Surface energy balance on the Antarctic plateau as measured with an automatic weather station during 2014

AWS data during 2014 collected at PANDA-N station, on the East Antarctica Plateau, are analysed. Net Short Wave Radiation (QSWR), net Long Wave Radiation (QLWR), sensible (QH), latent (QL) and subsurface or ground (QG) heat fluxes are computed. Annual averages for QSWR, QLWR, QH, QL and QG of 19.65, −49.16, 26.40, −0.77 and 3.86 W·m−2 were derived based on an albedo value of 0.8. QSWR and QH are the major sources of heat gain to the surface and QLWR is the major component of heat loss from the surface. An iterative method is used to estimate surface temperature in this paper; surface temperature of snow/ice is gradually increased or decreased, thereby changing longwave radiation, sensible, latent and subsurface heat fluxes, so that the net energy balance becomes zero. Mass loss due to sublimation at PANDA-N station for 2014 is estimated to be 12.18 mm w.e.·a−1; and mass gain due to water vapour deposition is estimated to be 3.58 mm w.e.·a−1. Thus the net mass loss due to sublimation/deposition is 8.6 mm w.e.·a−1. This study computes surface energy fluxes using a model, instead of direct measurements. Also there are missing data especially for wind speed, though 2 m air temperature data is almost continuously available throughout the year. The uncertainties of albedo, wind speed and turbulent fluxes cause the most probable error in monthly values of QLWR, QH, QL, QG and surface temperature of about ±4%, ±20%, ±50%, ±11% and ±0.74 K respectively

Quantification of a cardiac biomarker in human serum using extraordinary optical transmission (EOT)

10.1371/journal.pone.0120974PLoS ONE103e012097

Variation characteristics of carbon monoxide and ozone over the course of the 2014 Chinese National Arctic Research Expedition

The concentrations of carbon monoxide and ozone in the marine boundary layer were measured during the 6th Chinese National Arctic Research Expedition (from July to September, 2014). Carbon monoxide concentration ranged between 47.00 and 528.52 ppbv with an average of 103.59 ± 40.37 ppbv. A slight decrease with increasing latitude was observed, except for the extremely high values over the East China Sea which may be attributed to anthropogenic emissions. Ozone concentration ranged between 3.27 and 77.82 ppbv with an average of 29.46±10.48 ppbv. Ozone concentration decreased sharply with increasing latitude outside the Arctic Ocean (during both the northward and the southward course), while no significant variation was observed over the Arctic Ocean. The positive correlation between carbon monoxide and ozone in most sections suggests that the ozone in the marine boundary layer mainly originated from photochemical reactions involving carbon monoxide

Spatial variability of δ18O and δ2H in North Pacific and Arctic Oceans surface seawater

This study presents new observations of stable isotopic composition (δ18O, δ2H and deuterium excess) in surface waters of the North Pacific and Arctic Oceans that were collected during the sixth Chinese National Arctic Research Expedition (CHINARE) from mid-summer to early autumn 2014. Seawater δ18O and δ2H decrease with increasing latitudes from 39°N to 75°N, likely a result of spatial variability in evaporation/precipitation processes. This explanation is further confirmed by comparing the δ18O–δ2H relationship of seawater with that of precipitation. However, effects of freshwater inputs on seawater stable isotopic composition are also identified at 30°N–39°N. Furthermore, we find a non-significant relationship between the isotopic parameters (δ2H and δ18О) and salinity from 73°N northwards in the Arctic Ocean, implying that sea ice melting/formation may have some effect. These results suggest that the isotopic parameters δ2H and δ18О are useful for tracing marine hydrological processes

An observational study of precipitation types in the Alaskan Arctic

The effects of various precipitation types, such as snow, rain, sleet, hail and freezing rain, on regional hydrology, ecology, snow and ice surfaces differ significantly. Due to limited observations, however, few studies into precipitation types have been conducted in the Arctic. Based on the high-resolution precipitation records from an OTT Parsivel2 disdrometer in Utqiaġvik, Alaska, this study analysed variations in precipitation types in the Alaskan Arctic from 15 May to 16 October, 2019. Results show that rain and snow were the dominant precipitation types during the measurement period, accounting for 92% of the total precipitation. In addition, freezing rain, sleet, and hail were also observed (2, 4 and 11 times, respectively), accounting for the rest part of the total precipitation. The records from a neighbouring U.S. Climate Reference Network (USCRN) station equipped with T-200B rain gauges support the results of disdrometer. Further analysis revealed that Global Precipitation Measurement (GPM) satellite data could well characterise the observed precipitation changes in Utqiaġvik. Combined with satellite data and station observations, the spatiotemporal variations in precipitation were verified in various reanalysis datasets, and the results indicated that ECMWF Reanalysis v5 (ERA5) could better describe the observed precipitation time series in Utqiaġvik and the spatial distribution of data in the Alaskan Arctic. Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) overestimated the amount and frequency of precipitation. Japanese 55-year Reanalysis (JRA-55) could better simulate heavy precipitation events and the spatial distribution of the precipitation phase, but it overestimated summer snowfall

Climate and meteorological processes of the East Antarctic ice sheet between Zhongshan and Dome-A

The 1228 km over-snow traverse route between the Chinese Zhongshan Station, on the coast of Prydz Bay, and Dome-A, at 4091 m elevation the highest point of the East Antarctic ice sheet, has been the focus of CHINARE surface meteorological and climate studies since 2002. A network of seven Automatic Weather Stations has been deployed along this section, including at Dome-A itself, and some of these have now provided nearly-hourly data for over a decade. Atmospheric boundary layer turbulence and radiation observations have been made over the near-coastal ice sheet inland of Zhongshan and surface turbulence measurements using an ultrasonic anemometer system have also been made in the deep interior of the ice sheet. Summer GPS radiosonde soundings of the atmospheric boundary layer have been made at Kunlun Station, near Dome-A. In this paper these observations are combined to provide a comprehensive overview of the meteorological regime of this region of the ice sheet, its climate variability, and as a reference for future study of climate change. This includes investigation of the variation of surface climate features with elevation and distance from the coast, the height and structure of the boundary layer over the ice sheet, and seasonal and regional changes in ice/snow–air interactions, including turbulent and radiative energy fluxes. The air temperature and snow temperature between the coastal Zhongshan and Dome-A on the inland plateau have not changed significantly in the past decade compared with the inter-annual variability

A comparison of Antarctic ice sheet surface mass balance from atmospheric climate models and in situ observations

In this study, 3265 multiyear averaged in situ observations and 29 observational records at annual time scale are used to examine the performance of recent reanalysis and regional atmospheric climate model products [ERA-Interim, JRA-55, MERRA, the Polar version of MM5 (PMM5), RACMO2.1, and RACMO2.3] for their spatial and interannual variability of Antarctic surface mass balance (SMB), respectively. Simulated precipitation seasonality is also evaluated using three in situ observations and model intercomparison. All products qualitatively capture the macroscale spatial variability of observed SMB, but it is not possible to rank their relative performance because of the sparse observations at coastal regions with an elevation range from 200 to 1000 m. In terms of the absolute amount of observed snow accumulation in interior Antarctica, RACMO2.3 fits best, while the other models either underestimate (JRA-55, MERRA, ERA-Interim, and RACMO2.1) or overestimate (PMM5) the accumulation. Despite underestimated precipitation by the three reanalyses and RACMO2.1, this feature is clearly improved in JRA-55. However, because of changes in the observing system, especially the dramatically increased satellite observations for data assimilation, JRA-55 presents a marked jump in snow accumulation around 1979 and a large increase after the late 1990s. Although precipitation seasonality over the whole ice sheet is common for all products, ERA-Interim provides an unrealistic estimate of precipitation seasonality on the East Antarctic plateau, with high precipitation strongly peaking in summer. ERA-Interim shows a significant correlation with interannual variability of observed snow accumulation measurements at 28 of 29 locations, whereas fewer than 20 site observations significantly correlate with simulations by the other models. This suggests that ERA-Interim exhibits the highest performance of interannual variability in the observed precipitatio

Snow accumulation variability over the West Antarctic Ice Sheet since 1900: a comparison of ice core records with ERA-20C reanalysis

This study uses a set of 37 firn core records over the West Antarctic Ice Sheet (WAIS) to test the performance of ERA-20C reanalysis for snow accumulation and quantify temporal variability in snow accumulation since 1900. The firn cores are allocated to four geographical areas demarcated by drainage divides (i.e., Antarctic Peninsula (AP), western WAIS, central WAIS and eastern WAIS) to calculate stacked records of regional snow accumulation. Our results show that the inter-annual variability in ERA-20C precipitation minus evaporation (P-E) agrees well with the corresponding ice core snow accumulation composites in each of the four geographical regions, suggesting its skill for simulating snow accumulation changes before the modern satellite era (pre-1979). Snow accumulation experiences significantly positive trends for the AP and eastern WAIS, a negative trend for the western WAIS, and no significant trend for the central WAIS from 1900 to 2010. The contrasting trends are associated with changes in the large-scale moisture transport driven by a deepening of the low-pressure systems and anomalies of sea ice in the Amundsen Sea Low (ASL) region