Assimilation of radar and satellite data in mesoscale models: A physical initialization scheme

Autor: Marco Milan, Victor Venema, Dirk Schü ttemeyer, Clemens Simmer

Publikováno v: Meteorologische Zeitschrift, Vol 17, Iss 6, Pp 887-902 (2008)

The quality of numerical precipitation prediction depends on the accuracy of the model reproducing the true initial state of the atmosphere prior to the forecast. Typically a numerical model needs a spin-up time of several hours until its hydrologica

Externí odkaz: https://doaj.org/article/656b35bcc779405f9ecfd355e9a442ee

Insights from 20 years of temperature parallel measurements in Mauritius around the turn of the 20th Century

Autor: Martin Mahony, Thomas G. Thorne, Samuel O. Awe, Conor Murphy, Victor Venema, Simon Noone, Peter Thorne, Edley Michaud

There is considerable import in creating more complete, better understood, holdings of early meteorological data. Such data permit an improved understanding of climate variability and long-term changes. Early records are particularly incomplete in th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cd9c600de05b2bbab662d894a9877b6f
https://doi.org/10.5194/cp-2021-127

Random trend errors in climate station data due to inhomogeneities

Autor: Ralf Lindau, Victor Venema

Publikováno v: International Journal of Climatology. 40:2393-2402

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6865260292dc34d3d8fdb10b0d696b44
https://doi.org/10.1002/joc.6340

The joint influence of break and noise variance on the break detection capability in time series homogenization

Autor: Ralf Lindau, Victor Venema

Publikováno v: Advances in Statistical Climatology, Meteorology and Oceanography, Vol 4, Pp 1-18 (2018)

Instrumental climate records of the last centuries suffer from multiple breaks due to relocations and changes in measurement techniques. These breaks are detected by relative homogenization algorithms using the difference time series between a candid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c22ea3f3fb1a37893b3c3683f0bb3221
https://www.adv-stat-clim-meteorol-oceanogr.net/4/1/2018/ascmo-4-1-2018.pdf

A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature

Autor: Alexey Kaplan, John Kennedy, Boyin Huang, David E. Parker, Shoji Hirahara, Thomas M. Smith, Masayoshi Ishii, Huai-Min Zhang, Christopher P. Atkinson, Victor Venema, Finban Lindgren, Nick Rayner, Christopher J. Merchant, David I. Berry, Elizabeth C. Kent, Simone Morak-Bozzo, Souichiro Yasui, Giulia Carella, Philip Jones, Yoshikazu Fukuda

Publikováno v: Kent, E C, Berry, D I, Carella, G, Kennedy, J J, Parker, D E, Atkinson, C P, Rayner, N A, Smith, T M, Hirahara, S, Huang, B, Zhang, H-M, Kaplan, A, Fukuda, Y, Ishii, M, Jones, P D, Lindgren, F, Merchant, C J, Morak-Bozzo, S, Venema, V & Yasui, S 2017, ' A call for new approaches to quantifying biases in observations of sea-surface temperature ', Bulletin of the American Meteorological Society, vol. 98, no. 8, pp. 1601-1616 . https://doi.org/10.1175/BAMS-D-15-00251.1

Global surface-temperature is a fundamental measure of climate change. We discuss bias estimation for sea-surface temperature and recommend the improvements to data, observational metadata, and uncertainty modeling needed to make progress.Global surf

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5849edd91f9eaca332fca2a808e49f1d
https://doi.org/10.1175/bams-d-15-00251.1