Pentti Pirinen

Bio: Pentti Pirinen is an academic researcher from Finnish Meteorological Institute. The author has contributed to research in topics: Climate change & Precipitation. The author has an hindex of 14, co-authored 32 publications receiving 2961 citations.

European phenological response to climate change matches the warming pattern

Abstract: Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high-temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single-site or single-species studies are particularly open to suspicion of being biased towards predominantly reporting climate change-induced impacts. No comprehensive study or meta-analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade � 1 in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species’ phenology is responsive to temperature of the preceding

Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models

Abstract: The Finnish Meteorological Institute has calculated statistics for the new reference period of 1981–2010. During this project, the grid size has been reduced from 10 to 1 km, the evaluation of the interpolation has been improved, and comparisons between different methods has been performed. The climate variables of interest were monthly mean temperature and mean precipitation, for which the spatial variability was explained using auxiliary information: mean elevation, sea percentage, and lake percentage. We compared three methods for spatial prediction: kriging with external drift (KED), generalized additive models (GAM), and GAM combined with residual kriging (GK). Every interpolation file now has attached statistical key figures describing the bias and the normality of the prediction error. According to the cross-validation results, GAM was the best method for predicting mean temperatures, with only very small differences relative to the other methods. For mean precipitation, KED produced the most accurate predictions, followed by GK. In both cases, there was notable seasonal variation in the statistical skill scores. For the new reference period and future interpolations, KED was chosen as the primary method due to its robustness and accuracy.

Large impacts of climatic warming on growth of boreal forests since 1960.

Abstract: Boreal forests are sensitive to climatic warming, because low temperatures hold back ecosystem processes, such as the mobilization of nitrogen in soils. A greening of the boreal landscape has been observed using remote sensing, and the seasonal amplitude of CO2 in the northern hemisphere has increased, indicating warming effects on ecosystem productivity. However, field observations on responses of ecosystem productivity have been lacking on a large sub-biome scale. Here we report a significant increase in the annual growth of boreal forests in Finland in response to climatic warming, especially since 1990. This finding is obtained by linking meteorological records and forest inventory data on an area between 60° and 70° northern latitude. An additional increase in growth has occurred in response to changes in other drivers, such as forest management, nitrogen deposition and/or CO2 concentration. A similar warming impact can be expected in the entire boreal zone, where warming takes place. Given the large size of the boreal biome – more than ten million km2– important climate feedbacks are at stake, such as the future carbon balance, transpiration and albedo.

New gridded daily climatology of Finland: permutation-based uncertainty estimates and temporal trends in climate

Abstract: Long-term time series of key climate variables with a relevant spatiotemporal resolution are essential for environmental science. Moreover, such spatially continuous data, based on weather observations, are commonly used in, e.g., downscaling and bias correcting of climate model simulations. Here we conducted a comprehensive spatial interpolation scheme where seven climate variables (daily mean, maximum, and minimum surface air temperatures, daily precipitation sum, relative humidity, sea level air pressure, and snow depth) were interpolated over Finland at the spatial resolution of 10 × 10 km2. More precisely, (1) we produced daily gridded time series (FMI_ClimGrid) of the variables covering the period of 1961–2010, with a special focus on evaluation and permutation-based uncertainty estimates, and (2) we investigated temporal trends in the climate variables based on the gridded data. National climate station observations were supplemented by records from the surrounding countries, and kriging interpolation was applied to account for topography and water bodies. For daily precipitation sum and snow depth, a two-stage interpolation with a binary classifier was deployed for an accurate delineation of areas with no precipitation or snow. A robust cross-validation indicated a good agreement between the observed and interpolated values especially for the temperature variables and air pressure, although the effect of seasons was evident. Permutation-based analysis suggested increased uncertainty toward northern areas, thus identifying regions with suboptimal station density. Finally, several variables had a statistically significant trend indicating a clear but locally varying signal of climate change during the last five decades.

Projected changes in thermal seasons and the growing season in Finland

Abstract: The durations of the thermal seasons and the growing season till the end of this century are inferred from projected monthly mean temperatures, separately for the SRES A2 and B1 scenarios. For the baseline period 1971-2000, we use a high-resolution observational data set covering Finland, and an average of the temperature responses simulated by 19 global climate models (GCMs) is added to the observed temperatures to obtain projections for the future. Daily climatological temperatures, needed for the determination of the onset and end dates of the seasons and the effective temperature sum, are derived from the monthly means employing a Fourier algorithm that can reproduce monthly mean temperatures perfectly. Under baseline conditions, there are four thermal seasons everywhere in Finland apart from the elevated area in north-western Lapland. Under the A2 scenario, thermal winter will disappear in the South-western part of the country by the period 2070-2099. Elsewhere winter shortens by 2-4 months. Summer lengthens by slightly over 1 month. Intermediate seasons become longer everywhere except in northernmost Lapland. The thermal growing season lengthens in inland areas by 40-50 days, on the south-western coast even more. The effective temperature sum doubles in the north and increases 1.5-fold in the south. Conditions in Lapland would thus resemble those currently prevailing in southern Finland. Under the B1 scenario the change is smaller, especially in the second half of the century. The robustness of the findings was assessed by considering the differences between the temperature change projections of the various models. The uncertainty in the onset and termination dates was typically of the order of ±2 weeks. Regional downscaling based on regional climate model (RCM) data did not alter the main conclusions. Copyright © 2010 Royal Meteorological Society

Forecasting, Structural Time Series Models and the Kalman Filter

Abstract: In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Rapid Range Shifts of Species Associated with High Levels of Climate Warming

Abstract: The distributions of many terrestrial organisms are currently shifting in latitude or elevation in response to changing climate Using a meta-analysis, we estimated that the distributions of species have recently shifted to higher elevations at a median rate of 110 meters per decade, and to higher latitudes at a median rate of 169 kilometers per decade These rates are approximately two and three times faster than previously reported The distances moved by species are greatest in studies showing the highest levels of warming, with average latitudinal shifts being generally sufficient to track temperature changes However, individual species vary greatly in their rates of change, suggesting that the range shift of each species depends on multiple internal species traits and external drivers of change Rapid average shifts derive from a wide diversity of responses by individual species

Shifting plant phenology in response to global change

Abstract: Plants are finely tuned to the seasonality of their environment, and shifts in the timing of plant activity (i.e. phenology) provide some of the most compelling evidence that species and ecosystems are being influenced by global environmental change. Researchers across disciplines have observed shifting phenology at multiple scales, including earlier spring flowering in individual plants and an earlier spring green-up' of the land surface revealed in satellite images. Experimental and modeling approaches have sought to identify the mechanisms causing these shifts, as well as to make predictions regarding the consequences. Here, we discuss recent advances in several fields that have enabled scaling between species responses to recent climatic changes and shifts in ecosystem productivity, with implications for global carbon cycling.