Quantifying uncertainty in remotely sensed land cover maps

Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems

To bridge the gaps between traditional mesoscale modelling and microscale modelling, the National Center for Atmospheric Research, in collaboration with other agencies and research groups, has developed an integrated urban modelling system coupled to the weather research and forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modelling system consists of the following: (1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor–outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, (2) coupling to fine-scale computational fluid dynamic Reynolds-averaged Navier–Stokes and Large-Eddy simulation models for transport and dispersion (T&D) applications, (3) procedures to incorporate high-resolution urban land use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and (4) an urbanized high-resolution land data assimilation system. This paper provides an overview of this modelling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary-layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modelling system illustrate its promising utility, as a regional climate-modelling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios. Copyright © 2010 Royal Meteorological Society

Reducing inconsistencies in point observations of maximum flood inundation level

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

Probabilistic skill in ensemble seasonal forecasts

Simulation models are widely employed to make probability forecasts of future conditions on seasonal to annual lead times. Added value in such forecasts is reflected in the information they add, either to purely empirical statistical models or to simpler simulation models. An evaluation of seasonal probability forecasts from the Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction (DEMETER) and ENSEMBLES multi-model ensemble experiments is presented. Two particular regions are considered: Nino3.4 in the Pacific and the Main Development Region in the Atlantic; these regions were chosen before any spatial distribution of skill was examined. The ENSEMBLES models are found to have skill against the climatological distribution on seasonal time-scales. For models in ENSEMBLES that have a clearly defined predecessor model in DEMETER, the improvement from DEMETER to ENSEMBLES is discussed. Due to the long lead times of the forecasts and the evolution of observation technology, the forecast-outcome archive for seasonal forecast evaluation is small; arguably, evaluation data for seasonal forecasting will always be precious. Issues of information contamination from in-sample evaluation are discussed and impacts (both positive and negative) of variations in cross-validation protocol are demonstrated. Other difficulties due to the small forecast-outcome archive are identified. The claim that the multi-model ensemble provides a ‘better’ probability forecast than the best single model is examined and challenged. Significant forecast information beyond the climatological distribution is also demonstrated in a persistence probability forecast. The ENSEMBLES probability forecasts add significantly more information to empirical probability forecasts on seasonal time-scales than on decadal scales. Current operational forecasts might be enhanced by melding information from both simulation models and empirical models. Simulation models based on physical principles are sometimes expected, in principle, to outperform empirical models; direct comparison of their forecast skill provides information on progress toward that goal.

The implications of climate change for the water environment in England

This paper reviews the implications of climate change for the water environment and its management in England. There is a large literature, but most studies have looked at flow volumes or nutrients and none have considered explicitly the implications of climate change for the delivery of water management objectives. Studies have been undertaken in a small number of locations. Studies have used observations from the past to infer future changes, and have used numerical simulation models with climate change scenarios. The literature indicates that climate change poses risks to the delivery of water management objectives, but that these risks depend on local catchment and water body conditions. Climate change affects the status of water bodies, and it affects the effectiveness of measures to manage the water environment and meet policy objectives. The future impact of climate change on the water environment and its management is uncertain. Impacts are dependent on changes in the duration of dry spells and frequency of ‘flushing’ events, which are highly uncertain and not included in current climate scenarios. There is a good qualitative understanding of ways in which systems may change, but interactions between components of the water environment are poorly understood. Predictive models are only available for some components, and model parametric and structural uncertainty has not been evaluated. The impacts of climate change depend on other pressures on the water environment in a catchment, and also on the management interventions that are undertaken to achieve water management objectives. The paper has also developed a series of consistent conceptual models describing the implications of climate change for pressures on the water environment, based around the source-pathway-receptor concept. They provide a framework for a systematic assessment across catchments and pressures of the implications of climate change for the water environment and its management.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.

Climate change modelling and its roles to chinese crops yield

Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10% for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out

Towards improving the framework for probabilistic forecast evaluation

The evaluation of forecast performance plays a central role both in the interpretation and use of forecast systems and in their development. Different evaluation measures (scores) are available, often quantifying different characteristics of forecast performance. The properties of several proper scores for probabilistic forecast evaluation are contrasted and then used to interpret decadal probability hindcasts of global mean temperature. The Continuous Ranked Probability Score (CRPS), Proper Linear (PL) score, and IJ Good’s logarithmic score (also referred to as Ignorance) are compared; although information from all three may be useful, the logarithmic score has an immediate interpretation and is not insensitive to forecast busts. Neither CRPS nor PL is local; this is shown to produce counter intuitive evaluations by CRPS. Benchmark forecasts from empirical models like Dynamic Climatology place the scores in context. Comparing scores for forecast systems based on physical models (in this case HadCM3, from the CMIP5 decadal archive) against such benchmarks is more informative than internal comparison systems based on similar physical simulation models with each other. It is shown that a forecast system based on HadCM3 out performs Dynamic Climatology in decadal global mean temperature hindcasts; Dynamic Climatology previously outperformed a forecast system based upon HadGEM2 and reasons for these results are suggested. Forecasts of aggregate data (5-year means of global mean temperature) are, of course, narrower than forecasts of annual averages due to the suppression of variance; while the average “distance” between the forecasts and a target may be expected to decrease, little if any discernible improvement in probabilistic skill is achieved.

Variation of System Performance with Design and Climate for Combisystems in Sweden

In Sweden, 90% of the solar heating systems are solar domestic hot water and heating systems (SDHW&H), so called combisystems. These generally supply most of the domestic hot water needs during the summer and have enough capacity to supply some energy to the heating system during spring and autumn. This paper describes a standard Swedish combisystem and how the output from it varies with heating load, climate within Sweden, and how it can be increased with improved system design. A base case is defined using the standard combi- system, a modern Swedish single family house and the climate of Stockholm. Using the simulation program Trnsys, parametric studies have been performed on the base case and improved system designs. The solar fraction could be increased from 17.1% for the base case to 22.6% for the best system design, given the same system size, collector type and load. A short analysis of the costs of changed system design is given, showing that payback times for additional investment are from 5-8 years. Measurements on system components in the laboratory have been used to verify the simulation models used. More work is being carried out in order to find even better system designs, and further improvements in system performance are expected.

Testing of combined heating systems for small houses: Improved procedures for whole system test methods : Deliverable 2.3

Dynamic system test methods for heating systems were developed and applied by the institutes SERC and SP from Sweden, INES from France and SPF from Switzerland already before the MacSheep project started. These test methods followed the same principle: a complete heating system – including heat generators, storage, control etc., is installed on the test rig; the test rig software and hardware simulates and emulates the heat load for space heating and domestic hot water of a single family house, while the unit under test has to act autonomously to cover the heat demand during a representative test cycle. Within the work package 2 of the MacSheep project these similar – but different – test methods were harmonized and improved. The work undertaken includes:  • Harmonization of the physical boundaries of the unit under test. • Harmonization of the boundary conditions of climate and load. • Definition of an approach to reach identical space heat load in combination with an autonomous control of the space heat distribution by the unit under test. • Derivation and validation of new six day and a twelve day test profiles for direct extrapolation of test results.   The new harmonized test method combines the advantages of the different methods that existed before the MacSheep project. The new method is a benchmark test, which means that the load for space heating and domestic hot water preparation will be identical for all tested systems, and that the result is representative for the performance of the system over a whole year. Thus, no modelling and simulation of the tested system is needed in order to obtain the benchmark results for a yearly cycle. The method is thus also applicable to products for which simulation models are not available yet. Some of the advantages of the new whole system test method and performance rating compared to the testing and energy rating of single components are:  • Interaction between the different components of a heating system, e.g. storage, solar collector circuit, heat pump, control, etc. are included and evaluated in this test. • Dynamic effects are included and influence the result just as they influence the annual performance in the field. • Heat losses are influencing the results in a more realistic way, since they are evaluated under "real installed" and representative part-load conditions rather than under single component steady state conditions.   The described method is also suited for the development process of new systems, where it replaces time-consuming and costly field testing with the advantage of a higher accuracy of the measured data (compared to the typically used measurement equipment in field tests) and identical, thus comparable boundary conditions. Thus, the method can be used for system optimization in the test bench under realistic operative conditions, i.e. under relevant operating environment in the lab.   This report describes the physical boundaries of the tested systems, as well as the test procedures and the requirements for both the unit under test and the test facility. The new six day and twelve day test profiles are also described as are the validation results.

Granularity and disaggregation in compositional modelling with applications to ecological systems

In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling.

Efeitos da utilização de hedges cambiais nos resultados de empresas não financeiras: uma abordagem empírica

A realização de negócios em um mundo globalizado implica em aumentar a exposição das empresas não-financeiras a diversos riscos de origem financeira como câmbio, commodities e taxas de juros e que, dependendo da evolução destas variáveis macroeconômicas, podem afetar significativamente os resultados destas empresas. Existem diversas teorias acadêmicas que abordam sobre os benefícios gerados por programas de gestão de riscos em empresas não-financeiras como redução dos custos de financial distress e custos de agência bem como o uso de estratégias de hedge para fins fiscais. Tais iniciativas contribuiriam, em última instância, para a criação de valor para o negócio e poderiam garantir uma melhor previsibilidade dos fluxos de caixa futuros, tornando as empresas menos vulneráveis a condições adversas de mercado. Este trabalho apresenta dois estudos de caso com empresas não-financeiras brasileiras que possuíam exposições em moeda estrangeira e que não foram identificadas operações com derivativos cambiais durante o período de 1999 a 2005 que foi caracterizado pela alta volatilidade da taxa de câmbio. Através de modelos de simulação, algumas estratégias com o uso de derivativos foram propostas para as exposições cambiais identificadas para cada empresa com o objetivo de avaliar os efeitos da utilização destes derivativos cambiais sobre os resultados das empresas no que se refere à agregação de valor para o negócio e redução de volatilidade dos fluxos de caixa esperados. O trabalho não visa recomendar estratégias de hedge para determinada situação de mercado mas apenas demonstra, de forma empírica, quais os resultados seriam obtidos caso certas estratégias fossem adotadas, sabendo-se que inúmeras outras poderiam ser criadas para a mesma situação de mercado. Os resultados sugerem alguns insights sobre a utilização de derivativos por empresas não-financeiras sendo um tema relativamente novo para empresas brasileiras.

A influência de decisões arquitetônicas na eficiência energética do Campus vol. 1/UFRN

Building design is an effective way to achieve HVAC energy consumption reduction. However, this potentiality is often neglected by architects due to the lack of references to support design decisions. This works intends to propose architectural design guidelines for energy efficiency and thermal performance of Campus/UFRN buildings. These guidelines are based on computer simulations results using the software DesignBuilder. The definition of simulation models has begun with envelope variables, partially done after a field study of thirteen buildings at UFRN/Campus. This field study indicated some basic envelope patterns that were applied in simulation models. Occupation variables were identified with temperature and energy consumption monitoring procedures and a verification of illumination and equipment power, both developed at the Campus/UFRN administration building. Three simulation models were proposed according to different design phases and decisions. The first model represents early design decisions, simulating the combination of different types of geometry with three levels of envelope thermal performance. The second model, still as a part of early design phase, analyses thermal changes between circulation halls lateral and central and office rooms, as well as the heat fluxes and monthly temperatures in each circulation hall. The third model analyses the influence of middle-design and detail design decisions on energy consumption and thermal performance. In this model, different solutions of roofs, shading devices, walls and external colors were simulated. The results of all simulation models suggest a high influence of thermal loads due to the incidence of solar radiation on windows and surfaces, which highlights the importance of window shading devices, office room orientation and absorptance of roof and walls surfaces

Estudo do acoplamento do poço injetor nas simulações de injeção cíclica de vapor

Steam injection is a method usually applied to very viscous oils and consists of injecting heat to reduce the viscosity and, therefore, increase the oil mobility, improving the oil production. For designing a steam injection project it is necessary to have a reservoir simulation in order to define the various parameters necessary for an efficient heat reservoir management, and with this, improve the recovery factor of the reservoir. The purpose of this work is to show the influence of the coupled wellbore/reservoir on the thermal simulation of reservoirs under cyclic steam stimulation. In this study, the methodology used in the solution of the problem involved the development of a wellbore model for the integration of steam flow model in injection wellbores, VapMec, and a blackoil reservoir model for the injection of cyclic steam in oil reservoirs. Thus, case studies were developed for shallow and deep reservoirs, whereas the usual configurations of injector well existing in the oil industry, i.e., conventional tubing without packer, conventional tubing with packer and insulated tubing with packer. A comparative study of the injection and production parameters was performed, always considering the same operational conditions, for the two simulation models, non-coupled and a coupled model. It was observed that the results are very similar for the specified well injection rate, whereas significant differences for the specified well pressure. Finally, on the basis of computational experiments, it was concluded that the influence of the coupled wellbore/reservoir in thermal simulations using cyclic steam injection as an enhanced oil recovery method is greater for the specified well pressure, while for the specified well injection rate, the steam flow model for the injector well and the reservoir may be simulated in a non- coupled way