National Weather Service-Pennsylvania State University Weather Events

Transcription

1 National Weather Service-Pennsylvania State University Weather Events Western Windstorm of 1-2 December 2011-Draft by Richard H. Grumm National Weather Service State College PA Abstract:. A strong anticyclone moved over the Pacific Northwest beneath a large upper tropospheric ridge. Low pressure over the southwestern United States combined with this anticyclone to the north to produced strong easterly flow over the western United States. The resulting strong winds produced hundreds of reports of winds in excess of 50 mph and reports of wind damage. Wind gusts over 100 mph were reported near Mammoth Lakes, California (140 mph), Steamboat Spring, Colorado (123 mph) and Centerville, Utah (102 mph). The strong gradient between the large anticyclone and the weak low produced anomalous easterly flow. During the height of the event, low-level winds were 2 to 4σ above normal during. These strong winds were predicted in the NCEP deterministic models and ensemble forecast systems several days in advance. This paper will document the event to include the pattern which produced this high impact high wind event. Forecasts from the NCEP SREF and experimental 16km SREF are used to address predictability issues associated with this event.

2 1. INTRODUCTION A widespread high wind event impacted much of the western United States on 1-2 December At least 7 sites reported wind gusts in excess of 90 mph on 1 December 2011 (Table 1). The strong winds downed trees, power lines, and tipped trucks from California eastward into the intermountain West (AP 2011a and 2011b). The winds snapped trees, damaged cars, and downed power lines leaving hundreds of thousands of people without power. High winds and wind damage was experienced in California, Utah, Nevada, Wyoming, Arizona and New Mexico. Snow was reported in portions of New Mexico, Colorado and Wyoming due to strong easterly winds. Reports suggested events of this intensity occur about once a decade. In California, the event was characterized as a Santa Ana wind event (Raphael 2003; Small 1993). Santa Ana winds typically are dry east or northeasterly winds which channel through the mountain passes and Canyons of the coastal ranges of southern California. The name is derived from one of the canyons, Santa Ana Canyon, through which the winds blow. The National Weather Service typically uses the term for offshore (northeast) winds greater than 25kts (Small 1993). High pressure over the Great Basin (Raphael 2003) and low pressure off the coast of southern California is the typical set-up for most Santa Ana wind events. The Santa Ana wind season typically runs from September through April with the peak occurrence in the month of December. These events, though variable in frequency, appear to occur more often in La Nina year with fewer events in El Nino years. A large Pacific anticyclone moved over northwestern North America on 1 December 2011 as low pressure developed over southern California. The strong gradient between the anticyclone to the north and the cyclone to the south produced a high wind event over much of the intermountain west and along the California coast on 1-2 December Interestingly, in this event the low pressure was located over California and Nevada and thus the winds in southern California had a more northerly component during this event than in a typical Santa Ana event. From a synoptic perspective forecasting these events is relatively easy as the large scale pattern, with the anticyclone over the Great Basin and the cyclone off the coast, serves as a good indicator. Additionally, the large scale pattern is generally well predicted by global and regional models and by ensemble prediction systems. From a mesoscale perspective, the details as to where the strongest and most damaging winds will occur is a more challenging problem. Reinecke and Durran (2009) described the limits of predictability associated with downslope windstorms in the western United States. Upscale error growth in fine scale models likely limits predictability to on the order of hours. No attempt is made herein to deal with the predictability issues of these storms. The focus here is on defining the region most likely to be impacted by such events. The focus herein is on the use of climatological data with numerical forecast data and internal model climatological data to better define and thus anticipate such events. The climatological data method is as outlined by Hart and Grumm (2001) and Grumm and Hart (2001). The overall pattern is shown using standardized anomalies to show the strength of the anticyclone over the Great Basin and how significantly the winds and

3 forecast winds departed from climatology. These concepts are applied to 00-hour forecasts to assess the large scale pattern and forecasts to assess the potential for an extreme event. The internal model and ensemble M-Climate concept is based on the method described by Lalaurette (2003) on early detection of abnormal weather conditions using an extreme forecast index (EFI). The European Center uses an 18-year model climatology to produce the EFI. These data alert the forecaster to times when the model or ensemble prediction system is predicting an extreme event based on the internal climatology. The focus in this paper is on products to alert the forecaster to the potential for high winds. However, a spectrum of products exists to provide a wide range of guidance to alert the forecaster for areas where M-climate is implying an extreme or near extreme event based on the 18-year period of record. This paper will document the pattern associated with the high wind event of 1-2 December The focus is on the standardized anomalies as a tool to both analyze and predicted this and similar events. The NCEP SREF and 16km SREF are used to show how the event was forecast using forecasts and climatological data to better anticipate similar events in the future. More advanced ensemble based climatological data are used to demonstrate how using the current forecast, as compare to its internal climatology can be used to better anticipate high impact weather events. 2. Methods and Data The NCEP GFS is used to re-produce the conditions associated with the storm to include the large scale pattern. Though not used herein, the JRA-25 data (Onogi 2007) were used for comparison purposes. The standardized anomalies are displayed in standard deviations from normal as in Hart and Grumm (2001) and are computed using the climatology from the NCEP/NCAR global reanalysis data (Kalnay et al. 1996). The focus is on the pattern and anomalies associated with the storm. The value of EFS and anomalies with EFS data are presented. Ensemble data shown here are from the NCEP forecast systems. The NCEP short range ensemble forecast system (SREF) are used herein to show the probability strong winds at various levels to include 10m, 850 hpa, 700 hpa and 500 hpa. These data were also used to examine the pattern. The pattern and standardized anomalies followed the methods outlined in Hart and Grumm (2011) and the GFS 00-hour forecasts were used to establish the pattern and standardized anomalies. The NCEP 32km SREF data were examined here along with 2 comparative forecast cycles from the experimental 16km SREF. Most of these data are presented using the ensemble mean and the probability of each members forecasts exceeding a threshold relative to climatology. For example, mean sea-level forecasts are displayed with the probability of the 21-members forecasting surface pressures in excess of 2.5s above normal. Winds are displayed using a similar format. The 16km SREF had a complete dataset with data every 50 hpa. The operational SREF data had limited variables, for example, now 700 hpa data were in the SREF files. Several European Center for Medium Range Forecasting (ECMWF) products were used to show the potential for high winds in the western United States. Products form the ECMWF 50 member ensembles EFI are shown. Data include both planview and

4 point data. The EFI was developed as described by Lalaurette (2003). Forecasts from each member are compared to the internal ensemble climatology. An EFI approaching one would imply that most members a predicting values higher than those in the 18 year climatology. M-climate, the model internal climatology is used to compare the current forecasts to the model climate. This allows the forecaster to understand and see when the model is forecasting a high end event. In this study the focus is on EFI products related to high winds. The wind reports were gleaned from National Weather Service public information statements. Over 100 reports of wind gusts over 50 mph or wind damage were decode. Only winds in excess of 60 mph were included in Table 1. For brevity times are presented as day and hour in the format 30/2100 UTC and 01/1800 UTC which would be 2100 UTC 30 November and 1800 UTC 01 December 2011 respectively. Fully qualified dates are limited to comparative data from times outside of 20 November through 2 December The Storm system and impacts i. The large scale pattern The large scale pattern over North America showed an unseasonably strong ridge over the eastern Pacific (Fig. 1). As the ridge moved into the Pacific Northwest a close 5880 m contour developed with height anomalies on the order of 2 to 3σ above normal north of the close 500 hpa anticyclone. Though not shown, a strong 250 hpa jet developed in the strong gradient north of this ridge. The strong ridge obfuscates the relatively weak short-wave (Fig. 1a) moving down the coast of Vancouver which eventually deepened and formed a -2 to -3σ 500 hpa low over southern California by 01/1200 UTC. This short-wave led to cyclogenesis over southern California and Nevada (Fig. 2c-d) where surface pressure anomalies bottomed out at -2 to -3 σ below normal. North of this cyclone, a massive surface anticyclone over the eastern Pacific (Fig. 2a) strengthened and moved inland. The GFS 00-hour forecasts showed a 1040 hpa contour as the system moved onshore with +2 to +3 σ above normal pressure anomalies. The system intensified with a closed 1044 hpa contour developing over Washington and Idaho. A record high pressure of hpa was recorded at Seattle-Tacoma airport smashing the old record 1 of hpa set 28 January Record pressures in excess of 1042 hpa were set in December 2011, January 1949 and January The pressure records at Seattle-Tacoma airport date back to The strong gradient between the massive anticyclone and the low pressure to the south created a strong gradient. Within this gradient strong easterly flow developed and within this region of strong easterly flow, the high winds and non-convective wind damage was reported. Precipitation was limited to easterly favored upslope regions as the general air mass was very dry (Fig. 3) with normal to below normal precipitable water values observed over much of western North America affected by the massive upperlevel anticyclone. ii. Regional pattern and key anomalies 1 Based on data collected by Cliff Mass UW and his pun about the new recorded posted on his blog spot at

5 The evolution of the surface pressure over the western United States in 6-hour increments from 01/0000 through 02/0600 UTC (Fig. 4) shows the strong anticyclone move across Washington and Idaho (Fig. 4b-c) and the evolving cyclone to the southwest. Between the general -1 to -3σ pressure anomalies to the south and the +1 to 3 pressure anomalies to the north, a strong gradient developed over much of the Great Basin with a tight gradient from 1008 to 1040 hpa defining the area affected by the stronger winds (see Fig. 4d for example). The flow here implied enhanced upslope flow from New Mexico across Colorado to Wyoming in the east and down slope flow in California to the west of this region affected by the strong gradient. The GFS 850 hpa and 700 hpa u-wind and u-wind anomalies (Figs. 5 & 6) showed strong northeasterly winds over the great basin with -4 to -5 σ below normal easterly winds. At 700 hpa a broad region from Idaho to southern California had -3 to -5s 700 hpa wind anomalies at 01/1200 UTC (Fig. 6c). At 850 hpa, and much of the Great Basin lies above 1500 m, there was a region of -6σ 850 hpa winds in New Mexico (Fig. 5e). There were reports of upslope snows along the eastern slopes of the Rocky Mountains from New Mexico to Wyoming. The total wind at 700 hpa (Fig. 7) told a slightly different story with the strong winds about the general 700 hpa cyclone. Due to terrain and funneling the 700 hpa winds were strongest from the north along the California Coast from 01/0000 through 02/0000 UTC. At times the 700 hpa winds were 6 σ above normal in this region. Initially, the strongest winds were from the north (Fig. 7a) but became more northeasterly in time as the cyclone moved over southernmost California and Nevada. The increased easterly component likely contributed the Santa Anna winds more typical in southern California from about 01/1200 through 02/0000 UTC (Fig. 7c-e). These data imply that +5σ 700 hpa winds were present over California for over 18 hours (Figs. 7a-e) and at times there were locations where the 700 hpa winds were in excess of 6σ above normal. iii. Forecasts The event was relatively well predicted with 3-5 days of lead-time. Showing the array of forecasts would be time consuming so a few limited products are shown here. Focusing on the GFS forecasts then more advanced and potentially more useful ensemble products related to predicting high wind events. NCEP GFS MSLP forecasts from 28/0000 and 30/0000 UTC (Fig. 8 & 9) show the area of high pressure moving over the Pacific Northwest between 01/0000 and 01/1800 UTC. The red dot is the location of Seattle. The highest pressure in these 6- hourly data show close to 1043 hpa over that area between 01/0600 and 01/1200 UTC. The 3-hourly data implied the same basic result with the 1044 hpa contour never affecting Seattle. It is interesting to note the generally higher pressure over Washington and Idaho in the forecasts produced at 28/0000 verse those produced at 30/0000 UTC. Overall, the pressure forecasts were relatively well aligned with observations with a slight under forecast error in the anticyclone from the forecasts issued at 30/0000 UTC. The 700 hpa winds and wind anomalies (Fig. 10 & 11) similar to observed, showed strong easterly winds in the gradient between the anticyclone and the cyclone to the south. Subtracting the forecasts from the observed wind suggested some over predicting of the winds over portions of Colorado and Wyoming. But overall the pattern

6 and the potential region impacted by high winds was generally well predicted by the NCEP GFS at the two forecast cycles shown. Other cycles revealed similar results (not shown) with the strong anticyclone predicted at least 6 days in advance and the indication of strong winds over most of the Great Basin from about 26/0000 UTC onward. The operational 32km NCEP SREF forecasts initialized at 29/2100 UTC valid at 01/1800 UTC (Fig 12) show the probability of the mean sea-level pressure exceeding 2.5 σ above normal along with probability of 2.0 σ above normal winds at 500 and 850 hpa and at 2m. These data show the SREF correctly predicted the above normal surface pressures over the Pacific Northwest (Fig. 12a). Ideally, the negative pressure anomalies with the cyclone should be added to plots of this nature, though the low pressure over Arizona is clearly identifiable. Though not shown the forecasts indicated a -3.0σ and - 2.5σ pressure anomaly over southern Nevada in the NCEP SREF and GEFS respectively. Similar forecasts from the experimental 16km SREF from 29/2100 and 30/2100 UTC are shown in Figures 13 & 14 respectively. These forecasts provide some additional detail, with slightly higher pressure near the anticyclone center from the 29/2100 UTC forecast (Fig. 13a). There are some subtle differences in the wind field only visible by subtracting the fields (not shown). Some differences between the 16km and 32km version appear around the terrain in southern Idaho (Figs. 12d, 13d, and 14d) and about the higher resolution terrain in southeastern Oregon and Arizona. Overall, the 16 and 32km SREF products produce similar and useful forecasts. iv. Extreme forecast Indices EFI point diagrams were produced for all the points shown in Table 1. The forecast for Beus Canyon, UT is shown in Figure 15. The middle panels show the 24 hour maximum wind gusts. The left panels show the last 4 EC-EFS forecasts and the M-Climate value. The colored lines can be matched to the forecast cycles on the right hand panel. For example, the red curve is the EPS run from 24 hours earlier showing a 0 to 24 hour forecast. The M-climate range for the wind gusts over the past 18 years was 5 to 23 ms -1 and 60 percent of the time the winds were less than about 12 ms -1 based on the cumulative distribution function (CDF). The forecast CDF from the EPS show the lowest wind forecasts was about 16 ms -1 and ranged as high as 37 ms -1. The CDF for all forecasts were to the right of the CDF of M-Climate implying that the winds were forecast to be well above the internal model climatology. The bar graphs imply that for the 5 EPS runs shown, 95 to 99% of the forecasts exceed in M-Climate values. These data clearly indicated that the EPS winds forecasts were close to the 18-year M-Climate values. The EPS was forecasting a high end wind event. EFI diagrams for Centerville and Mammoth Springs show (Fig. 16) that fewer EPS members predicted an extreme event. Though most of the winds forecast at these sites were to the right of the M-Climate CDF indicating higher than normal wind values. Mammoth Springs had the highest reported wind gusts (Table. 1) which implies that terrain effects played a significant role in where the strongest winds were observed. The plan view images of the EFI for 10 meter winds over North America are shown in Figures 17 & 18. These data show that 132 hours out, the EFI values ranged from 0.50 to 0.70 over the southwestern United States, indicating that over 50% of the EPS members had winds that were higher than the M-Climate values. As the forecast length decreased and predictability increased, the EFI values reached 1 in some regions and ranged from 0.60 to 1.0 (Fig. 17 upper panel) over most of the region where the strong winds and wind damage was observed.

7 v. Observations Table 1 lists the locations and States where the highest reported wind gusts were observed. A map of these data is being developed. 4. Conclusions A large eastern Pacific ridge (Fig. 1 & 2) moved over the Pacific Northwest which produced anomalously high pressure over Washington and Idaho. Seattle-Tacoma airport set a new record surface pressure reading at the anticyclone moved over the region on 1 December To the south, a surface cyclone developed over southern California (Fig. 2). This produced a strong pressure gradient over the Great Basin which resulted in strong east-northeasterly winds. The strong winds produced damage and at least 3 locations in the western United States had gusts over 100 mph (Table 1). The strong winds persisted for over 18 hours downing trees and power lines from coastal California eastward across the Great Basin. Easterly facing slopes in New Mexico, Colorado, and Wyoming had snowfall as did several higher peaks in the Great Basin. The GFS 00-hour forecasts were used to document the strong anticyclone that moved across the region on 1 December 2011 and the anomalous 850 and 700 hpa winds. These data show the value of using climatological data with standard meteorological data to define the potential of an event to depart from normal. These data clearly showed the impact and value of knowing when the winds may be 3 to 6σ above normal. These data can put an event into context quickly. The GFS wind forecasts from 28/0000 and 30/00000, displayed with the standardized anomalies clearly indicated a high end event with 700 hpa u-wind anomalies in the -2 to -5s range over the Great Basin on 1 December (Figs. 10 & 11). These data can be of great value in forecasting high impact weather events, which in this case was a high impact high wind event. The NCEP SREF indicated a high probability of a 2.5σ above normal anticyclone over northern portions of the Great Basin and low pressure over Nevada and Arizona, a pattern often associated with strong winds and Santa Ana winds over the western United States (Ralph 2003). Ideal Santa Ana winds imply that the cyclone in this case was too far inland. In addition to the anomalous cyclone, the SREF and the 16km SREF showed a high probability of the 2m winds exceeding 2σ above normal over most of the region impacted by the high winds. Similar anomalous winds were shown in the 850 hpa, 700 hpa and 500 hpa winds. These forecasts implied a high probability of SREF winds exceeding the climatological values. The GFS 00-hour forecasts implied that these were relatively successful forecasts. The EFI data showed that at many locations in the western United States that the 24 hour wind gust forecasts were skewed to the high end of the 18-year internal model climate or M-Climate. The point diagrams showed at many locations in excess of 80% of the EPS members showed winds in excess M-Climate. At Beus Canyon values approached 100%. The Plainview images showed at the 24 hour range, the EFI was 0.7 to 1.0 over most of the southwestern United States and at 108 to 132 hours out, the EC-EPS showed an EFI in the 0.50 to 0.70 range over the southwestern United States. These data

8 imply the value of the EFI in alerting forecasters to the potential for extreme events, in this case high winds. As shown by the ECMWF, EFI values of 0.5 to 0.8 are good indicators of unusual weather. Values above 0.8 are typically associated with many high impact weather events. The rare case, where the EFI is 1 suggests all members of the EPS are exceeding M-Climate. The results shown here show the value that climatological and internal model climatological (M-Climate) data are extremely valuable in predicting high impact weather events. Both methods have their merits. A more important issue arises relative to how much time should be placed on diagnostics and s forecast concepts verse examining ensemble probabilistic tools which employ some form of climatological data. These ensemble tools with climatological data and M-Climate data imply a more practical method to identify high impact weather events (HIWE) using more data in a shorter period of time. Additionally, these data lend themselves to artificial intelligence (AI) applications which could improve forecasting many HIWE events. Weather data may evolve to the point of being just another piece of the information technology puzzle.. 5. Acknowledgements A special thanks to NCEP for access to the experimental 16km SREF data from 2100 UTC 29 and 30 November Thanks for the European Center for medium range forecasting, specifically Thomas Petroliagis, for access to extreme forecast index products and imagery 6. References Associated Press, 2011a: U.S West hit by high winds. 2 December (Daily wire reports with similar titles were published from 2 to 3 December 2011.) Associated Press, 2011a: Strong winds down trees and power lines in West. 1 December (Daily wire reports with similar titles were published from 1 to 3 December 2011.) Grumm, R.H. and R. Hart. 2001: Standardized Anomalies Applied to Significant Cold Season Weather Events: Preliminary Findings. Wea. and Fore., 16, Hart, R. E., and R. H. Grumm, 2001: Using normalized climatological anomalies to rank synoptic scale events objectively. Mon. Wea. Rev., 129, Lalaurette, F. 2003: Early Detection of abnormal weather conditions using a probabilistic extreme forecast index. QJRMS,129, Raphael, M. N., 2003: The Santa Ana winds of California. Earth Interact., 7, 1 13.

9 Reinecke, P.A and D. R. Durran, 2009: Initial-Condition sensitivities and predictability of downslope winds. JAS,66, Small, I., Santa Ana winds and the fire outbreak of fall 1993, NOAA Technical Memorandum NWS WR-230 June Sommers, W.T., LFM forecast variables related to Santa Ana wind occurrences, Mon. Wea. Rev., 106, , 1978.

10 LOCATION STATE WIND GUST (MPH) 3 WSW MAMMOTH LAKES CA 140 STEAMBOAT SPRINGS CO 123 CENTERVILLE UT WSW RED MOUNTAIN PASS CO 97 4 SSE PAHRUMP NV 94 WEST BOUNTIFUL UT 92 OGDEN PEAK UT 91 BADGER SPRING UT 89 7 WNW SANDIA PARK NM 88 FARMINGTON UT 86 CENTERVILLE UT 86 BOUNTIFUL UT 78 WEST BOUNTIFUL UT 76 8 E ALBUQUERQUE NM 75 W DESERT NV 75 BICYCLE LAKE AIRFIELD CA 74 6 SSW CASTAIC LAKE CA 72 8 NNE MOUNT WILSON CA 72 BEUS CANYON UT 71 OGDEN UT W FRAZIER PARK CA 70 5 NNE SAN FERNANDO CA 70 PAHRUMP NV 70 Table 1. Listing by location and State of the highest winds gusts reported. Only winds in excess of 70 mph were included in this table. Return to Introduction or return to EFI.

11 Figure 1. GFS 00-hour forecast of 500 hpa heights (m) and 500 hpa height anomalies from NCEP GFS initialized at a) 0000 UTC 30 November 2011 through f) 1200 UTC 2 December 2011 in 12 hour increments. Return to text.

12 Figure 2. As in Figure 1 except for mean sea-level pressure (hpa) and pressure anomalies. Return to text.

13 Figure 3. As in Figure 2 except for GFS precipitable water (mm) and precipitable water anomalies. Return to text.

14 Figure 4. As in Figure 3 except zoomed over the western United States and valid for 6-hour periods from a) 0000 UTC 01 December 2011 through f) 0600 UTC 2 December Return to text.

15 Figure 5. As in Figure 4 except for 850 hpa winds (ms-1) and u-wind anomalies. Return to text.

16 Figure 6. As in Figure 5 except for 700 hpa winds (ms-1) and u-wind anomalies. Return to text.

17 Figure 7. As in Figure 6 except for 700 hpa winds and 700 hpa total wind anomalies. Return to text.

18 Figure 8. NCEP GFS forecasts of mean sea-level pressure (hpa) and pressure anomalies initialized at 0000 UTC 28 November 2011 showing forecasts valid at a) 0000 UTC 1 December through f) 0600 UTC 2 December 2011 in 6-hourly forecast increments. The red dot is the approximate location of Seattle-Tacoma airport. Return to text.

19 Figure 9. NCEP GFS forecasts of mean sea-level pressure (hpa) and pressure anomalies initialized at 0000 UTC 30 November 2011 showing forecasts valid at a) 0000 UTC 1 December through f) 0600 UTC 2 December 2011 in 6-hourly forecast increments. Return to text.

20 Figure 10. As in Figure 8 except for 700 hpa winds (ms-1) and u-wind anomalies from GFS forecasts initialized at 0000 UTC 28 November The red dot is the approximate location of Seattle-Tacoma airport. Return to text.

21 Figure 11. As in Figure 10 except for GFS forecasts initialized at 0000 UTC 30 November Return to text.

22 Figure 12. NCEP 32km SREF forecasting initialized 2100 UTC 29 November valid at 1800 UTC 01 December 2011 showing a) ensemble mean surface pressure (hpa) and the probability of pressure exceeding 2.5s above normal, b) the 500 hpa winds and the probability of the wind exceeding 2.0s above normal, c) the 850 hpa winds and the probability of the winds exceeding 2.0s above normal and d) the 10m winds and probability of the 2m winds exceeding 2.0s above normal, Return to text.

23 Figure 13. As in Figure 12 except for NCEP 16km experimental SREF. Return to text.

24 Figure 14. As in Figure 12 except for NCEP 16km SREF initialized at 2100 UTC 30 November Return to text.

25 Figure 15 Figure 16. EC EPS extreme forecast plots for a point near Beus Canyon, Utah. Right hand side shows the cumulative distribution of the M-Climate (black line) and fore the past 4 EPS forecast cycles (colored lines) for 24 hour precipitation (mm), maximum wind gust (ms-1) and 2m temperatures. The percentages are to the right of the panels and the data range on the bottom. The right side panels show the color code relate to each EPS forecast and the valid time range. Bar graphs show the percentage of members above or below the M-Climate values. Return to EFI.

26 Figure 17. As in Figure 16 except for points near Centerville (left) and Mammoth Springs. Return to EFI.

27 Figure 17. ECMWF Extreme Forecast Index for 10 meter wind gusts valid for the period 0000 UTC 1-2 December 2011 from forecasts issued at 0000 UTC 1 December (upper) and 30 November The EFI ranges from 0.5 to 1.0 values of 1 indicated that all EPS members met or exceed the 18-year M-Climate maximum wind values. Return to EFI.

28 Figure 18. As in Figure 17 except for forecasts issued at 0000 UTC 29 November and 1200 UTC 26 November Return to text.