Model For Interdisciplinary Research On Climate Research Articles

Late Holocene glacier and climate fluctuations in the Mackenzie and Selwyn mountain ranges, northwestern Canada

Abstract. Over the last century, northwestern Canada experienced some of the highest rates of tropospheric warming globally, which caused glaciers in the region to rapidly retreat. Our study seeks to extend the record of glacier fluctuations and assess climate drivers prior to the instrumental record in the Mackenzie and Selwyn mountains of northwestern Canada. We collected 27 10Be surface exposure ages across nine cirque and valley glacier moraines to constrain the timing of their emplacement. Cirque and valley glaciers in this region reached their greatest Holocene extents in the latter half of the Little Ice Age (1600–1850 CE). Four erratic boulders, 10–250 m distal from late Holocene moraines, yielded 10Be exposure ages of 10.9–11.6 ka, demonstrating that by ca. 11 ka, alpine glaciers were no more extensive than during the last several hundred years. Estimated temperature change obtained through reconstruction of equilibrium line altitudes shows that since ca. 1850 CE, mean annual temperatures have risen 0.2–2.3 ∘C. We use our glacier chronology and the Open Global Glacier Model (OGGM) to estimate that from 1000 CE, glaciers in this region reached a maximum total volume of 34–38 km3 between 1765 and 1855 CE and had lost nearly half their ice volume by 2019 CE. OGGM was unable to produce modeled glacier lengths that match the timing or magnitude of the maximum glacier extent indicated by the 10Be chronology. However, when applied to the entire Mackenzie and Selwyn mountain region, past millennium OGGM simulations using the Max Planck Institute Earth System Model (MPI-ESM) and the Community Climate System Model 4 (CCSM4) yield late Holocene glacier volume change temporally consistent with our moraine and remote sensing record, while the Meteorological Research Institute Earth System Model 2 (MRI-ESM2) and the Model for Interdisciplinary Research on Climate (MIROC) fail to produce modeled glacier change consistent with our glacier chronology. Finally, OGGM forced by future climate projections under varying greenhouse gas emission scenarios predicts 85 % to over 97 % glacier volume loss by the end of the 21st century. The loss of glaciers from this region will have profound impacts on local ecosystems and communities that rely on meltwater from glacierized catchments.

Climate Suitability for Paddy in Sukabumi Regency by 2032 Using RCP 4.5 Scenario

Climate is the crucial determining component in defining the land suitability class for paddy. The paddy suitability class is expected to decrease as a result of global climate change. This study analyzed land suitability for paddy based on the Representative Concentration Pathways (RCP) 4.5 climate projection scenario of Sukabumi Regency in 2020 and 2032 using the Model for Interdisciplinary Research on Climate (MIROC) 5. The parameters analyzed were precipitation (pr), and near-surface air temperature (tas). The global data was adjusted to local conditions using a bias factor calculated using observed climate data from the Meteorological, Climatological, and Geophysical Agency Station in Bandung. Based on the results of this study, climate (precipitation and temperature) projections for Sukabumi Regency in 2020 and 2032 are classified as highly suitable (S1) for paddy cultivation. The result of this study indicates that there would be no change in the climate suitability class for paddy cultivation in Sukabumi Regency between 2020 to 2032. However, the results of this study also identified a significant numerical decline in precipitation. Therefore, we recommend necessary climate change mitigation and adaptation programs to reduce the future risk of decreasing rice production due to crop failure.

MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change

Abstract. Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. On the one hand, future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human-induced land-use change can affect the climate system through biogeophysical and biogeochemical effects. To investigate these interrelationships, we developed MIROC-INTEG-LAND (MIROC INTEGrated LAND surface model version 1), an integrated model that combines the land surface component of global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land-use models. The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balance, human water management, and crop growth incorporates a land use decision-making model based on economic activities. In MIROC-INTEG-LAND, spatially detailed information regarding water resources and crop yields is reflected in the prediction of future land-use change, which cannot be considered in the conventional integrated assessment models. In this paper, we introduce the details and interconnections of the submodels of MIROC-INTEG-LAND, compare historical simulations with observations, and identify various interactions between the submodels. By evaluating the historical simulation, we have confirmed that the model reproduces the observed states well. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand. The newly developed MIROC-INTEG-LAND could be combined with atmospheric and ocean models to develop an integrated earth system model to simulate the interactions among coupled natural–human earth system components.

Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6

Abstract. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community. In the present paper, simulated mean climate, internal climate variability, and climate sensitivity in MIROC6 are evaluated and briefly summarized in comparison with the previous version of our climate model (MIROC5) and observations. The results show that the overall reproducibility of mean climate and internal climate variability in MIROC6 is better than that in MIROC5. The tropical climate systems (e.g., summertime precipitation in the western Pacific and the eastward-propagating Madden–Julian oscillation) and the midlatitude atmospheric circulation (e.g., the westerlies, the polar night jet, and troposphere–stratosphere interactions) are significantly improved in MIROC6. These improvements can be attributed to the newly implemented parameterization for shallow convective processes and to the inclusion of the stratosphere. While there are significant differences in climates and variabilities between the two models, the effective climate sensitivity of 2.6 K remains the same because the differences in radiative forcing and climate feedback tend to offset each other. With an aim towards contributing to the sixth phase of the Coupled Model Intercomparison Project, designated simulations tackling a wide range of climate science issues, as well as seasonal to decadal climate predictions and future climate projections, are currently ongoing using MIROC6.

Mechanisms for and Predictability of a Drastic Reduction in the Arctic Sea Ice: APPOSITE Data with Climate Model MIROC

Abstract The mechanisms for and predictability of a drastic reduction in the Arctic sea ice extent (SIE) are investigated using the Model for Interdisciplinary Research on Climate (MIROC) version 5.2. Here, a control (CTRL) with forcing fixed at year 2000 levels and perfect-model ensemble prediction (PRED) experiments are conducted. In CTRL, three (model years 51, 56, and 57) drastic SIE reductions occur during a 200-yr-long integration. In year 56, the sea ice moves offshore in association with a positive phase of the summer Arctic dipole anomaly (ADA) index and melts due to heat input through the increased open water area, and the SIE drastically decreases. This provides the preconditioning for the lowest SIE in year 57 when the Arctic Ocean interior is in a warm state and the spring sea ice volume has a large negative anomaly due to drastic ice reduction in the previous year. Although the ADA is one of the key mechanisms behind sea ice reduction, it does not always cause a drastic reduction. Our analysis suggests that wind direction favoring offshore ice motion is a more important factor for drastic ice reduction events. In years experiencing drastic ice reduction events, the September SIE can be skillfully predicted in PRED started from July, but not from April. This is because the forecast errors for the July sea level pressure and those for the sea ice concentration and sea ice thickness along the ice edge are large in PRED started from April.

Impact of Global Change in Sulfur Dioxide, Black Carbon and Organic Carbon on PM2.5-Related Premature Mortality and Years Life Lost

Previous research has highlighted the importance of major atmospheric aerosols such as sulfate, through its precursor sulfur dioxide (SO2), black carbon (BC) and organic carbon (OC), and their effect on global climate regimes, specifically on their impact on particulate matter of size less than or equal to 2.5 micrometers in diameter (PM2.5). Coupled with these global climate simulations, are studies which highlight the negative effects of PM2.5 on human health. Globally, national policies attempt to address the change of these major active aerosols and their impact on PM2.5, which would later on presumably have a cascading effect towards the change of health risks. This study aims to determine how the change in the global anthropogenic aerosol emissions affect health, in particular through the change in attributable mortality (AN) and years of life lost (YLL). Model for Interdisciplinary Research on Climate (MIROC), a global atmospheric general circulation model (AGCM) developed by several Japanese institutions, was used to estimate the gridded atmospheric aerosol (SO2, BC, and OC) data for 0.25 by 0.25 degrees. The gridded data were then utilized to estimate the associated cause-specific risks via an integrated exposure response function, and its consequent disease burden, in terms of AN and YLL, per WHO Regions. SEARO and WPRO regions were observed to have apparent variations in AN and YLL with respect to the change in atmospheric aerosols. If atmospheric aerosols were to be reduced, both SEARO and WPRO will have co-benefits (reduced AN) among the cerebrovascular population. On the other hand, if life expectancy were to be considered, co-benefits (reduced YLL) were apparent among acute lower respiratory infection population, for both regions. The changes in the atmospheric aerosols have varying impact on the changes in the disease burden landscape globally, which could translate to varying health-oriented aerosol mitigation policies.

Changes in the Geographic Distribution of the Diana Fritillary (Speyeria diana: Nymphalidae) under Forecasted Predictions of Climate Change.

Climate change is predicted to alter the geographic distribution of a wide variety of taxa, including butterfly species. Research has focused primarily on high latitude species in North America, with no known studies examining responses of taxa in the southeastern United States. The Diana fritillary (Speyeria diana) has experienced a recent range retraction in that region, disappearing from lowland sites and now persisting in two phylogenetically distinct high elevation populations. These findings are consistent with the predicted effects of a warming climate on numerous taxa, including other butterfly species in North America and Europe. We used ecological niche modeling to predict future changes to the distribution of S. diana under several climate models. To evaluate how climate change might influence the geographic distribution of this butterfly, we developed ecological niche models using Maxent. We used two global circulation models, the community climate system model (CCSM) and the model for interdisciplinary research on climate (MIROC), under low and high emissions scenarios to predict the future distribution of S. diana. Models were evaluated using the receiver operating characteristics area under curve (AUC) test and the true skill statistics (TSS) (mean AUC = 0.91 ± 0.0028 SE, TSS = 0.87 ± 0.0032 SE for representative concentration pathway (RCP) = 4.5; and mean AUC = 0.87 ± 0.0031 SE, TSS = 0.84 ± 0.0032 SE for RCP = 8.5), which both indicate that the models we produced were significantly better than random (0.5). The four modeled climate scenarios resulted in an average loss of 91% of suitable habitat for S. diana by 2050. Populations in the southern Appalachian Mountains were predicted to suffer the most severe fragmentation and reduction in suitable habitat, threatening an important source of genetic diversity for the species. The geographic and genetic isolation of populations in the west suggest that those populations are equally as vulnerable to decline in the future, warranting ongoing conservation of those populations as well. Our results suggest that the Diana fritillary is under threat of decline by 2050 across its entire distribution from climate change, and is likely to be negatively affected by other human-induced factors as well.

Ocean Impacts on Australian Interannual to Decadal Precipitation Variability

In Australia, successful seasonal predictions of wet and dry conditions are achieved by utilizing the remote impact of sea surface temperature (SST) variability in tropical oceans, particularly the Pacific Ocean, on the seasonal timescale. Beyond seasonal timescales, however, it is still unclear which processes and oceans contribute to interannual-to-decadal wet/dry conditions in Australia. This research examines the interannual-to-decadal relationship between global SST anomalies (SSTAs) and Australian wet/dry variability by analyzing observational data and global climate model experiments conducted with the NCAR Community Earth System Model (CESM) and the Model for Interdisciplinary Research on Climate (MIROC). A 10-member ensemble simulation suite for 1960–2015 (CESM) and 1950–2010 (MIROC) is conducted by assimilating the observed three-dimensional ocean temperature and salinity anomalies into fully coupled global climate models. In both observational analyses and ocean assimilation experiments, the most dominant annual mean precipitation variability shows a clear relationship with SSTAs in the tropical Pacific and the Atlantic. Our partial ocean assimilation experiment, in which the ocean component of the CESM and MIROC are assimilated by the observed ocean temperature and salinity anomalies in the equatorial Pacific only, shows that the tropical Pacific SST variability is the main driver of Australian precipitation variability on the interannual-to-decadal timescales. However, our additional partial ocean assimilation experiment, in which the climate models incorporate the observed anomalies solely in the Atlantic ocean, demonstrates that the Atlantic Ocean can also affect Australian precipitation variability on the interannual-to-decadal timescale through changes in tropical Pacific SSTAs and the modulation of the global Walker circulation. Our results suggest that about a half of Australian interannual-to-decadal precipitation variability originates from the Atlantic Ocean.

Effect of ENSO events on larval and juvenile duration and transport of Japanese eel (Anguilla japonica).

Spawning ground of Japanese eel (Anguilla japonica) is located near the West Mariana Ridge seamount. The species travels through the North Equatorial Current (NEC) and then enters the Kuroshio Current (KC) on the migration toward East Asian growth habitats. Therefore, El Niño–Southern Oscillation (ENSO) events serve as the potentially important drivers of interannual variability across the equatorial Pacific. Because the NEC bifurcation and salinity profiles are related to ENSO events, we investigated the influence of locations of the NEC bifurcation and salinity front on the success of larval entry to the KC by numerically modeling particle transport in ocean currents from 1972 to 2013 and possible effects on the size of glass eels at continental recruitment and, via otolithometry on the duration of larval migration. Circulation and hydrography used for particle tracking were obtained from the results of the Model for Interdisciplinary Research on Climate (MIROC) high-resolution forecasting experiment. Our results demonstrated that during El Niño years, (1) the southward movement of the salinity front might cause the larvae to experience slower currents and (2) the northward movement of the NEC bifurcation might broaden the separation between their spawning ground and NEC bifurcation, thus prolonging the time needed for the larvae to enter the KC from their spawning ground, because of which the duration of entrainment in the water column and body size increase when eels reach estuarine waters. In addition, this might cause more water to flow into the Mindanao Current (MC), leading to a decline in the rate at which larvae get entrained into the KC.

Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments.

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods.

Palaeoclimatic distribution models predict Pleistocene refuges for the Neotropical harvestman Geraeocormobius sylvarum (Arachnida: Opiliones: Gonyleptidae)

ABSTRACTThis paper primarily aims to test a Pleistocene refuge-type scenario, as previously proposed for the gonyleptid Geraeocormobius sylvarum, a semi-deciduous forests dweller in subtropical Argentina, Brazil and Paraguay. Palaeodistributional models of this species were built using MaxEnt for two Last Glacial Maximum (LGM = 21,000 years ago) simulations – Community Climate System Model (CCSM) and Model for Interdisciplinary Research on Climate (MIROC) – and for 6000 years ago (−6k = HCO, the Holocene climatic optimum). Both LGM models retrieved a fragmented pattern. For CCSM, range was split into multiple, scattered fragments. MIROC resulted in very few patches, with a decided range reduction because of a strong humidity drop. Models for −6k recovered a moderate range expansion. No past connection between the core area and the yungas was predicted. Analysis of variables importance showed that two precipitation predictors (bc18, precipitation warmest quarter; bc14, precipitation driest month) and two temperature predictors (bc7, temperature annual range; bc9, mean temperature driest quarter) scored as the most influencing overall. The Limiting Factor analysis recognized them as limiting too, in different parts of the species range. LGM palaeomodels of G. sylvarum are compatible with the refuge hypothesis invoked in previous molecular analyses, to explain the high genetic diversity found in the core area. Additionally, the results reinforced the hypothesis of the recent anthropogenic origin of the yungas disjunct populations.

Forecasted Changes in West Africa Photovoltaic Energy Output by 2045

The impacts of climate change on photovoltaic (PV) output in the fifteen countries of the Economic Community of West African States (ECOWAS) was analyzed in this paper. Using a set of eight climate models, the trends of solar radiation and temperature between 2006–2100 were examined. Assuming a lifetime of 40 years, the future changes of photovoltaic energy output for the tilted plane receptor compared to 2006–2015 were computed for the whole region. The results show that the trends of solar irradiation are negative except for the Irish Centre for High-End Computing model which predicts a positive trend with a maximum value of 0.17 W/m2/year for Cape Verde and the minimum of −0.06 W/m2/year for Liberia. The minimum of the negative trend is −0.18 W/m2/year predicted by the Model for Interdisciplinary Research on Climate (MIROC), developed at the University of Tokyo Center for Climate System Research for Cape Verde. Furthermore, temperature trends are positive with a maximum of 0.08 K/year predicted by MIROC for Niger and minimum of 0.03 K/year predicted by Nature Conservancy of Canada (NCC), Max Planck Institute (MPI) for Climate Meteorology at Hamburg, French National Meteorological Research Center (CNRM) and Canadian Centre for Climate Modelling and Analysis (CCCMA) for Cape Verde. Photovolataic energy output changes show increasing trends in Sierra Leone with 0.013%/year as the maximum. Climate change will lead to a decreasing trend of PV output in the rest of the countries with a minimum of 0.032%/year in Niger.

The effects of future nationwide forest transition to discharge in the 21st century with regard to general circulation model climate change scenarios

Forest disturbance (or land-cover change) and climatic variability are commonly recognised as two major drivers interactively influencing hydrology in forested watersheds. Future climate changes and corresponding changes in forest type and distribution are expected to generate changes in rainfall runoff that pose a threat to river catchments. It is therefore important to understand how future climate changes will effect average rainfall distribution and temperature and what effect this will have upon forest types across Japan. Recent deforestation of the present-day coniferous forest and expected increases in evergreen forest are shown to influence runoff processes and, therefore, to influence future runoff conditions. We strongly recommend that variations in forest type be considered in future plans to ameliorate projected climate changes. This will help to improve water retention and storage capacities, enhance the flood protection function of forests, and improve human health. We qualitatively assessed future changes in runoff including the effects of variation in forest type across Japan. Four general circulation models (GCMs) were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM), and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble including multiple physics configurations and different reference concentration pathways (RCP2.6, 4.5, and 8.5), the results of which have produced monthly data sets for the whole of Japan. The impacts of future climate changes on forest type in Japan are based on the balance amongst changes in rainfall distribution, temperature and hydrological factors. Methods for assessing the impact of such changes include the Catchment Simulator modelling frameworks based on the Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO) model, which was expanded to estimate discharge by incorporating the effects of forest-type transition across the whole of Japan. The results indicated that, by the 2090s, annual runoff will increase above present-day values. Increases in annual variation in runoff by the 2090s was predicted to be around 14.1% when using the MRI-GCM data and 44.4% when using the HadGEM data. Analysis by long-term projection showed the largest increases in runoff in the 2090s were related to the type of forest, such as evergreen. Increased runoff can have negative effects on both society and the environment, including increased flooding events, worsened water quality, habitat destruction and changes to the forest moisture-retaining function. Prediction of the impacts of future climate change on water generation is crucial for effective environmental planning and management.

Intensification of tropical Pacific biological productivity due to volcanic eruptions

AbstractMajor volcanic eruptions generate widespread ocean cooling, which reduces upper ocean stratification. This effect has the potential to increase nutrient delivery into the euphotic zone and boost biological productivity. Using externally forced last millennium simulations of three climate/Earth System models (Model for Interdisciplinary Research On Climate (MIROC), Community Earth System Model (CESM), and LOch‐Vecode‐Ecbilt‐CLio‐agIsm Model (LOVECLIM)), we test the hypothesis that large volcanic eruptions intensify nutrient‐driven export production. It is found that strong volcanic radiative forcing enhances the likelihood of eastern Pacific El Niño‐like warming in CESM and LOVECLIM. This leads to an initial reduction of nutrients and export production in the eastern equatorial Pacific. However, this initial response reverses after about 3 years in association with La Niña cooling. The resulting delayed enhancement of biological production resembles the multiyear response in MIROC. The model simulations show that volcanic impacts on tropical Pacific dynamics and biogeochemistry persist for several years, thus providing a new source for potential multiyear ecosystem predictability.

Assessment of spatiotemporal variations in the fluvial wash-load component in the 21st century with regard to GCM climate change scenarios

For stream water, in which a relationship exists between wash-load concentration and discharge, an estimate of fine-sediment delivery may be obtained from a traditional fluvial wash-load rating curve. Here, we demonstrate that the remaining wash-load material load can be estimated from a traditional empirical principle on a nationwide scale. The traditional technique was applied to stream water for the whole of Japan. Four typical GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the following regional climate models to assess the wash-load component based on rating curves: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble, including multiple physics configurations and different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5), which was used to produce monthly datasets for the whole country of Japan. The impacts of future climate changes on fluvial wash load in Japanese stream water were based on the balance of changes in hydrological factors. The annual and seasonal variations of the fluvial wash load were assessed from the result of the ensemble analysis in consideration of the Greenhouse Gas (GHG) emission scenarios. The determined results for the amount of wash load increase range from approximately 20 to 110% in the 2040s, especially along part of the Pacific Ocean and the Sea of Japan regions. In the 2090s, the amount of wash load is projected to increase by more than 50% over the whole of Japan. The assessment indicates that seasonal variation is particularly important because the rainy and typhoon seasons, which include extreme events, are the dominant seasons. Because fluvial wash-load-component turbidity appears to vary exponentially, this phenomenon has an impact on the management of social capital, such as drinking water services. Prediction of the impacts of future climate change on fluvial wash-load sediment is crucial for effective environmental planning and the management of social capital to adapt to the next century. CapsuleWe demonstrate that simulations comprise an ensemble of factors, including multiple physical configurations, associated with the wash-load component for the whole of Japan.

An evaluation of simulated particulate sulfate over East Asia through global model intercomparison

AbstractSulfate aerosols simulated by an aerosol module coupled to the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) at a spatial resolution (220 km) widely used by global climate models were evaluated by a comparison with in situ observations and the same aerosol module coupled to the Model for Interdisciplinary Research on Climate (MIROC) over East Asia for January, April, July, and October 2006. The results indicated that a horizontal gradient of sulfate from the source over China to the outflow over Korea‐Japan was present in both the simulations and the observations. At the observation sites, the correlation coefficients of the sulfate concentrations between the simulations and the observations were high (NICAM: 0.49–0.89, MIROC: 0.61–0.77), whereas the simulated sulfate concentrations were lower than those obtained by the observation with the normalized mean bias of NICAM being −68 to −54% (all), −77 to −63% (source), and −67 to −30% (outflow) and that of MIROC being −61 to −28% (all), −77 to −63% (source), and −60 to +2% (outflow). Both NICAM and MIROC strongly underpredict surface SO2 over China source regions and Korea‐Japan outflow regions, but the MIROC SO2 is much higher than NICAM SO2 over both regions. These differences between the models were mainly explained by differences in the sulfate formation within clouds and the dry deposition of SO2. These results indicated that the uncertainty of the meteorological and cloud fields as well as the vertical transport patterns between the different host climate models has a substantial impact on the simulated sulfate distribution.

Possible future rainfall over Gangetic Plains (GP), India, in multi-model simulations of CMIP3 and CMIP5

The Gangetic Plain (GP) of India is much sensitive to rainfall due to its large spatial and temporal variability, and therefore, Coupled Model Intercomparison Project phases 3 and 5 (CMIP3 and CMIP5)-simulated rainfall is analysed over the GP. Model evaluation is carried out with observed rainfall of India Meteorological Department (IMD) and Global Precipitation and Climatology Project (GPCP). Community Climate System Model version 3 (CCSM3), Hadley Centre Global Environment Model (HadGEM) and Model for Interdisciplinary Research on Climate (MIROC) (Hires) of CMIP3 and CCSM4, CESM1 (WACCM) and CESM1 (CAM5) of CMIP5 sound well with observations. In CMIP3, projected future changes in June-July-August-September (JJAS) rainfall show either 5–15 % excess or 5 % deficit in CCSM3 (A2 scenario) and 10 % deficit in HadGEM1. In B1, MIROC (Hires) shows 5–10 % deficit. Under A1B scenario, deficit is possible in MIROC (Hires) and HadGEM1. In CMIP5, CESM1 (CAM5) shows 5–15 % deficit in Representative Concentration Pathway (RCP) 4.5. CCSM4 and CESM1 (WACCM) show 10–20 % excess while 5–15 % deficit is possible in CESM1 (CAM5) in RCP 8.5.

Predicting Irrigated and Rainfed Rice Yield Under Projected Climate Change Scenarios in the Eastern Region of India

Numerous estimates for the coming decades project changes in precipitation resulting in more frequent droughts and floods, rise in atmospheric CO2 and temperature, extensive runoff leading to leaching of soil nutrients, and decrease in freshwater availability. Among these changes, elevated CO2 can affect crop yields in many ways. It is imperative to understand the consequences of elevated CO2 on the productivity of important agricultural crop species in order to devise adaptation and mitigation strategies to combat impending climate change. In this study, we have modeled rice phenology, growth phase, and yield with the “Decision Support System for Agrotechnology Transfer (DSSAT) CERES rice model” and arrived at predicted values of yield under different CO2 concentrations at four different locations in Eastern India out of which three locations were irrigated and one location was rainfed. The ECHAM climate scenario, Model for Interdisciplinary Research on Climate (MIROC)3.0 climate scenario, and ensemble models showed different levels of yield increase with a clear reduction in yield under rainfed rice as compared to irrigated rice. A distinct regional and cultivar difference in response of rice yield to elevated CO2 was seen in this study. Results obtained by simulation modeling at different climate change scenarios support the hypothesis that rice plant responses to elevated CO2 are through stimulation of photosynthesis. Realization of higher yields is linked with source sink dynamics and partitioning of assimilates wherein sink capacity plays an important role under elevated CO2 conditions.

Phylogeographical structure of the boreal-montane orchidMalaxis monophyllosas a result of multi-directional gene flow

�2 ), but showing a lack of phylogeographical structure. This pattern might be caused by multiple phenomena and processes, e.g. broad-fronted recolonization with accompanying multi-directional gene flow between populations and expansion from at least two refugial areas. Despite the lack of phylogeographical structure, three centres of haplotype diversity were indicated in the European part of the range of M. monophyllos. According to these data, alpine and lowland glacial refugia located between the ice sheets in the European Alps and the Scandinavian glaciers seem most likely to be in Europe. Moreover, models of climatically suitable areas during the Last Glacial Maximum (LGM) confirmed the Alps as a possible refuge, and indicated an opportunity for the persistence of M. monophyllos populations in Beringia and parts of Siberia. Using two models (Model for Interdisciplinary Research on Climate (MIROC) and Community Climate System Model (CCSM)), we predicted a significant reduction in climatically suitable areas for M. monophyllos in the future (2080). Our study also demonstrated that the biological features of M. monophyllos, including breeding system and dispersal mode, seem to be crucial in understanding its phylogeographical pattern. Our results also highlighted the importance of anthropogenic habitats as reservoirs of genetic diversity and alternative habitats for this species in the context of declining natural populations. © 2015 The Linnean Society of London, Botanical Journal of the Linnean Society, 2015, ••, -. ADDITIONAL KEYWORDS: anthropogenic habitats - cpDNA - Orchidaceae - plastid DNA diversity centres - species distribution models.

Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation

Abstract. The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen–Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash–Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably representative of the range of future GCM projections.