A diagnostic analysis of MONEX-1979 onset vortex over the Arabian Sea

Based on MONEX-,1979 data over the Arabian Sea, the paper analyses observationally the structure, development and movement of a vortex which formed during onset of the monsoon around mid-June near the coast of Kerala developed into a cyclonic storm at mid-sea and moved towards the coast of Oman to die out there Heat budget computations bring out the differential behaviour of the different quadrants of the disturbance and appear to highlight the contrasting features between the northwestern and the other quadrants in regard to vertical. distributions of diabatic heating, local temperature tendency thermal advection and adiabatic heating or cooling. The study reveals an interaction of the vortex with two eastward-propagating subtropical westerly troughs which might have contributed significantly to its explosive development (decay) through warm (cold) advection. Both barotropic and baroclinic energy conversions appear to supply energy to the storm; though there appears to be a dominance of one over the other at different stages of development and at different heights. It seems likely that condensation heating also contributed to development of the storm.

Study of the reduction of the onset temperature in a loop-tube-type thermoacoustic prime mover using Conical Phase Adjuster.- Based study on the installation position and onset temperature of Conical Phase Adjuster -

In this report, we proposed the installation of a Conical Phase Adjuster (CPA) in a thermoacoustic prime mover as a method for reducing the onset temperature and investigated the effect of the installation position of CPA on the onset temperature using stability analysis. The onset temperature of CPA also was investigated experimentally by changing the installation position of CPA. As a result, when CPA was installed at 1000 mm from the high-temperature end of the stack, the onset temperature was 195 K lower than the onset temperature without CPA, that is, the installation of CPA in a loop-tube-type thermoacoustic prime mover reduced the onset temperature by 29 %. Comparing onset temperatures of PA had installed in a system, CPA is considered to have the same effect as PA because the onset temperature tendency of CPA to reduce at the installation position agrees with that of PA.

The amplification of Madden-Julian Oscillation boosted by temperature feedback

Due to small Coriolis force in tropics, the theoretical study of Madden-Julian Oscillation (MJO) often assumes weak temperature gradient balance, which neglects the temperature feedback (manifested in temperature tendency term). In this study, the effect of the temperature feedback on the MJO is investigated by using the MJO trio-interaction model, which can capture the essential large-scale features of the MJO.The scale analysis indicates that the rotation effect is strong for the MJO scales, so that the temperature feedback is as import as the moisture feedback (manifested in moisture tendency term), the latter is often considered to be critical for MJO. The experiments with the theoretical model show that the temperature feedback has significant impact on the MJO’s maintenance. When the temperature feedback is turned off, the simulated MJO cannot be maintained over the warm pool. This is because the temperature feedback could boost the energy generation. Without temperature feedback, only the latent heat can be generated. With temperature feedback, not only the latent heat but also the enthalpy (and therefore the available potential energy) can be generated. Therefore, the total energy generation is more efficient with temperature feedback, favoring the self-maintenance of the MJO. Further investigation shows that this effect of the temperature feedback on MJO amplification can be inferred from observations.The findings here indicates that the temperature feedback could have non-negligible impacts on MJO, and have implications in the simulation of MJO.

Predictability of the Strong Ural blocking Event in January 2012 in the Subseasonal to Seasonal Models of Europe and Canada

The occurrence of a Ural blocking (UB) event is an important precursor of severe cold air outbreaks in Siberia and East Asia, and thus is significant to accurately predict UB events. Using subseasonal to seasonal (S2S) models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Environment and Climate Change Canada (ECCC), we evaluated the predictability of a persistent UB event on 18 to 26 January 2012. Results showed that the ECCC model was superior to the ECMWF model in predicting the development stage of the UB event ten days in advance, while the ECMWF model had better predictions than the ECCC model for more than ten days in advance and the decaying stage of the UB event. By comparing the dynamic and thermodynamic evolution of the UB event predicted by the two models via the geostrophic vorticity tendency equation and temperature tendency equation, we found that the ECCC model better predicted the vertical vorticity advection, ageostrophic vorticity tendency, the tilting effect, horizontal temperature advection, and adiabatic heating during the development stage, whereas the ECMWF model better predicted the three dynamic and the two thermodynamic terms during the decaying stage. In addition, during both the development and decaying stages, the two models were good (bad) at predicting the vortex stretching term (horizontal vorticity advection), with the PCC between both the predictions and the observations larger (smaller) than +0.70 (+0.10) Thus, we suggest that the prediction of the persistent UB event in the S2S model might be improved by the better prediction of the horizontal vorticity advection.

The Impact of Stochastically Perturbed Parameterizations on Tornadic Supercell Cases in East China

The impact of stochastically perturbed parameterizations on short-term tornadic supercell ensemble forecasts (EFs) was evaluated using two tornado cases that occurred in eastern China. The initial condition (IC) perturbations of EFs were generated by a three-dimensional variational data assimilation system with perturbed radar data. The parameterization perturbations of EFs were produced by a stochastic procedure that was applied to diffusion and microphysics parameterizations. This procedure perturbed tendencies from both parameterizations and intercept parameters (INTCPs) of the microphysics parameterizations. In addition to individually perturbing these quantities, a combination of perturbations of diffusion and INTCPs was also examined. A resampling method was proposed to handle perturbations that vary substantially, and a vertical localization was applied to the microphysics tendency perturbations. The results indicated that combining perturbations of diffusion and INTCPs produced the intensity and path forecasts of the low-level vortex (LLV) that better match observations for a weak tornado case; this combination also had a positive impact on the LLV intensity forecast for a much stronger tornado case. This combination outperformed the stochastic procedures that perturbed only diffusion or INTCPs, which indicated that it is better to use both error representations. The vertical localization prevented the temperature tendency perturbations of microphysics from always suppressing storms in negative perturbation (<0.0) areas. The negative INTCP and diffusion perturbations benefited the strong LLV, which is consistent with that of the idealized case. The current stochastic procedure could not address the LLV displacement error that is caused by the IC error.

The Impact of a Stochastically Perturbing Microphysics Scheme on an Idealized Supercell Storm

The concept of stochastic parameterization provides an opportunity to represent spatiotemporal errors caused by microphysics schemes that play important roles in supercell simulations. In this study, two stochastic methods, the stochastically perturbed temperature tendency from microphysics (SPTTM) method and the stochastically perturbed intercept parameters of microphysics (SPIPM) method, are implemented within the Lin scheme, which is based on the Advanced Regional Prediction System (ARPS) model, and are tested using an idealized supercell case. The SPTTM and SPIPM methods perturb the temperature tendency and the intercept parameters (IPs), respectively. Both methods use recursive filters to generate horizontally smooth perturbations and adopt the barotropic structure for the perturbation r, which is multiplied by tendencies or parameters from this parameterization. A double-moment microphysics scheme is used for the truth run. Compared to the multiparameter method, which uses randomly perturbed prescribed parameters, stochastic methods often produce larger ensemble spreads and better forecast the intensity of updraft helicity (UH). The SPTTM method better predicts the intensity by intensifying the midlevel heating with its positive perturbation r, whereas it performs worse in the presence of negative perturbation. In contrast, the SPIPM method can increase the intensity of UH by either positive or negative perturbation, which increases the likelihood for members to predict strong UH.

Residual Mean Circulation and Temperature Changes during the Evolution of Stratospheric Sudden Warming Revealed in MERRA

Residual mean circulation and temperature changes during the evolution of major stratospheric sudden warming (SSW) are investigated by composite analyses of 22 SSW events from 1979 to 2012 during the Northern Hemisphere winter (November–March) using four reanalysis data sets (MERRA, ERA-Interim, NCEP-NCAR, and JRA-55). The SSW events are classified as Type-1 or Type-2 based on the relative amplitude of planetary waves with zonal wavenumbers 1 and 2. The residual mean circulation induced by each forcing term in the Transformed Eulerian mean (TEM) momentum equation and the temperature advection associated with the circulation are calculated for both types of SSW, based on the generalized downward control principle using the MERRA data set. When ‘Lag = 0’ is defined as the day on which the wind reversal occurred at 60° N and 10 hPa, strong poleward and downward motion exists at Lag = −8 and Lag = −1 for Type-1 and at Lag = −3 for Type-2, which is induced primarily by the Eliassen–Palm flux divergence forcing (EPD). The poleward and downward motion is stronger for Type-2 than for Type-1. Gravity wave drag (GWD) produces a smaller contribution to the residual circulation than EPD. During the warming phase (at Lag = −2), strong temperature advection by the EPD induces primarily polar stratospheric warming. On the other hand, during the temperature recovery phase (at Lag = +2), anomalous negative temperature advection and diabatic cooling produce negative temperature tendency anomalies. Structures in the temperature tendency and temperature advection calculated using the MERRA data set are similar to those calculated using the ERA-Interim data set.

Assimilation of Chinese Doppler Radar and Lightning Data Using WRF-GSI: A Case Study of Mesoscale Convective System

The radar-enhanced GSI (version 3.1) system and the WRF-ARW (version 3.4.1) model were modified to assimilate radar/lightning-proxy reflectivity. First, cloud-to-ground lightning data were converted to reflectivity using a simple assumed relationship between flash density and reflectivity. Next, the reflectivity was used in the cloud analysis of GSI to adjust the cloud/hydrometeors and moisture. Additionally, the radar/lightning-proxy reflectivity was simultaneously converted to a 3D temperature tendency. Finally, the model-calculated temperature tendencies from the explicit microphysics scheme, as well as cumulus parameterization at 3D grid points at which the radar temperature tendency is available, were updated in a forward full-physics step of diabatic digital filter initialization in the WRF-ARW. The WRF-GSI system was tested using a mesoscale convective system that occurred on June 5, 2009, and by assimilating Doppler radar and lightning data, respectively. The forecasted reflectivity with assimilation corresponded more closely to the observed reflectivity than that of the parallel experiment without assimilation, particularly during the first 6 h. After assimilation, the short-range precipitation prediction improved, although the precipitation intensity was stronger than the observed one. In addition, the improvements obtained by assimilating lightning data were worse than those from assimilating radar reflectivity over the first 3 h but improved thereafter.