43 research outputs found
Comparison of rain gauge observations with modeled precipitation over Cyprus using contiguous rain area analysis
No full textVerification of modeled rainfall with precipitation observed by a rain gauge network has been
performed in a case study over the Cyprus Island. Cyprus has a relatively dense rain gauge network. The applied
verification method is the Contiguous Rain Area (CRA) analysis. In this work some drawbacks are pointed out
when CRA method is applied in such a case study. Impact on CRA results, when considering different dimensions
of the compared model domain and different types of indicators (correlation and mean square error) used in the
comparison, are discussed. Results indicate that care has to be taken when verification of modeled rainfall is
performed over some of islands or hydrological basins
Verification of precipitation forecasts from two limited-area models over Italy and comparison with ECMWF forecasts using a resampling technique
Get PDFThis 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 lowerresolution
grid (0.5°), using a nearest-neighbor average method; this remapping allowed for comparison
with ECMWF model forecasts, and for LAM intercomparisons at lower resolution, with the advantage of
reducing the skill score sensitivity to small displacements errors. LAM skill scores depend on the resolution
of the verification grid, with an increase when they are verified on a lower-resolution grid. The selected
LAMs have a higher BIA compared to ECMWF, showing a tendency to overforecast precipitation, especially
along mountain ranges, possibly due to undesired effects from the large-scale and/or convective
precipitation parameterizations. Lower ECMWF BIA accounts for skill score differences. LAMBO precipitation
forecasts during winter (adjusted for BIA differences) have less misses than ECMWF over the
islands of Sardinia and Sicily. Higher-resolution orography definitely adds value to LAM forecasts
Sensitivity of Precipitation Forecast Skill Scores to Bilinear Interpolation and a Simple Nearest-Neighbor Average Method on High-Resolution Verification Grids
No full textGrid 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
Flood forecasting in the Tiber catchment area: a methodological analysis
No full textThe most difficult step in hydrological forecasting is precipitation forecast, since rain is the most irregular and least predictable meteorological field. Numerical meteorological models are the main tool to forecast the precipitation field over river basins where floods may be expected. Object of this paper is a preliminary analysis of the appropriate methodological approach to flood forecasting in the Tiber River basin. An assessment of the flood forecasting skill of a meteorological limited area model, coupled with a lumped rainfall-runoff model, is performed. The main indications which seem to arise are that integral precipitation over the catchment area is adequately forecast in its time-evolution, but the total rainfall shows a systematic deficit with respect to observations
Sensitivity of forecast rainfall verification to a radar adjustment technique
No full textA 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 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
SIMM: an integrated forecasting approach for the Mediterranean area
No full textMany ‘high-impact’ meteorological, marine and hydrological events in the Mediterranean area are characterized by horizontal spatial scales of the order of 10–100 km. Such events are, sometimes, driven by complex dynamical processes involving planetary scale atmospheric flows. Several international programs (ALPEX, POEM, MAP, PYREX, MEDEX) have improved the understanding of some of these processes. However, because of the Mediterranean's geomorphological structure, characterized by mountain chains (e.g. the Alps), semi-enclosed sea basins and small river catchments, many problems remain. It is clear that such problems have to be faced in the context of analysis-prediction systems bridging the gap between global and local scales of motion. These systems should allow for an adequate representation of key dynamical processes at all the relevant scales of motion.
The Hydro-Meteorological-Marine System (‘Sistema Idro-Meteo-Mare’, SIMM) is a first step in developing an integrated system, adequately covering all scales of motion from global to local. A short description of the system is presented, highlighting scientific concepts behind design choices. A summary of the results of verification tests is also illustrated, together with a general evaluation of the whole process in planning, developing and running SIMM in order to assist future updates of the system, currently under development. Copyright © 2007 Royal Meteorological Societ
Radar adjusted data versus modelled precipitation: a case study over Cyprus
No full textIn the framework of the European VOLTAIRE
project (Fifth Framework Programme), simulations of relatively
heavy precipitation events, which occurred over the island
of Cyprus, by means of numerical atmospheric models
were performed. One of the aims of the project was indeed
the comparison of modelled rainfall fields with multi-sensor
observations. Thus, for the 5 March 2003 event, the 24-h accumulated
precipitation BOlogna Limited Area Model (BOLAM)
forecast was compared with the available observations
reconstructed from ground-based radar data and estimated by
rain gauge data.
Since radar data may be affected by errors depending
on the distance from the radar, these data could be rangeadjusted
by using other sensors. In this case, the Precipitation
Radar aboard the Tropical Rainfall Measuring Mission
(TRMM) satellite was used to adjust the ground-based radar
data with a two-parameter scheme. Thus, in this work, two
observational fields were employed: the rain gauge gridded
analysis and the observational analysis obtained by merging
the range-adjusted radar and rain gauge fields.
In order to verify the modelled precipitation, both nonparametric
skill scores and the contiguous rain area (CRA)
analysis were applied. Skill score results show some differences
when using the two observational fields. CRA results
are instead quite in agreement, showing that in general
a 0.27 eastward shift optimizes the forecast with respect to
the two observational analyses. This result is also supported
by a subjective inspection of the shifted forecast field, whose
gross features agree with the analysis pattern more than the
non-shifted forecast one.
However, some open questions, especially regarding the
effect of other range adjustment techniques, remain open and
need to be addressed in future works
Linear and nonlinear post-processing of numerically forecasted surface temperature
No full textIn this paper we test different approaches to the
statistical post-processing of gridded numerical surface air
temperatures (provided by the European Centre for Medium-
Range Weather Forecasts) onto the temperature measured
at surface weather stations located in the Italian region of
Puglia. We consider simple post-processing techniques, like
correction for altitude, linear regression from different input
parameters and Kalman filtering, as well as a neural network
training procedure, stabilised (i.e. driven into the absolute
minimum of the error function over the learning set)
by means of a Simulated Annealing method. A comparative
analysis of the results shows that the performance with neural
networks is the best. It is encouraging for systematic use
in meteorological forecast-analysis service operations
