Detection and quantification of local anthropogenic and regional climatic transient signals in temperature logs from Czechia and Slovenia

The paper reports on detection and quantification of the impact of local anthropogenic structures and regional climatic changes on subsurface temperature field. The analyzed temperature records were obtained by temperature monitoring in a borehole in Prague-Spo?ilov (Czechia) and by repeated logging of a borehole in ?empeter (Slovenia). The observed data were compared with temperatures yielded by mathematical 3D time-variable geothermal models of the boreholes’ sites with the aim to decompose the observed transient component of the subsurface temperature into the part affected by construction of new buildings and other anthropogenic structures in surroundings of the boreholes and into the part affected by the ground surface temperature warming due to the surface air temperature rise. A direct human impact on the subsurface temperature warming was proved and contributions of individual anthropogenic structures to this change were evaluated. In the case of Spo?ilov, where the mean annual warming rate reached 0.034°C per year at the depth of 38.3?m during the period 1993–2008, it turned out that about half of the observed warming can be attributed to the air (ground) surface temperature change and half to the human activity on the surface in the immediate vicinity of the borehole. The situation is similar in ?empeter, where the effect of the recently built surface anthropogenic structures is detectable down to the depth of 80?m and the share of the anthropogenic signal on the non-stationary component of the observed subsurface temperature amounts to 30% at the depth of 50?m.     

Numerical simulation of the diurnal cycle of rainfall in SW Amazon basin during the 1999 rainy season: the role of convective trigger function

In continental areas, the maximum rainfall simulated with the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) occurs around 4?h earlier than the one observed with rain gauges. This work presents the successful implementation of a new convective trigger function (CTF) in the convective parameterization scheme used in BRAMS that corrects this misfit between model and observations. The importance of the CTF formulation on the diurnal cycle of rainfall over the Amazon Basin is reflected by the following numbers: Over Rondonia (SW Amazonia), the original version of BRAMS simulates the maximum rainfall at 1400 UTC (1000 LST), with the new CTF maximum shifting to 1800?UTC (1400?LST), while the S-band radar rainfall maximum is at 1900?UTC (1500?LST). This is attributed to two factors: (1) the new CTF is now coupled to the sensible and latent heat fluxes at surface; (2) during the early morning, the convective available potential energy is reduced.     

Methodology for the combination of sub-daily Earth rotation from GPS and VLBI observations

A combination procedure of Earth orientation parameters from Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) observations was developed on the basis of homogeneous normal equation systems. The emphasis and purpose of the combination was the determination of sub-daily polar motion (PM) and universal time (UT1) for a long time-span of 13 years. Time series with an hourly resolution and a model for tidal variations of PM and UT1-TAI (dUT1) were estimated. In both cases, 14-day nutation corrections were estimated simultaneously with the ERPs. Due to the combination procedure, it was warranted that the strengths of both techniques were preserved. At the same time, only a minimum of de-correlating or stabilizing constraints were necessary. Hereby, a PM time series was determined, whose precision is mainly dominated by GPS observations. However, this setup benefits from the fact that VLBI delivered nutation and dUT1 estimates at the same time. An even bigger enhancement can be seen for the dUT1 estimation, where the high-frequency variations are provided by GPS, while the long term trend is defined by VLBI. The estimated combined tidal PM and dUT1 model was predominantly determined from the GPS observations. Overall, the combined tidal model for the first time completely comprises the geometrical benefits of VLBI and GPS observations. In terms of root mean squared (RMS) differences, the tidal amplitudes agree with other empirical single-technique tidal models below 4 μas in PM and 0.25 μs in dUT1. The noise floor of the tidal ERP model was investigated in three ways resulting in about 1 μas for diurnal PM and 0.07 μs for diurnal dUT1 while the semi-diurnal components have a slightly better accuracy.     

Rainfall trends in the Brazilian Amazon Basin in the past eight decades

Rainfall series at 18 stations along the major rivers of the Brazilian Amazon Basin, having data since 1920s or 1930s, are analyzed to verify if there are appreciable long-term trends. Annual, rainy-season, and dry-season rainfalls are individually analyzed for each station and for the region as a whole. Some stations showed positive trends and some negative trends. The trends in the annual rainfall are significant at only six stations, five of which reporting increasing trends (Barcelos, Belem, Manaus, Rio Branco, and Soure stations) and just one (Itaituba station) reporting decreasing trend. The climatological values of rainfall before and after 1970 show significant differences at six stations (Barcelos, Belem, Benjamin Constant, Iaurete, Itaituba, and Soure). The region as a whole shows an insignificant and weak downward trend; therefore, we cannot affirm that the rainfall in the Brazilian Amazon basin is experiencing a significant change, except at a few individual stations. Subregions with upward and downward trends are interspersed in space from the far eastern Amazon to western Amazon. Most of the seasonal trends follow the annual trends, thus, indicating a certain consistency in the datasets and analysis.     

Evaporation estimates from Nasser Lake, Egypt, based on three floating station data and Bowen ratio energy budget

Nasser Lake is located in a hyper-arid region in the south of Egypt. Evaporation is by far the most important factor in explaining the water losses from the lake. To obtain better management scenarios for Nasser Lake, an accurate estimation of the lake evaporation losses thus is essential. This paper presents an update of previous evaporation estimates, making use of local meteorological and hydrological data collected from instrumented platforms (floating weather stations) at three locations on the lake: at Raft, Allaqi, and Abusembel (respectively at 2, 75, and 280 km upstream of the Aswan High Dam). Results from six conventional evaporation quantification methods were compared with the values obtained by the Bowen ratio energy budget method (BREB). The results of the BREB method showed that there is no significant difference between the evaporation rates at Allaqi and Abusembel. At Raft, higher evaporation rates were obtained, which were assumed to be overestimated due to the high uncertainty of the Bowen ratio (BR) parameter. The average BR value at Allaqi and Abusembel was used to eliminate this overestimates evaporation. Variance-based sensitivity and uncertainty analyses on the BREB results were conducted based on quasi-Monte Carlo sequences (Latin Hypercube sampling). The standard deviation of the total uncertainty on the BREB evaporation rate was found to be 0.62 mm day^?1. The parameter controlling the change in stored energy, followed by the BR parameter, was found to be the most sensitive parameters. Several of the six conventional methods showed substantial bias when compared with the BREB method. These were modified to eliminate the bias. When compared to the BREB-based values, the Penman method showed most favorably for the daily time scale, while for the monthly scale, the Priestley–Taylor and the deBruin–Keijman methods showed best agreement. Differences in mean evaporation estimates of these methods (against the BREB method) were found to be in the range 0.14 and 0.36 mm day^?1. All estimates were based calculations at the daily time scale covering a 10-year period (1995–2004).     

Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil

The objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box–Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state.     

Chemical characterization of fine particulate matter during peak PM10 episodes in Apulia (South Italy)

Some peak PM10 episodes, occurred during PM monitoring campaigns performed on October 2005 and February and June 2006 in Bari town, have been characterized. Moreover back trajectories of air masses and Principal Component Analyses were applied. Three of the peak PM10 episodes investigated were related to local emissions of primary pollutants during poor atmospheric dispersion conditions. The other two peak PM10 episodes considered are related with long range transport air masses toward Apulia region: in one case the chemical characterization and the back trajectories analysis indicate that high PM10 value detected is due to the Saharan dust advection in the Apulia region; in the other case air masses with different origin give rise to high PM10 value.Moreover PM10 daily mean concentrations, presented in this paper collected from January 2005 to August 2007 and obtained by automatic device in six stations of air quality monitoring networks in Bari territory, do not show a seasonal trend for PM10 concentrations, contrary to the PM10 trend shown in the towns of North Italy. This can be explained mostly considering that our region presents generally meteo-climatic conditions that favour pollutants dispersion.     

Rural household demographics, livelihoods and the environment

This paper reviews and synthesizes findings from scholarly work on linkages among rural household demographics, livelihoods and the environment. Using the livelihood approach as an organizing framework, we examine evidence on the multiple pathways linking environmental variables and the following demographic variables: fertility, migration, morbidity and mortality, and lifecycles. Although the review draws on studies from the entire developing world, we find the majority of microlevel studies have been conducted in either marginal (mountainous or arid) or frontier environments, especially Amazonia. Though the linkages are mediated by many complex and often context-specific factors, there is strong evidence that dependence on natural resources intensifies when households lose human and social capital through adult morbidity and mortality, and qualified evidence for the influence of environmental factors on household decision-making regarding fertility and migration. Two decades of research on lifecycles and land cover change at the farm level have yielded a number of insights about how households make use of different land-use and natural resource management strategies at different stages. A thread running throughout the review is the importance of managing risk through livelihood diversification, ensuring future income security, and culture-specific norms regarding appropriate and desirable activities and demographic responses. Recommendations for future research are provided.     

Investigation of regional climate models’ internal variability with a ten-member ensemble of 10-year simulations over a large domain

Previous investigations on regional climate models’ (RCM) internal variability (IV) were limited owing to small ensembles, short simulations and small domains. The present work extends previous studies with a ten-member ensemble of 10-year simulations performed with the Canadian Regional Climate Model over a large domain covering North America. The results show that the IV has no long-term tendency but rather fluctuates in time following the synoptic situation within the domain. The IV of mean-sea-level pressure (MSLP) and screen temperature (ST) show a small annual cycle with larger values in spring, which differs from previous studies. For precipitation (PCP), the IV shows a clear annual cycle with larger values in summer, as previously reported. The 10-year climatology of the IV for MSLP and ST shows a well-defined spatial distribution with larger values in the northeast of the domain, near the outflow boundary. A comparison of the IV of MSLP and ST in summer with the transient-eddy variance reveals that the IV is close to its maximum in a small region near the outflow boundary. Same analysis for PCP in summer shows that the IV reaches its maximum in most parts of the domain, except for a small region on the western side near the inflow boundary. Finally, a comparison of the 10-year climate of each simulation of the ensemble showed that the IV may have a significant impact on the climatology of some variables.     

Conditional probabilistic estimates of 21st century greenhouse gas emissions based on the storylines of the IPCC-SRES scenarios

The conditional probabilistic scenario analysis combines statistical methods of uncertainty analysis at parameter level with storylines which recognize the deep uncertainty that exists for several underlying trends. The model calculations indicate that cumulative 21st century emissions could range from 800 to 2500 GtC in the absence of climate policy. This range originates partly from the underlying storylines, and partly from the probabilistic analysis. Among the most important parameters contributing to the uncertainty range are uncertainty in income growth, population growth, parameters determining energy demand, oil resources and fuel preferences. The contribution of these factors is also scenario-dependent.