Assessment and enhancement of MERRA land surface hydrology estimates

The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979 present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by rerunning a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ECMWF Re-Analysis-Interim (ERA-I). MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 U.S. stations) are comparable and significantly greater than that of MERRA. Throughout the Northern Hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 U.S. basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies

Feature Selection for Interpatient Supervised Heart Beat Classification

Supervised and interpatient classification of heart beats is primordial in many applications requiring long-term monitoring of the cardiac function. Several classification models able to cope with the strong class unbalance and a large variety of feature sets have been proposed for this task. In practice, over 200 features are often considered, and the features retained in the final model are either chosen using domain knowledge or an exhaustive search in the feature sets without evaluating the relevance of each individual feature included in the classifier. As a consequence, the results obtained by these models can be suboptimal and difficult to interpret. In this work, feature selection techniques are considered to extract optimal feature subsets for state-of-the-art ECG classification models. The performances are evaluated on real ambulatory recordings and compared to previously reported feature choices using the same models. Results indicate that a small number of individual features actually serve the classification and that better performances can be achieved by removing useless features

Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System

New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set

The first determination of Generalized Polarizabilities of the proton by a Virtual Compton Scattering experiment

Absolute differential cross sections for the reaction (e+p -> e+p+gamma) have been measured at a four-momentum transfer with virtuality Q^2=0.33 GeV^2 and polarization \epsilon = 0.62 in the range 33.6 to 111.5 MeV/c for the momentum of the outgoing photon in the photon-proton center of mass frame. The experiment has been performed with the high resolution spectrometers at the Mainz Microtron MAMI. From the photon angular distributions, two structure functions which are a linear combination of the generalized polarizabilities have been determined for the first time.Comment: 4 pages, 3 figure

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the Version 2 validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities

Increased frequency of anti-Ma2 encephalitis associated with immune checkpoint inhibitors

Objective To report the induction of anti-Ma2 antibody-associated paraneoplastic neurologic syndrome (Ma2-PNS) in 6 patients after treatment with immune checkpoint inhibitors (ICIs). We also analyzed (1) patient clinical features compared with a cohort of 44 patients who developed Ma2-PNS without receiving ICI treatment and (2) the frequency of neuronal antibody detection before and after ICI implementation. Methods Retrospective nationwide study of all patients with Ma2-PNS developed during ICI treatment between 2017 and 2018. Results Our series of patients included 5 men and 1 woman (median age, 63 years). The patients were receiving nivolumab (n = 3), pembrolizumab (n = 2), or a combination of nivolumab and ipilimumab (n = 1) for treatment of neoplasms that included lung (n = 4) and kidney (n = 1) cancers and pleural mesothelioma (n = 1). Clinical syndromes comprised a combination of limbic encephalitis and diencephalitis (n = 3), isolated limbic encephalitis (n = 2), and a syndrome characterized by ophthalmoplegia and head drop (n = 1). No significant clinical difference was observed between our 6 patients and the overall cohort of Ma2-PNS cases. Post-ICI Ma2-PNS accounted for 35% of the total 17 Ma2-PNS diagnosed in our center over the 2017-2018 biennium. Eight cases had been detected in the preceding biennium 2015-2016, corresponding to a 112% increase of Ma2-PNS frequency since the implementation of ICIs in France. Despite ICI withdrawal and immunotherapy, 4/6 patients died, and the remaining 2 showed a moderate to severe disability. Conclusions We show a clear association between ICI use and increased diagnosis of Ma2-PNS. Physicians need to be aware that ICIs can trigger Ma2-PNS because clinical presentation can be challenging

First measurement of the Gerasimov-Drell-Hearn integral for Hydrogen from 200 to 800 MeV

A direct measurement of the helicity dependence of the total photoabsorption cross section on the proton was carried out at MAMI (Mainz) in the energy range 200 < E_gamma < 800 MeV. The experiment used a 4$\pi$ detection system, a circularly polarized tagged photon beam and a frozen spin target. The contributions to the Gerasimov-Drell-Hearn sum rule and to the forward spin polarizability $\gamma_0$ determined from the data are 226 \pm 5 (stat)\pm 12(sys) \mu b and -187 \pm 8 (stat)\pm 10(sys)10^{-6} fm^4, respectively, for 200 < E_\gamma < 800 MeV.Comment: 6 pages, 3 figures, 3 table