Short description
(English)
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Homogenisation of surface climate data is essential for the accurate monitoring of climate variability and climate change. Often, it is the extremes of weather and climate which have the greatest impact on society. However, the accurate deter-mination of variability and trends in climate extremes requires much greater effort of data quality assurance. Currently only a few statistical methods exist to help homogenise daily climate data. These methods are fundamentally different from traditional methods which have been used on monthly or annual climate data. Further research is needed in order to assess the impact of inhomogeneities on the climate record at the finer temporal scales. Within the context of COST Action ES0601 this project aims at: - Contribute to the goals of Working Group 4: Methods for homogenisation of daily data, namely: The testing, development and dissemination existing/new correction methods/strategies for daily or sub-daily surface climate data. The expected outcomes of this project are: - Compare existing methods for homogenizing daily and sub-daily surface climate data: Quantifying the added value of the techniques to our understanding of climate variability and extreme events in Switzerland. - Conduct research into the development of new and/or existing methods: Explore the added value of using phys-ical models combined with statistical techniques to improve data quality. - Apply the most adapted methods to long-term daily temperature and precipitation in Switzerland: Report on the improved understanding of climate variability and climate extremes in Switzerland from the mid-19th century to present.
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Partners and International Organizations
(English)
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AT, BA, BE, BG, CH, CY, CZ, DE, ES, FI, FR, GR, HR, HU, IE, IT, LV, NL, NO, PL, PT, RO, RS, SE, SI, SK, UK
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Abstract
(English)
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Homogenisation of surface climate data is essential for the accurate monitoring of climate variability and climate change. Often, it is the extremes of weather and climate which have the greatest impact on society. However, the accurate determination of variability and trends in climate extremes requires much greater effort of data quality assurance. Currently only a few statistical methods exist to help homogenise daily climate data. These methods are fundamentally different from traditional methods which have been used on monthly or annual climate data. Within the context of COST Action ES0601 our project aims to contribute to the goals of Working Group 4 (Methods for homogenisation of daily data), namely: The testing, development and dissemination of correction methods for daily or sub-daily surface climate data. In the first part of our study we compared three different currently used daily homogenization techniques. The results indicate that the performance of the different techniques is similar despite their different complexity and nature of origin. However, it could have been shown that one of the three tested daily homogenization technique is considerably affected by the choice of the reference series. For this technique a well correlated station is necessary for a good performance. The findings of this study together with results from the internal project DigiHom will serve as foundation for the implementation of an operational daily homogenization at MeteoSwiss. In the second part of our study we developed a new physics-based correction approach for the homogenisation of sub-daily temperature series. The correction approach makes use of the full meteorological information of a station, i.e., cloud cover and snow cover (albedo) are used together with information on the local environment (horizon, buildings etc.). Despite these additional informations, it was found that many of the detected breaks cannot be corrected with this model (i.e., they may not be related to the shielding and ventilation). The results of the two parts can now be adapted to generate homogeneous long-term daily temperature and precipitation data for the Swiss National Basic Climate Network. So called climate indicators for climate change will be published on a regular basis in a climate report.
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