of heavy rainfall during the Southwest Monsoon Experiment and the Terrain-Induced Mesoscale Rainfall Experiment conducted over and near Taiwan during May and June 2008. Each period is about 5-6 days long with episodic heavy rainfall events within. These events are shown to correspond primarily to periods when well-defined frontal boundaries are established near the coast. The boundaries are typically 1 km deep or less and feature contrasts of virtual temperature of only 2°-3°C. Yet, owing to the extremely moist condition of the upstream conditionally unstable air, these boundaries appear to exert a profound influence on convection initiation or intensification near the coast. Furthermore, the boundaries, once established, are long lived, possibly reinforced through cool downdrafts and prolonged by the absence of diurnal heating over land in generally cloudy conditions. These boundaries are linked phenomenologically with coastal fronts that occur at higher latitudes. [ABSTRACT FROM AUTHOR]

Tropical cyclones form over the seas: a typical data‐sparse region for conventional observations. Therefore, satellites, especially with microwave sensors, are ideal for cyclone studies. The advanced microwave sounding unit (AMSU) , in addition to providing very valuable data over non‐precipitating cloudy regions, can provide very high horizontal resolution of the temperature and humidity soundings. Such high‐resolution microwave data can improve the poorly analysed cyclone. The objective of this study is to investigate the impact of ingesting and assimilating the AMSU data together with conventional upper air and surface meteorological observations over India on the prediction of a tropical cyclone which formed over the Arabian Sea during November 2003 using analysis nudging. The impact of assimilating the AMSU‐derived temperature and humidity vertical profiles in a mesoscale model has not been tested yet over the Indian region. Such studies are important as most weather systems over India form over the seas. The present study is unique in the sense that it addresses the impact of ingesting and assimilating microwave sounding data (together with conventional India Meteorological Department data) on the prediction of a tropical cyclone, which formed over the Arabian Sea during November 2003 using analysis nudging. Two sets of numerical experiments are designed in this study. While the first set utilizes the National Center for Environmental Prediction (NCEP) reanalysis (for the initial and lateral boundary conditions) only in the fifth‐generation mesoscale model simulation, the second set utilized the AMSU satellite and conventional meteorological upper air and surface data to provide an improved analysis through analysis nudging. The results of the two sets of model simulations are compared with one another as well as with the NCEP reanalysis and the observations.The results of the study indicated that the impact of ingesting and assimilating microwave sounding data and the conventional meteorological data through nudging resulted in an improvement in the simulation of wind asymmetries and the warm temperature anomalies. The with‐assimilation run simulated stronger wind speeds and stronger vertical velocity motion as compared with the without‐assimilation run. The time series of the minimum sea level pressure (SLP) and maximum wind speed for the simulations with the microwave sounding data and conventional meteorological data show better agreement with the observations than the simulations without the assimilation. The central minimum pressure of the simulations with the modified analysis are lower by 7 hPa as compared with the simulations without the assimilations. Even though there is not much of a difference in the maximum wind speed between the two simulations at the initial forecast time, the results indicate that the simulations with microwave sounding data and conventional meteorological data reveal a marked (9 m/s) increase in the maximum wind speed over the simulations without the assimilation. While the lowest central pressure estimated from the satellite image is 988 hPa, the simulations with microwave sounding data and conventional meteorological data show a value of 999.5 hPa for the lowest central minimum pressure. One reason for the inability of the simulation with improved analysis to achieve the observed lowest SLP is that the NCEP reanalysis had manifested an extremely weak system in the first place and, despite assimilation with microwave sounding data and conventional meteorological data, only a moderate improvement in the lowest SLP could be achieved. A proper appreciation of the impact of the microwave sounding data can be obtained by comparing with the lowest SLP obtained from the simulation without assimilation which showed a value of 1007 hPa. The initial mis‐representation in the location of the centre of the cyclone in the NCEP reanalysis with respect to the observed location has led to marked errors in the track prediction of both the model simulations. The assimilation of microwave satellite data is yet to be implemented in the current operational regional model over India and hence the results of this study may be relevant to the operational tropical cyclone forecasting community. [ABSTRACT FROM AUTHOR]

A composite mesoscale precipitation event and a convectively coupled Kelvin wave produced by a diabatically accelerated cloud resolving model are compared. Special emphasis is placed on the vertical structure of density and moisture perturbations and the interaction of these perturbations with the composited dynamical fields. Both composites share the same general features, a gradual deepening and strengthening of convection followed by deep convection and a stratiform region, quite similar in character to observations and some recent idealized models. Composited frozen moist static energy (FMSE) perturbations are several times larger than virtual temperature perturbations, suggesting moisture is a dominant regulator of convection. An empirically derived two vertical mode decomposition of the dynamical and moisture fields is found to reproduce both composites quite well. The leading vertical modes of FMSE and virtual temperature variability are strongly correlated with the modes of vertical velocity variability; these correlations are strongest at near-zero time lags. Deep convection is associated with moistening in the lower and middle troposphere, while shallow convection is associated with a moist lower troposphere and dry middle and upper troposphere. To the extent that our numerical model is realistic, the empirical modal decomposition provides support for the use of two-mode idealized models for convective interaction with large-scale circulations and guidance for formulating feedbacks between convection and the thermodynamic profile in such models. The FMSE budget leads to an interpretation of the convective life-cycle as a recharge–discharge mechanism in column-integrated FMSE. The budget analysis places diabatic forcing, surface and radiative fluxes into the moist energetic framework. In particular, these fluxes are seen to prolong active convection, but play a passive role in its initiation. The modally decomposed FMSE budget highlights the dynamical importance of the second baroclinic mode in moistening the lower and middle troposphere before convective onset (recharging), and then discharging stored FMSE in the stratiform region. [ABSTRACT FROM AUTHOR]

A methodology and algorithms of spatial extrapolation of mesometeorological fields to a territory uncovered with observations are suggested. The atmospheric state and parameters are estimated using an extended Kalman filter for a simplified model of the space-time behavior of atmospheric parameters. The model is described by first-order stochastic differential equations. The results of statistical estimation of the quality of the algorithms used for spatial extrapolation of the mesoscale temperature and wind velocity fields are discussed. [ABSTRACT FROM AUTHOR]