Updated Wind Algorithm portrays strong onshore flow in the wake of near miss

Although many forecast models seemed to consistently steer the powerful category 4 hurricane into the US mainland luckily this did not come to fruition. That being said the east coast of the United States still was influenced by Joaquin in the form of historic flooding as well as coastal flooding. The major meteorological players in this scenario were the hurricane itself and areas of High Pressure to the north and east; it was the forecasted movement of these features that caused dramatic differences amongst the forecast models. Ultimately, the storm ended up maneuvering further south and deeper into the Bahamas than initially anticipated and then the storm moved further out to sea sparing the East Coast of a direct impact.

Joaquin Wx Map

Figure 1 www.wpc.ncep.noaa Showing surface analysis with Joaquin to the southeast and High pressure to the North and East (not shown) the pressure differences between these systems would ultimately create the onshore flow responsible for coastal flooding.


Joaquin Space

Figure 2 www.nasa.gov View of Joaquin form the ISS

Nonetheless, there were affects from the storm; the pressure gradient created strong onshore winds that pushed and piled water towards the east coast and led to coastal flooding concerns that were exacerbated by the presence of large waves from Joaquin. The updated Verisk Insurance Solutions’ wind algorithm highlighted the onshore winds up and down the East Coast. Looking at the image below (Figure 3) you can see an area of stronger winds along the eastern seaboard that contributed to higher tides and coastal flooding.



Joaquin Wind

Figure 3 Benchmark Web Wind map utilizing Updated Wind Algorithm portraying strong winds along the coast that contributed to coastal flooding.


Another unfortunate outcome of the onshore flow was the channeling of deep moisture from Joaquin and the tropics that led to historic amounts of rain in the southeast, which caused much destruction. This stresses the connected nature of meteorological events in that even a storm far out to sea was able to impact a large area very far away from its center. The fact that our proprietary wind algorithm handled this event so well comes as no surprise since it uses cutting edge model input, real world measurements, and is carefully verified with industry claims data. This is just one of the many examples of our wind algorithm proving itself in real world situations that in turn provides our customers the ability to shorten claims time, confidently make decisions on claims, and receive easy to understand trustworthy data. Our wind algorithm measures the speed and duration of straight line wind such as, thunderstorms, derechos, Santa Ana winds, micro bursts and other non-tornadic wind events. Verisk also provides a suite of products that handle tropical events as well as tornadic events (Respond™.) With such a trusted name and product, when a wind report or map is ordered it’s not only trustworthy and easy it’s a (pardon the bad pun) wind wind situation.


joaquin rain

Figure 4 Verisk Analysis of the historic rainfall in SC


Areas already taxed by flooding now get Bill



Bill’s effects will not just be felt along the impacted coastline as this will be a storm known more for the damage it causes from flooding rather than wind. Portions of eastern Texas and eastern Oklahoma, areas that certainly don’t need additional rainfall, could see anywhere from 3-6 inches with locally higher amounts over the next 2-3 days. This will escalate the threat of flash flooding across these areas. Rainfall amounts are a little less certain throughout the Midwest and Ohio Valley as the remnants of Bill will begin to track north and east. However, ample moisture should remain to produce respectable rain totals across these regions. Which will likely lead to areas of flooding in the Ohio river valley as well as portions of the North East; though not as widespread.bill

In terms of winds Bill is not that strong all things considered. That being said Verisk Climate’s Product Respond™ indicates the likelihood of winds gusting in excess of 65 mph along the Texas Coast, as well as sustained Tropical Storm strength winds in close proximity to major metropolitan areas such as Houston this is depicted in a sample of the Respond™ product below. Furthermore, today and in coming days isolated tornados cannot be ruled out in the area affected by Bill.





Tropical Storm Bill became the second named storm so far this year when the storm formed in the Gulf of Mexico South South-East of the Texas coast. Climatologically speaking this is a common area for development at this time of year, as depicted in figure 1 which portrays the average location of development for this week.



Figure 1 http://www.nhc.noaa.gov/climo/

Bill started as an area of convection over warm water; current sea surface temperatures in the area are running at around 80° F which is the lower threshold for optimum development. Hurricane Hunters began flying into the storm to investigate throughout the day on 6/15/15. Sustained winds were above the threshold for Tropical Storm classification upon initial investigation but until 11PM on the 15th the storm lacked a well-defined center of rotation. Once this criterion was met Bill was named and the storm continued to become more organized and take on more tropical cyclone characteristics. As Bill progresses inland it is poised to drench areas that have already been inundated by rainfall.

Normally tropical storms quickly deteriorate once they propagate inland, however model consensus is hinting at a possibility of Bill feeding off energy due to a process known as Brown Ocean. In a nut shell; storms deteriorate due to the lack of energy input once they move away from the warm ocean water, in some rather rare cases (notably Ike ‘08, and Erin ‘07) this deterioration does not occur or is slow due to the brown ocean effect. Below is an example of how Tropical Storms feed off the ocean to strengthen, in the case of the Brown Ocean the storm is not being fueled by the ocean, but by moisture rich soil, which is abundant within Bill’s impact region due to recent flooding.


Looking ahead Bill will move North North-East through Texas into Oklahoma maintenance of strength is possible due to the effects of the Brown Ocean. Ultimately Bill will decay and is poised to move into the Ohio Valley where it could aid in the spawning of some severe weather. Then Bill will possibly interact with a northern stream system; should be better resolved as the model consensus comes into agreement. In any event the remnants of Bill will continue to bring the risk of flooding to the Ohio Valley and portions of the North East.








How dual pol radar works better for hail maps

A New Era of Hail Detection

From 2011 into 2013, the entire contiguous United States radar network was upgraded to dual-polarization technology. For the radars, this simply meant that instead of emitting solely horizontal energy, vertical energy would now be emitted and captured as well. Empowered with two dimensional data, it was now possible to begin to differentiate between precipitation types, such as heavy rain and hail.

On top of this, in 2014, the National Weather Service also began implementing a new radar scanning pattern. This new pattern effectively doubled the temporal resolution of near-ground data, allowing for a scan to be completed every two minutes instead of every five. For hail detection, this could greatly improve the accuracy of hail start and stop locations as well as fluctuations in hail size throughout the storm life cycle.


Verisk Climate Hail Update

The state-of-the-art hail data and analysis that Verisk Climate delivers to clients uses the latest radar technology advancements to map precisely where hail fell and how severe it was. Our hail update for the 2015 severe weather season marks the insurance industry’s first availability of hail data derived from these two U.S. radar infrastructure improvements, dual-polarization radar data and two-minute radar data frequency.

The resulting data is used by property, auto, and crop insurance and related markets to proactively respond to catastrophes, verify insurance claim accuracy and predict demand surges in building materials and labor. It’s integrated into customer enterprise platforms and our products including

  • Respond™ Hail Size, Extent and Duration
  • Benchmark™ Hail History and Date of Loss Reports
  • Benchmark Hail Maps
  • RiskScape™ Hail for Underwriting
  • Verisk Insurance Solutions software applications

Consider the following case examples that demonstrate the advantages of incorporating these two technology upgrades into hail data analytics.

Case 1: Heavy Rain or Hail?

A thunderstorm cell is moving across Mississippi during the height of the severe weather season. Traditional radar products indicate very strong radar returns, indicative of large hail in the core of the storm. However, weather spotters on the ground only measure a few relatively small hailstones with most reports indicating just heavy rain. So what happened to the hail?

Traditional radar scans are only able to measure the intensity of falling precipitation. In this case, the intensity of the precipitation was quite heavy, shown by the red colors in the top half of the image, but the hail was melting as it fell to the ground. This resulted in smaller hail sizes or no hail at the surface. Using dual-polarization technology, the radar data can be used to categorize the falling precipitation. In this example, the additional information from dual-polarization, shown in the bottom half of the image, indicates that in the heavy precipitation regions, only small hail and rain were reaching the ground, shown in dark green, with only a couple very small pockets of larger hail, shown in red. By taking advantage of sophisticated dual-polarization technology, a more accurate hail swath can be obtained.


Case 2: Tornado Debris

A strong tornado is carving a path through a residential area. Debris can be seen flying thousands of feet through the air by witnesses to the event. However, they are not the only ones who can spot the debris.

Weather radar has been identifying what has been termed debris balls for years, circled in black in the image. A debris ball shows up as an area of high reflectivity on traditional radar, indicated by dark red and pink colors in the top half of the image. That means this debris ball can actually be mistaken for hail by traditional hail algorithms. With the advent of dual-pol, weather radar algorithms can now distinguish debris from weather, such as hail. This is because dual-pol data is capable of determining an approximate shape of the falling objects. In this case, the debris is correctly identified, pink colors in the bottom half of the image, and is clearly distinguishable from the large hailstones just to the north, circled in blue and indicated by a red color in the bottom half of the image. The incorporation of dual-pol data makes it easier to define areas of actual hail by removing instances of debris or other non-weather related radar clutter.


Case 3: A Fast-moving Thunderstorm

A springtime thunderstorm capable of producing large hail is racing eastward at over 70 mph. The thunderstorm begins to approach a populated urban center when traditional radar completes a scan of the storm. After five minutes has passed, the traditional weather radar has completed another scan. This scan shows that the storm has passed completely through the urban area and decreased dramatically in strength. Without more information, traditional hail algorithms would be forced to use logic that would smooth the data between these successive radar scans, creating an educated guess of what may have occurred during those five minutes. But what actually happened during those five minutes was never exactly known, was the city hit with large hail before the storm died down or was it spared?

Using more frequent scan data, the issues of smoothing between successive radar scans are dramatically reduced by using twice as many direct observations. In this example, an additional image of the storm when it was directly over the city could have been obtained. The image may have revealed that the storm had already begun a rapid decline in strength. With this additional information, a more accurate hail swath indicating more precise locations of damaging hail would be created. The data in this case helped to limit the area of damaging hail to far western portions of the city, instead of encompassing a larger portion of the metro area.

Want to Learn More?

To discover more about how you can take advantage of the latest advancement in hail data technology, please contact Patrick Pollard, VP Insurance Solutions.

You can also order a Hail Map or read about Benchmark Hail Maps.

Strong winds hit the Northeast from the first major blizzard of 2015.

Strong winds and heavy snow slammed the Boston area as the first major snowstorm of 2015 hit the Northeastern United States. The strongest winds were detected on along the coast of Massachusetts, as evident by the Daily Wind Map generated from Benchmark Web™ (See Figure.1). This widespread event produced winds as strong as 75 mph within 5 miles on shore. The strongest wind were secluded to a relatively small area though, as noted within the figure below. The 20 mph difference within 15 miles is very significant on scales such as this.

                         Figure.1 Daily Wind Map contours of the Massachusetts area on January 27th 2015.

One of the cities to experience some of the stronger wind speeds during this blizzard was Marshfield MA, a city near the coast of Massachusetts. Within the Benchmark Web Daily Wind Map, if we zoom into the Marshfield, MA area, we see that Marshfield is within a contour of 75 mph winds (see Figure.2). The high-resolution contours give great details on the locations where the wind speeds were strongest.

2015-02-26 16_22_04-Benchmark                       Figure.2 Zoomed in Daily Wind Map contours of the Massachusetts area on January 27th 2015.

The newly released Benchmark Wind History report, which provides a historical view of straightline wind events at a property and nearby, confirms that the date of 1/27/2015 was indeed the strongest detected within Marshfield, MA since 1/1/2009 (see Figure.3 below). The report also confirms that wind gusts in excess of 50 mph was detected for a remarkable time-span of 15 hours.

                                         Figure.3 Wind History Report for 1 main st. Marshfield, MA.


Benchmark Web wind reports are now live!

Verisk Climate just released Benchmark™ Wind History Reports through the Benchmark Web platform. This new report allows insurers to order wind data for their claims and underwriting processes.

The wind report is a quick and easy way to:

  • Identify at the first notice of loss whether damaging winds occurred
  • Verify the date of loss
  • Provide a historical view of straightline wind events at the property and nearby
  • Determine if damage occurred while the policy was in force

You can order a report for any property in the continental United States and for any date since January 1, 2009. Order your report here today or find out more information about Benchmark Web.

If you are an XactAnalysis or Xactimate user, you can order the wind report from the assignment record using Benchmark for XactAnalysis.

At least 25 Percent of Claims are Misclassified

A Costly Mistake

In a typical year, around 5% of homeowners will file a weather-related insurance claim in the United States.  One of the most common perils filed is that of hail damage.  Hailstorms can occur anywhere in the United States, but are most frequent across portions of the Great Plains and Midwest.  The high frequency of events can make it especially difficult for insurers to assign hail claims to the proper event date.

Analysis of industry-wide insurance claims from Verisk’s A-PLUS™ property loss database reveals that, consistently over the last five years, at least 25% of hail claims have been assigned an incorrect date of loss (DOL).  This issue is compounded when the hail event is further in time from the date when the claim is first reported.  The result has major implications for catastrophe (Cat) to non-Cat loss ratios, with a direct impact on potential for recoveries.

Percentage of hail claims that have no hail on their assigned date of loss (with a margin of error of one day) with respect to the lag between the reported date of loss and the claim open date (Source: Verisk Climate Benchmark™)

A 2014 Case Example

The 2014 hail season was a below normal year in terms of hail losses, but still recorded 20 PCS designated hail catastrophe events, covering 68 unique days.   The Colorado Front Range Urban Corridor was especially hard hit, with six separate hail catastrophe events impacting the region.  While the majority of hail losses can be traced back to the hail that occurred on one of these catastrophe dates, a significant number of claims were assigned to a non-Cat event.  Verisk Climate estimates that insurers have underestimated the impacts from the 2014 Cat events in Colorado by around 10%.  In addition, analysis has revealed that a few of the claims filed this year were actually the result of a hail event from two years ago, which occurred on June 6-7, 2012.

Areas potentially impacted by damaging hail associated with a 2014 PCS designated Cat event (shaded in yellow) across a portion of the Colorado Front Range Urban Corridor (Source: Verisk Climate Respond™)

The Question of When

Hail damage associated with storms that occurred over a year ago is not an uncommon finding.  Recent hailstorms across the northern suburbs of Dallas revealed a surprising number of claims that were likely attributable to 2012 Cat events.  This highlights an important message for the insurance industry; a properly assigned date of loss may be just as important as the assessment of whether a roof has hail damage.  In assigning hail damage, it is the question of when that has the potential to dramatically improve your financial results.  In some instances, insurers have even found that they were not covering a policy when the hail damage occurred.

Finding a Solution

The good news is that misclassifying claims can be easily avoided.  Claims data analytics including weather peril data can quickly identify these issues and provide insurers with the necessary information to reassign these claims to the proper date of loss.  This not only provides more accurate data for crucial statistics such as Cat to non-Cat loss ratios, but ultimately has the potential to impact insurers’ bottom lines through increases in recoveries and decreases in payments for damage done before the policy inception.

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Tax ID / EIN / TIN / FID / W-9 / Company information

Corporate Name: Insurance Services Office
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Corporate Phone Number: 201-469-2133
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Verisk Climate and Weather Decision Technologies Form Alliance to Develop New Applications Analyzing Business Effects from Weather

Verisk Climate Is Now WDT’s Channel into the Global Insurance and Restoration Markets

LEXINGTON, MASS., and NORMAN, OKLA., December 17, 2013 — Verisk Climate, a leading provider of enterprise climate risk management solutions, and Weather Decision Technologies (WDT), a high-technology leader in the weather industry, announced today they’ve formed a long-term alliance to develop new, more advanced analytics and solutions focused on the business impacts from weather perils.

Verisk Climate now serves as WDT’s channel into the global insurance and restoration markets. Verisk Climate will build upon content from Weather Decision Technologies to inform the climate-business analytics that Verisk Climate offers across all its markets, including insurance and reinsurance, corporate supply chain, and capital markets in the United States, Canada, Europe, and the Pacific region. Verisk Climate is a division within Verisk Analytics (Nasdaq:VRSK).  

“By combining WDT’s weather content with Verisk’s scientific capabilities, analytic leadership, and workflow integration, Verisk Climate’s customers will have access to the most sophisticated, reliable, and easy-to-use climate-business analytics on the market. Together, we are substantially expanding the resources available to Verisk Climate’s corporate logistics, insurance, and risk management clients,” said Kyle Beatty, president of the Verisk Climate division.

“Verisk Climate and WDT share a vision to transform how businesses prepare for and react to the weather. WDT’s focus on developing highly reliable, near-real-time weather content will enable a new generation of services that Verisk Climate will offer to its clients globally. Verisk Climate is an ideal ally for us to provide value to the global insurance industry and other markets it serves,” said Mike Eilts, president and CEO of WDT.

About Weather Decision Technologies (WDT) 
Weather Decision Technologies, Inc., is the industry leader, providing organizations with weather decision support on a global scale. WDT offers specific expertise as it applies to hazardous weather detection and prediction, forecast modeling, decision analytics, GIS, mobile apps, and interactive mapping. WDT employs the world-renowned WeatherOps forecast team, staffed by experts who provide global asset protection and commodities-trading decision support.
WDT maintains operational offices in Norman, Oklahoma, and Houston, Texas.

About Verisk Climate
Verisk Climate provides software, data, and analytics for enterprise climate risk management. The organization’s solutions help corporations improve resilience and profitability while enhancing service to their customers. Manufacturers, distributors, and retailers rely on Verisk Climate to accelerate revenue growth through more accurate forecasts of product demand and to promote stable operations by helping mitigate supply chain risk. Insurance carriers can apply Verisk Climate™ solutions to help improve customer service and reduce their property combined ratios through more accurate risk selection and lower claims expense. Verisk Climate draws on disaster risk models from AIR Worldwide, vertically integrated data from the Verisk Analytics family of companies, and environmental data and expertise from its Atmospheric and Environmental Research (AER) unit. Verisk Climate is a division within Verisk Analytics (Nasdaq:VRSK). For more information, visit www.veriskclimate.com.

Verisk Climate Press Contact:
Brenda Kelly
Verisk Climate and AER
P: +1 781.761.2348

WDT Press Contact
Lolly Taylor
Weather Decision Technologies, Inc
P: +1 405.579.7675 x225