Homogeneous time series of daily precipitation, temperature, and other meteorological variables are indispensable for climate change and variability studies
Also after homogenization, homogeneity and trend analysis deserves continuous attention, as new homogeneities might appear and improved homogenization methods are being developed. To deal with inhomogeneities, KNMI has set up a Protocol for Changes in the Measurement Infrastructure. This protocol implements the Global Climate Observing System (GCOS) climate monitoring principles. In practice this means the performance of parallel measurements in case of station moves or sensor changes.
Homogenization of daily temperature series
Following an earlier homogenization of the daily precipitation series, we recently homogenized the 20th century daily mean, minimum and maximum temperatures (Tmean, Tn, Tx) of the five principal climate stations in the Netherlands. For the investigated stations, it is known that there have been major relocations that caused inhomogeneities. In addition, for station De Bilt the relocation was accompanied by a major change in thermometer screen. The existence of parallel data makes it possible to correct for the inhomogeneities. The new series are a step forward because they allow a realistic comparison of mean and extreme temperatures from the beginning of the 20th century up till now. As an example Figure 1 shows the Tmean, Tn, and Tx time series before and after homogenization for De Bilt. For the stations considered, the new series give a consistent picture of climate change both in space and time.
Trends in al-sky radiation (1966-2015)
We analyzed the trends in all-sky radiation observations for the past 50 years for the five main climate stations of the Netherlands. In Figure 2 the bottom white line represents the mean all-sky radiation, from which a positive and significant trend of 1.81 Wm-2 per decade could be derived. Collocated observations of cloudiness were used to select for periods of clear skies and cloud amounts, from which amongst others the clear-sky radiation could be derived. The white line in the middle is the clear-sky radiation, which has a positive and significant trend of 2.33 Wm-2 per decade.
The analyzed observations were used in conjunction with a radiative transfer model to quantify all radiative components that are responsible for reducing the top-of-atmosphere solar flux over the Netherlands (TOA, 274 Wm-2) to the observed all-sky radiation (110 – 120 Wm-2). In order from top to bottom of the figure these components are:
From the figure it can be deduced that the trend in all-sky radiation is entirely due to trends in clouds (cloud amount, microphysics and thickness) and aerosols. Water vapor absorption is on average more important than aerosol scattering and absorption, but since water vapor absorption has no long-term trend it does not contribute to the trend in all-sky radiation.
From the figure it can be deduced that the trend in all-sky radiation is entirely due to trends in clouds (cloud amount, microphysics and thickness) and aerosols. Water vapor absorption is on average more important than aerosol scattering and absorption, but since water vapor absorption has no long-term trend it does not contribute to the trend in all-sky radiation.
Literatuur
Boers, R., T. Brandsma, and A. P. Siebesma. Impact of aerosols and clouds on decadal trends in all-sky solar radiation over the Netherlands (1966 – 2015). Submitted to Geophysical Research Letters.
Brandsma, T. Homogenization of daily temperature data of the five principal stations in the Netherlands (v1.0). De Bilt, Technical report; TR-356, 2016.
Buishand, T. A., G. De Martino, J. N. Spreeuw, and T. Brandsma. Homogeneity of precipitation series in the Netherlands and their trends in the past century. International Journal of Climatology, 33 (4), 815–833, 2013.
