{"title":"Optimal grid resolution for precipitation maps from commercial microwave link networks","authors":"R. van de Beek, J. Olsson, J. Andersson","doi":"10.5194/asr-17-79-2020","DOIUrl":null,"url":null,"abstract":"Abstract. High-resolution precipitation observation based on signal attenuation in a Commercial Microwave Link (CML) network is an emerging technique that is becoming more and more used. Commonly, the raw data – line measurements from successive time steps – are mapped onto a grid to estimate precipitation fields with a full spatio-temporal coverage. Assuming the CML-estimated precipitation to be accurate, the attainable resolutions\nin time and space are primarily dependent on two factors: (i) the spatial\ndistribution of the link network and (ii) the spatial correlation properties of the precipitation. Here we outline a pragmatic method for estimating the optimal resolution based on variogram analysis. The method is demonstrated using a CML network and a representative variogram in Stockholm, Sweden. Conceivable applications include preliminary investigations in cities considering starting CML-based precipitation observations.\n","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"88 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Science and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/asr-17-79-2020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 7
Abstract
Abstract. High-resolution precipitation observation based on signal attenuation in a Commercial Microwave Link (CML) network is an emerging technique that is becoming more and more used. Commonly, the raw data – line measurements from successive time steps – are mapped onto a grid to estimate precipitation fields with a full spatio-temporal coverage. Assuming the CML-estimated precipitation to be accurate, the attainable resolutions
in time and space are primarily dependent on two factors: (i) the spatial
distribution of the link network and (ii) the spatial correlation properties of the precipitation. Here we outline a pragmatic method for estimating the optimal resolution based on variogram analysis. The method is demonstrated using a CML network and a representative variogram in Stockholm, Sweden. Conceivable applications include preliminary investigations in cities considering starting CML-based precipitation observations.