Timestamp | Repository | Message | Link |
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Aug 12 7:35 AM | iem,main | 📝 Update NWS Level II Feed Monitor https://www.weather.gov/nl2/NEXRADView |
Link |
Aug 12 12:17 PM | iem,main | 📝 Address TAF schema changes per akrherz/pyIEM#1104 | Link |
Aug 12 1:08 PM | iem,main | 📝 Sundry updates per review | Link |
Aug 12 10:50 PM | iem,main | 📝 Workaround edge case with data not starting evenly | Link |
Aug 12 10:58 PM | iem,main | ♻️ Refactor get_ct into iemweb.util, fix JSON things | Link |
Aug 12 10:48 AM | pyiem,main | ✨ Support PROB30,PROB40,BECMG TAF Fields closes #1104 |
Link |
Aug 12 12:48 PM | pyiem,main | 🐛 Address TAF edge parsing case | Link |
Aug 12 1:56 PM | pyiem,main | ✅ Add test to ensure TAF processing | Link |
Aug 12 2:45 PM | pyiem,main | 🎨 Account for additional TAF edge case | Link |
Aug 12 3:13 PM | pyiem,main | 🎨 Address some typing lint | Link |
Aug 13 6:10 AM | iemvtec,main | 🔥 Remove not properly implemented dark mode | Link |
Aug 12 10:01 AM | iem-database,main | ✨ Update TAF storage per parsing needs refs akrherz/pyIEM#1104 |
Link |
Aug 12 1:00 PM | iem-database,main | ✅ Refresh TAF test data | Link |
Empty Bucket Days
Date: 12 Aug 05:30 AM
Votes: Good: 9
Bad: 0 Abstain: 0
For all of the complex, non-linear, and compute intensive models that exist within meteorology/climatology, sometimes the simplest can be quite illustrative. Such is the case for the "leaky bucket model". The concept is simple, you have a bucket with a given depth (capacity) for water (filled by precipitation events) that leaks at some daily rate (evaporation, infiltration, runoff, etc). The two constraints are that the bucket can not be filled beyond its capacity and an empty bucket can not leak. The featured chart presents the data for Ames (picking a 1.5 inch bucket depth and 0.15 inch daily leak rate) between 1 May and 11 August for this year (top panel) and then the count of days each year for this period with an empty bucket. The chart nicely shows that this theoretical bucket has not been empty since mid June, but was for a number of such days prior to then so while the 2025 total is well below a simple average, it is still a number of days higher than 2024! You can tweak this model as you wish by following the "Generate this Chart" link.
The featured media can be generated on-demand here
.Summary | By WFO | Watches | ||||||
---|---|---|---|---|---|---|---|---|
Type | US | IA | ARX | DVN | DMX | OAX | FSD | US |
Tornado | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Svr Tstorm | 25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Flash Flood | 26 | 0 | 0 | 0 | 0 | 0 | 0 | --- |
ARX = LaCrosse, WI DVN = Davenport, IA DMX = Des Moines, IA OAX = Omaha, NE FSD = Sioux Falls, SD
SVR+TOR Warnings Issued: 26 Verified: 9 [34.6%] Polygon Size Versus County Size [15.0%] Average Perimeter Ratio [30.2%] Percentage of Warned Area Verified (15km) [18.6%] Average Storm Based Warning Size [827 sq km] Probability of Detection(higher is better) [0.46] False Alarm Ratio (lower is better) [0.65] Critical Success Index (higher is better) [0.25]