93:
well as ensemble members of the various models, can help reduce forecast error. However, regardless how small the average error becomes with any individual system, large errors within any particularly piece of guidance are still possible on any given model run. Professionals are required to interpret the model data into weather forecasts that are understandable to the lay person. Professionals can use knowledge of local effects which may be too small in size to be resolved by the model to add information to the forecast. As an example, terrain is considered in the QPF process by using topography or climatological precipitation patterns from observations with fine detail. Using model guidance and comparing the various forecast fields to climatology, extreme events such as excessive precipitation associated with later
116:. In this time range it is possible to forecast smaller features such as individual showers and thunderstorms with reasonable accuracy, as well as other features too small to be resolved by a computer model. A human given the latest radar, satellite and observational data will be able to make a better analysis of the small scale features present and so will be able to make a more accurate forecast for the following few hours. However, there are now
224:
151:(NCEP), and the Canadian Forecasting Center). Ensemble mean forecasts for precipitation have the same problems associated with their use in other fields, as they average out more extreme values, and therefore have limited usefulness for extreme events. In the case of the SREF ensemble mean, used within the United States, this decreasing usefulness starts with values as low as 0.50 inches (13 mm).
55:, or in the lowest levels of the atmosphere, which decreases with height. QPF can be generated on a quantitative, forecasting amounts, or a qualitative, forecasting the probability of a specific amount, basis. Radar imagery forecasting techniques show higher skill than model forecasts within 6 to 7 hours of the time of the radar image. The forecasts can be verified through use of
215:, River Forecast Centers, and local forecast offices within the National Weather Service create precipitation forecasts for up to five days in the future, forecasting amounts equal to or greater than 0.01 inches (0.25 mm). Starting in the mid-to-late 1990s, QPFs were used within hydrologic forecast models to simulate impact of rainfall on river stages.
254:, or POD, is found by dividing the overlap between the forecast and observed fields by the size of the observed field: the goal here is a score of 1. The critical success index, or CSI, divides the overlap between the forecast and observed fields by the combined size of the forecast and observed fields: the goal here is a score of 1. The
20:
160:
92:
In the past, the forecaster was responsible for generating the entire weather forecast based upon available observations. Today, meteorologists' input is generally confined to choosing a model based on various parameters, such as model biases and performance. Using a consensus of forecast models, as
202:
The Hong Kong
Observatory generates short term rainstorm warnings for systems which are expected to accumulate a certain amount of rainfall per hour over the next few hours. They use three levels of warning. The amber warning indicates that a rainfall intensity of 30 millimetres (1.2 in) per
142:
entails the production of many forecasts to reflect the uncertainty in the initial state of the atmosphere (due to errors in the observations and insufficient sampling). The range of different forecasts produced can then assess the uncertainty in the forecast. Ensemble forecasts are increasingly
193:
began a method of forecasting rainfall using a combination, or ensemble, of different forecast models in 2006. It is termed The Poor Man's
Ensemble (PME). Its forecasts are more accurate over time than any of the individual models composing the ensemble. The PME is quick to produce, and is
42:
accumulated over a specified time period over a specified area. A QPF will be created when precipitation amounts reaching a minimum threshold are expected during the forecast's valid period. Valid periods of precipitation forecasts are normally synoptic hours such as 00:00, 06:00, 12:00 and
167:
In addition to graphical rainfall forecasts showing quantitative amounts, rainfall forecasts can be made describing the probabilities of certain rainfall amounts being met. This allows the forecaster to assign the degree of uncertainty to the forecast. This technique is considered to be
47:. Terrain is considered in QPFs by use of topography or based upon climatological precipitation patterns from observations with fine detail. Starting in the mid-to-late 1990s, QPFs were used within hydrologic forecast models to simulate impact to rivers throughout the United States.
97:
events lead to better forecasts. While increasing accuracy of forecast models implies that humans may no longer be needed in the forecast process at some point in the future, there is currently still a need for human intervention.
77:
Algorithms exist to forecast rainfall based on short term radar trends, within a matter of hours. Radar imagery forecasting techniques show higher skill than model forecasts within 6 to 7 hours of the time of the radar image.
203:
hour is expected. The red warning indicates rainfall amounts of 50 millimetres (2.0 in) per hour are anticipated. The black warning indicates that rainfall rates of 70 millimetres (2.8 in) are possible.
227:
24 hours rain accumulation on the Val d'Irène radar in
Eastern Canada. Notice the zones without data in the East and Southwest caused by radar beam blocking from mountains. (Source: Environment Canada)
722:
VERIFICATION OF QUANTITATIVE PRECIPITATION FORECAST GUIDANCE FROM NWP MODELS AND THE HYDROMETEOROLOGICAL PREDICTION CENTER FOR 2005–2007 TROPICAL CYCLONES WITH CONTINENTAL U.S. RAINFALL IMPACTS.
686:
Verification of
Quantitative Precipitation Forecast Guidance From NWP Models and the Hydrometeorological Prediction Center For 2005–2007 Tropical Cyclones With Continental U.S. Rainfall Impacts.
144:
258:, or FAR, divides the area of the forecast which does not overlap the observed field by the size of the forecasted area. The goal value in this measure is zero.
572:
148:
134:
The detail that can be given in a forecast increases with time as errors decrease. There comes a point when the errors are so large that the forecast has no
172:
forecasts, as a period's chance of rain equals the chance that 0.01 inches (0.25 mm) will fall in any particular spot. In this case, it is known as
389:
Quantitative
Precipitation Forecast (QPF) from Weather Prediction Models and Radar Nowcasts, and Atmospheric Hydrological Modelling for Flood Simulation.
549:
315:
501:
391:
704:
446:
411:
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24:
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with the actual state of the atmosphere. Looking at a single forecast model does not indicate how likely that forecast is to be correct.
353:
370:
620:
640:
688:
322:
246:, compares the size of the forecast field to the observed field, with the goal of a score of 1. The threat score involves the
270:
120:
using those data and mesoscale numerical model to make better extrapolation, including evolution of those features in time.
63:
estimates, or a combination of both. Various skill scores can be determined to measure the value of the rainfall forecast.
565:
758:
478:
173:
48:
407:
291:
269:
global forecast model performed best in regards to its rainfall forecasts over the last few years, outperforming the
462:
255:
247:
670:
Development of
Quantitative Precipitation Forecast (QPF) Confidence Factor Using Short Range Ensemble Forecasts.
235:
observations can be gridded into areal averages, which are then compared to the grids for the forecast models.
627:
597:
508:
485:
169:
107:
52:
316:"Quantitative Precipitation Forecast: Its Generation and Verification at the Southeast River Forecast Center"
546:
266:
326:
643:
190:
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139:
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176:. These probabilities can be derived from a deterministic forecast using computer post-processing.
604:
87:
701:
763:
499:
The Use Of
Eensemble and Anomaly Data to Anticipate Extreme Flood Events in the Northeastern U.S.
522:
The complex relationship between forecast skill and forecast value : A real-world analysis.
251:
242:
Several statistical scores can be based on the observed and forecast fields. One, known as a
431:
The Use of
Ensemble Forecasts to Produce Improved Medium Range (3-15 days) Weather Forecasts.
262:
521:
350:
708:
702:
Optimization of quantitative precipitation forecast time horizons used in river forecasts.
624:
553:
505:
482:
395:
357:
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Sensitivity of quantitative precipitation forecast to height dependent changes in humidity
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of the forecast and observed sets, with a maximum possible verification score of 1. The
223:
617:
601:
112:
The forecasting of the precipitation within the next six hours is often referred to as
371:
Probabilistic
Quantitative Precipitation Forecast for Flood Prediction: An Application
752:
585:
236:
117:
72:
60:
39:
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459:
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informative, relative to climatology. This method has been used for years within
721:
685:
656:
373:. Journal of Hydrometeorology, February 2008, pp. 76–95. Retrieved on 2008-12-31.
163:
Table showing probabilities of certain rainfall amounts in various blocks of time
135:
736:
430:
349:
Christian Keil, Andreas Röpnack, George C. Craig, and Ulrich
Schumann (2008).
232:
56:
475:
429:
Klaus Weickmann, Jeff Whitaker, Andres Roubicek and Catherine Smith (2008).
412:
Weather Forecasting Through the Ages via Internet Archive Wayback Machine.
239:
estimates can be used outright, or corrected for rain gauge observations.
737:
Hydrometeorological Prediction Center QPF for the lower 48 United States
19:
159:
534:
497:
Neil A. Stuart, Richard H. Grumm, John Cannon, and Walt Drag (2007).
274:
222:
194:
available through their Water and the Land page on their website.
158:
94:
18:
414:
143:
being used for operational weather forecasting (for example at
602:
Is It Going to Rain Today? Understanding The Weather Forecast.
524:
Weather and forecasting, pp. 554-559. Retrieved on 2008-05-25.
44:
741:
684:
Michael J. Brennan, Jessica L. Clark, and Mark Klein (2008).
433:
Earth Systems Research Laboratory. Retrieved on 2007-02-16.
51:
show significant sensitivity to humidity levels within the
360:. Geophysical Research Letters. Retrieved on 2008-12-31.
720:
Michael J. Brennan, Jessica L. Clark, and Mark Klein.
711:
23rd Conference on Hydrology. Retrieved on 2008-12-31.
231:
Rainfall forecasts can be verified a number of ways.
511:
Eastern Region Headquarters. Retrieved on 2009-01-01.
488:
Western Region Headquarters. Retrieved on 2008-12-31.
672:
American Geophysical Union. Retrieved on 2008-12-31.
639:Executive and International Affairs Branch (2007).
145:European Centre for Medium-Range Weather Forecasts
630:Office, Tulsa, Oklahoma. Retrieved on 2009-01-01.
23:Example of a five-day rainfall forecast from the
659:Hong Kong Observatory. Retrieved on 2009-02-08.
573:National Centers for Environmental Prediction
149:National Centers for Environmental Prediction
8:
657:Short-range rainfall forecast in Hong Kong.
444:Tropical cyclone motion and intensity talk.
180:Entities which generate rainfall forecasts
680:
678:
655:Edwin S.T. Lai & Ping Cheung (2001).
547:Weather and Climate | What Is Nowcasting?
294:: using QPF and EPS for flood forecasting
383:
381:
379:
668:J. Im, Ed Danaher, Keith Brill (2004).
460:Tropical Cyclone Report: Hurricane Ike.
425:
423:
309:
307:
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16:Expected amount of melted precipitation
618:Probabilistic QPF Detailed Definition.
520:Roebber P. J. and Bosart L. F. (1996)
447:Hydrometeorological Prediction Center
369:P. Reggiani and A. H. Weerts (2008).
287:Tropical cyclone rainfall forecasting
213:Hydrometeorological Prediction Center
25:Hydrometeorological Prediction Center
7:
641:Meteorological and Related Research.
265:which impact the United States, the
586:Probabilistic QPF for River Basins.
584:American Geophysical Union (1995).
38:) is the expected amount of melted
32:quantitative precipitation forecast
476:Optimizing Output From QPF Helper.
14:
570:SREF Precipitation Verification.
742:Irrigation controller using QPF
689:American Meteorological Society
398:ACTIF. Retrieved on 2009-01-01.
323:Georgia Institute of Technology
211:Within the United States, the
1:
566:Environmental Modeling Center
174:probability of precipitation
408:Goddard Space Flight Center
292:European Flood Alert System
780:
700:Noreen O. Schwein (2009).
691:. Retrieved on 2008-12-31.
646:. Retrieved on 2009-02-08.
607:. Retrieved on 2009-01-01.
575:. Retrieved on 2008-12-31.
465:. Retrieved on 2009-02-08.
449:. Retrieved on 2007-07-21.
417:. Retrieved on 2008-05-25.
127:
105:
85:
70:
623:October 14, 2008, at the
533:Glossary of Meteorology.
481:February 5, 2009, at the
463:National Hurricane Center
724:Retrieved on 2008-12-31.
628:National Weather Service
598:National Weather Service
588:Retrieved on 2009-01-01.
556:Retrieved on 2011-09-08.
536:Retrieved on 2015-05-26.
509:National Weather Service
504:October 7, 2008, at the
486:National Weather Service
442:Todd Kimberlain (2007).
314:Bushong, Jack S (2005).
252:probability of detection
170:National Weather Service
108:Nowcasting (meteorology)
53:planetary boundary layer
474:Daniel Weygand (2008).
228:
164:
82:Use of forecast models
27:
644:Bureau of Meteorology
616:Steve Amburn (2008).
226:
191:Bureau of Meteorology
162:
22:
458:Robbie Berg (2009).
387:Charles Lin (2005).
155:Probability approach
140:Ensemble forecasting
130:Ensemble forecasting
124:Ensemble forecasting
759:Weather forecasting
605:University of Texas
88:Weather forecasting
707:2011-06-09 at the
552:2011-09-05 at the
394:2009-02-05 at the
356:2011-06-06 at the
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28:
277:forecast models.
263:tropical cyclones
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325:. Archived from
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256:false alarm rate
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49:Forecast models
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731:External links
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334:. Retrieved
327:the original
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248:intersection
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219:Verification
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166:
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113:
111:
91:
76:
67:Use of radar
35:
31:
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136:correlation
43:18:00
753:Categories
336:2008-12-31
299:References
233:Rain gauge
114:nowcasting
102:Nowcasting
57:rain gauge
764:Hydrology
198:Hong Kong
185:Australia
147:(ECMWF),
705:Archived
621:Archived
600:(2007).
568:(2008).
550:Archived
502:Archived
479:Archived
410:(2007).
392:Archived
354:Archived
281:See also
330:(PDF)
319:(PDF)
275:ECMWF
261:With
95:flood
415:NASA
273:and
244:bias
189:The
30:The
271:NAM
267:GFS
45:GMT
36:QPF
755::
677:^
422:^
378:^
321:.
306:^
339:.
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