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At least 469 records · Page 26Linked to original sources
USGS2014

An enhanced model of land water and energy for global hydrologic and earth-system studies

LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.

Journal of Hydrometeorology↗
USGS2019

Facilitated adaptation for conservation – Can gene editing save Hawaii's endangered birds from climate driven avian malaria?

Avian malaria has played a significant role in causing extinctions, population declines, and limiting the elevational distribution of Hawaiian honeycreepers. Most threatened and endangered honeycreepers only exist in high-elevation forests where the risk of malaria infection is limited. Because Culex mosquito vectors and avian malaria dynamics are strongly influenced by temperature and rainfall, future climate change is predicted to expand malaria infection to high-elevation forests and intensify malaria infection at lower elevations, likely resulting in future extinctions and loss of avian biodiversity in Hawaii. Novel, landscape-level mosquito control strategies are promising, but are logistically challenging and require costly long-term efforts. As an alternative or supplemental strategy, we evaluated the potential of releasing a gene-edited malaria-resistant honeycreeper (Iiwi, Drepanis coccinea) in Hawaiian rainforests; a strategy known as facilitated adaptation. While this approach also has significant technical challenges and costs, it may offer a more permanent solution to increasing malaria threats. If malaria-resistant honeycreepers can be developed, facilitated adaptation may provide a practical strategy for the reestablishment of abundant avian populations in Hawaiian forests. A successful strategy could be the release of malaria-resistant Iiwi in mid-elevation forests where development of a resistant population has the best chance of success. Establishment of a resistant Iiwi population could provide a source for dispersal and development of resistant populations in high-elevation forests and a permanent source of resistant individuals for translocation to other vulnerable areas.

Hawaii↗
USGS2015

Application of MC1 to Wind Cave National Park: Lessons from a small-scale study: Chapter 8

MC1 was designed for application to large regions that include a wide range in elevation and topography, thereby encompassing a broad range in climates and vegetation types. The authors applied the dynamic global vegetation model MC1 to Wind Cave National Park (WCNP) in the southern Black Hills of South Dakota, USA, on the ecotone between ponderosa pine forest to the northwest and mixed-grass prairie to the southeast. They calibrated MC1 to simulate adequate fire effects in the warmer southeastern parts of the park to ensure grasslands there, while allowing forests to grow to the northwest, and then simulated future vegetation with climate projections from three GCMs. The results suggest that fire frequency, as affected by climate and/or human intervention, may be more important than the direct effects of climate in determining the distribution of ponderosa pine in the Black Hills region, both historically and in the future.

South Dakota↗
USGS2016

Natural recovery of biological soil crusts after disturbance

Natural recovery of biological soil crusts (biocrusts) is influenced by a number of different parameters, such as climate, soil conditions, the severity of disturbance, and the timing of disturbance relative to the climatic conditions. In recent studies, it has been shown that recovery is often not linear, but a highly dynamic process directly influenced by non-linear external parameters as extraordinary climatic conditions (e.g., particularly dry or wet year). Natural recovery often follows a general succession pattern, starting out with cyanobacteria and algae, which is then followed by lichens and bryophytes at a later stage. However, this general sequence can be altered by parameters like dust deposition, fire effects, and special climatic conditions as in fog deserts and under mesic climates. Recent studies have proposed that under favorable, stable soil conditions, the initial soil-stabilizing cyanobacteria-dominated succession stages may be omitted and moss-dominated biocrusts can develop in the initial phases of biocrust development. During natural recovery of biocrusts, soil properties change, e.g., soil nutrient and organic matter contents increase. Also, silt and clay contents of encrusted soils increase with biocrust maturity, which may be caused by two mechanisms, i.e. entrapment of fine soil particles by biocrusts and the new formation of smaller particles by weathering of the existing substrate.

Book chapter↗
USGS2024

Transdisciplinary research supports the sustainability of barrier island systems threatened by climate change

The management of developed barrier islands is often piece-meal and reactionary despite the complex, dynamic nature of these systems, and sustainable practices will become increasingly difficult due to heightened pressures of climate change. Adaptation actions, including nature-based solutions, need to be thoroughly evaluated prior to implementation to understand system-wide impacts and avoid maladaptation. Anarde et al. (2024a), ( https://doi.org/10.1029/2023ef003672 ), Anarde et al. (2024b), ( https://doi.org/10.1029/2023ef004200 ) is the latest important contribution in a growing body of transdisciplinary research that more robustly evaluates the complex physical process-and-response relationship of barrier systems via sophisticated numerical modeling approaches that also interface with socioeconomic models to inform coastal management actions in response to mitigating coastal risk. This new research indicates the importance of coordinated system-scale barrier island management, as strategies to reduce coastal hazard risk in one location will directly affect adjacent communities. Further, this work demonstrates that reducing barrier management interventions may actually promote barrier recovery and sustainability in the face of sea level rise. In addition, recent advances in the analysis and application of remotely sensed data from satellites and oblique aerial photography provide scientists an unprecedented opportunity to track coastal evolution over a wide range of spatial and temporal scales at minimal cost. As sea level rise and changing storm patterns challenge the sustainable management of barrier island systems, integrating these advanced, transdisciplinary tools will enable scientists and coastal practitioners to more thoroughly evaluate coastal adaptation options, efficiently invest limited resources to mitigate coastal hazard risk for communities, support healthy ecosystems, and reduce system-wide impacts.

Earth's Future↗
USGS2016

Introduction to special issue on carbon and landscape dynamics

In October, 2013, at the Geological Society of America annual meeting, a theme session focused on carbon and landscape dynamics. That event led to interest in producing a special issue in ESPL compiling papers on this subject. The 13 papers collected for this special issue reflect the diversity of recent geomorphic research, across a range of climatic and geomorphic settings, addressing some aspect of carbon dynamics.

Earth Surface Processes and Landforms↗
USGS2017

Range position and climate sensitivity: The structure of among-population demographic responses to climatic variation

Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs ( Lithobates sylvaticus ) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.

Global Change Biology↗
USGS2014

Incorporating climate change and morphological uncertainty into coastal change hazard assessments

Documented and forecasted trends in rising sea levels and changes in storminess patterns have the potential to increase the frequency, magnitude, and spatial extent of coastal change hazards. To develop realistic adaptation strategies, coastal planners need information about coastal change hazards that recognizes the dynamic temporal and spatial scales of beach morphology, the climate controls on coastal change hazards, and the uncertainties surrounding the drivers and impacts of climate change. We present a probabilistic approach for quantifying and mapping coastal change hazards that incorporates the uncertainty associated with both climate change and morphological variability. To demonstrate the approach, coastal change hazard zones of arbitrary confidence levels are developed for the Tillamook County (State of Oregon, USA) coastline using a suite of simple models and a range of possible climate futures related to wave climate, sea-level rise projections, and the frequency of major El Niño events. Extreme total water levels are more influenced by wave height variability, whereas the magnitude of erosion is more influenced by sea-level rise scenarios. Morphological variability has a stronger influence on the width of coastal hazard zones than the uncertainty associated with the range of climate change scenarios.

Natural Hazards↗
USGS2025

Effects of climate change on midwestern ecosystems: Eastern North American temperate freshwater marsh, wet meadow and shrubland

The Eastern North American Temperate Freshwater Marsh, Wet Meadow and Shrubland is a hydrologically dynamic ecosystem highly sensitive to shifts in water availability. Across the Midwest, climate change is expected to intensify two primary stressors, flooding and drought, resulting in increased hydrologic variability that may threaten the persistence of these wetlands. Increased spring precipitation and more frequent extreme rainfall events are projected to cause deeper, longer-lasting inundation, while rising temperatures, reduced snowpack, and heightened evaporative demand are likely to increase the frequency and severity of droughts. Changes in hydrology may significantly alter both habitat structure and community composition. Physical disturbance from scouring and erosion may intensify, while nutrient and sediment loading from surrounding land uses may lead to eutrophication and terrestrialization. Vegetation zonation is likely to become destabilized under more extreme hydrological conditions, with flood-tolerant or droughtadapted species replacing those with narrower hydrologic tolerances. The two habitat groups within this broader ecosystem show differing vulnerabilities. The Eastern North American Freshwater Marsh, including both Great Lakes coastal and inland systems, is considered among the most hydrologically dynamic and disturbance-prone wetland types. Vegetation in these marshes is typically stratified along water depth gradients, forming distinct zones that depend on variable hydrology to persist, but deep or prolonged inundation can disrupt this zonation and reduce plant diversity. In contrast, the Midwest Wet Prairie, Wet Meadow and Shrub Swamp, generally lacks persistent surface water and relies on precipitation and snowmelt to maintain seasonal saturation. As a result, this habitat group is especially prone to drying and potentially susceptible to woody encroachment and shifts toward drier-adapted plant communities. Across both habitat groups, invasive species are expected to gain a competitive edge under future climate conditions. Invasive wetland plants often exhibit high plasticity and can tolerate a wide range of disturbances and hydrologic conditions, allowing them to expand rapidly during both flood and drought periods. Interacting pressures underscore the growing vulnerability of the Eastern North American Temperate Freshwater Marsh, Wet Meadow and Shrubland under future climate scenarios.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗
USGS2017

Small mammals as indicators of climate, biodiversity, and ecosystem change

Climate is a driving evolutionary force for biodiversity in high-latitude Alaska. This region is complex and dynamic with high annual variation in temperature and light. Through deeper time, Alaska has experienced major climate extremes over much longer periodicity. For example, the Quaternary Period (the last ~2.5 million years), commonly known as the Ice Age, was punctuated by more than 20 major glacial-interglacial cycles. During glacial phases, water was locked up in ice sheets that covered much of North America, and the resulting lower sea levels exposed a land connection between Alaska and Siberia, a combined region known as Beringia (Figure 1). This isthmus provided vast expanses of land for species to inhabit, provided they could withstand potentially harsh polar conditions. Each extended glacial phase periodically transitioned into a shorter interglacial warm phase. These climate reversals melted continental ice sheets to expose corridors for reinvasion of terrestrial species, particularly those associated with forested habitats further south. Those species that survived at northern latitudes through repeated glacial-interglacial cycles formed the Arctic tundra communities that persist today. At present, Alaska supports diverse communities associated with both tundra and forests (Figure 2). These communities often interact with one another across latitudinal and elevational gradients, with tundra species generally found further north or higher in elevation. Alaska’s climate is continuing to change today, strongly influencing local environments and the distribution and dynamics of wildlife species.

Alaska, Siberia↗
USGS2023

Plant community predictions support the potential for big sagebrush range expansion adjacent to the leading edge

Big sagebrush ecosystems are widespread across drylands of western North America and provide numerous services, but the abundance of these ecosystems has declined substantially and the future of these ecosystems is uncertain. As a result, characterizing potential areas for expansion of these ecosystems is important. Species distribution models of the big sagebrush suggest areas of increasing climatic habitat suitability at northern latitudes under climate change scenarios. This implies the formation of a leading edge during a future big sagebrush range expansion. Such an expansion requires that current nearby range margin big sagebrush populations are stable and serve as future seed sources. Our goal was to quantify the impacts of future climate conditions on the plant community composition and biomass in the in range margin big sagebrush plant communities adjacent to the leading edge. We did this using an individual-based soil water and plant growth simulation model, STEPWAT2. We assessed community dynamics throughout the twenty-first century using 13 climate models under two representative concentration pathways to capture the variability among projections. Our results show minimal overall change in plant community composition and little change in biomass, suggesting that range margin big sagebrush plant communities adjacent to the leading edge will remain stable to serve as essential dispersal sources for future range expansion, assuming no other relevant changes such as changes in disturbance regimes. These assessments of plant community responses to shifts in climate and characterization of variability in future projections will help inform conservation planning and management of the big sagebrush ecosystem.

Regional Environmental Change↗
USGS2014

A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems

Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.

Annual Review of Ecology, Evolution, and Systemati↗
USGS2024

Wildfire probability estimated from recent climate and fine fuels across the big sagebrush region

Background Wildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush ( Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better understanding of long-term wildfire drivers across the big sagebrush region. Here, we integrated wildfire observations with climate and vegetation data to derive a statistical model for the entire big sagebrush region that represents how annual wildfire probability is influenced by climate and fine fuel characteristics. Results Wildfire frequency varied significantly across the sagebrush region, and our statistical model represented much of that variation. Biomass of annual and perennial grasses and forbs, which we used as proxies for fine fuels, influenced wildfire probability. Wildfire probability was highest in areas with high annual forb and grass biomass, which is consistent with the well-documented phenomenon of increased wildfire following annual grass invasion. The effects of annuals on wildfire probability were strongest in places with dry summers. Wildfire probability varied with the biomass of perennial grasses and forbs and was highest at intermediate biomass levels. Climate, which varies substantially across the sagebrush region, was also predictive of wildfire probability, and predictions were highest in areas with a low proportion of precipitation received in summer, intermediate precipitation, and high temperature. Conclusions We developed a carefully validated model that contains relatively simple and biologically plausible relationships, with the goal of adequate performance under novel conditions so that useful projections of average annual wildfire probability can be made given general changes in conditions. Previous studies on the impacts of vegetation and climate on wildfire probability in sagebrush ecosystems have generally used more complex machine learning approaches and have usually been applicable to only portions of the sagebrush region. Therefore, our model complements existing work and forms an additional tool for understanding future wildfire and ecological dynamics across the sagebrush region.

Fire Ecology↗
USGS2015

Coastal landforms and processes at the Cape Cod National Seashore, Massachusetts—A primer

Anyone who spends more than a few days on Cape Cod (the Cape) quickly becomes a coastal geologist, quickly learning the rhythms of daily tides and the seasonal cycles of beaches growing and being swept away by storms; swimmers and surfers track how the breakers appear, and dog-walkers notice the hard-packed sand blanketed overnight by an airy layer that leaves deep labored tracks. Careful observers whose paths wander to the ocean’s edge will observe many of the landforms and coastal processes described in this book and if we have done our job well, the stories told here will seem familiar. Watchful experience brings insights; indeed, this is how scientists and perhaps how artists work, describing patterns that explain and predict. When is the next high tide? What will the winter bring? Where do we build, fish, swim? How do wind and waves offshore in the North Atlantic help arrange the plants and dunes and hollows on the beach? And most of all, as human animals drawn to live and play on the edge of the ocean, how do we get the benefits of this complex natural system of geology and biology? How do we affect coastal processes; how is the coast changing now and how is the coast likely to change in years ahead with climate warming and climate change? This book is about the highly dynamic coastal landforms of Cape Cod—the beaches, bluffs, spits, dunes, barrier beaches, estuaries, and salt marshes. What they are, why they are where they are, how they behave with respect to the greater Cape Cod coastal system—how the landforms respond to day-to-day and long-term geologic processes, such as waves and currents, change in sediment transport, relative sea-level rise, and meteorological processes such as hurricanes, nor’easters, and cold front passages. It is also about how the landforms got to be where they are and the way they are and where they are headed in the near future with the predicted effects of global climate warming and change. Our objective is to provide a single source of understandable and readable scientific information for those who live, play, and work on outer Cape Cod and at the Cape Cod National Seashore, as well as to provide an introduction to Cape Cod’s coastal landforms for anyone with an interest in Earth science and nature who wants a better understanding of coastal systems and processes. Basic to an understanding of coastal landforms is the fact that they work together—they interact—as elements of many systems, and therefore our ultimate concern is not the individual landform itself but rather the geologic systems that make up Cape Cod and the Cape Cod National Seashore. Much of this discussion can be applied as well to Nantucket, Martha’s Vineyard, and other coastal regions. The coast of outer Cape Cod, about 15,000 years old and about 30 miles (mi; 50 kilometers [km]) long, is but a tiny piece of the global Earth system that operates within a much larger realm of space and time. Cape Cod’s coastal landforms are temporary holding patterns within a continual interplay of land, sea, atmosphere, climate, ice, and life, including a variety of human activities that both affect and are affected by these processes. These interactions produce the landforms, and the landforms alter the interactions. The resulting landforms provide habitats for a wide variety of coastal plants and animals. The habitats along with their inhabitants and the interacting environmental factors controlling them constitute the Cape’s complex and varied ecosystems. But for now, we are here to enjoy it. We welcome you to delight and wonder at the perpetually changing handshake between the ocean and shore at New England’s Great Beach.

Massachusetts↗
USGS1999

Le Conte's sparrows breeding in Conservation Reserve Program fields: precipitation and patterns of population change

The climate of the North American Great Plains is highly dynamic, with great year-to-year variability in precipitation and periodic, often extreme, wet and dry cycles (Bragg 1995). Drought is a major force of ecological disturbance on the Great Plains and has played a key role in directing the evolution of the grassland biota of this region (Knopf and Samson 1997). Although grassland birds may differ in their responses to enviromenental variations (Rotenberry and Wiens 1991), climatic variability and concomitant unpredictability of resources strongly influence populations of grassland birds across space and time (Wiens 1974, 1986; Cody 1985). Not surprisingly, breeding bird populations on the Great Plains are highly dynamic, exhibiting considerable annual variation in composition, abundance, and distribution (Johnson and Grier 1988, George et al. 1992, Zimmerman 1992, Igl and Johnson 1997). Recently, interest in grassland birds has increased with the recognition that many species are declining both continentally (Droege and Sauer 1994) and globally (Goriup 1988). Identification of the specific factors associated with grassland bird declines in North America, however, remains largely enigmatic (Herkert 1997), and it is complicated by the considerable annual fluctuations in grassland bird distribution and abundance (Igl and Johnson 1997). Although there is evidence that land-use changes on the breeding grounds may have contributed to grassland bird declines (e.g., Igl and Johnson 1997), there also is an indication that long-term drought conditions may have influenced recent population changes of some breeding birds on the Great Plains (Droege and Sauer 1989, Peterjohn and Sauer 1993, Bethke and Nudds 1995, Igl and Johnson 1997). Le Conte's Sparrow (Ammodramus leconteii) is a secretive grassland bird that breeds in central and southern Canada and the northcentral United States (Murray 1969). It winters primarily in the southern United States (Peterson 1980, 1990). Like populations of many grassland breeding birds in North America (Fretwell 1986, Igl and Johnson 1997), Le Conte's Sparrow populations exhibit numerical highs and lows depending on local moisture conditions (Peabody 1901, Stewart 1975, Knapton 1979, Zimmer 1979, Madden 1996). This observation, however, is based largely on anecdotal evidence or short-term observations. Long-term studies of Le Conte's Sparrow populations are limited. Le Conte's Sparrow is poorly represented on the North American Breeding Bird Survey (BBS) because of small sample sizes, poor coverage in the northern portion of its breeding range, and the species' furtive behavior (Sauer et al. 1995). Moreover, dramatic fluctuations in Le Conte's Sparrow abundance tend to obscure the species' long-term population trends on the BBS (Sauer et al. 1995). In this paper we examine long-term population changes of Le Conte's Sparrows breeding in perennial grassland fields enrolled in the Conservation Reserve Program (CRP) on the northern Great Plains. We discuss patterns of population change of Le Conte's Sparrows associated with changes in precipitation and moisture conditions.

Studies in Avian Biology↗
USGS2016

Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades

Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH 4 ) emissions in China is important for improving our knowledge on CH 4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH 4 model to quantify the human and climate change induced contributions to natural wetland CH 4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH 4 emissions reduction (0.92 TgCH 4 ), and climate change contributed 20.4% to the CH 4 emissions increase (0.31 TgCH 4 ), suggesting that decreasing CH 4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH 4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH 4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH 4 emissions estimation.

Scientific Reports↗
USGS2019

A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

Geoscientific Model Development↗
USGS2016

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty 1 , 2 . Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies 3 . Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

Nature Climate Change↗