126 research outputs found

    Are elevated moist layers a blind spot for hyperspectral infrared sounders? A model study

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    The ability of the hyperspectral satellite-based passive infrared (IR) instrument IASI to resolve elevated moist layers (EMLs) within the free troposphere is investigated. EMLs are strong moisture anomalies with significant impact on the radiative heating rate profile and typically coupled to freezing level detrainment from convective cells in the tropics. A previous case study by indicated inherent deficiencies of passive satellite-based remote sensing instruments in resolving an EML. In this work, we first put the findings of into the context of other retrieval case studies of EML-like structures, showing that such structures can in principle be retrieved, but retrievability depends on the retrieval method and the exact retrieval setup. To approach a first more systematic analysis of EML retrievability, we introduce our own basic optimal estimation (OEM) retrieval, which for the purpose of this study is based on forward-modelled (synthetic) clear-sky observations. By applying the OEM retrieval to the same EML case as , we find that a lack of independent temperature information can significantly deteriorate the humidity retrieval due to a strong temperature inversion at the EML top. However, we show that by employing a wider spectral range of the hyperspectral IR observation, this issue can be avoided and EMLs can generally be resolved. We introduce a new framework for the identification and characterization of moisture anomalies, a subset of which are EMLs, to specifically quantify the retrieval's ability to capture moisture anomalies. The new framework is applied to 1288 synthetic retrievals of tropical ocean short-range forecast model atmospheres, allowing for a direct statistical comparison of moisture anomalies between the retrieval and the reference dataset. With our basic OEM retrieval, we find that retrieved moisture anomalies are on average 17 % weaker and 15 % thicker than their true counterparts. We attribute this to the retrieval smoothing error and the fact that rather weak and narrow moisture anomalies are most frequently missed by the retrieval. Smoothing is found to also constrain the magnitude of local heating rate extremes associated with moisture anomalies, particularly for the strongest anomalies that are found in the lower to mid troposphere. In total, about 80 % of moisture anomalies in the reference dataset are found by the retrieval. Below 5 km altitude, this fraction is only of the order of 52 %. We conclude that the retrieval of lower- to mid-tropospheric moisture anomalies, in particular of EMLs, is possible when the anomaly is sufficiently strong and its thickness is at least of the order of about 1.5 km. This study sets the methodological basis for more comprehensively investigating EMLs based on real hyperspectral IR observations and their operational products in the future

    Temperature-dependence of the clear-sky feedback in radiative-convective equilibrium

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    Abstract We quantify the temperature-dependence of the clear-sky climate sensitivity in a one-dimensional radiative-convective equilibrium model. The atmosphere is adjusted to fixed surface temperatures between 280 and 330 K while preserving other boundary conditions in particular the relative humidity and the CO2 concentration. We show that an out-of-bounds usage of the radiation scheme rapid radiative transfer model for GCMs (RRTMG) can lead to an erroneous decrease of the feedback parameter and an associated ?bump? in climate sensitivity as found in other modeling studies. Using a line-by-line radiative transfer model, we find no evidence for a strengthening of the longwave radiative feedback for surface temperatures between 305 and 320 K. However, the line-by-line simulations also show a slight decrease in climate sensitivity when surface temperatures exceed 310 K. This decrease is caused by water-vapor masking the radiative forcing at the flanks of the CO2 absorption band, which reduces the total radiative forcing by about 18%

    Optically thin clouds in the trades

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    We develop a new method to describe the total cloud cover including optically thin clouds in trade wind cumulus cloud fields. Climate models and large eddy simulations commonly underestimate the cloud cover, while estimates from observations largely disagree on the cloud cover in the trades. Currently, trade wind clouds significantly contribute to the uncertainty in climate sensitivity estimates derived from model perturbation studies. To simulate clouds well, especially how they change in a future climate, we have to know how cloudy it is.In this study we develop a method to quantify the cloud cover from a cloud-free perspective. Using well-known radiative transfer relations we retrieve the cloud-free contribution in high-resolution satellite observations of trade cumulus cloud fields during EUREC4A. Knowing the cloud-free part, we can investigate the remaining cloud-related contributions consisting of areas detected by common cloud-masking algorithms and undetected areas related to optically thin clouds. We find that the cloud-mask cloud cover underestimates the total cloud cover by 33 %. Aircraft lidar measurements support our findings by showing a high abundance of optically thin clouds during EUREC4A. Mixing the undetected optically thin clouds into the cloud-free signal can cause an underestimation of the cloud radiative effect of up to −7.5 %. We further discuss possible artificial correlations in aerosol–cloud cover interaction studies that might arise from undetected optically thin low clouds. Our analysis suggests that the known underestimation of trade wind cloud cover and simultaneous overestimation of cloud brightness in models are even higher than assumed so far

    How adequately are elevated moist layers represented in reanalysis and satellite observations?

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    We assess the representation of elevated moist layers (EMLs) in ERA5 reanalysis, the Infrared Atmospheric Sounding Interferometer (IASI) L2 retrieval Climate Data Record (CDR) and the Atmospheric Infrared Sounder (AIRS)-based Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)-Aqua L2 retrieval. EMLs are free-tropospheric moisture anomalies that typically occur in the vicinity of deep convection in the tropics. EMLs significantly affect the spatial structure of radiative heating, which is considered a key driver for meso-scale dynamics, in particular convective aggregation. To our knowledge, the representation of EMLs in the mentioned data products has not been explicitly studied – a gap we start to address in this work. We assess the different datasets' capability of capturing EMLs by collocating them with 2146 radiosondes launched from Manus Island within the western Pacific warm pool, a region where EMLs occur particularly often. We identify and characterise moisture anomalies in the collocated datasets in terms of moisture anomaly strength, vertical thickness and altitude. By comparing the distributions of these characteristics, we deduce what specific EML characteristics the datasets are capturing well and what they are missing. Distributions of ERA5 moisture anomaly characteristics match those of the radiosonde dataset quite well, and remaining biases can be removed by applying a 1 km moving average to the radiosonde profiles. We conclude that ERA5 is a suitable reference dataset for investigating EMLs. We find that the IASI L2 CDR is subject to stronger smoothing than ERA5, with moisture anomalies being on average 13 % weaker and 28 % thicker than collocated ERA5 anomalies. The CLIMCAPS L2 product shows significant biases in its mean vertical humidity structure compared to the other investigated datasets. These biases manifest as an underestimation of mean moist layer height of about 1.3 km compared to the three other datasets that yields a general mid-tropospheric moist bias and an upper-tropospheric dry bias. Aside from these biases, the CLIMCAPS L2 product shows a similar, if not better, capability of capturing EMLs compared to the IASI L2 CDR. More nuanced evaluations of CLIMCAPS' capabilities may be possible once the underlying cause for the identified biases has been found and fixed. Biases found in the all-sky scenes do not change significantly when limiting the analysis to clear-sky scenes. We calculate radiatively driven vertical velocities ωrad derived from longwave heating rates to estimate the dynamical effect of the moist layers. Moist-layer-associated ωrad values derived from Global Climate Observing System Reference Upper-Air Network (GRUAN) soundings range between 2 and 3 hPa h−1, while mean meso-scale pressure velocities from the EUREC4A (Elucidating the Role of Clouds-Circulation Coupling in Climate) field campaign range between 1 and 2 hPa h−1, highlighting the dynamical significance of EMLs. Subtle differences in the representation of moisture and temperature structures in ERA5 and the satellite datasets create large relative errors in ωrad on the order of 40 % to 80 % with reference to GRUAN, indicating limited usefulness of these datasets to assess the dynamical impact of EMLs.</p

    A New Halocarbon Absorption Model Based on HITRAN Cross-Section Data and New Estimates of Halocarbon Instantaneous Clear-Sky Radiative Forcing

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    The article describes a new practical model for the infrared absorption of chlorofluorocarbons and other gases with dense spectra, based on high-resolution transmission molecular absorption database (HITRAN) absorption cross-sections. The model is very simple, consisting of frequency-dependent polynomial coefficients describing the pressure and temperature dependence of absorption. Currently it is implemented for the halocarbon species required by the Radiative Forcing Model Intercomparison Project. In cases where cross-section data is available at a range of different temperatures and pressures, this approach offers practical advantages compared to previously available options, and is traceable, since the polynomial coefficients follow directly from the laboratory spectra. The new model is freely available and has several important applications, notably in remote sensing and in developing advanced radiation schemes for global circulation models that include halocarbon absorption. For demonstration, the model is applied to the problem of computing instantaneous clear-sky halocarbon radiative efficiencies and present day radiative forcing. Results are in reasonable agreement with earlier assessments that were carried out with the less explicit Pinnock method, and thus broadly validate that method. Plain Language Summary Chlorofluorocarbons and other related gases have dense and complicated absorption spectra that can be measured in the laboratory. We bring such measurements to a form that can be used for simulations of the transfer of radiation through the atmosphere. Then we use the new model to calculate new estimates of the climate impact of these man-made gases. The results broadly validate earlier calculations that were done with a less explicit method

    A general database of hydrometeor single scattering properties at microwave and sub-millimetre wavelengths

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    A main limitation today in simulations and inversions of microwave observations of ice hydrometeors (cloud ice, snow, hail, etc.) is the lack of data describing the interaction between electromagnetic waves and the particles. To improve the situation, the development of a comprehensive dataset of such scattering properties has been started. The database aims at giving a broad coverage in both frequency (1 to 886 GHz) and temperature (190 to 270 K), to support both passive and active current and planned measurements, and to provide data corresponding to the full Stokes vector. This first version of the database is restricted to totally random particle orientation. Data for 34 particle sets, i.e. habits, have been generated. About 17 of the habits can be classified as single crystals, three habits can be seen as heavily rimed particles, and the remaining habits are aggregates of different types, e.g. snow and hail. The particle sizes considered vary between the habits, but maximum diameters of 10 and 20 mm are typical values for the largest single crystal and aggregate particles, respectively, and the number of sizes per habit is at least 30. Particles containing liquid water are also inside the scope of the database, but this phase of water is so far only represented by a liquid sphere habit. The database is built upon the netCDF4 file format. Interfaces to browse, extract and convert data for selected radiative transfer models are provided in MATLAB and Python. The database and associated tools are publicly available from Zenodo (https://doi.org/10.5281/zenodo.1175572, Ekelund et al., 2018b), and https://doi.org/10.5281/zenodo.1175588, Mendrok et al., 2018, respectively). Planned extensions include non-spherical raindrops, melting particles and a second orientation case that can be denoted as azimuthally random

    Protein loop compaction and the origin of the effect of arginine and glutamic acid mixtures on solubility, stability and transient oligomerization of proteins

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    Addition of a 50 mM mixture of l-arginine and l-glutamic acid (RE) is extensively used to improve protein solubility and stability, although the origin of the effect is not well understood. We present Small Angle X-ray Scattering (SAXS) and Nuclear Magnetic Resonance (NMR) results showing that RE induces protein compaction by collapsing flexible loops on the protein core. This is suggested to be a general mechanism preventing aggregation and improving resistance to proteases and to originate from the polyelectrolyte nature of RE. Molecular polyelectrolyte mixtures are expected to display long range correlation effects according to dressed interaction site theory. We hypothesize that perturbation of the RE solution by dissolved proteins is proportional to the volume occupied by the protein. As a consequence, loop collapse, minimizing the effective protein volume, is favored in the presence of RE

    Electrical Components for Marine Renewable Energy Arrays: A Techno-Economic Review

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    This paper presents a review of the main electrical components that are expected to be present in marine renewable energy arrays. The review is put in context by appraising the current needs of the industry and identifying the key components required in both device and array-scale developments. For each component, electrical, mechanical and cost considerations are discussed; with quantitative data collected during the review made freely available for use by the community via an open access online repository. This data collection updates previous research and addresses gaps specific to emerging offshore technologies, such as marine and floating wind, and provides a comprehensive resource for the techno-economic assessment of offshore energy arrays

    Radiative Flux and Forcing Parameterization Error in Aerosol-Free Clear Skies

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    This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentially unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. A dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations

    Perspectives of Patients with Insulin-Treated Type 1 and Type 2 Diabetes on Hypoglycemia: Results of the HAT Observational Study in Central and Eastern European Countries

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    INTRODUCTION: The aim of this study was to determine the level of awareness of hypoglycemia, the level of fear for hypoglycemia, and the response to hypoglycemic events among insulin-treated diabetes patients from Central and Eastern Europe (CEE). The impact of hypoglycemia on the use of healthcare resources and patient productivity was also assessed. METHODS: This was a multicenter, non-interventional, two-part, patient self-reported questionnaire study that comprised both a retrospective cross-sectional evaluation and a prospective observational evaluation. Study participants were insulin-treated adult patients with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) from CEE. RESULTS: Most patients (85.4% T1DM and 83.6% T2DM) reported normal hypoglycemia awareness. The median hypoglycemia fear score was 5 out of 10 for T1DM and 4 out of 10 for T2DM patients. Patients increased glucose monitoring, consulted a doctor/nurse, and/or reduced the insulin dose in response to hypoglycemia. As a consequence of hypoglycemia, patients took leave from work/studies or arrived late and/or left early. Hospitalization was required for 31 (1.2%) patients with T1DM and 66 (2.1%) patients with T2DM. CONCLUSION: Hypoglycemia impacts patients' personal and social functioning, reduces productivity, and results in additional costs, both direct (related to increased use of healthcare resources) and indirect (related to absenteeism. FUNDING: Novo Nordisk
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