Does the model regional bias affect the projected regional climate change? An analysis of global model projections

An analysis is presented of the dependence of the regional temperature and precipitation change signal on systematic regional biases in global climate change projections. The CMIP3 multi-model ensemble is analyzed over 26 land regions and for the A1B greenhouse gas emission scenario. For temperature, the model regional bias has a negligible effect on the projected regional change. For precipitation, a significant correlation between change and bias is found in about 30% of the seasonal/regional cases analyzed, covering a wide range of different climate regimes. For these cases, a performance-based selection of models in producing climate change scenarios can affect the resulting change estimate, and it is noted that a minimum of four to five models is needed to obtain robust precipitation change estimates. In a number of cases, models with largely different precipitation biases can still produce changes of consistent sign. Overall, it is assessed that in the present generation of models the regional bias does not appear to be a dominant factor in determining the simulated regional change in the majority of cases.     

Atmospheric moisture budget estimates of regional evapotranspiration from RES‐91

Abstract

Diurnal changes in the local atmospheric moisture budget over the Canadian Prairies are computed using sequential radiosonde soundings from the 1991 Regional Evaporation Study (RES‐91). Previous attempts to estimate evapotranspiration with radiosonde data have used either similarity theory or a moisture budget, but have been confined to the boundary layer in either case. These studies, as well as semi‐empiric operational techniques which use surface‐based data, exclude the effects of moisture advection and energy exchanges between the boundary layer and the free atmosphere, assuming negligible effects on evapotranspiration. The moisture budget method adopted here includes horizontal advection explicitly, and treats vertical fluxes implicitly through a total tropospheric moisture budget.

Comparison of the evapotranspiration estimates with those of other techniques are positive only when results are averaged over several days to weeks. While the advection estimates are a major source of error for the “daily” estimates in this particular study, it is shown that neither advection nor moisture flux through the boundary layer can be ignored in estimating daily evapotranspiration, regardless of the technique used. The results also suggest that evapotranspiration is more variable on a daily basis than other techniques have indicated. With an improved synoptic database now available for advection estimates, the moisture budget technique may provide an excellent ground‐truth method for fine‐tuning techniques for remote sensing of evapotranspiration, and could lead to improved parametrization schemes for both NWP models and GCMs.     

The 15‐km version of the Canadian regional forecast system

Abstract

A new mesoscale version of the regional forecast system became operational at the Canadian Meteorological Centre on 18 May 2004. The main changes to the regional modelling system include an increase in both the horizontal and vertical resolutions (15‐km horizontal resolution and 58 vertical levels instead of 24‐km resolution and 28 levels) as well as major upgrades to the physics package. The latter consist of a new condensation package, with an improved formulation of the cloudy boundary layer, a new shallow convection scheme based on a Kuo‐type closure, and the Kain and Fritsch deep convection scheme, together with a subgrid‐scale orography parametrization scheme to represent gravity wave drag and low‐level blocking effects. The new forecast system also includes a few changes to the regional data assimilation such as additional radiance data from satellites.

Objective verifications using a series of cases and parallel runs, along with subjective evaluations by CMC meteorologists, indicate significantly improved performance using the new 15‐km resolution forecast system. We can conclude from these verifications that the model exhibits a marked reduction in errors, improved predictability by about 12 hours, better forecasts of precipitation, a significant reduction in the spin‐up time, and a different implicit‐explicit partitioning of precipitation. A number of other features include: sharper precipitation patterns, better representation of trace precipitation, and general improvements of deepening lows and hurricanes. In mountainous regions, several aspects are better represented due to combined higher‐resolution orography and the low‐level blocking term.     

SPOM: A regional model of the sub‐polar north Atlantic

Abstract

A regional model of the sub‐polar North Atlantic has been developed for use in process and variability studies of this important high‐latitude area. Open boundary conditions handle connections with the rest of the Atlantic Ocean at 38°N, while buffer zones are used in the northern boundary regions. Extensive testing and experimentation has led to a model which can reproduce major elements of the hydrography and circulation in the region, although limitations exist. A key model feature is the inclusion of a finite volume partial cell topographic representation that significantly improves the structure of the underlying bottom topography. Improvements include a tighter and sharper gyre structure, increased transports, sub‐polar mode water formation sites linked to the topographic slope along the outside of the gyre and a more reasonable representation of Labrador Sea water properties and dispersal pathways. The choice of inflow conditions for the open southern boundary affects the deep western boundary current, as well as the representation of Mediterranean Water, which has a significant effect on Labrador Sea water in the eastern basin.     

The Bise—Climatology of a regional wind north of the Alps

Summary The Bise is one of several regional winds in the Alpine area occuring in connection with postfrontal pressure rise and cold air advection. Like the Mistral, the Bise is also induced by a synoptiscale 850hPa pressure gradient (dp/dn _(NESW)1 hPa/100 km) and strongly determined by orographic effects.Apart from the classical postfrontal Bise in Spring, a deep Bise with strong cold air advection and sometimes rain appears during winter. A rough survey of the factors determining the wind profile during Bise, which is quite often characterized by a low-level jet structure, shows that dynamical effects induced by the topography like flow splitting, channeling and the formation of countercurrents may be very important.With 11 Figures     

High resolution regional climate model simulations for Germany: part I—validation

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.     

Can ensembles of regional climate model simulations improve results from sensitivity studies?

Intrinsic variability (IV) in regional climate models (RCMs) is often assumed to be small because at climatological timescales, the model solutions tend to be dominated by the model??s lateral boundary conditions. Recent studies have indicated that this IV may actually be large in certain instances for some variables. Direct interpretation of anomalies from RCM sensitivity studies relies on the assumption that differences between model simulations are entirely due to a physical forcing. However, if IV is as large or larger than the physical signal, then this assumption is violated. Using a 20 member ensemble of RCM simulations, we verify that IV of precipitation within a RCM can be large enough to violate the sensitivity study assumption, and we show that generating ensembles of simulations can help reduce the level of IV. We also present two indicators that can rule out the influence of IV when it is ambiguous whether anomalies within a sensitivity study are due to the sensitivity perturbation or whether they are due to IV.     

Using Föhn conditions to characterize urban and regional sources of particles

Characterizations of urban and regional sources of particulate matter (PM) were performed in the Milan area (North of Italy) during Föhn and stagnant (non-Föhn) conditions. The measurements were performed at two different places: in an urban area North of Milan (Bresso) and in a regional area at the EMEP-GAW station in Ispra (about 65 km NW from Milan) during the winter periods of the years 2002–2007. Particle size distributions and chemical bulk analysis of aerosols are combined with single particle mass spectrometry to obtain information about the chemical content of the particles and their mixing state. Föhn conditions are characterized by extremely clean background air from which background aerosol is scavenged, and consequently local sources (here defined as sources between the sampling sites and the mountain range top about 100–150 km away depending on the wind direction) determine the aerosol properties.It was observed that during Föhn events the accumulation mode in the size range 50 nm < d < 300 nm practically disappears and that the size fraction below 50 nm dominates the total number distribution. The significant change in the number size distribution and the large decrease in PM10 mass during Föhn events are accompanied by a significant change in the chemical composition of the particles. Results from bulk chemical analysis showed high amounts of carbonaceous compounds and very low concentrations of ammonium nitrate (as indicator for secondary chemistry) during Föhn episodes, in contrast to stagnant conditions, when secondary components are dominating the aerosol composition. Single particle measurements confirm the high contribution of carbonaceous compounds in locally emitted particles.It was concluded that particles that originated in the urban area come mainly from combustion processes, especially direct traffic emissions, domestic heating and industrial activities, whereas the regionally emitted particles are different with much less traffic contribution.We estimate that under prevailing (non-Föhn) winter conditions, about 50–65% of the aerosol mass load in the city of Milan are caused by local emissions, and about 35–50% come from regional background. This finding suggests that in order to improve air quality in a big city like Milan, it is important to combine local traffic restriction interventions with other long-term regional scale air-quality-measures.     

A scaling analysis of soil moisture–precipitation interactions in a regional climate model

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found that high soil moisture resulted in greater precipitation amounts and a higher frequency of events, suggesting the occurrence of a positive soil moisture–precipitation feedback. The scaling analysis performed on cumulative precipitation determined that these fields did not exhibit signs of self-similarity and, therefore, statistical properties cannot be predicted at other resolutions. The scaling properties of soil moisture were highly variable in time which has important implications for the use of remotely sensed data, as scaling properties from 1 day cannot necessarily be applied to subsequent days.     

Meeting the EU 2°C climate target: global and regional emission implications

Abstract

This article presents a set of multi-gas emission pathways for different CO₂-equivalent concentration stabilization levels, i.e. 400, 450, 500 and 550 ppm CO₂-equivalent, along with an analysis of their global and regional reduction implications and implied probability of achieving the EU climate target of 2°C. For achieving the 2°C target with a probability of more than 60%, greenhouse gas concentrations need to be stabilized at 450 ppm CO₂-equivalent or below, if the 90% uncertainty range for climate sensitivity is believed to be 1.5–4.5°C. A stabilization at 450 ppm CO₂-equivalent or below (400 ppm) requires global emissions to peak around 2015, followed by substantial overall reductions of as much as 25% (45% for 400 ppm) compared to 1990 levels in 2050. In 2020, Annex I emissions need to be approximately 15% (30%) below 1990 levels, and non-Annex I emissions also need to be reduced by 15–20% compared to their baseline emissions. A further delay in peaking of global emissions by 10 years doubles maximum reduction rates to about 5% per year, and very probably leads to high costs. In order to keep the option open of stabilizing at 400 and 450 ppm CO₂-equivalent, the USA and major advanced non-Annex I countries will have to participate in the reductions within the next 10–15 years.     

Addressing regional disparities in allowance allocation in China’s national emissions trading scheme

China's national emissions trading scheme (ETS) is expected to be operational in 2017. Effectively addressing regional disparities at the provincial level in allowance allocation will greatly affect the acceptance of the allocation approach and thus deserves careful consideration. This article aims to explore possible approaches for addressing regional disparities, by introducing regional adjustment factors (RAF) in free allowance allocation. Based on the principle of ‘national unified rules?+?stricter adjustment by provincial authorities’, four single factorial and three multi-factorial methods are proposed to calculate the RAFs, through a normalization process. These methods are associated with the most acknowledged factors dealing with regional disparities, including per-capita GDP; per-capita CO₂ emissions; industrial sector contribution to GDP; economy-wide emissions control targets and CO₂ emissions per unit GDP, per unit power and heat output and per unit industrial added value. A comparative analysis is made for the seven methods, in regard to value distribution and level of matching regional political demand.

Key policy insights

• ‘Allowing stricter regional adjustment’ represents a dominant feature for China's national ETS, which aims to address regional disparities and government demands.

• How the adjustment plan is designed will have a major influence on the operation of the national ETS and regional business competitiveness. Provincial governments need to consider the trade-off between auction revenue and local business competitiveness.

• Applying the different methods leads to more scattered results for some regions, for whom the choice of adjustment approach will therefore have a greater impact.

• Based on the analysis, four adjustment methods that generate similar results – the per-capita GDP-based method, the intensity reduction target-based method, the 12th FYP target-based method and intensity-based grandfathering – are recommended for most provincial-level regions, with some exceptions.

     

Simulation of the Indian monsoon using the RegCM3–ROMS regional coupled model

A regional coupled atmosphere–ocean model was developed to study the role of air–sea interactions in the simulation of the Indian summer monsoon. The coupled model includes the regional climate model (RegCM3) as atmospheric component and the regional ocean modeling system (ROMS) as oceanic component. The two-way coupled model system exchanges sea surface temperature (SST) from the ocean to the atmospheric model and surface wind stress and energy fluxes from the atmosphere to the ocean model. The coupled model is run for four years 1997, 1998, 2002 and 2003 and the results are compared with observations and atmosphere-only model runs employing Reynolds SSTs as lower boundary condition. It is found that the coupled model captures the main features of the Indian monsoon and simulates a substantially more realistic spatial and temporal distribution of monsoon rainfall compared to the uncoupled atmosphere-only model. The intraseasonal oscillations are also better simulated in the coupled model compared to the atmosphere-only model. These improvements are due to a better representation of the feedbacks between the SST and convection and highlight the importance of air–sea coupling in the simulation of the Indian monsoon.     

“Grand Paris”: regional landscape change to adapt city to climate warming

“Grand Paris” is a study carried out by ten teams of researchers and city planners in the aim of putting forward general guidelines for Paris urban area’s evolution by 2030. All the teams suggest making the area “greener” in some way, to combat climate warming by CO₂ sequestration. Our team also shows that extending the nearby forests by 30 %, favouring short farm-to-consumer circuits and using lighter coloured building materials will decrease the urban heat island, reducing the mortality during heat waves as well as the need for air-conditioning. These results lead us to reverse the way of thinking urban planning: the geographic and natural aspects should replace the urban infrastructure as a driver for planning urban development. This new strategy allows city changes on quite a large scale, that will have a favourable impact in terms of economics, leisure activities, greenhouse gas emissions and the local microclimate.     

Application of a “Big-Tree” model to regional climate modeling: a sensitivity study

Summary ¶In order to better understand land-atmosphere interactions and increase the predictability of climate models, it is important to investigate the role of forest representation in climate modeling. Corresponding to the big-leaf model commonly employed in land surface schemes to represent the effects of a forest, a so called big-tree model, which uses multi-layer vegetation to represent the vertical canopy heterogeneity, was introduced and incorporated into the National Center for Atmospheric Research (NCAR) regional climate model RegCM2, to make the vegetation model more physically based. Using this augmented RegCM2 and station data for China during 1991 Meiyu season, we performed 10 experiments to investigate the effects of the application of the big-tree model on the summer monsoon climate.With the big-tree model incorporated into the regional climate model, some climate characteristics, e.g. the 3-month-mean surface temperature, circulation, and precipitation, are significantly and systematically changed over the model domain, and the change of the characteristics differs depending on the area. Due to the better representation of the shading effect in the big-tree model, the temperature of the lower layer atmosphere above the plant canopy is increased, which further influences the 850hPa temperature. In addition, there are significant decreases in the mean latent heat fluxes (within 20–30W/m²) in the three areas of the model domain.The application of the big-tree model influences not only the simulated climate of the forested area, but also that of the whole model domain, and its impact is greater on the lower atmosphere than on the upper atmosphere. The simulated rainfall and surface temperature deviate from the originally simulated result and are (or seem to be) closer to the observations, which implies that an appropriate representation of the big-tree model may improve the simulation of the summer monsoon climate.We also find that the simulated climate is sensitive to some big-tree parameter values and schemes, such as the shape, height, zero-plane displacement height and mixing-length scheme. The simulated local/grid differences may be very large although the simulated areal-average differences may be much lower. The area-average differences in the monthly-mean surface temperature and heat fluxes can amount to 0.5°C and 4W/m², respectively, which correspond to maximum local/grid differences of 3.0°C and 40W/m² respectively. It seems that the simulated climate is most sensitive to the parameter of the zero-plane displacement among the parameters studied.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

Projected climate change scenario over California by a regional ocean–atmosphere coupled model system

This study examines a future climate change scenario over California in a 10-km coupled regional downscaling system of the Regional Spectral Model for the atmosphere and the Regional Ocean Modeling System for the ocean forced by the global Community Climate System Model version 3.0 (CCSM3). In summer, the coupled and uncoupled downscaled experiments capture the warming trend of surface air temperature, consistent with the driving CCSM3 forcing. However, the surface warming change along the California coast is weaker in the coupled downscaled experiment than it is in the uncoupled downscaling. Atmospheric cooling due to upwelling along the coast commonly appears in both the present and future climates, but the effect of upwelling is not fully compensated for by the projected large-scale warming in the coupled downscaling experiment. The projected change of extreme warm events is quite different between the coupled and uncoupled downscaling experiments, with the former projecting a more moderate change. The projected future change in precipitation is not significantly different between coupled and uncoupled downscaling. Both the coupled and uncoupled downscaling integrations predict increased onshore sea breeze change in summer daytime and reduced offshore land breeze change in summer nighttime along the coast from the Bay area to Point Conception. Compared to the simulation of present climate, the coupled and uncoupled downscaling experiments predict 17.5 % and 27.5 % fewer Catalina eddy hours in future climate respectively.     

Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations

The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.     

Empowering NGOs? Long-term effects of ecological and institutional change on regional fisheries management organizations

The participation of environmental non-governmental organizations (ENGOs) in regional fisheries management organizations has inspired optimism among many observers and researchers about increasing the effectiveness of these regional organizations in managing highly migratory and straddling fish stocks sustainably. Others claim that the attendance of ENGOs in meetings of regional fisheries management organizations as accredited observers or as part of member state or cooperating non-member state delegations, could make decision-making complex, long, and inefficient. More generally, NGO participation has attracted broad scholarly interest in the study of interest groups and transnational advocacy in political science. Yet, we know little about the determinants of ENGO participation in meetings of regional fisheries management organizations in the first place. To fill this gap, this article develops a theoretical framework conceptualizing ENGO participation and developing expectations about how ecological and institutional change shapes ENGO participation. The framework deals with structural determinants of ENGO participation, as existing literature primarily has been preoccupied with the study of actor-specific explanations of specific NGOs’ impact in specific political processes. By contrast, we examine how ecological change – such as target fish stock health and biomass status – and institutional change – such as financial resources, membership composition of regional fisheries management organizations and participation by other non-state actors, such as experts and fishing industry representatives – shape ENGO participation. We empirically explore this framework in the context of seven regional fisheries management organizations. A dataset comprising yearly fish stock-level data on participation, institutional, and ecological factors, for 1980–2014, was compiled for our quantitative inquiry into the determinants of ENGO participation. We find robust evidence that institutional change shapes ENGO participation, but not ecological factors related to target fish stock health. We discuss our findings against the backdrop of ongoing debates about NGOs in political science, and spell out broader implications for future research on NGOs in regional fisheries management organizations.     

The impacts avoided with a 1.5 °C climate target: a global and regional assessment

The 2015 Paris Agreement commits countries to pursue efforts to limit the increase in global mean temperature to 1.5 °C above pre-industrial levels. We assess the consequences of achieving this target in 2100 for the impacts that are avoided, using several indicators of impact (exposure to drought, river flooding, heat waves and demands for heating and cooling energy). The proportion of impacts that are avoided is not simply equal to the proportional reduction in temperature. At the global scale, the median proportion of projected impacts avoided by the 1.5 °C target relative to a rise of 4 °C ranges between 62 and 95% across sectors: the greatest reduction is for heat wave impacts. The 1.5 °C target results in impacts that would be between 27 and 62% lower than with the 2 °C target. For each indicator, there are differences in the proportions of impacts avoided between regions depending on exposure and the regional changes in climate (particularly precipitation). Uncertainty in the proportion of impacts that are avoided for a specific sector depends on the range in the shape of the relationship between global temperature change and impact, and this varies between sectors.