In this study four mesoscale forecasting systems were used to investigate the four-dimensional structure of atmospheric refractivity and ducting layers that occur within evolving synoptic conditions over the eastern seaboard of the United States. The aim of this study was to identify the most important components of forecasting systems that contribute to refractive structures simulated in a littoral environment. Over a 7-day period in April-May of 2000 near Wallops Island, Virginia, meteorological parameters at the ocean surface and within the marine atmospheric boundary layer (MABL) were measured to characterize the spatiotemporal variability contributing to ducting. By using traditional statistical metrics to gauge performance, the models were found to generally overpredict MABL moisture, resulting in fewer and weaker ducts than were diagnosed from vertical profile observations. Mesoscale features in ducting were linked to highly resolved sea surface temperature forcing and associated changes in surface stability and to local variations in internal boundary layers that developed during periods of offshore flow. Sensitivity tests that permit greater mesoscale detail to develop on the model grids revealed that initialization of the simulations and the resolution of sea surface temperature analyses were critical factors for accurate predictions of coastal refractivity.

Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the austral summer months, either due to cloud cover or cloud optical thickness being too low. The problem has been the focus of many studies, most of which utilised satellite datasets for model evaluation. We use multi-year ship based observations and the CERES spaceborne radiation budget measurements to 5 contrast cloud representation and SW radiation in the atmospheric component Global Atmosphere (GA) version 7.0 and 7.1 of the HadGEM3 GCM and the MERRA-2 reanalysis. We find that MERRA-2 is biased in the opposite direction to GA (reflects too much SW radiation). In addition, MERRA-2 performs better in terms of absolute SW bias than nudged runs of GA7.0 and GA7.1 in the 60-70 • S latitude band. GA7.1 reduces the SO SW radiation biases relative to GA7.0, but significant errors remain at up to 20 Wm −2 between 60 and 70 • S in the austral summer months. Using ship-based ceilometer observations, we find low 10 cloud below 2 km to be predominant in the Ross Sea and the Indian Ocean sector of the SO. Utilising a novel surface lidar simulator developed for this study, derived from an existing COSP-ACTSIM spaceborne lidar simulator, we find that GA7.0 and MERRA-2 both underestimate low cloud occurrence relative to the ship observations by 18-25% on average, though the cloud cover in MERRA-2 is closer to observations by about 7%. Based on radiosonde observations, we also find the low cloud to be strongly linked to boundary-layer atmospheric stability and the sea surface temperature. GA7.0 and MERRA-2 agree 15 well with observations in terms of boundary-layer stability, suggesting that subgrid-scale parametrisations do not generate enough cloud in response to the thermodynamic profile of the atmosphere and the surface temperature. Our analysis shows that MERRA-2 has a much greater proportion of cloud liquid water in the SO in January than GA7.0, a likely key contributor to the difference in SW radiation. We show that boundary-layer stability and relative humidity fields are very similar in GA7.0 and Atmos. Chem. Phys. Discuss., https://doi.

Abstract. Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the austral summer months, either due to cloud cover or cloud albedo being too low. The problem has been the focus of many studies, most of which utilised satellite datasets for model evaluation. We use multi-year ship-based observations and the CERES spaceborne radiation budget measurements to contrast cloud representation and SW radiation in the atmospheric component Global Atmosphere (GA) version 7.1 of the HadGEM3 GCM and the MERRA-2 reanalysis. We find that the prevailing bias is negative in GA7.1 and positive in MERRA-2. GA7.1 performs better than MERRA-2 in terms of absolute SW bias. Significant errors of up to 21 W m−2 (GA7.1) and 39 W m−2 (MERRA-2) are present in both models in the austral summer. Using ship-based ceilometer observations, we find low cloud below 2 km to be predominant in the Ross Sea and the Indian Ocean sectors of the SO. Utilising a novel surface lidar simulator developed for this study, derived from an existing Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) – active remote sensing simulator (ACTSIM) spaceborne lidar simulator, we find that GA7.1 and MERRA-2 both underestimate low cloud and fog occurrence relative to the ship observations on average by 4 %–9 % (GA7.1) and 18 % (MERRA-2). Based on radiosonde observations, we also find the low cloud to be strongly linked to boundary layer atmospheric stability and the sea surface temperature. GA7.1 and MERRA-2 do not represent the observed relationship between boundary layer stability and clouds well. We find that MERRA-2 has a much greater proportion of cloud liquid water in the SO in austral summer than GA7.1, a likely key contributor to the difference in the SW radiation bias. Our results suggest that subgrid-scale processes (cloud and boundary layer parameterisations) are responsible for the bias and that in GA7.1 a major part of the SW radiation bias can be explained by cloud cover underestimation, relative to underestimation of cloud albedo.

Iron-deficient erythropoiesis may occur in patients with adequate levels of storage iron as well as those with tissue iron deficiency. Here we compare two methods of detecting iron-deficient erythropoiesis. The measurement of percent hypochromic cells in the full blood count provides a direct indicator of iron-deficient erythropoiesis. The zinc protoporphyrin (ZPP) determination is simple, precise and reproducible, and also appears to provide a sensitive index of iron-deficient erythropoiesis. There was a significant correlation between ZPP levels and percent hypochromic cells in patients with iron deficiency anaemia, rheumatoid arthritis and with patients with renal failure undergoing dialysis and receiving erythropoietin. However in the latter group ZPP levels were raised in almost all patients, suggesting that there may be interference by other metabolites in the assay. This may be overcome by washing the red cells before assay, but the procedure becomes cumbersome. If the laboratory is equipped to determine percent hypochromic cells during the blood count this direct measure of iron-deficient erythropoiesis dispenses with the need to determine ZPP. Otherwise ZPP determinations on washed cells may be of diagnostic use.

The purpose of the Tropical Air–Sea Propagation Study (TAPS), which was conducted during November–December 2013, was to gather coordinated atmospheric and radio frequency (RF) data, offshore of northeastern Australia, in order to address the question of how well radio wave propagation can be predicted in a clear-air, tropical, littoral maritime environment. Spatiotemporal variations in vertical gradients of the conserved thermodynamic variables found in surface layers, mixing layers, and entrainment layers have the potential to bend or refract RF energy in directions that can either enhance or limit the intended function of an RF system. TAPS facilitated the collaboration of scientists and technologists from the United Kingdom, the United States, France, New Zealand, and Australia, bringing together expertise in boundary layer meteorology, mesoscale numerical weather prediction (NWP), and RF propagation. The focus of the study was on investigating for the first time in a tropical, littoral environment the i) refractivity structure in the marine and coastal inland boundary layers; ii) the spatial and temporal behavior of momentum, heat, and moisture fluxes; and iii) the ability of propagation models seeded with refractive index functions derived from blended NWP and surface-layer models to predict the propagation of radio wave signals of ultrahigh frequency (UHF; 300 MHz–3 GHz), super-high frequency (SHF; 3–30 GHz), and extremely high frequency (EHF; 30–300 GHz). Coordinated atmospheric and RF measurements were made using a small research aircraft, slow-ascent radiosondes, lidar, flux towers, a kitesonde, and land-based transmitters. The use of a ship as an RF-receiving platform facilitated variable-range RF links extending to distances of 80 km from the mainland. Four high-resolution NWP forecasting systems were employed to characterize environmental variability. This paper provides an overview of the TAPS experimental design and field campaign, including a description of the unique data that were collected, preliminary findings, and the envisaged interpretation of the results.