Peculiarities of surface air temperature variations over the Far East regions in 1976–2005

Peculiarities are investigated of the air temperature variation tendencies at some stations of the Far East in 1976–2005. The estimate of linear trend equation coefficients is computed according to the air temperature observation data using the least squares method. It is demonstrated that the air temperature trend in northern regions possesses a small probability at small values of residual variability. In the southern regions, the trend significance increases for almost all seasons at small values of residual variability. At midlatitude stations, the trend significance in January and February decreases considerably due to the large values of residual variability.     

Comparison of Vegetation Indices from Two Ground Based Sensors

The best and commonly used ground-based sensor to monitor crop growth, ASD FieldSpecPro Spectroradiometer (Analytical Spectral Devices, Boulder, CO, USA) is a passive sensor, which can be used under adequate light condition. However, now-a-days active sensors such as GreenSeeker? (GS) handheld crop response (Trimble Agriculture division, USA) are used for monitoring crop growth and are flexible in terms of timeliness and illumination conditions besides being cheaper than the ASD. Before its wide use, the suitability and accuracy of GS should be assessed by comparing the NDVI measured by this instrument with that by ASD, under diverse wheat growing conditions of India. Keeping this in view, the present experiment was undertaken with the following objectives: (1) to find out the temporal variation of NDVI measured both by ASD and GS treatments, (2) to find out relationship between the NDVI measured through ASD and GS and, (3) to evaluate the suitability of GS for NDVI measurements. It was observed that the numerical value of NDVI as measured by GS was always significantly (P < 0.05) lower than that measured by ASD for all the experiments under study. The NDVI-ASD and NDVI-GS were significantly positively correlated (P < 0.01) with the correlation coefficients being +0.94, +0.88 and +0.87 for irrigation and nitrogen experiment, irrigation and cultivars experiment, and tillage, residue and nitrogen experiments, respectively. Further, the regression equation developed between the NDVI-ASD and NDVI-GS: [NDVI-GS = 1.070 × (NDVI-ASD ? 0.292] can be successfully used to compute the NDVI of ASD from that computed by GS.     

Estimation of Partial Pressure of Carbon Dioxide and Air-Sea Fluxes in Hooghly Estuary Based on In Situ and Satellite Observations

An empirical model is developed and used with remotely sensed predictors: sea surface temperature (SST) and chlorophyll-a concentration (Chl-a), to compute surface water partial pressure of carbon dioxide (pCO_2w) and air-sea fluxes of CO₂ in the Hooghly estuary and its adjacent coastal oceans. In situ observations used here were based on measurements carried out in this region during winter and summer periods in 2008. The estimated pCO_2w compares well with the in situ observations at root mean square error ±18 μatm. In winter, estimated pCO_2w ranges between 320 and 500 μatm with large values (>400 μatm) on the south-western and south-eastern flanks of the coastal domain and lower values (340–375 μatm) on the main-channel. In summer, it remained spatially uniform at 450 μatm. Extrapolation of the results over the study region based on the Moderate Imaging Specroradiometer (MODIS) measured SST and Chl-a suggests that the region is a strong source of atmospheric CO₂ during the summer with net release of 0.095 Tg C year^?1 (equivalent to mean flux of 90 molC m^?2 year^?1) and is a weak source during the winter with net release of 0.006 Tg C yr^?1 (0.5 molC m^?2 year^?1) from the geographical extent of 6000 Km² area.     

Nonlinear least-squares method via an isomorphic geometrical setup

The resolution of a nonlinear parametric adjustment model is addressed through an isomorphic geometrical setup with tensor structure and notation, represented by a u-dimensional “model surface” embedded in a flat n-dimensional “observational space”. Then observations correspond to the observational-space coordinates of the pointQ, theu initial parameters correspond to the model-surface coordinates of the “initial” pointP, and theu adjusted parameters correspond to the model-surface coordinates of the “least-squares” point . The least-squares criterion results in a minimum-distance property implying that the vector Q must be orthogonal to the model surface. The geometrical setup leads to the solution of modified normal equations, characterized by a positive-definite matrix. The latter contains second-order and, optionally, thirdorder partial derivatives of the observables with respect to the parameters. This approach significantly shortens the convergence process as compared to the standard (linearized) method.     

Seismic hazard monitoring in Kamchatka and its applications to the M = 6.6 earthquake of 6 October 1987

The earthquake of 6 October 1987 (M = 6.6), which occurred near the Shipunsky Cape, Kamchatka, was the largest crustal event in the vicinity of the main city of Kamchatka — Petropavlovsk-Kamchatsky — during the last three decades. It was followed by numerous aftershocks. This earthquake allowed us to test the effectiveness of the seismic hazard monitoring in Kamchatka, including the seismological, geodetic and hydrogeochemical surveys. The seismic survey provided the location and source nature of the main shock and aftershocks and the seismic environment of the main shock. The geodetic and hydrogeochemical surveys have yielded data on the response to earthquakes of the Earth's surface deformations, water level, and chemical elements concentration in the underground water. As a result, the following data were obtained:

u

The earthquake of 6 October had a seismic moment 4–10 E18 Nm, thrust type of faulting and the source volume of 20 × 20 × 10 km³. The maximum intensity was VI–VII (MSK-64 scale) and maximum acceleration 88 cm/s².

Before this event, a relative increase in the number of the upper mantle (depth more than 100 km) moderate magnitude earthquakes during 5 years and a one-year period of seismic quiescence for small shallow earthquakes, were recognized. Significant anomalies in HCO₃ and H₃BO₃ concentrations in the underground waters were observed in the wells a week before the main shock.

     

Simulating the effect of Nitrogen application on Wheat Yield by linking remotely sensed measurements with wtgrows simulation model

A field experiment was conducted on wheat at New Delhi with five treatments of Nitrogen (N) fertilizer application (0, 30, 60, 90 and 120 kgha^-1). Relationship has been established between observed leaf area index (LAI) and remotely sensed vegetation indices. These relationships are inverted and used for predicting LAI from vegetation indices on different days after sowing. The “re-initialization” strategy is implemented in model WTGROWS in which initial conditions of model are changed so that the model simulated LAI match remote sensing predicted LAI. The model performance with re-initialization has been evaluated by comparing the simulated grain yield and total above-ground dry matter (TDM) values with the actual observations. The results show that in-season re-initialization is effective in model course correction by improving the simulated results of yield and TDM for different N treatments even though the model was run with no N stress condition. Model re-initialization at different days shows that the closer is the day of re-initialization to crop anthesis the more effective is model course correction. Also, the treatment showing maximum error in yield simulation without re-initialization shows maximum reduction in error by re-initialization. The approach shows that the remote sensing inputs can substitute for some of the inputs or errors in inputs required by crop models for yield prediction.     

Low-low satellite-to-satellite tracking: a comparison between analytical linear orbit perturbation theory and numerical integration

Low-low satellite-to-satellite tracking (ll-SST) range-rate observations have been predicted by two methods: one based on a linear perturbation theory in combination with the Hill equations, and one based on solving the equations of motion of two low-flying satellites by numerical integration. The two methods produce almost equivalent Fourier spectra of the range-rate observations after properly taking into account a few resonant terms. For a typical GRACE-type configuration, where the two satellites trail each other at a distance of 300 km at an altitude of 460 km, and in the presence of the EGM96 gravity field model, complete to spherical harmonic degree and order 70, the agreement between the Fourier spectra is about 1 mm/s compared to a root-mean-square (RMS) value of more than 220 mm/s for the range-rate signal. The discrepancy of 1 mm/s can be reduced significantly when not taking into account perturbations caused by the J₂ term. Excluding the J₂ term, the agreement between the two methods improves to 0.4 mm/s compared to a RMS value of 6 mm/s for the range-rate signal. These values are 0.01 and 2.3 mm/s when ignoring the spectrum for frequencies below two cycles per orbital revolution, reducing the discrepancy even further to about 0.5% of the signal. The selected linear perturbation theory is thus capable of modeling gravity field induced range-rate observations with very high precision for a large part of the spectrum.     

Wet tropospheric effects on precise relative GPS height determination

Summary Considerable interest has been generated recently in the use of the Global Positioning System (GPS) for precise height determination. A major error source in these measurements is the propagation delay due to atmospheric water vapour. In order to achieve the high precisions required for such applications as absolute sea-level monitoring improvement of wet delay modelling is necessary. Results from a GPS campaign show a significant correlation (0.91) between the variability of the wet delay measured using a water vapour radiometer (WVR) at the Onsala site and the absolute value of the residual error in the height determination of a 134 km baseline from Onsala to Jönköping. This correlation indicates that the atmosphericvariability as inferred from the WVR data includes information on the quality of the GPS height estimate. During periods of high atmospheric activity, e.g., during the passage of a weather front, the use of a six-parameter gradient model reduces the spread for the vertical coordinate from 40 mm to 20 mm (with standard deviations of 17 mm and 9 mm respectively) over the 134 km baseline (less than 1 × 10^–7) using 8 hour data spans on 11 different days over a six month period.