After this paper was published, one of the readers of our paper pointed out that CA-Est and FI-Van did not have any T water data.Therefore, for each panel in figure 4, the mutual information score for T water and CA-Est will now be replaced with a white color.The same will be carried out for T water and FI-Van.A brief sentence has also been added at the end of the figure 4 caption to indicate lack of T water data for CA-Est and FI-Van.This correction does not affect our results.We apologize for any inconvenience these errors may have caused.

Accounting for temporal changes in carbon dioxide (CO _2 ) effluxes from freshwaters remains a challenge for global and regional carbon budgets. Here, we synthesize 171 site-months of flux measurements of CO _2 based on the eddy covariance method from 13 lakes and reservoirs in the Northern Hemisphere, and quantify dynamics at multiple temporal scales. We found pronounced sub-annual variability in CO _2 flux at all sites. By accounting for diel variation, only 11% of site-months were net daily sinks of CO _2 . Annual CO _2 emissions had an average of 25% (range 3%–58%) interannual variation. Similar to studies on streams, nighttime emissions regularly exceeded daytime emissions. Biophysical regulations of CO _2 flux variability were delineated through mutual information analysis. Sample analysis of CO _2 fluxes indicate the importance of continuous measurements. Better characterization of short- and long-term variability is necessary to understand and improve detection of temporal changes of CO _2 fluxes in response to natural and anthropogenic drivers. Our results indicate that existing global lake carbon budgets relying primarily on daytime measurements yield underestimates of net emissions.

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Geophysical Research Letters. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]Diel to interannual variation in carbon dioxide emissions from lakes and reservoirsAuthorsMalgorzataGolubiDNikaanKoupaei-AbyazaniiDTimoVesalaIvanMammarellaiDAnneOjalaGilBohreriDGesa AWeyhenmeyeriDPeter D.BlankeniDWernerEugsteriDFranziskaKoebschJiquanCheniDKevin P.CzajkowskiiDChandrashekharDeshmukhFrédéricGuérinJouniHeiskanenElynHumphreysiDAndersJonssoniDJanKarlssoniDGeorge W.KlingiDXuhuiLeeiDHepingLiuAnnaleaLohilaiDErik JohannesLundiniDTimothy HectorMorinEvaPodgrajsekMariaProvenzaleAnnaRutgersoniDTorstenSachsiDErikSahléeDominiqueSerçaiDChangliangShaoiDChristopherSpenceIan B.StrachaniDWeiXiaoiDAnkur RashmikantDesaiiDSee all authors Malgorzata GolubiDDundalk Institute of TechnologyiDhttps://orcid.org/0000-0001-9361-0331view email addressThe email was not providedcopy email addressNikaan Koupaei-AbyazaniiDUniversity of Wisconsin-MadisoniDhttps://orcid.org/0000-0001-6982-230Xview email addressThe email was not providedcopy email addressTimo VesalaUniversity of Helsinki, Institute for Atmospheric and Earth System Researchview email addressThe email was not providedcopy email addressIvan MammarellaiDUniversity of HelsinkiiDhttps://orcid.org/0000-0002-8516-3356view email addressThe email was not providedcopy email addressAnne OjalaNatural Resources Instituteview email addressThe email was not providedcopy email addressGil BohreriDOhio State UniversityiDhttps://orcid.org/0000-0002-9209-9540view email addressThe email was not providedcopy email addressGesa A WeyhenmeyeriDEcology and Genetics/LimnologyiDhttps://orcid.org/0000-0002-4013-2281view email addressThe email was not providedcopy email addressPeter D. BlankeniDUniversity of Colorado BoulderiDhttps://orcid.org/0000-0002-7405-2220view email addressThe email was not providedcopy email addressWerner EugsteriDETH ZurichiDhttps://orcid.org/0000-0001-6067-0741view email addressThe email was not providedcopy email addressFranziska KoebschGFZ German Research Centre for Geosciencesview email addressThe email was not providedcopy email addressJiquan CheniDMichigan State UniversityiDhttps://orcid.org/0000-0003-0761-9458view email addressThe email was not providedcopy email addressKevin P. CzajkowskiiDUniversity of ToledoiDhttps://orcid.org/0000-0002-0472-4204view email addressThe email was not providedcopy email addressChandrashekhar DeshmukhAPRIL Asiaview email addressThe email was not providedcopy email addressFrédéric GuérinIRD - Marseille, France.view email addressThe email was not providedcopy email addressJouni HeiskanenUniversity of Helsinkiview email addressThe email was not providedcopy email addressElyn HumphreysiDCarleton UniversityiDhttps://orcid.org/0000-0002-5397-2802view email addressThe email was not providedcopy email addressAnders JonssoniDDepartment of Ecology and Environmental ScienceiDhttps://orcid.org/0000-0002-0807-0201view email addressThe email was not providedcopy email addressJan KarlssoniDUmea UniversityiDhttps://orcid.org/0000-0001-5730-0694view email addressThe email was not providedcopy email addressGeorge W. KlingiDUniversity of Michigan-Ann ArboriDhttps://orcid.org/0000-0002-6349-8227view email addressThe email was not providedcopy email addressXuhui LeeiDYale University, School of Forestry and Environmental StudiesiDhttps://orcid.org/0000-0003-1350-4446view email addressThe email was not providedcopy email addressHeping LiuWashington State Universityview email addressThe email was not providedcopy email addressAnnalea LohilaiDFinnish Meteorological InstituteiDhttps://orcid.org/0000-0003-3541-672Xview email addressThe email was not providedcopy email addressErik Johannes LundiniDSwedish Polar Research SecretariatiDhttps://orcid.org/0000-0002-3785-8305view email addressThe email was not providedcopy email addressTimothy Hector MorinState University of New York College of Environmental Science and Forestryview email addressThe email was not providedcopy email addressEva PodgrajsekOX2view email addressThe email was not providedcopy email addressMaria ProvenzaleUniversity of Helsinkiview email addressThe email was not providedcopy email addressAnna RutgersoniDUppsala UniversityiDhttps://orcid.org/0000-0001-7656-1881view email addressThe email was not providedcopy email addressTorsten SachsiDHelmholtz Centre Potsdam - German Research Centre for Geosciences (GFZ)iDhttps://orcid.org/0000-0002-9959-4771view email addressThe email was not providedcopy email addressErik SahléeEarth Sciencesview email addressThe email was not providedcopy email addressDominique SerçaiDLaboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, FranceiDhttps://orcid.org/0000-0001-8688-1440view email addressThe email was not providedcopy email addressChangliang ShaoiDInstitute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural SciencesiDhttps://orcid.org/0000-0002-4968-8577view email addressThe email was not providedcopy email addressChristopher SpenceEnvironment and Climate Change Canadaview email addressThe email was not providedcopy email addressIan B. StrachaniDMcGill UniversityiDhttps://orcid.org/0000-0001-6457-5530view email addressThe email was not providedcopy email addressWei XiaoiDNanjing University of Information Science and TechnologyiDhttps://orcid.org/0000-0002-9199-2177view email addressThe email was not providedcopy email addressAnkur Rashmikant DesaiiDCorresponding Author• Submitting AuthorUniversity of Wisconsin-MadisoniDhttps://orcid.org/0000-0002-5226-6041view email addressThe email was not providedcopy email address

Lakes are significant emitters of methane to the atmosphere, and thus are important components of the global methane budget. Methane is typically produced in lake sediments, with the rate of methane production being strongly temperature dependent. Local and regional studies highlight the risk of increasing methane production under future climate change, but a global estimate is not currently available. Here, we project changes in global lake bottom temperatures and sediment methane production rates from 1901 to 2099. By the end of the 21st century, lake bottom temperatures are projected to increase globally, by an average of 0.86-2.60°C under Representative Concentration Pathways (RCPs) 2.6-8.5, with greater warming projected at lower latitudes. This future warming of bottom waters will likely result in an increase in methane production rates of 13%-40% by the end of the century, with many low-latitude lakes experiencing an increase of up to 17 times the historical (1970-1999) global average under RCP 8.5. The projected increase in methane production will likely lead to higher emissions from lakes, although the exact magnitude of the emission increase requires more detailed regional studies.

Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various Representative Greenhouse Gas Concentration Pathways, all consistently bias-corrected on a 0.5° × 0.5° global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and for nearly 17,500 lakes using uncalibrated models and forcing data from the global grid where lakes are present. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

Accounting for temporal changes in carbon dioxide (CO2) emissions from freshwaters remains a challenge for global and regional carbon budgets. Here, we synthesize 171 site-months of e...

Lakes are an important component of the global weather and climate system, but the modeling of their thermal regimes has shown large uncertainties due to the highly diverse lake properties and model configurations. Here, we evaluate the algorithms of four key lake thermal processes including turbulent heat fluxes, wind‐driven mixing, light extinction, and snow density, using a highly diverse lake data set provided by the Inter‐Sectoral Impact Model Intercomparison Project (ISIMIP) 2a lake sector. Algorithm codes are configured and run separately within the same parent model to rule out any interference from factors apart from the algorithms examined. Evaluations are based on both simulation accuracy and recalibration complexity for application to global lakes. For turbulent heat fluxes, the non‐Monin–Obukhov similarity (MOS) based, more simplified algorithms perform better in predicting lake epilimnion temperatures and achieve high convergence in the values of the calibrated parameters. For wind‐driven mixing, a two‐algorithm strategy considering lake shape and season is suggested with the regular mixing algorithm used for spring and earlier summer and the mixing‐enhanced algorithm for summer steady stratification and fall overturn periods. There are no evident differences in the simulated thermocline depths using different light extinction algorithms or the observation. Finally, for lake ice phenology, an optimal algorithm is decided for most northern lakes while the Arctic lakes require separate consideration. Our study provides highly practical guides for improving 1‐D lake models and feasible parameterization strategies to better simulate global lake thermal regimes.

Lake ecosystems are jeopardized by the impacts of climate change on ice seasonality and water temperatures. Yet historical simulations have not been used to formally attribute changes in lake ice and temperature to anthropogenic drivers. In addition, future projections of these properties are limited to individual lakes or global simulations from single lake models. Here we uncover the human imprint on lakes worldwide using hindcasts and projections from five lake models. Reanalysed trends in lake temperature and ice cover in recent decades are extremely unlikely to be explained by pre-industrial climate variability alone. Ice-cover trends in reanalysis are consistent with lake model simulations under historical conditions, providing attribution of lake changes to anthropogenic climate change. Moreover, lake temperature, ice thickness and duration scale robustly with global mean air temperature across future climate scenarios (+0.9 °C °Cair–1, –0.033 m °Cair–1 and –9.7 d °Cair–1, respectively). These impacts would profoundly alter the functioning of lake ecosystems and the services they provide. Anthropogenic climate change is impacting the temperature and ice cover of lakes across the globe, according to an attribution analysis based on hindcasts and projections from lake models.

One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 ± 7.0 days earlier and end 11.3 ± 4.7 days later by the end of this century. It is very likely that this 33.3 ± 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely.

Lake ecosystems, and the organisms that live within them, are vulnerable to temperature change 1 – 5 , including the increased occurrence of thermal extremes 6 . However, very little is known about lake heatwaves—periods of extreme warm lake surface water temperature—and how they may change under global warming. Here we use satellite observations and a numerical model to investigate changes in lake heatwaves for hundreds of lakes worldwide from 1901 to 2099. We show that lake heatwaves will become hotter and longer by the end of the twenty-first century. For the high-greenhouse-gas-emission scenario (Representative Concentration Pathway (RCP) 8.5), the average intensity of lake heatwaves, defined relative to the historical period (1970 to 1999), will increase from 3.7 ± 0.1 to 5.4 ± 0.8 degrees Celsius and their average duration will increase dramatically from 7.7 ± 0.4 to 95.5 ± 35.3 days. In the low-greenhouse-gas-emission RCP 2.6 scenario, heatwave intensity and duration will increase to 4.0 ± 0.2 degrees Celsius and 27.0 ± 7.6 days, respectively. Surface heatwaves are longer-lasting but less intense in deeper lakes (up to 60 metres deep) than in shallower lakes during both historic and future periods. As lakes warm during the twenty-first century 7 , 8 , their heatwaves will begin to extend across multiple seasons, with some lakes reaching a permanent heatwave state. Lake heatwaves are likely to exacerbate the adverse effects of long-term warming in lakes and exert widespread influence on their physical structure and chemical properties. Lake heatwaves could alter species composition by pushing aquatic species and ecosystems to the limits of their resilience. This in turn could threaten lake biodiversity 9 and the key ecological and economic benefits that lakes provide to society.

Lakes have important influence on weather and climate from local to global scales. However, their prediction using numerical models is notoriously difficult because lakes are highly heterogeneous across the globe, but observations are sparse. Here, we assessed the performance of a 1‐D lake model in simulating the thermal structures of 58 lakes with diverse morphometric and geographic characteristics by following the phase 2a local lake protocol of the Intersectoral Impact Model Intercomparison Project (ISIMIP2a). After calibration, the root‐mean‐square errors (RMSE) were below 2°C for 70% and 75% of the lakes for epilimnion and full‐profile temperature simulations, with an average of 1.71°C and 1.43°C, respectively. The model performance mainly depended on lake shape rather than location, supporting the possibility of grouping model parameters by lake shape for global applications. Furthermore, through machine‐learning based parameter sensitivity tests, we identified turbulent heat fluxes, wind‐driven mixing, and water transparency as the major processes controlling lake thermal and mixing regimes. Snow density was also important for modeling the ice phenology of high‐latitude lakes. The relative influence of the key processes and the corresponding parameters mainly depended on lake latitude and depth. Turbulent heat fluxes showed a decreasing importance in affecting epilimnion temperature with increasing latitude. Wind‐driven mixing was less influential to lake stratification for deeper lakes while the impact of light extinction, on the contrary, showed a positive correlation with lake depth. Our findings may guide improvements in 1‐D lake model parameterizations to achieve higher fidelity in simulating global lake thermal dynamics.

Heat uptake is a key variable for understanding Earth system response to greenhouse gas forcing. Recent assessments highlighted that most of the excess energy is stored in the oceans, whereas the land, atmosphere and ice melt take up smaller amounts. However, despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique combination of global-scale lake models, global hydrological models and Earth system models to, for the first time, quantify global heat uptake by lakes, reservoirs and rivers over the industrial period (1900-2020). We use a total of 16 different simulations of global-scale lake models and global hydrological models driven by the same bias-corrected climate forcing from four different global climate models, conducted within the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). The model output is combined with reservoir and lake data from the Global Reservoir and Dam (GRanD) database and HydroLAKES. Total inland water heat uptake in the industrial period amounts to 2.8 ± 4.3x1020 J by the end of the period, with the largest uptake realised after 1990. The overall uptake is dominated by warming of natural lakes (2.9 ± 2.0x1020 J, the multi-model mean and standard deviation; 103% of total inland water heat uptake), followed by reservoir warming (5.9 ± 2.7x1018 J; 2.1%). The multi-model mean heat uptake by rivers contributes negatively to the total heat uptake (-0.15 ± 4.3x1020 J; -5.3%), but encompasses a large uncertainty originating from the river storage term, simulated by the global hydrological models. The global picture of positive heat uptake by natural lakes is confirmed at the regional scale in the major lake regions by all global-scale lake model and global climate model combinations. The heat uptake by inland waters makes up ~3.2% of continental heat uptake reported in the IPCC AR5 (2013). The rapid increase in dam construction and resulting reservoir expansion in the second half of the 20th century causes a heat redistribution from ocean to land by storing extra water on land. Remarkably, this heat redistribution exceeds the anthropogenic heat uptake by inland waters by a factor of ~ 9.6, adding up to 27 ± 2.1x1020 J. Our results overall underline the importance of inland waters for buffering atmospheric warming through enhanced anthropogenic greenhouse gas concentrations.

Most estimates of carbon dioxide (CO2) evasion from freshwaters rely on calculating partial pressure of aquatic CO2 (pCO2) from two out of three CO2‐related parameters using carbonate equilibria. However, the pCO2 uncertainty has not been systematically evaluated across multiple lake types and equilibria. We quantified random errors in pH, dissolved inorganic carbon, alkalinity, and temperature from the North Temperate Lakes Long‐Term Ecological Research site in four lake groups across a broad gradient of chemical composition. These errors were propagated onto pCO2 calculated from three carbonate equilibria, and for overlapping observations, compared against uncertainties in directly measured pCO2. The empirical random errors in CO2‐related parameters were mostly below 2% of their median values. Resulting random pCO2 errors ranged from ±3.7% to ±31.5% of the median depending on alkalinity group and choice of input parameter pairs. Temperature uncertainty had a negligible effect on pCO2. When compared with direct pCO2 measurements, all parameter combinations produced biased pCO2 estimates with less than one third of total uncertainty explained by random pCO2 errors, indicating that systematic uncertainty dominates over random error. Multidecadal trend of pCO2 was difficult to reconstruct from uncertain historical observations of CO2‐related parameters. Given poor precision and accuracy of pCO2 estimates derived from virtually any combination of two CO2‐related parameters, we recommend direct pCO2 measurements where possible. To achieve consistently robust estimates of CO2 emissions from freshwater components of terrestrial carbon balances, future efforts should focus on improving accuracy and precision of CO2‐related parameters (including direct pCO2) measurements and associated pCO2 calculations.

The European Water Framework Directive (WFD) requires that the ecological status of waterbodies is assessed using multiple biological quality elements (BQEs) that are combined into a single status class. The recommended combination rule (the "one-out, all-out" rule; OOAO) has been criticised for being unreasonably conservative and for being sensitive to uncertainty. In this study, the objective was to compare the sensitivity to uncertainty of four different combination rules: (1) OOAO, (2) OOAO with exclusion of one element, (3) average and (4) weighted average. Index values for 5 BQEs (phytoplankton, phytobenthos, macrophytes, macroinvertebrates and fish) sampled from 10 lakes in the We! River catchment in Poland were used to classify the lakes according to the OOAO and the three alternative combination rules. Based on the mean and (where possible) standard deviation of these index values, we modelled the risk of misclassification by simulating 10,000 resamples for each BQEs in each lake, classifying each resample and calculating the proportion of misclassified resamples under each combination rule. For individual BQEs, the risk of misclassification increased both with higher uncertainty (standard deviation) and with the proximity of the index value to a class boundary. Under the OOAO rule, the risk of misclassification was more biased towards worse status ("underclassification") than towards better status. Furthermore, risk of underclassification was more affected by uncertainty under the OOAO rule compared with the alternative combination rules. This analysis has demonstrated the weaknesses associated with the OOAO rule for integration of BQEs for lake classification. However, the alternative combination rules are associated with other shortcomings, such as the need for subjective judgement, and involve a higher risk of not protecting the most sensitive BQE and thus the whole ecosystem. We recommend that future versions of instructions for WFD implementation consider alternatives to the OOAO combination rule, and provide guidelines for weighting of individual BQEs. (C) 2014 Elsevier Ltd. All rights reserved.