3DVAR assimilation of SSM/I data over the sea for the IOP2b MAP case

International audienceData assimilation by 3DVAR of data from the Special Sensor Microwave/Imager (SSM/I) has been performed to study the IOP2b case (19-21 September 1999) of the Mesoscale Alpine Programme (MAP). Only data over the sea surface are used to avoid the contamination of the surface emissivity. Moreover, the rainy data are filtered out because the assimilation algorithm of 3DVAR does not take into account the scattering processes. SSM/I data are assimilated in two different ways: as Brightness Temperature directly, or as Precipitable Water and surface wind speed retrieved from the Brightness Temperature. The effect of the thinning of the observations has been studied and a set of sensitivity test cases has been carried out; the one by one removal of the SSM/I frequencies from the initial dataset allows to evaluate their impact on the Initial Conditions. A few experiments are performed using these new Initial Conditions to initialize the MM5 (PSU/NCAR) model. The results show that the assimilation of the retrieved quantities, i.e. Precipitable Water and surface wind speed, does not produces large improvement in the Initial Conditions. Vice versa, the assimilation of the Brightness temperatures produces a large variability of the Initial Conditions. The forecast experiments show that the model is very sensitive to the 22GHz and 37GHz frequencies

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

Network Sensitivity of Systemic Risk

A growing body of studies on systemic risk in financial markets has emphasized the key importance of taking into consideration the complex interconnections among financial institutions. Much effort has been put in modeling the contagion dynamics of financial shocks, and to assess the resilience of specific financial markets - either using real network data, reconstruction techniques or simple toy networks. Here we address the more general problem of how shock propagation dynamics depends on the topological details of the underlying network. To this end we consider different realistic network topologies, all consistent with balance sheets information obtained from real data on financial institutions. In particular, we consider networks of varying density and with different block structures, and diversify as well in the details of the shock propagation dynamics. We confirm that the systemic risk properties of a financial network are extremely sensitive to its network features. Our results can aid in the design of regulatory policies to improve the robustness of financial markets

Heterogeneity, quality, and reputation in an adaptive recommendation model

Abstract.: Recommender systems help people cope with the problem of information overload. A recently proposed adaptive news recommender model [M. Medo, Y.-C. Zhang, T. Zhou, Europhys. Lett. 88, 38005 (2009)] is based on epidemic-like spreading of news in a social network. By means of agent-based simulations we study a "good get richer” feature of the model and determine which attributes are necessary for a user to play a leading role in the network. We further investigate the filtering efficiency of the model as well as its robustness against malicious and spamming behaviour. We show that incorporating user reputation in the recommendation process can substantially improve the outcom

Emergence of scale-free leadership structure in social recommender systems

The study of the organization of social networks is important for understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems

Assessing the volcanic hazard for Rome. 40Ar/39Ar and In-SAR constraints on the most recent eruptive activity and present-day uplift at Colli Albani Volcanic District

We present new 40Ar/39Ar data which allow us to refine the recurrence time for the most recent eruptive activity occurred at Colli Albani Volcanic District (CAVD) and constrain its geographic area. Time elapsed since the last eruption (36 kyr) overruns the recurrence time (31 kyr) in the last 100 kyr. New interferometric synthetic aperture radar data, covering the years 1993–2010, reveal ongoing inflation with maximum uplift rates (>2 mm/yr) in the area hosting the most recent (<200 ka) vents, suggesting that the observed uplift might be caused by magma injection within the youngest plumbing system. Finally, we frame the present deformation within the structural pattern of the area of Rome, characterized by 50 m of regional uplift since 200 ka and by geologic evidence for a recent (<2000 years) switch of the local stress-field, highlighting that the precursors of a new phase of volcanic activity are likely occurring at the CAVD

Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale

International audienceThe Microwave Infrared Combined Rainfall Algorithm (MICRA) consists in a statistical integration method using the satellite microwave-based rain-rate estimates, assumed to be accurate enough, to calibrate spaceborne infrared measurements on limited sub-regions and time windows. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The actual implementation is explained, although the basic concepts of MICRA are very general and the method is easy to be extended for considering innovative statistical techniques or measurements from additional space-borne platforms. In order to demonstrate the potentiality of MICRA, case studies over central Italy are also discussed. Finally, preliminary results of MICRA validation by ground based remote and in situ measurements are shown and a comparison with a Neural Network (NN) based technique is briefly illustrated

Calcium/calmodulin-dependent kinases can regulate the TSH expression in the rat pituitary.

PURPOSE: The endocrine secretion of TSH is a finely orchestrated process controlled by the thyrotropin-releasing hormone (TRH). Its homeostasis and signaling rely on many calcium-binding proteins belonging to the "EF-hand" protein family. The Ca2+/calmodulin (CaM) complex is associated with Ca2+/CaM-dependent kinases (Ca2+/CaMK). We have investigated Ca2+/CaMK expression and regulation in the rat pituitary. METHODS: The expression of CaMKII and CaMKIV in rat anterior pituitary cells was shown by immunohistochemistry. Cultured anterior pituitary cells were stimulated by TRH in the presence and absence of KN93, the pharmacological inhibitor of CaMKII and CaMKIV. Western blotting was then used to measure the expression of these kinases and of the cAMP response element-binding protein (CREB). TSH production was measured by RIA after time-dependent stimulation with TRH. Cells were infected with a lentiviral construct coding for CaMKIV followed by measurement of CREB phosphorylation and TSH. RESULTS: Our study shows that two CaM kinases, CaMKII and CaMKII, are expressed in rat pituitary cells and their phosphorylation in response to TRH occurs at different time points, with CaMKIV being activated earlier than CaMKII. TRH induces CREB phosphorylation through the activity of both CaMKII and CaMKIV. The activation of CREB increases TSH gene expression. CaMKIV induces CREB phosphorylation while its dominant negative and KN93 exert the opposite effects. CONCLUSION: Our data indicate that the expression of Ca2+/CaMK in rat anterior pituitary are correlated to the role of CREB in the genetic regulation of TSH, and that TRH stimulation activates CaMKIV, which in turn phosphorylates CREB. This phosphorylation is linked to the production of thyrotropin

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