Precipitation - according to instruments, models and proxies

The paper
Bunde, A., U. Büntgen, J. Ludescher, J. Luterbacher, and H. von Storch:  Is there memory in precipitation?
has been published by  Nature Climate Change 3: 174-175. A fine cooperation of theoretical physicists and climate scientists.

The paper asks if  proxies, which supposedly represent rainfall, really present rainfall or something else, such as integrated rainfall, which is something like soil moisture? In any case, shorter rainfall series derived from instrumental data as well as from millennial simulation show a white noise behavior for yearly data, whereas proxies from tree rings have memory. Of course, both instrumental data may be too short and model data flawed, but it is more plausible that the tree ring data reflect not only precipitation but other factors, and, indeed it is the amount of water available to trees in the solid which matters, not how much is precipitating. -

The paper is available from the copyright-walled nature web-page. Alternatively, we offer here an earlier, and shorter version. The published version is longer, explains more details, but is unchanged in substance.
Obviously, this paper is rather technical, and of little interest for those of our readers, who prefer to argue only politically (which is fine :-)) with little interest in the inner working of science. However, I consider the case an interesting example, how scientific progress is meandering forward in little steps - and that self-critical reflection is still an active element in the daily work of climate scientists. Footnote and references are deleted - but the manuscript with references is available from academia.edu.

"Precipitation variation can affect ecological systems, agricultural yields and human societies among various spatio-temporal scales. Paleoclimatic insight on the persistence of wet and dry conditions is relevant to assess perspectives and drivers of ongoing climate change. Since systematic meteorological measurements are mainly limited to the last century, pre-instrumental evidence of precipitation variability during the past millennium derives from proxy-based reconstructions and outputs from climate model simulations. Here we address, if these sources reflect a consistent picture of past precipitation variability. In fact, they do not.

We compare tree ring-based reconstructions from North America, Central Europe and High Asia with forced model simulations and instrumental measurements. To quantify the temporal rhythm of each precipitation record, we first consider the persistence lengths l that are defined by the numbers of successive years in each record during which precipitation is either below or above the median (dry or wet period). It is known that in uncorrelated data (white noise), the persistent length is distributed exponentially, i.e. its frequency of occurrence decreases exponentially with increasing l. We show that the persistence lengths derived from model simulations and instrumental observations resemble white noise (Fig. 1c,d). In contrast, the length distribution of the reconstructions is quite broad and thus indicative for strong multi-annual and multi-decadal persistence (pink noise) (Fig.1a). Long-term persistent data with Hurst exponents ~0.8-0.9 do indeed reveal similar behaviour (Fig. 1b).
We further quantify average precipitation patterns after wet or dry periods of certain lengths l. Data without persistence mirror temporal insensitivity, whereas systems with memory exhibit more (less) precipitation after wet (dry) periods. The reconstructions indicate a strong dependence on previous climate (Fig. 1 insets), again comparable to long-term persistent data with Hurst exponents ~0.8-0.9,whereas the simulations and observations again reflect white noise behaviour. These essential differences also derive from more advanced mathematical techniques like wavelet and detrended fluctuation analysis, and further appear robust in extreme year statistics (see Supplementary Information for details). The reconstructed extremes cluster in time, while the model and observational extremes occur more randomly distributed.

In light of the above, it appears obvious that there is no consistent picture of past precipitation variability emerging from the main two data sources. The course of millennium-long model simulations of regional precipitation variability is supported by instrumental measurements of the last century, suggesting that the occurrence of dry and wet periods generally follows white noise behaviour. It is likely that tree-ring width chronologies overestimate the true precipitation memory,since tree growth is rather influenced by (red) fluctuations in soil moisture availability than by (white) changes in rainfall. Independent lines of palaeoclimatological evidence, however, provide long-term changes in the Earth’s hydrological cycle, which likely caused prolonged episodes of relative droughtat regional to continental scales.


Fig. 1.
Histogram of persistence lengths of
(a) tree ring-based precipitation reconstruction from Central Europe (396BC-604AC) and (985-1985), Colorado (1000-1988), and High Asia (1000-1998), as well as
(b) synthetic long-term persistent data of comparable length (L=1000) with Hurst exponents of 0.8 and 0.9.
(c) ECHAM6 precipitation output for the three proxy areas considered (885-1885), and
(d) monthly precipitation measurements (Potsdam, Germany,1893-1999), together with generated white noise (green) of the same length. The scales are in years for model and reconstructed data, and in months for the instrumental data. The insets show the difference between the (conditional) average precipitation Pn after n consecutive wet or dry years (resp. months) and the mean precipitation P, in units of the standard deviation of each record."

Print this post