18 research outputs found
CERA-20C: A Coupled Reanalysis of the Twentieth Century
No full textCERA-20C is a coupled reanalysis of the twentieth century which aims to reconstruct the past weather and climate of the Earth system including the atmosphere, ocean, land, ocean waves, and sea ice. This reanalysis is based on the CERA coupled atmosphere-ocean assimilation system developed at ECMWF. CERA-20C provides a 10 member ensemble of reanalyses to account for errors in the observational record as well as model error. It benefited from the prior experience of the retrospective atmospheric analysis ERA-20C. The dynamical model and the data assimilation systems initially developed for NWP had been modified to take into account the evolution of the radiative forcing and the observing system. To limit the impact of changes in the observing system throughout the century, only conventional surface observations have been used in the atmosphere. CERA-20C improves the specification of the background and the observation errors, two key elements to ensure a consistent weighting of the uncertainties across geophysical variables, space, and time. The quality of CERA-20C has been evaluated against other centennial reanalyses and independent observations. Although CERA-20C inherits some limitations of ERA-20C to represent correctly the tropical cyclones in the first part of the century, it shows significant improvements in the troposphere, compared to ERA-20C and 20CRv2c (the twentieth century reanalysis produced by NOAA/CIRES). A preliminary study of the climate variability in CERA-20C has been carried out. CERA-20C improves on the representation of atmosphere-ocean heat fluxes and mean sea level pressure compared to previous uncoupled ocean and atmospheric historical reanalyses performed at ECMWF
GPCC Climatology Version 2022 (at 0.25°, 0.5°, 1.0°, 2.5°): Monthly Land-Surface Precipitation Climatology for Every Month and the Total Year from Rain-Gauges built on GTS-based and Historical Data
No full textGPCC Climatology Version 2022 (at 0.25°, 0.5°, 1.0°, 2.5°): Monthly Land-Surface Precipitation Climatology for Every Month and the Total Year from Rain-Gauges built on GTS-based and Historical Data
No full textMisfit of Complete Maxillary Dentures’ Posterior Palatal Seal following Polymerisation with Four Different Autopolymerising Resins: An In Vitro Study
No full textBackground: The majority of complete dentures are still conventionally manufactured using a flask-and-pack technique. However, the polymerization process may introduce a distortion of the denture body. The aim of this study was to evaluate the three-dimensional fit of the posterior palatal seal of maxillary complete dentures with the original impression, and to give recommendations for scraping. Methods: Four autopolymerising resins were used to manufacture 40 palatal plates each for high, medium and flat palates (total n = 120). The misfit was captured by taking a reline impression with a highly fluid silicone, the dimensions of which were measured with a flat-bed scanner. Results: The shape of the palate had a significant impact (median p = 0.0435), but not the resin type (median p = 0.2575). It was largest for the flat palate and smallest for the high palate. The largest misfit was observed in the palatal midline area (flat-palate average median: 685 µm; high and medium palates: 620 µm) decreasing towards the lateral and anterior regions. Conclusions: The results suggest compensating for the palatal misfit that occurs with autopolymerising resins by scraping a postdam of an approximately 0.7 mm depth to the master cast, decreasing towards the anterior and lateral areas. In high and medium palates, the scraping could be less pronounced
Application of homogenization methods for Ireland's monthly precipitation records: Comparison of break detection results
No full textTime series homogenization for 299 of the available precipitation records for the island of Ireland (IENet) was performed. Four modern relative homogenization methods, that is, HOMER, ACMANT, CLIMATOL and AHOPS were applied to this network of station series where contiguous intact monthly records range from 30 to 70 years within the base period 1941–2010. Break detection results are compared between homogenization methods, and coincidences with available documentary information (metadata) were analysed. The lowest (highest) number of breaks were detected with HOMER (ACMANT). Large differences of break frequency were found, namely ACMANT and AHOPS detected 8 times as many breaks than HOMER, while the break frequency with CLIMATOL was intermediate. Also, the ratio of series classified to be homogeneous varies widely between the methods. It is 85% with HOMER, 60% with CLIMATOL, 31% with AHOPS, while only 22% with ACMANT. In a further experiment, all the available time series for Ireland and Northern Ireland, (910 series) were used with ACMANT and CLIMATOL to explore the stability of break frequency for the same 299 series examined in the base experiment. While overall break frequency slightly increased (by 6–13%), the break positions notably changed for individual time series. The number of breaks changed for 59% (23%) of the series with ACMANT (CLIMATOL). For the breaks detected coincidentally by at least three methods including ACMANT and CLIMATOL in the base experiment, the second experiment confirmed the break positions in 86–87% of the breaks. The consequences of these results in relation to the reliability of statistical homogenization are discussed. Sometimes markedly different step functions provide comparable good approaches. However, the accuracy of homogenized time series cannot be related directly to the instability of break detection results
Evaluating the Hydrological Cycle over Land Using the Newly-Corrected Precipitation Climatology from the Global Precipitation Climatology Centre (GPCC)
No full textThe 2015 release of the precipitation climatology from the Global Precipitation Climatology Centre (GPCC) for 1951–2000, based on climatological normals of about 75,100 rain gauges, allows for quantification of mean land surface precipitation as part of the global water cycle. In GPCC’s 2011-release, a bulk climatological correction was applied to compensate for gauge undercatch. In this paper we derive an improved correction approach based on the synoptic weather reports for the period 1982–2015. The compared results show that the climatological approach tends to overestimate the correction for Central and Eastern Europe, especially in the northern winter, and in other regions throughout the year. Applying the mean weather-dependent correction to the GPCC’s uncorrected precipitation climatology for 1951–2000 gives a value of 854.7 mm of precipitation per year (excluding Antarctica) or 790 mm for the global land surface. The warming of nearly 1 K relative to pre-industrial temperatures is expected to be accompanied by a 2%–3% increase in global (land and ocean) precipitation. However, a comparison of climatology for 30-year reference periods from 1931–1960 up to 1981–2010 reveals no significant trend for land surface precipitation. This may be caused by the large variability of precipitation, the varying data coverage over time and other issues related to the sampling of rain-gauge networks. The GPCC continues to enlarge and further improve the quality of its database, and will generate precipitation analyses with homogeneous data coverage over time. Another way to reduce the sampling issues is the combination of rain gauge-based analyses with remote sensing (i.e., satellite or radar) datasets
Precipitation trends in the island of Ireland using a dense, homogenized, observational dataset
No full textA dense monthly precipitation dataset of Ireland and Northern Ireland was homogenized with several modern homogenization methods. The efficiency of these homogenizations was tested by examining the similarity of homogenization results both in the real data homogenization and in the homogenization of a simulated dataset. The analysis of homogenization results shows that the real dataset is characterized by a large number of, but mostly small, non-climatic biases, and a moderate reduction of such biases can be achieved with homogenization. Finally, a combination of the ACMANT and Climatol homogenization results was applied to improve the data accuracy before the trend calculations. These two methods were selected for their proven high accuracy, missing data tolerance and ability to complete time series via the infilling of missing values before the trend calculations. Metadata were used within the Climatol method. To facilitate this analysis the study area was split into smaller climatic regions by using the Ward clustering method. Five climatic zones consistent with the known spatial patterns of precipitation in Ireland were established. Linear regression fitting and the Mann-Kendall test were applied. Low frequency fluctuations were also examined by applying a Gaussian filter. The results show that the precipitation amount generally increases in the study area, particularly in the northwestern region. The most significant increasing trends for the whole study period (1941–2010) are found for late winter and spring precipitation, as well as for the annual totals. In the period from the early 1970s the increase of precipitation is general in all seasons of the year except in winter, but the statistical significance of this increase is weak
Rainfall estimates on a gridded network (REGEN) – a global land-based gridded dataset of daily precipitation from 1950 to 2016
No full textWe present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a Gridded Network – REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network – Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station time series were quality-controlled using strict criteria and flagged values were removed. Remaining values were interpolated to create area-average estimates of daily precipitation for global land areas on a 1∘ × 1∘ latitude–longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. The REGEN datasets are expected to contribute to the advancement of hydrological science and practice by facilitating studies aiming to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets.This research has been supported by the Australian Research Council (grant nos. DP160103439, CE110001028 and DE150100456) and the Spanish Ministry for Science and Innovation (grant no. RYC-2017-22964)Peer ReviewedPostprint (published version
EMO-5: A high-resolution multi-variable gridded meteorological data set for Europe
No full textIn this paper we present EMO-5 (“European Meteorological Observations”, spatial resolution of 5 km), a European high-resolution, (sub-)daily, multi-variable meteorological dataset built on historical and real-time observations obtained by integrating data from 18 964 ground weather stations, four high-resolution regional observational grids (i.e. CombiPrecip, ZAMG – INCA, EURO4M-APGD, and CarpatClim), and one global reanalysis (ERA-Interim/Land). EMO-5 includes the following at daily resolution: total precipitation, temperatures (minimum and maximum), wind speed, solar radiation, and water vapour pressure. In addition, EMO-5 also makes available 6-hourly precipitation and mean temperature data. The raw observations from the ground weather stations underwent a set of quality controls before SPHEREMAP and Yamamoto interpolation methods were applied in order to estimate for each 5×5 km grid cell the variable value and its affiliated uncertainty, respectively. The quality of the EMO-5 precipitation data was evaluated. Results show that EMO-5 successfully captured 80 % of the heavy precipitation events, and that it is of comparable quality to a regional high-resolution dataset. The availability of the uncertainty fields increases the transparency of the dataset and hence the possible usage. EMO-5 (version 1) covers the time period from 1990 to 2019, with a near real-time release of the latest gridded observations foreseen with version 2. As a product of Copernicus, EMO-5 dataset is free and open.JRC.E.1 - Disaster Risk Managemen
Quality control of a global hourly rainfall dataset
No full textSub-daily rainfall observations are vital to help us understand, model and adapt to changing climate extremes. However, gauge records often have quality issues, for example due to equipment malfunctions and recording errors. This paper presents a new, open-source quality control algorithm (GSDR-QC) to identify these issues in hourly rainfall data, along with an application of the algorithm to the Global Sub-Daily Rainfall (GSDR) observational dataset. The algorithm is based on 25 quality checks, which are combined into a simple rule base to remove suspicious data. The quality checks and rule base are adaptable to help incorporate local or regional information. Comparison with manually quality-controlled gauge data shows that the procedure results in an overall improvement to the quality of the GSDR dataset. A UK case study further demonstrates the performance of the GSDR-QC procedure, while showing how region-specific data and understanding can be incorporated into the quality control process.</p
