Southeastern Texas historic rain of 18 April 2016 by Richard H. Grumm and Charles Ross National Weather Service State College, PA 16803

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1 Southeastern Texas historic rain of 18 April 2016 by Richard H. Grumm and Charles Ross National Weather Service State College, PA Introduction Extremely heavy rainfall across southeastern Texas (Fig.1) produced major flooding in the Houston Metropolitan area during the morning hours of 18 April The flooding disrupted most human activities closing roads and causing the Houston areas schools to close for two days due to water on roads, and led to at least eight confirmed deaths (Houston Chronicle, AP 2016). Observed rainfall was likely over inches (Table 1 based on NWPNS) based on gage data. The Stage-IV data (Fig. 1) indicated 250 to 300 mm (14 inches) of rain for the 24 hour period ending at 1800 UTC 18 April The Stage-IV gridded rainfall 24 hour total ending at 1800 UTC 18 April (Fig. 2) indicated areas in southeastern Texas had 75 to 125% of the 100 year recurrence interval in the 24 hour period. The Average Recurrence Interval (ARI) is based on the blended NOAA14 and NOAA40 data 1. The 6-hour period of heaviest rain was observed in the period of 0600 to 1200 UTC (Fig. 2 lower panel). The impacts of the event included extreme flooding, closed schools, and 8 fatalities. A critical issue in the Houston area is underpasses. The majority of the fatalities involved individuals driving into deeply flooded under passes. One individual died after she drove around a barrier before the steep drop-off into the under pass. The other 7 people drove into flood under passes. The City is investigating better means to prevent this type of tragedy. Many of the deaths occurred in under passes where similar deaths have occurred before (Houston Chronicle 2016). Based on decades of research on heavy rainfall (Junker and Schneider 1997; Junker et al. 1999; Grumm and Hart 2000; Hart and Grumm 2000) this was an ideal pattern for heavy rain, often classified as a Maddox-Synoptic event (Maddox et al 1979) with deep southerly flow and a plume of relatively deep moisture. The standardized anomalies often help characterize the potential for heavy rainfall (Grumm 2011). Most heavy rainfall events involve deep and persistent plumes of moisture, which as will be shown, occurred with this event. Forecasting heavy rainfall has traditionally relied on a combination of pattern recognition and the output of forecast system quantitative precipitation forecasts (QPF). As forecast systems improve probabilistic data can assist with this problem. Ideally, if a forecast system can predict the pattern then the system should produce the lift and simulate rainfall within the pattern. The location and amount of rainfall will likely be incorrect. But the pattern in the system should be related to the QPF. Rapidly updating convective allowing high resolution models offer some improvement in QPFs (Sun et al. 2014) especially in convective environments. 1 Over Texas the older NOAA40 data is still used.

2 This event was highly convective in nature and thus the expected predictability might be considered to be on the low side. However, due to the strong synoptic forcing and the correct forecast of the pattern the event was relatively well predicted. It will be shown that the NCEP GEFS forecast over 3 inches of rain in southeast Texas. The use of climate data, such as ARI (Fig. 2), may help identify where heavy rain has fallen based on radar estimates and gridded rainfall estimates. These data may also help improve identifying potential areas of rainfall when these data are displayed relative to model or forecast system QPFs. This paper will document the pattern in which the heavy rainfall occurred and present methods which may aide anticipating and characterizing this and similar events. The focus is on using climate data to identify the potential for heavy rainfall including the pattern in which the event occurred and the value of Average recurrence intervals (ARI: NOAA14) to characterize the observed and forecast precipitation. The estimate precipitation (QPE) and forecast precipitation (QPE) are shown along with ratios relative to the ARI values. Forecasts from several NCEP forecasts systems are also shown relative to the ARI values as ratios. 2. Methods and data The climate forecast system re-analysis (CFSR) data was used to reconstruct the pattern and the standardized anomalies associated with the event. The CFSR is used to show the pattern, which forecasters often use to gain confidence in a potential significant weather event. These same patterns, when forecast may produce high end QPF which may reinforce confidence in the forecast. The Stage-IV rainfall data (Seo 1998) was used to estimate the rainfall over 6-hour intervals and produce accumulations in 12, 24, and 48 hour intervals. The NOAA14 data were used to produce the recurrence intervals. The focus here was on 100 year ARI values of 6 and 24 hour durations. The 6 and 24 hour durations at 100 recurrence intervals have been seamed together with NOAA40 data to cover the entire USA. Other intervals do not cover Texas and most of the western United States and thus were used limitedly herein. The NCEP GEFS and GFS data were used to forecasts of the extreme QPF. Both QPF and QPE the ARI data was used to compute a QPF/ARI and QPE/ARI ratio respectively expressed as a percentage. In all images showing the ratios the basic shaded and displayed data was computed as: ARI-Ratio = 100* ( QPF / ARI) (1) For analysis such as stage IV data the QPE is substituted for the QPF and is thus interpreted the same way.

3 3. Results a. The pattern The 500 hpa pattern over the United States from 0000 UTC 16 to 1200 UTC 18 April 2016 (Fig. 3) showed a large scale blocking ridge over the Great Lakes and a weak cut-off 500 hpa low over the Rocky Mountains. The height anomalies in the ridge were on the order of 2σ above normal. The important aspect of the Texas rain event was the implied deep southerly flow from the Gulf of Mexico over east Texas into the central Plains. The brought a plume of high precipitable water (PW) air from southeastern Texas to Canada (Fig. 4). Strong low-level southerly winds were present at 850 hpa (not shown) and there were strong low-level winds (Fig. 5) over much of eastern Texas northward into the central Plains. The PW viewed in 6-hour increments (Fig. 6) showed PW anomalies in the +2 to +3σ range in eastern Texas. In addition to the high PW air the 0.5x0.5 degree CFSR data indicated convective instability over southern Texas. Most of the higher CAPE (Fig. 7) was west and south of the region of heavier rainfall. Cleary, deep moisture and convective instability played critical role in the rainfall event. Based on satellite data it was clear that the high CAPE as on the warm side of a shallow eastwest boundary. This boundary propagated to the south and the new convection developed over the boundary (Fig. 8). The meridional blocking flow allowed the flow of moisture out of the Gulf which interacted (WV imagery on CIMMS blog) the shortwave as it exited the southern Rockies. b. GEFS forecasts The GEFS was able to predict the larger scale blocking ridge and cut-off low over the Rocky Mountains (not shown). This it forecast the plume of deep moisture and southerly flow. This in turn provided a response in the GEFS to forecast heavy rain in south east Texas (Figs. 9 & 10). Due to the strong southerly flow the GEFS forecast the potential for heavy rain, in excess of 75 mm or more QPF as shown in Figure 9 with 6 days of lead-time. The forecast from 0000 UTC April 2016 showed the lowest probability but the forecasts converged over time and as early as 0000 UTC 14 April the GEFS had a close 75 mm contour in the ensemble mean (Fig. 9b). The mean QPF in the GEFS showed the broader heavy precipitation pattern which the Texas event occurred within (Fig. 10). These data show the mean QPF from all 21-member and each members 100 mm contour. Several GEFS members were forecasting over 100 mm of QPF in the 24 hours ending at 0000 UTC 9 April The GEFS QPF for the 24 hour period ending at 0000 UTC 19 April relative to the GEFS-R internal model climatology is shown in Figure 11. These data show that 3 inches (75mm) is close to the all-time highest QPF forecast in the GEFS-R. The operational model was forecast a near to record event within the model phase space. c. Deterministic forecasts-ncep GFS

4 The NCEP GFS forecasts of 24 and 6 hour QPF relative to the NOAA14/40 data indicated that the GFS was forecasting a heavy rain event in eastern Texas (Figs. 12 & 13). The 24 hour QPF indicated over 6 inches of 6 QPF which was within the 75 to 100% 24-hour duration 100 year recurrence intervals. The 1200 UTC 16 April GFS actually had some areas where the QPF/ARI ratios exceed 1 (over 100%). Thus the ARI indicated potential for a near 100 year recurrence interval rainfall event. Similar to the GEFS, the GFS had issues with the extreme amounts and issues with the location. It should be noted that the GFS finer resolution likely contributed to the 5-7 inch amounts verse the 3-4 inch amounts in the GEFS. The GFS 6-hour QPF to 6-hour ARI ratios showed a less organized signal. There was considerable run-to-run variation and the best signals were forecast for the periods ending at 0600 and 1800 UTC (Fig. 13). There was a relatively QPF minimum in the GFS at 1200 UTC (not shown). d. NCEP 3km HRRR The HRRR was compared to the 6-hour ARI as the NCEP version only runs for 15 hours and NOAA40 data over Texas is for 6 and 24 hours at this time. Six HRRR runs on 18 April show the QPF and QPF/ARI ratios valid for the 6 hour period ending at 1200 UTC 18 April 2016 (Fig. 14). These data show that at times, the HRRR forecast over 8 inches of QPF and the QPF/ARI ratios were in the 125% range. The finer resolution 3km HRRR produced more QPF than the ~16km GFS. But like the GFS and GEFS the exact locations of the higher QPF values varied by run and the HRRR too was unable to get the extreme values observed in gages. 4. Conclusions An extremely heavy rainfall event affected southeastern Texas on 18 April The heavy rain in the Houston area produced flooding and extreme flooding in Urban areas to include many deep under passes in the City of Houston. The flooded under passes were the location of 8 fatalities during the event. Thus, despite relatively good forecasts from available guidance, the loss of life was not mitigated. The pattern was nearly ideal for heavy rainfall and is well established pattern for heavy rain. The NCEP models were able to predict the pattern and thus they were able to forecast relatively high QPF values. The GEFS-R M-Climate data verse the GEFS QPF provided a check to determine how significant the QPF was. As shown in Figures 8 & 9, the GEFS forecast a high probability of 75 mm or QPF and individual members were forecasting over 100 mm of rainfall. These numbers seem small relative to the extreme rainfall amounts observed. However, based on the GEFS climatology, the 75 to 100 mm QPFs (3-4 inches) represented a record rain event in the forecast system for the time of year. In this case the GEFS was forecasting close to a record event within the model atmosphere which translated to record event over portions of southeastern Texas. The GEFS got the concept of an extreme rain event correct in the correct general region. It could not and should not be expected to forecast the correct location and the extreme amounts as observed.

5 The NCEP GFS and HRRR forecasts were compared to the ARI data. This provided a check of the QPF relative to a climate reference. These data too indicated that the GFS and HRRR were forecasting a high end QPF event with several forecasts showing that the model QPF would be 75 to 125% of the 24 hour 100-year ARI. Relative to the observed amounts by spotters and the gridded Stage-IV data, the GEFS grossly under predicted the extreme rainfall. However, this relatively coarse system was in fact forecasting a record event within its forecast phase space. Additionally, the GFS and HRRR under forecast the QPF, however both systems QPF ranged from 75 to 125% of the 24 hour and 6 hour 100-year ARI values suggesting that they were capable of indicating the potential for a high end rainfall and thus a potentially, a high end flood event. 5. Acknowledgements NWS extreme QPF team for case information and access to ARI data. 6. References Associated Press 2016a: Louisiana, Mississippi: Thousands of homes damaged by floods. AP 2016 and similar stories. Associated Press 2016b-: Unusually widespread flooding across Louisiana, Mississippi. AP 2016 and similar stories 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, Grumm, R. H. 2011: New England Record Maker Rain Event of March National Weather Association, Electronic Journal of Operational Meteorology, 2011-EJ4 Grumm, R.H. and R. Hart, 2000: Anticipating heavy rainfall events: Climatological aspects. Preprints, Symposium on Precipitation Extremes: Prediction, Impacts, and Responses, Albuquerque, New Mexico, Amer. Meteor. Soc Hart R., and R.H. Grumm, 2000: Anticipating heavy rainfall events: Forecast aspects. Preprints, Symposium on Precipitation Extremes: Prediction, Impacts, and Responses, Albuquerque, New Mexico, Amer. Meteor. Soc Junker, N.W. and R.S Schneider, 1997: Two case studies of quasi-stationary convection during the 1993 great Midwest flood. National Weather Association Digest., 21,5-13., R.S. Schneider, and S.L. Fauver, 1999: A Study of heavy rainfall events during the great Midwest flood of Wea. Forecasting., 14,

6 Seo, D.J., 1998: Real-time estimation of rainfall fields using rain gauge data under fractional coverage conditions. J. of Hydrol., 208,

7 Figure 1. Stage-IV gridded rainfall showing the total rainfall (mm) in 6-hour intervals periods ending at a) 1800 UTC 17 April through e) 1800 UTC 18 April to The total 24 hour rainfall is shown in panel (f). Return to text.

8 LOCATION AMOUNT COUNTY LITTLE MOUND Harris MATHIS RD CYPRESS SHARP Harris ROAD TRAILSIDE Harris 8 ENE FAYETTEVILLE Austin SO. MAYDE CK Harris US 290 NW STATION PARK Harris AND R CYPRESS CK NR HOCKLEY Harris (SHARP MILL CREEK NEAR Austin BELLVILLE WHITE OAK BAYOU AT Harris LAKEVIEW 5 NNW MISSION BEND Harris GREENS Harris BAMMEL N. HOU BUFFALO BAYOU AT US Waller FM Montgomery HUFSMITH Montgomery 6 WSW JERSEY VILLAGE Harris BRAYS BELTWAY Harris 8 WILLOW CK NEAR Harris TOMBALL (KUYK BRAYS BAYOU AT ALIEF Harris CYPRESS Harris INVERNESS FO SAN FELIPE Austin 4 WSW THE WOODLANDS Harris 5 W JERSEY VILLAGE Harris 4 SE TOMBALL Harris

9 LOCATION AMOUNT COUNTY LITTLE MOUND MATHIS RD Harris CYPRESS SHARP ROAD Harris TRAILSIDE Harris 8 ENE FAYETTEVILLE Austin SO. MAYDE CK Harris US 290 NW STATION PARK AND R Harris CYPRESS CK NR HOCKLEY (SHARP Harris MILL CREEK NEAR BELLVILLE Austin WHITE OAK BAYOU AT LAKEVIEW Harris 5 NNW MISSION BEND Harris GREENS BAMMEL N. HOU Harris BUFFALO BAYOU AT US Waller FM Montgomery HUFSMITH Montgomery 6 WSW JERSEY VILLAGE Harris BRAYS BELTWAY Harris WILLOW CK NEAR TOMBALL (KUYK Harris BRAYS BAYOU AT ALIEF Harris CYPRESS INVERNESS FO Harris SAN FELIPE Austin 4 WSW THE WOODLANDS Harris 5 W JERSEY VILLAGE Harris 4 SE TOMBALL Harris Table 1. List of rainfall (inches) at select towns within select counties. Data were limited to reports over 10 inches. Return to text.

10 Figure 2. Upper panels shows the total rainfall in inches and the ratio of the 100 year 24-hour ARI for the period ending at 1800 UTC 18 April. The lower panels show the 6-hour rainfall ending at 1200 UTC 18 April and the 100 year 6-hour rainfall to the 100 year 6-hour ARI. Rainfall contours in powers of 2 inches. Shading is the ratio as a percentage as in the color bars. Return to text.

11 Figure 3. CFRSR data showing 500 hpa heights (m) and height anomalies in 12 hour increments from a) 0000 UTC 16 April to f) 1200 UTC 18 April Return to text.

12 Figure 4. As in Figure 3 except for precipitable water. Return to text.

13 Figure 5. As in Figure 4 except for 850 hpa wind speeds (ms-1) in 6 hour increments from a) 1200 UTC 17 April through f) 1800 UTC 18 April Return to text.

14 Figure 6. As in Figure 5 except for precipitable water (mm) and precipitable water anomalies. Return text.

15 Figure 7. As in Figure 6 except for convective available potential energy.. Return text.

16 Figure 8. Visual image from 1733 UTC 18 April taken from CIMMS high resolution loop of the convection over southeastern Texas. Arrow points out the boundary which extended to the coast where convection formed over as the boundary propagated to the south. The CIMMS blog had several good image loops of the convective evolutions. Return text.

17 Figure 9. NCEP GEFS forecasts of the probability of 75 mm or more QPF in the 24 hour period ending at 0000 UTC 19 April Data from NCEP GEFS initialized at a) 0000 UTC 13 April, b) UTC 14 April, c) 0000 UTC 15 April, d) 0000 UTC 15 April, e) 0000 UTC 17 April and d) 1200 UTC 17 April Shading shows the probability and solid line shows ensemble mean 75mm contour if present. Return to text.

18 Figure 10. As in Figure 9 except GEFS ensemble mean QPF (shaded) and each members 100 mm contour if present. Return to text.

19 Figure 11. GEFS 24 hour QPF and QPF relative to GEFS_R climatology for the 24 hour period ending at 0000 UTC 19 April GEFS forecast cycles were from 0000 UTC 16 and 17 April Return to text.

20 Figure 12. NCEP GFS forecasts of QPF (inches) and the ratio of the 24 hour QPF to the 24 hour 100 year ARI in percent (shaded). GFS forecasts shown all valid at 0000 UTC 19 April initialized at a) 1200 UTC 15 April, b) 0000 UTC 16 April, c) 1200 UTC 16 April, d)0000 UTC 17 April, e)1200 UTC 17 April and f) 1800 UTC 18 April. Return to text.

21 Figure 13. As in Figure 12 except for 6-hour QPF and 6 hour ARI. Return to text.

22 Figure 14. NCEP 3km HRRR forecasts of QPF for the 6-hour period ending at 1200 UTC 18 April 2016 and the 6-hour 100 year QPF/ARI ratio for successively initialized HRRR forecasts initialized from a) 0100 UTC through f) 0600 UTC 18 April Return to text.