Czech Academy of Sciences, Global Change Research Institute

ABSTRACT Radiocarbon ( 14 C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14 C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14 C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14 C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14 C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14 C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

To address challenges associated with climate resilience, health and well-being in urban areas, current policy platforms are shifting their focus from ecosystem-based to nature-based solutions (NBS), broadly defined as solutions to societal challenges that are inspired and supported by nature. NBS result in the provision of co-benefits, such as the improvement of place attractiveness, of health and quality of life, and creation of green jobs. Few frameworks exist for acknowledging and assessing the value of such co-benefits of NBS and to guide cross-sectoral project and policy design and implementation. In this paper, we firstly developed a holistic framework for assessing co-benefits (and costs) of NBS across elements of socio-cultural and socio-economic systems, biodiversity, ecosystems and climate. The framework was guided by a review of over 1700 documents from science and practice within and across 10 societal challenges relevant to cities globally. We found that NBS can have environmental, social and economic co-benefits and/or costs both within and across these 10 societal challenges. On that base, we develop and propose a seven-stage process for situating co-benefit assessment within policy and project implementation. The seven stages include: 1) identify problem or opportunity; 2) select and assess NBS and related actions; 3) design NBS implementation processes; 4) implement NBS; 5) frequently engage stakeholders and communicate co-benefits; 6) transfer and upscale NBS; and 7) monitor and evaluate co-benefits across all stages. We conclude that the developed framework together with the seven-stage co-benefit assessment process represent a valuable tool for guiding thinking and identifying the multiple values of NBS implementation.

Abstract. With the eddy covariance (EC) technique, net fluxes of carbon dioxide (CO2) and other trace gases as well as water and energy fluxes can be measured at the ecosystem level. These flux measurements are a main source for understanding biosphere–atmosphere interactions and feedbacks through cross-site analysis, model–data integration, and upscaling. The raw fluxes measured with the EC technique require extensive and laborious data processing. While there are standard tools1 available in an open-source environment for processing high-frequency (10 or 20 Hz) data into half-hourly quality-checked fluxes, there is a need for more usable and extensible tools for the subsequent post-processing steps. We tackled this need by developing the REddyProc package in the cross-platform language R that provides standard CO2-focused post-processing routines for reading (half-)hourly data from different formats, estimating the u* threshold, as well as gap-filling, flux-partitioning, and visualizing the results. In addition to basic processing, the functions are extensible and allow easier integration in extended analysis than current tools. New features include cross-year processing and a better treatment of uncertainties. A comparison of REddyProc routines with other state-of-the-art tools resulted in no significant differences in monthly and annual fluxes across sites. Lower uncertainty estimates of both u* and resulting gap-filled fluxes by 50 % with the presented tool were achieved by an improved treatment of seasons during the bootstrap analysis. Higher estimates of uncertainty in daytime partitioning (about twice as high) resulted from a better accounting for the uncertainty in estimates of temperature sensitivity of respiration. The provided routines can be easily installed, configured, and used. Hence, the eddy covariance community will benefit from the REddyProc package, allowing easier integration of standard post-processing with extended analysis. 1http://fluxnet.fluxdata.org/2017/10/10/toolbox-a-rolling-list-of-softwarepackages-for-flux-related-data-processing/, last access: 17 August 2018

Many environmental challenges are exacerbated within the urban landscape, such as stormwater runoff and flood risk, chemical and particulate pollution of urban air, soil and water, the urban heat island, and summer heat waves. Urban trees, and the urban forest as a whole, can be managed to have an impact on the urban water, heat, carbon and pollution cycles. However, there is an increasing need for empirical evidence as to the magnitude of the impacts, both beneficial and adverse, that urban trees can provide and the role that climatic region and built landscape circumstance play in modifying those impacts. This special section presents new research that advances our knowledge of the ecological and environmental services provided by the urban forest. The 14 studies included provide a global perspective on the role of trees in towns and cities from five continents. Some studies provide evidence for the cooling benefit of the local microclimate in urban green space with and without trees. Other studies focus solely on the cooling benefit of urban tree transpiration at a mesoscale or on cooling from canopy shade at a street and pedestrian scale. Other studies are concerned with tree species differences in canopy interception of rainfall, water uptake from biofilter systems, and water quality improvements through nutrient uptake from stormwater runoff. Research reported here also considers both the positive and the negative impacts of trees on air quality, through the role of trees in removing air pollutants such as ozone as well as in releasing potentially harmful volatile organic compounds and allergenic particulates. A transdisciplinary framework to support future urban forest research is proposed to better understand and communicate the role of urban trees in urban biogeochemical cycles that are highly disturbed, highly managed, and of paramount importance to human health and well-being.

Abstract Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990–2009) from two observation‐based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon‐climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation‐based data that show little IAV and trend, while the process‐based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation‐based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.

With rising demand for biomass, cropland expansion and intensification represent the main strategies to boost agricultural production, but are also major drivers of biodiversity decline. We investigate the consequences of attaining equal global production gains by 2030, either by cropland expansion or intensification, and analyse their impacts on agricultural markets and biodiversity. We find that both scenarios lead to lower crop prices across the world, even in regions where production decreases. Cropland expansion mostly affects biodiversity hotspots in Central and South America, while cropland intensification threatens biodiversity especially in Sub-Saharan Africa, India and China. Our results suggest that production gains will occur at the costs of biodiversity predominantly in developing tropical regions, while Europe and North America benefit from lower world market prices without putting their own biodiversity at risk. By identifying hotspots of potential future conflicts, we demonstrate where conservation prioritization is needed to balance agricultural production with conservation goals.

The Paris Agreement aims to limit global mean temperature rise this century to well below 2 °C above pre-industrial levels. This target has wide-ranging implications for Europe and its cities, which are the source of substantial greenhouse gas emissions. This paper reports the state of local planning for climate change by collecting and analysing information about local climate mitigation and adaptation plans across 885 urban areas of the EU-28. A typology and framework for analysis was developed that classifies local climate plans in terms of their alignment with spatial (local, national and international) and other climate related policies. Out of eight types of local climate plans identified in total we document three types of stand-alone local climate plans classified as type A1 (autonomously produced plans), A2 (plans produced to comply with national regulations) or A3 (plans developed for international climate networks). There is wide variation among countries in the prevalence of local climate plans, with generally more plans developed by central and northern European cities. Approximately 66% of EU cities have a type A1, A2, or A3 mitigation plan, 26% an adaptation plan, and 17% a joint adaptation and mitigation plan, while about 33% lack any form of stand-alone local climate plan (i.e. what we classify as A1, A2, A3 plans). Mitigation plans are more numerous than adaptation plans, but planning for mitigation does not always precede planning for adaptation. Our analysis reveals that city size, national legislation, and international networks can influence the development of local climate plans. We found that size does matter as about 80% of the cities with above 500,000 inhabitants have a comprehensive and stand-alone mitigation and/or an adaptation plan (A1). Cities in four countries with national climate legislation (A2), i.e. Denmark, France, Slovakia and the United Kingdom, are nearly twice as likely to produce local mitigation plans, and five times more likely to produce local adaptation plans, compared to cities in countries without such legislation. A1 and A2 mitigation plans are particularly numerous in Denmark, Poland, Germany, and Finland; while A1 and A2 adaptation plans are prevalent in Denmark, Finland, UK and France. The integration of adaptation and mitigation is country-specific and can mainly be observed in two countries where local climate plans are compulsory, i.e. France and the UK. Finally, local climate plans produced for international climate networks (A3) are mostly found in the many countries where autonomous (type A1) plans are less common. This is the most comprehensive analysis of local climate planning to date. The findings are of international importance as they will inform and support decision-making towards climate planning and policy development at national, EU and global level being based on the most comprehensive and up-to-date knowledge of local climate planning available to date.

Abstract. There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on long duration records and flood-rich and flood-poor periods rather than on short duration flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.

Abstract Twenty-five years since foundational publications on valuing ecosystem services for human well-being 1,2 , addressing the global biodiversity crisis 3 still implies confronting barriers to incorporating nature’s diverse values into decision-making. These barriers include powerful interests supported by current norms and legal rules such as property rights, which determine whose values and which values of nature are acted on. A better understanding of how and why nature is (under)valued is more urgent than ever 4 . Notwithstanding agreements to incorporate nature’s values into actions, including the Kunming-Montreal Global Biodiversity Framework (GBF) 5 and the UN Sustainable Development Goals 6 , predominant environmental and development policies still prioritize a subset of values, particularly those linked to markets, and ignore other ways people relate to and benefit from nature 7 . Arguably, a ‘values crisis’ underpins the intertwined crises of biodiversity loss and climate change 8 , pandemic emergence 9 and socio-environmental injustices 10 . On the basis of more than 50,000 scientific publications, policy documents and Indigenous and local knowledge sources, the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) assessed knowledge on nature’s diverse values and valuation methods to gain insights into their role in policymaking and fuller integration into decisions 7,11 . Applying this evidence, combinations of values-centred approaches are proposed to improve valuation and address barriers to uptake, ultimately leveraging transformative changes towards more just (that is, fair treatment of people and nature, including inter- and intragenerational equity) and sustainable futures.

To date, projections of European crop yields under climate change have been based almost entirely on the outputs of crop-growth models. While this strategy can provide good estimates of the effects of climatic factors, soil conditions and management on crop yield, these models usually do not capture all of the important aspects related to crop management, or the relevant environmental factors. Moreover, crop-simulation studies often have severe limitations with respect to the number of crops covered or the spatial extent. The present study, based on agroclimatic indices, provides a general picture of agroclimatic conditions in western and central Europe (study area lays between 8.5°W–27°E and 37–63.5°N), which allows for a more general assessment of climate-change impacts. The results obtained from the analysis of data from 86 different sites were clustered according to an environmental stratification of Europe. The analysis was carried for the baseline (1971–2000) and future climate conditions (time horizons of 2030, 2050 and with a global temperature increase of 5 °C) based on outputs of three global circulation models. For many environmental zones, there were clear signs of deteriorating agroclimatic condition in terms of increased drought stress and shortening of the active growing season, which in some regions become increasingly squeezed between a cold winter and a hot summer. For most zones the projections show a marked need for adaptive measures to either increase soil water availability or drought resistance of crops. This study concludes that rainfed agriculture is likely to face more climate-related risks, although the analyzed agroclimatic indicators will probably remain at a level that should permit rainfed production. However, results suggests that there is a risk of increasing number of extremely unfavorable years in many climate zones, which might result in higher interannual yield variability and constitute a challenge for proper crop management.

In this paper volatile organic compounds (VOCs) from durum wheat cultivars and landraces were analyzed using PTR-TOF-MS. The aim was to characterize the VOC's profile of the wholemeal flour and of the kernel to find out if any VOCs were specific to varieties and sample matrices. The VOC data is accompanied by SDS-PAGE analyses of the storage proteins (gliadins and glutenins). Statistical analyses was carried out both on the signals obtained by MS and on the protein profiles. The difference between the VOC profile of two cultivars or two preparations of the same sample - matrices, in this case kernel vs wholemeal flour - can be very subtle; the high resolution of PTR-TOF-MS - down to levels as low as pptv - made it possible to recognize these differences. The effects of grinding on the VOC profiles were analyzed using SIMPER and Tanglegram statistical methods. Our results show that it is possible describe samples using VOC profiles and protein data.

Abstract. Despite recent research identifying a clear anthropogenic impact on glacier recession, the effect of recent climate change on glacier-related hazards is at present unclear. Here we present the first global spatio-temporal assessment of glacial lake outburst floods (GLOFs) focusing explicitly on lake drainage following moraine dam failure. These floods occur as mountain glaciers recede and downwaste. GLOFs can have an enormous impact on downstream communities and infrastructure. Our assessment of GLOFs associated with the rapid drainage of moraine-dammed lakes provides insights into the historical trends of GLOFs and their distributions under current and future global climate change. We observe a clear global increase in GLOF frequency and their regularity around 1930, which likely represents a lagged response to post-Little Ice Age warming. Notably, we also show that GLOF frequency and regularity – rather unexpectedly – have declined in recent decades even during a time of rapid glacier recession. Although previous studies have suggested that GLOFs will increase in response to climate warming and glacier recession, our global results demonstrate that this has not yet clearly happened. From an assessment of the timing of climate forcing, lag times in glacier recession, lake formation and moraine-dam failure, we predict increased GLOF frequencies during the next decades and into the 22nd century.

In an increasingly urbanized world, air pollution mitigation is considered one of most important issues in city planning. Urban trees help to improve air quality by facilitating widespread deposition of various gases and particles through the provision of large surface areas as well as through their influence on microclimate and air turbulence. However, many of these trees produce wind‐dispersed pollen (a known allergen) and emit a range of gaseous substances that take part in photochemical reactions – all of which can negatively affect air quality. The degree to which these air‐quality impacts are manifested depends on species‐specific tree properties: that is, their “traits”. We summarize and discuss the current knowledge on how such traits affect urban air pollution. We also present aggregated traits of some of the most common tree species in Europe, which can be used as a decision‐support tool for city planning and for improving urban air‐quality models.

Abstract In view of future changes in climate, it is important to better understand how different plant functional groups ( PFG s) respond to warmer and drier conditions, particularly in temperate regions where an increase in both the frequency and severity of drought is expected. The patterns and mechanisms of immediate and delayed impacts of extreme drought on vegetation growth remain poorly quantified. Using satellite measurements of vegetation greenness, in‐situ tree‐ring records, eddy‐covariance CO 2 and water flux measurements, and meta‐analyses of source water of plant use among PFG s, we show that drought legacy effects on vegetation growth differ markedly between forests, shrubs and grass across diverse bioclimatic conditions over the temperate Northern Hemisphere. Deep−rooted forests exhibit a drought legacy response with reduced growth during up to 4 years after an extreme drought, whereas shrubs and grass have drought legacy effects of approximately 2 years and 1 year, respectively. Statistical analyses partly attribute the differences in drought legacy effects among PFG s to plant eco‐hydrological properties (related to traits), including plant water use and hydraulic responses. These results can be used to improve the representation of drought response of different PFG s in land surface models, and assess their biogeochemical and biophysical feedbacks in response to a warmer and drier climate.

Root exudates comprise a large variety of compounds released by plants into the rhizosphere, including low-molecular-weight primary metabolites (particularly saccharides, amino acids and organic acids) and secondary metabolites (phenolics, flavonoids and terpenoids). Changes in exudate composition could have impacts on the plant itself, on other plants, on soil properties (e.g. amount of soil organic matter), and on soil organisms. The effects of drought on the composition of root exudates, however, have been rarely studied. We used an ecometabolomics approach to identify the compounds in the exudates of Quercus ilex (holm oak) under an experimental drought gradient and subsequent recovery. Increasing drought stress strongly affected the composition of the exudate metabolome. Plant exudates under drought consisted mainly of secondary metabolites (71% of total metabolites) associated with plant responses to drought stress, whereas the metabolite composition under recovery shifted towards a dominance of primary metabolites (81% of total metabolites). These results strongly suggested that roots exude the most abundant root metabolites. The exudates were changed irreversibly by the lack of water under extreme drought conditions, and the plants could not recover.

Abstract Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system 1 . Remote-sensing estimates to quantify carbon losses from global forests 2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced 6 and satellite-derived approaches 2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea 2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Monitoring agricultural systems becomes increasingly important in the context of global challenges like climate change, biodiversity loss, population growth, and the rising demand for agricultural products. High-resolution, national-scale maps of agricultural land are needed to develop strategies for future sustainable agriculture. However, the characterization of agricultural land cover over large areas and for multiple years remains challenging due to the locally diverse and temporally variable characteristics of cultivated land. We here propose a workflow for generating national agricultural land cover maps on a yearly basis that accounts for varying environmental conditions. We tested the approach by mapping 24 agricultural land cover classes in Germany for the three years 2017, 2018, and 2019, in which the meteorological conditions strongly differed. We used a random forest classifier and dense time series data from Sentinel-2 and Landsat 8 in combination with monthly Sentinel-1 composites and environmental data and evaluated the relative importance of optical, radar, and environmental data. Our results show high overall accuracy and plausible class accuracies for the most dominant crop types across different years despite the strong inter-annual meteorological variability and the presence of drought and non-drought years. The maps show high spatial consistency and good delineation of field parcels. Combining optical, SAR, and environmental data increased overall accuracies by 6% to 10% compared to single sensor approaches, in which optical data outperformed SAR. Overall accuracy ranged between 78% and 80%, and the mapped areas aligned well with agricultural statistics at the regional and national level. Based on the multi-year dataset we mapped major crop sequences of cereals and leaf crops. Most crop sequences were dominated by winter cereals followed by summer cereals. Monocultures of summer cereals were mainly revealed in the Northwest of Germany. We showcased that high spatial and thematic detail in combination with annual mapping will stimulate research on crop cycles and studies to assess the impact of environmental policies on management decisions. Our results demonstrate the capabilities of integrated optical time series and SAR data in combination with variables describing local and seasonal environmental conditions for annual large-area crop type mapping.

Abstract. The COST (European Cooperation in Science and Technology) Action ES0601: advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random independent break-type inhomogeneities with normally distributed breakpoint sizes were added to the simulated datasets. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study. After the deadline at which details of the imposed inhomogeneities were revealed, 22 additional solutions were submitted. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training the users on homogenization software was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that automatic algorithms can perform as well as manual ones.