Post-Materialism as a Cultural Factor Influencing Entrepreneurial Activity across Nations

The study of the determinants of entrepreneurship at the country level has been domi-nated by economic influences. The relative stability of differences in levels of entrepreneurship across countries suggests that other forces such as certain institutional and/or cultural factors are at play. The objective of this paper is to explore how post-materialism explains differences in entrepreneurial activity across countries. Entrepreneurial activity is defined as the percent of a country's population that is self-employed, using a broad definition that also includes CEOs of both unincorporated and legally incorporated establishments. The measure for post-materialism is based upon Inglehart's four-item post-materialism index. Because of the known interactions between economic and cultural factors found in previous research, a set of economic and cultural factors is included to provide a clearer picture of the independent role post-materialism plays in prediction of self-employment levels. In particular, education, life satisfaction, church attendance and political (left or right) extremism are used as control variables in our analyses using data of 14 OECD countries over in recent period. Findings confirm the significance of post-materialism in predicting self-employment even when controlling for economic and cultural factors. However, strong co-variation between post-materialism and other cultural factors makes it difficult to clearly discriminate between the effects.

Diagnosis of Local Land-Atmosphere Feedbacks in India

Following the convective triggering potential (CTP)–humidity index (HIlow) framework by Findell and Eltahir, the sensitivity of atmospheric convection to soil moisture conditions is studied for India. Using the same slab model as Findell and Eltahir, atmospheric conditions in which the land surface state affects convective precipitation are determined. For India, CTP–HIlow thresholds for land surface–atmosphere feedbacks are shown to be slightly different than for the United States. Using atmospheric sounding data from 1975 to 2009, the seasonal and spatial variations in feedback strength have been assessed. The patterns of feedback strengths thus obtained have been analyzed in relation to the monsoon timing. During the monsoon season, atmospheric conditions where soil moisture positively influences precipitation are present about 25% of the time. During onset and retreat of the monsoon, the south and east of India show more potential for feedbacks than the north. These feedbacks suggest that large-scale irrigation in the south and east may increase local precipitation. To test this, precipitation data (from 1960 to 2004) for the period about three weeks just before the monsoon onset date have been studied. A positive trend in the precipitation just before the monsoon onset is found for irrigated stations. It is shown that for irrigated stations, the trend in the precipitation just before the monsoon onset is positive for the period 1960–2004. For nonirrigated stations, there is no such upward trend in this period. The precipitation trend for irrigated areas might be due to a positive trend in the extent of irrigated areas, with land–atmosphere feedbacks inducing increased precipitation

Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following 5 question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics 10 of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in sim15 ulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit 20 large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations

Full carbon accounting: mission impossible?

Quantifying mitigation efforts against a large background variability is a demanding task, in which scientific complexity and manageable, transparent accounting systems have difficulty to meet. Can we bring these together

Effects of precipitation uncertainty on discharge calculations for main river basins

This study quantifies the uncertainty in discharge calculations caused by uncertainty in precipitation input for 294 river basins worldwide. Seven global gridded precipitation datasets are compared at river basin scale in terms of mean annual and seasonal precipitation. The representation of seasonality is similar in all datasets, but the uncertainty in mean annual precipitation is large, especially in mountainous, arctic, and small basins. The average precipitation uncertainty in a basin is 30%, but there are strong differences between basins. The effect of this precipitation uncertainty on mean annual and seasonal discharge was assessed using the uncalibrated dynamic global vegetation and hydrology model Lund-Potsdam-Jena managed land (LPJmL), yielding even larger uncertainties in discharge (average 90%). For 95 basins (out of 213 basins for which measurements were available) calibration of model parameters is problematic because the observed discharge falls within the uncertainty of the simulated discharge. A method is presented to account for precipitation uncertainty in discharge simulations

Sensible and latent heat flux from radiometric surface temperatures at the regional scale: methodology and validation

The CarboEurope Regional Experiment Strategy (CERES) was designed to develop and test a range of methodologies to assess regional surface energy and mass exchange of a large study area in the south-western part of France. This paper describes a methodology to estimate sensible and latent heat fluxes on the basis of net radiation, surface radiometric temperature measurements and information obtained from available products derived from the Meteosat Second Generation (MSG) geostationary meteorological satellite, weather stations and ground-based eddy covariance towers. It is based on a simplified bulk formulation of sensible heat flux that considers the degree of coupling between the vegetation and the atmosphere and estimates latent heat as the residual term of net radiation. Estimates of regional energy fluxes obtained in this way are validated at the regional scale by means of a comparison with direct flux measurements made by airborne eddy-covariance. The results show an overall good matching between airborne fluxes and estimates of sensible and latent heat flux obtained from radiometric surface temperatures that holds for different weather conditions and different land use types. The overall applicability of the proposed methodology to regional studies is discusse

Effects of precipitation uncertainty on discharge calculations for main river basins

This study quantifies the uncertainty in discharge calculations caused by uncertainty in precipitation input for 294 river basins worldwide. Seven global gridded precipitation datasets are compared at river basin scale in terms of mean annual and seasonal precipitation. The representation of seasonality is similar in all datasets, but the uncertainty in mean annual precipitation is large, especially in mountainous, arctic, and small basins. The average precipitation uncertainty in a basin is 30%, but there are strong differences between basins. The effect of this precipitation uncertainty on mean annual and seasonal discharge was assessed using the uncalibrated dynamic global vegetation and hydrology model Lund-Potsdam-Jena managed land (LPJmL), yielding even larger uncertainties in discharge (average 90%). For 95 basins (out of 213 basins for which measurements were available) calibration of model parameters is problematic because the observed discharge falls within the uncertainty of the simulated discharge. A method is presented to account for precipitation uncertainty in discharge simulations