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Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.MIROC.MIROC6.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MIROC6 climate model, released in 2017, includes the following components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.MIROC.MIROC-ES2L.ssp370' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MIROC-ES2L climate model, released in 2018, includes the following components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T42; 128 x 64 longitude/latitude; 40 levels; top level 3 hPa), land: MATSIRO6.0+VISIT-e ver.1.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), ocnBgchem: OECO ver.2.0; NPZD-type with C/N/P/Fe/O cycles, seaIce: COCO4.9. The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, land: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

COVID-19 pandemic has brought tremendous environmental burden due to huge amount of medical wastes (about 54,000 t/d as of November 22, 2020), including face mask, gloves, clothes, goggles, and sanitizer/disinfectant containers. A proper waste management is urgently required to mitigate the spread of the disease, minimize the environmental impacts, and take their potential advantages for further utilization. This work provides a prospective review on the possible thermochemical treatments for those COVID-19 related medical wastes (CMW), as well as their possible conversion to fuels. The characteristics of each waste are initially analyzed and described, especially their potential as energy source. It is clear that most of CMWs are dominated by plastic polymers. Thermochemical processes, including incineration, torrefaction, pyrolysis, and gasification, are reviewed in terms of applicability for CMW. In addition, the mechanical treatment of CMW into sanitized refuse-derived fuel (SRDF) is also discussed as the preliminary stage before thermochemical conversion. In terms of material flexibility, incineration is practically applicable for all types of CMW, although it has the highest potential to emit the largest amount of CO2 and other harmful gasses. Furthermore, gasification and pyrolysis are considered promising in terms of energy conversion efficiency and environmental impacts. On the other hand, carbonization faces several technical problems following thermal degradation due to insufficient operating temperature.

Abstract. The last half century has witnessed the increasing trend of renewable energy utilization with solar photovoltaic (PV) systems as one of the most popular option. Solar PV continues to supplement the main grid in powering both commercial establishments (mainly for reduced electricity expense) as well as residential houses in isolated areas (for basic energy requirement such as for lighting purposes). The objective of this study is to assess the available solar PV power (PPV) potential considering the effects of high temperature, dust and snow in the Asia Pacific region. The PPV potential was estimated considering the effects of the said meteorological parameters using several satellite data including shortwave radiation from Advanced Himawari Imager 8 (AHI8), MOD04 aerosol data from Moderate Resolution Imaging Spectroradiometer (MODIS), precipitation rate from Global Satellite Mapping of Precipitation (GSMaP), air temperature from NCEP/DOE AMIP-II Reanalysis-2 data, and snow water equivalent (SWE) from Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The model is validated by comparing its outputs with the measured PV power from two solar PV installations in Bangkok, Thailand and Perth, Australia. Results show that maximum PPV is estimated at 2.5 GW (cell efficiency of 17.47%) for the region with the maximum decrease in PPV estimated to be about < 2%, 22% and 100% due to high temperature (temperature coefficient of power = 0.47%/K), dust and snow, respectively. Moreover, areas in India and Northern China were observed to experience the effects of both dust and temperature during March-April-May (MAM) season. Meanwhile, countries located in the higher latitudes were severely affected by snow while Australia by high temperature during Dec-Jan-Feb (DJF) season. The model has a mean percentage prediction error (PPE) range of 5% to18% and 7% to 23% in seasonal and monthly estimations, respectively. Outputs from this study can be used by stakeholders of solar PV in planning for small-scale or large-scale solar PV projects in the solar rich region of Asia Pacific.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.MIROC.MIROC-ES2L.ssp119' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MIROC-ES2L climate model, released in 2018, includes the following components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T42; 128 x 64 longitude/latitude; 40 levels; top level 3 hPa), land: MATSIRO6.0+VISIT-e ver.1.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), ocnBgchem: OECO ver.2.0; NPZD-type with C/N/P/Fe/O cycles, seaIce: COCO4.9. The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, land: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

The purpose of the study is to realize energy efficient features for a dedicated desiccant air-conditioning system throughout the season, and propose a new high-efficiency application of this system. Many advanced air-conditioning systems are intended to reduce energy and/or space only for sensitive heat conditioning. During the dehumidification season, the results show that a latent heat conditioning system using a desiccant air-conditioner achieves over 20% higher energy efficiency than conventional systems. A new humidification system that combines a desiccant outdoor air-conditioning unit and heat-pump is proposed for the winter season. The experimental results show that the humidification performance satisfies the minimum demand for an outdoor air conditioner in many areas of Japan, but the energy efficiency is slightly inferior to that of traditional boiler systems. Some improvements in the structure and operation of this system are suggested to improve the higher energy efficiency.

Dataset for the paper "Future projections for the Antarctic ice sheet until the year 2300 with a climate-index method" (Journal of Glaciology, doi: 10.1017/jog.2023.41). Please see the README for details. V1.1: Run-specs header files for SICOPOLIS added. README updated. V1: Initial upload. * * * * * * * The following script may be used to download the entire content of the archive on a Unix/Linux system: #!/bin/bash # --- download_all.sh --- repodir="https://zenodo.org/record/8107061/files" files=("_README.pdf" \ "run_specs_headers.zip" \ "all_scalar.zip" \ "hist.zip" "ctrl_proj_ext.zip" \ "exp05_ext.zip" "exp06_ext.zip" "exp07_ext.zip" "exp08_ext.zip" \ "exp09_ext.zip" "exp10_ext.zip" "exp12_ext.zip" "exp13_ext.zip" \ "expA05_ext.zip" "expA06_ext.zip" "expA07_ext.zip" "expA08_ext.zip" \ "expB06_ext.zip" "expB07_ext.zip" "expB08_ext.zip" \ "expB09_ext.zip" "expB10_ext.zip") for file in ${files[@]}; do wget "${repodir}/${file}" done echo "--- Done! ---" Funding acknowledgements: Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Nos. JP17H06104 and JP17H06323. JSPS Grant-in-Aid for Japan-France Integrated Action Program (SAKURA Program) No. JPJSBP120213203.

Abstract To mitigate the negative effects of climate change, it is necessary to conserve carbon stocks in forests. Typhoons fell many standing trees and generate a substantial amount of coarse woody debris (CWD). In boreal forests, CWD contributes to maintaining carbon stocks for a long time after a disturbance because the decomposition rate of CWD is relatively low. We know that salvage logging after a disturbance tremendously decreases the forest carbon stock over the short term after logging but know little about its long-term effects. We targeted a catastrophic windthrow caused by a super typhoon in 1954 in boreal forests in northern Japan and estimated the long-term effects of salvage logging after the windthrow on the above- and belowground carbon stocks by comparing old-growth forests with low damage from the super typhoon in 1954 or any subsequent typhoons (OG), forests damaged by the typhoon with remaining CWD (i.e., windthrow, WT), and forests damaged by the typhoon followed by salvage logging (WT + SL). The CWD carbon stock of decay class 5 (i.e., the most decayed CWD) in WT was significantly larger than that in OG and WT + SL, suggesting that the CWD in decay class 5 in WT had been generated by the typhoon 64 years ago, and the negative effect of salvage logging on the carbon stock still remains apparent in the CWD carbon stock of decay class 5. The carbon stock of the organic (O) layer in WT was larger than that in WT + SL, probably because of three factors: (1) the slower decomposition rate of fallen leaves and twigs of conifers than broadleaves, as conifer litter is abundant in WT; (2) greater carbon transition from the CWD to the O layer in WT; and (3) the occurrence of a lower decomposition rate in the O layer in WT. However, the total carbon stock in WT + SL has almost recovered to the level of that in WT within the last 64 years. The carbon stocks of broadleaves that grew rapidly after the disturbance and the newly accumulated dead trees generated throughout the stand developmental process might contribute to the recovery of carbon stock in WT + SL. These results indicate that salvage logging affects the allocation of carbon in the forest even after 64 years after a catastrophic windthrow, although there was no large difference in total carbon stock.