Modelling net erosion responses to enviroclimatic changes recorded upon multisecular timescales

Land use change has been recognized throughout the Earth as one of the most important factors influencing the occurrence of rainfall-driven geomorphological processes. However, relating the occurrence of historical soil erosion rates is difficult because of the lack of long-term research projects in river basins. Also, complex models are not adequate to reconstruct erosion rate changes because they require significant input data not always available on long timescales. Given the problems with assessing sediment yield using complex erosion models, the objective of this study is to explore a parsimonious scale-adapted erosion model (ADT) from the original Thornes and Douglas algorithms, which aims at reconstruction of annual net erosion (ANE) upon multisecular timescales. As a test site, the Calore River basin (3015 km² in southern Italy) provides a peculiar and unique opportunity for modelling erosion responses to climate and land cover changes, where input-data generation and interpretation results were also supported by documented hydrogeomorphological events that occurred before and after land deforestation. In this way, ANE_ADT-values were reconstructed for the period 1675–2004 by using precipitation indexes, complemented by recent instrumental records, and by using land cover statistics from documented agrarian sources. Pulses of natural sedimentation in the predeforestation period have been related to Vesuvius volcanic activity and changes in rainstorm frequency. After deforestation, the basin system became unstable with sudden fluctuations in the hydrogeomorphological regime contributing significantly to increased erosion and, in turn, sediment transport sequences via river drainage towards the Tyrrhenian coast.     

Search for long term variations of the interplanetary magnetic field

A statistical study is made of the long term variations of the interplanetary magnetic field parameters collected in the years 1964 to 1973 by 12 spacecraft (IMP's, Pioneers and HEOS). Although temporal fluctuations are observed on field components and magnitudes no clear solar cycle variation is found. The same conclusion holds for the statistical distributions and variances of these parameters. A search for possible heliographic latitude effects on the field also leads to a negative conclusion.     

The western Mediterranean climate: how will it respond to global warming?

The paper discusses the newly produced temperature and precipitation series from instrumental observations in the Western Mediterranean (WM) area, dating back to 1654. The two series had a continuous swing and unstable coupling passing from correlation to anti-correlation. Only after 1950 are they permanently anti-correlated with increasing temperature and decreasing precipitation. It is not clear how long this coupling will persist. The analysis of the correlation between the Northern Hemisphere (NH) and the WM temperature anomalies and their trends shows a certain variability from 1850 to 1950; later a strong coupling between NH and WM. Results suggest that the WM climate is approaching a turning point that might locally oppose the adverse effects of Global Warming.     

Magnetic and thermal energies in the solar wind

Magnetic and thermal energy densities measured in the solar wind by the spacecraft Vela-3/IMP-3, Explorer-34 and HEOS-1 are compared. A linear relation seems to exist, on the average, between these parameters, suggesting a possible equipartition of energy between plasma and magnetic field.     

Mixed nonlinear regression for modelling historical temperatures in Central–Southern Italy

This paper has exploited, for Central and Southern Italy (Mediterranean Sub-regional Area), an unprecedented historical dataset as an attempt to model seasonal (winter and summer) air temperatures in pre-instrumental time (back to 1500). Combining information derived from proxy–documentary data and large-scale simulation, a statistical downscaling approach in the form of mixed regression model was developed to adapt larger-scale estimations (regional component) to the sub-regional temperature pattern (local component). It interprets local temperature anomalies by means of monthly based Temperature Anomaly Scaled Index in the range ?5 (very cold conditions in June) to 2 (very warm conditions). The modelled response agrees well with the independent data from the validation sample (Nash–Sutcliffe efficiency coefficient, >0.60). The advantage of the approach is not merely increased accuracy in estimation. Rather, it relies on the ability to extract (and exploit) the right information to replicate coherent temperature series in historical times.