Retrieval of effective cloud field parameters from radiometric data

Theoretical and Applied Climatology - This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully...     

What Ångström—Prescott equation tells us about the cloud and clear-sky climatologies?

Theoretical and Applied Climatology - The Ångström–Prescott equation defines generically the relationship between solar energy available at ground level and sunshine duration. From...     

Spectral band decomposition combined with nonlinear models: application to indoor formaldehyde concentration forecasting

This paper proposes a new approach for forecasting continuous indoor air quality time series and in particular the concentration of a common air pollutant in offices like formaldehyde. Forecasting is achieved through the combination of the spectral band decomposition using fast Fourier transform and nonlinear time series modeling. Two nonlinear models have been tested: a threshold autoregressive (TAR) model and a Chaos dynamics-based modeling. This study shows the benefit of the Fourier decomposition coupled with nonlinear modeling of each extracted component, compared to forecasting applied directly on the raw data. Both TAR and Chaos dynamics models are able to reproduce nonlinearities, with slightly better performance in the case of the second model. These hybrid models provide good performance on forecast time horizon up to 12 h ahead.     

Sub-brown dwarfs as seats of life based on non-polar solvents: Thermodynamic restrictions

Sub-brown dwarfs (SBD) might originate either around a star or in solitary fashion. These bodies can retain atmospheres composed of molecular gases, which, upon cooling, have basal pressures of tens of bars or more. Pressure-induced opacity of these gases prevents such a body from eliminating its internal radioactive heat and its surface temperature can exceed the melting point of the life-supporting solvent for an extended period of time. Earth life uses water as a solvent but synthesis of observational data makes it possible to conceive chemical reactions that might support life involving non-carbon compounds, occurring in solvents other than water. In this paper a non-polar solvent is considered: ethane. Thermodynamic requirements to be fulfilled by a hypothetic gas constituent of a life-supporting SBD atmosphere are studied. Three gases are analyzed: nitrogen, carbon dioxide and methane. For thermodynamic reasons carbon dioxide is excluded from the list of candidate gases. We show that bodies with ethane oceans are possible in interstellar space. This may happen on SBD of (significantly) smaller or larger mass than the Earth. Generally, in case of SBD smaller in size than the Earth, the atmosphere exhibits a convective layer near the surface and a radiative layer at higher altitudes while the atmosphere of SBDs larger in size than Earth does not exhibit a convective layer. The prescribed thermodynamic state of ethane on the surface has some influence on the features of the atmosphere. The atmospheric mass of a life-hosting SBD of Earth size is two or three orders of magnitude larger than the mass of Earth atmosphere.     

The Hormuz Strait Dam Macroproject—21st Century Electricity Development Infrastructure Node (EDIN)?

Ocean gulfs offer a means of artificially creating a depression, which can be used for a regionally significant hydroelectric macroproject. We examine here the case for a dam at the Strait of Hormuz that blocks a large gulf situated in an arid region. A 35 m evaporation of this concentration basin will reduce its watery surface area by ∼53% and allow generation of ∼2.050 MW (or possibly ∼2.500 MW) of electricity. Our conclusion is that the proposed Electricity Development Infrastructure Node (EDIN) is a feasible and desirable macroproject. If the macroproject starts in the near-term future, it would require a significant change in the logistics of oil and gas transport from this region. Alternatively, it can be considered as an attractive future solution for the energy requirements of the region after exhaustion of its oil and gas reserves.     

Accuracy of CM-SAF solar irradiance incident on horizontal surface

The Climate Monitoring Satellite Application Facility (CM-SAF) provides estimates of global solar irradiance incident on horizontal surface at Earth surface. Measurements performed in 2010 at five Romanian meteorological stations are used to test the accuracy of the CM-SAF irradiance data. The dataset contains null solar global irradiance values, which cannot be explained by very large values of the zenith angle neither by overcast sky conditions. Sub-databases have been created. The database Z85 consists of irradiance data, without filtering and processing. The database Z85SIS+ remove all null irradiance values. For a given database, the root mean square error (RMSE) with respect to the ground-based measurements is rather similar for all stations, i.e. around 35 % for Z85 and 24 % for Z85SIS+. On average, the database Z85SIS+ has smaller mean bias error (MBE) than the database Z85, independent of the degree of cloudiness. For the database Z85, MBE (RMSE) ranges, depending on station, between ?9.4 and ?1.2 % (35.3 and 39.1 %). For database Z85SIS+, the MBE (RMSE) ranges, depending on station, between ?4.0 and 0.1 % (23.0 and 29.1 %). On overcast sky, we found for some stations MBE?=??0.1 % and RMSE?=?46.4 % when the database Z85SIS+ has been considered. The accuracy of the database Z85 is lower; we found MBE?=??7.0 % and RMSE?=?58.8 % as extreme cases.     

Nowcasting sunshine number using logistic modeling

In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127–136, 2002). Our statistical approach is based on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different frequencies and with a short discussion of technical problems that such a goal brings.