Lake surface temperatures in a changing climate: a global sensitivity analysis

We estimate the effects of climatic changes, as predicted by six climate models, on lake surface temperatures on a global scale, using the lake surface equilibrium temperature as a proxy. We evaluate interactions between different forcing variables, the sensitivity of lake surface temperatures to these variables, as well as differences between climate zones. Lake surface equilibrium temperatures are predicted to increase by 70 to 85 % of the increase in air temperatures. On average, air temperature is the main driver for changes in lake surface temperatures, and its effect is reduced by ~10 % by changes in other meteorological variables. However, the contribution of these other variables to the variance is ~40 % of that of air temperature, and their effects can be important at specific locations. The warming increases the importance of longwave radiation and evaporation for the lake surface heat balance compared to shortwave radiation and convective heat fluxes. We discuss the consequences of our findings for the design and evaluation of different types of studies on climate change effects on lakes.     

Simulated effects of land immersion on regional arid climate: a case study of the pre-Saharan playa of Chott el-Jerid (south of Tunisia)

The potential effects on the regional climate induced by partially immersing the arid pre-Saharan playa basin of Chott el-Jerid (south of Tunisia) are investigated by comparing two multi-year (1991–2011) sets of numerical simulations each consisting of ten-member ensemble and performed using the WRF regional climate model. The first WRF ensemble is performed under current land use and land cover, while the second is carried out after introducing a virtual large and shallow surface water reservoir (a lake) in Chott el-Jerid. The most pronounced effects generated by the artificial lake are circumscribed over its surface and slightly spread downwind to the other parts of the Chott. The lake has a clear moderating effect on near-surface air temperatures by increasing (decreasing) the wintertime (summertime) air temperatures. Sensible heat fluxes are remarkably increased in winter and decreased in summer over the lake following the temperature gradient between the lake surface and the overlying atmosphere. Latent heat fluxes, moisture convergence, and water vapor mixing ratio are increased over the lake throughout the year, especially in winter. The lake also induces domain-wide decreased (increased) surface pressures and land (lake) breeze circulation in winter (summer). Simulated rainfall amounts are most increased over the lake in winter likely because of an enhanced atmospheric instability, while they slightly decrease in summer.     

Improvements of the coupled WRF-Lake model over Lake Nam Co,Central Tibetan Plateau

A series of model sensitivity simulations are carried out to calibrate and improve the Weather Research and Forecasting Model coupled with a one-dimensional lake model (WRF-Lake) based on observations over Lake Nam Co. Using the default lake model parameters, the solution of WRF-Lake exhibits significant biases in both the lake thermodynamics and regional climatology, i.e., higher lake surface temperature (LST), earlier onset of summer thermal stratification, and overestimated near-surface air temperature and precipitation induced by the lake’s excessive warming and moistening impacts. The performance of WRF-Lake is improved through adjusting the initial lake temperature profile, the temperature of maximum water density (Tdmax), the surface roughness length, and the light extinction coefficient. Results show that initializing the water temperature with spring observation mitigates the LST overestimation and reduces the timing error of the onset of thermal stratification. By further adjusting Tdmax from 4 °C to the observed value of 3.5 °C, the LST increase from June to mid-July is enhanced and the buildup of thermal stratification is more accurately predicted. Through incorporating the parameterized surface roughness length and decreasing the light extinction coefficient, the model better reproduces the observed daily evolution of LST and vertical lake temperature profile. The calibrated WRF-Lake effectively mitigates the overestimation of over-lake air temperature at 2 m height and precipitation over regions downwind the lake. This suggests that an improved lake scheme within the coupled WRF-Lake is essential for realistically simulating the lake–air interactions and the regional climate over the lake-rich Tibetan Plateau.

     

Sensitivity of climate change projections to uncertainties in the estimates of observed changes in deep-ocean heat content

The MIT 2D climate model is used to make probabilistic projections for changes in global mean surface temperature and for thermosteric sea level rise under a variety of forcing scenarios. The uncertainties in climate sensitivity and rate of heat uptake by the deep ocean are quantified by using the probability distributions derived from observed twentieth century temperature changes. The impact on climate change projections of using the smallest and largest estimates of twentieth century deep ocean warming is explored. The impact is large in the case of global mean thermosteric sea level rise. In the MIT reference (“business as usual”) scenario the median rise by 2100 is 27 and 43 cm in the respective cases. The impact on increases in global mean surface air temperature is more modest, 4.9 and 3.9 C in the two respective cases, because of the correlation between climate sensitivity and ocean heat uptake required by twentieth century surface and upper air temperature changes. The results are also compared with the projections made by the IPCC AR4’s multi-model ensemble for several of the SRES scenarios. The multi-model projections are more consistent with the MIT projections based on the largest estimate of ocean warming. However, the range for the rate of heat uptake by the ocean suggested by the lowest estimate of ocean warming is more consistent with the range suggested by the twentieth century changes in surface and upper air temperatures, combined with the expert prior for climate sensitivity.     

Do weak AR4 models bias projections of future climate changes over Australia?

Regional climate projections using climate models commonly use an “all-model” ensemble based on data sets such as the Intergovernmental Panel on Climate Change’s (IPCC) 4th Assessment (AR4). Some regional assessments have omitted models based on specific criteria. We use a criteria based on the capacity of climate models to simulate the observed probability density function calculated using daily data, model-by-model and region-by-region for each of the AR4 models over Australia. We demonstrate that by omitting those climate models with relatively weak skill in simulating the observed probability density functions of maximum and minimum temperature and precipitation, different regional projections are obtained. Differences include: larger increases in the mean maximum and mean minimum temperatures, but smaller increases in the annual maximum and minimum temperatures. There is little impact on mean precipitation but the better models simulate a larger increase in the annual rainfall event combined with a larger decrease in the number of rain days. The weaker models bias the amount of mean warming towards lower increases, bias annual maximum temperatures to excessive warming and bias precipitation such that the amount of the annual rainfall event is under-estimated. We suggest that omitting weak models from regional scale estimates of future climate change helps clarify the nature and scale of the projected impacts of global warming.     

Projections of Climate Change Effects on Water Temperature Characteristics of Small Lakes in the Contiguous U.S.

To simulate effects of projected climate change on water temperature characteristics of small lakes in the contiguous U.S., a deterministic, one-dimensional year-round water temperature model is applied. In cold regions the model simulates ice and snow cover on a lake. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous U.S. for the period 1961–1979 were used to represent present climate conditions. The projected climate change owing to a doubling of atmospheric CO₂ was obtained from the output of the Canadian Climate Center General Circulation Model. The simulated water temperature and ice characteristics are related to the geometric and trophic state lake characteristics and to geographic location. By interpolation, the sensitivity of lake water temperature characteristics to latitude, longitude, lake geometry and trophic status can therefore be quantified for small lakes in the contiguous U.S. The 2× CO₂ climate scenario is projected to increase maximum and minimum lake surface temperatures by up to 5.2°C. (Maximum surface water temperatures in lakes near the northern and the southern border of the contiguous U.S. currently differ by up to 13°C.) Maximum temperature differences between lake surface and lake bottom are projected to increase in average by only 1 to 2°C after climate warming. The duration of seasonal summer stratification is projected to be up to 66 days longer under a 2×CO₂ climate scenario. Water temperatures of less than 8°C are projected to occur on lake bottoms during a period which is on the order of 50 days shorter under a 2×CO₂ climate scenario. With water temperature change projected to be as high as 5.2°C, ecological impacts such as shifts in species distributions and in fish habitat are most likely. Ice covers on lakes of northern regions would also be changed strongly.     

Global river discharge and water temperature under climate change

Climate change will affect hydrologic and thermal regimes of rivers, having a direct impact on freshwater ecosystems and human water use. Here we assess the impact of climate change on global river flows and river water temperatures, and identify regions that might become more critical for freshwater ecosystems and water use sectors. We used a global physically based hydrological-water temperature modelling framework forced with an ensemble of bias-corrected general circulation model (GCM) output for both the SRES A2 and B1 emissions scenario. This resulted in global projections of daily river discharge and water temperature under future climate. Our results show an increase in the seasonality of river discharge (both increase in high flow and decrease in low flow) for about one-third of the global land surface area for 2071–2100 relative to 1971–2000. Global mean and high (95th percentile) river water temperatures are projected to increase on average by 0.8–1.6 (1.0–2.2) °C for the SRES B1–A2 scenario for 2071–2100 relative to 1971–2000. The largest water temperature increases are projected for the United States, Europe, eastern China, and parts of southern Africa and Australia. In these regions, the sensitivities are exacerbated by projected decreases in low flows (resulting in a reduced thermal capacity). For strongly seasonal rivers with highest water temperatures during the low flow period, up to 26% of the increases in high (95th percentile) water temperature can be attributed indirectly to low flow changes, and the largest fraction is attributable directly to increased atmospheric energy input. A combination of large increases in river temperature and decreases in low flows are projected for the southeastern United States, Europe, eastern China, southern Africa and southern Australia. These regions could potentially be affected by increased deterioration of water quality and freshwater habitats, and reduced water available for human uses such as thermoelectric power and drinking water production.     

Mid-21st century projections in temperature extremes in the southern Colorado Rocky Mountains from regional climate models

This study analyzes mid-21st century projections of daily surface air minimum (T_min) and maximum (T_max) temperatures, by season and elevation, over the southern range of the Colorado Rocky Mountains. The projections are from four regional climate models (RCMs) that are part of the North American Regional Climate Change Assessment Program (NARCCAP). All four RCMs project 2°C or higher increases in T_min and T_max for all seasons. However, there are much greater (>3°C) increases in T_max during summer at higher elevations and in T_min during winter at lower elevations. T_max increases during summer are associated with drying conditions. The models simulate large reductions in latent heat fluxes and increases in sensible heat fluxes that are, in part, caused by decreases in precipitation and soil moisture. T_min increases during winter are found to be associated with decreases in surface snow cover, and increases in soil moisture and atmospheric water vapor. The increased moistening of the soil and atmosphere facilitates a greater diurnal retention of the daytime solar energy in the land surface and amplifies the longwave heating of the land surface at night. We hypothesize that the presence of significant surface moisture fluxes can modify the effects of snow-albedo feedback and results in greater wintertime warming at night than during the day.     

Temperature change and macroinvertebrate biodiversity: assessments of organism vulnerability and potential distributions

Peninsular environments are ecosystems that are one of the most vulnerable to global warming. Despite the importance of conserving regional biodiversity, peninsular environments are among the least studied with respect to the influences of global warming. In this study, we used data on benthic macroinvertebrate communities from 521 sites across Korea (a nationwide scale) to evaluate the potential impact of temperature increases on river ecosystems. Weighted averaging regression models (WARMs) were used to project the relationships between relative macroinvertebrate abundance and water temperature, based on the temperature data of the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Maximum tolerance water temperatures were used to quantify the risks to macroinvertebrates at the catchment and national scales. Ambient air temperatures in the 2090s were projected to increase by an average of 3.4?ºC relative to the baseline of the 2000s at the national scale. Mayflies, stoneflies and caddisflies were identified as potentially the most sensitive taxa to global warming. The impact of global warming on macroinvertebrates was predicted to be minimal prior to the 2060s; however, by the 2080s, species loss was predicted to be 55 %. Potential distribution ranges of cold water species in the future decades were expected to decrease continuously over time, while those of warm species were expected to increase from the 2000s to the 2040s and then decrease until the 2080s. Our projections may be useful for understanding how climate parameters affect the biogeographical patterns of aquatic biodiversity from a thermal-preference perspective.     

Impact of Secular Climate Change on the Thermal Structure of a Large Temperate Central European Lake

Strong climate-related secular trends are apparent in a 52-yr long (1947–1998) uninterrupted series of monthly temperature profiles fromLake Zurich, a large, deep (136 m), temperate lake on the Swiss Plateau. Decadal mean water temperatures have undergone a secular increase at all depths, reflecting the high degree of regional warming that occurred in the European Alpine area during the 20th century. From the 1950s to the 1990s, high warming rates ( 0.24 K per decade) in the uppermost 20 m of the lake (i.e., the epi/metalimnion) combined with lower warming rates ( 0.13 K per decade) below 20 m (i.e., in the hypolimnion), have resulted in a20% increase in thermal stability and a consequent extension of 2–3 weeksin the stratification period. In common with many other parts of the world, 20th-century climate change on the Swiss Plateau has involved a steep secular increase in daily minimum (nighttime) air temperatures, but not in daily maximum (daytime) air temperatures. With respect to both secular change and decadal-scale variability, the temporal structure of the temperature of the surface mixed layer of Lake Zurich faithfully reflects that of the regional daily minimum air temperature, but not that of the daily maximum. The processes responsible for longer-term changes in the temperature structure of the lake therefore act during the night, presumably by suppressing nighttime convective cooling of the surface mixed layer. Application of a one-box heat exchange model suggests that the observed secular changes in thermal structure are due to shifts in the nighttime rate of emission of infrared radiation from the atmosphere and in the nighttime rates of latent and sensible heat exchange at the air-water interface. The increase in hypolimnetic temperatures is mainly a result of the increased prevalence of warm winters in Europe.     

Tropical and extratropical cyclone damages under climate change

This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone damages under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 478 estimates of the temperature-damage relationship from nineteen studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5 °C increase in global surface air temperature would cause hurricane damages to increase by 63 %. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are +28 % and +23 %, respectively. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.     

Relative effects of climate change and wildfires on stream temperatures: a simulation modeling approach in a Rocky Mountain watershed

Freshwater ecosystems are warming globally from the direct effects of climate change on air temperature and hydrology and the indirect effects on near-stream vegetation. In fire-prone landscapes, vegetative change may be especially rapid and cause significant local stream temperature increases but the importance of these increases relative to broader changes associated with air temperature and hydrology are not well understood. We linked a spatially explicit landscape fire and vegetation model (FireBGCv2) to an empirical regression equation that predicted daily stream temperatures to explore how climate change and its impacts on fire might affect stream thermal conditions across a partially forested, mountainous landscape in the western U.S. We used the model to understand the roles that wildfire and management actions such as fuel reduction and fire suppression could play in mitigating stream thermal responses to climate change. Results indicate that air temperature increases associated with future climates could account for a much larger proportion of stream temperature increases (as much as 90 % at a basin scale) than wildfire. Similarly, land management scenarios that limited wildfire prevalence had negligible effects on future stream temperature increases. These patterns emerged at broader spatial scales because wildfires typically affected only a subset of a stream’s network. However, at finer spatial and temporal scales stream temperatures were sensitive to wildfire. Although wildfires will continue to cause local, short-term effects on stream temperatures, managers of aquatic systems may need to find other solutions to cope with the larger impact from climate change on future stream warming that involves adapting to the increases while developing broad strategies for riparian vegetation restoration.     

RegCM3 CORDEX东亚试验模拟和预估的中国夏季温度变化

按照CORDEX (COordinated Regional Downscaling Experiment) 计划试验设计要求,利用中国科学院大气物理研究所全球模式FGOALS-g2的数据驱动区域气候模式RegCM3,针对1986~2005年历史气候和2010~2065年RCP8.5排放情景下气候预估,对东亚地区进行了50 km动力降尺度模拟。首先评估了RegCM3模式及驱动模式FGOALS-g2对1986~2005年夏季中国地表气温和极端高温事件的模拟能力,然后比较了两个模式在RCP8.5排放情景下对中国夏季地表气温和极端高温事件预估的变化,重点分析了动力降尺度结果的优势。结果表明,两个模式均能合理再现夏季中国地表气温和极端高温事件的大尺度气候态特征。相对于全球模式,区域模式由于水平分辨率较高,能在刻画地表气温分布的细节上体现出优势。在RCP8.5排放情景下,两个模式预估的三个地表气温指标均显著升高,到21世纪中期 (2046~2065年),两个模式预估的全国平均地表气温增幅相当,气温日较差变化均较小。在FGOALS-g2模式预估中,到21世纪中期,三个地表气温指标的增幅相当,气温日较差没有明显变化,东北和青藏高原的地表气温增幅最大。在RegCM3模式预估中,到21世纪中期,中国大部分地区日最高气温 (Tmax) 增幅大于日最低气温 (Tmin) 增幅,气温日较差增加;而在青藏高原西部,Tmax的增幅较Tmin偏低,气温日较差减小。在RCP8.5排放情景下,两个模式预估的极端高温事件到21世纪中期也显著增加,RegCM3模式预估的极端高温事件全国平均增幅略高于FGOALS-g2模式的预估。在两个模式的预估中,日最高气温最大值 (TXx)、暖昼指数 (TX90p) 和持续暖期指数 (WSDI) 变化的空间分布特征与Tmax相似;和当代相比TX90p增加了60%以上,而WSDI增加了一倍以上。     

On the simulation of Laurentian Great Lakes water levels under projections of global climate change

A new method is proposed to estimate future net basin supplies and lake levels for the Laurentian Great Lakes based on GCM projections of global climate change. The method first dynamically downscales the GCM simulation with a regional climate model, and then bias—corrects the simulated net basin supply in order to be used directly in a river—routing/lake level scheme. This technique addresses two weaknesses in the traditional approach, whereby observed sequences of climate variables are perturbed with fixed ratios or differences derived directly from GCMs in order to run evaporation and runoff models. Specifically, (1) land surface—atmosphere feedback processes are represented, and (2) changes in variability can be analyzed with the new approach. The method is demonstrated with a single, high resolution simulation, where small changes in future mean lake levels for all the upper Great Lakes are found, and an increase in seasonal range—especially for Lake Superior—is indicated. Analysis of a small ensemble of eight lower resolution regional climate model simulations supports these findings. In addition, a direct comparison with the traditional approach based on the same GCM projections used as the driving simulations in this ensemble shows that the new method indicates smaller declines in level for all the upper Great Lakes than has been reported previously based on the traditional method, though median differences are only a few centimetres in each case.     

Predicting Patterns of Near-Surface Air Temperature Using Empirical Data

The signal of recent global warming has been detected in meteorological records, borehole temperatures and by several indirect climate indicators. Anthropogenic warming continues to evolve, and various methods are used to study and predict the changes of the global and regional climate. Results derived from GCMs, palaeoclimate reconstructions, and regional climate models differ in detail. An empirical model could be used to predict the spatial pattern of the near-surface air temperature and to narrow the range of regional uncertainties. The idea behind this approach is to study the correlations between regional and global temperature using century-scale meteorological records, and to evaluate the regional pattern of the future climate using regression analysis and the global-mean air temperature as a predictor. This empirical model, however, is only applicable to those parts of the world where regional near-surface air temperature reacts linearly to changes of the global thermal regime. This method and data from a set of approximately 2000 weather stations with continuous century-scale records of the monthly air temperature was applied to develop the empirical map of the regional climate sensitivity. Data analysis indicated that an empirical model could be applied to several large regions of the World, where correlations between local and global air temperature are statistically significant. These regions are the western United States, southern Canada, Alaska, Siberia, south-eastern Asia, southern Africa and Australia, where the correlation coefficient is typically above 0.9. The map of regional climate sensitivity has been constructed using calculated coefficients of linear regression between the global-mean and regional annual air temperature. As long as the correlations between the local and global air temperature are close to those in the last several decades, this map provides an effective tool to scale down the projection of the global air temperature to regional level. According to the results of this study, maximum warming at the beginning of the 21st century will take place in the continental parts of North America and Eurasia. The empirical regional climate sensitivity defined here as the response of the mean-annual regional temperature to 1 °C global warming was found to be 5–6 °C in southern Alaska, central Canada, and over the continental Siberia, 3–4 °C on the North Slope of Alaska and western coast of the U.S.A., and 1–2 °C in most of the central and eastern U.S.A. and eastern Canada. Regions with negative sensitivity are located in the southeastern U.S.A., north-western Europe and Scandinavia. The local tendency towards cooling, although statistically confirmed by modern data, could, however, change in the near future.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO₂ fertilization effect on vegetation is examined by using two levels of atmospheric CO₂ concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO₂ fertilization effects.     

Statistical estimation of high-resolution surface air temperature from MODIS over the Yangtze River Delta,China

High-resolution surface air temperature data are critical to regional climate modeling in terms of energy balance, urban climate change, and so on. This study demonstrates the feasibility of using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) to estimate air temperature at a high resolution over the Yangtze River Delta region, China. It is found that daytime LST is highly correlated with maximum air temperature, and the linear regression coefficients vary with the type of land surface. The air temperature at a resolution of 1 km is estimated from the MODIS LST with linear regression models. The estimated air temperature shows a clear spatial structure of urban heat islands. Spatial patterns of LST and air temperature differences are detected, indicating maximum differences over urban and forest regions during summer. Validations are performed with independent data samples, demonstrating that the mean absolute error of the estimated air temperature is approximately 2.5°C, and the uncertainty is about 3.1°C, if using all valid LST data. The error is reduced by 0.4°C (15%) if using best-quality LST with errors of less than 1 K. The estimated high-resolution air temperature data have great potential to be used in validating high-resolution climate models and other regional applications.     

Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century glacier contribution to sea-level rise. Glacier volume changes are calculated with a surface mass balance model combined with volume-area scaling, applied to 89 glaciers in different climatic regions. The mass balance model is based on a simplified energy balance approach, with separated contributions by net solar radiation and the combined other fluxes. Future mass balance is calculated from anomalies in air temperature, precipitation and atmospheric transmissivity, taken from eight global climate models forced with the A1B emission scenario. Regional and global sea-level contributions are obtained by scaling the volume changes at the modelled glaciers to all glaciers larger than 0.1 km² outside the Greenland and Antarctic ice sheets. This results in a global value of 0.102 ± 0.028 m (multi-model mean and standard deviation) relative sea-level equivalent for the period 2012–2099, corresponding to 18 ± 5 % of the estimated total volume of glaciers. Glaciers in the Antarctic, Alaska, Central Asia and Greenland together account for 65 ± 4 % of the total multi-model mean projected sea-level rise. The projected sea-level contribution is 35 ± 17 % larger when only anomalies in air temperature are taken into account, demonstrating an important compensating effect by increased precipitation and possibly reduced atmospheric transmissivity. The variability in projected precipitation and atmospheric transmissivity changes is especially large in the Arctic regions, making the sea-level contribution for these regions particularly sensitive to the climate model used. Including additional uncertainties in the modelling procedure and the input data, the total uncertainty estimate for the future projections becomes ±0.063 m.     

Variability and alterations of water temperatures across the Elbe and Danube River Basins

Climate change is predicted to be a major threat to river ecosystems in the 21st century, but long-term records of water temperature in streams and rivers are rare. This study uses long-term water temperature series from the Elbe and the Danube River Basin to quantify the variability, magnitude, and extent of temperature alterations at different time scales. The observed patterns in monthly and daily water temperatures have been successfully described through statistical models based on air temperature, river discharge and the North Atlantic Oscillation Index. These models reveal that air temperature variability describes more than 80 % of the total water-temperature variability, linking anticipated changes in water temperature mainly to those in air temperature. The North Atlantic Oscillation effect deteriorates with decreasing latitude, while the discharge effect becomes more important and increases with the increase in discharge amount. The detected water temperature alterations include a phase shift in spring warming of almost 2 weeks, an increase in the number of days with temperatures above 25 °C and an increase in the duration of summer heat stress. These findings underline a significant risk for fundamental changes in river ecosystems, specifically in disruption of established patterns in food-web synchrony, and may lead to significant distortions in community structure and composition.     

Regional water temperature characteristics of lakes subjected to climate change

A deterministic, validated, one-dimensional, unsteady-state lake water quality model was linked to a daily weather data base to simulate daily water temperature profiles in lakes over a period of twenty-five (1955–79) years. Twenty seven classes of lakes which are characteristic for the north-central U.S. were investigated. Output from a global climate model (GISS) was used to modify the weather data base to account for a doubling of atmospheric CO₂. The simulations predict that, after climate change, epilimnetic temperatures will be higher but increase less than air temperature, hypolimnetic temperatures in seasonally stratified dimictic lakes will be largely unchanged or even lower than at present, evaporative water loss will be increased by as much as 300 mm for the season, onset of stratification will occur earlier and overturn later in the season, and overall lake stability will become greater in spring and summer.