Under review
We are currently reviewing the following articles. Additional reviews welcome.
Leeper, R.D., J. Rennie and M.A. Palecki, 2015: Observational Perspectives from U.S. Climate Reference Network (USCRN) and Cooperative Observer Program (COOP) Network: Temperature and Precipitation Comparison. (-)
Venema et al., 2012: Benchmarking homogenization algorithms for monthly data. (-)
Hausfather et al., 2016: Evaluating the impact of U.S. Historical Climatology Network homogenization using the U.S. Climate Reference Network. (-)
Kuglitsch et al., 2012: Break detection of annual Swiss temperature series. (-)
Gubler et al., 2017: The influence of station density on climate data homogenization. (85)
New articles
This lists new articles that are not yet reviewed by us to keep up to date with the newest research. In chronological order. Please suggest missing articles in the comments below.
Resch, G., Koch, R., Marty, C., Chimani, B., Begert, M., Buchmann, M., Aschauer, J., & Schöner, W. (2022). A quantile-based approach to improve homogenization of snow depth time series. International Journal of Climatology, 1– 17. https://doi.org/10.1002/joc.7742
Buchmann, M., Coll, J., Aschauer, J., Begert, M., Brönnimann, S., Chimani, B., Resch, G., Schöner, W., and Marty, C.: Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods, The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, 2022.
Gillespie, IM, Haimberger, L, Compo, GP, Thorne, PW. Assessing potential of sparse‐input reanalyses for centennial‐scale land surface air temperature homogenisation. Int J Climatol. 2021; 41 (Suppl. 1): E3000– E3020. https://doi.org/10.1002/joc.6898
Squintu AA, van der Schrier G, Brugnara Y, Klein Tank A, 2019: Homogenization of daily temperature series in the European climate assessment & dataset. Int J Climatol 39(3):1243–126
Peter Domonkos, José A. Guijarro, Victor Venema, Manola Brunet and Javier Sigró, 2021: Efficiency of time series homogenization: method comparison with 12 monthly temperature test datasets. Journal of Climate, 34, no. 8, pp. 2877–2891. https://doi.org/10.1175/JCLI-D-20-0611.1
Coppa, G, Quarello, A, Steeneveld, G‐J, Jandrić, N, Merlone, A. Metrological evaluation of the effect of the presence of a road on near‐surface air temperatures. Int J Climatol. 2021; 1– 20. https://doi.org/10.1002/joc.7044
Skrynyk, O, Aguilar, E, Guijarro, J, Randriamarolaza, LYA, Bubin, S. Uncertainty evaluation of Climatol’s adjustment algorithm applied to daily air temperature time series. Int J Climatol. 2021; 41 (Suppl. 1): E2395– E2419. https://doi.org/10.1002/joc.6854
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Matthew J. Menne, Claude N. Williams, Byron E. Gleason, J. Jared Rennie, and Jay H. Lawrimore, 2018: The Global Historical Climatology Network Monthly Temperature Dataset, Version 4. Journal of Climate, 31, No. 24: 9835-9854. https://doi.org/10.1175/JCLI-D-18-0094.1
Tsinkoa, Y., A. Bakhshaii, E.A. Johnson, and Y.E. Martin, 2018: Comparisons of fire weather indices using Canadian raw and homogenized weather data. Agricultural and Forest Meteorology, 262, pp. 110-119. https://doi.org/10.1016/j.agrformet.2018.07.005
Menne, Matthew J., Claude N. Williams, Byron E. Gleason, J. Jared Rennie, and Jay H. Lawrimore, 2018: The Global Historical Climatology Network Monthly Temperature Dataset, Version 4. Journal of Climate, in press. https://doi.org/10.1175/JCLI-D-18-0094.1
Lindau, Ralf and Victor Venema, 2018: On the reduction of trend errors by the ANOVA joint correction scheme used in homogenization of climate station records. International Journal of Climatology, published online. https://doi.org/10.1002/joc.5728
Lindau, Ralf and Victor Venema, 2018: The Joint Influence Of Break And Noise Variance On The Break Detection Capability In Time Series Homogenization. Advances in Statistical Climatology, Meteorology and Oceanography, 4, 1-18, https://doi.org/10.5194/ascmo-4-1-2018.
Yosef, Yizhak, Enric Aguilar and Pinhas Alpert, 2018: Detecting and adjusting artificial biases of long‐term temperature records in Israel. International Journal of Climatology, published online, doi: 10.1002/joc.5500.
Chimani, Barbara, Victor Venema, Annemarie Lexer, Konrad Andre, Ingeborg Auer, Johanna Nemec, 2018: Inter‐comparison of methods to homogenize daily relative humidity. International Journal of Climatology, published online, doi: 10.1002/joc.5488.
Hoover, J. , L. Yao, 2018: Aspirated and non‐aspirated automatic weather station Stevenson screen intercomparison. International Journal of Climatology, in press, 9 March 2018, doi: 10.1002/joc.5453.
Yang, Jie, Qingquan Liu, Wei Dai, 2017: A method for solar radiation error correction of temperature measured in a reinforced plastic screen for climatic data collection. International Journal of Climatology, 38, 10.1002/joc.5247.
Ribeiro S., Caineta J., Costa A.C., 2017: Assessing the Performance of the GSIMCLI Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark. In: Gómez-Hernández J., Rodrigo-Ilarri J., Rodrigo-Clavero M., Cassiraga E., Vargas-Guzmán J. (eds) Geostatistics Valencia 2016. Quantitative Geology and Geostatistics, vol 19. Springer, Cham, doi: 10.1007/978-3-319-46819-8_63.
Lucie A. Vincent, Ewa J. Milewska, Xiaolan L. Wang and Megan M. Hartwell, 2018: Uncertainty in homogenized daily temperatures and derived indices of extremes illustrated using parallel observations in Canada. International Journal of Climatology, 38(2), pages 692–707, doi: 10.1002/joc.5203.
Dienst, M., Lindén, J., Engström, E. and Esper, J. (2017), Removing the relocation bias from the 155-year Haparanda temperature record in Northern Europe. International Journal of Climatology, 37: 4015–4026. doi: 10.1002/joc.4981.
Marcolini, G., Bellin, A. and Chiogna, G., 2017: Performance of the Standard Normal Homogeneity Test for the homogenization of mean seasonal snow depth time series. International Journal of Climatology, 37: 1267–1277. doi: 10.1002/joc.4977.
Domonkos, P. and Coll, J., 2017: Time series homogenisation of large observational datasets: The impact of the number of partner series on the efficiency. Climate Research, 74, 31-42. doi: 10.3354/cr01488.