Assessment of Kalpana-1 Rainfall Product over Indian Meteorological Sub-Divisions During the Summer Monsoon Season

In this paper, Kalpana-1 derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates are compared with two multisatellite rainfall products namely, TRMM Multisatellite Precipitation Analysis (TMPA)-3B42 and Global Satellite Mapping of Precipitation (GSMaP), and India Meteorological Department (IMD) surface rain gauge (SRG)-based rainfall at meteorological sub-divisional scale over India. The performance of the summer monsoon rainfall of 2013 over Indian meteorological sub-divisions is assessed at different temporal scales. Comparison of daily accumulated rainfall over India from IMSRA shows a linear correlation of 0.72 with TMPA-3B42 and 0.70 with GSMaP estimates. IMSRA is capable to pick up daily rainfall variability over the monsoon trough region as compared to TMPA-3B42 and GSMaP products, but underestimates moderate to heavy rainfall events. Satellite-derived rainfall maps at meteorological sub-divisional scales are in reasonably good agreement with IMD-SRG based rainfall maps with some exceptions. However, IMSRA performs better than GSMaP product at meteorological sub-divisional scale and comparable with TMPA data. All the satellite-derived rainfall products underestimate orographic rainfall along the west coast, the Himalayan foothills and over the northeast India and overestimate rainfall over the southeast peninsular India. Overall results suggest that IMSRA estimates have potential for monsoon rainfall monitoring over the Indian meteorological sub-divisions and can be used for various hydro-meteorological applications.     

Uncertainties in modelling future hydrological change over West Africa

The aim of this paper is to evaluate current knowledge and uncertainties associated with the impact of increasing greenhouse gas and aerosol concentrations on the West African monsoon. For this purpose, coupled and time-slice simulations are used. A global measure of the monsoon changes is defined in order to avoid regional biases and to try and obtain significant results. The position and width of the monsoon in latitude are the main focuses. There is almost no agreement between the Coupled General Circulation models from the Coupled models Inter-Comparison project—Phase II in regard to the impact of climate change on the monsoon. Moreover, very simple discriminations between the models seem inappropriate to get a better signal. The role of the different forcings in time-slice simulations is then investigated. The sea surface temperature (SST) and particularly the pattern of the SST are shown to be the most important forcing. This accounts for the diversity of the results either from the coupled or the forced simulations with different SST changes. With a fixed SST, but of a smaller magnitude in AMJ, there are still uncertainties, coming first from the Atmospheric General Circulation models and the way they balance greenhouse gas and global SST increase. Finally the uncertainty due to the Land Surface models (LSMs) is not negligible. The greenhouse gas and the LSMs are shown to have more impact in August, when the monsoon is at its highest latitude on the continent.     

Multi-reference evaluation of uncertainty in earth orientation parameter measurements

Uncertainties in polar motion and length-of-day measurements are evaluated empirically using several data series from the space-geodetic techniques of the global positioning system (GPS), satellite laser ranging (SLR), and very long baseline interferometry (VLBI) during 1997–2002. In the evaluation procedure employed here, known as the three-corner hat (TCH) technique, the signal common to each series is eliminated by forming pair-wise differences between the series, thus requiring no assumed values for the “truth” signal. From the variances of the differenced series, the uncertainty of each series can be recovered when reasonable assumptions are made about the correlations between the series. In order to form the pair-wise differences, the series data must be given at the same epoch. All measurement data sets studied here were sampled at noon (UTC); except for the VLBI series, whose data are interpolated to noon and whose UT1 values are also numerically differentiated to obtain LOD. The numerical error introduced to the VLBI values by the interpolation and differentiation is shown to be comparable in magnitude to the values determined by the TCH method for the uncertainties of the VLBI series. The TCH estimates for the VLBI series are corrupted by such numerical errors mostly as a result of the relatively large data intervals. Of the remaining data sets studied here, it is found that the IGS Final combined series has the smallest polar motion and length-of-day uncertainties.     

Spatial process and data models: Toward integration of agent-based models and GIS

The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, we identify four key relationships affecting how geographic data (fields and objects) and agent-based process models can interact: identity, causal, temporal and topological. We discuss approaches to implementing tight integration, focusing on a middleware approach that links existing GIS and ABM development platforms, and illustrate the need and approaches with example agent-based models.     

GGM02 – An improved Earth gravity field model from GRACE

A new generation of Earth gravity field models called GGM02 are derived using approximately 14 months of data spanning from April 2002 to December 2003 from the Gravity Recovery And Climate Experiment (GRACE). Relative to the preceding generation, GGM01, there have been improvements to the data products, the gravity estimation methods and the background models. Based on the calibrated covariances, GGM02 (both the GRACE-only model GGM02S and the combination model GGM02C) represents an improvement greater than a factor of two over the previous GGM01 models. Error estimates indicate a cumulative error less than 1 cm geoid height to spherical harmonic degree 70, which can be said to have met the GRACE minimum mission goals. Electronic Supplementary Material Supplementary material is available in the online version of this article at     

Characterization and quantification of data voids in the shuttle Radar topography mission data

The goal of this study was to characterize and quantify the occurrence of data voids in data from the Shuttle Radar Topography Mission (SRTM) for the conterminous United States. For this purpose, SRTM data and corresponding data from the national elevation data were downloaded in 21 samples spatially organized to cover the main topography of the U.S. Void locations in SRTM data were compared to terrain attributes and subsequently the area of individual data voids to the same attributes. It was found that data voids amounted to 0.3% of the total dataset. Data voids were found in all topographic settings but more often in slopes steeper than approximately 20/spl deg/ that face south (170/spl deg/), and also in flat areas such as lakes and rivers. It was also found that more than 50% of all data voids were composed of connected pixels in groups less than six pixels. The largest data voids could be attributed to water bodies, while the rest could be explained by terrain-radar interaction characteristics.