Evaluation of methods of spatial interpolation for monthly rainfall data over the state of Rio de Janeiro,Brazil

Five deterministic methods of spatial interpolation of monthly rainfall were compared over the state of Rio de Janeiro, southeast Brazil. The methods were the inverse distance weight (IDW), nearest neighbor (NRN), triangulation with linear interpolation (TLI), natural neighbor (NN), and spline tension (SPT). A set of 110 weather stations was used to test the methods. The selection of stations had two criteria: time series longer than 20 years and period of data from 1960 to 2009. The methods were evaluated using cross-validation, linear regression between values observed and interpolated, root mean square error (RMSE), coefficient of determination (r ²), coefficient of variation (CV, %), and the Willmott index of agreement (d). The results from different methods are influenced by the meteorological systems and their seasonality, as well as by the interaction with the topography. The methods presented higher precision (r ²) and accuracy (d, RMSE) during the summer and transition to autumn, in comparison with the winter or spring months. The SPT had the highest precision and accuracy in relation to other methods, in addition to having a good representation of the spatial patterns expected for rainfall over the complex terrain of the state and its high spatial variability.     

Estimation of Surface-Layer Scaling Parameters in the Unstable Boundary Layer: Implications for Orographic Flow Speed-Up

A method is proposed for estimating the surface-layer depth \((z_s)\) and the friction velocity \((u_*)\) as a function of stability (here quantified by the Obukhov length, L) over the complete range of unstable flow regimes. This method extends that developed previously for stable conditions by Argaín et al. (Boundary-Layer Meteorol 130:15–28, 2009), but uses a qualitatively different approach. The method is specifically used to calculate the fractional speed-up \((\varDelta S)\) in flow over a ridge, although it is suitable for more general boundary-layer applications. The behaviour of \(z_s \left( L\right) \) and \(u_*\left( L\right) \) as a function of L is indirectly assessed via calculation of \(\varDelta S\left( L\right) \) using the linear model of Hunt et al. (Q J R Meteorol Soc 29:16–26, 1988) and its comparison with the field measurements reported in Coppin et al. (Boundary-Layer Meteorol 69:173–199, 1994) and with numerical simulations carried out using a non-linear numerical model, FLEX. The behaviour of \(\varDelta S\) estimated from the linear model is clearly improved when \(u_*\) is calculated using the method proposed here, confirming the importance of accounting for the dependences of \(z_s\left( L \right) \) and \(u_*\left( L \right) \) on L to better represent processes in the unstable boundary layer.     

The economics of boldness: equity,action, and hope

Equity is usually interpreted in terms of the concept of justice, such that an equitable share of the atmospheric space is understood in terms of past emissions. This emphasizes the collective nature of sharing the burden of mitigation and the duty to act for those who have emitted the most. An alternative is considered: the aggregate costs and benefits to all Parties that could result from both increasing the level of collective ambition and implementing a climate regime that supports bold actions across all Parties. The regional impacts and carbon flow costs across differentiated scenarios are assessed and it is argued that the majority of developing-country Parties would be better off if a high ambition outcome to which all contributed, but some more than others. Moreover, those with middle or low emissions would have proportionally more to gain (or lose) relative to the level of ambition compared to those that have had higher emissions. The climate regime should be built on the principle of common but differentiated responsibility and respective capabilities (CBDR&RC), in which all act early even if some do much more; one that accounts for justice but does not forget hope.

Policy relevance

Differing interpretations of equity and the principles of the United Nations Framework Convention on Climate Change (UNFCCC) are discussed, with a focus on how these can enhance or hinder collective action. Whilst the climate change negotiations are usually taken as games in which one party gains and another loses, and interactions are dogged by continuous conflict, it is explored instead how negotiation responses can be framed in terms of cooperation. This would emphasize the gains that could be achieved by common but differentiated collective action, which could result in a collective avoidance of impacts. The possibilities that this shift of perspective could bring are explored by comparing costs under global cooperation (or lack of it). It is found that cooperation reduces the total costs for these regions. Thus, thinking in terms of cooperation focuses the options for negotiation on the means and interpretations of the UNFCCC principles that spur action and avoid climate impacts through collective action.     

Investment risk and return under renewable decarbonization of a power market

How does financial performance risk affect investments in low-carbon electricity-generating technologies to achieve climate policy targets? A detailed risk simulation of price formation in the Great Britain wholesale power market is used to show that the increasing replacement of fossil facilities with wind, ceteris paribus, may cause a deterioration of the financial risk–return performance metrics for incremental investments. Low-carbon investments appear to be high risk, low return, and as such may require a progressively higher level of support over time than envisaged by the conventional degression trajectories. The increasing riskiness of the wholesale market will to some extent offset the benefits of lower capital costs and operational efficiencies if investors need to satisfy cautious debt coverage ratios alongside positive expected returns. This increased risk is additional to the well-known ‘merit order effect’ of low-carbon investments progressively depressing wholesale prices and hence their expected investment returns.

Policy relevance

Policy support for renewable technologies such as wind is usually based upon levelized costs and is expected to reduce over time as capital costs and operational efficiencies improve. However, levelized costs do not take full account of the risk aversion that investors may have in practice. Expected policy support reductions may be moderated to some extent by the increased financial performance risk that intermittent technologies bring to the power market. The annual risk-return profiles for incremental investments deteriorate for all technologies as wind replaces fossil fuels. This extra risk premium will need to be incorporated into evaluating policy incentives for new investments in a decarbonizing power market.     

Modeling monthly mean air temperature for Brazil

Air temperature is one of the main weather variables influencing agriculture around the world. Its availability, however, is a concern, mainly in Brazil where the weather stations are more concentrated on the coastal regions of the country. Therefore, the present study had as an objective to develop models for estimating monthly and annual mean air temperature for the Brazilian territory using multiple regression and geographic information system techniques. Temperature data from 2,400 stations distributed across the Brazilian territory were used, 1,800 to develop the equations and 600 for validating them, as well as their geographical coordinates and altitude as independent variables for the models. A total of 39 models were developed, relating the dependent variables maximum, mean, and minimum air temperatures (monthly and annual) to the independent variables latitude, longitude, altitude, and their combinations. All regression models were statistically significant (α?≤?0.01). The monthly and annual temperature models presented determination coefficients between 0.54 and 0.96. We obtained an overall spatial correlation higher than 0.9 between the models proposed and the 16 major models already published for some Brazilian regions, considering a total of 3.67?×?10⁸?pixels evaluated. Our national temperature models are recommended to predict air temperature in all Brazilian territories.     

The impacts of a plume-rise scheme on earth system modeling: climatological effects of biomass aerosols on the surface temperature and energy budget of South America

Theoretical and Applied Climatology - Seasonal forest fires in the Amazon are the largest source of pollutants in South America. The impacts of aerosols due to biomass burning on the temperature...     

On the consistency of the current conventional EOP series and the celestial and terrestrial reference frames

Precise transformation between the celestial reference frames (CRF) and terrestrial reference frames (TRF) is needed for many purposes in Earth and space sciences. According to the Global Geodetic Observing System (GGOS) recommendations, the accuracy of positions and stability of reference frames should reach 1 mm and 0.1 mm year\(^{-1}\), and thus, the Earth Orientation Parameters (EOP) should be estimated with similar accuracy. Different realizations of TRFs, based on the combination of solutions from four different space geodetic techniques, and CRFs, based on a single technique only (VLBI, Very Long Baseline Interferometry), might cause a slow degradation of the consistency among EOP, CRFs, and TRFs (e.g., because of differences in geometry, orientation and scale) and a misalignment of the current conventional EOP series, IERS 08 C04. We empirically assess the consistency among the conventional reference frames and EOP by analyzing the record of VLBI sessions since 1990 with varied settings to reflect the impact of changing frames or other processing strategies on the EOP estimates. Our tests show that the EOP estimates are insensitive to CRF changes, but sensitive to TRF variations and unmodeled geophysical signals at the GGOS level. The differences between the conventional IERS 08 C04 and other EOP series computed with distinct TRF settings exhibit biases and even non-negligible trends in the cases where no differential rotations should appear, e.g., a drift of about 20 \(\upmu \)as year\(^{-1 }\)in \(y_{\mathrm{pol }}\) when the VLBI-only frame VTRF2008 is used. Likewise, different strategies on station position modeling originate scatters larger than 150 \(\upmu \)as in the terrestrial pole coordinates.     

Revisit the calibration errors on experimental slant total electron content (TEC) determined with GPS

The calibration errors on experimental slant total electron content (TEC) determined with global positioning system (GPS) observations is revisited. Instead of the analysis of the calibration errors on the carrier phase leveled to code ionospheric observable, we focus on the accuracy analysis of the undifferenced ambiguity-fixed carrier phase ionospheric observable determined from a global distribution of permanent receivers. The results achieved are: (1) using data from an entire month within the last solar cycle maximum, the undifferenced ambiguity-fixed carrier phase ionospheric observable is found to be over one order of magnitude more accurate than the carrier phase leveled to code ionospheric observable and the raw code ionospheric observable. The observation error of the undifferenced ambiguity-fixed carrier phase ionospheric observable ranges from 0.05 to 0.11 total electron content unit (TECU) while that of the carrier phase leveled to code and the raw code ionospheric observable is from 0.65 to 1.65 and 3.14 to 7.48 TECU, respectively. (2) The time-varying receiver differential code bias (DCB), which presents clear day boundary discontinuity and intra-day variability pattern, contributes the most part of the observation error. This contribution is assessed by the short-term stability of the between-receiver DCB, which ranges from 0.06 to 0.17 TECU in a single day. (3) The remaining part of the observation errors presents a sidereal time cycle pattern, indicating the effects of the multipath. Further, the magnitude of the remaining part implies that the code multipath effects are much reduced. (4) The intra-day variation of the between-receiver DCB of the collocated stations suggests that estimating DCBs as a daily constant can have a mis-modeling error of at least several tenths of 1 TECU.     

Efficient collection of training data for sub-pixel land cover classification using neural networks

Artificial neural networks (ANNs) are a popular class of techniques for performing soft classifications of satellite images. They have successfully been applied for estimating crop areas through sub-pixel classification of medium to low resolution images. Before a network can be used for classification and estimation, however, it has to be trained. The collection of the reference area fractions needed to train an ANN is often both time-consuming and expensive. This study focuses on strategies for decreasing the efforts needed to collect the necessary reference data, without compromising the accuracy of the resulting area estimates. Two aspects were studied: the spatial sampling scheme (i) and the possibility for reusing trained networks in multiple consecutive seasons (ii). Belgium was chosen as the study area because of the vast amount of reference data available. Time series of monthly NDVI composites for both SPOT-VGT and MODIS were used as the network inputs. The results showed that accurate regional crop area estimation (R² > 80%) is possible using only 1% of the entire area for network training, provided that the training samples used are representative for the land use variability present in the study area. Limiting the training samples to a specific subset of the population, either geographically or thematically, significantly decreased the accuracy of the estimates. The results also indicate that the use of ANNs trained with data from one season to estimate area fractions in another season is not to be recommended. The interannual variability observed in the endmembers’ spectral signatures underlines the importance of using up-to-date training samples. It can thus be concluded that the representativeness of the training samples, both regarding the spatial and the temporal aspects, is an important issue in crop area estimation using ANNs that should not easily be ignored.     

A New Method for Determining Compound Specific Carbon Isotope of Chlorinated Solvents in Porewater

A new method for the extraction of chlorinated solvents (CSs) from porewater with dimethylacetamide (DMA) used as a solvent and the determination of δ¹³C by gas chromatography-isotope ratio mass spectrometry (GC-IRMS) with solid-phase microextraction (SPME) are presented. This method was used for the determination of δ¹³C of chloroethenes and chloromethanes. The extraction of the CSs from porewater with DMA led to a minimal loss of mass of solvent and chlorinated compounds. The accuracy of the method was verified with the analysis of the pure injected compounds using elemental analyzer—isotope ratio mass spectrometry (EA-IRMS). It has been effectively applied in a study area in saturated soil samples of a pollutant source zone of perchloroethylene (PCE) and trichloroethylene (TCE). The limit of quantification of the new method was 0.034 μg/g for PCE and TCE for 10–20 g of soil sample. This new method allows for compound-specific isotope analysis of CSs in porewater, which can be beneficial in sites where the identification of contamination sources and the behavior of the contaminants are not clear.