A sulfotransferase specific to N-21 of gonyautoxin 2/3 from crude enzyme extraction of toxic dinoflagellate Alexandrium tamarense CI01

Sulfotransferase (ST) is the first enzyme discovered in association with paralytic shellfish poisoning (PSP) toxin biosynthesis in toxic dinoflagellates. This study investigates the ST activity in crude enzyme extraction of a toxic dinoflagellate species, Alexandrium tamarense CI01. The results show that crude enzyme can transfer a sulfate group from 3’-phosphoadenosine 5’-phosphosulfate (PAPS) to N-21 in the carbamoyl group of gonyautoxin 2/3 (GTX2/3) to produce C1/C2, but is inactive toward STX to produce GTX5. The crude enzyme is optimally active at pH 6.0 and 15°C. The activity is enhanced by Co2 , Mg2 , Mn2 and Ca2 individually, but is inhibited by Cu2 . Moreover, the activity shows no difference when various sulfur compounds are used as sulfate donors. These results demonstrate that the ST specific to GTX2/3 is present in the cells of A. tamarense CI01 and is involved in PSP toxin biosynthesis. In addition, the ST from different dinoflagellates is species-specific, which explains well the various biosynthesis pathways of the PSP toxins in toxic dinoflagellates.     

Predicting the dependency of a degree of saturation on void ratio and suction using effective stress principle for unsaturated soils

The paper presents an approach to predicting variation of a degree of saturation in unsaturated soils with void ratio and suction. The approach is based on the effective stress principle for unsaturated soils and several underlying assumptions. It focuses on the main drying and wetting processes and does not incorporate the effects of hydraulic hysteresis. It leads to the dependency of water retention curve (WRC) on void ratio, which does not require any material parameters apart from the parameters specifying WRC for the reference void ratio. Its validity is demonstrated by comparing predictions with the experimental data on four different soils taken over from the literature. Good correlation between the measured and predicted behaviour indirectly supports applicability of the effective stress principle for unsaturated soils. Copyright © 2009 John Wiley & Sons, Ltd.     

Consistent seasonal snow cover depth and duration variability over the Western Himalayas (WH)

Precipitation in solid form, i.e., snow, during winter season over the Western Himalayas (WH) leads to the build-up of seasonal snow cover. Seasonal snow cover build-up (snow cover depth and duration) largely depends on atmospheric variables such as temperature, precipitation, radiation, wind, etc. Integrated (combined) influence of atmospheric variables on seasonal snow cover gets reflected in terms of spatial and temporal variability in seasonal snow cover build-up pattern. Hence spatial and temporal variability of seasonal snow cover build-up can serve as a good indicator of climate change in high altitude mountainous regions like the WH. Consistent seasonal snow cover depth and duration, delay days and early melt days of consistent seasonal snow cover at 11 stations spread across different mountain ranges over the WH were analyzed. Mean, maximum and percentiles (25th, 50th, 75th, 90th and 95th) of consistent seasonal snow cover depth and duration show decline over the WH in the recent past 2–3 decades. Consistent seasonal snow cover is found to melt early and snow cover build-up pattern is found to show changes over the WH. Decline in consistent seasonal snow cover depth, duration and changing snow cover build-up pattern over the WH in recent decades indicate that WH has undergone considerable climate change and winter weather patterns are changing in the WH.     

Characteristics of the Asian–Pacific Oscillation in Boreal Summer Simulated by BCC_CSM with Different Horizontal Resolutions

The summer Asian–Pacific Oscillation(APO) is a major teleconnection pattern that reflects the zonal thermal contrast between East Asia and the North Pacific in the upper troposphere. The performance of Beijing Climate Center Climate System Models(BCC CSMs) with different horizontal resolutions, i.e., BCC CSM1.1 and BCC CSM1.1(m), in reproducing APO interannual variability, APO-related precipitation anomalies, and associated atmospheric circulation anomalies, is evaluated.The results show that BCC CSM1.1(m) can successfully capture the interannual variability of the summer APO index. It is also more capable in reproducing the APO's spatial pattern, compared to BCC CSM1.1, due to its higher horizontal resolution. Associated with a positive APO index, the northward-shifted and intensified South Asian high, strengthened extratropical westerly jet, and tropical easterly jet in the upper troposphere, as well as the southwesterly monsoonal flow over North Africa and the Indian Ocean in the lower troposphere, are realistically represented by BCC CSM1.1(m), leading to an improvement in reproducing the increased precipitation over tropical North Africa, South Asia, and East Asia, as well as the decreased precipitation over subtropical North Africa, Japan, and North America. In contrast, these features are less consistent with observations when simulated by BCC CSM1.1. Regression analysis further indicates that surface temperature anomalies over the North Pacific and the southern and western flanks of the Tibetan Plateau are reasonably reproduced by BCC CSM1.1(m), which contributes to the substantial improvement in the simulation of the characteristics of summer APO compared to that of BCC CSM1.1.     

An algorithm to retrieve precipitation with synthetic aperture radar

This paper presents a new type of rainfall retrieval algorithm, called the model-oriented statistical and Volterra integration. It is a combination of the model-oriented statistical (MOS) and Volterra integral equation (VIE) approaches. The steps involved in this new algorithm can be briefly illustrated as follows. Firstly, information such as the start point and width of the rain is obtained through pre-analysis of the data received by synthetic aperture radar (SAR). Secondly, the VIE retrieval algorithm is employed over a short distance to obtain information on the shape of the rain. Finally, the rain rate can be calculated by using the MOS retrieval algorithm. Simulation results show that the proposed algorithm is effective and simple, and can lead to time savings of nearly 50% compared with MOS. An example of application of SAR data is also discussed, involving the retrieval of precipitation information over the South China Sea.     

Estimation of Above Ground Biomass for Central Indian Deciduous Forests Using ALOS PALSAR L-Band Data

Reliable and accurate estimates of tropical forest above ground biomass (AGB) are important to reduce uncertainties in carbon budgeting. In the present study we estimated AGB of central Indian deciduous forests of Madhya Pradesh (M.P.) state, India, using Advanced Land Observing Satellite – Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR) L-band data of year 2010 in conjunction with field based AGB estimates using empirical models. Digital numbers of gridded 1?×?1° dual polarization (HH & HV) PALSAR mosaics for the study area were converted to normalized radar cross section (sigma naught - σ⁰). A total of 415 sampling plots (0.1 ha) data collected over the study area during 2009–10 was used in the present study. Plot-level AGB estimates using volume equations representative to the study area were computed using field inventory data. The plot-level AGB estimates were empirically modeled with the PALSAR backscatter information in HH, HV and their ratios from different forest types of the study area. The HV backscatter information showed better relation with field based AGB estimates with a coefficient of determination (R²) of 0.509 which was used to estimate spatial AGB of the study area. Results suggested a total AGB of 367.4 Mt for forests of M.P. state. Further, validation of the model was carried out using observed vs. predicted AGB estimates, which suggested a root mean square error (RMSE) of ±19.32 t/ha. The model reported robust and defensible relation for observed vs. predicted AGB values of the study area.     

Using a regional numerical weather prediction model for GNSS positioning over Brazil

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.     

Weak GPS signal tracking using FFT discriminator in open loop receiver

An open loop tracking architecture, which tracks GPS signals under weak and challenging conditions, is analyzed. The in-phase and quadrature-phase integration pair is regarded as a single tone complex signal. An FFT-based method is used as a frequency discriminator to estimate the Doppler frequency residual of the single tone signal. Another FFT-based method applies complex squaring to eliminate the effect of the navigation data bits polarities. The performance of the FFT-based discriminators is assessed in three criteria. Those criteria are the signal strength and dynamic range that can be tracked and the accuracy of the estimated Doppler frequency. In addition, the performance of the discriminators is analyzed to provide the theoretical and simulated peak detection probability. The results indicate that the FFT discriminator can track signals about 5 dB weaker than the signals that can be tracked by the complex squared FFT discriminator. In a quasi-static environment, the Doppler frequency residual can be assumed to be around zero, which can enable the FFT-based discriminators to track signals with approximately 2 dB less power. Moreover, the performance of the FFT-based discriminators is compared with the performance of two other frequency discriminators, namely the fast–slow and power-based. The comparison results indicate that these two frequency discriminators give higher frequency estimation accuracy, but they have a narrower dynamic range.