Soil moisture: A critical focus for global change studies

The scientific and human dimensions of global change have many overlapping themes which offer a focus on processes occurring at the continental surface. Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land/air boundary. Soil moisture controls the extent to which plants can exploit sunlight in photosynthesis and the effectiveness with which agriculture, forestry and freshwater resources can be developed. The importance of the soil moisture to many, diverse communities has resulted in a very large collection of numerical models all of which simulate soil moisture. This paper outlines why and how a series of soil moisture simulation intercomparisons were conducted in a one-year exercise jointly sponsored by the International Geosphere Biosphere Programme and the World Climate Research Programme.     

Type II bursts of different subclasses associated to transients and mass ejection in the higher corona

The list of mass ejections published in Solar Geophysical Data during the period of Jan. 1981 to Oct. 1987 contains about 1300 Surges, Sprays and Type II bursts. The relationship between the mass ejection events and the shock front events is investigated by means of correlation of time and position. The result shows that type II bursts start as frequently after the mass ejections as prior to them.     

Is dark matter created in the gravitation field of galaxies?

Using the heuristic arguments of quantum physics we describe a new mechanism of the creation of short-living particles from the virtual ones in a stationary gravitation field. The mass of these particles is a function of the intensity of gravitation field. We suppose that the particles created in the gravitation field form a part of the non-baryonic dark matter. Having the intensity of gravitation field in a galaxy we can calculate the density of dark matter created in it by the vacuum quantum fluctuation. We calculate the distribution of this dark matter in a model galaxy and show that its total mass is comparable with the visible mass of the galaxy.     

First results from the Gauribidanur Radio heliograph

Observations of the Sun at two frequencies (51 and 77 MHz) using the East-West arm of the Gauribidanur Radio heliograph are presented.     

Solar-planetary cycles in Jupiter's great red spot darkness

The change in the darkness of the Great Red Spot (GRS) of Jupiter (1894–1974) has been analysed with Fourier (FFT), Maximum Entropy and Power spectrum (Blackman-Tukey window) (PSA) methods of spectrum analysis. Significance, non-randomness and stationarity tests assigned high variance to periodicities of 33 ± 4, 13–15, about 11, 9 and 3 yrs. The highest correlation between solar activity and GRS darkness was found for the 14th and 16th solar cycle. The periodicities obtained are interpreted as the combined eftects of solar activity, planetary resonances and internal jovian mechanisms.     

Brief description of bare essentials of surface transfer and results from simulations with the HAPEX-MOBILHY data

The Bare Essentials of Surface Transfer (BEST) land surface scheme is briefly described and the key physical parameterisations discussed. Results are then presented to illustrate how the model performs, with forcing data for HAPEX-MOBILHY, compared to a series of other schemes in the simulation of evaporation and sensible heat. The implications of the models performance, and some indications of the future development of the scheme are provided. The basic version of BEST was found to overestimate evaporation for the HAPEX-MOBILHY data, simulating 816 mm yr⁻¹ compared to a range of 550 to 816 mm yr⁻¹ for all models. A modification to the β parameterisation reduced the evaporation to 759 mm yr⁻¹ which, although an improvement, is still probably too high.     

The time-scale for core collapse in spherical star clusters

The collapse time for a cluster of equal-mass stars is usually stated to be either 330 central relaxation times (t_rc) or 12-19 half-mass relaxation times (t_rh). But the first of these times applies only to the late stage of core collapse, and the second only to low-concentration clusters. To clarify how the time depends on the density profile, the Fokker-Planck equation is solved for the evolution of a variety of isotropic cluster models, including King models, models with power-law density cusps of ρ ∼ r^−γ, and models with nuclei. The collapse times for King models vary considerably with the cluster concentration when expressed in units of t_rc or t_rh, but vary much less when expressed in units of t_rc divided by a dimensionless measure of the temperature gradient in the core. Models with cusps have larger temperature gradients and evolve faster than King models, but not all of them collapse: those with 0 < γ < 2 expand because they start with a temperature inversion. Models with nuclei collapse or expand as the nuclei would in isolation if their central relaxation times are short; otherwise their evolution is more complicated. Suggestions are made for how the results can be applied to globular clusters, galaxies, and clusters of dark objects in the centers of galaxies.Scott D. Tremaine     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.