Anticipating record events using patterns and pattern forecast: Mid-Mississippi Valley floods of April 2011

Transcription

1 Anticipating record events using patterns and pattern forecast: Mid-Mississippi Valley floods of April 2011 Richard H. Grumm National Weather Service State College, PA Abstract: A persistent pattern produced a multi-day rain event which resulted in devastating flooding over portions of the Mid-Mississippi Valley in April Successive heavy rains, or meteorological events from April 2011 produced a high impact hydrological event over the region. Each rainfall event was meteorologically significant but the collective impact of the persistent pattern played a critical role in the historic flooding which followed. Composites of the pattern indicated that in the mean, a plume of high precipitable water air, a strong low-level jet, and a persistent jet entrance region remained over the region for over 7 days. Each meteorological event impacted slightly different regions. Successive rainfall events over a relatively similar geographic area were a contributing factor to the severity and impact of this long duration hydrologic event. Standardized anomalies are often used to determine the meteorological and climatological rarity of a weather event. Applying this concept to patterns over periods of 1 to 10 days may help understand some of the historically significant events. Applying this concept to numerical output and ensemble output may aid in predicting these historically significant events. This concept is applied here to the Mid-Mississippi Valley floods of April 2011.

2 1. INTRODUCTION A devastating heavy rainfall event affected the Mid-Mississippi Valley (MMV:AP2011a and AP2011b) from April The overall flooding was the result of successive heavy rainfall events over an 8 day period which produced over 12 inches of rain over portions of Missouri and Arkansas (Fig. 1). There were some days where the heavy rainfall axis shifted to the north and then to the south (Fig. 2). Thus, many areas experienced heavy rainfall events separated by periods of 1-2 days. But the cumulative effect was devastating. In addition to the heavy rainfall, the persistent pattern produced widespread severe weather and several deadly tornadoes. The flooding over portions of the MMV was characterized as devastating and historic (AP: 2011b). The wet pattern ended with a strong frontal system which produced the deadly 27 April 2011 southern United States tornado outbreak. The general patterns associated with heavy rainfall are well documented (Bodner et. al 2011; Junker et. al. 1999). They focused on long duration events, comparing the 1993 and 2008 heavy rainfall episodes during which successive heavy rainfall affected a similar geographic region of the United States over several weeks. They found that heavy rainfall in the central United States is often associated with a persistent deep trough over the western United States and a ridge over the eastern United States. This large scale pattern favors the development for a stronger than normal low-level southerly jet (Bodner et. al 2011). In their study, each individual rain event was associated with over 75 mm of precipitation were associated with +2.5σ or greater 850 hpa v-wind anomalies upstream of the region affected by heavy rainfall. Additionally, these events were also associated with +2σ or greater precipitable water (PW) anomalies 850 hpa moisture flux anomalies in excess of +3.5σ. The more generalized concept of using standardized anomalies to identify meteorologically significant weather events in the eastern United States identified by Hart and Grumm (2001) and Grumm and Hart (2001). Graham and Grumm (2010) conducted a similar study over the western United States. The

3 spectrum of events included many significant and well documented synoptic scale significant winter storms, ice storms, wind events and heavy rainfall events. The list includes a few surprises including the Yellowstone tornado event of July Heavy rainfall and flooding events dominated the list of top-10 moisture anomaly events in the western United States (Table 3d: Graham and Grumm 2010). These studies demonstrated that many historic and record events were associated with significant anomalies. Furthermore, these studies suggest that standardized anomalies may be of value in distinguishing an ordinary from a potentially extraordinary event. The tie in of standardized anomalies in the forecast process and heavy rainfall was demonstrated by Junker et al. (2008). Computing anomalies from numerical weather prediction models and ensembles, they demonstrated how forecast of standardized anomalies of key parameter associated with heavy rainfall can provide confidence in the potential for heavy rainfall. In the western United States, strong low-level winds, above normal precipitable water and above normal 850 hpa moisture flux were good predictors of potentially heavy rainfall events. These parameter help define the character and the strength of the moist conveyor belt (Carlson 1980) or atmospheric river (AR: Ralph et. al 2006; Nieman et. al 2002;Neiman et al. 2008) often associated with larger scale heavy rainfall events. When used with probabilistic ensemble quantitative precipitation forecasts, these forecast may aid in identifying potentially rare high end precipitation events. The event of April 2011 had persistent and anomalous moisture and accompanying anomalous southerly flow, key ingredients for a significant heavy rainfall event (Doswell et. al 1996) and for historic events (Bodner et. al 2011 and Junker et. al 2009). This pattern was diagnosed over periods of 1 to 7 days and this persistent pattern was predicted by the NCEP GFS and Global Ensemble forecast system (GEFS). This case illustrates the potential value of evaluating a persistent synoptic pattern and significant anomalies to predict heavy rainfall.

4 This paper will document the historic and devastating rainfall and flooding over the MMV on April The focus is on the persistent synoptic scale pattern and anomalies associated with this meteorologically and climatologically significant event over periods of 1 to 7 days in duration. The NCEP GFS 00-hour forecasts are used to show the composite of the pattern. Forecasts from the NCEP ensemble forecast systems (EFS) and GFS forecasts are presented to show the value of using multi-anomalies to assess the persistence of a pattern know to produce heavy rainfall and flooding. 2. METHODS AND DATA The 500 hpa heights, 850 hpa temperatures and winds, other standard level fields were derived from the NCEP Global Forecast System (GFS), North American Mesoscale Model (NAM), Global Ensemble Forecast System (GEFS), Short Range Ensemble Forecast (SREF) and the NCEP/NCAR (Kalnay et al. 1996) reanalysis data. The means and standard deviations used to compute the standardized anomalies were from the NCEP/NCAR data as described by Hart and Grumm (2001). Anomalies were displayed in standard deviations from normal, as standardized anomalies and are used to show the anomalies, probability of heavy rainfall and Quantitative Precipitation Forecasts (QPF) associated with this event. All data were displayed using GrADS (Doty and Kinter 1995). The standardized anomalies computed as: SD = (F M)/σ ( ) Where F is the value from the reanalysis data at each grid point, M is the mean for the specified date and time at each grid point and σ is the value of 1 standard deviation at each grid point. Model and ensemble data shown here were primarily limited to the GFS and GEFS. The NAM and SREF data were also available for use in this study. Displays will focus on the observed pattern and some forecast issues associated with the pattern.

5 Both the unified precipitation dataset (UPD: Seo 1998) and the stage-iv precipitation data (Lin and Mitchell 2005; Nelson et. al. 2010) were used to evaluate the rainfall associated with this event. The stage-iv data are presented in this document. In addition to computing standardized anomalies for distinct times associated with individual meteorological rainfall events, anomalies were computed by averaging the fields and each instantaneous standardized anomaly value over 1 to 7 day periods. This was facilitated identifying the signal and the persistence in the long-term signal of the pattern. This concept was then used to obtain multi-day pattern forecasts from the NCEP GFS and GEFS. For brevity, times will be displayed in day and hour format such a 25/0000 UTC signifies 25 April 2011 at 0000 UTC. 3. METEOROLOGICAL OVERVIEW i. Synoptic scale pattern The multi-day composite pattern from 19/1200 through 28/1200 UTC (Fig. 3) showed the persistent 500 hpa ridge, with +1σ height anomalies over the western Atlantic. North of this ridge, a persistent 250 hpa jet with +1 to +2σ winds was present (Fig. 3b). Beneath the jet the 850 hpa winds showed a persistent flow from the western Gulf into the MMV and Ohio Valleys (Fig. 3c). This low-level jet was associated with the plume of deep moisture and above normal precipitable water (Fig. 3d) with +1 to +2σ above normal PW anomalies focused over the MMV for the 7 day period. These data show that a jet entrance region and moisture plume were evident over the Ohio and MM Valleys for a 7-day period. The heavy rains from 24/0000 through 26/0000 UTC (Figs. 2c-d) indicated a 48 hour period of extremely heavy rainfall. The composites for the 48-hour period (Fig. 4) show the strong 500 hpa ridge over the western Atlantic and the persistent jet entrance over the MMV (Fig. 4c). The PW field shows the quasi-

6 stationary frontal boundary with 2 to 3σ above normal PW anomalies on the warm side of the implied boundary. This persistent pattern for the 48 hour period is a pattern often associated with heavy rainfall, normally examined in individual 3-6 hourly increments. These data could be examined over 6- to 24-hour periods to examine the impact of each individual event. Showing all time periods and individual rainfall and severe episodes would be prohibitive. For brevity select PW data valid at 0000 UTC April is shown (Fig. 5). These data show that PW anomalies were as high as 3σ above normal and that the orientation of the boundary varied from east-west to nearly north-south at times. These data also show the shift of the PW field to the south which (Fig. 5c) at 21/0000 UTC which explained heavy rain farther south (Fig. 2b) which produced a break in the rain over most of eastern Missouri and Illinois, though a new surge of rain over western Missouri indicated emerging meteorological rainfall event. The 850 hpa winds and wind anomalies (Fig. 6) showed several surges of strong southerly winds. Though not shown, the first surge of +3 to +4σ 850 hpa winds occurred at 20/0000 UTC from Arkansas, across southern Illinois into Indiana. The strongest 850 hpa winds at 850 hpa were observed at 26/0000 UTC (Fig. 6e) when the winds were over 4σ above normal over eastern Arkansas. There was considerable daily variability in the moisture and wind patterns (Figs 4 and 5) which lead the variability of where the heavy rain was observed over the 7-day period (Fig. 2). Despite this variability, the relative persistence led to the extremely heavy rainfall over the 7-day period (Fig. 1). ii. Forecasts-GFS The 20/1200 UTC 5-day composite forecast (Fig. 7) shows the same pattern found in the GFS 00-hour forecasts. Due to 6-hourly climatological data, the composite is comprised of 6-hourly forecasts for the period shown. These data clearly show the persistent 500 hpa ridge over the western Atlantic with the

7 enhanced 250 hpa jet over the ridge (Fig. 7b). The strong low-level 850 hpa jet (Fig. 7c) and the plume of high PW were clearly evident in these forecasts. This forecast cycle and several other forecast cycles showed that the persistent pattern was predicted by the GFS. This was true over 24, 48, 72, 96 and 120 hour increments. The 20/1200 and 23/0000 UTC GFS are used to show the pattern for the period of heavy rainfall for the period of 24/0000 through 26/0000 UTC (Figs. 8 and 9). These forecasts are rather similar each shows, with subtle differences, the persistent 500 hpa ridge, the strong and enhanced 250 hpa jet over the ridge, and the low-level response with a strong LLJ and a plume of high PW air focused over the MMV and Ohio Valleys during the 48 hour period. Potentially valuable information on the potential for a long duration heavy rainfall event. The 23/0000 UTC composite forecast for the period of 23/0000 through 28/1200 UTC (Fig. 10) shows the same general pattern as in the previous images. However, the pattern had become progressive. The plume of high PW from the Gulf appears truncated as dry air (not shown) move across the western Gulf States and the LLJ jet shifted eastward. This pattern is consistent with heavy rainfall in the MMV and Ohio Valleys though it shows some drying in the southern most areas. Composite QPF from 6 GFS cycles (Fig. 11) show the heavy rainfall over the MMV. These data show that over the period of each forecast, ending at 26/0000 UTC, the GFS focused the heaviest rainfall over the MMV and Ohio Valleys. Rainfall amounts were generally over 96 mm with some forecasts showing around 128 mm of QPF. iii. Forecasts-GEFS The mean pattern from the 21-member GEFS for the period from 20/1200 through 26/1200 (Fig. 12) and 24/0000 through 26/0000 (Fig. 13) show similar features to those shown in the analyzed composites and

8 in the GFS. These data imply a high probability of this pattern verifying and they imply a potentially predictable pattern. Similar results can be obtained by using GEFS forecasts from 17 through 24 April The GEFS QPF and probability of 75 mm and 100 mm for the period of heavy rain from 24/0000 through 26/0000 UTC (Fig. 14) and the longer period of 22/1200 through 28/1200 UTC (Fig. 15) indicated that correctly predicting the large scale pattern produced a realistic QPF over the affected region. Details of these forecasts, obtained by subtracting the ensemble mean from the verifying QPF (not shown) indicate a slight north and westward shift of the QPF shield and areas of maximum QPF relative to the observed rainfall. The potential for over 100 mm of QPF over the region was predicted several days in advance (Fig. 16). Though not shown, there was considerable skill in predicting the overall pattern at these ranges too, which produced the relatively useful QPFs. 4. CONCLUSIONS The persistent pattern (Fig. 3) over the 7 day period of April 2011 showed a signal often associated with many heavy rainfall events when examined using hourly or 6-hourly model or re-analysis data. However, this represents the mean pattern over 7 days, encompassing several meteorologically significant events which typically lasted hours. The persistent jet entrance region and moisture plume over the region implies that the pattern often associated with rainfall endured. The key feature was likely the subtropical ridge over the western Atlantic. Strong 250 hpa jets and surge of high PW air are common features on the periphery of strong subtropical ridges. A similar ridge was present over Russian during the record heat of July-August 2010 and a strong jet was present over that ridge over Scandinavia and northern Russia (Grumm 2011).

9 Bodner et al (2011) examined the record rainfall events of 1993 and Using composites over the periods of heavy rain for those two events, they found a persistent signal, similar to the signal shown here. If these composites have value in identifying heavy rainfall events in a case study mode, they clearly can be used to better anticipate similar events in a forecast mode. Multi-day output from deterministic models and global ensemble data could be used to improve the diagnosis and prediction of potentially devastating record heat and rainfall events. The composites over the period of the long duration event (Fig 3) are important in identifying a pattern that could include several heavy rain episodes over a prolonged period of time. The composites of individual periods of prolonged heavy rainfall (Fig. 4) are also important as they relate the impact of a prolonged rain event. Finally, the short-term individual periods are important for the details of when it may rain heavily in a relatively short period. This time intervals relate to significant broad scale river flooding to the scales of short-term flash flooding. There was considerable daily variability in the moisture and wind patterns (Figs 4 and 5) which lead the variability of where the heavy rain was observed over the 7-day period (Fig. 2). Despite this variability, the relative persistence led to the extremely heavy rainfall over the 7-day period (Fig. 1). Forecasting gauging the potential for heavy rainfall is an area where ensemble forecast output has not been fully established. Some key features associated with heavy rainfall events include: A plume of high PW air into the affected region with over +2.5SD PW anomalies. A deep 500 hpa trough with -1 to -2SD height anomalies to the west of the affected area A strong low-level jet at 850 and 925 hpa with v-wind anomalies over 2 SDs above normal A strong upper-level 250 hpa jet near the affected region A general area of low pressure in or just west of the affected region

10 The GFS and GEFS QPFs showed considerable skill in delineating the region susceptible to heavy rain. There was some bias in placing the QPF to the north and west of where the axis of heaviest rain was observed. Despite this error, with the ability to correctly produce the persistent pattern, the GFS and GEFS were able to produce heavy rains in the correct geographic area. Both systems under predicted the amount of rainfall relative to observations. The coarse 75km GEFS would not be expected to produce the higher end precipitation and is incapable of resolving the convective evolutions. The higher resolution GFS at approximately 27km resolution had higher over all QPFs but also under predicted the maximums rainfall. Finer resolution models and EFS may have predicted higher amounts of rainfall. However, the convective evolutions associated with this event (not shown) suggest that the exact details would not be predicted by any forecasts system. Thus, it may be of value to know what an internal model and internal EFS climatologically significant rainfall is. These data could then be used to add value to the forecast. Knowing when a forecast system is predicting near record QPF is likely helpful in knowing when a meteorologically and climatologically significant event is possible. 5. Acknowledgements Thanks to Neil Stuart and Wes Junker for valuable editorial and meteorological information. Wes also provided a list of heavy rainfall events over the Gulf States for comparison purposes. The data used in this study was made available in real-time and for post analysis by the Pennsylvania State University. 6. REFERENCES Associated Press, 2011a: Storms bring deadly tornado, flooding to Midwest (Daily wire reports with similar titles were published from 24 to 27 April 2011.)

11 Associated Press, 2011b: Floodwaters threaten to overrun Midwest levees (Daily wire reports with similar titles were published from 24 to 27 April 2011.) Bodner, M.J., N.W Junker, R.H. Grumm and R.S Schumacher 2011: Comparison of Atmospheric Circulation Patterns during the 2008 and 1993 Historic Midwest floods. Accepted NWA Digest March Bentley, M. L., and T. L. Mote, 1998: climatology of derecho-producing mesoscale convective systems in the central and eastern United States Part I: Temporal and spatial distribution. Bull. Amer. Meteor. Soc., 79, Carbone, R. E., J. D. Tuttle, D. A. Ahijevych, and S. B. Trier, 2002: Inferences of predictability associated with warm season precipitation episodes. J. Atmos. Sci., 29, Carlson, T.N 1980: Airflow through Midlatitude Cyclones and the comma head pattern. Mon. Wea. Rev.,108, Corfidi, S.F., N.W. Junker, F.H. Glass, 1990: The Louisiana/Mississippi Flash Flood and Severe Weather Outbreak of November th Conf. on Severe Local Storms, Kananaskis Park, Alta Doswell,C.A.,III, H.E Brooks and R.A. Maddox, 1996: Flash flood forecasting: ingredients based approach. Wea. Forecasting, 11, Doty, B. E., and J. L. Kinter III, 1995: Geophysical data and visualization using GrADS. Visualization Techniques Space and Atmospheric Sciences, E. P. Szuszczewicz and Bredekamp, Eds., NASA,

12 Fritsch, J., R. Kane, and C. Chelius, 1986: The Contribution of Mesoscale Convective Weather Systems to the Warm-Season Precipitation in the United States. J. Appl. Meteor., 25, Graham, R.A and R.H. Grumm, 2010: Utilizing normalized anomalies to assess synopticscale weather events in the western United States. Wea. Forecasting,25, Grumm, R.H., and R. Hart, 2001a: Anticipating Heavy Rainfall: Forecast Aspects. Preprints, Symposium on Precipitation Extremes, Albuquerque, NM, Amer. Meteor. Soc., Grumm, R.H., and R. Holmes, 2007: Patterns of heavy rainfall in the mid-atlantic. Pre-prints, Conference on Weather Analysis and Forecasting, Park City, UT, Amer. Meteor. Soc., 5A.2. Grumm, Richard H. 2000, "Forecasting the Precipitation Associated with a Mid-Atlantic States Cold Frontal Rainband", National Wea. Digest,24, Hart, R. E., and R. H. Grumm, 2001: Using normalized climatological anomalies to rank synoptic scale events objectively. Mon. Wea. Rev., 129, Hayes, 2011: Record floods of greater Nashville: Including flooding in Middle Tennessee and western Kentucky, May NOAA/NWS, 67pp. Lin, Y. and K.E. Mitchell, 2005: The NCEP Stage II/IV hourly precipitation analyses: development and applications. Preprints, AMS 19 th Conference on Hydrology, San Diego, CA. Paper 1.2.

13 Junker, N. W., R. S. Schneider and S. L. Fauver, 1999: Study of heavy rainfall events during the Great Midwest Flood of Wea. Forecasting, 14, Junker, N.W., R.H. Grumm,R.H. Hart, L.F Bosart, K.M. Bell, and F.J. Pereira, 2008: Use of normalized anomaly fields to anticipate extreme rainfall in the mountains of northern California.Wea. Forecasting, 23, , M.J. Brennan, F. Pereira, M.J. Bodner, and R.H. Grumm, 2009: Assessing the Potential for Rare Precipitation Events with Standardized Anomalies and Ensemble Guidance at the Hydrometeorological Prediction Center. Bull. Amer. Meteor. Soc., 90, Maddox,R.A., C.F Chappell, and L.R. Hoxit. 1979: Synoptic and meso-alpha aspects of flash flood events. Bull. Amer. Meteor. Soc., 60, Maddox, R.A., 1980: Mesoscale convective complexes. BAMS, 61, Maddox, R. A., 1983: Large-scale atmospheric conditions associated with midlatitude mesoscale convective complexes. Mon. Wea. Rev., 111, Maddox, R.A., K.W. Howard, D.L. Bartels, and D.M. Rogers: Chapter 17: Mesoscale Convective Complexes in the Middle Latitudes. Mesoscale Meteorology and Forecasting, American Meteorological Society, Maddox, R.A., 1980: Mesoscale convective complexes. BAMS, 61, Moore, J.T., F.H. Glass, C.E. Graves, S.M. Rochette, and M.J. Singer, 2003: The Environment of Warm-Season Elevated Thunderstorms Associated with Heavy Rainfall over the Central United States. Wea. Forecasting, 18, Neiman, P.J., F.M. Ralph, G.A. Wick, J. D. Lundquist, and M. D. Dettinger, 2008: Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the west coast of North America based on eight years of SSMI/satellite observations. J. Hydrometeor., 9, Nelson, B. R., D-J. Seo, D Kim, 2010: Multisensor Precipitation Reanalysis. J. Hydrometeor, 11, Neiman, P.J., F.M. Ralph, A.B. White, D.E. Kingsmill, and P.O.G. Persson, 2002: The Statistical Relationship between Upslope Flow and Rainfall in California's Coastal Mountains: Observations during CALJET. Mon. Wea. Rev., 130,

14 Nelson, B. R., D-J. Seo, D Kim, 2010: Multisensor Precipitation Reanalysis. J. Hydrometeor, 11, Ralph, F. M., G. A. Wick, S. I. Gutman, M. D. Dettinger, C. R. Cayan, and A. B. White, 2006: Flooding on California s Russian River: The role of atmospheric rivers. Geophys.Res. Lett., 33, L13801, doi: /2006gl Seo, D.J., 1998: Real-time estimation of rainfall fields using rain gauge data under fractional coverage conditions. J. of Hydrol., 208, Seo, D. J. and J. P Breidenbach, 2002: Real-Time Correction of Spatially Nonuniform Bias in Radar Rainfall Data Using Rain Gauge Measurements. J. Hydrometeorology, 3, Schumacher, R.S., and R.H. Johnson, 2005: Organization and Environmental Properties of Extreme-Rain-Producing Mesoscale Convective Systems. Mon. Wea. Rev., 133, Schumacher, R.S., and R.H. Johnson, 2006: Characteristics of U.S. Extreme Rain Events during Wea. Forecasting, 21, Stuart, N. and R. Grumm 2009, "The Use of Ensemble and Anomaly Data to Anticipate Extreme Flood Events in the Northeastern United States", Nat. Wea. Digest, 33, Tuttle, J. D., and C. A. Davis, 2006: Corridors of warm season precipitation in the central United States. Mon. Wea. Rev., 134, Wetzel, P.J., W.R. Cotton, and R.L. McAnelly, 1983: A long-lived mesoscale convective complex, Part II: Evolution and structure of the mature complex. Monthly Weather Review,105,

15 Figure 1. Total rainfall from 6 hourly data for the period of 1200 UTC 19 April 2011 through 1200 UTC 28 April Return to text.

16 Figure 2. As in Figure 1 except for 24-hour accumulated precipitation for the periods ending as specified. Dates were selected based on rainfall amounts. Days with lower overall rainfall are not shown but were used in the composite in Figure 1. Return to text.

17 Figure 3. Composite data and anomalies from 1200 UTC 19 to 28 April 2011 showing a) 500 hpa heights and anomalies, b) 250 hpa winds (ms-1) and anomalies, c) 850 hpa winds and anomalies and d) precipitable and precipitable water anomalies. The red square in panel a is the approximate location of Springfield, Missouri. Return to text.

18 Figure 4. As in Figure 3 except for composite pattern for the 48 hour period of 0000 UTC 24 through 0000 UTC 26 April Return to text.

19 Figure 5. As in Figure 3 except GFS 00 hour forecasts of PW and PW anomalies valid at 0000 UTC in 24 hour increments from a) 19 April through f) 24 April Return to text.

20 Figure 6. As in Figure 4 except for 850 hpa winds and wind anomalies in 24 hour increments from a) 0000 UTC 22 April through f) 0000 UTC 27 April Return to text.

21 Figure 7. GFS forecasts initialized at 1200 UTC 20 April 2011 showing composites of all forecasts from 1200 UTC 20 April through 0000 UTC 26 April Data include composite a) 500 hpa heights and anomalies, b) 250 hpa winds and anomalies, c) 850 hpa winds and anomalies, and d) precipitable water and anomalies.

22 Figure 8. As in Figure 7 except composite forecasts for the period of 0000 UTC 24 April 2011 through 0000 UTC 26 April Return to text.

23 Figure 9. As in Figure 8 except GFS initialized at 0000 UTC 23 April 2011 showing composite forecasts for the period of 0000 UTC 24 April 2011 through 0000 UTC 26 April Return to text.

24 Figure 10. As in Figure 9 except composite forecasts for the period of 0000 UTC 23\4 April 2011 through 1200 UTC 28 April Return to text.

25 Figure 11. GFS total accumulated forecasts for GFS initialized a) 0000 UTC 23 April 2011, b) 1800 UTC 22 April 2011, c) 1200 UTC 22 April 2011, d) 0600 UTC 22 April, e) 0000 UTC 22 April, f) 1800 UTC 21 April g) 1200 UTC 21 April, h) 0600 UTC 21 April, and i) 0000 UTC 21 April Return to text.

26 Figure 12. As in Figure 8 except for 21-member GEFS mean initialized at 1200 UTC 21 April for the period of 1200 UTC 20 April through 1200 UTC 26 April Return to text.

27 Figure 13. As in Figure 12 except 21-member GEFS valid for the period of 0000 UTC April Return to text.

28 Figure 14. GEFS forecasts of the probability of 75mm or more QPF in the 48 hour period ending at 0000 UTC 26 April 2011 and each members 75 mm QPF plotted over the mean QPF from the 21-member GEFS initialized at a) 0000 UTC 20 April 2011, b) 1200 UTC 21 April and c) 0000 UTC 22 April Lower panels are matched to the upper panels. Return to text.

29 Figure 15. As in Figure 14 except for the 100 mm precipitation for the period encompassing 1200 UTC 21 April through 1200 UTC 28 April Return to text.

30 Figure 16. As in Figure 14 except for GEFS forecasts for the period of 1200 UTC 20 April through 1200 UTC 28 April 2011 from forecasts initialized at 0000 UTC 19 April, 1200 UTC 19 April and 000 UTC 20 April Return to text.

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