66 research outputs found
What can we learn from the cloudsat radiometric mode observations of snowfall over the ice-free ocean?
The quantification of global snowfall by the current observing system remains challenging, with the CloudSat 94 GHz Cloud Profiling Radar (CPR) providing the current state-of-the-art snow climatology, especially at high latitudes. This work explores the potential of the novel Level-2 CloudSat 94 GHz Brightness Temperature Product (2B-TB94), developed in recent years by processing the noise floor data contained in the 1B-CPR product; the focus of the study is on the characterization of snow systems over the ice-free ocean, which has well constrained emissivity and backscattering properties. When used in combination with the path integrated attenuation (PIA), the radiometric mode can provide crucial information on the presence/amount of supercooled layers and on the contribution of the ice to the total attenuation. Radiative transfer simulations show that the location of the supercooled layers and the snow density are important factors affecting the warming caused by supercooled emission and the cooling induced by ice scattering. Over the ice-free ocean, the inclusion of the 2B-TB94 observations to the standard CPR observables (reflectivity profile and PIA) is recommended, should more sophisticated attenuation corrections be implemented in the snow CloudSat product to mitigate its well-known underestimation at large snowfall rates. Similar approaches will also be applicable to the upcoming EarthCARE mission. The findings of this paper are relevant for the design of future missions targeting precipitation in the polar regions
Impact of ASAR soil moisture data on the MM5 precipitation forecast for the Tanaro flood event of April 2009
The representation of land-atmosphere interactions in weather forecast models has a strong impact on the Planetary Boundary Layer (PBL) and, in turn, on the forecast. Soil moisture is one of the key variables in land surface modelling, and an inadequate initial soil moisture field can introduce major biases in the surface heat and moisture fluxes and have a long-lasting effect on the model behaviour. Detecting the variability of soil characteristics at small scales is particularly important in mesoscale models because of the continued increase of their spatial resolution. In this paper, the high resolution soil moisture field derived from ENVISAT/ASAR observations is used to derive the soil moisture initial condition for the MM5 simulation of the Tanaro flood event of April 2009. The ASAR-derived soil moisture field shows significantly drier conditions compared to the ECMWF analysis. The impact of soil moisture on the forecast has been evaluated in terms of predicted precipitation and rain gauge data available for this event have been used as ground truth. The use of the drier, highly resolved soil moisture content (SMC) shows a significant impact on the precipitation forecast, particularly evident during the early phase of the event. The timing of the onset of the precipitation, as well as the intensity of rainfall and the location of rain/no rain areas, are better predicted. The overall accuracy of the forecast using ASAR SMC data is significantly increased during the first 30 h of simulation. The impact of initial SMC on the precipitation has been related to the change in the water vapour field in the PBL prior to the onset of the precipitation, due to surface evaporation. This study represents a first attempt to establish whether high resolution SAR-based SMC data might be useful for operational use, in anticipation of the launch of the Sentinel-1 satellite
Impact of ASAR soil moisture data on the MM5 precipitation forecast for the Tanaro flood event of April 2009
Abstract. The representation of land-atmosphere interactions in weather forecast models has a strong impact on the Planetary Boundary Layer (PBL) and, in turn, on the forecast. Soil moisture is one of the key variables in land surface modelling, and an inadequate initial soil moisture field can introduce major biases in the surface heat and moisture fluxes and have a long-lasting effect on the model behaviour. Detecting the variability of soil characteristics at small scales is particularly important in mesoscale models because of the continued increase of their spatial resolution. In this paper, the high resolution soil moisture field derived from ENVISAT/ASAR observations is used to derive the soil moisture initial condition for the MM5 simulation of the Tanaro flood event of April 2009. The ASAR-derived soil moisture field shows significantly drier conditions compared to the ECMWF analysis. The impact of soil moisture on the forecast has been evaluated in terms of predicted precipitation and rain gauge data available for this event have been used as ground truth. The use of the drier, highly resolved soil moisture content (SMC) shows a significant impact on the precipitation forecast, particularly evident during the early phase of the event. The timing of the onset of the precipitation, as well as the intensity of rainfall and the location of rain/no rain areas, are better predicted. The overall accuracy of the forecast using ASAR SMC data is significantly increased during the first 30 h of simulation. The impact of initial SMC on the precipitation has been related to the change in the water vapour field in the PBL prior to the onset of the precipitation, due to surface evaporation. This study represents a first attempt to establish whether high resolution SAR-based SMC data might be useful for operational use, in anticipation of the launch of the Sentinel-1 satellite
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for snowfall retrieval at high latitudes
The High lAtitude sNow Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS) is a new machine-learning (ML)-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder (ATMS) observations that has been developed specifically to detect and quantify high-latitude snowfall events that often form in cold, dry environments and produce light snowfall rates. ATMS and the future European MetOp-SG Microwave Sounder offer good high-latitude coverage and sufficient microwave channel diversity (23 to 190 GHz), which allows surface radiometric properties to be dynamically characterized and the non-linear and sometimes subtle passive microwave response to falling snow to be detected. HANDEL-ATMS is based on a combined active–passive microwave observational dataset in the training phase, where each ATMS multichannel observation is associated with coincident (in time and space) CloudSat Cloud Profiling Radar (CPR) vertical snow profiles and surface snowfall rates. The main novelty of the approach is the radiometric characterization of the background surface (including snow-covered land and sea ice) at the time of the overpass to derive the multichannel surface emissivities and clear-sky contribution to be used in the snowfall retrieval process. The snowfall retrieval is based on four different artificial neural networks (ANNs) for snow water path (SWP) and surface snowfall rate (SSR) detection and estimate. HANDEL-ATMS shows very good detection capabilities, POD = 0.83, FAR = 0.18, and HSS = 0.68, for the SSR detection module. Estimation error statistics show a good agreement with CPR snowfall products for SSR >10-2 mm h−1 (RMSE = 0.08 mm h−1, bias = 0.02 mm h−1). The analysis of the results for an independent CPR dataset and of selected snowfall events is evidence of the unique capability of HANDEL-ATMS to detect and estimate SWP and SSR also in the presence of extremely cold and dry environmental conditions typical of high latitudes.</p
A Multisensor Investigation of Convection During HyMeX SOP1 IOP13
A multisensor analysis of the convective precipitation event occurred over Rome during the IOP13 (October 15th, 2012) of the HyMeX (Hydrological cycle in the Mediterranean eXperiment) Special Observation Period (SOP) 1 is presented. Thanks to the cooperation among Italian meteorological services and scientific community and a specific agreement with NASA-GSFC, different types of devices for meteorological measurements were made available during the HyMeX SOP.1. For investigating this event, used are the 3-D lightning data provided by the LINET, the CNR ISAC dual-pol C-band radar (Polar 55C), located in Rome, the Drop Size Distributions (DSD) collected by the 2D Video Disdrometer (2DVD) and the collocated Micro Rain Radar (MRR) installed at the Radio Meteorology Lab. of "Sapienza" University of Rome, located 14 km from the Polar 55C radar. The relation between microphysical structure and electrical activity during the convective phase of the event was investigated using LINET lightning data and Polar 55C (working both in PPI and RHI scanning mode) observations. Location of regions of high horizontal reflectivity (Zh) values ( > 50 dBz), indicating convective precipitation, were found to be associated to a high number of LINET strokes. In addition, an hydrometeor classification scheme applied to the Polar 55C scans was used to detect graupel and to identify a relation between number of LINET strokes and integrated IWC of graupel along the event. Properties of DSDs measured by the 2DVD and vertical DSD profiles estimated by MRR and their relation with the lighting activity registered by LINET were investigated with specific focus on the transition from convective to stratiform regimes. A good agreement was found between convection detected by these instruments and the number of strokes detected by LINET
Multi-sensor analysis of convective activity in central Italy during the HyMeX SOP 1.1
Abstract. A multi-sensor analysis of convective precipitation events that occurred in central Italy in autumn 2012 during the HyMeX (Hydrological cycle in the Mediterranean experiment) Special Observation Period (SOP) 1.1 is presented. Various microphysical properties of liquid and solid hydrometeors are examined to assess their relationship with lightning activity. The instrumentation used consisted of a C-band dual-polarization weather radar, a 2-D video disdrometer, and the LINET lightning network. Results of T-matrix simulation for graupel were used to (i) tune a fuzzy logic hydrometeor classification algorithm based on Liu and Chandrasekar (2000) for the detection of graupel from C-band dual-polarization radar measurements and (ii) to retrieve graupel ice water content. Graupel mass from radar measurements was related to lightning activity. Three significant case studies were analyzed and linear relations between the total mass of graupel and number of LINET strokes were found with different slopes depending on the nature of the convective event (such as updraft strength and freezing level height) and the radar observational geometry. A high coefficient of determination (R2 = 0.856) and a slope in agreement with satellite measurements and model results for one of the case studies (15 October 2012) were found. Results confirm that one of the key features in the electrical charging of convective clouds is the ice content, although it is not the only one. Parameters of the gamma raindrop size distribution measured by a 2-D video disdrometer revealed the transition from a convective to a stratiform regime. The raindrop size spectra measured by a 2-D video disdrometer were used to partition rain into stratiform and convective classes. These results are further analyzed in relation to radar measurements and to the number of strokes. Lightning activity was not always recorded when the precipitation regime was classified as convective rain. High statistical scores were found for relationships relating lightning activity to graupel aloft
Perspectives on metaphyseal conservative stems
Total hip replacement is showing, during the last decades, a progressive evolution toward principles of reduced bone and soft tissue aggression. These principles have become the basis of a new philosophy, tissue sparing surgery. Regarding hip implants, new conservative components have been proposed and developed as an alternative to conventional stems. Technical and biomechanical characteristics of metaphyseal bone-stock-preserving stems are analyzed on the basis of the available literature and our personal experience. Mayo, Nanos and Metha stems represent, under certain aspects, a design evolution starting from shared concepts: reduced femoral violation, non-anatomic geometry, proximal calcar loading and lateral alignment. However, consistent differences are level of neck preservation, cross-sectional geometry and surface finishing. The Mayo component is the most time-tested component and, in our hands, it showed an excellent survivorship at the mid-term follow-up, with an extremely reduced incidence of aseptic loosening (partially reduced by the association with last generation acetabular couplings). For 160 implants followed for a mean of 4.7 years, survivorship was 97.5% with 4 failed implants: one fracture with unstable stem, 1 septic loosening and 2 aseptic mobilizations. DEXA analysis, performed on 15 cases, showed a good calcar loading and stimulation, but there was significant lateral load transfer to R3–R4 zones, giving to the distal part of the stem a function not simply limited to alignment. Metaphyseal conservative stems demonstrated a wide applicability with an essential surgical technique. Moreover, they offer the options of a “conservative revision” with a conventional primary component in case of failure and a “conservative revision” for failed resurfacing implants
Overview of the first HyMeX Special Observation Period over Italy: observations and model results
Abstract. The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September–6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria–Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in northeastern Italy, IOP13 (15–16 October 2012) in central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19)
Precipitation products from the hydrology SAF
Abstract. The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) was established by the EUMETSAT Council on 3 July 2005, starting activity on 1 September 2005. The Italian Meteorological Service serves as Leading Entity on behalf of twelve European member countries. H-SAF products include precipitation, soil moisture and snow parameters. Some products are based only on satellite observations, while other products are based on the assimilation of satellite measurements/products into numerical models. In addition to product development and generation, H-SAF includes a product validation program and a hydrological validation program that are coordinated, respectively, by the Italian Department of Civil Protection and by the Polish Institute of Meteorology and Water Management. The National Center of Aeronautical Meteorology and Climatology (CNMCA) of the Italian Air Force is responsible for operational product generation and dissemination. In this paper we describe the H-SAF precipitation algorithms and products, which have been developed by the Italian Institute of Atmospheric Sciences and Climate (in collaboration with the international community) and by CNMCA during the Development Phase (DP, 2005–2010) and the first Continuous Development and Operations Phase (CDOP-1, 2010–2012). The precipitation products are based on passive microwave measurements obtained from radiometers onboard different sun-synchronous low-Earth-orbiting satellites (especially, the SSM/I and SSMIS radiometers onboard DMSP satellites and the AMSU-A + AMSU-B/MHS radiometer suites onboard EPS-MetOp and NOAA-POES satellites), as well as on combined infrared/passive microwave measurements in which the passive microwave precipitation estimates are used in conjunction with SEVIRI images from the geostationary MSG satellite. Moreover, the H-SAF product generation and dissemination chain and independent product validation activities are described. Also, the H-SAF program and its associated activities that currently are being carried out or are planned to be performed within the second CDOP phase (CDOP-2, 2012–2017) are presented in some detail. Insofar as CDOP-2 is concerned, it is emphasized that all algorithms and processing schemes will be improved and enhanced so as to extend them to satellites that will be operational within this decade – particularly the geostationary Meteosat Third Generation satellites and the low-Earth-orbiting Core Observatory of the international Global Precipitation Measurement mission. Finally, the role of H-SAF within the international science and operations community is explained.</p
The validation service of the hydrological SAF geostationary and polar satellite precipitation products
Abstract. The development phase (DP) of the EUMETSAT Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF) led to the design and implementation of several precipitation products, after 5 yr (2005–2010) of activity. Presently, five precipitation estimation algorithms based on data from passive microwave and infrared sensors, on board geostationary and sun-synchronous platforms, function in operational mode at the H-SAF hosting institute to provide near real-time precipitation products at different spatial and temporal resolutions. In order to evaluate the precipitation product accuracy, a validation activity has been established since the beginning of the project. A Precipitation Product Validation Group (PPVG) works in parallel with the development of the estimation algorithms with two aims: to provide the algorithm developers with indications to refine algorithms and products, and to evaluate the error structure to be associated with the operational products. In this paper, the framework of the PPVG is presented: (a) the characteristics of the ground reference data available to H-SAF (i.e. radar and rain gauge networks), (b) the agreed upon validation strategy settled among the eight European countries participating in the PPVG, and (c) the steps of the validation procedures. The quality of the reference data is discussed, and the efforts for its improvement are outlined, with special emphasis on the definition of a ground radar quality map and on the implementation of a suitable rain gauge interpolation algorithm. The work done during the H-SAF development phase has led the PPVG to converge into a common validation procedure among the members, taking advantage of the experience acquired by each one of them in the validation of H-SAF products. The methodology is presented here, indicating the main steps of the validation procedure (ground data quality control, spatial interpolation, up-scaling of radar data vs. satellite grid, statistical score evaluation, case study analysis). Finally, an overview of the results is presented, focusing on the monthly statistical indicators, referred to the satellite product performances over different seasons and areas
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