Using the Regional Ocean Modeling System (ROMS) to improve the ocean circulation from a GCM 20<Superscript>th</Superscript> century simulation

Global coupled climate models are generally capable of reproducing the observed trends in the globally averaged atmospheric temperature. However, the global models do not perform as well on regional scales. Here, we present results from a 20-year, high-resolution ocean model experiment for the Atlantic and Arctic Oceans. The atmospheric forcing is taken from the final 20 years of a twentieth-century control run with a coupled atmosphere–ocean general circulation model. The ocean model results from the regional ocean model are validated using observations of hydrography from repeat cruises in the Barents Sea. Validation is performed for average quantities and for probability distributions in space and time. The validation results reveal that, though the regional model is forced by a coupled global model that has a noticeable sea ice bias in the Barents Sea, the hydrography and its variability are reproduced with an encouraging quality. We attribute this improvement to the realistic transport of warm, salty waters into the Barents Sea in the regional model. These lateral fluxes in the ocean are severely underestimated by the global model. The added value with the regional model that we have documented here lends hope to advance the quality of oceanic climate change impact studies.     

A Bayesian hierarchical approach for spatial analysis of climate model bias in multi-model ensembles

Coupled atmosphere–ocean general circulation models are key tools to investigate climate dynamics and the climatic response to external forcings, to predict climate evolution and to generate future climate projections. Current general circulation models are, however, undisputedly affected by substantial systematic errors in their outputs compared to observations. The assessment of these so-called biases, both individually and collectively, is crucial for the models’ evaluation prior to their predictive use. We present a Bayesian hierarchical model for a unified assessment of spatially referenced climate model biases in a multi-model framework. A key feature of our approach is that the model quantifies an overall common bias that is obtained by synthesizing bias across the different climate models in the ensemble, further determining the contribution of each model to the overall bias. Moreover, we determine model-specific individual bias components by characterizing them as non-stationary spatial fields. The approach is illustrated based on the case of near-surface air temperature bias in the tropical Atlantic and bordering regions from a multi-model ensemble of historical simulations from the fifth phase of the Coupled Model Intercomparison Project. The results demonstrate the improved quantification of the bias and interpretative advantages allowed by the posterior distributions derived from the proposed Bayesian hierarchical framework, whose generality favors its broader application within climate model assessment.     

Transport of salt and freshwater in the Atlantic Subpolar Gyre

Transport of salt in the Irminger Current, the northern branch of the Atlantic Subpolar Gyre coupling the eastern and western subpolar North Atlantic, plays an important role for climate variability across a wide range of time scales. High-resolution ocean modeling and observations indicate that salinities in the eastern subpolar North Atlantic decrease with enhanced circulation of the North Atlantic subpolar gyre (SPG). This has led to the perception that a stronger SPG also transports less salt westward. In this study, we analyze a regional ocean model and a comprehensive global coupled climate model, and show that a stronger SPG transports more salt in the Irminger Current irrespective of lower salinities in its source region. The additional salt converges in the Labrador Sea and the Irminger Basin by eddy transports, increases surface salinity in the western SPG, and favors more intense deep convection. This is part of a positive feedback mechanism with potentially large implications for climate variability and predictability.     

Effect of modelling scale on the assessment of climate change impact on river runoff

Abstract

The effect of using two distributed hydrological models with different degrees of spatial aggregation on the assessment of climate change impact on river runoff was investigated. Analyses were conducted in the Narew River basin situated in northeast Poland using a global hydrological model (WaterGAP) and a catchment-scale hydrological model (SWAT). Climate change was represented in both models by projected changes in monthly temperature and precipitation between the period 2040–2069 and the baseline period, resulting from two general circulation models: IPSL-CM4 and MIROC3.2, both coupled with the SRES A2 emissions scenario. The degree of consistency between the global and the catchment model was very high for mean annual runoff, and medium for indicators of high and low runoff. It was observed that SWAT generally suggests changes of larger magnitude than WaterGAP for both climate models, but SWAT and WaterGAP were consistent as regards the direction of change in monthly runoff. The results indicate that a global model can be used in Central and Eastern European lowlands to identify hot-spots where a catchment-scale model should be applied to evaluate, e.g. the effectiveness of management options.

Editor D. Koutsoyiannis; Associate editor F.F. Hattermann

Citation Piniewski, M., Voss, F., Bärlund, I., Okruszko, T., and Kundzewicz. Z.W., 2013. Effect of modelling scale on the assessment of climate change impact on river runoff. Hydrological Sciences Journal, 58 (4), 737–754.     

Estimating trends of Atlantic meridional overturning circulation from long-term hydrographic data and model simulations

The ocean meridional overturning circulation (MOC) plays a central role for the climate in the Atlantic realm. Since scenarios for future climate change indicate a significant reduction of the MOC under global warming, an assessment of variations and trends of the real MOC is important. Using observations at ocean weather ship (OWS) stations and along oceanic sections, we examine the hydrographic information that can be used to determine MOC trends via its signature in water mass properties obtained from model simulations with the climate model ECHAM5/MPI-OM. We show that temperature trends at mid-latitudes provide useful indirect measure of large-scale changes of deep circulation: A mid-depth warming is related to MOC weakening and a cooling to MOC strengthening. Based on our model experiments, we argue that a continuation of measurements at key OWS sites may contribute to a timely detection of a possible future MOC slowdown and to separate the signal from interannual-to-multidecadal MOC variability. The simulations suggest that the subsurface hydrographic information related to MOC has a lower variability than the MOC trend measured directly. Based on our model and the available long-term hydrographic data, we estimate non-significant MOC trends for the last 80 years. For the twenty-first century, however, the model simulations predict a significant MOC decline and accompanied mid-depth warming trend.     

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.     

On the physics of the Atlantic Multidecadal Oscillation

The Atlantic Multidecadal Oscillation (AMO) is a pronounced signal of climate variability in the North Atlantic sea-surface temperature field. In this paper, we propose an explanation of the physical processes responsible for the timescale and the spatial pattern of the AMO. Our approach involves the analysis of solutions of a hierarchy of models. In the lowest member of the model hierarchy, which is an ocean-only model for flow in an idealized basin, the variability shows up as a multidecadal oscillatory mode which is able to destabilize the mean thermohaline circulation. In the highest member of the model hierarchy, which is the Geophysical Fluid Dynamics Laboratory R30 climate model, multidecadal variability is found as a dominant statistical mode of variability. The connection between both results is established by tracing the spatial and temporal expression of the multidecadal mode through the model hierarchy while monitoring changes in specific quantities (mechanistic indicators) associated with its physics. The proposed explanation of the properties of the AMO is eventually based on the changes in the spatial patterns of variability through the model hierarchy.Responsible Editor: Tal Ezer     

A coarse resolution North Atlantic ocean circulation model: an intercomparison study with a paleoceanographic example

Paleoreconstructions suggest that during the Last Glacial Maximum (LGM) the North Atlantic circulation was noticeably different from its present state. However, the glacial salt conveyor belt is believed to be similar to the present-day’s conveyor, albeit weaker and shallower because of an increased freshwater flux in high-latitudes. We present here the investigation of the conveyor operation based on ocean circulation modelling using two numerical models in parallel. The GFDL primitive equation model and a planetary geostrophic model are employed to address the problem of the paleocirculation modelling in cases of uncertain and sparse data comprising the glacial surface boundary conditions. The role of different simplifications that may be used in the ocean climate studies, including the role of grid resolution, bottom topography, coast-line, etc., versus glacial-interglacial changes of the ocean surface climatology is considered. The LGM reverse conveyor gyre appeared to be the most noticeable feature of the glacial-to-interglacial alteration of the ocean circulation. The reversed upper-ocean conveyor, weaker and subducting ‘normal’ conveyor in the intermediate depths, and the change of the deep-ocean return flow route are robust signatures of the glacial North Atlantic climate. The results are found to be ‘model-independent’ and fairly insensitive to all factors other than the onset of the glacial surface conditions.     

How the performance of hydrological models relates to credibility of projections under climate change

Two approaches can be distinguished in studies of climate change impacts on water resources when accounting for issues related to impact model performance: (1) using a multi-model ensemble disregarding model performance, and (2) using models after their evaluation and considering model performance. We discuss the implications of both approaches in terms of credibility of simulated hydrological indicators for climate change adaptation. For that, we discuss and confirm the hypothesis that a good performance of hydrological models in the historical period increases confidence in projected impacts under climate change, and decreases uncertainty of projections related to hydrological models. Based on this, we find the second approach more trustworthy and recommend using it for impact assessment, especially if results are intended to support adaptation strategies. Guidelines for evaluation of global- and basin-scale models in the historical period, as well as criteria for model rejection from an ensemble as an outlier, are also suggested.     

Distributed modelling of future changes in hydrological processes of Spencer Creek watershed

The hydrologic impact of climate change has been largely assessed using mostly conceptual hydrologic models. This study investigates the use of distributed hydrologic model for the assessment of the climate change impact for the Spencer Creek watershed in Southern Ontario (Canada). A coupled MIKE SHE/MIKE 11 hydrologic model is developed to represent the complex hydrologic conditions in the Spencer Creek watershed, and later to simulate climate change impact using Canadian global climate model (CGCM 3·1) simulations. Owing to the coarse resolution of GCM data (daily GCM outputs), statistical downscaling techniques are used to generate higher resolution data (daily precipitation and temperature series). The modelling results show that the coupled model captured the snow storage well and also provided good simulation of evapotranspiration (ET) and groundwater recharge. The simulated streamflows are consistent with the observed flows at different sites within the catchment. Using a conservative climate change scenario, the downscaled GCM scenarios predicted an approximately 14–17% increase in the annual mean precipitation and 2–3 °C increase in annual mean maximum and minimum temperatures for the 2050s (i.e., 2046–2065). When the downscaled GCM scenarios were used in the coupled model, the model predicted a 1–5% annual decrease in snow storage for 2050s, approximately 1–10% increase in annual ET, and a 0·5–6% decrease in the annual groundwater recharge. These results are consistent with the downscaled temperature results. For future streamflows, the coupled model indicated an approximately 10–25% increase in annual streamflows for all sites, which is consistent with the predicted changes in precipitation. Overall, it is shown that distributed hydrologic modelling can provide useful information not only about future changes in streamflow but also changes in other key hydrologic processes such as snow storage, ET, and groundwater recharge, which can be particularly important depending on the climatic region of concern. The study results indicate that the coupled MIKE SHE/MIKE 11 hydrologic model could be a particularly useful tool for understanding the integrated effect of climate change in complex catchment scale hydrology. Copyright © 2010 John Wiley & Sons, Ltd.     

An intermediate coupled model for the tropical ocean-atmosphere system

An intermediate ocean-atmosphere coupled model is developed to simulate and predict the tropical interannual variability. Originating from the basic physical framework of the Zebiak-Cane(ZC) model, this tropical intermediate couple model(TICM) extends to the entire global tropics, with a surface heat flux parameterization and a surface wind bias correction added to improve model performance and inter-basin connections. The model well reproduces the variabilities in the tropical Pacific and Indian basins. The simulated El Ni?o-Southern Oscillation(ENSO) shows a period of 3–4 years and an amplitude of about 2°C, similar to those observed. The variabilities in the Indian Ocean, including the Indian Ocean basin mode(IOBM) and the Indian Ocean Dipole(IOD), are also reasonably captured with a realistic relationship to the Pacific. However, the tropical Atlantic variability in the TICM has a westward bias and is overly influenced by the tropical Pacific. A 47-year hindcast experiment using the TICM for the period of 1970–2016 indicates that ENSO is the most predictable mode in the tropics. Skillful predictions of ENSO can be made one year ahead, similar to the skill of the latest version of the ZC model, while a "spring predictability barrier" still exists as in other models. In the tropical Indian Ocean, the predictability seems much higher in the west than in the east. The correlation skill of IOD prediction reaches 0.5 at a 5-month lead, which is comparable to that of the state-of-the-art coupled general circulation models. The prediction of IOD shows a significant "winter-spring predictability barrier", implying combined influences from the tropical Pacific and the local sea-air interaction in the eastern Indian Ocean. The TICM has little predictive skill in the equatorial Atlantic for lead times longer than 3 months, which is a common problem of current climate models badly in need of further investigation.     

Analysis of uncertainties in the hydrological response of a model‐based climate change impact assessment in a subcatchment of the Spree River,Germany

Climate change impact assessments form the basis for the development of suitable climate change adaptation strategies. For this purpose, ensembles consisting of stepwise coupled models are generally used [emission scenario → global circulation model → downscaling approach (DA) → bias correction → impact model (hydrological model)], in which every item is affected by considerable uncertainty. The aim of the current study is (1) to analyse the uncertainty related to the choice of the DA as well as the hydrological model and its parameterization and (2) to evaluate the vulnerability of the studied catchment, a subcatchment of the highly anthropogenically impacted Spree River catchment, to hydrological change. Four different DAs are used to drive four different model configurations of two conceptually different hydrological models (Water Balance Simulation Model developed at ETH Zürich and HBV‐light). In total, 452 simulations are carried out. The results show that all simulations compute an increase in air temperature and potential evapotranspiration. For precipitation, runoff and actual evapotranspiration, opposing trends are computed depending on the DA used to drive the hydrological models. Overall, the largest source of uncertainty can be attributed to the choice of the DA, especially regarding whether it is statistical or dynamical. The choice of the hydrological model and its parameterization is of less importance when long‐term mean annual changes are compared. The large bandwidth at the end of the modelling chain may exacerbate the formulation of suitable climate change adaption strategies on the regional scale. Copyright © 2013 John Wiley & Sons, Ltd.     

Response of a Coupled Ocean�CAtmosphere Model to Greenland Ice Melting

We investigate the transient response of the global coupled ocean?Catmosphere system to enhanced freshwater forcing representative of melting of the Greenland ice sheets. A 50-year long simulation by a coupled atmosphere?Cocean general circulation model (CGCM) is compared with another of the same length in which Greenland melting is prescribed. To highlight the importance of coupled atmosphere?Cocean processes, the CGCM results are compared with those of two other experiments carried out with the oceanic general circulation model (OGCM). In one of these OGCM experiments, the prescribed surface fluxes of heat, momentum and freshwater correspond to the unperturbed simulation by the CGCM; in the other experiment, Greenland melting is added to the freshwater flux. The responses by the CGCM and OGCM to the Greenland melting have similar patterns in the Atlantic, albeit the former having five times larger amplitudes in sea surface height anomalies. The CGCM shows likewise stronger variability in all state variables in all ocean basins because the impact of Greenland melting is quickly communicated to all ocean basins via atmospheric bridges. We conclude that the response of the global climate to Greenland ice melting is highly dependent on coupled atmosphere?Cocean processes. These lead to reduced latent heat flux into the atmosphere and an associated increase in net freshwater flux into the ocean, especially in the subpolar North Atlantic. The combined result is a stronger response of the coupled system to Greenland ice sheet melting.     

Toward Improved Estimation of the Dynamic Topography and Ocean Circulation in the High Latitude and Arctic Ocean: The Importance of GOCE

The Arctic plays a fundamental role in the climate system and shows significant sensitivity to anthropogenic climate forcing and the ongoing climate change. Accelerated changes in the Arctic are already observed, including elevated air and ocean temperatures, declines of the summer sea ice extent and sea ice thickness influencing the albedo and CO₂ exchange, melting of the Greenland Ice Sheet and increased thawing of surrounding permafrost regions. In turn, the hydrological cycle in the high latitude and Arctic is expected to undergo changes although to date it is challenging to accurately quantify this. Moreover, changes in the temperature and salinity of surface waters in the Arctic Ocean and Nordic Seas may also influence the flow of dense water through the Denmark Strait, which are found to be a precursor for changes in the Atlantic meridional overturning circulation with a lead time of around 10 years (Hawkins and Sutton in Geophys Res Lett 35:L11603, 2008). Evidently changes in the Arctic and surrounding seas have far reaching influences on regional and global environment and climate variability, thus emphasizing the need for advanced quantitative understanding of the ocean circulation and transport variability in the high latitude and Arctic Ocean. In this respect, this study combines in situ hydrographical data, surface drifter data and direct current meter measurements, with coupled sea ice–ocean models, radar altimeter data and the latest GOCE-based geoid in order to estimate and assess the quality, usefulness and validity of the new GOCE-derived mean dynamic topography for studies of the ocean circulation and transport estimates in the Nordic Seas and Arctic Ocean.     

Feature of thermohaline circulation in two-layer conceptual model based on energy constraint

The assertion that the thermohaline circulation(THC)is driven and sustained by mechanical energy has been increasingly accepted.The simplest conceptual model describing the THC is the Stommel two-box model.Given the vertical stratification in the real ocean,layered models were designed and used.In this research,using a two-layer conceptual model based on energy constraint,we studied basic features of thermal-mode and saline-mode circulations.We focused on the effects of freshwater flux and mixing energy on the intensity and multiple equilibrium states of the THC.The results show that more important than affecting the THC intensity,both the decrease of freshwater flux and increase of mixing energy can lead to an"abrupt transition"in the THC from a stable saline to a stable thermal mode,which further develops the THC energy theory.     

The effect of climate and land use change on flow duration in the Maryland Piedmont region

This paper describes the use of a continuous streamflow model to examine the effects of climate and land use change on flow duration in six urbanizing watersheds in the Maryland Piedmont region. The hydrologic model is coupled with an optimization routine to achieve an agreement between observed and simulated streamflow. Future predictions are made for three scenarios: future climate change, land use change, and jointly varying climate and land use. Future climate is modelled using precipitation and temperature predictions for the Canadian Climate Centre (CCC) and Hadley climate models. Results show that a significant increase in temperature under the CCC climate predictions produces a decreasing trend in low flows. A significant increasing trend in precipitation under the Hadley climate predictions produces an increasing trend in peak flows. Land use change by itself, as simulated by an additional 10% increase in imperviousness (from 20·5 to 30·5%), produces no significant changes in the simulated flow durations. However, coupling the effects of land use change with climate change leads to more significant decreasing trends in low flows under the CCC climate predictions and more significant increasing trends in peak flows under Hadley climate predictions than when climate change alone is employed. These findings indicate that combined land use and climate change can result in more significant hydrologic change than either driver acting alone. Copyright © 2008 John Wiley & Sons, Ltd.     

Large scale climate and rainfall seasonality in a Mediterranean Area: Insights from a non‐homogeneous Markov model applied to the Agro‐Pontino plain

In the context of climate change and variability, there is considerable interest in how large scale climate indicators influence regional precipitation occurrence and its seasonality. Seasonal and longer climate projections from coupled ocean–atmosphere models need to be downscaled to regional levels for hydrologic applications, and the identification of appropriate state variables from such models that can best inform this process is also of direct interest. Here, a Non‐Homogeneous Hidden Markov Model (NHMM) for downscaling daily rainfall is developed for the Agro‐Pontino Plain, a coastal reclamation region very vulnerable to changes of hydrological cycle. The NHMM, through a set of atmospheric predictors, provides the link between large scale meteorological features and local rainfall patterns. Atmospheric data from the NCEP/NCAR archive and 56‐years record (1951–2004) of daily rainfall measurements from 7 stations in Agro‐Pontino Plain are analyzed. A number of validation tests are carried out, in order to: 1) identify the best set of atmospheric predictors to model local rainfall; 2) evaluate the model performance to capture realistically relevant rainfall attributes as the inter‐annual and seasonal variability, as well as average and extreme rainfall patterns. Validation tests show that the best set of atmospheric predictors are the following: mean sea level pressure, temperature at 1000 hPa, meridional and zonal wind at 850 hPa and precipitable water, from 20°N to 80°N of latitude and from 80°W to 60°E of longitude. Furthermore, the validation tests show that the rainfall attributes are simulated realistically and accurately. The capability of the NHMM to be used as a forecasting tool to quantify changes of rainfall patterns forced by alteration of atmospheric circulation under climate change and variability scenarios is discussed.     

Projected risks to groundwater‐dependent terrestrial vegetation caused by changing climate and groundwater abstraction in the Central Perth Basin,Western Australia

The effect of potential climate change on groundwater‐dependent vegetation largely depends on the nature of the climate change (drying or wetting) and the level of current ecosystem dependence on groundwater resources. In south‐western Australia, climate projections suggest a high likelihood of a warmer and drier climate. The paper examines the potential environmental impacts by 2030 at the regional scale on groundwater‐dependent terrestrial vegetation (GDTV) adapted to various watertable depths, on the basis of the combined consideration of groundwater modelling results and the framework for GDTV risk assessment. The methodology was tested for the historical period from 1984 to 2007, allowing validation of the groundwater model results' applicability to such an assessment. Climate change effects on GDTV were evaluated using nine global climate models under three greenhouse gas emission scenarios by applying the climate projections to groundwater models. It was estimated that under dry climate scenarios, GDTV is likely to be under high and severe risk over more than 20% of its current habitat area. The risk is also likely to be higher under an increase in groundwater abstraction above current volumes. The significance of climate change risk varied across the region, depending on both the intensity of the change in water regime and the sensitivity of the GDTV to such change. Greater effects were projected for terrestrial vegetation dependent on deeper groundwater (6–10 m). Copyright © 2013 John Wiley & Sons, Ltd.     

Downscaling IPCC control run and future scenario with focus on the Barents Sea

Global atmosphere-ocean general circulation models are the tool by which projections for climate changes due to radiative forcing scenarios have been produced. Further, regional atmospheric downscaling of the global models may be applied in order to evaluate the details in, e.g., temperature and precipitation patterns. Similarly, detailed regional information is needed in order to assess the implications of future climate change for the marine ecosystems. However, regional results for climate change in the ocean are sparse. We present the results for the circulation and hydrography of the Barents Sea from the ocean component of two global models and from a corresponding pair of regional model configurations. The global models used are the GISS AOM and the NCAR CCSM3. The ROMS ocean model is used for the regional downscaling of these results (ROMS-G and ROMS-N configurations, respectively). This investigation was undertaken in order to shed light on two questions that are essential in the context of regional ocean projections: (1) How should a regional model be set up in order to take advantage of the results from global projections; (2) What limits to quality in the results of regional models are imposed by the quality of global models? We approached the first question by initializing the ocean model in the control simulation by a realistic ocean analysis and specifying air-sea fluxes according to the results from the global models. For the projection simulation, the global models’ oceanic anomalies from their control simulation results were added upon initialization. Regarding the second question, the present set of simulations includes regional downscalings of the present-day climate as well as projected climate change. Thus, we study separately how downscaling changes the results in the control climate case, and how scenario results are changed. For the present-day climate, we find that downscaling reduces the differences in the Barents Sea between the original global models. Furthermore, the downscaled results are closer to observations. On the other hand, the downscaled results from the scenario simulations are significantly different: while the heat transport into the Barents Sea and the salinity distribution change modestly from control to scenario with ROMS-G, in ROMS-N the heat transport is much larger in the scenario simulation, and the water masses become much less saline. The lack of robustness in the results from the scenario simulations leads us to conclude that the results for the regional oceanic response to changes in the radiative forcing depend on the choice of AOGCM and is not settled. Consequently, the effect of climate change on the marine ecosystem of the Barents Sea is anything but certain.