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J. F. González-Rouco, H. Heyen, E. Zorita, and F. Valero

Abstract

The lowest spatial scale at which current climate models are considered to be skillful is on the order of 1000 km because of resolution and computer capabilities. The estimation of the regional changes caused by anthropogenic emissions of greenhouse gases and aerosols therefore is problematic. Here a statistical downscaling scheme is used to study the relationship between large-scale sea level pressure and regional precipitation in southwestern Europe, both in observed data and in outputs from a general circulation model (GCM) forced with increasing levels of greenhouse gases and sulfate aerosols. The results indicate that the GCM does reproduce the main aspects of the large- to local-scale coupled variability. Furthermore, these large- to local-scale relationships remain stable in the scenario simulations. The GCM runs predict increases of advection of oceanic air masses to the Iberian Peninsula that will produce a slight decrease of precipitation amounts in the north coast and the opposite effect in the rest of the territory, with values that could reach 10 mm decade−1 in the south. In the homogenized historical records, the obtained pattern of change is very similar. These results support estimations of future regional trends simulated by the GCM under future emission scenarios.

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J. C. Pérez, J. P. Díaz, A. González, J. Expósito, F. Rivera-López, and D. Taima

Abstract

The ability of the Weather Research and Forecasting (WRF) Model simulations to perform climate regionalization studies in an orographically complex region, the Canary Islands, is analyzed. Six different 5-yr simulations were carried out to investigate the sensitivity to several parameterization schemes and to uncertainties in sea surface temperature (SST). The simulated maximum and minimum temperatures, together with the daily rainfall, were compared with observational data. To take into account the climatic differences in this archipelago, observational sites were grouped using a geographical regionalization based on principal component analysis and a clustering technique to group the stations according to their climatic characteristics. The analysis showed that both the microphysics and the boundary layer schemes have a large impact on the simulated precipitation. However, the largest differences were observed when the cumulus parameterization, in the coarser domains, was changed. An analysis of the vertical profiles of the simulated hydrometeors was performed to study the differences revealed by the different simulations. Although the cumulus scheme was not applied in the innermost domain, the total amount of water available in the atmospheric column is modified. Moreover, an average increase of 0.7°C in SST, estimated from phase 5 of the Coupled Model Intercomparison Project (CMIP5) variability, produces changes of the same order as those those obtained with different parameterizations. Temperatures are similarly simulated by the different configurations, except for the case in which an SST increment was introduced. Two configurations (CTRL and LSM-PX) were able to correctly reproduce the studied variables in the Canary Islands, improving the Interim ECMWF Re-Analysis (ERA-Interim) data and showing their abilities for regional-scale climate studies in this archipelago.

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J. Fidel González-Rouco, J. Luis Jiménez, Vicente Quesada, and Francisco Valero

Abstract

A quality control process involving outliers processing, homogenization, and interpolation has been applied to 95 monthly precipitation series in the Iberian Peninsula, southern France, and northern Africa during the period 1899–1989. A detailed description of the procedure results is provided and the impact of adjustments on trend estimation is discussed.

Outliers have been censored by trimming extreme values. Homogeneity adjustments have been developed by applying the Standard Normal Homogeneity Test in combination with an objective methodology to select reference series.

The spatial distribution of outliers indicates that they are due to climate variability rather than measurement errors. After carrying out the homogeneity procedure, 40% of the series were found to be homogeneous, 49.5% became homogeneous after one adjustment, and 9.5% after two adjustments. About 30% of the inhomogeneities could be traced to information in the scarce history files.

It is shown that these data present severe homogeneity problems and that applying outliers and homogeneity adjustments greatly changes the patterns of trends for this area.

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P. A. Jiménez, E. García-Bustamante, J. F. González-Rouco, F. Valero, J. P. Montávez, and J. Navarro

Abstract

Daily wind variability in the Comunidad Foral de Navarra in northern Spain was studied using wind observations at 35 locations to derive subregions with homogeneous temporal variability. Two different methodologies based on principal component analysis were used to regionalize: 1) cluster analysis and 2) the rotation of the selected principal components. Both methodologies produce similar results and lead to regions that are in general agreement with the topographic features of the terrain. The meridional wind variability is similar in all subregions, whereas zonal wind variability is responsible for differences between them. The spectral analysis of wind variability within each subregion reveals a dominant annual cycle and the varying presence of higher-frequency contributions in the subregions. The valley subregions tend to present more variability at high frequencies than do higher-altitude sites. Last, the influence of large-scale dynamics on regional wind variability is explored by studying connections between wind in each subregion and sea level pressure fields. The results of this work contribute to the characterization of wind variability in a complex terrain region and constitute a framework for the validation of mesoscale model wind simulations over the region.

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Pedro A. Jimenez, Jordi Vila-Guerau de Arellano, Jorge Navarro, and J. Fidel Gonzalez-Rouco
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Etor E. Lucio-Eceiza, J. Fidel González-Rouco, Jorge Navarro, and Hugo Beltrami

Abstract

A quality control (QC) process has been developed and implemented on an observational database of surface wind speed and direction in northeastern North America. The database combines data from 526 land stations and buoys spread across eastern Canada and five adjacent northeastern U.S. states. It combines the observations of three different institutions spanning from 1953 to 2010. The quality of these initial data varies among source institutions. The current QC process is divided into two parts. Part I, described herein, is focused on issues related to data management: issues stemming from data transcription and collection; differences in measurement units and recording times; detection of sequences of duplicated data; unification of calm and true north criteria for wind direction; and detection of physically unrealistic data measurements. As a result, around ~0.1% of wind speed and wind direction records have been identified as erroneous and deleted. The most widespread error type is related to duplications within the same station, but the error type that entails more erroneous data belongs to duplications among different sites. Additionally, the process of data compilation and standardization has had an impact on more than 90% of the records. A companion paper (Part II) deals with a group of errors that are conceptually different, and is focused on detecting measurement errors that relate to temporal consistency and biases in wind speed and direction.

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Pedro A. Jiménez, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, and Elena García-Bustamante

Abstract

Meteorological data of good quality are important for understanding both global and regional climates. In this respect, great efforts have been made to evaluate temperature- and precipitation-related records. This study summarizes the evaluations made to date of the quality of wind speed and direction records acquired at 41 automated weather stations in the northeast of the Iberian Peninsula. Observations were acquired from 1992 to 2005 at a temporal resolution of 10 and 30 min. A quality assurance system was imposed to screen the records for 1) manipulation errors associated with storage and management of the data, 2) consistency limits to ensure that observations are within their natural limits of variation, and 3) temporal consistency to assess abnormally low/high variations in the individual time series. In addition, the most important biases of the dataset are analyzed and corrected wherever possible. A total of 1.8% wind speed and 3.7% wind direction records was assumed invalid, pointing to specific problems in wind measurement. The study not only tries to contribute to the science with the creation of a wind dataset of improved quality, but it also reports on potential errors that could be present in other wind datasets.

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Daniel E. Comarazamy, Jorge E. González, Jeffrey C. Luvall, Douglas L. Rickman, and Pedro J. Mulero

Abstract

This paper focuses on the surface–atmospheric interaction in a tropical coastal city including the validation of an atmospheric modeling and an impact study of land-cover and land-use (LCLU) changes. The Regional Atmospheric Modeling System (RAMS), driven with regional reanalysis data for a 10-day simulation, is used to perform the study in the San Juan metropolitan area (SJMA), one of the largest urban conglomerations in the Caribbean, which is located in the island of Puerto Rico and taken as the test case. The model’s surface characteristics were updated using airborne high-resolution remote sensing information to obtain a more accurate and detailed configuration of the SJMA. Surface and rawinsonde data from the San Juan Airborne Thermal and Land Applications Sensor (ATLAS) Mission are used to validate the modeling system, yielding satisfactory results in surface/canopy temperature, near-surface air temperatures, and vertical profiles. The impact analysis, performed with the updated SJMA configuration and a potential natural vegetation (PNV) scenario, showed that the simulation with specified urban LCLU indexes in the bottom boundary produced higher air temperatures over the area occupied by the city, with positive values of up to 2.5°C. The same analysis showed changes in the surface radiative balance in the urban case attributed to modifications in the LCLU. This additional heat seems to motivate additional vertical convection that may be leading to possible urban-induced precipitation downwind of the SJMA. This was evident in a precipitation disturbance when the city is present (∼0.9 mm, 22.5% increase) captured by the model that was accompanied by increases in cloud formation and vertical motions mainly downwind of the city.

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Etor E. Lucio-Eceiza, J. Fidel González-Rouco, Jorge Navarro, Hugo Beltrami, and Jorge Conte

Abstract

A quality control (QC) process has been developed and applied to an observational database of surface wind speed and wind direction in northeastern North America. The database combines data from three datasets of different initial quality, including a total of 526 land stations and buoys distributed over the provinces of eastern Canada and five adjacent northeastern U.S. states. The data span from 1953 to 2010. The first part of the QC deals with data management issues and is developed in a companion paper. Part II, presented herein, is focused on the detection of measurement errors and deals with low-variability errors, like the occurrence of unrealistically long calms, and high-variability problems, like rapid changes in wind speed; some types of biases in wind speed and wind direction are also considered. About 0.5% (0.16%) of wind speed (wind direction) records have been flagged. Additionally, 15.87% (1.73%) of wind speed (wind direction) data have been corrected. The most pervasive error type in terms of affected sites and erased data corresponds to unrealistic low wind speeds (89% of sites affected with 0.35% records removed). The amount of detected and corrected/removed records in Part II (~9%) is approximately two orders of magnitude higher than that of Part I. Both management and measurement errors are shown to have a discernible impact on the statistics of the database.

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Juan J. González-Alemán, Francisco Valero, Francisco Martín-León, and Jenni L. Evans

Abstract

Since more research is needed on subtropical cyclones (STCs) formed within the North Atlantic eastern basin, this survey analyzes them from a synoptic point of view, on a climatological basis, with the main aims of studying their common features, complementing other studies of these storms in the North Atlantic, and aiding the forecasting community. Fifteen cases of STCs were identified during the period 1979–2011 by applying a set of criteria from two databases. Composite analysis reveals that an extratropical depression acts as a precursor when it is isolated from the westerlies and then suffers a deepening when becoming subtropical instead of decaying through occlusion. This process is accompanied by an atmospheric circulation, within the North Atlantic, whose main feature is characterized by notable departures from the climatological pattern with a statistically significant anomalous high pressure to the north of the STCs. Three conceptual models of synoptic pattern of subtropical cyclogenesis are derived and show that these departures appeared because the westerly circulation moves poleward and/or the flow has a great meridional component, with the possibility of a blocked flow pattern occurring. Moreover, the identified STCs predominantly formed in a highly sheared (>10 m s−1) environment with low sea surface temperature values (<25°C), which differs from the dominant features of STCs in the North Atlantic, especially within its western region. Finally, a recent (2010) STC, identified by the authors, is synoptically discussed in order to achieve a better interpretation of the general results.

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