An addition to the diversity of dendrobatid frogs in Venezuela: description of three new collared frogs (Anura: Dendrobatidae: Mannophryne)

Three new species of collared frogs of the genus Mannophryne are described from Venezuela. Two are newly discovered taxa from the Venezuelan Andes, whereas the third species, previously confused with M. trinitatis, is from the Caracas area in the Cordillera de la Costa. The call of the three new species and that of Mannophryne collaris are described. Taxonomic, zoogeographic, and conservation issues are discussed

Contribution of uneven warming to the observed wind stilling in North China for 1961-2016

This work has been supported by the project “Detection and attribution of changes in extreme wind gusts over land” (2017-03780) funded by the Swedish Research Council

Advances in the homogenization of daily peak wind gusts: an application to the Australian series

Póster presentado en: EGU General Assembly 2018 celebrada del 8 al 13 de abril en Viena, Austria.Daily Peak Wind Gusts (DPWG) time-series are valuable data for evaluation of wind related hazard risk to the population and different economic sectors. Yet wind time-series are prone to be affected by inhomogeneities temporally and spatially (e.g. through change of instruments at a site compared to surrounding sites) that may mislead the studies of their variability and trends. The aim of this work is to present the advances in the homogenization of DPWG by analyzing 548 sites time-series across Australia covering the 1941-2016 time period. Due to the low correlation coefficients between these series, especially in the first decades when the station density is much lower, the average wind speed data from the NCEP/NCAR reanalysis were tried as reference series. However, their lower correlations with the DPWG data suggests avoiding this approach. We proposed a robust monthly homogenization using the R package Climatol, which detected 353 break-points at the monthly scale. Some of them were supported by the history of the stations, but detailed analysis of the metadata of 35 selected stations did not find a good correspondence since many changes do not necessarily produce inhomogeneities. When NCEP/NCAR reanalysis are used as references, more break-points are detected around 2003, but it is not clear whether they are due to a general change of the DPWG algorithm in the observation network or rather an artifact due to inhomogeneities in the reanalysis series. The monthly dates of the detected break-points were used in a new application of the Climatol package to adjust the series at daily basis, yielding a homogenized and filled DPWG database for assessing the variability of extreme wind events. Resultant trends of the homogenized DPWG series showed the benefits of the homogenization in the form a much lower dispersion of their values.This work has been also supported by the Project “Detection and attribution of changes in extreme wind gusts ove rland” (2017-03780) funded by the Swedish Research Council, and the MULTITEST (Multiple verification of automatic software homogenizing monthly temperatura and precipitation series; CGL2014-52901-P) Project ,funded b ythe Spanish Ministry of Economy and Competitivity

Amphibia, Anura, Hylidae, Scarthyla vigilans: range extensions and new state records from Delta Amacuro and Miranda states, Venezuela

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A new approach to homogenize daily peak wind gusts: an application to the Australian series

Póster presentado en: EMS Annual Meeting - European Conference for Applied Meteorology and Climatology 2018, celebrado en Budapest del 3 al 7 de septiembre de 2018.Daily Peak Wind Gusts (DPWG) time-series are valuable data for the evaluation of wind related hazard risks to different socioeconomic and environmental sectors. Yet wind time-series analyses can be impacted by several artefacts, both temporally and spatially, that may introduce inhomogeneities that mislead the studies of their decadal variability and trends. The aim of this study is to present a new strategy in the homogenization of a challenging climate extreme such as the DPWG using 548 time-series across Australia for 1941-2016. This automatic homogenization of DPWG is implemented in the recently developed Version 3.0 of the R package Climatol. The new approach is an advance in homogenization of climate records as identifies 353 breakpoints based on monthly data, splits the daily series into homogeneous sub-periods, and homogenizes them without needing the monthly corrections. The major advantages of this homogenization strategy are its ability to: (i) automatically homogenize a large number of DPWG series, including short-term ones and without needing site metadata (e.g., the change in observational equipment in 2010/2011 was correctly identified); (ii) use the closest reference series even not sharing a common period with candidate series or presenting missing data; and (iii) supply homogenized series, correcting anomalous data (quality control by spatial coherence), and filling in all the missing data. The NCEP/NCAR reanalysis wind speed data was also trialled in aiding homogenization given the station density was very low during the early decades of the record; however, reanalysis data did not improve the homogenization. Application of the new approach found a reduced range of DPWG trends based on site data, and an increased negative regional trend of this climate extreme, compared to raw data and homogenized data using NCEP/NCAR. The analysis produced the first homogenized DPWG dataset to assess and attribute long-term variability of extreme winds across Australia.This work has been also supported by the Project “Detection and attribution of changes inextreme wind gusts over land ”(2017-03780) funded by the Swedish Research Council, and the MULTITEST (Multiple verification of automatic software homogenizing monthly temperatura and precipitation series; CGL2014-52901-P) project, funded by the Spanish Ministry of Economy and Competitivity

An approach to homogenize daily peak wind gusts: an application to the Australian series

Daily Peak Wind Gust (DPWG) time series are important for the evaluation of wind-related hazard risks to different socioeconomic and environmental sectors. Yet, wind time series analyses can be impacted by several artefacts, both tempo-rally and spatially, which may introduce inhomogeneities that mislead the study of their decadal variability and trends. The aim of this study is to present a strategy in the homogenization of a challenging climate extreme such as the DPWG using 548 time series across Australia for 1941–2016. This automatic homogenization of DPWG is implemented in the recently developed Version 3.1 of the R package Climatol. This approach is an advance in homogenization of climate records as it identifies 353 break points based on monthly data, splits the daily series into homo- geneous subperiods, and homogenizes them without needing the monthly corrections. The major advantages of this homogenization strategy are its ability to: (a) automatically homogenize a large number of DPWG series, including short-term ones and without needing site metadata (e.g., the change in observational equipment in 2010/2011 was correctly identified); (b) use the closest reference series even not sharing a common period with candidate series or presenting missing data; and (c) supply homogenized series, correcting anomalous data (quality control by spatial coherence), and filling in all the missing data. The NCEP/NCAR reanalysis wind speed data were also trialled in aiding homogenization given the station density was very low during the early decades of the record; however, reanalysis data did not improve the homogenization. Application of this approach found a reduced range of DPWG trends based on site data, and an increased negative regional trend of this climate extreme, compared to raw data and homogenized data using NCEP/NCAR. The analysis produced the first homogenized DPWG dataset to assess and attribute long-term variability of extreme winds across Australia.C.A.-M. received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 703733 (STILLING project). This work was also supported by the project “Detection and attribution of changes in extreme wind gusts over land” (2017-03780) funded by the Vetenskapsrådet, and the MULTITEST (Multiple verification of automatic software homogenizing monthly temperature and precipitation series; CGL2014-52901-P) project, funded by the Spanish Ministry of Economy and Competitivity

Assessing the Impact of Different Measurement Time Intervals on Observed Long-Term Wind Speed Trends

During the last two decades climate studies have reported a tendency toward a decline in measured near-surface wind speed in some regions of Europe, North America, Asia and Australia. This weakening in observed wind speed has been recently termed >global stilling>, showing a worldwide average trend of -0.140 m s -1 dec -1 during last 50-years. The precise cause of the >global stilling> remains largely uncertain and has been hypothetically attributed to several factors, mainly related to: (i) an increasing surface roughness (i.e. forest growth, land use changes, and urbanization); (ii) a slowdown in large-scale atmospheric circulation; (iii) instrumental drifts and technological improvements, maintenance, and shifts in measurements sites and calibration issues; (iv) sunlight dimming due to air pollution; and (v) astronomical changes. This study proposed a novel investigation aimed at analyzing how different measurement time intervals used to calculate a wind speed series can affect the sign and magnitude of long-term wind speed trends. For instance, National Weather Services across the globe estimate daily average wind speed using different time intervals and formulae that may affect the trend results. Here we analyzed near-surface wind speed trends recorded at 19 land-based stations across Spain comparing monthly mean wind speed series obtained from: (a) daily mean wind speed data averaged from standard 10-min mean observations at 0000, 0700, 1300 and 1800 UTC; and (b) average wind speed of 24 hourly measurements (i.e., wind run measurements) from 0000 to 2400 UTC. As a complementary analysis, in this study we also quantified the impact of anemometer drift (i.e. bearing malfunction) by presenting preliminary results (i.e. 11 months of paired measurements) from a comparison of one new anemometer sensor against one malfunctioned anemometer sensor due to old bearings.We would like to thank the AEMET for supplying wind speed data. C. A-M. received a postdoctoral fellowship # JCI-2011-10263. Research supported by projects CGL2011-27574-C02-02, CGL2011-27536/HID and CGL2011-29263-C02-01 financed by the Spanish Commission of Science and Technology.Peer Reviewe

Stilling project: advances in the compilation and homogenization of historical wind speed data for the assessment of the stilling phenomenon

Póster presentado en: EGU General Assembly 2018 celebrada del 8 al 13 de abril en Viena, Austria.During the last decade scientists have reported a terrestrial slowdown in wind speed across the world. This weakening in wind speed has been recently termed the “stilling” phenomenon, with a worldwide average trend of -0.140 m s-1 decade-1 reported since the 1960s. The precise causes of this “stilling” remain largely uncertain and have been hypothetically attributed to several factors, mainly related to an increase in surface roughness (i.e. forest growth, land use changes, and urbanization) with little attention paid to changes in atmospheric circulation. Unlike this “stilling” over land, satellite measurements have revealed that wind speed has increased over ocean surfaces, which introduces uncertainty to the “stilling” debate. Therefore, scientists are currently debating if global warming has and will impact on changes in wind speed.The uncertainty on the causes driving the “stilling” over land is mainly due to short availability (i.e. since the 1960s) and low quality of observed wind speed records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) and the recent report “State of the Climate in 2015” . The main objective of the ongoing EU funded project STILLING (MSCAIF-2015 GA-703733) is to fill the key gap of short availability and low quality of wind speed datasets, and improve the limited knowledge on the causes driving the “stilling” in a climate change scenario. This has not yet been addressed by the scientific community due to (i) scientists have traditionally paid little attention on variability of wind speed; (ii) digitization of climate series at National Weather Services (NWS) systematically started in the 1960s, however, some longer but isolated past wind speed records are available for scientists to be rescued and analyzed; and (iii) efforts on advances in homogenization algorithms to improve quality of wind speed series have been scarce. The STILLING project covers a novel research niche on the “stilling” debate, and this contribution will present the advances in the compilation and homogenization of historical wind speed data (prior to the 1960s) to better assess trends/cycles and causes on multidecadal time periods and reliable datasets than previous studies.This research has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 703733 (STILLING project)

Abnormal social behaviors and altered gene expression rates in a mouse model for Potocki-Lupski syndrome

The Potocki-Lupski syndrome (PTLS) is associated with a microduplication of 17p11.2. Clinical features include multiple congenital and neurobehavioral abnormalities and autistic features. We have generated a PTLS mouse model, Dp(11)17/+, that recapitulates some of the physical and neurobehavioral phenotypes present in patients. Here, we investigated the social behavior and gene expression pattern of this mouse model in a pure C57BL/6-Tyrc-Brd genetic background. Dp(11)17/+ male mice displayed normal home-cage behavior but increased anxiety and increased dominant behavior in specific tests. A subtle impairment in the preference for a social target versus an inanimate target and abnormal preference for social novelty (the preference to explore an unfamiliar mouse versus a familiar one) was also observed. Our results indicate that these animals could provide a valuable model to identify the specific gene(s) that confer abnormal social behaviors and that map within this delimited genomic deletion interval. In a first attempt to identify candidate genes and for elucidating the mechanisms of regulation of these important phenotypes, we directly assessed the relative transcription of genes within and around this genomic interval. In this mouse model, we found that candidates genes include not only most of the duplicated genes, but also normal-copy genes that flank the engineered interval; both categories of genes showed altered expression levels in the hippocampus of Dp(11)17/+ mic

Uneven warming likely contributed to declining near-surface wind speeds in Northern China between 1961 and 2016

A decline in mean near-surface (10 m) wind speed has been widely reported for many land regions over recent decades, yet the underlying cause(s) remains uncertain. This study investigates changes in near-surface wind speed over northern China from 1961 to 2016, and analyzes the associated physical mechanisms using station observations, reanalysis products and model simulations from the Community Atmosphere Model version 5.1 (CAM5). The homogenized near-surface wind speed shows a significantly (p 50°N) in recent decades, which has weakened the annual and seasonal meridional air temperature gradient (−0.33°C to −0.12°C dec−1, p < 0.05, except autumn) between these regions (50°–60°N, 75°–135°E) and the northern China zone (35°–45°N, 75°–135°E). This caused a significant (p < 0.05) decrease in annual and seasonal pressure gradient (−0.43 to −0.20 hPa dec−1) between the two zones, which contributed to the slowdown of winds. CAM5 simulations demonstrate that spatially uneven air temperature increases and near-surface wind speed decreases over northern China can be realistically reproduced using the so-called “all forcing” simulation, while the “natural only forcing” simulation fails to realistically simulate the uneven warming patterns and declines in near-surface wind speed over most of northern China, except for summer.This study was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, Grant No. 2019QZKK0606), the National Natural Science Foundation of China (Grant No. 41621061), and by the National Key Research and Development Program—Global Change and Mitigation Project (Grant No. 2016YFA0602404). This work was also supported by a Swedish Research Council (2017-03780) and a Swedish Research Council for Sustainable Development (2019-00509) grant, and by the IBER-STILLING project, funded by the Spanish Ministry of Science, Innovation and Universities (RTI2018-095749-A-I00; MCIU/AEI/FEDER, UE)