Permafrost and ground freezing/thawing processes are physically and eco-climatologically important factors in the terrestrial cryosphere. The model reproducibility of frozen ground affects the certainty and reliability of simulated eco-climate conditions in cold regions as well as on a global scale. This study evaluated the variations and their attributes in the model performance developed and employed in the recent decade regarding the subsurface thermal state using outputs from Japanese and international model intercomparison projects and reanalysis data. The simulated surface and subsurface physical states were compared at four Arctic sites under different frozen ground conditions (Fairbanks, Kevo, Tiksi, and Yakutsk). The results showed that despite large variations in the modeled permafrost temperature, all the models, including the reanalysis data, successfully reproduced the permafrost conditions for the continuous permafrost sites. In contrast, some models failed to reproduce the presence of permafrost for the sites in the discontinuous to isolated permafrost zones. Evaluations of near-surface ground temperature variability revealed that the overall wellness of the simulated ground thermal states relied on winter reproducibility. The importance of snowpack metamorphosis for adequate thermal insulation was confirmed and demonstrated. The results at the coastal tundra site imply the importance of snow cover redistribution and wind crust formation owing to strong winds, the lack of which resulted in overestimations of thermal insulation and overcooled near-surface ground by most models.

Due to the lack of black carbon (BC) measurement data in some cases, elemental carbon (EC) is often used as a surrogate of BC, with a simple assumption that they are interchangeable. Such assumption will inevitably lead to uncertainties in radiative forcing estimation and health impact assessment. In order to quantitatively and sys-tematically evaluate the relationship between BC and EC as well as factors responsible for their difference, 3-year collocated equivalent BC (eBC) and EC measurements with 1-h resolution were performed in Beijing, China continuously from 2016 to 2019. EBC concentration was measured by the multi-wavelength aethalometer (AE-33) based on optical analysis, while EC concentration was determined by semi-continuous OC/EC analyzer with thermal-optical method. The results showed that around 90% of eBC concentration was higher than that of EC, with average difference between eBC and EC as 1.21 mu g m(-3) (accounting for 33% of average eBC in Beijing). EBC and EC concentrations exhibited strong correlation (r = 0.90) during the whole study period, but the slopes (or eBC/EC ratio) and correlation coefficients varied across seasons (spring: 1.67 and 0.94; summer: 0.91 and 0.65; fall: 1.15 and 0.88; winter: 1.09 and 0.91, respectively). Based on the information from shell/core ratios by Single Particle Soot Photometer (SP2), source apportionment results by positive matrix factorization model, and chemical composition of PM2.5, the differences between eBC and EC concentrations were found to be primarily related to BC aging process and secondary components as evidenced by strong positive correlation with sec-ondary species (e.g., secondary organic carbon and nitrate). This study provided seasonal specific conversion factors of eBC and EC in Beijing and helpful reference for other areas, which will contribute new knowledge of carbonaceous aerosol and reduce uncertainty in assessing future climate change and health studies of BC.

The harmonization of sampling, sample preparation and laboratory analysis methods to detect carbon compounds in snow requires detailed documentation of those methods and their uncertainties. Moreover, intercomparison experiments are needed to reveal differences and quantify the uncertainties further. Here, we document our sampling, filtering, and analysis protocols used in the intercomparison experiment from three laboratories to detect water-insoluble carbon in seasonal surface snow in the high-mountain environment at Kolm Saigurn (47.067842 degrees N, 12.98394 degrees E, alt 1598 m a.s.l.), Austria. The participating laboratories were TU Wien (Austria), the University of Florence (Italy), and the Finnish Meteorological Institute (Finland). For the carbon analysis, the NIOSH5040 and EUSAAR2 protocols of the OCEC thermal-optical method were used. The median of the measured concentrations of total carbon (TC) was 323 ppb, organic carbon (OC) 308 ppb, and elemental carbon (EC) 16 ppb. The methods and protocols used in this experiment did not reveal large differences between the laboratories, and the TC, OC, and EC values of four inter-comparison locations, five meters apart, did not show meter-scale horizontal variability in surface snow. The results suggest that the presented methods are applicable for future research and monitoring of carbonaceous particles in snow. Moreover, a recommendation on the key parameters that an intercomparison experiment participant should be asked for is presented to help future investigations on carbonaceous particles in snow. The work contributes to the harmonization of the methods for measuring the snow chemistry of seasonal snow deposited on the ground.

There have been extensive studies on poleward expansion of the Hadley cells and the associated poleward shift of subtropical dry zones in the past decade. In the present study, we study the trends in the width and strength of the Hadley cells, using currently available simulation results of the Coupled Model Intercomparison Project Phase-6 (CMIP6), and compare the trends with that in CMIP5 simulations. Our results show that the total annual-mean trend in the width of the Hadley cells is 0.13 degrees +/- 0.02 degrees per decade over 1970-2014 in CMIP6 historical All-forcing simulations. It is almost the same as that in CMIP5. The trend in the strength of the Northern-Hemisphere (NH) cell shows much greater weakening in CMIP6 than in CMIP5, while the strength trend in the Southern-Hemisphere (SH) cell shows slight strengthening. Single-forcing simulations demonstrate that increasing greenhouse gases cause widening and weakening of both the NH and SH Hadley cells, while anthropogenic aerosols and stratospheric ozone changes cause weak strengthening trends in the SH cell. CMIP6 projection simulation results show that both the widening and weakening trends increase with radiative forcing. (C) 2020 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.

Black carbon (BC) is a primary aerosol emitted directly into the atmosphere from incomplete combustion. It absorbs incoming solar radiation and outgoing terrestrial radiation, which has significant implications to aerosol radiative forcing. Aethalometer employs optical attenuation technique to measure real-time BC mass concentrations. BC mass concentration measured using a single spot aethalometer (AE31) can be significantly uncertain due to filter loading effect. A modified version of AE31, namely, a dual spot aethalometer (AE33), uses a real-time loading effect compensation algorithm and measures BC mass concentrations. BC mass concentrations measured using single and dual spot aethalometers over an urban location are analysed. BC mass concentration from AE33 is higher (11%) than BC measured by post processed loading effect compensated AE31 data. Daily averaged BC mass concentration measured by AE31 and AE33 shows a very good linear agreement (coefficient of determination (0.98), and a small zero offset (0.22)). Aerosol absorption coefficients show an average difference of 28.5% between the two aethalometers. Aerosol absorption coefficient is utilised with nephelometer measured aerosol scattering coefficients to compute single scattering albedo (SSA). SSA (550 nm) estimated from the AE33 is always higher (similar to 8%) than AE31. Estimates of aerosol radiative forcing show that when SSA changes from 0.65 to 0.70 over urban regions the atmospheric warming changes by 10%, while when SSA changes from 0.85 to 0.90 the atmospheric warming changes by 25%. This study highlights the non-linear relation between SSA and aerosol forcing, and reveals how crucial it is to determine single scattering albedo accurately in order to reduce the uncertainty in aerosol radiative forcing estimate.

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (ESMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for reducing existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling, we used soil profile observations (585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m(-2)) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors, when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primary factors leading to observed differences were (1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in ESMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks. (C) 2016 The Authors. Published by Elsevier B.V.