Uncertainty Estimates and the Interpretation of Climate Change Forecasts

2012 ◽  
Author(s):  
Jared E. Leclerc ◽  
Susan Joslyn
Keyword(s):  
Climate Change ◽  
Uncertainty Estimates

Soil respiration under different agricultural land use types in Croatia

2021 ◽  
Author(s):  
Darija Bilandžija ◽  
Marija Galić ◽  
Željka Zgorelec
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Respiration ◽  
Management Practices ◽  
Agricultural Land ◽  
Ghg Emissions ◽  
Paris Agreement ◽  
Energy Crop ◽  
Climate Conditions ◽  
Uncertainty Estimates

<p>In order to mitigate climate change and reduce the anthropogenic greenhouse gas (GHG) emissions, the Kyoto protocol has been adopted in 1997 and the Paris Agreement entered into force in 2016. The Paris Agreement have ratified 190 out of 197 Parties of the United Nations Framework Convention on Climate Change (UNFCCC) and Croatia is one of them as well. Each Party has obliged regularly to submit the national inventory report (NIR) providing the information on the national anthropogenic GHG emissions by sources and removals by sinks to the UNFCCC. Reporting under the NIR is divided into six categories / sectors, and one of them is land use, land use change and forestry (LULUCF) sector, where an issue of uncertainty estimates on carbon emissions and removals occurs. As soil respiration represents the second-largest terrestrial carbon flux, the national studies on soil respiration can reduce the uncertainty and improve the estimation of country-level carbon fluxes. Due to the omission of national data, the members of the University of Zagreb Faculty of Agriculture, Department of General Agronomy have started to study soil respiration rates in 2012, and since then many different studies on soil respiration under different agricultural land uses (i.e. annual crops, energy crop and vineyard), management practices (i.e. tillage and fertilization) and climate conditions (i.e. continental and mediterranean) in Croatia have been conducted. The obtained site specific results on field measurements of soil carbon dioxide concentrations by <em>in situ</em> closed static chamber method will be presented in this paper.</p>

scholarly journals Reanalysing glacier mass balance measurement series

2013 ◽  
Vol 7 (4) ◽  
pp. 1227-1245 ◽  
Author(s):  
M. Zemp ◽  
E. Thibert ◽  
M. Huss ◽  
D. Stumm ◽  
C. Rolstad Denby ◽  
...  
Keyword(s):  
Climate Change ◽  
Data Quality ◽  
Mass Balance ◽  
Sea Level ◽  
Error Estimation ◽  
Standard Procedure ◽  
Systematic Errors ◽  
Glacier Mass Balance ◽  
Uncertainty Estimates ◽  
Measurement Series

Abstract. Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until recently, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without consideration of errors. In this study, we propose a framework for reanalysing glacier mass balance series that includes conceptual and statistical toolsets for assessment of random and systematic errors, as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme, drawing on an analysis that comprises over 50 recording periods for a dozen glaciers, and we make recommendations to investigators and users of glacier mass balance data. Reanalysing glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality, including reliable uncertainty estimates.

scholarly journals Refining error estimates for a millennial temperature reconstruction

2009 ◽  
Vol 5 (6) ◽  
pp. 2631-2668
Author(s):  
M. N. Juckes
Keyword(s):  
Climate Change ◽  
20Th Century ◽  
Error Estimates ◽  
Northern Hemisphere ◽  
Large Range ◽  
Temperature Reconstruction ◽  
Intergovernmental Panel ◽  
The Past ◽  
Uncertainty Estimates ◽  
Past Millennium

Abstract. The statistical uncertainties in a 1000 year Northern Hemisphere mean temperature reconstruction obtained from 15 proxy chronologies are examined in detail by analysing the range of estimates obtained from all possible subsets of the proxy collection with up to 6 proxies omitted. The study is motivated in part by the large range of recently published reconstructions in the 15th and 16th centuries. The uncertainty estimates support the conclusions of the 3rd and 4th Intergovernmental Panel on Climate Change (IPCC) assessment reports concerning the likelihood that temperatures at the end of the 20th century were likely (greater than 66% confidence) to have been exceptional. It is also shown that the last ten years to date have been warmer than any decade of the past millennium with 95% confidence.

scholarly journals Assessing Hydrologic Impact of Climate Change with Uncertainty Estimates: Bayesian Neural Network Approach

2010 ◽  
Vol 11 (2) ◽  
pp. 482-495 ◽  
Author(s):  
Mohammad Sajjad Khan ◽  
Paulin Coulibaly
Keyword(s):  
Neural Network ◽  
Climate Change ◽  
Rainfall Runoff ◽  
Bayesian Neural Network ◽  
Uncertainty Estimates ◽  
Change Impact ◽  
Climate Change Impact Study ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Different Sources

Abstract A major challenge in assessing the hydrologic effect of climate change remains the estimation of uncertainties associated with different sources, such as the global climate models, emission scenarios, downscaling methods, and hydrologic models. There is a demand for an efficient and easy-to-use rainfall–runoff modeling tool that can capture the different sources of uncertainties to generate future flow simulations that can be used for decision making. To manage the large range of uncertainties in the climate change impact study on water resources, a neural network–based rainfall–runoff model—namely, Bayesian neural network (BNN)—is proposed. The BNN model is used with Canadian Centre for Climate Modelling and Analysis Coupled GCM, versions 1 and 2 (CGCM1 and CGCM2, respectively) with two emission scenarios, Intergovernmental Panel on Climate Change (IPCC) IS92a and Special Report on Emissions Scenarios (SRES) B2. One widely used statistical downscaling model (SDSM) is used in the analysis. The study is undertaken to simulate daily river flow and daily reservoir inflow in the Serpent and the Chute-du-Diable watersheds, respectively, in northeastern Canada. It is found that the uncertainty bands of the mean ensemble flow (i.e., flow simulated using the mean of the ensemble members of downscaled meteorological variables) is able to mostly encompass all other flows simulated with various individual downscaled meteorological ensemble members whichever CGCM or emission scenario is used. In addition, the uncertainty bands are also able to typically encompass most of the flows simulated with another rainfall–runoff model, namely, Hydrologiska Byråns Vattenbalansavdelning (HBV). The study results suggest that the BNN model could be used as an effective hydrological modeling tool in assessing the hydrologic effect of climate change with uncertainty estimates in the form of confidence intervals. It could be a good alternative method where resources are not available to implement the general multimodel ensembles approach. The BNN approach makes the climate change impact study on water resources with uncertainty estimate relatively simple, cost effective, and time efficient.

A Hybrid Dynamical–Statistical Downscaling Technique. Part II: End-of-Century Warming Projections Predict a New Climate State in the Los Angeles Region

2015 ◽  
Vol 28 (12) ◽  
pp. 4618-4636 ◽  
Author(s):  
Fengpeng Sun ◽  
Daniel B. Walton ◽  
Alex Hall
Keyword(s):  
Climate Change ◽  
Los Angeles ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Regional Scale ◽  
Global Climate Models ◽  
First Century ◽  
Climate Change Signal ◽  
Uncertainty Estimates ◽  
Twenty First Century

Abstract Using the hybrid downscaling technique developed in part I of this study, temperature changes relative to a baseline period (1981–2000) in the greater Los Angeles region are downscaled for two future time slices: midcentury (2041–60) and end of century (2081–2100). Two representative concentration pathways (RCPs) are considered, corresponding to greenhouse gas emission reductions over coming decades (RCP2.6) and to continued twenty-first-century emissions increases (RCP8.5). All available global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are downscaled to provide likelihood and uncertainty estimates. By the end of century under RCP8.5, a distinctly new regional climate state emerges: average temperatures will almost certainly be outside the interannual variability range seen in the baseline. Except for the highest elevations and a narrow swath very near the coast, land locations will likely see 60–90 additional extremely hot days per year, effectively adding a new season of extreme heat. In mountainous areas, a majority of the many baseline days with freezing nighttime temperatures will most likely not occur. According to a similarity metric that measures daily temperature variability and the climate change signal, the RCP8.5 end-of-century climate will most likely be only about 50% similar to the baseline. For midcentury under RCP2.6 and RCP8.5 and end of century under RCP2.6, these same measures also indicate a detectable though less significant climatic shift. Therefore, while measures reducing global emissions would not prevent climate change at this regional scale in the coming decades, their impact would be dramatic by the end of the twenty-first century.

scholarly journals Uncertainties and re-analysis of glacier mass balance measurements

2013 ◽  
Vol 7 (2) ◽  
pp. 789-839 ◽  
Author(s):  
M. Zemp ◽  
E. Thibert ◽  
M. Huss ◽  
D. Stumm ◽  
C. Rolstad Denby ◽  
...  
Keyword(s):  
Climate Change ◽  
Data Quality ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Error Estimation ◽  
Standard Procedure ◽  
Systematic Errors ◽  
Glacier Mass Balance ◽  
Uncertainty Estimates

Abstract. Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until present, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without error considerations. In this study, we propose a framework for re-analyzing glacier mass balance series including conceptual and statistical toolsets for assessment of random and systematic errors as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme drawing on an analysis that comprises over 50 recording periods for a dozen glaciers and we make recommendations to investigators and users of glacier mass balance data. Reanalysis of glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality and provide thorough uncertainty estimates.

scholarly journals The State-of-the-Art of Urban Climate Change Modeling and Observations

2020 ◽  
Vol 4 (4) ◽  
pp. 631-646
Author(s):  
Rafiq Hamdi ◽  
Hiroyuki Kusaka ◽  
Quang-Van Doan ◽  
Peng Cai ◽  
Huili He ◽  
...  
Keyword(s):  
Climate Change ◽  
Spatial Data ◽  
Climate Models ◽  
Global Climate ◽  
Spatial Scales ◽  
Urban Expansion ◽  
Urban Climate ◽  
Coastal Hazards ◽  
Urban Structure ◽  
Uncertainty Estimates

AbstractAs an effect of climate change, cities need detailed information on urban climates at decision scale that cannot be easily delivered using current observation networks, nor global and even regional climate models. A review is presented of the recent literature and recommendations are formulated for future work. In most cities, historical observational records are too short, discontinuous, or of too poor quality to support trend analysis and climate change attribution. For climate modeling, on the other hand, specific dynamical and thermal parameterization dedicated to the exchange of water and energy between the atmosphere and the urban surfaces have to be implemented. Therefore, to fully understand how cities are impacted by climate change, it is important to have (1) simulations of the urban climate at fine spatial scales (including coastal hazards for coastal cities) integrating global climate scenarios with urban expansion and population growth scenarios and their associated uncertainty estimates, (2) urban climate observations, especially in Global South cities, and (3) spatial data of high resolution on urban structure and form, human behavior, and energy consumption.

Averting robo-bees: why free-flying robotic bees are a bad idea

2019 ◽  
Vol 3 (6) ◽  
pp. 723-729
Author(s):  
Roslyn Gleadow ◽  
Jim Hanan ◽  
Alan Dorin
Keyword(s):  
Climate Change ◽  
Computer Simulation ◽  
Food Security ◽  
European Countries ◽  
Plant Interactions ◽  
Plant Insect Interactions ◽  
Native Habitat ◽  
Insect Pollinators ◽  
Insect Interactions

Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduction of agricultural monocultures, and the destruction of insect native habitat, are all potential contributors to this grave situation. Some researchers are working towards a future where natural insect pollinators might be replaced with free-flying robotic bees, an ecologically problematic proposal. We argue instead that creating environments that are friendly to bees and exploring the use of other species for pollination and bio-control, particularly in non-European countries, are more ecologically sound approaches. The computer simulation of insect-plant interactions is a far more measured application of technology that may assist in managing, or averting, ‘Insect Armageddon' from both practical and ethical viewpoints.

Modelling ecosystem adaptation and dangerous rates of global warming

2019 ◽  
Vol 3 (2) ◽  
pp. 221-231 ◽  
Author(s):  
Rebecca Millington ◽  
Peter M. Cox ◽  
Jonathan R. Moore ◽  
Gabriel Yvon-Durocher
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Diffusion Rate ◽  
Individual Species ◽  
Genetic Evolution ◽  
Rates Of Change ◽  
Rapid Climate Change ◽  
Warming Climate ◽  
Intraspecies Competition ◽  
High Trait

Abstract We are in a period of relatively rapid climate change. This poses challenges for individual species and threatens the ecosystem services that humanity relies upon. Temperature is a key stressor. In a warming climate, individual organisms may be able to shift their thermal optima through phenotypic plasticity. However, such plasticity is unlikely to be sufficient over the coming centuries. Resilience to warming will also depend on how fast the distribution of traits that define a species can adapt through other methods, in particular through redistribution of the abundance of variants within the population and through genetic evolution. In this paper, we use a simple theoretical ‘trait diffusion’ model to explore how the resilience of a given species to climate change depends on the initial trait diversity (biodiversity), the trait diffusion rate (mutation rate), and the lifetime of the organism. We estimate theoretical dangerous rates of continuous global warming that would exceed the ability of a species to adapt through trait diffusion, and therefore lead to a collapse in the overall productivity of the species. As the rate of adaptation through intraspecies competition and genetic evolution decreases with species lifetime, we find critical rates of change that also depend fundamentally on lifetime. Dangerous rates of warming vary from 1°C per lifetime (at low trait diffusion rate) to 8°C per lifetime (at high trait diffusion rate). We conclude that rapid climate change is liable to favour short-lived organisms (e.g. microbes) rather than longer-lived organisms (e.g. trees).

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