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Introduction: Collateral circulation plays a crucial role in determining the extent of brain tissue ischemia and functional outcome in large vessel occlusive (LVO) stroke. Heart failure (HF) is known to cause cerebral hypoperfusion, yet the relationship between HF and robustness of collateral flow has not been well described. Here we hypothesized that HF is associated with poor collateral flow and functional outcome in patients presenting with LVO treated with mechanical thrombectomy (MT). Methods: A single center retrospective study of patients presenting with LVO ischemic stroke who underwent MT between 2012-2020 was done. Single-phase CTA of head prior to MT was used to assess collateral status with poor status defined as ≤ 50% filling and good status as >50% filling. Classification of HF by left ventricular ejection fraction (LVEF) on echocardiogram was used where HF with reduced ejection fraction (HFrEF) had LVEF ≤40%, HF with preserved EF (HFpEF) had LVEF ≥50% with evidence of structural heart disease, and no HF was LVEF≥50% without structural heart disease. Functional outcome was modified Rankin scale (mRS) at 90 days with scores of 0-2 representing good outcome and 3-6 representing poor outcome. Multivariable logistic regression analyses were performed to evaluate the association between HF and poor collaterals after adjusting for vascular risk factors. Results: We identified 235 patients, mean age was 69 ±15 years, median NIHSS was 18, and 45.5% had HF (HFrEF 12.8%, HFmrEF 4.7%, HFpEF 28.1%) while 54.5% had no HF. Poor collaterals were seen in 47.7%, and those with HF were likely to have poor collaterals compared to those without HF (56.1% vs 35.1%, P=.001). There was a dose-dependent relationship between severity of HF and poor collaterals: adjusted odds of poor collaterals were 1.63 and 2.45 in HFpEF and HFrEF, compared to those without HF (trend p=.018). Patients with poor collaterals were likely to have poor outcome at 3 months compared to those with good collaterals (75.0% vs 57.8%; p=.015). Conclusion: Patients with HFrEF were twice as likely to have poor collaterals. This study demonstrated a likely mechanism for poor outcomes seen in ischemic stroke with HF, future studies may explore whether optimization of HF may augment collaterals to improve outcomes.

This paper reviews the data quality and impact of observations from the FY-3 satellite series used operationally in the ECMWF system. This includes data from the passive microwave radiometers MWHS-1, MWHS-2 and MWRI, as well as observations from the radio occultation receiver GNOS. Evaluations against background equivalents show that the quality of the observations is broadly comparable to that of similar instruments on other polar-orbiting satellites, even though biases for the passive microwave observations can be somewhat larger and more complex for some channels. An observing system experiment shows that the FY-3 instruments jointly contribute significantly to the forecast skill in the ECMWF system. Positive impact of up to 2% is seen for most variables out to the day-2 forecasts over hemispheric scales, with significant benefits for total column water vapor or for temperature and wind in the stratosphere out to day 4.

Cenerimod is a sphingosine-1-phosphate 1 receptor modulator under development for treatment of systemic lupus erythematosus.This single-centre, open-label, single-dose study investigated the mass b...

Atrial fibrillation (AF) and cerebral amyloid angiopathy (CAA) present risks of ischemic stroke and intracerebral hemorrhage (ICH). Vitamin K antagonist use is associated with fluctuations in international normalized ratio (INR), which predispose to a higher bleeding risk. Patients with a diagnosis of AF and ICH while on a vitamin K antagonist were identified using the Rochester Epidemiology Project. Sixty patients were identified (mean age 81.3 years; 24 men). Thirty-three (55%) exhibited characteristics consistent with possible (n = 25) or probable (n = 8) CAA. Mean time in therapeutic range in the 30 days preceding ICH was 55.4%, with no difference between CAA and non-CAA patients. Mean time spent above therapeutic range (INR > 3.0) was 17.7%, with no difference between CAA and non-CAA patients. Following ICH, 21 (35%) died within 30 days, with total mortality at 76.7% after 176.4 person-years of follow-up (mean 2.9 years). Time in therapeutic range in the 30 days prior to ICH had no significant impact on 7-day mortality, nor risk of recurrent ICH or ischemic stroke. Patients with warfarin-related ICH were often outside of the therapeutic range within the month preceding hemorrhage but more frequently were subtherapeutic. Even with careful avoidance of supratherapeutic INR, vitamin K antagonist use in CAA patients is unlikely to have a major effect in preventing ICH and must be used with caution.

In this paper we present L-band data usage for Numerical Weather Prediction applications and Emergency Services at the European Centre for Medium-Range Weather Forecasts (ECMWF).

Radio Frequency Interference (RFI) is a growing threat to all Earth Observation (EO) passive microwave missions. Many RFI detection algorithms are used on-board and in the ground segment data processing, but there is no single algorithm that can detect all RFI instances. The best strategy is always to combine several detection methods. This paper presents the results of the new Ground RFI Detection System (GRDS). The GRDS uses a combination of a wide variety of RFI detection algorithms to clean the Earth Observation measurements from RFI. The system is built to be able to scan for RFI for any EO mission. The initial results show the important reduction on RFI in the EO data as measured by the European Center for Mid-Range Weather Forecast (ECMWF) first guess departure statistics.

International audience

Radio Frequency Interference (RFI) is a serious constraint affecting the Earth Observation (EO) passive microwave missions whose effect has been increasing. There is no single algorithm that can detect all RFI instances. The best strategy always is to combine several detection methods. This paper presents a new system concept: Ground RFI Detection System (GRDS). The GRDS uses a wide variety of RFI detection algorithm to clean the Earth Observation measurements from RFI. The system architecture is modular and it is built to be able to scan for RFI for any EO mission. The initial assessments reported show the potential for this GRDS system.

International audience; This paper presents the forward modelling aspects of the SMOS (Soil Moisture and Ocean Salinity) activities at ECMWF (European Centre for Medium-Range Weather Forecasts). Several parameterizations of the Community Microwave Emission Modelling Platform (CMEM) are used to simulate L-band Brightness Temperatures (TBs) and compared to the SMOS TBs for 2010-2011. We show that simulated TBs are primarily sensitive, by order of importance, to the soil roughness model, the vegetation opacity and the soil dielectric model. In particular, best CMEM results are obtained with the simple Wigneron soil roughness model and the Wigneron model for the vegetation opacity. For the soil dielectric model, performances of the Wang and Schmugge and the Mironov models are shown to be similar and better than the Dobson model. The Wang and Schmugge model is then used in the next steps of this paper combined with the Wigneron roughness and vegetation models. The paper describes a multi-angular multi-polarised bias correction method based on a linear rescaling (mean and variance) computed at the monthly scale using SMOS observations and ECMWF-CMEM re-analysed TBs for a four year period (2010-2013). Results show that for 2010-2013 the seasonal multi-angular multi-polarisation bias correction approach reduces global RMSE to 7.91 K, compared to 16.7 K before bias correction, whereas the mean absolute bias is reduced to 1.39 K, compared to 11.04 K before bias correction. The consistency between the seasonality of simulated and the observed TBs is also improved by using a monthly bias correction, leading to correlation values improvement to 0.62 after bias correction compared to 0.56 before. The 2010-2013 bias correction applied to the 2014-2016 period at 40°incidence reduces the global RMSE from 15.56 K to 8.19 K, and the mean absolute bias from 10.16 K to 2.51 K, with no impact on the correlation values that remain at 0.61 in both cases. Long term monitoring of SMOS TB is presented covering a 7-year period (2010-2016) at both polarisations, at 40°incidence angle. Results show that the consistency between SMOS and ECMWF reanalysis-based TBs progressively improved between 2010 and 2016, pointing out improvements of level 1 SMOS TB products quality through the SMOS lifetime.

This paper presents an evaluation of the quality of data from the MicroWave Humidity Sounder-2, flown on the FY-3C polar orbiting satellite, and first results of trials assimilating the data in all-sky conditions in the European Centre for Medium Range Weather Forecasts’ assimilation system. This instrument combines traditional microwave humidity sounding capabilities at 183 GHz with new channels at 118 GHz, which have never before been available from space. The aim of this paper is twofold: to contribute to the calibration/validation of this satellite by evaluating the data and to test for the first time the impact of assimilating 118-GHz sounding channels in a global numerical weather prediction system. MWHS-2 was first evaluated by comparing observation minus short-range forecast statistics to similar instruments, which indicated that the quality was generally similar. Adding the 118- and 183-GHz channels to the full operational observing system led to small improvements in the short-range (~12 h) forecast accuracy for both sets of channels, and improvements in the 2–4-day wind forecast accuracy for the 183-GHz channels. Short-range forecasts were improved for global humidity in particular when assimilating the 183-GHz channels (0.5% improvement) and for cloud and low-level wind in the Southern Hemisphere extra-tropics when assimilating the 118-GHz channels (by, respectively, 0.5% and 0.2%). In the absence of other atmospheric observations, assimilating the 118-GHz channels improved the global forecast accuracy, but the overall impact was less than for the 183-GHz channels, or for equivalent Advanced Microwave Sounding Unit-A channels.

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Ten years ago, humidity observations were thought to give little benefit to global weather forecasts. Nowadays, at the European Centre for Medium-range Weather Forecasts, satellite microwave radiances sensitive to humidity, cloud and precipitation provide 20% of short-range forecast impact, as measured by adjoint-based forecast sensitivity diagnostics. This makes them one of the most important sources of data and equivalent in impact to microwave temperature sounding observations. Forecasts of dynamical quantities, and precipitation, are improved out to at least day 6. This article reviews the impact of and the science behind these data. It is not straightforward to assimilate cloud and precipitation-affected observations when the intrinsic predictability of cloud and precipitation features is limited. Assimilation systems must be able to operate in the presence of all-pervasive cloud and precipitation ‘mislocation’ errors. However, by assimilating these observations using the ‘all-sky’ approach, and supported by advances in data assimilation and forecast modelling, modern data assimilation systems can infer the dynamical state of the atmosphere, not just from traditional temperature-related observations, but from observations of humidity, cloud and precipitation.

This study aims at improving the assimilation of scatterometer wind observations in global Numerical Weather Prediction (NWP) model by refining the background quality control and optimizing the observation sampling strategy. To improve the background quality control, different Huber Norm distribution implementations are tested and compared against the current “Gaussian plus flat” distribution. Sensitivity experiments show that the usage of the Huber Norm distribution improves the analysis and forecasts. The benefit is mainly seen in the lower model levels in the tropics and extra-tropical Southern Hemisphere. The optimal wind sampling is investigated by testing several combinations of thinning scheme and observation error standard deviation. The impact is demonstrated with a large sample and illustrated by a case study. The case study shows the impact of different settings on the analysis and forecast of a tropical cyclone. A revised wind sampling setting, where four times more observations and a higher observation error than the current operational one are used, showed slightly positive impact on the European Centre for Medium-Range Weather Forecasts (ECMWF) global NWP analyses and forecasts.

International audience; The sea surface temperature (SST), ocean wind speed (OWS), and sea surface salinity (SSS) are fundamental variables for understanding, monitoring, and predicting the state of the ocean and atmosphere. The analysis of these ocean parameters from passive microwave satellite measurements requires a Radiative Transfer Model (RTM). In this study, we compare three ocean RTMs from 1.4 to 89 GHz. A data set of satellite observations from Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer‐2 (AMSR2) collocated with surface and atmospheric parameters from ECMWF ERA‐Interim and Mercator reanalysis has been developed. The selected ocean RTMs are as follows: LOCEAN a physical model with parameters adjusted to L band measurements, FASTEM (FAST microwave Emissivity Model) a fast parameterized model, and RSS (Remote Sensing Systems) an empirical model fitting satellite observations. Global systematic errors between simulations and observations tend to increase with frequency and are generally higher at horizontal than at vertical polarizations. Then, the analysis focuses on the accuracy of the RTMs as a function of the key ocean variables, SST, SSS, and OWS. Major discrepancies are found at frequencies above 1.4 GHz, for OWS higher than 7 m/s, with the LOCEAN and the FASTEM models, with differences strongly increasing with increasing OWS. Cold SSTs are identified as a source of disagreement between the simulations and the observations, regardless of the model. This is a critical issue, especially at 6 GHz, which is the key channel for the SST analysis from satellite. The present study is the first step toward the development of a new physically based community model.

1. This phase-I study (NCT02240290) was designed to investigate the human absorption, disposition and mass balance of 14C-tozadenant, a novel A2a receptor antagonist in clinical development for Parkinson s disease. 2. Six healthy male subjects received a single oral dose of tozadenant (240 mg containing 81.47 KBq of [14C]-tozadenant). Blood, urine and feces were collected over 14 days. Radioactivity was determined by liquid scintillation counting or accelerator mass spectrometry (AMS). Tozadenant and metabolites were characterized using HPLC-MS/MS and HPLC-AMS with fraction collection. 3. At 4 h, the Cmax of tozadenant was 1.74 μg/mL and AUC(0-t) 35.0 h μg/mL, t1/2 15 h, Vz/F 1.82 L/kg and CL/F 1.40 mL/min/kg. For total [14C] radioactivity, the Cmax was 2.29 μg eq/mL at 5 h post-dose and AUC(0-t) 43.9 h μg eq/mL. Unchanged tozadenant amounted to 93% of the radiocarbon AUC(0-48h). At 312 h post-dose, cumulative urinary and fecal excretion of radiocarbon reached 30.5% and 55.1% of the dose, respectively. Unchanged tozadenant reached 11% in urine and 12% of the dose in feces. Tozadenant was excreted as metabolites, including di-and mono-hydroxylated metabolites, N/O dealkylated metabolites, hydrated metabolites. 4. The only identified species circulating in plasma was unchanged tozadenant. Tozadenant was primarily excreted in urine and feces in the form of metabolites.

This paper discusses the role of the observation operator in data assimilation and how the evolving strategy of Numerical Weather Prediction is creating new challenges for Radiative Transfer Model developments, placing an increasing demand on these models and their consistency, bias characterisation and range of capabilities. The paper concludes that to meet future challenges models will need to be developed in a modular style taking elements from many research groups, giving attention to consistency of physical assumptions, interfaces and coding standards.

This paper evaluates uncertainties in the ocean permittivity model needed to compute surface emission and reflection, at frequencies of 6 - 90 GHz. The study transforms permittivities and laboratory measurement uncertainties into typical brightness temperatures for microwave imagers. It is established that the permittivity model used by FASTEM agrees with the laboratory measurements to within their published uncertainties at frequencies of 23 GHz, 37 GHz and 89 GHz, but this is not the case at 6.8, 10.65 and 18.7 GHz, particularly at low temperatures. The laboratory measurement uncertainties transformed into typical brightness temperatures are reported and compared to observation minus short-range forecast (O - B) differences for microwave imagers for a range of ocean surface skin temperatures. For GMI and AMSR-2 these differences show very little skin-temperature dependent bias when calculated using FASTEM. However, when a new version of the permittivity model is used in FASTEM, that fits the low-frequency laboratory data better, an increase in skin temperature dependent bias is observed for channels at 10 - 23 GHz that is larger than the stated measurement uncertainties. This suggests that either the laboratory measurements have additional sources of systematic error at low frequencies, or there are additional sources of bias in the mean O - B calculations for microwave imagers that are currently masked by biases in FASTEM. To resolve this, reference-quality measurements of seawater permittivity are needed at all relevant microwave frequencies and temperatures, particularly at low temperatures and low frequencies.

This paper presents the Soil Moisture and Ocean Salinity (SMOS) mission data assimilation activities conducted at the European Centre for Medium-Range Weather Forecasts (ECMWF) to analyse soil moisture for Numerical Weather Prediction (NWP) applications. Two different approaches are presented based on SMOS brightness temperature and SMOS neural network soil moisture data assimilation, respectively. For the first approach, SMOS brightness temperature data assimilation relies on forward modelling. Long term results, spanning the SMOS period, of SMOS forward modelling, monitoring and data assimilation are presented. They emphasize the relevance of SMOS data for monitoring and to support NWP model developments. For the second approach, a SMOS soil moisture product has been produced based on a Neural Network (NN) trained on ECMWF soil moisture. So, the SMOS-ECMWF NN soil moisture product captures the SMOS signal variability in time and space, while by design its climatology is consistent with that of the ECMWF soil moisture, which makes it suitable for data assimilation purpose. This approach, initially tested for 2012 in a global scale stand alone approach, shows that SMOS NN data assimilation slightly improves the two-metre air temperature forecast in the short range at regional scale. For NWP applications this approach has been further developed with a near real time production of the SMOS-ECMWF NN soil moisture product, with the implementation of the SMOS NN data assimilation in the ECMWF Integrated Forecasting System (IFS), and with high resolution (9km) global scale testing compatible with the current ECMWF NWP system.

This paper assesses the impact of Advanced Microwave Scanning Radiometer-2 (AMSR2) radiances in the all-sky assimilation of the European Centre for Medium-Range Weather Forecasts (ECMWF). Individual impacts of three microwave imagers including AMSR2 were examined by using a baseline experiment that had no microwave imager data. The three microwave imagers brought similar improvements in humidity, temperature, and wind first guess (FG) fields in the troposphere. Improvements were found both in fits to analyses and to other observations. Moreover, significant improvements of wind and geopotential height fields in the troposphere were found in day 3 to day 6 forecasts. AMSR2 made larger improvements than other microwave imagers to geopotential height forecasts in the northern hemisphere. The use of AMSR2 radiance data in addition to the other existing microwave imagers gave mixed results. Consistent improvements in the FG fit to humidity observations were confirmed. However, the FG fit for several channels of the microwave temperature sounding instruments was degraded. The mean FG departure of AMSR2 showed biases that varied according to time of day and meteorological conditions. The causes of the biases were identified as insufficient representation of cloud liquid water path (LWP) in the forecast model under unstable conditions and insufficient amplitude of LWP diurnal variation in stratocumulus areas in the tropics. The assimilation of too much biased data might start to bring negative effects for the analyses and forecasts, which for some parameters could outweigh the improvements in the assimilation. However despite this AMSR2 brought significant improvements of the geopotential height field in the southern hemisphere lower troposphere for day 5 to day 7 forecasts.

Asymmetric features of oceanic brightness temperature from spaceborne microwave imagers in high surface wind speed conditions were investigated with two kinds of collocated data. The first is simultaneous measurements of microwave brightness temperatures and surface wind vectors from the Advanced Microwave Scanning Radiometer (AMSR) and SeaWinds on Advanced Earth Observing Satellite II. The second is microwave brightness temperature observations (AMSR2 and the Special Sensor Microwave Imager Sounder) and surface wind vectors in the European Centre for Medium-Range Weather Forecasts numerical weather prediction model. Both collocated data sets showed that the vertical-polarized and the horizontal-polarized microwave brightness temperature have out-of-phase asymmetric features in terms of relative wind direction (RWD) at high surface wind speeds. Furthermore, different asymmetric features were found for the northern and Southern Hemispheres and for ascending and descending satellite orbits. Although similar asymmetric features can be found in other microwave imager studies, the causes of the asymmetry have not been fully investigated. To investigate the cause of the asymmetry, the observation frequency regarding air–sea temperature difference was examined in upwind, downwind, and crosswind cases. Two important factors contribute to the asymmetry. First, the observations from inclined polar orbit satellites provide different samplings on atmospheric stability in terms of the RWD. Second, the oceanic microwave brightness temperatures have negative correlations with atmospheric stability at high surface wind speeds. The out-of-phase asymmetry is closely related with atmospheric stability, and it appears under a high-surface-wind-speed condition.

Osimertinib is a third-generation, central nervous system-active, epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) selective for EGFR-TKI sensitizing and T790M resistance mutations. This phase 1, open-label study (NCT02491944) investigated absolute bioavailability and pharmacokinetics (PK) of oral and intravenous (IV) osimertinib. Ten healthy subjects (21-61 years) received a single oral 80-mg dose concomitantly with a 100 μg (containing 1 μCi) IV microtracer dose of [14 C]osimertinib. Oral and IV PK were determined simultaneously for osimertinib and its active metabolites, AZ5104 and AZ7550. High-performance liquid chromatography and accelerator mass spectrometry were used to characterize IV dose PK. Geometric mean absolute oral bioavailability of osimertinib was 69.8% (90% confidence interval, 66.7, 72.9). Oral osimertinib was slowly absorbed (median time to maximum plasma concentration [tmax ] 7.0 hours). Following tmax , plasma concentrations fell in an apparent monophasic manner. IV clearance and volume of distribution were 16.8 L/h and 1285 L, respectively. Arithmetic mean elimination half-life estimates were 59.7, 52.6, and 72.6 hours for osimertinib, AZ5104, and AZ7550, respectively (oral dosing), and 54.9, 68.4, and 99.7 hours for [14 C]osimertinib, [14 C]AZ5104, and [14 C]AZ7550, respectively (IV dosing). Oral osimertinib was well absorbed. Simultaneous IV and oral PK analysis proved useful for complete understanding of osimertinib PK and showed that the first-pass effect was minimal for osimertinib.

Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties. The inclusion of stochastic schemes to represent model uncertainties has improved the probabilistic skill of the ECMWF ensemble by increasing reliability and reducing the error of the ensemble mean. Recent progress, challenges and future directions regarding stochastic representations of model uncertainties at ECMWF are described in this paper. The coming years are likely to see a further increase in the use of ensemble methods in forecasts and assimilation. This will put increasing demands on the methods used to perturb the forecast model. An area that is receiving a greater attention than 5 to 10 years ago is the physical consistency of the perturbations. Other areas where future efforts will be directed are the expansion of uncertainty representations to the dynamical core and to other components of the Earth system as well as the overall computational efficiency of representing model uncertainty.

We developed an empirical relative wind direction (RWD) model function to represent azimuthal variations of oceanic microwave radiances of vertical and horizontal polarizations. The RWD model function was based on radiance measurements from the Advanced Microwave Scanning Radiometer and Special Sensor Microwave Imager/Sounder (SSMIS). Ocean surface wind vector data from SeaWinds on board the Advanced Earth Observing Satellite-II and European Centre for Medium-range Weather Forecasts (ECMWF) Integrated Forecasting System were utilized for the RWD model function development. The RWD model function was introduced to a microwave ocean emissivity model: a FAST microwave Emissivity Model (FASTEM) in a radiative transfer model for satellite radiance assimilation. Performances of the RWD model function were much more realistic than present azimuthal model functions in FASTEM for low wind speed and high-frequency channels. Assimilation experiments using the RWD model function were performed in the ECMWF system. The experiment demonstrated reductions of first-guess departure biases arising from modelling of the azimuthal variations in areas of high wind-speed and low variability of wind direction. For example, bias reductions in ascending and descending SSMIS 19 GHz vertically polarized radiance in the Somali jet over the Arabian Sea were approximately 0.6 and 0.7 K. The bias reductions were found for all assimilated microwave imager channels in a wide wind-speed range. Moreover, analysis increments of specific humidity in the lower troposphere were reduced (e.g. 0.2 g kg−1 reduction at 1000 hPa in the Somali jet). We found improvements of relative humidity and temperature in short-range forecasts in the lower troposphere. The experiment results clearly showed the importance of modelling the azimuthal variation of emissivity for assimilation of microwave imager observations. The new RWD model function, combined with the other components of FASTEM, will be available as FASTEM-6.

In this article, a possible way to improve one of the techniques currently used by the numerical weather prediction (NWP) community to assimilate observations from hyperspectral infrared sounders (e.g. the Infrared Atmospheric Sounding Interferometer, IASI) in the presence of clouds is investigated. In particular, attention is focused on increasing the complexity of the cloud radiative model – where clouds are considered as single-layer grey bodies of negligible depth – used by a one-dimensional variational retrieval (1D-Var) cloud analysis that provides cloud parameters used in forward calculations within the global data assimilation system. A new two-layer cloud scheme is tested in the 1D-Var and results are compared with a single layer approach. In the new scheme four cloud-analysis control variables are included and are analysed simultaneously with temperature and humidity profiles. A validation of the new scheme using both simulated and observed IASI radiances shows that the two-layer cloud representation reduces significantly the bias in the mean profiles of retrieved minus background temperature differences, particularly in less homogeneous scenes. However, the bias is still too large to allow useful assimilation of channels below the cloud. Nevertheless, providing a better estimate of cloud position is valuable as it helps to prevent the assimilation of channels sensitive to the atmosphere below the cloud. Furthermore, the statistical analysis of the retrievals from IASI measurements – complemented by the Advanced Very High Resolution Radiometer cluster information – shows that the new scheme is more accurate in more heterogeneous scenes. This suggests that an a priori assessment of the degree of inhomogeneity in a scene may be useful to constrain the data appropriately, leading to a more effective use of cloudy radiances within the global 4D-Var assimilation.

Advances in computer power have made it possible to increase the spatial resolution of regional numerical models to a scale encompassing larger convective elements of less than 5 km in size. One goal of high resolution is to begin to resolve convective processes, and therefore it is necessary to evaluate the realism of convective clouds resolved explicitly at this resolution. This paper presents a method that is based on satellite comparisons to examine the simulation of continental tropical convection over Africa, in a high-resolution integration of the Met Office Unified Model (UK UM), developed under the Cascade project. The spatial resolution of these simulations is 1.5 km, the temporal resolution is 15 min, and the convection is resolved explicitly. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer measurements were simulated by the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV) model, and then a comparison between the simulations and real SEVIRI measurements was performed. The analysis using the presented method shows that the UK UM can represent tropical convection dynamics realistically. However, an error has been found in the high-level humidity distribution, which is characterized by strong humidity gradients. A key point of this paper is to present a method for establishing the credibility of a convection-permitting model by direct comparison with satellite data.

Objective To externally validate currently available bladder cancer nomograms for prediction of all-cause survival (ACS), cancer-specific survival (CSS), other-cause mortality (OCM) and progression-free survival (PFS). Patients and Methods Retrospective analysis of a prospectively maintained database of 282 patients who underwent robot-assisted radical cystectomy (RARC) at a single institution was performed. The Bladder Cancer Research Consortium (BCRC), International Bladder Cancer Nomogram Consortium (IBCNC) and Lughezzani nomograms were used for external validation, and evaluation for accuracy at predicting oncological outcomes. The 2- and 5-year oncological outcomes were compared, and nomogram performance was evaluated through measurement of the concordance (c-index) between nomogram-derived predicted oncological outcomes and observed oncological outcomes. Results The median (range) patient age was 70 (36–90) years. At a mean follow-up of 20 months, local or distant disease recurrence developed in 30% of patients. With an overall mortality rate of 33%, 17% died from bladder cancer. The actuarial 2- and 5-year PFS after RARC was 62% (95% confidence interval [CI] 54–68) and 55% (95% CI 46–63), respectively. The actuarial 2- and 5-year ACS was 66% (95% CI 59–72) and 47% (95% CI 37–55), respectively, and the 2- and 5-year CSS was 81% (95% CI 74–86) and 67% (95% CI 57–76), respectively. The PFS c-index for IBCNC was 0.70 at 5 years, and for BCRC was 0.77 at both the 2 and 5 years. The accuracy of ACS and CSS prediction was evaluated using the BCRC and Lughezzani nomograms. Using the BCRC nomogram, c-indices of for 2- and 5-year ACS were each 0.73 and c-indices for 2- and 5-year CSS were 0.70 each. The performance of Lughezzani nomogram for 5-year ACS, cancer-specific mortality and OCM were 0.73, 0.72 and 0.40, respectively. The BCRC nomogram prediction of advanced pathological stage and lymph node metastasis was modest, with c-indices of 0.66 and 0.61, respectively. Conclusions Bladder cancer nomograms available from the current open RC literature adequately predict ACS, CSS and PFS after RARC. However, prediction of advanced tumour stage and lymph node metastasis was modest and the Lughezzani nomogram failed to predict OCM.

1. This phase-I study (NCT02240290) was designed to investigate the human absorption, disposition and mass balance of

Satellite measurements from microwave instruments have made a significant contribution to the skill of numerical weather forecasting, on both global and regional scales. A FAST microwave Emissivity Model (FASTEM), which was developed by the Met Office, U.K., has been widely utilized to compute the surface emitted radiation in forward calculations. However, the FASTEM model was developed for frequencies in the range of 20-60 GHz, and it is biased at higher and lower frequencies. Several critical components such as variable sea surface salinity and full Stokes vector have not been generally taken into account. In this paper, the effects of the permittivity models are investigated, and a new permittivity model is generated by using the measurements for fresh and salt water at frequencies between 1.4 and 410 GHz. A modified sea surface roughness model from Durden and Vesecky is applied to the detailed two-scale surface emissivity calculations. This ocean emissivity model at microwave is now being used in the Community Radiative Transfer Model, and it has resulted in some major improvements in microwave radiance simulations. This paper is a joint effort of the Met Office, U.K., and the Joint Center for the Satellite Data Assimilation, U.S. The model is called as FASTEM-4 in the Radiative Transfer for TIROS Operational Vertical Sounder model.

The purpose of this paper is to evaluate the potential of a 229-GHz channel as part of a humidity sounder to improve the sounder's cloud-screening capability. The humidity-sounding channels centered around the 183.31-GHz water-vapor line are affected by ice-cloud scattering. Usually, in the operational assimilation of humidity data, the problem of undetected clouds is overcome by setting high observation errors for humidity channels. However, high observation errors diminish the impact of good clear-sky data also, thus, leading to a smaller impact from humidity sounders in weather forecasts. It is expected that a channel at 229 GHz can offer a better cloud-detection capability due to its higher sensitivity to ice scattering compared with the existing channels. Here, a simple cloud-screening method is devised based on the difference between observed and background brightness temperatures. This method was tested for 229 GHz and for an existing channel at 166 GHz, and the results are compared. The new method using 229 GHz is also compared with an existing cloud-screening test, namely, the cirrus-cost test which uses the 183-GHz channels. The study demonstrates that a channel at 229 GHz has a better skill at detecting cirrus clouds which could be interpreted as an error in the background humidity profile. Therefore, addition of a 229-GHz channel can allow more weight to be given to the 183-GHz channels in data assimilation thus significantly increasing their impact on weather forecasting.