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Precipitation Forecasts (precipitation + forecast)

Distribution by Scientific Domains

Earth and Environmental Science	100%

Selected Abstracts

On the use of the intensity-scale verification technique to assess operational precipitation forecasts

METEOROLOGICAL APPLICATIONS, Issue 1 2008
Gabriella Csima
Abstract The article describes the attempt to include the intensity-scale technique introduced by Casati et al. (2004) into a set of standardized verifications used in operational centres. The intensity-scale verification approach accounts for the spatial structure of the forecast field and allows the skill to be diagnosed as a function of the scale of the forecast error and intensity of the precipitation events. The intensity-scale method has been used to verify two different resolutions of the European Centre for Medium-Range Weather Forecasts (ECMWF) operational quantitative precipitation forecast (QPF) over France, and to compare the performance of the ECMWF and the Hungarian Meteorological Service operational model (ALADIN) forecasts, run over Hungary. Two case studies have been introduced, which show some interesting insight into the spatial scale of the error. The distribution of daily skill score for an extended period of time is also presented. The intensity-scale technique shows that the forecasts in general exhibit better skill for large-scale events, and lower skill for small-scale and intense events. In the paper, it is mentioned how some of the stringent assumptions on the domain over which the method can be applied, and the availability of the matched forecasts and observations, can limit its usability in an operational environment. Copyright © 2008 Royal Meteorological Society [source]

Assimilation of radar reflectivity into the LM COSMO model with a high horizontal resolution

METEOROLOGICAL APPLICATIONS, Issue 4 2006
Z. Sokol
Abstract An assimilation of radar reflectivity into a numerical weather prediction (NWP) model with a horizontal resolution of 2.8 km is presented and applied to three severe convective events. The suggested assimilation method takes into account differences between the model and radar-derived precipitation in modifying vertical profiles of water vapour mixing ratio in each model time step by the nudging approach. Version 3.9 of the LM COSMO (Local Model COSMO) ,NWP model used in this study includes the explicit formulation of the cloud and rain processes involved. Two variants of the assimilation technique are designed and outputs of their implementation are compared. The first variant makes use of the ground data only, while the second utilises vertical profiles of precipitation water. Both variants provide an improvement of precipitation forecast in comparison with outputs of the control run without assimilation procedures applied. When the assimilated radar data indicate initial precipitation near an expected storm, the NWP model is capable of forecasting basic features of the storm development two to three hours ahead. Three case studies are presented. In one, the assimilation method that takes into account the vertical structure of the precipitation water yields better results than the others which utilise ground data only. However, for the remaining two case studies both types of the assimilation method produce comparable results. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Data assimilation of high-density observations.

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 605 2005
II: Impact on the forecast of the precipitation for the MAP/SOP IOP2b
Abstract The impact of the data assimilation of high-density (space and time) data on the precipitation forecast is evaluated by improving the initial conditions of a mesoscale model. The high-frequency data allow for improving the three-hourly initial and boundary conditions as well. The data assimilation is performed using initial objective analysis (Cressman and multiquadric schemes) and 3D-Var. The MM5 (version 3) mesoscale model from Penn State University/National Center for Atmospheric Research is used to evaluate the impact of the improved initial and boundary conditions on the model simulations. The comparison of model results with observations shows: (i) the forecast of the precipitation at high resolution produces better results than those without data assimilation only if three-hourly data are assimilated by multiquadric; (ii) the mean error of the model rainfall largely decreases only if 3D-Var is used, but no comparable improvement in the spatial distribution of the precipitation is found; (iii) the improvement for the rainfall is not as good as it is for the initial conditions for all experiments. Moreover, the observations ingested by objective analysis modify both the amount and the timing of the precipitation on the Po valley. On the other hand, 3D-Var modifies only the amount of the precipitation, but both techniques barely recover large-model failure. Copyright © 2005 Royal Meteorological Society [source]

A strategy for perturbing surface initial conditions in LAMEPS

ATMOSPHERIC SCIENCE LETTERS, Issue 2 2010
Yong Wang
Abstract The lack or inadequate representation of uncertainties in the surface initial conditions (ICs) affects the quality of ensemble forecast, in particular the near surface temperature and precipitation. In this paper, a strategy for perturbing surface ICs in limited area model ensemble prediction system, noncycling surface breeding (NCSB) is proposed. The strategy combines short-range surface forecasts driven by perturbed atmospheric forcing and the breeding method for generating the perturbation to surface ICs. NCSB is implemented and tested in Aire Limitée Adaptation dynamique Développement InterNational-limited area ensemble forecasting (ALADIN-LAEF). Statistical verification demonstrates that the application of NCSB improves the ALADIN-LAEF 2m temperature and precipitation forecast. Positive impacts are also obtained for temperature and specific humidity in the lower atmosphere. Copyright © 2010 Royal Meteorological Society [source]

Testing a model for predicting the timing and location of shallow landslide initiation in soil-mantled landscapes

EARTH SURFACE PROCESSES AND LANDFORMS, Issue 9 2003
M. Casadei
Abstract The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever-expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km2 catchment a near-annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in,nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process-based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ,ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity,duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide-producing storms. Landslide and soil production parameters were ,xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ,rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de,ne whether a rainstorm was a signi,cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi,ed the 1982 storm as the only landslide-producing storm during the period 1980,86. Application of this parameter combination to the entire 45 year record successfully identi,ed the three events, but also predicted that two other landslide-producing events should have occurred. This performance is signi,cantly better than the empirical intensity,duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non-producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi,cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd. [source]

On the use of the intensity-scale verification technique to assess operational precipitation forecasts

Assessing the spatial and temporal variation in the skill of precipitation forecasts from an NWP model

METEOROLOGICAL APPLICATIONS, Issue 1 2008
Nigel Roberts
Abstract It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques. Copyright © 2008 Royal Meteorological Society [source]

Point and areal validation of forecast precipitation fields

METEOROLOGICAL APPLICATIONS, Issue 1 2006
Eddy Yates
Abstract Two high resolution quantitative precipitation forecasts with different levels of realism are evaluated. Classical scores (bias, correlation and scores based on contingency tables) confirm that the two forecasts do not have the same quality. A multi-scale extension of these scores has then been made to produce a validation for hydrological purposes. Rainfall fields are integrated over surfaces of various scales. For better simulation, scores indicate an increase in the quality of the simulated precipitation for larger surfaces (typically more than 100 km2): the localisation errors are reduced by the aggregation. This helps to determine the usefulness of such forecasts for hydrological purposes. Copyright © 2006 Royal Meteorological Society. [source]

Measuring forecast skill: is it real skill or is it the varying climatology?

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 621C 2006
Thomas M. Hamill
Abstract It is common practice to summarize the skill of weather forecasts from an accumulation of samples spanning many locations and dates. In calculating many of these scores, there is an implicit assumption that the climatological frequency of event occurrence is approximately invariant over all samples. If the event frequency actually varies among the samples, the metrics may report a skill that is different from that expected. Many common deterministic verification metrics, such as threat scores, are prone to mis-reporting skill, and probabilistic forecast metrics such as the Brier skill score and relative operating characteristic skill score can also be affected. Three examples are provided that demonstrate unexpected skill, two from synthetic data and one with actual forecast data. In the first example, positive skill was reported in a situation where metrics were calculated from a composite of forecasts that were comprised of random draws from the climatology of two distinct locations. As the difference in climatological event frequency between the two locations was increased, the reported skill also increased. A second example demonstrates that when the climatological event frequency varies among samples, the metrics may excessively weight samples with the greatest observational uncertainty. A final example demonstrates unexpectedly large skill in the equitable threat score of deterministic precipitation forecasts. Guidelines are suggested for how to adjust skill computations to minimize these effects. Copyright © 2006 Royal Meteorological Society [source]

Propagation of uncertainty from observing systems into NWP: COST-731 Working Group 1

ATMOSPHERIC SCIENCE LETTERS, Issue 2 2010
A. Rossa
Abstract The COST-731 Action is focused on uncertainty propagation in hydrometeorological forecasting chains. The goals and activities of the Action Working Group 1 can be subdivided by (1) describing and studying the impact of imperfect observations, mostly from radar, (2) exploiting radar data assimilation as a promising avenue for improved short-range precipitation forecasts and (3) high-resolution ensemble forecasting. Activities of Working Group 1 are presented along with their possible significance for hydrological applications. Copyright © 2010 Royal Meteorological Society and Crown copyright [source]

Using an intensity-scale technique to assess the added benefit of high-resolution model precipitation forecasts

ATMOSPHERIC SCIENCE LETTERS, Issue 2 2006
Marion P. Mittermaier
Abstract Deterministic precipitation forecasts from the 12- and 4-km versions of the Unified Model (UM) were compared using an intensity-scale technique. Averaging raw model output is always recommended to minimise grid-scale errors. The retained detail in averaged 4-km forecasts produces an improved prediction of larger accumulations. © Crown Copyright 2006. Reproduced with the permission of the Controller of HMSO. Published by John Wiley & Sons, Ltd. [source]