Contrasting biosphere responses to hydrometeorological extremes: revisiting the 2010 western Russian heatwave

Abstract. Combined droughts and heatwaves are among those compound extreme events that induce severe impacts on the terrestrial biosphere and human health. A record breaking hot and dry compound event hit western Russia in summer 2010 (Russian heatwave, RHW). Events of this kind are relevant from a hydrometeorological perspective, but are also interesting from a biospheric point of view because of their impacts on ecosystems, e.g., reductions in the terrestrial carbon storage. Integrating both perspectives might facilitate our knowledge about the RHW. We revisit the RHW from both a biospheric and a hydrometeorological perspective. We apply a recently developed multivariate anomaly detection approach to a set of hydrometeorological variables, and then to multiple biospheric variables relevant to describe the RHW. One main finding is that the extreme event identified in the hydrometeorological variables leads to multidirectional responses in biospheric variables, e.g., positive and negative anomalies in gross primary production (GPP). In particular, the region of reduced summer ecosystem production does not match the area identified as extreme in the hydrometeorological variables. The reason is that forest-dominated ecosystems in the higher latitudes respond with unusually high productivity to the RHW. Furthermore, the RHW was preceded by an anomalously warm spring, which leads annually integrated to a partial compensation of 54 % (36 % in the preceding spring, 18 % in summer) of the reduced GPP in southern agriculturally dominated ecosystems. Our results show that an ecosystem-specific and multivariate perspective on extreme events can reveal multiple facets of extreme events by simultaneously integrating several data streams irrespective of impact direction and the variables' domain. Our study exemplifies the need for robust multivariate analytic approaches to detect extreme events in both hydrometeorological conditions and associated biosphere responses to fully characterize the effects of extremes, including possible compensatory effects in space and time.

[1]  Xiufeng Wang,et al.  CO2 emissions from the 2010 Russian wildfires using GOSAT data. , 2017, Environmental pollution.

[2]  W. Larcher.  Physiological Plant Ecology: Ecophysiology and Stress Physiology of Functional Groups , 1995 .

[3]  MüllerKlaus-Robert,et al.  From outliers to prototypes , 2006 .

[4]  N. Verhoest,et al.  GLEAM v3: satellite-based land evaporation and root-zone soil moisture , 2016 .

[5]  Ying Fan,et al.  Hydrologic regulation of plant rooting depth , 2017, Proceedings of the National Academy of Sciences.

[6]  S. Rahmstorf,et al.  Increase of extreme events in a warming world , 2011, Proceedings of the National Academy of Sciences.

[7]  T. Holmes,et al.  Global land-surface evaporation estimated from satellite-based observations , 2010 .

[8]  Markus Reichstein,et al.  Detection and attribution of large spatiotemporal extreme events in Earth observation data , 2013, Ecol. Informatics.

[9]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[10]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[11]  S. Seneviratne,et al.  Role of soil moisture versus recent climate change for the 2010 heat wave in western Russia , 2016 .

[12]  Markus Reichstein,et al.  Earlier springs decrease peak summer productivity in North American boreal forests , 2013 .

[13]  Jakob Zscheischler,et al.  A submonthly database for detecting changes in vegetation‐atmosphere coupling , 2015 .

[14]  Markus Reichstein,et al.  Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms , 2016 .

[15]  Joachim Denzler,et al.  Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques , 2016 .

[16]  M. Reichstein,et al.  Drought, Heat, and the Carbon Cycle: a Review , 2018, Current Climate Change Reports.

[17]  D. Easterling,et al.  Changes in climate extremes and their impacts on the natural physical environment , 2012 .

[18]  T. Vesala,et al.  Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis , 2007 .

[19]  S. Seneviratne,et al.  Dependence of drivers affects risks associated with compound events , 2017, Science Advances.

[20]  R. Seager,et al.  The Curious Case of Projected Twenty-First-Century Drying but Greening in the American West. , 2017, Journal of climate.

[21]  Alex J. Cannon,et al.  Wetter summers can intensify departures from natural variability in a warming climate , 2018, Nature Communications.

[22]  Tim R. McVicar,et al.  Global estimation of effective plant rooting depth: Implications for hydrological modeling , 2016 .

[23]  Jeffrey W. White,et al.  The uncertainty of crop yield projections is reduced by improved temperature response functions , 2017, Nature Plants.

[24]  J. Nickerson,et al.  A multivariate exponentially weighted moving average control chart for photovoltaic processes , 2005, Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, 2005..

[25]  S. Seneviratne,et al.  Contrasting response of European forest and grassland energy exchange to heatwaves , 2010 .

[26]  Pascal Yiou,et al.  Asymmetric European summer heat predictability from wet and dry southern winters and springs , 2012 .

[27]  R. Seager,et al.  Blue Water Trade‐Offs With Vegetation in a CO2‐Enriched Climate , 2018 .

[28]  S. Rahmstorf,et al.  Evidence for wave resonance as a key mechanism for generating high-amplitude quasi-stationary waves in boreal summer , 2017, Climate Dynamics.

[29]  T. A. Black,et al.  Reduction in carbon uptake during turn of the century drought in western North America , 2012 .

[30]  Michael Brzoska,et al.  Climate Change and Violent Conflict , 2012, Science.

[31]  K. Haslinger,et al.  Space‐Time Patterns of Meteorological Drought Events in the European Greater Alpine Region Over the Past 210 Years , 2017 .

[32]  A. Teuling,et al.  Disentangling the response of forest and grassland energy exchange to heatwaves under idealized land-atmosphere coupling , 2014 .

[33]  Zhiguo Cao,et al.  Hydrologic regulation of plant rooting depth: Pay attention to the widespread scenario with intense seasonal groundwater table fluctuation , 2018, Proceedings of the National Academy of Sciences.

[34]  Atul K. Jain,et al.  Compensatory water effects link yearly global land CO2 sink changes to temperature , 2017, Nature.

[35]  M. Beekmann,et al.  Atmospheric impacts of the 2010 Russian wildfires: integrating modelling and measurements of an extreme air pollution episode in the Moscow region , 2011 .

[36]  S. Schubert,et al.  Northern Eurasian Heat Waves and Droughts , 2014 .

[37]  Tao Zhang,et al.  Was there a basis for anticipating the 2010 Russian heat wave? , 2011 .

[38]  Melinda D. Smith.  An ecological perspective on extreme climatic events: a synthetic definition and framework to guide future research , 2011 .

[39]  W. Oechel,et al.  Impacts of droughts and extreme-temperature events on gross primary production and ecosystem respiration: a systematic assessment across ecosystems and climate zones , 2017 .

[40]  Stefan Metzger,et al.  Detecting impacts of extreme events with ecological in situ monitoring networks , 2017 .

[41]  Markus Reichstein,et al.  Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts , 2015, Global change biology.

[42]  Public Perception of Climate Change and the New Climate Dice , 2012, 1204.1286.

[43]  J. Janowiak,et al.  The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present) , 2003 .

[44]  N. Ramankutty,et al.  Influence of extreme weather disasters on global crop production , 2016, Nature.

[45]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .

[46]  S. Running,et al.  Analysing the spatio-temporal impacts of the 2003 and 2010 extreme heatwaves on plant productivity in Europe , 2014 .

[47]  P. Ciais,et al.  Europe-wide reduction in primary productivity caused by the heat and drought in 2003 , 2005, Nature.

[48]  J. Peters,et al.  Quantifying changes in climate variability and extremes: Pitfalls and their overcoming , 2015 .

[49]  Martin F. Lambert,et al.  A compound event framework for understanding extreme impacts , 2014 .

[50]  N. Eisenhauer,et al.  Plant diversity maintains long-term ecosystem productivity under frequent drought by increasing short-term variation. , 2017, Ecology.

[51]  Diego G. Miralles,et al.  Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation , 2014 .

[52]  Hans Joachim Schellnhuber,et al.  Quasiresonant amplification of planetary waves and recent Northern Hemisphere weather extremes , 2013, Proceedings of the National Academy of Sciences.

[53]  Nathaniel A. Brunsell,et al.  Warm spring reduced carbon cycle impact of the 2012 US summer drought , 2016, Proceedings of the National Academy of Sciences.

[54]  H. Storch,et al.  Statistical Analysis in Climate Research , 2000 .

[55]  P. Jones,et al.  REPRESENTING TWENTIETH CENTURY SPACE-TIME CLIMATE VARIABILITY. , 1998 .

[56]  M. Matsueda.  Predictability of Euro‐Russian blocking in summer of 2010 , 2011 .

[57]  C. Tucker,et al.  The 2010 Russian drought impact on satellite measurements of solar-induced chlorophyll fluorescence: Insights from modeling and comparisons with parameters derived from satellite reflectances , 2015 .

[58]  E. Parzen.  On Estimation of a Probability Density Function and Mode , 1962 .

[59]  KriegelHans-Peter,et al.  A survey on unsupervised outlier detection in high-dimensional numerical data , 2012 .

[60]  Shaoqiang Wang,et al.  Detection of Positive Gross Primary Production Extremes in Terrestrial Ecosystems of China During 1982–2015 and Analysis of Climate Contribution , 2018, Journal of Geophysical Research: Biogeosciences.

[61]  Klaus-Robert Müller,et al.  From outliers to prototypes: Ordering data , 2006, Neurocomputing.

[62]  G. Henebry,et al.  Land surface anomalies preceding the 2010 Russian heat wave and a link to the North Atlantic oscillation , 2014 .

[63]  M. Heimann,et al.  Contrasting and interacting changes in simulated spring and summer carbon cycle extremes in European ecosystems , 2017 .

[64]  Mathieu Vrac,et al.  Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy) , 2017 .

[65]  Charles W. Champ,et al.  A multivariate exponentially weighted moving average control chart , 1992 .

[66]  S. Seneviratne,et al.  Investigating soil moisture-climate interactions in a changing climate: A review , 2010 .

[67]  Bofu Yu,et al.  The effect of vapor pressure deficit on water use efficiency at the subdaily time scale , 2014 .

[68]  Benjamin Lloyd-Hughes,et al.  A spatio‐temporal structure‐based approach to drought characterisation , 2012 .

[69]  Erich Barke,et al.  Hierarchical partitioning , 1996, Proceedings of International Conference on Computer Aided Design.

[70]  Hans-Peter Kriegel,et al.  A survey on unsupervised outlier detection in high‐dimensional numerical data , 2012, Stat. Anal. Data Min..

[71]  Ricardo García-Herrera,et al.  The Hot Summer of 2010: Redrawing the Temperature Record Map of Europe , 2011, Science.

[72]  S. Seneviratne,et al.  Climate extremes and the carbon cycle , 2013, Nature.