COMPARING ANALYSIS OF PRETREATMENT METHODS OF WOOD AND BONE MATERIALS FOR THE CHRONOLOGY OF PERIPHERAL BURIALS AT TUNNUG 1, TUVA REPUBLIC, RUSSIA

ABSTRACT Nine burials from Tunnug 1 site in Tuva Republic, which contained human and animal bones as well as remains of wood, were chosen for intercomparison study of preparation methods. Nine human bones, nine animal bones and 11 pieces of wood were prepared. Gelatin extracted from bones was purified using the UF method but the extraction from bones was modified with respect to acid and base treatment. Wood samples were treated as whole using acid-base-acid and cellulose was extracted for comparison. The results confirmed a highly consistent chronology of the sites centered at 200–400 CE, however, a few bones resulted in an offset between ages obtained by different methods. The extraction of cellulose was limited due to the poor preservation of wood. Our results highlight problems of dating poorly preserved bones and wood.

Impact of the choice of surface mass balance models and their calibration on large-scale glacier change projections

<p>A recent large model intercomparison study (GlacierMIP) showed that differences between the glacier models is a dominant source of uncertainty for future glacier change projections, in particular in the first half of the century.  Each glacier model has their own unique set of process representations and climate forcing methodology, which makes it impossible to determine the model components that contribute most to the projection uncertainty. This study aims to improve our understanding of the sources of large scale glacier model uncertainty using the Open Global Glacier Model (OGGM), focussing on the surface mass balance (SMB) in a first step. We calibrate and run a set of interchangeable SMB model parameterizations (e.g. monthly vs. daily, constant vs. variable lapse rates, albedo, snowpack evolution and refreezing) under controlled boundary conditions. Based on ensemble approaches, we explore the influence of (i) the parameter calibration strategy and (ii) SMB model complexity on regional to global glacier change. These uncertainties are then put in relation to a qualitative selection of other model design choices, such as the forcing climate dataset and ice dynamics model parameters. </p>

Multi-model intercomparisons of air quality simulations for the KORUS-AQ campaign

The Korea-United States Air Quality (KORUS-AQ) field study was conducted during May–June 2016 to understand the factors controlling air quality in South Korea. Extensive aircraft and ground network observations from the campaign offer an opportunity to address issues in current air quality models and reduce model-observation disagreements. This study examines these issues using model evaluation against the KORUS-AQ observations and intercomparisons between models. Six regional and two global chemistry transport models using identical anthropogenic emissions participated in the model intercomparison study and were used to conduct air quality simulations focusing on ozone (O3), aerosols, and their precursors for the campaign. Using the KORUSv5 emissions inventory, which has been updated from KORUSv1, the models successfully reproduced observed nitrogen oxides (NOx) and volatile organic compounds mixing ratios in surface air, especially in the Seoul Metropolitan Area, but showed systematic low biases for carbon monoxide (CO), implying possible missing CO sources in the inventory in East Asia. Although the DC-8 aircraft-observed O3 precursor mixing ratios were well captured by the models, simulated O3 levels were lower than the observations in the free troposphere in part due to too low stratospheric O3 influxes, especially in regional models. During the campaign, the synoptic meteorology played an important role in determining the observed variability of PM2.5 (PM diameter ≤ 2.5 μm) concentrations in South Korea. The models successfully simulated the observed PM2.5 variability with significant inorganic sulfate-nitrate-ammonium aerosols contribution, but failed to reproduce that of organic aerosols, causing a large inter-model variability. From the model evaluation, we find that an ensemble of model results, incorporating individual models with differing strengths and weaknesses, performs better than most individual models at representing observed atmospheric compositions for the campaign. Ongoing model development and evaluation, in close collaboration with emissions inventory development, are needed to improve air quality forecasting.

Large-Scale Analysis of Global Gridded Precipitation and Temperature Datasets for Climate Change Impact Studies

Currently, there are a large number of diverse climate datasets in existence, which differ, sometimes greatly, in terms of their data sources, quality control schemes, estimation procedures, and spatial and temporal resolutions. Choosing an appropriate dataset for a given application is therefore not a simple task. This study compares nine global/near-global precipitation datasets and three global temperature datasets over 3138 North American catchments. The chosen datasets all meet the minimum requirement of having at least 30 years of available data, so they could all potentially be used as reference datasets for climate change impact studies. The precipitation datasets include two gauged-only products (GPCC and CPC-Unified), two satellite products corrected using ground-based observations (CHIRPS V2.0 and PERSIANN-CDR V1R1), four reanalysis products (NCEP CFSR, JRA55, ERA-Interim, and ERA5), and one merged product (MSWEP V1.2). The temperature datasets include one gauge-based (CPC-Unified) and two reanalysis (ERA-Interim and ERA5) products. High-resolution gauge-based gridded precipitation and temperature datasets were combined as the reference dataset for this intercomparison study. To assess dataset performance, all combinations were used as inputs to a lumped hydrological model. The results showed that all temperature datasets performed similarly, albeit with the CPC performance being systematically inferior to that of the other three. Significant differences in performance were, however, observed between the precipitation datasets. The MSWEP dataset performed best, followed by the gauge-based, reanalysis, and satellite datasets categories. Results also showed that gauge-based datasets should be preferred in regions with good weather network density, but CHIRPS and ERA5 would be good alternatives in data-sparse regions.

Modelling mixed-phase clouds with the large-eddy model UCLALES–SALSA

The large-eddy model UCLALES–SALSA, with an exceptionally detailed aerosol description for both aerosol number and chemical composition, has been extended for ice and mixed-phase clouds. Comparison to a previous mixed-phase cloud model intercomparison study confirmed the accuracy of newly implemented ice microphysics. A further simulation with a heterogeneous ice nucleation scheme, in which ice-nucleating particles (INPs) are also a prognostic variable, captured the typical layered structure of Arctic mid-altitude mixed-phase cloud: a liquid layer near cloud top and ice within and below the liquid layer. In addition, the simulation showed a realistic freezing rate of droplets within the vertical cloud structure. The represented detailed sectional ice microphysics with prognostic aerosols is crucially important in reproducing mixed-phase clouds.

Trueness evaluation and verification of inter-assay agreement of serum folate measuring systems

BackgroundDefinitive data to establish if the use of the WHO International Standard (IS) 03/178 as a common calibrator of commercial measuring systems (MSs) has improved the harmonization of serum total folate (tFOL) measurements to a clinically suitable level are lacking. Here, we report the results of an intercomparison study aimed to verify if the current inter-assay variability is acceptable for clinical application of tFOL testing.MethodsAfter confirming their commutability, the IS 03/178 and National Institute for Standards and Technology SRM 3949 L1 were used for evaluating the correctness of traceability implementation by manufacturers and the MSs trueness, respectively. The inter-assay agreement was verified using 20 patient pools. The measurement uncertainty (U) of tFOL measurements on clinical samples was also estimated. An outcome-based model for defining desirable performance specifications for bias and imprecision for serum tFOL measurements was applied.ResultsThe majority of evaluated MSs overestimated the WHO IS value of +5% or more with the risk to produce an unacceptably high number of false-negative results in clinical practice. The mean inter-assay CV on all pools and on those with tFOL values >3.0 μg/L (n = 15) was 12.5% and 7.1%, respectively. In neither case the goal of 3.0% was fulfilled. The residual bias resulted in an excessive U of tFOL measurement on clinical samples.ConclusionsThe implementation of traceability of tFOL MSs to the WHO IS 03/178 is currently inadequate, resulting in an inter-assay variability that does not permit the use of a common threshold for detecting folate deficiency.