Model For Interdisciplinary Research On Climate Version 5 Research Articles

Comprehensive Impact of Changing Siberian Wildfire Severities on Air Quality, Climate, and Economy: MIROC5 Global Climate Model’s Sensitivity Assessments

AbstractWildfires emit atmospheric aerosols, affecting climate and air quality. Siberia is a known source region of wildfires. However, comprehensive knowledge regarding the impact associated with particulate matter pollution due to Siberian wildfires on climate and air quality and their effects on mortality and the economy under present and near‐future warmer atmospheric conditions remains poor. Thus, we performed model sensitivity experiments (atmospheric model and coupled atmosphere‐ocean model settings) simulating the effects of changing Siberian wildfire emissions under the present and near‐future climate conditions, using the Model for Interdisciplinary Research on Climate version 5 (MIROC5). Increased Siberian wildfire smoke likely caused a cooling effect in broad areas of the Northern Hemisphere and worsened the air quality near the source and in the downwind region (i.e., East Asia). The more Siberian wildfires occur, the more air pollution is present in those regions, which likely increases mortality and welfare losses there. However, the total impact of changing temperature on the gross domestic product under present and near‐future climate conditions is ambiguous. Our comprehensive results on the air quality changes due to Siberian wildfires under present and near‐future climate conditions suggest that increased efforts to limit the aerosol impact of Siberian wildfires are crucial to prevent possible excess mortality and economic losses.

Forecasting 100-year changes of streamflow in the Mun River Basin (NE Thailand) under the HAPPI experiment using the SWAT model

Abstract The Lower Mekong River is one of the significant rivers nurturing people on the Southeast Asian mainland. Its tributaries include the Mun River (NE Thailand), which often experiences extreme water events. In this study, the streamflow change in the year 2115 was simulated by relying on the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) experiment and the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) climate model for average global warming of 1.5 °C (Plus1.5) and 2.0 °C (Plus2.0) above pre-industrial levels and compared with the base year in 2015 for the Mun River Basin. The Soil–Water Assessment Tool (SWAT) was used for the streamflow simulation. The results showed an increasing air temperature against lowering rainfall and relative humidity (except for the post-monsoon months), suggesting overall rain suppression in response to the warming climate. The median projected annual streamflow to the Mekong River in 2115 decreased for both ‘Plus1.5’ (−32.5%, median) and ‘Plus2.0’ (−23.1%, median). However, increasing annual streamflow could be found only in the middle part. Seasonal streamflow changes revealed a different spatiotemporal response to climate change resulting in inconsistent streamflow changes across the basin. The adaptive measures for the middle part should be focused on flooding control, whereas the upper and the lower parts should be against drought.

Policy-Making toward Integrated Water Resources Management of Zarrine River Basin via System Dynamics Approach under Climate Change Impact

In terms of having a comprehensive vision toward supplying the water requirements, a multi-criteria decision-making approach was employed on the Zarrine River Basin (ZRB) in the northwest of Iran. First, the climate change impacts were analyzed with the Long Ashton Research Station Weather Generator (LARS-WG) downscaling approach by using General Circulation Models (GCMs) including the European Consortium Earth System Model (EC-EARTH), Hadley Centre Global Environment Model version 2 (HADGEM2), Model for Interdisciplinary Research on Climate, version 5 (MIROC5), and Max Planck Institute Earth System Model (MPI-ESM), from Coupled Model Intercomparison Project 5 (CMIP5) under Representative Concentration Pathway (RCP4.5, RCP8.5) scenarios for 2021–2080. Afterward, the downscaled variables were utilized as inputs to the Artificial Neural Network (ANN) model to predict future runoff under the climate change impact. Finally, the system dynamics (SD) model was employed to simulate various scenarios for assessing water balance utilizing the Vensim software. The results of downscaling models suggested that the temperature of the basin will increase by 0.47 and 0.91 °C under RCPs4.5 and 8.5 by 2040, respectively. Additionally, the precipitation will decrease by 3.5 percent under RCP4.5 and 14 percent under RCP8.5, respectively. Moreover, simulation results revealed that the water demand in various sectors will be enormously increased. The contribution of the climate change impact on the future run-off was a seven percent decrease, on average, over the basin. The SD model, according to presented plausible scenarios including decreasing agriculture product and shifting irrigation efficiency, cloud-seeding, population control, and household consumption reduction, reducing meat and animal-husbandry production, and groundwater consumption control, resulted in a water balance equilibrium over five years. However, the performance of individual scenarios was not effective; instead, a combination of several scenarios led to effective performance in managing reduced runoff under climate change.

Climate change and hydrological regime of the high-altitude Indus basin under extreme climate scenarios

Climate change is recognized as one of the greatest challenges of 21st century. This study investigated climate and hydrological regimes of the high-altitude Indus basin for the historical period and extreme scenarios of future climate during 21st century. Improved datasets of precipitation and temperature were developed and forced to a fully-distributed physically-based energy-balance Variable Infiltration Capacity (VIC) hydrological model to simulate the water balance at regional and sub-basin scale. Relative to historical baseline, the results revealed highly contrasting signals of climate and hydrological regime changes. Against an increase of 0.6 °C during the last 40 years, the median annual air temperature is projected to increase further between 0.8 and 5.7 °C by the end of 21st century. Similarly, a decline of 11.9% in annual precipitation is recorded, but future projections are highly conflicting and spatially variable. The Karakoram region is anticipated to receive more precipitation, while SW-Hindukush and parts of W-Himalayan region may experience decline in precipitation. The Model for Interdisciplinary Research On Climate version-5 (MIROC5) generally shows increases, while Max Planck Institute Earth System Model at base resolution (MPI-ESM-LR) indicates decreases in precipitation and river inflows under three Representative Concentration Pathways (RCPs) of 2.6, 4.5 and 8.5. Indus-Tarbela inflows are more likely to increase compared to Kabul, Jhelum and Chenab river inflows. Substantial increase in the magnitudes of peak flows and one-month earlier attainment is projected for all river gauges. High flows are anticipated to increase under most scenarios, while low flows may decrease for MPI-ESM-LR in Jhelum, Chenab and Kabul river basins. Hence, hydrological extremes are likely to be intensified. Critical modifications in the strategies and action plans for hydropower generation, construction and operation of storage reservoirs, irrigation withdrawals, flood control and drought management will be required to optimally manage water resources in the basin.

Downscaling of climate extremes over South America – Part I: Model evaluation in the reference climate

In this paper, we evaluate temperature and precipitation trends over South America (SA), simulated by the regional Eta model with 20-km horizontal resolution nested to three global models: The Canadian Earth System Model Second Generation (CanESM2-ES), The Met Office Hadley Centre Global Environmental Model - Earth System (HadGEM2-ES) and the Model for Interdisciplinary Research on Climate version 5 (MIROC5). The simulated trends are compared to observed trends (OBS) using six (four) extreme temperature (precipitation) indices recommended by the Expert Team on Climate Change Detection and Indices. In both simulations and OBS, extreme temperature trends over Amazon (AMZ) and Northeast Brazil (NEB) are higher than over South East SA (SESA) and West SA (WSA). Also, trends based on maximum temperatures are, in general, smaller than those based on minimum temperatures. The three downscaling simulations reproduce these features. The temperature simulations of the Eta-CanESM2 (Eta-MIROC5) show the largest (smallest) trends among the three simulations. The Eta-MIROC5, performs better than the other two simulations, reproducing the signals and the magnitudes of the extreme temperature trends, and some cooling trends over SESA, as shown in the observation. Precipitation trends from the three simulations do not compare well with observations, such as temperature trends. However, Eta-MIROC5 presents the best simulations, showing increase in the magnitude of the precipitation extremes over most of SA. The results from the three simulations presented here will be further used for the assessment of climate change projections in the SA region.

Performance evaluation of Eta/HadGEM2-ES and Eta/MIROC5 precipitation simulations over Brazil

Climate change effects can have significant impacts worldwide. Extreme events can modify water availability and agricultural production, making climate change planning an essential task. The National Institute for Space Research (INPE in Portuguese) in Brazil has made a large dataset of regional climate model outputs (simulations and projections) available, which opens up many possibilities of carrying out high-resolution climate change studies. However, there is still no performance evaluation of the model-derived rainfall output against high-resolution ground-based observation data considering the Brazilian biomes. This paper attempts to fill this gap and evaluates the simulated precipitation throughout Brazil. We used gridded observed precipitation data and historical climate simulations from the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) and from the Hadley Center Global Environment Model, version 2 (HadGEM2-ES), which were downscaled by the Eta RCM (Regional Climate Model). For the overlapping period (1980–2005), there is good agreement (PBIAS up to 10%) of downscaled annual simulations for the Amazon and Cerrado biomes and large biases (reaching 40%) in the Pampa biome, compared to the observations. Our results showed that HadGEM2-ES is capable of representing long-term mean monthly precipitation for large areas well, such as the Amazon and Cerrado. Furthermore, the Eta RCM has considerably improved the driving GCM MIROC5 simulations. In conclusion, we recommend using the HadGEM2-ES simulations for the Amazon, Eta/HadGEM2-ES for the Atlantic Forest, Cerrado, and Pampa, and Eta/MIROC5 for the Caatinga and Pantanal. Our study provides an overview of two downscaled simulation datasets in Brazil that may help verify the models' suitability for further climate change assessments.

Determination of Extreme Hydrological Index using HBV Model Simulation Results (Case Study : Upper Ciliwung Watershed)

The study of climate change on hydrological response is a crucial as climate change impact will drive the change in hydrological regimes of river. Upper Ciliwung watershed is one of the critical rivers in Java Island, which has been affected by climate change. This study aims to: (i) simulate the discharge flow using the Hydrologiska Byrans Vattenbalansavdelning (HBV) model; (ii) simulate future flow using three general circulation models (GCM) namely Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk.3.6.0, Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Geophysical Fluid Dynamics Laboratory-Coupled Model generation 3 (GFDL-CM3); (iii) determine the changes of extreme hydrological index during historical period (2001-2015) and projected period (2031-2045). The historical year simulation and projections are used to determine eight hydrologic extreme indices for high flow and low flow. We calibrated the HBV model for two years (2001-2002) and validated it for two years (2003-2004). Our model performed well in discharge simulation as shown by the NSE values (0.66 for calibration and validation). Then we calculated the indices for each period used (historical and projected). To show the changes in hydrological regimes, we compare the indices between two periods. Changes in the index of the two periods tend to decrease in value on the index parameters that characterize the minimum extreme events. Hence, that it is possible in the projected period there will be extreme hydrological events in the form of drought.

Assessment of the climate change risks for inflow into Sagami Dam reservoir using a hydrological model

Abstract Adverse effects of future climate change on water supply systems are of concern. High turbidity caused by abrupt flood, and drought caused by continuous dry days are the major risks. To assess such risks, a comprehensive method to simulate hydrology with high spatiotemporal resolution should be developed. In this study, a series of methods from parameter estimation to future simulation using the Soil and Water Assessment Tool (SWAT) was demonstrated for Sagami Dam reservoir, which is a typical water supply reservoir in Japan. A proposed parameter calibration method by optimizing percent bias followed by optimizing Nash–Sutcliffe efficiency gave good performance of model prediction of the daily average reservoir inflow in the past. Using this model, the changes in inflow under expected climate change were simulated. Three predicted daily climates by the Model for Interdisciplinary Research on Climate version 5 (MIROC5) under three representative concentration pathways, i.e., RCP 2.6, 4.5, and 8.5, in 2081–2100 were used for the simulation, whereas observed daily climate during 1981–2000 was used as the past reference. The risks were discussed by considering their seasonality, indicating increases in flood and drought in June and July, and in February and April, respectively.

Weakening of Nonlinear ENSO Under Global Warming

AbstractThe amplitude response of the El Niño–Southern Oscillation (ENSO) to global warming is examined in two global climate models with realistic ENSO nonlinearity. Geophysical Fluid Dynamics Laboratory Earth System Model Version 2M (GFDL‐ESM2M) and Model for Interdisciplinary Research on Climate version 5 (MIROC5) are the two models that exhibit realistic ENSO nonlinearity. With quadrupled atmospheric carbon dioxide, the ENSO amplitude of GFDL‐ESM2M decreases by about 40%, whereas that of MIROC5 remains almost constant. Because GFDL‐ESM2M exhibits stronger climatological thermal stratification than MIROC5, greenhouse gas forcing increases the upper ocean stability and causes the thermocline to be less sensitive to wind perturbations. The stiffer thermocline inhibits the nonlinear variations of sea surface temperature so that the ENSO amplitude substantially weakens. Idealized nonlinear recharge oscillator model experiments further support climatological thermal stratification as a determinant of the warming response. Observations exhibit stronger thermal stratification than both models, which suggests that the real world may terminate strong, nonlinear El Niños sooner than model‐based projections.

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

Abstract. This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere–ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude–longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Impact of Arctic Wetlands on the Climate System: Model Sensitivity Simulations with the MIROC5 AGCM and a Snow-Fed Wetland Scheme

Abstract Wetlands cover large areas of the middle and high latitudes and influence the surface water and energy budget, surface hydrology, and the climate system. In this study, a scheme implicitly representing a snow-fed wetland, in which snowmelt can be stored with consideration of subgrid terrain complexity, was implemented in the Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO) land surface model. An atmospheric general circulation model (AGCM) experiment was conducted using the Model for Interdisciplinary Research on Climate, version 5 (MIROC5), with and without the wetland scheme, with the main aim of reducing the model bias of warm and dry boreal summer at mid- to high latitudes. The experiment showed not only a better surface hydrology but also a weaker land–atmosphere coupling strength and larger (smaller) latent (sensible) heat flux due to the delayed snowmelt runoff. The summer warm and dry bias was partially improved over snowy and flat areas, particularly over much of western Eurasia and North America, without an apparent deterioration of simulated surface hydrology and climate over the rest of the land in the other seasons; the mean absolute error of 2-m air temperature and precipitation over land at 45°–90°N in summer decreased by 19% and 4%, respectively. The next step of model development will involve implementing an explicit representation of subgrid-scale surface water and related processes.

Projected climate change impacts in rainfall erosivity over Brazil

The impacts of climate change on soil erosion may bring serious economic, social and environmental problems. However, few studies have investigated these impacts on continental scales. Here we assessed the influence of climate change on rainfall erosivity across Brazil. We used observed rainfall data and downscaled climate model output based on Hadley Center Global Environment Model version 2 (HadGEM2-ES) and Model for Interdisciplinary Research On Climate version 5 (MIROC5), forced by Representative Concentration Pathway 4.5 and 8.5, to estimate and map rainfall erosivity and its projected changes across Brazil. We estimated mean values of 10,437 mm ha−1 h−1 year−1 for observed data (1980–2013) and 10,089 MJ mm ha−1 h−1 year−1 and 10,585 MJ mm ha−1 h−1 year−1 for HadGEM2-ES and MIROC5, respectively (1961–2005). Our analysis suggests that the most affected regions, with projected rainfall erosivity increases ranging up to 109% in the period 2007–2040, are northeastern and southern Brazil. Future decreases of as much as −71% in the 2071–2099 period were estimated for the southeastern, central and northwestern parts of the country. Our results provide an overview of rainfall erosivity in Brazil that may be useful for planning soil and water conservation, and for promoting water and food security.

Impacts of land use changes from the Hanoi Master Plan 2030 on urban heat islands: Part 2. Influence of global warming

Hanoi City, Vietnam, presented the Hanoi Master Plan 2030 in 2011 to cope with rapid population growth and urbanisation. The main objective of this two-part study was to investigate the impacts of land use changes brought by the master plan on urban heat islands in Hanoi by 2030. This paper analyses the contributions of land use changes and global warming to the future increase in urban temperatures in Hanoi by the 2030s. Firstly, numerical simulations using Weather Research and Forecasting (WRF) were conducted for the present land use as well as the land use condition of the master plan under the same weather conditions to detect only the impact of land use changes. Secondly, WRF simulations were conducted for the land use condition of the master plan under the influence of global warming in the 2030s utilising the climate data projected by a Global Climate Model (GCM), Model for Interdisciplinary Research on Climate Version 5 (MIROC5), via a direct dynamical downscaling method. In the 2030s, the average air temperature increase in existing urban areas was projected to be up to 2.1°C, of which up to 1.5 and 0.6°C are attributable to global warming and land use changes, respectively.

An assessment of climate change impacts on maize yields in Hebei Province of China.

The climate change impacts on maize yields are quantified in this paper using statistical models with panel data from 3731 farmers' observations across nine sample villages in Hebei Province of China. The marginal impacts of climate change and the simulated impacts on maize yields based on scenarios of Representative Concentration Pathways 2.6, 4.5, 6.0, and 8.5 from the global climate models of Model for Interdisciplinary Research on Climate version 5 (MIROC5) and Meteorological Research Institute Coupled General Circulation Model version 3 (MRI-CGCM3) were then calculated, analyzed, and explained. The results indicate that, first, the most important finding was that climate change impacts on maize yields were significant and a 1°C warming or a 1mm decrease in precipitation resulted in a 150.255kg or a 1.941kg loss in maize yields per hectare, respectively. Second, villages with latitudes of less than 39.832 and longitudes of more than 114.839 in Hebei province suffered losses due to warm weather. Third, the simulated impacts for the full sample are all negative based on scenarios from MIROC5, and their magnitudes are more than those of MRI-CGCM3 are. Based on scenarios in the 2050s, the biggest loss for maize yields per hectare for the full sample accounts for about one-tenth of the mean maize yield from 2004 to 2010, and all of the villages are impacted. Hence, it is important to help farms adopt an adaptation strategy to tackle the risk of loss for maize yields from climate change, and it is necessary to develop agricultural synthesis services as a public adaptation policy at the village level to interact with the adaptation strategy at the farm level.

Predictability of Two Types of El Niño Assessed Using an Extended Seasonal Prediction System by MIROC

Abstract Predictability of El Niño–Southern Oscillation (ENSO) is examined using ensemble hindcasts made with a seasonal prediction system based on the atmosphere and ocean general circulation model, the Model for Interdisciplinary Research on Climate, version 5 (MIROC5). Particular attention is paid to differences in predictive skill in terms of the prediction error for two prominent types of El Niño: the conventional eastern Pacific (EP) El Niño and the central Pacific (CP) El Niño, the latter having a maximum warming around the date line. Although the system adopts ocean anomaly assimilation for the initialization process, it maintains a significant ability to predict ENSO with a lead time of more than half a year. This is partly due to the fact that the system is little affected by the “spring prediction barrier,” because increases in the error have little dependence on the thermocline variability. Composite analyses of each type of El Niño reveal that, compared to EP El Niños, the ability to predict CP El Niños is limited and has a shorter lead time. This is because CP El Niños have relatively small amplitudes, and thus they are more affected by atmospheric noise; this prevents development of oceanic signals that can be used for prediction.

Evaluation of a high-resolution historical simulation over China: climatology and extremes

China faces an increasing challenge in water resources in the coming decades; thus high-confidence climate projection is of particular importance for the country’s future. In this paper, we evaluate the performance of a long high-resolution continuous simulation over China based on multiple observations and the corresponding historical simulation. The simulation is completed using the Weather Research and Forecasting (WRF) model driven by the Model for Interdisciplinary Research on Climate version 5 (MIROC5) in the context of the Coupled Model Intercomparison Project Phase 5. The results show that both MIROC5 and WRF can capture the distribution and variability of temperature over China, whereas WRF shows improvements, particularly for simulation of regional features. Compared with MIROC5, WRF can reproduce the spatial distribution, annual cycle, probability distribution, and seasonal evolution of the precipitation over mainland China and the sub-regions with better performance. The trend is of fundamental importance in the future projection estimations, and WRF shows better skill in simulating the annual mean precipitation trend. However, there is overestimation of precipitation in Southeast China while negative one in the middle latitude of China in WRF simulation, which can be traced back to model bias in atmospheric circulation and water vapor transportation in these regions. Several extreme climate indices are selected to further assess the model’s performance in simulating climate extremes, WRF can well reproduce the main features with better model skill compared with MIROC5. The better performance of WRF indicates the necessity of the dynamical downscaling technique and the robustness of regional climate simulation in future regional climate projection over China.

Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.