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Precipitation Fields (precipitation + field)
Selected AbstractsEvolution of tropical and extratropical precipitation anomalies during the 1997,1999 ENSO cycleINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 8 2001Scott Curtis Abstract The 1997,1999 El Niño,Southern Oscillation (ENSO) period was very powerful, but also well observed. Multiple satellite rainfall estimates combined with gauge observations allow for a quantitative analysis of precipitation anomalies in the tropics and elsewhere accompanying the 1997,1999 ENSO cycle. An examination of the evolution of the El Niño and accompanying precipitation anomalies revealed that a dry Maritime Continent (MC) preceded the formation of positive sea-surface temperature (SST) anomalies in the eastern Pacific Ocean. Thirty- to sixty-day oscillations in the winter of 1996,1997 may have contributed to this lag relationship. Furthermore, westerly wind burst events may have maintained the drought over the MC. The warming of the equatorial Pacific was then followed by an increase in convection. A rapid transition from El Niño to La Niña occurred in May 1998, but as early as October,November 1997, precipitation indices captured substantial changes in Pacific rainfall anomalies. The global precipitation patterns for this event were in good agreement with the strong consistent ENSO-related precipitation signals identified in earlier studies. Differences included a shift in precipitation anomalies over Africa during the 1997,1998 El Niño and unusually wet conditions over northeast Australia during the later stages of the El Niño. Also, the typically wet region in the north tropical Pacific was mostly dry during the 1998,1999 La Niña. Reanalysis precipitation was compared with observations during this time period and substantial differences were noted. In particular, the model had a bias towards positive precipitation anomalies and the magnitudes of the anomalies in the equatorial Pacific were small compared with the observations. Also, the evolution of the precipitation field, including the drying of the MC and eastward progression of rainfall in the equatorial Pacific, was less pronounced for the model compared with the observations. Copyright © 2001 Royal Meteorological Society [source] Small-scale precipitation variability in the Alps: Climatology in comparison with semi-idealized numerical simulationsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 636 2008G. Zängl Abstract This study examines small-scale precipitation patterns in a north-Alpine region, and their dependence on the freezing level and on the crest-level (700 hPa) wind direction and speed. On the one hand, measurements from a uniquely dense operational rain-gauge network are analyzed for a period of 15 years (1991--2005). Information on the ambient atmospheric fields was extracted from climate-mode MM5 simulations driven with ECMWF (re-analysis data. On the other hand, high-resolution semi-idealized MM5 simulations have been conducted, combining realistic topography with idealized atmospheric fields. The atmospheric flow parameters have been chosen to be representative of those used to classify the observational data, focusing on atmospheric conditions conducive to stratiform, orographically enhanced precipitation in the region under consideration. The results of the data analysis indicate a pronounced tendency for local precipitation maxima in the lee of individual mountain ridges, whereas the variability between stations in the centre of wider valleys and stations on the windward foot of individual ridges is comparatively small. This points towards a strong contribution of local precipitation enhancement due to the seeder--feeder mechanism, combined with downstream advection of the precipitating hydrometeors by the ambient winds. The data analysis also reveals that strong winds and high temperatures tend to shift the precipitation field towards the interior of the Alps, whereas low temperatures and weak winds favour precipitation maxima near the northern edge of the Alps. The semi-idealized simulations are consistent with these findings, but their quantitative agreement with the observed precipitation patterns depends on the ambient flow conditions. The closest agreement is found for atmospheric conditions conducive to strong orographic lifting, for which our present idealized flow fields were designed. Lower skill is obtained for conditions not dominated by orographic lifting, which implies that future work should include a generalization of the idealized flow fields. Nevertheless, precipitation patterns generated with semi-idealized simulations seem to be very promising to support the spatial interpolation of point measurements (such as are needed for precipitation climatologies), which currently is usually based on statistical methods rather than physically motivated structures. Copyright © 2008 Royal Meteorological Society [source] Resolution errors associated with gridded precipitation fieldsINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 15 2005C. J. Willmott Abstract Spatial-resolution errors are inherent in gridded precipitation (P) fields,such as those produced by climate models and from satellite observations,and they can be sizeable when P is averaged spatially onto a coarse grid. They can also vary dramatically over space and time. In this paper, we illustrate the importance of evaluating resolution errors associated with gridded P fields by investigating the relationships between grid resolution and resolution error for monthly P within the Amazon Basin. Spatial-resolution errors within gridded-monthly and average-monthly P fields over the Amazon Basin are evaluated for grid resolutions ranging from 0.1° to 5.0°. A resolution error occurs when P is estimated for a location of interest within a grid-cell from the unbiased, grid-cell average P. Graphs of January, July and annual resolution errors versus resolution show that, at the higher resolutions (<3° ), aggregation quickly increases resolution error. Resolution error then begins to level off as the grid becomes coarser. Within the Amazon Basin, the largest resolution errors occur during January (summer), but the largest percentage errors appear in July (winter). In January of 1980, e.g., resolution errors of 29, 52 and 65 mm,or 11, 19 and 24% of the grid-cell means,were estimated at resolutions of 1.0°, 3.0° and 5.0°. In July of 1980, however, the percentage errors at these three resolutions were considerably larger, that is, 15%, 27% and 33% of the grid-cell means. Copyright © 2005 Royal Meteorological Society [source] Point and areal validation of forecast precipitation fieldsMETEOROLOGICAL APPLICATIONS, Issue 1 2006Eddy 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] STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWPTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 620 2006Neill E. Bowler Abstract An ensemble-based probabilistic precipitation forecasting scheme has been developed that blends an extrapolation nowcast with a downscaled NWP forecast, known as STEPS: Short-Term Ensemble Prediction System. The uncertainties in the motion and evolution of radar-inferred precipitation fields are quantified, and the uncertainty in the evolution of the precipitation pattern is shown to be the more important. The use of ensembles allows the scheme to be used for applications that require forecasts of the probability density function of areal and temporal averages of precipitation, such as fluvial flood forecasting,a capability that has not been provided by previous probabilistic precipitation nowcast schemes. The output from a NWP forecast model is downscaled so that the small scales not represented accurately by the model are injected into the forecast using stochastic noise. This allows the scheme to better represent the distribution of precipitation rate at spatial scales finer than those adequately resolved by operational NWP. The performance of the scheme has been assessed over the month of March 2003. Performance evaluation statistics show that the scheme possesses predictive skill at lead times in excess of six hours. © Crown copyright, 2006. [source] | ||||||||||