Carboxylic monoacids in the air of mayombe forest (Congo): Role of the forest as a source or sink

In the tropical rain forests of the Congo during the dry season, from June to September 1987, carboxylic acid partial pressures (P _gas) in the air above the canopy, at ground level, and at the boundary layer, were estimated from water samples such as fog and rainwater. The concentrations of these acids were also measured in the sap of tree leaves. Tree leaves act as a sink or as a source if the acid P _gas is greater of lower than the acid concentrations in molecular form in sap. For each of these soluble gases, there is a value of P _gas where the exchange is nul. This is called the compensation point. Values of the compensation point for some tree leaves were evaluated according to Henry's law. Henry's law coefficients at ppm levels were redetermined for formic (HCOOH), acetic (CH₃COOH), propionic (CH₃CH₂COOH), and isobutyric (CH₃CH(CH₃)COOH) acids.By comparison of P _gas and compensation points, it is concluded that the forest was a potential source for these acids. The soil-or the litter-acts as a significant source of a carboxylic acid of C₃ or C₄ atoms in the aliphatic chain. This carboxylic acid, not yet fully characterized, could play an important role in the rain acidity in forested zones of the equatorial areas.The direct emission of these carboxylic acids by vegetation was the main source in the boundary layer above the forest. The average emissions were 3.1×10⁹, 7.8×10⁹, and 8.4×10⁹ molecules cm^-2 s^-1 for HCOOH, CH₃COOH, and CH₃CH₂COOH, respectively. The savanna is an exogenous source of HCOOH and CH₃CH₂COOH during moderately rainy days for 30% of the time. The ozonolysis of isoprene seems to be a small source of HCOOH.     

Nitrous oxide emissions from gasohol, ethanol and CNG light duty vehicles

A sample of 21 light duty vehicles powered by Otto cycle engines were tested on a chassis dynamometer to measure the exhaust emissions of nitrous oxide (N₂O). The tests were performed at the Vehicle Emission Laboratory of CETESB (Environmental Company of the State of Sao Paulo) using the US-FTP-75 (Federal Test Procedure) driving cycle. The sample tested included passenger cars running on three types of fuels used in Brazil: gasohol, ethanol and CNG. The measurement of N₂O was made using two methods: Non Dispersive InfraRed (NDIR) analyzer and Fourier Transform InfraRed spectroscopy (FTIR). Measurements of regulated pollutants were also made in order to establish correlations between N₂O and NO_x. The average N₂O emission factors obtained by the NDIR method was 78?±?41?mg.km^?1 for vehicles running with gasohol, 73?±?45?mg.km^?1 for ethanol vehicles and 171?±?69?mg.km^?1 for CNG vehicles. Seventeen results using the FTIR method were also obtained. For gasohol vehicles the results showed a good agreement between the two methods, with an average emission factor of 68?±?41?mg.km^?1. The FTIR measurement results of N₂O for ethanol and CNG vehicles were much lower than those obtained by the NDIR method. The emission factors were 17?±?10?mg.km^?1 and 33?±?17?mg.km^?1, respectively, possibly because of the interference of water vapor (present at a higher concentration in the exhaust gases of these vehicles) on measurements by the NDIR method.     

Lake ice phenology in Berlin-Brandenburg from 1947–2007: observations and model hindcasts

Rising northern hemispheric mean air temperatures reduce the amount of winter lake ice. These changes in lake ice cover must be understood in terms of resulting effects on lake ecosystems. Accurate predictions of lake ice phenology are essential to assess resulting impact. We applied the one-dimensional physical lake model FLake to analyse past variability in ice cover timing, intensity and duration of Berlin-Brandenburg lakes. The observed ice phenology in two lakes in the period 1961–2007 was reconstructed by FLake reasonably well and with higher accuracy than by state-of-the-art linear regression models. Additional modelling results of FLake for 38 Berlin-Brandenburg lakes, observed in the winter of 2008/09, were quite satisfactory and adequately reproduced the effects of varying lake morphology and trophic state. Observations and model results showed that deeper and clearer lakes had more ice-free winters, later ice cover freezing and earlier ice cover thawing dates, resulting in shorter ice-covered periods and fewer ice-covered days than shallow and less clear lakes. The 1947–2007 model hindcasts were implemented using FLake for eight Berlin-Brandenburg lakes without ice phenology observations. Results demonstrated past trends of later ice start and earlier ice end, shorter ice cover duration and an increase in ice-free winters.     

Determination of surface layer parameters at the edge of a suburban area

Vertical wind and air temperature profile related parameters in the surface layer at the edge of suburban area of Zagreb (Croatia) have been considered. For that purpose, adopted Monin–Obukhov similarity theory and a set of observations of wind and air temperature at 2 and 10?m above ground, recorded in 2005, have been used. The root mean square differences (errors) principle has been used as a tool to estimate the effective roughness length as well as standard deviations of wind speed and wind gusts. The results of estimation are effective roughness lengths dependent on eight wind direction sectors unknown before. Gratefully to that achievement, representativeness of wind data at standard 10-m height can be clarified more deeply for an area of at least about 1?km in upwind direction from the observation site. Extrapolation of wind data for lower or higher levels from standard 10-m height are thus properly representative for a wider inhomogeneous suburban area and can be used as such in numerical models, flux and wind energy estimation, civil engineering, air pollution and climatological applications.     

Performance of ENSEMBLES regional climate models over Central Europe using various metrics

We show the evaluation of ENSEMBLES regional climate models (RCMs) driven by reanalysis ERA40 over a region centered at the Czech Republic. Attention is paid especially to the model ALADIN-CLIMATE/CZ, being used as the basis of the new climate change scenarios simulation for the Czech Republic. The validation criteria used here are based on monthly or seasonal mean air temperature and precipitation. We concentrate not only on spatiotemporal mean values but also on temporal standard deviation, inter-annual variability, the mean annual cycle, and the skill of the models to represent the observed spatial patterns of these quantities. Model ALADIN-CLIMATE/CZ performs quite well in comparison to the other RCMs; we find its performance satisfactory for further use for impact studies. However, it is also shown that the results of evaluation of the RCMs’ skill in simulating observed climate strongly depend on the criteria incorporated for the evaluation.     

Estimation of relative humidity based on artificial neural network approach in the Aegean Region of Turkey

The aim of this study is to estimate the monthly mean relative humidity (MRH) values in the Aegean Region of Turkey with the help of the topographical and meteorological parameters based on artificial neural network (ANN) approach. The monthly MRH values were calculated from the measurement in the meteorological observing stations established in Izmir, Mugla, Aydin, Denizli, Usak, Manisa, Kutahya and Afyonkarahisar provinces between 2000 and 2006. Latitude, longitude, altitude, precipitation and months of the year were used in the input layer of the ANN network, while the MRH was used in output layer of the network. The ANN model was developed using MATLAB software, and then actual values were compared with those obtained by ANN and multi-linear regression methods. It seemed that the obtained values were in the acceptable error limits. It is concluded that the determination of relative humidity values is possible at any target point of the region where the measurement cannot be performed.     

Some evidence on European monsoon existence

Large-scale European atmospheric circulation induced by temperature differences between the continent and the North Atlantic Ocean causes thermodynamic and climatic conditions that initiate a European monsoon. In Eastern Europe, the rainy season occurs in early summer, and the dry season occurs in winter. In Western Europe, the rainy season is in the early winter and the dry season is in the spring. This precipitation trend, as well as other climatic features, suggests the existence of a European monsoon.     

Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data

Extreme weather conditions can strongly affect agricultural production, with negative impacts that can at times be detected at regional scales. In France, crop yields were greatly influenced by drought and heat stress in 2003 and by extremely wet conditions in 2007. Reported regional maize and wheat yields where historically low in 2003; in 2007 wheat yields were lower and maize yields higher than long-term averages. An analysis with a spatial version (10?×?10?km) of the EPIC crop model was tested with regards to regional crop yield anomalies of wheat and maize resulting from extreme weather events in France in 2003 and 2007, by comparing simulated results against reported regional crops statistics, as well as using remotely sensed soil moisture data. Causal relations between soil moisture and crop yields were specifically analyzed. Remotely sensed (AMSR-E) JJA soil moisture correlated significantly with reported regional crop yield for 2002–2007. The spatial correlation between JJA soil moisture and wheat yield anomalies was positive in dry 2003 and negative in wet 2007. Biweekly soil moisture data correlated positively with wheat yield anomalies from the first half of June until the second half of July in 2003. In 2007, the relation was negative the first half of June until the second half of August. EPIC reproduced observed soil dynamics well, and it reproduced the negative wheat and maize yield anomalies of the 2003 heat wave and drought, as well as the positive maize yield anomalies in wet 2007. However, it did not reproduce the negative wheat yield anomalies due to excessive rains and wetness in 2007. Results indicated that EPIC, in line with other crop models widely used at regional level in climate change studies, is capable of capturing the negative impacts of droughts on crop yields, while it fails to reproduce negative impacts of heavy rain and excessively wet conditions on wheat yield, due to poor representations of critical factors affecting plant growth and management. Given that extreme weather events are expected to increase in frequency and perhaps severity in coming decades, improved model representation of crop damage due to extreme events is warranted in order to better quantify future climate change impacts and inform appropriate adaptation responses.