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This work presents a catalog of daily precipitation fields in the Balearic Islands created with data from AEMET (State Meteorological Agency) assistant observations, including records from 1912. The original digital daily data file has been interpolated onto a regular 100 m-resolution grid (namely PREGRIDBAL), defined with the aim of becoming a valid standard for future methodological improvements and catalog upgrades. Daily precipitation amounts on each grid point are calculated using an analysis method based on ordinary kriging, using the daily anomaly with respect to the annual mean for all available observations each day. Due to quality concerns, the time span for products derived from the catalog is limited to the 1950-2009 period, when the number of operating stations reached 200. Therefore, from the time series of daily maps, monthly-, annual-, quinquennial-, and decadal-accumulations are produced. Similarly, the catalog allowed for quantification of climate trends in rainfall amounts in the Balearic Islands, with the significant advantage of minimizing the biases originated from heterogeneities in the spatial distribution of stations across the archipelago. Results show a general decrease in precipitation during the 1950-2009 period. From 1950 to 1979, the average annual precipitation across the islands was 624.3 mm, while from 1980 to 2009 it diminished to 555.36 mm. Changes in precipitation patterns, which vary among the different areas, are also detected. The most significant reductions are found in the northern half of the archipelago and especially in Mallorca, where the Tramuntana mountain range stands out. All seasonal trends show a decrease, with values ranging between 1 and 3 mm decade-1, with the exception of autumn, which reaches a positive trend up to 7 mm decade-1. October shows the most dramatic decrease (-10:34 mm decade-1) and, conversely, September and November show an increase in precipitation (3.28 and 1.82 mm decade-1, respectively) with a statistical significance above 85% across almost the entire archipelago, and even exceeding 95% in Eivissa and Formentera. [ABSTRACT FROM AUTHOR]

This work presents a catalog of daily precipitation in the Balearic Islands created with data from AEMET assistant observers, including registers since 1912. The original digital daily data file has been interpolated onto a regular 100m resolution grid (namely PREGRIDBAL), defined with the aim of becoming a valid standard for future methodological improvements and catalog upgrades. Daily precipitation amounts on each grid-point are calculated using an analysis method based on ordinary Kriging, using the daily anomaly with respect to the annual mean for all available observations each day. Due to quality concerns, the time span for products derived from the catalogue is limited to the 1950-2009 period. Therefore, from the elementary daily maps, monthly-, annual-, quinquennial-, and decadal-accumulations are produced. Similarly, the catalog allowed for quantification of climate trends in rainfall amounts in the Balearic Islands, with the significant advantage of minimising the biases originated from heterogeneities in the spatial distribution of stations across the archipelago. Results show a general decrease in precipitation during the 1950-2009 period. From 1950 to 1979, the average annual precipitation across the islands was 624,3mm, while from 1980 to 2009 diminished to 555,36mm. Changes in precipitation patterns, which vary among the different areas, are also detected. Most significant reductions (over 80% significance on the trend) are found in the north half of the archipelago and especially in Mallorca, where the Tramuntana mountain range stands out. All seasonal trends show a decrease, with values ranging between 1 and 3mm per decade, with the exception of autumn, which reaches up to 7mm per decade. October shows the most dramatic decrease (-10,34mm per decade) and, conversely, September and November show an increase in precipitation (3,28 and 1,82mm per decade, respectively) with a statistical significance above 85% in almost all the archipelago, and even exceeding 95% in the Pitiüses. [ABSTRACT FROM AUTHOR]

The European project INDECIS* (Integrated approach for the development across Europe of user oriented climate indicators for GFCS high-priority sectors: agriculture, disaster risk reduction, energy, health, water and tourism) needs quality controlled and homogenized daily series of several essential climate variables to produce climate indices for their target economical sectors. Work Package 3 is the project team dedicated to provide these high quality series from their raw versions stored at the European Climate Assessment and Dataset (ECA&D).As a first step, a benchmarking exercise was designed in order to test available methodologies on two target areas: Southern Sweden and Slovenia. After considering other alternatives, the Royal Netherlands Meteorological Institute (KNMI) Regional Atmospheric Climate Model (RACMO) version 2 driven by Hadley Global Environment Model 2 - Earth System (MOHC-HadGEM2-ES) was selected as benchmark homogeneous data-set because of its high spatial resolution (0.11°), daily time step and a correspondence of the output variables with the studied ECA&D variables.Relocation inhomogeneities and other perturbations were then applied to the homogeneous data-set to compile different benchmark flavors with varied difficulties. These benchmarks were released to be used by developers and users of homogenization packages in order to test their performances when applied to daily climatic series, not only of extreme temperatures and precipitation as has been customary in past benchmarking efforts, but also of cloud cover, wind speed, relative humidity, sea level pressure, sunshine duration and snow depth.The performance of the applied methodologies are evaluated by comparing errors in the corrected series, their trends and monthly indices relevant to the project objectives. The discussion includes considerations about the difficulties found when homogenizing the different variables and prospects for the homogenization of the complete set of ECA&D series, which will be used by the rest of the INDECIS teams.-----* Project INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). [ABSTRACT FROM AUTHOR]

Meteorological observations may be affected by events unrelated to spatio-temporal variability specific to weather phenomena (errors in transmitting or measuring). Independent of natural weather and climate variability and change, the shifts in the measuring instruments, and changes in the location or the surroundings of the stations can influence meteorological measurements. Findings of meteorological and climatic studies may be altered when they are based on data sets that contain inhomogeneities; therefore, in order to reduce or eliminate the false signals from the climatic data series, methods of homogenisation were developed.In this work, the homogenisation and data filling of the hourly air temperature data, measured on the territory and in the immediate vicinity of Romania, were performed using the R package climatol: Climate Tools (Series Homogenization and Derived Products). Four data sources have been used: Romanian National Meteorological Administration Network, Romanian National Air Quality Monitoring Network, Regional Basic Synoptic Networks and Meteorological Aerodrome Report Network.By using the climatol homogenization method, values related to unrealistic changes in the natural meteorological and climatic system were identified and corrected. Also, missing data were filled by considering the similarities between the data from each station and the reference series (records from the stations which are best correlated with the values of the analysed station). Comparing the homogenization results with the initial (non-homogenized) data revealed that by removing the breakpoints and correcting the analysed series, the statistical properties of the homogenized data set do not differ significantly from those computed from raw data. The main result of this study is a homogenized hourly air temperature dataset at country scale which combines data from several networks of measurements. This work was supported by a grant of Ministry of Research and Innovation, CNCS - UEFISCDI, project number PN-III-P1-1.1-PD-2016-1579, within PNCDI III. [ABSTRACT FROM AUTHOR]