Climate Change on Newfoundland and Labrador Shelves: Results From a Regional Downscaled Ocean and Sea-Ice Model Under an A1B Forcing Scenario 2011–2069

Climate change may affect ocean and ice conditions in coastal oceans and thus have significant impacts on coastal infrastructure, marine navigation, and marine ecosystems. In this study a three-dimensional ice–ocean model is developed to examine likely changes of ocean and ice conditions over the Newfoundland and Labrador Shelves in response to climate change. The model is configured with a horizontal grid of approximately 7?km and a vertical grid of 46 levels and is run from 1979 to 2069. The projection period is 2011 to 2069 under a median emission scenario A1B used by the Intergovernmental Panel on Climate Change. For the projection period, the surface atmospheric forcing fields used are from the Canadian Regional Climate Model over the North Atlantic. The open boundary conditions come from the Canadian Global Climate Model, Version 3 (CGCM3), adjusted for the 1981–2010 mean of the Simple Ocean Data Assimilation model output. The simulated fields over the 1981–2010 period have patterns consistent with observations. Over the Newfoundland and Labrador Shelves during the projection period, the model shows general trends of warming, freshening, and decreasing ice. From 2011 to 2069, the model projects that under A1B sea surface temperature will increase by 1.4°C; bottom temperature will increase by 1.6°C; sea surface salinity will decrease by 0.7; bottom salinity will decrease by 0.3; and sea-ice extent will decrease by 70%. The sea level will rise by 0.11?m at the St. John's tide-gauge station because of oceanographic change, and the freshwater transport of the Labrador Current will double as a result of freshening. The regional ice–ocean model reproduces more realistic present climate conditions and projects considerably different future climate conditions than CGCM3.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Historical and potential changes of precipitation and temperature of Alberta subjected to climate change impact: 1900–2100

We investigated changes to precipitation and temperature of Alberta for historical and future periods. First, the Mann-Kendall test and Sen’s slope were used to test for historical trends and trend magnitudes from the climate data of Alberta, respectively. Second, the Special Report on Emissions Scenarios (SRES) (A1B, A2, and B1) of CMIP3 (Phase 3 of Coupled Model Intercomparison Project), projected by seven general circulation models (GCM) of the Intergovernmental Panel on Climate Change (IPCC) for three 30 years periods (2020s, 2050s, and 2080s), were used to evaluate the potential impact of climate change on precipitation and temperature of Alberta. Third, trends of projected precipitation and temperature were investigated, and differences between historical versus projected trends were estimated. Using the 50-km resolution dataset from CANGRD (Canadian Grid Climate Data), we found that Alberta had become warmer and somewhat drier for the past 112 years (1900–2011), especially in central and southern Alberta. For observed precipitation, upward trends mainly occurred in northern Alberta and at the leeward side of Canadian Rocky Mountains. However, only about 13 to 22 % of observed precipitation showed statistically significant increasing trends at 5 % significant level. Most observed temperature showed significant increasing trends, up to 0.05 °C/year in DJF (December, January, and February) in northern Alberta. GCMs’ SRES projections indicated that seasonal precipitation of Alberta could change from ?25 to 36 %, while the temperature would increase from 2020s to 2080s, with the largest increase (6.8 °C) in DJF. In all 21 GCM-SRES cases considered, precipitation in both DJF and MAM (March, April, and May) is projected to increase, while temperature is consistently projected to increase in all seasons, which generally agree with the trends of historical precipitation and temperature. The SRES A1B scenario of CCSM3 might project more realistic future climate for Alberta, where its water resources can become more critical in the future as its streamflow is projected to decrease continually in the future.     

Assessment of CMIP3 climate models and projected changes of precipitation and temperature in the Yangtze River Basin, China

The projected changes of precipitation and temperature in the Yangtze River Basin in the 20th Century from 20 models of the CMIP3 (phase 3 of the Coupled Model Inter-comparison Project) dataset are analyzed based on the observed precipitation and temperature data of 147 meteorological stations in the Yangtze River Basin. The results show that all models tend to underestimate the annual mean temperature over the Yangtze River Basin, and to overestimate the annual mean precipitation. The temporal changes of simulated annual mean precipitation and temperature are broadly comparable with the observations, but with large variability among the results of the models. Most of the models can reproduce maximum precipitation during the monsoon season, while all models tend to underestimate the mean temperature of each month over the Yangtze River Basin. The Taylor diagram shows that the differences between modeled and observed temperature are relatively smaller as compared to differences in precipitation. For a detailed investigation of regional characteristics of climate change in the Yangtze River Basin during 2011–2050, the multi-model ensembles produced by an upgraded REA method are carried out for more reliable projections. The projected precipitation and temperature show large spatial variability in the Yangtze River Basin. Mean precipitation will increase under the A1B and B1 scenarios and decrease under the A2 scenario, with linear trends ranging from ?21 to 28.5?mm/decade. Increasing mean temperature can be found in all scenarios with linear trends ranging from 0.15 to 0.48°C/decade. Grids in the head region of the Jingshajiang catchment show distinct increasing trends for all scenarios. Some physical processes associated with precipitation are not well represented in the models.     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature

We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor’s skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.     

Climate Change Scenarios for the Hudson Bay Region: An Intermodel Comparison

General circulation models (GCMs) are unanimous in projecting warmer temperatures in an enhanced CO₂ atmosphere, with amplification of this warming in higher latitudes. The Hudson Bay region, which is located in the Arctic and subarctic regions of Canada, should therefore be strongly influenced by global warming. In this study, we compare the response of Hudson Bay to a transient warming scenario provided by six-coupled atmosphere-ocean models. Our analysis focuses on surface temperature, precipitation, sea-ice coverage, and permafrost distribution. The results show that warming is expected to peak in winter over the ocean, because of a northward retreat of the sea-ice cover. Also, a secondary warming peak is observed in summer over land in the Canadian and Australian-coupled GCMs, which is associated with both a reduction in soil moisture conditions and changes in permafrost distribution. In addition, a relationship is identified between the retreat of the sea-ice cover and an enhancement of precipitation over both land and oceanic surfaces. The response of the sea-ice cover and permafrost layer to global warming varies considerably among models and thus large differences are observed in the projected regional increase in temperature and precipitation. In view of the important feedbacks that a retreat of the sea-ice cover and the distribution of permafrost are likely to play in the doubled and tripled CO₂ climates of Hudson Bay, a good representation of these two parameters is necessary to provide realistic climate change scenarios. The use of higher resolution regional climate model is recommended to develop scenarios of climate change for the Hudson Bay region.     

Projected Climate Change in the Northwestern Arid Regions of China: An Ensemble of Regional Climate Model Simulations

The projected temperature and precipitationchange under different emissions scenarios using Coupled Model Intercomparison Project Phase 5 models over the northwestern arid regions of China(NWAC) were analyzed using the ensemble of three high-resolution dynamical downscaling simulations: the simulation of the Regional Climate Model version 4.0(Reg CM4) forced by the Beijing Climate Center Climate System Model version 1.1(BCC_CSM1.1); the Hadley Centre Global Environmental Model version 3 regional climate model(Had GEM3-RA) forced by the Atmosphere-Ocean coupled Had GEM version 2(Had GEM2-AO); and the Weather Research and Forecasting(WRF) model forced by the Norwegian community Earth System Model(Nor ESM1-M). Model validation indicated that the multimodel simulations reproduce the spatial and temporal distribution of temperature and precipitation well. The temperature is projected to increase over NWAC under both the 4.5 and 8.5 Representative Concentration Pathways scenarios(RCP4.5 and RCP8.5, respectively) in the middle of the 21 st century, but the warming trend is larger under the RCP8.5 scenario. Precipitation shows a significant increasing trend in spring and winter under both RCP4.5 and RCP8.5; but in summer, precipitation is projected to decrease in the Tarim Basin and Junggar Basin. The regional averaged temperature and precipitation show increasing trends in the future over NWAC; meanwhile, the large variability of the winter mean temperature and precipitation may induce more extreme cold events and intense snowfall events in these regions in the future.     

Evaluation of pan-Arctic melt-freeze onset in CMIP5 climate models and reanalyses using surface observations

The seasonal melt-freeze transitions are fundamental features of the Arctic climate system. The representation of the pan-Arctic melt and freeze onset (north of 60°N) is assessed in two reanalyses and eleven CMIP5 global circulation models (GCMs). The seasonal melt-freeze transitions are retrieved from surface air temperature (SAT) across the land and sea-ice domains and evaluated against surface observations. While monthly averages of SAT are reasonably well represented in models, large model-observation and model–model disparities of timing of melt and freeze onset are evident. The evaluation against surface observations reveals that the ERA-Interim reanalysis performs the best, closely followed by some of the climate models. GCMs and reanalyses capture the seasonal melt-freeze transitions better in the central Arctic than in the marginal seas and across the land areas. The GCMs project that during the 21st century, the summer length—the period between melt and freeze onset—will increase over land by about 1 month at all latitudes, and over sea ice by 1 and 3 months at low and high latitudes, respectively. This larger summer-length increase over sea ice at progressively higher latitudes is related to a retreat of summer sea ice during the 21st century, since open water freezes roughly 40 days later than ice-covered ocean. As a consequence, by the year 2100, the freeze onset is projected to be initiated within roughly 10 days across the whole Arctic Ocean, whereas this transition varies by about 80 days today.     

Developing climate change scenarios for Tamil Nadu, India using MAGICC/SCENGEN

This paper describes the projection of climate change scenarios under increased greenhouse gas emissions, using the results of atmospheric-ocean general circulation models in the Coupled Model Intercomparison Project phase 3 dataset. A score is given to every model based on global and regional performance. Four out of 20 general circulation models (GCMs) were selected based on skill in predicting observed annual temperature and precipitation conditions. The ensemble of these four models shows superiority over the individual model scores. These models were subjected to increases in future anthropogenic radiative forcings for constructing climate change scenarios. Future climate scenarios for Tamil Nadu were developed with MAGICC/SCENGEN software. Model results show both temperature and precipitation increases under increased greenhouse gas scenarios. Northeast and northwest parts of Tamil Nadu show a greater increase in temperature and precipitation. Seasonally, the maximum rise in temperature occurred during the MAM season, followed by DJF, JJA, and SON. Decreasing trends of precipitation were observed during DJF and MAM.     

Downscaling daily precipitation over the Yellow River source region in China: a comparison of three statistical downscaling methods

Three statistical downscaling methods are compared with regard to their ability to downscale summer (June–September) daily precipitation at a network of 14 stations over the Yellow River source region from the NCEP/NCAR reanalysis data with the aim of constructing high-resolution regional precipitation scenarios for impact studies. The methods used are the Statistical Downscaling Model (SDSM), the Generalized LInear Model for daily CLIMate (GLIMCLIM), and the non-homogeneous Hidden Markov Model (NHMM). The methods are compared in terms of several statistics including spatial dependence, wet- and dry spell length distributions and inter-annual variability. In comparison with other two models, NHMM shows better performance in reproducing the spatial correlation structure, inter-annual variability and magnitude of the observed precipitation. However, it shows difficulty in reproducing observed wet- and dry spell length distributions at some stations. SDSM and GLIMCLIM showed better performance in reproducing the temporal dependence than NHMM. These models are also applied to derive future scenarios for six precipitation indices for the period 2046–2065 using the predictors from two global climate models (GCMs; CGCM3 and ECHAM5) under the IPCC SRES A2, A1B and B1scenarios. There is a strong consensus among two GCMs, three downscaling methods and three emission scenarios in the precipitation change signal. Under the future climate scenarios considered, all parts of the study region would experience increases in rainfall totals and extremes that are statistically significant at most stations. The magnitude of the projected changes is more intense for the SDSM than for other two models, which indicates that climate projection based on results from only one downscaling method should be interpreted with caution. The increase in the magnitude of rainfall totals and extremes is also accompanied by an increase in their inter-annual variability.     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

CMIP5 simulated climate conditions of the Greater Horn of Africa (GHA). Part II: projected climate

This is the second of the two-part paper series on the analysis and evaluation of the Fifth phase of Coupled Model Intercomparison Project (CMIP5) simulation of contemporary climate as well as IPCC, AR5 Representative Concentrations Pathways (RCP), 4.5 and 8.5 scenarios projections of the Greater Horn of Africa (GHA) Climate. In the first part (Otieno and Anyah in Clim Dyn, 2012) we focused on the historical simulations, whereas this second part primarily focuses on future projections based on the two scenarios. Six Earth System Models (ESMs) from CMIP5 archive have been used to characterize projected changes in seasonal and annual mean precipitation, temperature and the hydrological cycle by the middle of twenty-first century over the GHA region, based on IPCC, 5th Assessment Report (AR5) RCP4.5 and RCP8.5 scenarios. Nearly all the models outputs analyzed reproduce the correct mean annual cycle of precipitation, with some biases among the models in capturing the correct peak of precipitation cycle, more so, March–April–May (MAM) seasonal rainfall over the equatorial GHA region. However, there is significant variation among models in projected precipitation anomalies, with some models projecting an average increase as others project a decrease in precipitation during different seasons. The ensemble mean of the ESMs indicates that the GHA region has been experiencing a steady increase in both precipitation and temperature beginning in the early 1980s and 1970s respectively in both RCP4.5 and RCP8.5 scenarios. Going by the ensemble means, temperatures are projected to steadily increase uniformly in all the seasons at a rate of 0.3/0.5 °C/decade under RCP4.5/8.5 scenarios over northern GHA region leading to an approximate temperature increase of 2/3 °C by the middle of the century. On the other hand, temperatures will likely increase at a rate of 0.3/0.4 °C/decade under RCP4.5/8.5 scenarios in both equatorial and southern GHA region leading to an approximate temperature increase of 2/2.5 °C by the middle of twenty-first century. Nonetheless, projected precipitation increase varied across seasons and sub-regions. With the exception of the equatorial region, that is projected to experience precipitation increase during DJF season, most sub-regions are projected to experience precipitation increase within their peak seasons, with the highest rate of increase experienced during DJF and OND seasons over southern and equatorial GHA regions respectively. Notably, as precipitation increases, the deficit (E < P) between evaporation (E) and precipitation (P) increased over the years, with a negatively skewed distribution. This generally implies that there is a high likelihood of an increased deficit in local moisture supply. This remarkable change in the general hydrological cycle (i.e. deficit in local moisture) is projected to be also coincident with intensified westerly anomaly influx from the Congo basin into the region. However, better understanding of the detailed changes in hydrological cycle will require comprehensive water budget analyses that require daily or sub-daily variables, and was not a specific focus of the present study.     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models

The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO₂ concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO₂ concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.     

Sea-Ice Concentration Multivariate Assimilation for the Canadian East Coast in a Coupled Sea Ice–Ocean Model

The present study focuses on the impact of ocean state (i.e., salinity and temperature) updates on the sea-ice analysis and short-term forecast in an assimilative sea ice–ocean coupled system. A relatively simple sea-ice assimilation scheme was applied to the sea ice–ocean coupled North Atlantic Nucleus for European Modelling of the Ocean (NEMO) system with a focus on the Canadian East Coast. In this assimilation scheme the ocean state was updated directly based on the correlations between the model's sea-ice concentration and the upper ocean salinity and temperature. These correlations were based on a limited time ensemble generated by applying random perturbations to the atmospheric forcing fields. High deviations in the sea-ice conditions were found along the ice edge, implying that the sea-ice edge position is sensitive to small atmospheric forcing variations. Assimilation runs with and without ocean state updates (i.e., sea-ice concentration nudging) were conducted and compared for the winter of 2002. Both continuous and intermittent assimilation schemes were examined. In a continuous sea-ice assimilation experiment, the ocean direct update is unnecessary. When the sea-ice updates are introduced intermittently the ocean state has to be altered to accommodate them, or they will be rapidly diminished by the model's dynamics. The correlations between sea-ice concentration and ocean salinity and temperature based on the first 15 days of January were used for corrections during the entire winter season when, in addition to thermodynamic processes, dynamic processes are responsible for, and even dominate, sea-ice evolution on the Labrador and Newfoundland shelves. This was an adequate choice as was demonstrated by the results of the study which showed that the experiments with ocean state adjustments generated more accurate short-term sea-ice forecasts.     

Near-Term Projections of Global and Regional Land Mean Temperature Changes Considering Both the Secular Trend and Multidecadal Variability

Near-term climate projections are needed by policymakers; however, these projections are difficult because internally generated climate variations need to be considered. In this study, temperature change scenarios in the near-term period 2017–35 are projected at global and regional scales based on a refined multi-model ensemble approach that considers both the secular trend (ST) and multidecadal variability (MDV) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. The ST and MDV components are adaptively extracted from each model simulation by using the ensemble empirical mode decomposition (EEMD) filter, reconstructed via the Bayesian model averaging (BMA) method for the historical period 1901–2005, and validated for 2006–16. In the simulations of the “medium” representative concentration pathways scenario during 2017–35, the MDV-modulated temperature change projected via the refined approach displays an increase of 0.44°C (90% uncertainty range from 0.30 to 0.58°C) for global land, 0.48°C (90% uncertainty range from 0.29 to 0.67°C) for the Northern Hemispheric land (NL), and 0.29°C (90% uncertainty range from 0.23 to 0.35°C) for the Southern Hemispheric land (SL). These increases are smaller than those projected by the conventional arithmetic mean approach. The MDV enhances the ST in 13 of 21 regions across the world. The largest MDV-modulated warming effect (46%) exists in central America. In contrast, the MDV counteracts the ST in NL, SL, and eight other regions, with the largest cooling effect (220%) in Alaska.     

The influence of Hudson Bay runoff and ice‐melt on the salinity of the inner Newfoundland Shelf

Abstract

The present study examines sources of the interannual variability in salinity on the Newfoundland continental shelf observed in a 40‐year time series from an oceanographic station known as Station 27. Specifically, we investigate, through lag‐correlation analysis, the a priori hypotheses that the salinity anomalies at Station 27 are determined by freshwater runoff anomalies from Hudson and Ungava bays and by ice‐melt anomalies in Hudson Bay and on the Labrador Shelf. Interannual variations of summer runoff into Hudson Bay were significantly negatively correlated with salinity anomalies on the Newfoundland Shelf with a lag (9 months) that is consistent with expected travel times based on known current velocities in Hudson Bay and along the Labrador Shelf. Sea‐ice extent over the Labrador and northern Newfoundland shelves was significantly negatively correlated with salinity at a lag of 3 to 4 months, corresponding to the time of minimum salinity at Station 27. It appears that ice‐melt over the Labrador‐northern Newfoundland Shelf is primarily responsible for the seasonal salinity minimum over the Newfoundland Shelf. Interannual variability in runoff into Ungava Bay and ice‐melt in Hudson Bay were not correlated with interannual salinity variations on the Newfoundland Shelf.     

Climate Comparisons and Change Projections for the Northwest Atlantic from Six CMIP5 Models

Abstract

Key physical variables for the Northwest Atlantic (NWA) are examined in the “historical” and two future Representative Concentration Pathway (RCP) simulations of six Earth System Models (ESMs) available through Phase 5 of the Climate Model Intercomparison Project (CMIP5). The variables are air temperature, sea-ice concentration, surface and subsurface ocean temperature and salinity, and ocean mixed-layer depth. Comparison of the historical simulations with observations indicates that the models provide a good qualitative and approximate quantitative representation of many of the large-scale climatological features in the NWA (e.g., annual cycles and spatial patterns). However, the models represent the detailed structure of some important NWA ocean and ice features poorly, such that caution is needed in the use of their projected future changes. Monthly “climate change” fields between the bidecades 1986–2005 and 2046–2065 are described, using ensemble statistics of the changes across the six ESMs. The results point to warmer air temperatures everywhere, warmer surface ocean temperatures in most areas, reduced sea-ice extent and, in most areas, reduced surface salinities and mixed-layer depths. However, the magnitudes of the inter-model differences in the projected changes are comparable to those of the ensemble-mean changes in many cases, such that robust quantitative projections are generally not possible for the NWA.     

Projected Changes in Surface Air Temperature and Surface Wind in the Gulf of St. Lawrence

Abstract

The impacts of climate change on surface air temperature (SAT) and winds in the Gulf of St. Lawrence (GSL) are investigated by performing simulations from 1970 to 2099 with the Canadian Regional Climate Model (CRCM), driven by a five-member ensemble. Three members are from Canadian Global Climate Model (CGCM3) simulations following scenario A1B from the Intergovernmental Panel on Climate Change (IPCC); one member is from the Community Climate System Model, version 3 (CCSM3) simulation, also following the A1B scenario; and one member is from the CCSM4 (version 4) simulation following the Representative Concentration Pathway (RCP8.5) scenario. Compared with North America Regional Reanalysis (NARR) data, it is shown that CRCM can reproduce the observed SAT spatial patterns; for example, both CRCM simulations and NARR data show a warm SAT tongue along the eastern Gulf; CRCM simulations also capture the dominant northwesterly winds in January and the southwesterly winds in July. In terms of future climate scenarios, the spatial patterns of SAT show plausible seasonal variations. In January, the warming is 3°–3.5°C in the northern Gulf and 2.5°–3°C near Cabot Strait during 2040–2069, whereas the warming is more uniform during 2070–2099, with SAT increases of 4°–5°C. In summer, the warming gradually decreases from the western side of the GSL to the eastern side because of the different heat capacities between land and water. Moreover, the January winds increase by 0.2–0.4?m?s^?1 during 2040–2069, related to weakening stability in the atmospheric planetary boundary layer. However, during 2070–2099, the winds decrease by 0.2–0.4?m?s^?1 over the western Gulf, reflecting the northeastward shift in northwest Atlantic storm tracks. In July, enhanced baroclinicity along the east coast of North America dominates the wind changes, with increases of 0.2–0.4?m?s^?1. On average, the variance for the SAT changes is about 10% of the SAT increase, and the variance for projected wind changes is the same magnitude as the projected changes, suggesting uncertainty in the latter.     

Projecting date palm distribution in Iran under climate change using topography,physicochemical soil properties,soil taxonomy,land use,and climate data

This study set out to model potential date palm distribution under current and future climate scenarios using an emission scenario, in conjunction with two different global climate models (GCMs): CSIRO-Mk3.0 (CS), and MIROC-H (MR), and to refine results based on suitability under four nonclimatic parameters. Areas containing suitable physicochemical soil properties and suitable soil taxonomy, together with land slopes of less than 10° and suitable land uses for date palm (Phoenix dactylifera) were selected as appropriate refining tools to ensure the CLIMEX results were accurate and robust. Results showed that large regions of Iran are projected as likely to become climatically suitable for date palm cultivation based on the projected scenarios for the years 2030, 2050, 2070, and 2100. The study also showed CLIMEX outputs merit refinement by nonclimatic parameters and that the incremental introduction of each additional parameter decreased the disagreement between GCMs. Furthermore, the study indicated that the least amount of disagreement in terms of areas conducive to date palm cultivation resulted from CS and MR GCMs when the locations of suitable physicochemical soil properties and soil taxonomy were used as refinement tools.