Improved rainfall estimation over the Indian region using satellite infrared technique

The GOES Precipitation Index (GPI) technique (Arkin, 1979) for rainfall estimation has been in operation for the last three decades. However, its applications are limited to the larger temporal and spatial scales. The present study focuses on the augmentation on GPI technique by incorporating a moisture factor for the environmental correction developed by Vicente et al. (1998). It consists of two steps; in the first step the GPI technique is applied to the Kalpana-IR data for rainfall estimation over the Indian land and oceanic region and in the second step an environmental moisture correction factor is applied to the GPI-based rainfall to estimate the final rainfall. Detailed validation with rain gauges and comparison with Tropical Rainfall Measuring Mission (TRMM) merged data product (3B42) are performed and it is found that the present technique is able to estimate the rainfall with better accuracy than the GPI technique over higher temporal and spatial domains for many operational applications in and around the Indian regions using Indian geostationary satellite data. Further comparison with the Doppler Weather Radar shows that the present technique is able to retrieve the rainfall with reasonably good accuracy.     

Short-term variation of cosmic ray diurnal anisotropy and solar activity

A correlative analysis has been made between cosmic ray intensity and solar activity (sunspot numbers) during high amplitude days for the period 1991–1995. The high amplitude days with the time of maximum in the corotational/azimuthal direction do not indicate any significant correlation with solar activity. The diurnal amplitude significantly remains constant and high (0.5%) during the entire period. Our observations suggest that the direction of the anisotropy of high amplitude anisotropic wave train events contribute significantly to the short-term behavior of the cosmic ray diurnal anisotropy. The correlation coefficient is found to remain positive during solar activity maximum for all the high amplitude anisotropic wave train events.     

Rainfall retrieval over Indian land and oceanic regions from SSM/I microwave data

Present study focuses on the estimation of rainfall over Indian land and oceanic regions from the Special Sensor Microwave/Imager (SSM/I) on the Defense Meteorological Satellite Program (DMSP) F-13. Based on the measurements at 19.35, 22.235 and 85.5 GHz channels of SSM/I Satellite, scattering index (SI) has been developed for the Indian land and oceanic regions separately. These scattering indices were co-located against rainfall from Precipitation Radar (PR) onboard Tropical Rainfall Measuring Mission (TRMM) to develop a new regional relationship between the SI and the rain rate for the Indian land and oceanic regions. A non-linear fit between the rain rate and the SI is established for rain measurement. In order to have confidence in our method, we have also estimated rainfall using the global rainfall and scattering index relationship developed by Ferraro and Marks [Ferraro, R.R., Marks, G.F. The development of SSM/I rain rate retrieval algorithms using ground based radar measurements. J. Atmos. Ocean. Technol. 12, 755–770, 1995]. The validation with the rain-gauge shows that the present scheme is able to retrieve rainfall with better accuracy than that of Ferraro and Marks (1995). Further intercomparison with TRMM-2A12 and validation with rain-gauges rainfall showed that the present algorithm is able to retrieve the rainfall with reasonably good accuracy.     

Ionospheric precursors observed at low latitudes around the time of koyna earthquake

On December 11, 1967 at 05:21 LT, an immense earthquake of magnitude 6.7 struck Koyna, the Indian province of Maharashtra. Its epicenter was located at geographic latitude 17.37°N and longitude 73.75°E with depth of about 3 km. Ground based measurements show variation in the critical frequency of ionospheric F2 layer (foF2) before and after the shock. In the present study the behavior of F2-region of ionosphere has been examined over the equatorial and low latitudinal region ionosphere during the month of December 1967 around the time of Koyna earthquake. For this purpose, the ionospheric data collected with the help of ground-based ionosondes installed at Hyderabad (located close to the earthquake epicenter) Ahmedabad, Trichirapulli, Kodaikanal and Trivendrum have been utilized. The upper and lower bound of Interquartile range (IRQ) are constructed to monitor the variations in foF2 other than day-to-day and diurnal pattern for finding the seismo-ionospheric precursors. Some anomalous electron density variations are observed between post midnight hours to local pre-noon hours at each station. These anomalies are strongly time dependent and appeared a couple of days before the main shock. The period considered in this study comes under the quiet geomagnetic conditions. Hence, the observed anomalies (which are more than the usual day-to-day variability) over all stations are likely to be associated with this imminent earthquake. The possible mechanism to explain these anomalies is the effect of seismogenic electric field generated just above the surface of earth within the earthquake preparation zone well before the earthquake due to emission of radioactive particles and then propagated upward, which perturbs the F-region ionosphere.     

An algorithm for estimation and separation of ephemeris and clock errors in SBAS

The estimation and separation of ephemeris and clock errors is an integral part of a SBAS (Space Based Augmentation System). Generally, the global solution is based on the full state approach for satellite errors (ephemeris and clock) and station errors, using a large least square estimator; or the other way is to sequentially estimate the ephemeris and clock through a Kalman filter, using a complex model of the satellite dynamics. In this paper, the estimation and separation of ephemeris and clock errors is addressed through a unique approach of combining both the methods. The algorithm employs measurements, which are pre-processed for various errors and known biases. A single difference technique is used to separately estimate the ephemeris and clock components. The ephemeris Kalman filter uses a priori information of ephemeris errors along with measurements through a minimum variance estimator to provide ephemeris error estimate. A similar approach is adopted in the clock error estimation process, to provide clock and clock rate estimates. The algorithm results are presented using simulated data for known errors in ephemeris/clock and subsequent retrieval. This algorithm estimates these errors as corrections to the broadcast Global Positioning System (GPS) navigation data, required by a SBAS user for accuracy improvement.     

Microbiological characterization of a regenerative life support system.

A Variable Pressure Plant Growth Chamber (VPGC), at the Johnson Space Center's (JSC) ground-based Regenerative Life Support Systems (RLSS) test bed, was used to produce crops of soil-grown lettuce. The crops and chamber were analyzed for microbiological diversity during lettuce growth and after harvest. Bacterial counts for the rhizosphere, spent nutrient medium, heat exchanger condensate, and atmosphere were approximately 10(11) Colony Forming Units (CFU) g-1 10(5) CFU ml-1, 10(5) CFU ml-1, and 600 CFU m-3, respectively. Pseudomonas was the predominant bacterial genus. Numbers of fungi were about 10(5) CFU g-1 in the rhizosphere, 4-200 CFU ml-1 in the spent nutrient medium, 110 CFU ml-1 in the heat exchanger condensate, and 3 CFU m-3 in the atmosphere. Fusarium and Trichoderma were the predominant fungal genera.     

Effect of Interplanetary Transients on Cosmic Ray Anisotropic Variations

In the present work the cosmic ray intensity data recorded with ground-based neutron monitor at Deep River has investigated taking into account the associated interplanetary magnetic field and solar wind plasma data during 1981—1994.A large number of days having abnormally high/low amplitudes for successive number of five or more days as compared to annual average amplitude of diurnal anisotropy have been taken as high/low amplitude anisotropic wave train events(HAE/LAE).The amplitude of the diurnal anisotropy of these events is found to increase on the days of magnetic cloud as compared to the days prior to the event and it found to decrease during the later period of the event as the cloud passes the Earth.The High-Speed Solar Wind Streams(HSSWS)do not play any significant role in causing these types of events. The interplanetary disturbances(magnetic clouds)are also effective in producing cosmic ray decreases.Hαsolar flares have a good positive correlation with both amplitude and direction of the anisotropy for HAEs, whereas PMSs have a good positive correlation with both amplitude and direction of the anisotropy for LAEs. The source responsible for these unusual anisotropic wave trains in CR has been proposed.     

ULF wave index as magnetospheric and space-weather parameters

Waves in the Ultra Low Frequency (ULF) band owe their existence to solar wind turbulence and transport momentum and energy from the solar wind to the magnetosphere and farther down. Therefore an index based on ULF wave power could better characterize solar wind–magnetosphere interaction than K_P, Dst, AE, etc. indices which described mainly quasi-study state condition of the system. We have shown that the ULF wave index accurately characterize relativistic electron dynamics in the magnetosphere as these waves are closely associated with circulation, diffusion and energization of relativistic electrons in the magnetosphere. High speed solar wind streams also act as a significant driver of activity in the Earth’s magnetosphere co-rotating interaction region and are responsible for geomagnetic activities. In the present paper, we have analyzed various cases related with very weak (quiet) days, weak days, storm days and eclipse events and discussed the utility of the ULF wave index to explain the magnetospheric dynamics and associated properties. We have tried to explain that the ULF wave index can equally be useful as a space weather parameter like the other indices.     

Retrieval of spinach crop parameters by microwave remote sensing with back propagation artificial neural networks: A comparison of different transfer functions

Back propagation artificial natural network (BPANN) is a well known and widely used machine learning methodology in the field of remote sensing. In this paper an attempt is made to retrieve the spinach crop parameters like biomass, leaf area index, average plant height and soil moisture content by using the X-band scattering coefficients with BPANN at different growth stages of this crop. The maturity age of this crop was found to be 45 days from the date of sowing. After 45 days from the date of sowing, this crop was cut at a certain height for production. Then, it is a point of interest to investigate the microwave response of variation in production. Significant variations in all the crop parameters were observed after cutting the crop and consequently made the problem more critical. Our work confirms the utility of BPANN in handling such a non-linear data set. The BPANN is essentially a network of simple processing nodes arranged into different layers as input, hidden and the output. The input layer propagates components of a particular input vector after weighting these with synaptic weights to each node in the hidden layer. At each node, these weighted input vector components are added. Each hidden layer computes output corresponding to these weighted sum through a non-linear/linear function (e.g. LOGSIG, TANSIG and PURLIN). These functions are known as transfer functions. Thus, each of the hidden layer nodes compute output values, which become inputs to the nodes of the output layer. At nodes of output layer also a weighted sum of outputs of previous layer (hidden layer) are obtained and processed through a transfer function. Thus, the output layer nodes compute the network output for the particular input vector. In this paper, output nodes use linear transfer function. Different transfer functions e.g. TANSIG, LOGSIG and PURELIN were used and the performance of the ANN was optimized by changing the number of neurons in the hidden layers. The present analysis suggests the need of critical analysis of the BPANN in terms of selection of the best transfer function and other network parameters for the better results.