Exploiting existing ground-based remote sensing networks to improve high-resolution weather forecasts

A new generation of high-resolution (1 km) forecast models promises to revolutionize the prediction of hazardous weather such as windstorms, flash floods, and poor air quality. To realize this promise, a dense observing network, focusing on the lower few kilometers of the atmosphere, is required to verify these new forecast models with the ultimate goal of assimilating the data. At present there are insufficient systematic observations of the vertical profiles of water vapor, temperature, wind, and aerosols; a major constraint is the absence of funding to install new networks. A recent research program financed by the European Union, tasked with addressing this lack of observations, demonstrated that the assimilation of observations from an existing wind profiler network reduces forecast errors, provided that the individual instruments are strategically located and properly maintained. Additionally, it identified three further existing European networks of instruments that are currently underexploited, but with minimal expense they could deliver quality-controlled data to national weather services in near–real time, so the data could be assimilated into forecast models. Specifically, 1) several hundred automatic lidars and ceilometers can provide backscatter profiles associated with aerosol and cloud properties and structures with 30-m vertical resolution every minute; 2) more than 20 Doppler lidars, a fairly new technology, can measure vertical and horizontal winds in the lower atmosphere with a vertical resolution of 30 m every 5 min; and 3) about 30 microwave profilers can estimate profiles of temperature and humidity in the lower few kilometers every 10 min. Examples of potential benefits from these instruments are presented

G band atmospheric radars: new frontiers in cloud physics

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow

How can existing ground-based profiling instruments improve European weather forecasts?

Observations of profiles of winds, aerosol, clouds, winds, temperature and humidity in the lowest few km of the atmosphere from networks of ceilometers, Doppler wind lidars and microwave radiometers are starting to flow in real time to forecasting centers in Europe. To realise the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few km are hardly accessible by satellite, especially in dynamically-active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real-time to forecast centers. The three classes of instruments are: (i) Automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog and volcanic ash, the last two being especially important for air traffic control; (ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind-gusts and low-level jets; and (iii) Microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. Twenty-two European countries and fifteen European National Weather Services are collaborating in the project, that involves the implementation of common operating procedures, instrument calibrations, data formats and retrieval algorithms. Currently, data from 220 ceilometers in 17 countries are being distributed in near real-time to national weather forecast centers; this should soon rise to many hundreds. The wind lidars should start delivering real time data in late 2018, and the plan is to incorporate the microwave radiometers in 2019. Initial data assimilation tests indicate a positive impact of the new data

First-line fadrozole HCI (CGS 16949A) versus tamoxifen in postmenopausal women with advanced breast cancer: Prospective randomised trial of the Swiss Group for Clinical Cancer Research SAKK 20/88

Background: In a phase III randomized trial, we compared the effectiveness and tolerability of fadrozole (CGS 16949A), a non-steroidal aromatase inhibitor, to tamoxifen as first-line endocrine therapy in postmenopausal women with advanced breast cancer. Patients and methods: Two hundred twelve eligible patients were randomized to receive tamoxifen 20 mg daily, or fadrozole 1 mg twice daily orally until disease progression or the advent of undue toxicity. The treatments were to be discontinued upon disease progression. Results: Prognostic factors were well balanced between the treatment groups, except for sites of metastatic disease. Fadrozole-treated patients had significantly more visceral, especially liver, involvement and less bone-dominant disease. Response rates for fadrozole and tamoxifen were similar, 20% and 27% (95% Confidence Limits (CL): 13%-29% and 21%-35%), respectively. Time to treatment failure was longer in patients randomized to tamoxifen (8.5 months for tamoxifen vs. 6.1 months for fadrozole), but did not reach statistical significance after adjustment for prognostic factors (P=0.09). Fadrozole, for which a significantly lower percentage of clinically relevant toxic effects (WHO toxicity gradeij2) was recorded (27% vs. 13% respectively; P=0.009), was better tolerated than tamoxifen. Severe cardiovascular events including 3 fatalities were seen only in patients treated with tamoxifen. Eighty-two patients crossed over to tamoxifen and 66 patients to fadrozole. Crossover endocrine therapy led to response or stable disease in 64% of the patients. The overall survival times of the two treatment groups were similar. Conclusions: Fadrozole and tamoxifen showed similar efficacy as first-line treatments in postmenopausal patients with advanced breast cancer. Fadrozole was significantly better tolerated and may therefore be an appropriate alternative to tamoxifen, especially for patients predisposed to thromboembolic event

Long-term observations minus background monitoring of ground-based brightness temperatures from a microwave radiometer network

Abstract. Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal-resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g. variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O–B). Monitoring of O–B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O–B analysis for MWR observations in clear-sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective-scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O–B monitoring can effectively detect instrument malfunctions. O–B statistics (bias, standard deviation, and root mean square) for water vapour channels (22.24–30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line centre ( ∼  2–2.5 K) towards the high-frequency wing ( ∼  0.8–1.3 K). Statistics for zenith and lower-elevation observations show a similar trend, though values increase with increasing air mass. O–B statistics for temperature channels show different behaviour for relatively transparent (51–53 GHz) and opaque channels (54–58 GHz). Opaque channels show lower uncertainties (< 0.8–0.9 K) and little variation with elevation angle. Transparent channels show larger biases ( ∼  2–3 K) with relatively low standard deviations ( ∼  1–1.5 K). The observations minus analysis TB statistics are similar to the O–B statistics, suggesting a possible improvement to be expected by assimilating MWR TB into NWP models. Lastly, the O–B TB differences have been evaluated to verify the normal-distribution hypothesis underlying variational and ensemble Kalman filter-based DA systems. Absolute values of excess kurtosis and skewness are generally within 1 and 0.5, respectively, for all instrumental sites, demonstrating O–B normal distribution for most of the channels and elevations angles

JOYCE: Jülich Observatory for cloud evolution

The Jülich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Jülich in the most western part of Germany, is a recently established platform for cloud research. The main objective of JOYCE is to provide observations, which improve our understanding of the cloudy boundary layer in a midlatitude environment. Continuous and temporally highly resolved measurements that are specifically suited to characterize the diurnal cycle of water vapor, stability, and turbulence in the lower troposphere are performed with a special focus on atmosphere–surface interaction. In addition, instruments are set up to measure the micro- and macrophysical properties of clouds in detail and how they interact with different boundary layer processes and the large-scale synoptic situation. For this, JOYCE is equipped with an array of state-of-the-art active and passive remote sensing and in situ instruments, which are briefly described in this scientific overview. As an example, a 24-h time series of the evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead