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Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model
B. Yang, Y. Qian, G. Lin, R. Leung,Y. Zhang
Atmospheric Chemistry and Physics (ACP) & Discussions (ACPD) , 2012,
Abstract: The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across p
Regional climate model data used within the SWURVE project – 2: addressing uncertainty in regional climate model data for five European case study areas
B. Hingray, A. Mezghani,T. A. Buishand
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2007,
Abstract: To produce probability distributions for regional climate change in surface temperature and precipitation, a probability distribution for global mean temperature increase has been combined with the probability distributions for the appropriate scaling variables, i.e. the changes in regional temperature/precipitation per degree global mean warming. Each scaling variable is assumed to be normally distributed. The uncertainty of the scaling relationship arises from systematic differences between the regional changes from global and regional climate model simulations and from natural variability. The contributions of these sources of uncertainty to the total variance of the scaling variable are estimated from simulated temperature and precipitation data in a suite of regional climate model experiments conducted within the framework of the EU-funded project PRUDENCE, using an Analysis Of Variance (ANOVA). For the area covered in the 2001–2004 EU-funded project SWURVE, five case study regions (CSRs) are considered: NW England, the Rhine basin, Iberia, Jura lakes (Switzerland) and Mauvoisin dam (Switzerland). The resulting regional climate changes for 2070–2099 vary quite significantly between CSRs, between seasons and between meteorological variables. For all CSRs, the expected warming in summer is higher than that expected for the other seasons. This summer warming is accompanied by a large decrease in precipitation. The uncertainty of the scaling ratios for temperature and precipitation is relatively large in summer because of the differences between regional climate models. Differences between the spatial climate-change patterns of global climate model simulations make significant contributions to the uncertainty of the scaling ratio for temperature. However, no meaningful contribution could be found for the scaling ratio for precipitation due to the small number of global climate models in the PRUDENCE project and natural variability, which is often the largest source of uncertainty. In contrast, for temperature, the contribution of natural variability to the total variance of the scaling ratio is small, in particular for the annual mean values. Simulation from the probability distributions of global mean warming and the scaling ratio results in a wider range of regional temperature change than that in the regional climate model experiments. For the regional change in precipitation, however, a large proportion of the simulations (about 90%) is within the range of the regional climate model simulations.
Quantification of structural uncertainty in climate data records from GPS radio occultation
A. K. Steiner, D. Hunt, S.-P. Ho, G. Kirchengast, A. J. Mannucci, B. Scherllin-Pirscher, H. Gleisner, A. von Engeln, T. Schmidt, C. Ao, S. S. Leroy, E. R. Kursinski, U. Foelsche, M. Gorbunov, S. Heise, Y.-H. Kuo, K. B. Lauritsen, C. Marquardt, C. Rocken, W. Schreiner, S. Sokolovskiy, S. Syndergaard,J. Wickert
Atmospheric Chemistry and Physics (ACP) & Discussions (ACPD) , 2013,
Abstract: Global Positioning System (GPS) radio occultation (RO) has provided continuous observations of the Earth's atmosphere since 2001 with global coverage, all-weather capability, and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS). Precise time measurements enable long-term stability but careful processing is needed. Here we provide climate-oriented atmospheric scientists with multicenter-based results on the long-term stability of RO climatological fields for trend studies. We quantify the structural uncertainty of atmospheric trends estimated from the RO record, which arises from current processing schemes of six international RO processing centers, DMI Copenhagen, EUM Darmstadt, GFZ Potsdam, JPL Pasadena, UCAR Boulder, and WEGC Graz. Monthly-mean zonal-mean fields of bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature from the CHAMP mission are compared for September 2001 to September 2008. We find that structural uncertainty is lowest in the tropics and mid-latitudes (50° S to 50° N) from 8 km to 25 km for all inspected RO variables. In this region, the structural uncertainty in trends over 7 yr is <0.03% for bending angle, refractivity, and pressure, <3 m for geopotential height of pressure levels, and <0.06 K for temperature; low enough for detecting a climate change signal within about a decade. Larger structural uncertainty above about 25 km and at high latitudes is attributable to differences in the processing schemes, which undergo continuous improvements. Though current use of RO for reliable climate trend assessment is bound to 50° S to 50° N, our results show that quality, consistency, and reproducibility are favorable in the UTLS for the establishment of a climate benchmark record.
Quantification of structural uncertainty in climate data records from GPS radio occultation
A. K. Steiner,D. Hunt,S.-P. Ho,G. Kirchengast
Atmospheric Chemistry and Physics Discussions , 2012, DOI: 10.5194/acpd-12-26963-2012
Abstract: Global Positioning System (GPS) radio occultation (RO) provides continuous observations of the Earth's atmosphere since 2001 with global coverage, all-weather capability, and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS). Precise time measurements enable long-term stability but careful processing is needed. Here we provide climate-oriented atmospheric scientists with multicenter-based results on the long-term stability of RO climatological fields for trend studies. We quantify the structural uncertainty of atmospheric trends estimated from the RO record, which arises from current processing schemes of six international RO processing centers, DMI Copenhagen, EUM Darmstadt, GFZ Potsdam, JPL Pasadena, UCAR Boulder, and WEGC Graz. Monthly-mean zonal-mean fields of bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature from the CHAMP mission are compared for September 2001 to September 2008. We find that structural uncertainty is lowest in the tropics and mid-latitudes (50° S to 50° N) from 8 km to 25 km for all inspected RO variables. In this region, the structural uncertainty in trends over 7 yr is <0.03% f or bending angle, refractivity, and pressure, <3 m for geopotential height of pressure levels, and <0.06 K for temperature; low enough for detecting a climate change signal within about a decade. Larger structural uncertainty above about 25 km and at high latitudes is attributable to differences in the processing schemes, which undergo continuous improvements. Though current use of RO for reliable climate trend assessment is bound to 50° S to 50° N, our results show that quality, consistency, and reproducibility are favorable in the UTLS for the establishment of a climate benchmark record.
European atmosphere in 2050, a regional air quality and climate perspective under CMIP5 scenarios
A. Colette,B. Bessagnet,R. Vautard,S. Szopa
Atmospheric Chemistry and Physics Discussions , 2013, DOI: 10.5194/acpd-13-6455-2013
Abstract: To quantify changes in air pollution in Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant and relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent Representative Concentrations Pathways (RCP) produced for the Fifth Assessment Report (AR5) of IPCC whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 °C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Climate Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or long range transport. Whereas the well documented "climate penalty" bearing upon ozone over Europe is confirmed, other features appear less robust compared to the literature: such as the impact of climate on PM2.5. The quantitative disentangling of each contributing factor shows that the magnitude of the ozone climate penalty has been overstated in the past while on the contrary the contribution of the global ozone burden is overlooked in the literature.
An integrated assessment modelling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)
E. Monier,J. R. Scott,A. P. Sokolov,C. E. Forest
Geoscientific Model Development Discussions , 2013, DOI: 10.5194/gmdd-6-2213-2013
Abstract: This paper describes an integrated assessment modelling framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyse uncertainties in emissions resulting from both uncertainties in the economic model parameters and uncertainty in future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. Thus, the IGSM-CAM is a computationally efficient framework to explore the uncertainty in future global and regional climate change associated with uncertainty in the climate response and projected emissions. This study presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) and three sets of climate parameters. The chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century global climate change. As such, this study presents new estimates of the 90% probability interval of regional climate change for different emissions scenarios. These results underscore the large uncertainty in regional climate change resulting from uncertainty in climate parameters and emissions, especially when it comes to changes in precipitation.
Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios: A Case Study of Swedish Precipitation
Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios: A Case Study of Swedish Precipitation

Deliang Chen,Christine Achberger,Jouni R?is?nen,Cecilia Hellstr?m,
Deliang CHEN
,Christine ACHBERGER,Jouni R¨AIS¨ANEN,Cecilia HELLSTR¨OM

大气科学进展 , 2006,
Abstract: There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project (CMIP2) are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.
Climate change and hydropower production in the Swiss Alps: quantification of potential impacts and related modelling uncertainties
B. Hingray, N. Mouhous, A. Mezghani, K. Bogner, B. Schaefli,A. Musy
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2007,
Abstract: A probabilistic assessment of climate change and related impacts should consider a large range of potential future climate scenarios. State-of-the-art climate models, especially coupled atmosphere-ocean general circulation models and Regional Climate Models (RCMs) cannot, however, be used to simulate such a large number of scenarios. This paper presents a methodology for obtaining future climate scenarios through a simple scaling methodology. The projections of several key meteorological variables obtained from a few regional climate model runs are scaled, based on different global-mean warming projections drawn in a probability distribution of future global-mean warming. The resulting climate change scenarios are used to drive a hydrological and a water management model to analyse the potential climate change impacts on a water resources system. This methodology enables a joint quantification of the climate change impact uncertainty induced by the global-mean warming scenarios and the regional climate response. It is applied to a case study in Switzerland, a water resources system formed by three interconnected lakes located in the Jura Mountains. The system behaviour is simulated for a control period (1961–1990) and a future period (2070–2099). The potential climate change impacts are assessed through a set of impact indices related to different fields of interest (hydrology, agriculture and ecology). The results obtained show that future climate conditions will have a significant influence on the performance of the system and that the uncertainty induced by the inter-RCM variability will contribute to much of the uncertainty of the prediction of the total impact. These CSRs cover the area considered in the 2001–2004 EU funded project SWURVE.
Decadal regional air quality simulations over Europe in present climate: near surface ozone sensitivity to external meteorological forcing
E. Katragkou, P. Zanis, I. Tegoulias, D. Melas, I. Kioutsioukis, B. C. Krüger, P. Huszar, T. Halenka,S. Rauscher
Atmospheric Chemistry and Physics (ACP) & Discussions (ACPD) , 2010,
Abstract: Regional climate-air quality decadal simulations over Europe were carried out with the RegCM3/CAMx modeling system for the time slice 1991–2000, in order to study the impact of different meteorological forcing on surface ozone. The RegCM3 regional climate model was firstly constrained by the ERA40 reanalysis dataset which is considered as an experiment with perfect meteorological boundary conditions and then it was constrained by the global circulation model ECHAM5. A number of meteorological parameters were examined including the 500 mb geopotential height, solar radiation, temperature, cloud liquid water path, planetary boundary layer height and surface wind. The different RegCM meteorological forcing resulted in changes of near surface ozone over Europe ranging between ± 4 ppb for winter and summer. The area showing the greatest sensitivity in O3 during winter is central and southern Europe while in summer central north continental Europe. The different meteorological forcing impacts on the atmospheric circulation, which in turn affects cloudiness and solar radiation, temperature, wind patterns and the meteorology depended biogenic emissions. For comparison reasons, the impact of chemical boundary conditions on surface ozone was additionally examined with a series of sensitivity studies, indicating that surface ozone changes are comparable to those caused by the different meteorological forcing. These findings suggest that, when it comes to regional climate-air quality simulations, the selection of external meteorological forcing can be as important as the selection of adequate chemical lateral boundary conditions.
Decadal regional air quality simulations over Europe in present climate: near surface ozone sensitivity to external meteorological forcing  [PDF]
E. Katragkou,P. Zanis,I. Tegoulias,D. Melas
Atmospheric Chemistry and Physics (ACP) & Discussions (ACPD) , 2010, DOI: 10.5194/acp-10-11805-2010
Abstract: Regional climate-air quality decadal simulations over Europe were carried out with the RegCM3/CAMx modeling system for the time slice 1991–2000, in order to study the impact of different meteorological forcing on surface ozone. The RegCM3 regional climate model was firstly constrained by the ERA40 reanalysis dataset which is considered as an experiment with perfect meteorological boundary conditions and then it was constrained by the global circulation model ECHAM5. A number of meteorological parameters were examined including the 500 mb geopotential height, solar radiation, temperature, cloud liquid water path, planetary boundary layer height and surface wind. The different RegCM meteorological forcing resulted in changes of near surface ozone over Europe ranging between ± 4 ppb for winter and summer. The area showing the greatest sensitivity in O3 during winter is central and southern Europe while in summer central north continental Europe. The different meteorological forcing impacts on the atmospheric circulation, which in turn affects cloudiness and solar radiation, temperature, wind patterns and the meteorology depended biogenic emissions. For comparison reasons, the impact of chemical boundary conditions on surface ozone was additionally examined with a series of sensitivity studies, indicating that surface ozone changes are comparable to those caused by the different meteorological forcing. These findings suggest that, when it comes to regional climate-air quality simulations, the selection of external meteorological forcing can be as important as the selection of adequate chemical lateral boundary conditions.
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