Convection-parameterized and convection-permitting modelling of heavy precipitation in decadal simulations of the greater Alpine region with COSMO-CLM

Heavy precipitation is a challenging phenomenon with high impact on human lives and infrastructure, and thus a better modelling of its characteristics can improve understanding and simulation at climate timescales. The achievement of convection-permitting modelling (CPM) resolutions (Δx&lt;4 km) has brought relevant advancements in its representation. However, further research is needed on how the very high resolution and switching-off of the convection parameterization affects the representation of processes related to heavy precipitation. In this study, we evaluate reanalysis-driven simulations for the greater Alpine area over the period 2000–2015 and assess the differences in representing heavy precipitation and other model variables in a CPM setup with a grid size of 3 km and a regional climate model (RCM) setup at 25 km resolution using the COSMO-CLM model. We validate our simulations against high-resolution observations (E-OBS (ENSEMBLES observations), HYRAS (Hydrometeorologische Rasterdatensätze), MSWEP (Multi-Source Weighted-Ensemble Precipitation), and UWYO (University of Wyoming)). The study presents a revisited version of the precipitation severity index (PSI) for severe event detection, which is a useful method to detect severe events and is flexible for prioritizing long-lasting events and episodes affecting typically drier areas. Furthermore, we use principal component analysis (PCA) to obtain the main modes of heavy precipitation variance and the associated synoptic weather types (WTs). The PCA showed that four WTs suffice to explain the synoptic situations associated with heavy precipitation in winter, due to stationary fronts and zonal flow regimes. Whereas in summer, five WTs are needed to classify the majority of heavy precipitation events. They are associated with upper-level elongated troughs over western Europe, sometimes evolving into cutoff lows, or with winter-like situations of strong zonal circulation. The results indicate that CPM represents higher precipitation intensities, better rank correlation, better hit rates for extremes detection, and an improved representation of heavy precipitation amount and structure for selected events compared to RCM. However, CPM overestimates grid point precipitation rates, which agrees with findings in past literature. CPM systematically represents more precipitation at the mountain tops. However, the RCMs may show large intensities in other regions. Integrated water vapour and equivalent potential temperature at 850 hPa are systematically larger in RCM compared to CPM in heavy precipitation situations (up to 2 mm and 3 K, respectively) due to wetter mid-level conditions and an intensified latent heat flux over the sea. At the ground level, CPM emits more latent heat than RCM over land (15 W m−2), bringing larger specific humidity north of the Alps (1 g kg−1) and higher CAPE (convective available potential energy) values (100 J kg−1). RCM, on the contrary simulates a wetter surface level over Italy and the Mediterranean Sea. Surface temperatures in RCM are up to 2 ∘C higher in RCM than in CPM. This causes outgoing longwave radiation to be larger in RCM compared to CPM over those areas (10 W m−2). Our analysis emphasizes the improvements of CPM for heavy precipitation modelling and highlights the differences against RCM that should be considered when using COSMO-CLM climate simulations.</p

Quality Control of Surface Wind Observations in Northeastern North America. Part I: Data Management Issues

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 similar to 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

Surface wind over Europe: Data and variability

This work improves the characterization and knowledge of the surface wind climatology over Europe with the development of an observational database with unprecedented quality control (QC), the European Surface Wind Observational database (EuSWiO). EuSWiO includes more than 3,829 stations with sub-daily resolution for wind speed and direction, with a number of sites spanning the period of 1880–2017, a few hundred time series starting in the 1930s and relatively good spatial coverage since the 1970s. The creation of EuSWiO entails the merging of eight different data sets and its submission to a common QC. About 5% of the total observations were flagged, correcting a great part of the extreme and unrealistic values, which have a discernible impact on the statistics of the database. The daily wind variability was characterized by means of a classification technique, identifying 11 independent subregions with distinct temporal wind variability over the 2000–2015 period. Significant decreases in the wind speed during this period are found in five regions, whereas two regions show increases. Most regions allow for extending the analysis to earlier decades. Caution in interpreting long-term trends is needed as wind speed data have not been homogenized. Nevertheless, decreases in the wind speed since the 1980s can be noticed in most of the regions. This work contributes to a deeper understanding of the temporal and spatial surface wind variability in Europe. It will allow from meteorological to climate and climate change studies, including potential applications to the analyses of extreme events, wind power assessments or the evaluation of reanalysis or model-data comparison exercises at continental scales

Quality Control of Surface Wind Observations in Northeastern North America. Part II: Measurement Errors

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

A quality assurance process of a surface wind database in Eastern Canada

Presentación realizada para las XXXII Jornadas Científicas de la Asociación Meteorológica Española y 13º Encuentro Hispano-Luso de Meteorología celebrados en Alcobendas (Madrid), del 28 al 30 de mayo de 2012

An assessment of observed and simulated temperature variability in Sierra de Guadarrama

This work provides a first assessment of temperature variability at interannual and decadal timescales in Sierra de Guadarrama, a high mountain protected area of the Central System in the Iberian Peninsula. Observational data from stations located in the area and simulated data from a high-resolution simulation (1 km) with the Weather Research and Forecasting (WRF) model, fed from ERA Interim reanalysis, are used in order to analyse the temperatura variability in the period 2000–2018. Comparison among all datasets allows evaluation of the realism of the model simulations. The results show that the model tends to underestimate the observational mean temperatures and anomalies at high-altitude stations. A linear mean temperature vertical gradient of −5.81 ◦C/km is observed, but it is overestimated by the model (−6.56 ◦C/km). The variability of the daily temperature anomalies for both observations and, to a lesser extent, simulations increases with height. The added value that the WRF offers against the use of the ERA Interim is evaluated. The results show that the WRF provides a better performance than the reanalysis, as it shows smaller biases with respect to observational temperature anomalies. Finally, the study of temperature trends over the Sierra de Guadarrama and its surroundings for the period 2000–2018 shows a warming in the area, significantly pronounced in autumn. When extended to the last decades, observations show that this warming has been happening since the first half of the 20th century, especially during the period 1970–2018, but not as much as during 2000–2018.This research was funded by CEI Moncloa UPM-UCM-Ciemat Cooperation Agreement: GuMNet (Guadarrama Monitoring Network) Initiative, Ministerio de Ciencia e Innovación: GreatModelS (RTI2018-102305-B-C21d), Ministerio de Ciencia e Innovación: GreatModelS (RTI2018-102305-B-C21d), Ministerio de Ciencia e Innovación: ILModels (CGL2014-59644-R/CLI)

Variabilidad y predictibilidad del viento a escala regional: modelos dinámico y estadístico sobre terreno complejo

Ponencia presentada en: XXXI Jornadas Científicas de la AME y el XI Encuentro Hispano Luso de Meteorología celebrado en Sevilla, del 1 al 3 de marzo de 2010

Expected Recurrence of Extreme Winds in Northwestern Sahara and Associated Uncertainties

Estimating the probability of the occurrence of hazardous winds is crucial for their impact in human activities; however, this is inherently affected by the shortage of observations. This becomes critical in poorly sampled regions, such as the northwestern Sahara, where this work is focused. The selection of any single methodological variant contributes with additional uncertainty. To gain robustness in the estimates, we expand the uncertainty space by applying a large body of methodologies. The methodological uncertainty is constrained afterward by keeping only the reliable experiments. In doing so, we considerably narrow the uncertainty associated with the wind return levels. The analysis suggest that not necessarily all methodologies are equally robust. The highest 10-min speed (wind gust) for a return period of 50 years is about 45 ms-1 (56 ms-1). The intensity of the expected extreme winds is closely related to orography. The study is based on wind and wind gust observations that were collected and quality controlled for the specific purposes herein. We also make use of a 12-year high-resolution regional simulation to provide simulation-based wind return level maps that endorse the observation-based results. Such an exhaustive methodological sensitivity analysis with a long high-resolution simulation over this region was lacking in the literature

Surface wind over Europe: Data and variability

This work improves the characterization and knowledge of the surface wind climatology over Europe with the development of an observational database with unprecedented quality control (QC), the European Surface Wind Observational database (EuSWiO). EuSWiO includes more than 3,829 stations with sub-daily resolution for wind speed and direction, with a number of sites spanning the period of 1880–2017, a few hundred time series starting in the 1930s and relatively good spatial coverage since the 1970s. The creation of EuSWiO entails the merging of eight different data sets and its submission to a common QC. About 5% of the total observations were flagged, correcting a great part of the extreme and unrealistic values, which have a discernible impact on the statistics of the database. The daily wind variability was characterized by means of a classification technique, identifying 11 independent subregions with distinct temporal wind variability over the 2000–2015 period. Significant decreases in the wind speed during this period are found in five regions, whereas two regions show increases. Most regions allow for extending the analysis to earlier decades. Caution in interpreting long-term trends is needed as wind speed data have not been homogenized. Nevertheless, decreases in the wind speed since the 1980s can be noticed in most of the regions. This work contributes to a deeper understanding of the temporal and spatial surface wind variability in Europe. It will allow from meteorological to climate and climate change studies, including potential applications to the analyses of extreme events, wind power assessments or the evaluation of reanalysis or model-data comparison exercises at continental scales