Page 248 - Contributed Paper Session (CPS) - Volume 2
P. 248
CPS1846 Maryam I. et al.
As it appears to be the viable initial approach in terms of ease of
implementation and time taken to obtain the results for this large problem.
However, it will be well worth making the effort to quantify these uncertainties
over larger samples.
References
1. L. Cao, Z. Yan, P. Zhao, Y. Zhu, Y. Yu, G. Tang, and P. Jones. Climatic
warming in China during 1901–2015 based on an extended dataset of
instrumental temperature records. Environmental Research Letters,
12(6):064005, 2017. URL http://stacks.iop.org/1748-
9326/12/i=6/a=064005.
2. P. Domonkos and J. Coll. Homogenisation of temperature and
precipitation time series with ACMANT3: Method description and
efficiency tests. International Journal of Climatology, 37(4):1910–1921,
2017.
3. R.J.H. Dunn, K.M. Willett, C.P. Morice, and D.E. Parker. Pairwise
homogeneity assessment of HadISD. Climate of the Past, 10(4):1501,
2014.
4. R.J.H. Dunn, K.M. Willett, D.E. Parker, and L. Mitchell. Expanding HadISD:
Quality-controlled, sub-daily station data from 1931. Geoscientific
Instrumentation, Methods and Data Systems, 5(2):473, 2016.
5. J.M. Edwards, J.R. McGregor, M.R. Bush, and F.J. Bornemann. Assessment
of numerical weather forecasts against observations from Cardington:
seasonal diurnal cycles of screen-level and surface temperatures and
surface fluxes. Quarterly Journal of the Royal Meteorological Society,
137(656):656–672, 2011.
6. Elizabeth Jane Good. An in situ-based analysis of the relationship
between land surface “skin” and screen-level air temperatures. Journal of
Geophysical Research: Atmospheres, 121(15):8801–8819, 2016.
7. J. Hansen, R. Ruedy, M. Sato, and K. Lo. Global surface temperature
change. Reviews of Geophysics, 48(4), 2010.
8. Z. Hausfather, K. Cowtan, M.J. Menne, and C.N. Williams. Evaluating the
impact of us historical climatology network homogenization using the us
climate reference network. Geophysical Research Letters, 43(4):1695–
1701, 2016.
9. M. Ilyas, C.M. Brierley, and S. Guillas. Uncertainty in regional
temperatures inferred from sparse global observations: Application to a
probabilistic classification of El Niño. Geophysical Research Letters,
44(17):9068–9074, 2017.
10. M. Ishii, A. Shouji, S. Sugimoto, and T. Matsumoto. Objective analyses of
sea-surface temperature and marine meteorological variables for the
237 | I S I W S C 2 0 1 9