Christophe Accadia

Sensitivity of Precipitation Forecast Skill Scores to Bilinear Interpolation and a Simple Nearest-Neighbor Average Method on High-Resolution Verification Grids

Grid transformations are common postprocessing procedures used in numerical weather prediction to transfer a forecast field from one grid to another. This paper investigates the statistical effects of two different interpolation techniques on widely used precipitation skill scores like the equitable threat score and the Hanssen‐Kuipers score. The QUADRICS Bologna Limited Area Model (QBOLAM), which is a parallel version of the Bologna Limited Area Model (BOLAM) described by Buzzi et al., is used, and it is verified on grids of about 10 km (grid-box size). The precipitation analysis is obtained by means of a Barnes objective analysis scheme. The rain gauge data are from the Piedmont and Liguria regions, in northwestern Italy. The data cover 243 days, from 1 October 2000 to 31 May 2001. The interpolation methods considered are bilinear interpolation and a simple nearest-neighbor averaging method, also known as remapping or budget interpolation, which maintains total precipitation to a desired degree of accuracy. A computer-based bootstrap technique is applied to perform hypothesis testing on nonparametric skill scores, in order to assess statistical significance of score differences. Small changes of the precipitation field induced by the two interpolation methods do affect skill scores in a statistically significant way. Bilinear interpolation affects skill scores more heavily, smoothing the maxima, and smearing and increasing the minima of the precipitation field over the grid. The remapping procedure seems to be more appropriate for performing high-resolution grid transformations, although the present work shows that a precipitation edge-smearing effect at lower precipitation thresholds exists. Equitable threat score is more affected than Hanssen‐Kuipers score by the interpolation process, since this last score weights all kind of successes (hits and correct no-rain forecasts). Correct no-rain forecasts at higher thresholds often outnumber hits, misses, and false alarms, reducing the sensitivity to false alarm changes introduced by the interpolation process.

Comparison of 10-m Wind Forecasts from a Regional Area Model and QuikSCAT Scatterometer Wind Observations over the Mediterranean Sea

Surface wind forecasts from a limited-area model [the Quadrics Bologna Limited-Area Model (QBOLAM)] covering the entire Mediterranean area at 0.1° grid spacing are verified against Quick Scatterometer (QuikSCAT) wind observations. Only forecasts within the first 24 h in coincidence with satellite overpasses are used. Two years of data, from 1 October 2000 to 31 October 2002, have been considered, allowing for an adequate statistical assessment under different wind conditions. This has been carried out by analyzing the fields of the mean wind vectors, wind speed bias, correlation, difference standard deviation, steadiness, gustiness, and mean wind direction difference, in order to investigate spatial variability. Statistics have been computed on a seasonal basis. A comparison of satellite and forecast winds with measurements from three buoys was also performed. Some critical areas of the Mediterranean Sea where wind forecast quality is lower than average have been identified. Such areas correspond to semienclosed basins surrounded by important orography and to small regions at the lee side of the main islands. In open-sea regions the model underestimates wind strength from about 0.5 m s 1 in spring and summer to 1.0 m s 1 in winter, as evidenced by the existing biases against scatterometer data. Also, a wind direction bias (scatterometer minus model) generally between 5° and 15° exists. A survey of the identified and likely sources of forecast error is performed, indicating that orography representation plays an important role. Numerical damping is identified as a likely factor reducing forecast wind strength. The need for a correction scheme is envisaged to provide more accurate forcing for numerical sea state forecasting models, wind energy evaluation, and latent and/or sensible heat exchanges.

Verification of Precipitation Forecasts from Two Limited-Area Models over Italy and Comparison with ECMWF Forecasts Using a Resampling Technique

Abstract This paper presents the first systematic limited area model (LAM) precipitation verification work over Italy. A resampling technique was used to provide skill score results along with confidence intervals. Two years of data were used, starting in October 2000. Two operational LAMs have been considered, the Limited Area Model Bologna (LAMBO) operating at the Agenzia Regionale Prevenzione e Ambiente-Servizio Meteorologico Regionale (ARPA-SMR) of the Emilia–Romagna region, and the QUADRICS Bologna Limited Area Model (QBOLAM) running at the Agenzia per la Protezione dell’Ambiente e per i Servizi Tecnici (APAT). A 24-h forecast skill score comparison was first performed on the native 0.1° high-resolution grids, using a Barnes scheme to produce the observed 24-h accumulated rainfall analysis. Two nonparametric skill scores were used: the equitable threat score (ETS) and the Hanssen and Kuipers score (HK). Frequency biases (BIA) were also calculated. LAM forecasts were also remapped on a lower-resolutio...

Impact Assessment of Simulated Doppler Wind Lidars with a Multivariate Variational Assimilation in the Tropics

This paper deals with the dynamical aspect of variational data assimilation in the tropics and the role of the background-error covariances in the observing system simulation experiments for the tropics. The study uses a model that describes the horizontal structure of the potential temperature and wind fields in regions of deep tropical convection. The assimilation method is three- and four-dimensional variational data assimilation. The background-error covariance model for the assimilation is a multivariate model that includes the mass–wind couplings representative of equatorial inertio-gravity modes and equatorial Kelvin and mixed Rossby–gravity modes in addition to those representative of balanced equatorial Rossby waves. Spectra of the background errors based on these waves are derived from the tropical forecast errors of the European Centre for Medium-Range Weather Forecasts (ECMWF) model. Tropical mass–wind (im)balances are illustrated by studying the potential impact of the spaceborne Doppler wind lidar (DWL) Atmospheric Dynamic Mission (ADM)-Aeolus, which measures horizontal line-of-sight (LOS) wind components. Several scenarios with two DWLs of ADM-Aeolus type are compared under different flow conditions and using different assumptions about the quality of the backgrounderror covariances. Results of three-dimensional variational data assimilation (3DVAR) illustrate the inefficiency of multivariate assimilation in the tropics. The consequence for the assimilation of LOS winds is that the missing part of the wind vector can hardly be reconstructed from the mass-field observations and applied balances as in the case of the midlatitudes. Results of four-dimensional variational data assimilation (4DVAR) show that for large-scale tropical conditions and using reliable background-error statistics, differences among various DWL scenarios are not large. As the background-error covariances becomes less reliable, horizontal scales become smaller and the flow becomes less zonal, the importance of obtaining information about the wind vector increases. The added value of another DWL satellite increases as the quality of the background-error covariances deteriorates and it can be more than twice as large as in the case of reliable covariances.

Sensitivity of forecast rainfall verification to a radar adjustment technique

A ground-based radar (GR) has to measure rain from close to the radar to large distances from it. Consequently, the scattering volume of the GR changes significantly. As an advantage, the scattering volume of a space-borne radar is of similar size at all locations, thus allowing the compensation of the decreasing spatial resolution of the GR with range (range-adjustment). Adjustment with range is here performed by means of data observed by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) using a ∼10 dB per decade factor. For instance, about 8 dB are added to the measured reflectivity at 100 km, while 2 dB are subtracted at 10 km from the radar site. Thus, two different radar datasets, the range-adjusted data and the original ones, can be compared with forecast precipitation. In the framework of the EU VOLTAIRE project (Fifth Framework Programme), where observations from rain gauges, GR, TRMM PR and forecast precipitation were available for the island of Cyprus, such a kind of study was performed. The chosen comparison method was a contiguous rain area (CRA) analysis. Three pattern-matching criteria, involving mean square error, mean absolute error and correlation, have been used to match forecast and observed precipitation patterns. In this paper, we show that the results of the comparison in a selected case study are sensitive to the application of a range-adjustment technique. Observational analysis, obtained by merging rain gauge data with the adjusted GR data, seems to give more stable results when changing the pattern-matching criterion, and proposing it as the better field reconstruction in the comparison.

Multisensor Comparison and Numerical Modeling of Atmospheric Water Fields: A VOLTAIRE Case Study over Cyprus

Abstract This paper presents a study performed within the framework of the European Union’s (EU) VOLTAIRE project (Fifth Framework Programme). Among other tasks, the project aimed at the integration of the Tropical Rainfall Measuring Mission (TRMM) data with ground-based observations and at the comparison between water fields (precipitation and total column water vapor) as estimated by multisensor observations and predicted by NWP models. In particular, the VOLTAIRE project had as one of its main objectives the goal of assessing the application of satellite-borne instrument measures to model verification. The island of Cyprus was chosen as the main “test bed,” because it is one of the few European territories covered by the passage of the TRMM Precipitation Radar (PR) and it has a dense rain gauge network and an operational weather radar. TRMM PR provides, until now, the most reliable space-borne spatial high-resolution precipitation measurements. Attention is focused on the attempt to define a methodolog...

Using ASCAT Scatterometer Winds to Evaluate Relative Biases in the QuikSCAT-Derived Wind Vorticity

Relative wind vorticity ω (hereafter vorticity) is a crucial parameter to understand the spatial features of the wind field. In the Mediterranean Sea, which is the area where this study is focused, these are particularly interesting because they are often the effects of the interaction between the airflow and the orography. Wind vorticity has been derived from both Quick Scatterometer (QuikSCAT) and Advanced Scatterometer (ASCAT) 12.5-km scatterometer data downloaded from the National Aeronautics and Space Administration Physical Oceanography Distributed Active Archive Center data archive, and compared in the period from March to November 2009. The monthly mean fields of the vorticity ω̅ show discrepancies which need to be understood. This paper thus aims to understand the nature of these differences, to make the two vorticity data sets compatible and usable as a common data set. Results have been provided in terms of the relative bias in vorticity 〈Δ̅ω̅〉, which is the mean difference between the ASCAT ω̅^A and QuikSCAT ω̅^Q monthly mean vorticities averaged over the entire Mediterranean Basin and the entire study period. This difference 〈Δ̅ω̅〉 = 0.093 ·10^-5 ±0.05 ·10^-5s^-1) is mainly due to a relative vorticity bias in the cyclonic component of ω̅, rather than in the anticyclonic component, whose bias is four times smaller. This bias does not depend significantly on the variable accuracy of the wind speed and direction across the QuikSCAT swath. This study led us to define and analyze the so-called vorticity noise, which is present particularly in the QuikSCAT-derived vorticity, to understand if, and how, it can contribute to the relative bias in vorticity. The contribution of this kind of noise on ω̅ has been found relevant only for the cyclonic vorticity of ω̅^Q. By applying a cyclonic denoising to each swath of QuikSCAT, 〈Δ̅ω̅〉 = -0.016 ·10^-5 ±0.05 ·10^-5s^-1 is obtained, drastically reduced with respect to the initial value. This may be considered the typical bias over the Mediterranean Sea between ω̅^A and (ω̅^Q derived from the 12.5-km data, after applying the cyclonic denoising to QuikSCAT vorticity fields.

The EUMETSAT Polar System-Second Generation (EPS-SG) micro-wave and sub-millimetre wave imaging missions

The EUMETSAT Polar System (EPS) will be followed by a second generation system, EPS-SG, in the 2020-2040 timeframe and contribute to the Joint Polar System being jointly set up with NOAA. Among the various missions which are part of EPS-SG, there are the Microwave Imager (MWI) and the Ice Cloud Imager (ICI). The MWI frequencies are from 18 GHz up to 183 GHz. All MWI channels up to 89 GHz measure both V and H polarisations. The primary objective of the MWI mission is to support Numerical Weather Prediction at regional and global scales. The MWI will not only provide continuity of measurements for some heritage microwave imager channels (e.g. SSM/I, AMSR-E) but will also include additional channels such as the 50-55 / 118 GHz bands. The combined use of these channels will provide more information on cloud and precipitation over sea and land. The ICI will provide measurements over the sub-millimetre spectral range contributing to an innovative characterisation of clouds over the whole globe. The ICI has channels at 183 GHz, 325 GHz and 448 GHz with single V polarisation and two channels at 243 GHz and 664 GHz with both V and H polarisation. The ICI’s primary objectives are to support climate monitoring and validation of ice cloud models and the parameterisation of ice clouds in weather and climate models through the provision of ice cloud products.

Definition of mission requirements for the follow-on EUMETSAT polar system

EUMETSAT has initiated preparatory activities for the definition of the follow-on EUMETSAT Polar System (post- EPS) needed for the timeframe 2020 onwards as a replacement for the current EUMETSAT Polar System. Based on the first outputs of the EUMETSAT post-EPS user consultation process initiated in 2005, mission requirements for potential post-EPS missions have been drafted. Expertise from a variety of communities was drawn upon in order to ascertain user needs expressed in terms of geophysical variables, for operational meteorology, climate monitoring, atmospheric chemistry, oceanography, and hydrology. Current trends in the evolution of these applications were considered in order to derive the necessary satellite products that will be required in the post-EPS era. The increasing complexity of models with regard to parameterisation and data assimilation, along with the trend towards coupled atmosphere, ocean and land models, generates new requirements, particularly in the domains of clouds and precipitation, trace gases and ocean/land surface products. Following the requirements definition, concept studies at instrument and system levels will shortly commence with the support of the European Space Agency (ESA), together with industry and representatives of the user and science communities. Such studies, planned for completion by end of 2008, aim at defining and trading off possible mission and system concepts and will establish preliminary functional requirements for full or partial implementation of post-EPS mission requirements. Cost drivers and needs for critical research and development will also be identified. The generation of both the user and mission requirements have been supported substantially by the post-EPS Mission Experts Team and the Application Expert Groups. Their support is gratefully acknowledged.