Seasonal climate prediction for South America with FSU Multi-model Synthetic Superensemble algorithm

Summary Objective combination schemes of predictions from different models have been applied to seasonal climate forecasts. These schemes are successful in producing a deterministic forecast superior to individual member models and better than the multi-model ensemble mean forecast. Recently, a variant of the conventional superensemble formulation was created to improve skills for seasonal climate forecasts, the Florida State University (FSU) Synthetic Superensemble. The idea of the synthetic algorithm is to generate a new data set from the predicted multimodel datasets for multiple linear regression. The synthetic data is created from the original dataset by finding a consistent spatial pattern between the observed analysis and the forecast data set. This procedure is a multiple linear regression problem in EOF space. The main contribution this paper is to discuss the feasibility of seasonal prediction based on the synthetic superensemble approach and to demonstrate that the use of this method in coupled models dataset can reduce the errors of seasonal climate forecasts over South America. In this study, a suite of FSU coupled atmospheric oceanic models was used. In evaluation the results from the FSU synthetic superensemble demonstrate greater skill for most of the variables tested here. The forecast produced by the proposed method out performs other conventional forecasts. These results suggest that the methodology and database employed are able to improve seasonal climate prediction over South America when compared to the use of single climate models or from the conventional ensemble averaging. The results show that anomalous conditions simulated over South America are reasonably realistic. The negative (positive) precipitation anomalies for the summer monsoon season of 1997/98 (2001/02) were predicted by Synthetic Superensemble formulation quite well. In summary, the forecast produced by the Synthetic Superensemble approach outperforms the other conventional forecasts.     

Motion of Venusian clouds by the deposition of meteoroids

The theory of superrotation of the Earth's atmosphere by global deposition of meteoroids recently developed by the author (Mitra, 1974) is extended after a slight refinement to explain the rotation period of Venusian clouds. A satisfactory agreement with observations is obtained.     

Mass distribution in the solar system

The present-day observed mass distribution in the solar system including the Sun is shown to be compatible with the idea of the splitting of a number of ring-shaped rotating clouds of particles in the equatorial plane of a single contracting nebula. The formation of such a nebula is discussed and it is inferred that during the course of contraction this nebula has remained a sphere of uniform density spinning with the Keplerian velocity of its surface layer. The mass of a planet is taken as the portion of this spherical solar nebula gained at the time of splitting by its gaseous ring of dimensions satisfying Roche and accretional limits.     

Convective dynamos in spherical wedge geometry

Self‐consistent convective dynamo simulations in wedge‐shaped spherical shells are presented. Differential rotation is generated by the interaction of convection with rotation. Equatorward acceleration and dynamo action are obtained only for sufficiently rapid rotation. The angular velocity tends to be constant along cylinders. Oscillatory large‐scale fields are found to migrate in the poleward direction. Comparison with earlier simulations in full spherical shells and Cartesian domains is made (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The fallacy of Oppenheimer Snyder collapse: no general relativistic collapse at all,no black hole,no physical singularity

By applying Birkhoff’s theorem to the problem of the general relativistic collapse of a uniform density dust, we directly show that the density of the dust ρ=0 even when its proper number density n would be assumed to be finite! The physical reason behind this exact result can be traced back to the observation of Arnowitt et al. (Phys. Rev. Lett. 4: 375, 1960) that the gravitational mass of a neutral point particle is zero: m=0. And since, a dust is a mere collection of neutral point particles, unlike a continuous hydrodynamic fluid, its density ρ=mn=0. It is nonetheless found that for k=?1, a homogeneous dust can collapse and expand special relativistically in the fashion of a Milne universe. Thus, in reality, general relativistic homogeneous dust collapse does not lead to the formation of any black hole in conformity of many previous studies (Logunov et al., Phys. Part. Nucl. 37: 317, 2006; Kiselev et al., Theor. Math. Phys. 164: 972, 2010; Mitra, J. Math. Phys. 50: 042502, 2009a; Suggett, J. Phys. A 12: 375 1979b). Interestingly, this result is in agreement with the intuition of Oppenheimer and Snyder (Phys. Rev. 56: 456, 1939) too:“Physically such a singularity would mean that the expressions used for the energy-momentum tensor does not take into account some essential physical fact which would really smooth the singularity out. Further, a star in its early stages of development would not possess a singular density or pressure, it is impossible for a singularity to develop in a finite time.”     

An atmospheric instability derived with MODIS profile using real-time direct broadcast data over the Indian region

In this study, assessing the atmospheric instability, a new index, named here as MODIS (Moderate Resolution Imaging Spectroradiometer) profile index (MPI), has been statistically computed using temperature and moisture profile data from the real-time direct broadcast receiving systems installed at three places of India Meteorological Department. The training dataset has been prepared using MODIS temperature and moisture profile from the Aqua and Terra satellites over the Indian region for clear and convective weather conditions during the period of March to June 2011. The MPI values are produced at 5?×?5?km pixel resolution when at least 6 out of 9 FOVs from MODIS granules are found cloud free. If more than 3 FOVs are cloudy, the MPI has not been computed. The formulation of MPI and its comparison have been examined with well-established traditionally used K index, Lifted Index and total totals index derived from radiosonde profiles of temperature, pressure and humidity. It has been observed that in most of the cases, MPI has well correlated with those derived from ground truth observations. Therefore, spatially interpolated MPI can be utilized as an indicator for regional and location-specific forecast over the areas where radiosonde data are not available. The results also indicated that MPI can be used as a sensitive measure in very early stages of instability developments such as thunderstorm and rainfall because no other single stability index can provide a distinct threshold value for these events. Therefore, a single MPI value at a certain threshold can be treated as a stability index instead of other available indices. It is also being proposed that the inclusion of MPI as a stability parameter in physical or numerical modeling can improve accurate local severe storm predictions as a useful predictor and can also be used as diagnostic tools. The MPI can make a useful simulation using entire temperature and moisture profile data for the assessment of instability significantly to severe weather forecasting since other instability indices are often derived from a fixed pressure level quantity of vertical profile parameters.     

Geomorphology and Petroleum Prospects of Cauvery Basin,Tamilnadu, Based on Interpretation of Indian Remote Sensing Satellite (IRS) Data

Geomorphological studies of the Cauvery basin, Tamilnadu were carried out using IRS images with special emphasis on identification of zones of hydrocarbon occurrences. The basin exhibits landforms of fluvial and fluvio-marine plains. Two major trends of lineaments and 15 circular anomalies have been identified. The NW-SE trend appears to be younger and might have played an important role in migration and entrapment of hydrocarbons. Six circular anomalies are associated with known oil/gas wells. The study has identified probable zones of hydrocarbon occurrences.     

Forest cover change prediction using hybrid methodology of geoinformatics and Markov chain model: A case study on sub-Himalayan town Gangtok,India

In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020.     

Comprehensive test of different cumulus parameterization schemes for the simulation of the Indian summer monsoon

Summary The global spectral model of NCMRWF at T80 horizontal resolution and 18 vertical levels has been integrated for the summer season (July) using different cumulus parameterization schemes namely, the Simplified Arakawa-Schubert scheme (SAS), the Relaxed Arakawa-Schubert Scheme (RAS), and the Kuo-type cumulus parameterization scheme (KUO). The results have been compared with mean analysis of the operational NCMRWF model (ANA) and other available observations. Results indicate that, while the global distributions of basic fields such as the wind, temperature and moisture are fairly well simulated by all the three schemes, there are many differences seen in the simulation of the typical features of the Indian summer monsoon. The strength of the Low Level Westerly Jet (LLWJ), the Cross Equatorial Flow (CEF), and the Tropical Easterly Jet (TEJ) are better simulated by RAS and SAS as compared to ANA than the KUO scheme. RAS and SAS produce strong rising motion owing to strong intensity of convection produced by these two schemes. This in turn produces stronger Hadley cell by RAS and SAS than compared to the KUO scheme. Simulation of the 200 mb velocity potential and divergent wind by RAS and SAS produced two prominent centers, one in the Bay of Bengal and another in the Western Pacific, which correspond to the intense latent heating by cumulus convection during the active monsoon phase. The velocity potential and divergent winds were weaker in KUO, than compared to RAS and SAS. The simulation of OLR is improved by RAS as compared to observations. The cold bias produced by KUO at 200 mb is reduced by RAS and is substantially improved by SAS. Study of observed and simulated rainfall indicated that RAS and SAS produced better distribution of precipitation over the Western Ghat Mountains and the Arakan coast, where deep cumulus convection is produced due to orographic forcing of the warm moist air. The KUO scheme underestimated the rainfall over these two regions, but produced slightly better distribution of rainfall over the northwest and central India, where the intensity of convection is relatively weaker. Evaluation of overall dynamics, thermal structure and rainfall indicates that in general, SAS is able to provide relatively better results compared to other two schemes. Received October 3, 2000/Revised December 5, 2000     

The retention of ammonia and sulfur dioxide during riming of ice particles and dendritic snow flakes: laboratory experiments in the Mainz vertical wind tunnel

Laboratory experiments were carried out in the Mainz vertical wind tunnel to determine the retention of the trace gases ammonia and sulfur dioxide dissolved in supercooled cloud droplets during riming. The conditions during riming were similar to the ones in atmospheric mixed phase clouds: temperatures from ?18 °C to ?5 °C, liquid water contents between 1 and 1.5 g m^?3, liquid drop radii between 10 and 20 μm, liquid phase concentrations from 1 to 22 mg/l. As collectors, floating ice particles and snow flakes with diameters between 6 mm and 1.5 cm were used. After riming the retention coefficients, i.e. the fractions of the species which remained in the ice phase after freezing were determined. Retention coefficients lying between 0.1 and 1.0 were measured depending on the solubility and dissociation of the trace gas, liquid phase concentration, ambient air temperature, and shape of rimed collector. This can be explained from the chemists’ point of view by the effective Henry’s law constant of the species and physically with the rate of latent heat removal from the rimed collector during freezing. Parameterizations derived from the different experimental cases describe the retention coefficients as a function of temperature. In general, an average retention of ammonia of 92?±?21 % was determined independently of liquid phase concentration while mean values for sulfur dioxide were 53?±?10 % at low liquid phase concentrations and 29?±?7 % at high liquid phase concentrations.