John D. Lenters

Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance, and vegetation structure

While a new class of Dynamic Global Ecosystem Models (DGEMs) has emerged in the past few years as an important tool for describing global biogeochemical cycles and atmosphere-biosphere interactions, these models are still largely untested. Here we analyze the behavior of a new DGEM and compare the results to global-scale observations of water balance, carbon balance, and vegetation structure. In this study, we use version 2 of the Integrated Biosphere Simulator (IBIS), which includes several major improvements and additions to the prototype model developed by Foley et al. [1996]. IBIS is designed to be a comprehensive model of the terrestrial biosphere; the model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO2 fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). In order to test the performance of the model, we have assembled a wide range of continental and global-scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO2 flux. Using these field data and model results for the contemporary biosphere (1965–1994), our evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO2 flux agree reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results.

Rapid and highly variable warming of lake surface waters around the globe

In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes.

Surface water balance of the continental United States, 1963–1995: Regional evaluation of a terrestrial biosphere model and the NCEP/NCAR reanalysis

The land surface water balance of the continental United States is analyzed from 1963 to 1995 using a terrestrial biosphere model (IBIS), reanalysis data from NCEP/NCAR, a hydrologic routing model (HYDRA), and numerous observational data sets. Emphasis is placed on evaluating the performance of IBIS and the reanalysis, particularly over the central United States. IBIS is forced with daily climatic inputs from NCEP; an additional simulation is performed using observed precipitation. The NCEP reanalysis is found to have excessive precipitation and evapotranspiration over the central United States (particularly in the summertime), an exaggerated seasonal cycle of runoff, and low snow depths. The net surface water balance exhibits a dry bias that is corrected by nudging soil moisture toward climatology. Unfortunately, this correction term is large and appears to have a detrimental impact on other water balance components (particularly runoff). Fields that are reasonably well simulated in the reanalysis include fall and winter precipitation over the central United States, soil moisture in Illinois, and interannual variations in runoff. Results from the IBIS simulations show generally better agreement with observations than the NCEP reanalysis but continue to have nontrivial errors in certain fields. Over the central United States, these discrepancies include high winter/spring evapotranspiration (1 mm d−1 too high), low snow depth, and weak spring runoff (30–50% too low). The errors are at least partially caused by underestimated cloud cover and early spring green-up. A spatial analysis of the U.S. water balance reveals that some of the strongest seasonal and interannual variations in precipitation, evapotranspiration, and soil moisture occur over the central United States.

Long-term Trends in the Seasonal Cycle of Great Lakes Water Levels

Numerous long-term trends in the rate-of-change in monthly mean Great Lakes water levels are identified for the period 1860 to 1998. Statistically significant trends are found for 2, 4, 5, and 7 months of the year for Lakes Superior, Michigan-Huron, Erie, and Ontario, respectively. Many of the trends translate into large changes in net water flux (600 to 1,700 m3/s). In each case, significant positive trends are roughly offset by negative trends during other times of the year. Together with similar trends in monthly lake level anomalies (deviations from the annual mean), these trends indicate important changes in the seasonal cycle of Great Lakes water levels. Specifically, Lakes Erie and Ontario are rising and falling (on an annual basis) roughly one month earlier than they did 139 years ago. Maximum lake levels for Lake Superior are also slightly earlier in the year, and the amplitude of the seasonal cycle of Lake Ontario is found to increase by 23% over the 139-year period. Some of the changes are consistent with the predicted impacts of global warming on spring snowmelt and runoff in the Great Lakes region. Other potential contributors to the observed trends include seasonal changes in precipitation and humaninduced effects such as lake regulation and changes in land use.

A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.

Global patterns of lake ice phenology and climate' Model simulations and observations

Lake ice phenology parameters (dates of ice onset and thaw) provide an integrative climatic description of autumn to springtime conditions. Interannual variations in lake ice duration and thickness allow estimates of local climatic variability. In addition, long-term changes in lake ice phenology may provide a robust indication of climatic change. The relationship between lake ice and climate enables the use of process-based models for predicting the dates of freeze-up and thaw. LIMNOS (Lake Ice Model Numerical Operational Simulator) is one such model, which was originally designed to simulate the ice phenology of several lakes in southern Wisconsin. In this study, LIMNOS is modified to run globally on a 0.5° by 0.5° latitude-longitude grid using average monthly climate data. We initially simulate the ice phenology for lakes of 5- and 20-m mean depths across the northern hemisphere to demonstrate the effects of lake depth, latitude, and elevation on ice phenology. To evaluate the results of LIMNOS we also simulate the ice phenology of 30 lakes across the northern hemisphere which have long-term ice records. LIMNOS reproduces the general geographic patterns of ice-on and ice-off dates, although ice-off dates tend to occur later in the model. Lakes with extreme depths, surface areas, or precipitation are simulated less accurately than small, shallow lakes. This study reveals strengths and weaknesses of LIMNOS and suggests aspects which need improving. Future investigations should focus on the use of geographically extensive lake ice observations and modeling to elucidate patterns of climatic variability and/or climate change.

The Importance of Spring and Autumn Atmospheric Conditions for the Evaporation Regime of Lake Superior

AbstractFeedbacks between ice extent and evaporation have long been suspected to be important for Lake Superior evaporation because it is during autumn and winter when latent heat fluxes are highest. Recent direct measurements of evaporation made at the Stannard Rock Lighthouse have provided new information on the physical controls on Lake Superior evaporation, in particular that evaporation can react within hours to days to a change in synoptic conditions. However, the large heat capacity of the lake creates a strong seasonal cycle of energy storage and release. There is a complex interaction among heat storage, evaporation, and ice cover that is highly dependent on atmospheric conditions in the spring and autumn “shoulder seasons.” Small changes in conditions in November and March caused by synoptic-scale events can have profound impacts on annual evaporation, the extent of ice cover, and the length of the ice-covered period. Early winter air temperatures in November and December dictate the nature of i...

Miscanthus establishment and overwintering in the Midwest USA: a regional modeling study of crop residue management on critical minimum soil temperatures.

Miscanthus is an intriguing cellulosic bioenergy feedstock because its aboveground productivity is high for low amounts of agrochemical inputs, but soil temperatures below −3.5°C could threaten successful cultivation in temperate regions. We used a combination of observed soil temperatures and the Agro-IBIS model to investigate how strategic residue management could reduce the risk of rhizome threatening soil temperatures. This objective was addressed using a historical (1978–2007) reconstruction of extreme minimum 10 cm soil temperatures experienced across the Midwest US and model sensitivity studies that quantified the impact of crop residue on soil temperatures. At observation sites and for simulations that had bare soil, two critical soil temperature thresholds (50% rhizome winterkill at −3.5°C and −6.0°C for different Miscanthus genotypes) were reached at rhizome planting depth (10 cm) over large geographic areas. The coldest average annual extreme 10 cm soil temperatures were between −8°C to −11°C across North Dakota, South Dakota, and Minnesota. Large portions of the region experienced 10 cm soil temperatures below −3.5°C in 75% or greater for all years, and portions of North and South Dakota, Minnesota, and Wisconsin experienced soil temperatures below −6.0°C in 50–60% of all years. For simulated management options that established varied thicknesses (1–5 cm) of miscanthus straw following harvest, extreme minimum soil temperatures increased by 2.5°C to 6°C compared to bare soil, with the greatest warming associated with thicker residue layers. While the likelihood of 10 cm soil temperatures reaching −3.5°C was greatly reduced with 2–5 cm of surface residue, portions of the Dakotas, Nebraska, Minnesota, and Wisconsin still experienced temperatures colder than −3.5°C in 50–80% of all years. Nonetheless, strategic residue management could help increase the likelihood of overwintering of miscanthus rhizomes in the first few years after establishment, although low productivity and biomass availability during these early stages could hamper such efforts.

Quantifying sources of error in multitemporal multisensor lake mapping

Regional- to global-scale lake maps can now be produced using existing technology and freely available data and serve as powerful tools for a variety of lake- and water-related studies. The accuracy of these studies depends in part on the accuracy of the lake map that they use. Mapping lakes using remote sensing requires a careful study of error and uncertainty. Errors in lake maps are caused by sensor-specific, lake-specific, and processing-specific factors. These can be further broken down to spatial, spectral/radiometric, and temporal factors. In this study, we analyse and compare these factors using modern and historical Landsat images along with intensive ground surveys of lakes in northern Alaska. Percentage error in lake area (relative to lake size) decreases for larger and more circular lakes, making a minimum size threshold an effective error mitigation practice. Image resampling involved in image transformation significantly increased error in lake area and is easily avoided by performing co-registration in the vector domain. Spectral properties varied for individual lakes due to depth, suspended sediment, vegetation, and other in situ factors, necessitating a normalized water index and independently derived threshold values for each lake. For lake change detection studies, spatially degrading a finer resolution image to the resolution of the coarser image (a common practice) does not significantly affect the difference in observed lake area. Due to the large numbers of lakes, particularly in the climatologically sensitive Arctic region, small errors in individual lake areas can compound to significantly impact results on regional to global scales. This study is intended to inform future static and multitemporal lake remote-sensing studies by evaluating errors and uncertainties in lake area, as measured by remote sensing.

Workshop examines warming of lakes worldwide

First Global Lake Temperature Collaboration (GLTC) Workshop; Lincoln, Nebraska, 1–5 June 2012 It is widely recognized that climate change is affecting terrestrial and aquatic ecosystems. Recent studies have revealed significant warming of lakes throughout the world, and this rate of warming is often larger than that of the ambient air temperature (up to 2–3 times more rapid). Although hypotheses have been proposed to explain these high rates of lake warming (e.g., ice albedo feedbacks or changes in cloud cover), the fundamental drivers remain poorly understood. Furthermore, these rapid warming rates have profound implications for lake hydrodynamics, productivity, and biotic communities. It is essential therefore that global data sets of water temperature be compiled to monitor and understand these long-term changes in lakes, reservoirs, and other inland water bodies.