ALBERT

Beschreibung: The influence of multiple spatio-temporal scales on the error growth and predictability of atmospheric flows is analyzed throughout the paper. To this aim, we consider the two-scale Lorenz'96 model and study the interplay of the slow and fast variables on the error growth dynamics. It is shown that when the coupling between slow and fast variables is weak the slow variables dominate the evolution of fluctuations whereas in the case of strong coupling the fast variables impose a non-trivial complex error growth pattern on the slow variables with two different regimes, before and after saturation of fast variables. This complex behavior is analyzed using the recently introduced Mean-Variance Logarithmic (MVL) diagram.

Beschreibung: We present a novel approach to characterize and graphically represent the spatiotemporal evolution of ensembles using a simple diagram. To this aim we analyze the fluctuations obtained as differences between each member of the ensemble and the control. The lognormal character of these fluctuations suggests a characterization in terms of the first two moments of the logarithmic transformed values. On one hand, the mean is associated with the exponential growth in time. On the other hand, the variance accounts for the spatial correlation and localization of fluctuations. In this paper we introduce the MVL (Mean-Variance of Logarithms) diagram to intuitively represent the interplay and evolution of these two quantities. We show that this diagram uncovers useful information about the spatiotemporal dynamics of the ensemble. Some universal features of the diagram are also described, associated either with the nonlinear system or with the ensemble method and illustrated using both toy models and numerical weather prediction systems.

Beschreibung: Most fire protection agencies throughout the world have developed forest fire risk forecast systems, usually building upon existing fire danger indices and meteorological forecast data. In this context, the daily predictability of wildfires is of utmost importance in order to allow the fire protection agencies to issue timely fire hazard alerts. In this study, we address the predictability of daily fire occurrence using the components of the Canadian Fire Weather Index (FWI) System and related variables calculated from the latest ECMWF (European Centre for Medium Range Weather Forecasts) reanalysis, ERA-Interim. We develop daily fire occurrence models in peninsular Spain for the period 1990–2008 and, considering different minimum burned area thresholds for fire definition, assess their ability to reproduce the inter-annual fire frequency variability. We based the analysis on a phytoclimatic classification aiming the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climate/fuel conditions. We then extend the analysis in order to assess the predictability of monthly burned areas. The sensitivity of the models to the level of spatial aggregation of the data is also evaluated. Additionally, we investigate the gain in model performance with the inclusion of socioeconomic and land use/land cover (LULC) covariates in model formulation. Fire occurrence models have attained good performance in most of the phytoclimatic zones considered, being able to faithfully reproduce the inter-annual variability of fire frequency. Total area burned has exhibited some dependence on the meteorological drivers, although model performance was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, highlighting the adequacy of the FWI system for fire occurrence prediction in the study area. The results were improved when using aggregated data across regions compared to when data were sampled at the grid-box level. The inclusion of socioeconomic and LULC covariates contributed marginally to the improvement of the models, and in most cases attained no relevant contribution to total explained variance – excepting northern Spain, where anthropogenic factors are known to be the major driver of fires. Models of monthly fire counts performed better in the case of fires larger than 0.1 ha, and for the rest of the thresholds (1, 10 and 100 ha) the daily occurrence models improved the predicted inter-annual variability, indicating the added value of daily models. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as a response variable. Our results leave the door open to the development a more complex modelling framework based on daily data from numerical climate model outputs based on the FWI system.

Beschreibung: We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990–2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter–annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.

Beschreibung: The study of extreme events has become of great interest in recent years due to their direct impact on society. Extremes are usually evaluated by using extreme indicators, based on order statistics on the tail of the probability distribution function (typically percentiles). In this study, we focus on the tail of the distribution of daily maximum and minimum temperatures. For this purpose, we analyse high (95th) and low (5th) percentiles in daily maximum and minimum temperatures on the Iberian Peninsula, respectively, derived from different downscaling methods (statistical and dynamical). First, we analyse the performance of reanalysis-driven downscaling methods in present climate conditions. The comparison among the different methods is performed in terms of the bias of seasonal percentiles, considering as observations the public gridded data sets E-OBS and Spain02, and obtaining an estimation of both the mean and spatial percentile errors. Secondly, we analyse the increments of future percentile projections under the SRES A1B scenario and compare them with those corresponding to the mean temperature, showing that their relative importance depends on the method, and stressing the need to consider an ensemble of methodologies.

Beschreibung: Wildfires are a major concern on the Iberian Peninsula, and the establishment of effective prevention and early warning systems are crucial to reduce impacts and losses. Fire weather indices are daily indicators of fire danger based upon meteorological information. However, their application in many studies is conditioned to the availability of sufficiently large climatological time series over extensive geographical areas and of sufficient quality. Furthermore, wind and relative humidity, important for the calculation of fire spread and fuel flammability parameters, are relatively scarce data. For these reasons, different reanalysis products are often used for the calculation of surrogate fire danger indices, although the agreement with those derived from observations remains as an open question to be addressed. In this study, we analyze this problem focusing on the Canadian Fire Weather Index (FWI) – and the associated Seasonal Severity Rating (SSR) – and considering three different reanalysis products of varying resolutions on the Iberian Peninsula: NCEP, ERA-40 and ERA-Interim. Besides the inter-comparison of the resulting FWI/SSR values, we also study their correspondence with observational data from 7 weather stations in Spain and their sensitivity to the input parameters (precipitation, temperature, relative humidity and wind velocity). As a general result, ERA-Interim reproduces the observed FWI magnitudes with better accuracy than NCEP, with lower/higher correlations in the coast/inland locations. For instance, ERA-Interim summer correlations are above 0.5 in inland locations – where higher FWI magnitudes are attained – whereas the corresponding values for NCEP are below this threshold. Nevertheless, departures from the observed distributions are generally found in all reanalysis, with a general tendency to underestimation, more pronounced in the case of NCEP. In spite of these limitations, ERA-Interim may still be useful for the identification of extreme fire danger events. (e.g. those above the 90th percentile value) and for the definition of danger levels/classes (with level thresholds adapted to the observed/reanalysis distributions).

Beschreibung: A reliable and up-to-date maritime emission inventory is essential for atmospheric scientists quantifying the impact of shipping. The objective of this study is to estimate the atmospheric emissions of SO2, NOx, CO2 and PM10 by international merchant shipping in 2007 in the Strait of Gibraltar, Spain, including the Algeciras Bay by two methods. Two methods (both bottom-up) have been used in this study: 1. Establishing engine power-based emission factors (g kWh−1, EPA) or the mass of pollutant per work performed by the engine for each of the relevant components of the exhaust gas from diesel engines and power for each ship. 2. Establishing fuel-based emission factors (kg emitted/t of fuel) or mass of pollutant per mass of combusted fuel for each of the relevant components of the exhaust gas and a fuel-consumption inventory (IMO). In both methods, the means to estimate engine power and fuel-consumption inventories are the same. The exhaust from boilers and incinerators is regarded as a small contributor and excluded. In total, an estimated average of 1 389 111.05 t of CO2, 23 083.09 t of SO2, 32 005.63 t of NOx and 2972 t of PM10 were emitted from January 2007 until December 2007 by international and domestic shipping. The estimated total fuel consumption amounts to 437 405.84 t. The major differences between the estimates generated by the two methods are for NOx (16% in certain cases) and CO (up to 23%). A total difference for all compounds of 3038 t (approximately 2%) has been found between the two methods but it is not areasonable estimate of uncertainty. Therefore, the results for both methods may be considered acceptable because the actual uncontrolled deviations appear in the changes in emission factors that occur for a given engine with age. These deviations are often difficult to quantify and depend on individual shipboard service and maintenance routines. Emission factors for CO and NOx are not constant and depend on engine condition. For example, tests conducted by the authors of this paper demonstrate that when an engine operates under normal in-service conditions, the emissions are within limits. However, with a small fault in injection timing, the NOx emission exceeds the limits (30% higher value in some cases). A fault in the maintenance of the injection nozzles increases the CO emission (15% higher value in some cases).

Beschreibung: This work presents a framework, WRF4G, to manage the experiment workflow of the Weather Research and Forecasting (WRF) modelling system. WRF4G provides a flexible design, execution and monitoring for a general class of scientific experiments. It has been designed with the aim of facilitating the management and reproducibility of complex experiments. Furthermore, the concepts behind the design of this framework can be straightforwardly extended to other models. We describe the user interface and the new concepts required to design parameter-sweep, hindcast and climate simulation experiments. A number of examples are provided, based on the design used for existing (published) WRF experiments. This software is open-source and publicly available http://www.meteo.unican.es/software/wrf4g).

Beschreibung: In the winter-rain southern Atacama Desert of the Coquimbo Region of Chile, El Niño - Southern Oscillation (ENSO) events modulate primary productivity. In this region, there are important changes in water availability between La Niña (dry) and El Niño (rainy) years. Using inter-annual comparisons of LANDSAT images from 30° to 31° S latitude, we observed changes in primary productivity between dry and rainy years at the regional level. There were also significant, negative correlations between productivity and elevation, with changes occurring first at low elevation during rainy years. The limiting factors to dryland vegetation primary productivity is different in regard to elevation. Rain during an El Niño year is the main factor that explains the increase in primary productivity at low elevation, while lower temperatures reduce and delay the net primary productivity at mid elevation.

Beschreibung: Fundamentally, El Niño Southern Oscillation (ENSO) is a climatic and oceanographic phenomenon, but it has profound effects on terrestrial ecosystems. Although the ecological effects of ENSO are becoming increasingly known from a wide range of terrestrial ecosystems (Holmgren et al., 2001), their impacts have been more intensively studied in arid and semiarid systems. In this brief communication, we summarize the main conclusions of a recent symposium on the effects of ENSO in these ecosystems, which was convened as part of the First Alexander von Humboldt International Conference on the El Niño Phenomenon and its Global Impact, in Guayaquil, Ecuador, from 16–20 May 2005. Participants in the symposium shared results and perspectives from research conducted in North and South America and Australia, regions where the ecological effects of ENSO have been studied in depth. Although the reports covered a wide array of organisms and ecological systems (Fig. 1), a recurring theme was the strong increase in rainfall associated with ENSO events in dry ecosystems (during the El Niño phase of the oscillation in the Americas and the La Niña phase in Australia). Because inter-annual variability in precipitation is such a strong determinant of productivity in arid and semiarid ecosystems, increased ENSO rainfall is crucial for plant recruitment, productivity and diversity in these ecosystems. Several long-term studies show that this pulse in primary productivity causes a subsequent increase in herbivores, followed by an increase in carnivores, with consequences for changes in ecosystem structure and functioning that can be quite complex.