67 research outputs found
Advances in the homogenization of daily peak wind gusts: an application to the Australian series
PĂłster 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 âDetection and attribution of changes in extreme wind gusts ove rlandâ (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
State of the Tropics 2014 report
[Extract] Is life in the Tropics getting better? The landmark State of the Tropics 2014 Report addresses this nominally simple question. It provides the first in-depth, objective assessment of the Tropics as an environmental and geopolitical entity in its own right. Drawing on the knowledge, experience and diverse backgrounds of leading institutions across the Tropics the report assesses the state of the region and examines the implications of the immense changes the region is experiencing.
The assessment demonstrates that nations in the Tropics have made extraordinary progress across a wide range of environmental, social and economic indicators in recent decades. Rapid population and economic growth mean its influence is set to rise dramatically in coming decades. The nature of this influence will depend on how the region addresses its many challenges, and whether it realises its potential and opportunities. The report provides a basis from which to work towards a prosperous, sustainable and equitable future for the Tropics and will be a valuable resource for policy makers, geopolitical analysts, researchers, students and other stakeholders interested in the Tropics
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 1941â2016. 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 Unionâs Horizon 2020 research and innovation programme under the Marie SkĆodowska-Curie grant agreement No. 703733 (STILLING project). This work was also supported by the project âDetection and attribution of changes in extreme wind gusts over landâ (2017-03780) funded by the VetenskapsrĂ„det, 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
A new approach to homogenize daily peak wind gusts: an application to the Australian series
PĂłster 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 âDetection and attribution of changes inextreme wind gusts over land â(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
Trends of daily peak wind gusts in Australia, 1948-2016
PĂłster presentado en: EGU General Assembly 2019 celebrada del 7 al 12 de abril en Viena, Austria.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, such as anemometer changes and site location changes, both temporally and spatially, that may introduce inhomogeneities that mislead the study of their decadal variability and trends. A previous study (EGU2018-14546 and Azorin-Molina et al. 2019. Int. J. Climatol. 39(4), 2260-2277) presented a strategy in the homogenization of this challenging climate extreme such as the DPWG. The automatic homogenization of this DPWG dataset was implemented in the recently developed version 3.1 of the R package Climatol which: (i) represents an advance in homogenization of this extreme climate record; and (ii) produced the first homogenized DPWG dataset to assess and attribute long-term variability of extreme winds across Australia. Given the inconsistencies of wind gust trends under the widespread decline in near-surface wind speed (stilling), the aim of this poster presentation is to show DPWG trends in 35 Bureau of Meteorology operated stations for 1948-2016, with particular focus on the spatiotemporal magnitude (wind speed maxima) of DPWG at annual, seasonal and monthly timescales.This work has been supported by the project âDetection and attribution of changes in extreme wind gusts over landâ (2017-03780) funded by the Swedish Research Council
A decline of observed daily peak wind gusts with distinct seasonality in Australia, 1941â2016
Wind gusts represent one of the main natural hazards due to their increasing socioeconomic and environmental impacts on, for example, human safety, maritimeâterrestrialâaviation activities, engineering and insurance applications, and energy production. However, the existing scientific studies focused on observed wind gusts are relatively few compared to those on mean wind speed. In Australia, previous studies found a slowdown of near-surface mean wind speed, termed ââstilling,ââ but a lack of knowledge on the multidecadal variability and trends in the magnitude (wind speed maxima) and frequency (exceeding the 90th percentile) of wind gusts exists. A new homogenized daily peak wind gusts (DPWG) dataset containing 548 time series across Australia for 1941â2016 is analyzed to determine long-term trends in wind gusts. Here we show that both the magnitude and frequency of DPWG declined across much of the continent, with a distinct seasonality: negative trends in summerâspringâautumn and weak negative or nontrending (even positive) trends in winter. We demonstrate that oceanâatmosphere oscillations such as the Indian Ocean dipole and the southern annular mode partly modulate decadal-scale variations of DPWG. The long-term declining trend of DPWG is consistent with the ââstillingââ phenomenon, suggesting that global warming may have reduced Australian wind gusts
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Australian climate warming: observed change from 1850 and global temperature targets
Mean annual temperature is often used as a benchmark for monitoring climate change and as an indicator of its potential impacts. The Paris Agreement of 2015 aims to keep the global average temperature well below 2°C above pre-industrial levels, with a preferred limit of 1.5°C. Therefore, there is interest in understanding and examining regional temperature change using this framework of âglobal warming levelsâ, as well as through emissions pathways and time horizons. To apply the global warming level framework regionally, we need to quantify regional warming from the late 19th century to today, and to future periods where the warming levels are reached. Here we supplement reliable observations from 1910 with early historical datasets currently available back to 1860 and the latest set of global climate model simulations from CMIP5/CMIP6 to examine the past and future warming of Australia from the 1850â1900 baseline commonly used as a proxy for pre-industrial conditions. We find that Australia warmed by ~1.6°C between 1850â1900 and 2011â2020 (with uncertainty unlikely to substantially exceed ±0.3°C). This warming is a ratio of ~1.4 times the ~1.1°C global warming over that time, and in line with observed global land average warming. Projections for global warming levels are also quantified and suggest future warming of slightly less than the observed ratio to date, at ~1.0â1.3 for all future global warming levels. We also find that to reliably examine regional warming under the emissions pathway framework using the latest climate models from CMIP6, appropriate weights to the ensemble members are required. Once these weights are applied, results are similar to CMIP5
A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900
A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900â2014, 1979â2014 and 1998â2014. The best estimates of warming trends and there 95% confidence ranges for 1900â2014 are approximately 0.102â±â0.006â°C/decade for the whole year, and 0.104â±â0.009, 0.112â±â0.007, 0.090â±â0.006, and 0.092â±â0.007â°C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900â2014 and 1979â2014. For an even shorter and more recent period (1998â2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes
WMO assessment of weather and climate mortality extremes : lightning, tropical cyclones, tornadoes, and hail
A World Meteorological Organization (WMO) Commission for Climatology international panel was convened to examine and assess the available evidence associated with five weather-related mortality extremes: 1) lightning (indirect), 2) lightning (direct), 3) tropical cyclones, 4) tornadoes, and 5) hail. After recommending for acceptance of only events after 1873 (the formation of the predecessor of the WMO), the committee evaluated and accepted the following mortality extremes: 1) ''highest mortality (indirect strike) associated with lightning'' as the 469 people killed in a lightning-caused oil tank fire in Dronka, Egypt, on 2 November 1994; 2) ''highest mortality directly associated with a single lightning flash'' as the lightning flash that killed 21 people in a hut in Manica Tribal Trust Lands, Zimbabwe (at time of incident, eastern Rhodesia), on 23 December 1975; 3) ''highest mortality associated with a tropical cyclone'' as the Bangladesh (at time of incident, East Pakistan) cyclone of 12-13 November 1970 with an estimated death toll of 300 000 people| 4) ''highest mortality associated with a tornado'' as the 26 April 1989 tornado that destroyed the Manikganj district, Bangladesh, with an estimated death toll of 1300 individuals| and 5) ''highest mortality associated with a hailstorm'' as the storm occurring near Moradabad, India, on 30 April 1888 that killed 246 people. These mortality extremes serve to further atmospheric science by giving baseline mortality values for comparison to future weather-related catastrophes and also allow for adjudication of new meteorological information as it becomes available.https://www.ametsoc.org/ams/index.cfm/publications/journals/weather-climate-and-society2018-01-30hj2017Geography, Geoinformatics and Meteorolog
The state of the Martian climate
60°N was +2.0°C, relative to the 1981â2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes
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