Dennis,

Tropical waves are more frequent than hurricanes, at times with more rain than a hurricane and can have a substantial residual effect after the rain event already included in NOAA records, might be worth investigating.

Now that I know how to estimate the basic rain calendar I will look for the tropical waves calendar. NOAA has a lot of data available, it should be there, but understanding the data might take me more time. I am trying to get in contact with an ex-coworker who specializes in hydrology but have not being able to find him.

We get tropical waves every other week on peak season and at times they collide, at times they come one after the other, some coming from the west generated by cold fronts from the US and some coming from the east generated in Africa.

In some jobs weak waves make and impact in other jobs not even the strongest have a residual impact other than the rain event in NOAA records. Probably I would look for the monthly distribution of tropical waves, depressions and storms that never made it into a Hurricane but that poured over certain amount of rain, say over 3 inches. This I will use to trigger a sequence of weather event that will represent 2 extra days lost after the rain event. I have no idea how it will come out.

I believe I will end up using about 3 weather calendars, one for rain using rainfall >=0.1 in/day, another for rain using rainfall >=0.3 in/day and another for the tropical waves, depressions and storms . These will be applied differently to different jobs, to different activities as the need be.

Best regards,

Rafael

Raymund:

RE: Are the lost days to weather when accumulated will be granted as Extension of Time?

• Days lost to rain are usually granted when it rains above normal, one of the issues is what is normal, another what is the rainfall amount threshold that will trigger the impact. Simple contract rules that make it clear the risk are good but rules subject to interpretation are not good for purpose of contracting rules. I am looking for the rules that shall be subject to interpretation of the person that bears the responsibility for the delivery of the job.

RE: Clients will likely consider to grant those lost days because it is a natural cause beyonds contactor's nor client's control.

• Below the established amount it is 100% risk to the contractor after the amount it is a shared risk, time extension is granted no liquidated damages or extended overhead are applied.
• In some (few) jobs it make sense to shift all risk to the Contractor but usually in such cases the rules are clear.
• In some cases (many) not sharing the risk can backfire, contractors will work under adverse conditions yielding poor quality of work. If I bear all the risk for rain, I will pour the slab no matter how dark the clouds are, if it comes out bad, the owner will have to accept a repair that is not as good.

RE: Risks are expected from unexpected sources. There are a lot of Risk we expect to happen but sometimes before it is about to happens, preventive measures were introduced. Sometimes Risks had come with unexpected low impact.

• Agree.

RE: With regard to your researches to estimates the lost days to weather, is the reason to determine it earlier would means the impact will be considered in the mark up for Pricing of Tender?

• Impact is to be considered as a possible cost in the pricing, you never know costs ahead it is always an estimate. In addition the main idea is to make good planning with the use of appropriate buffers calculated in a rational way.

Best regards,

Rafael

Dennis,

I thank you a lot because it is the first time I looked at NOAA for the data, at the beginning I did not know where to look and the exercise have been a positive learning experience.  To me the question now becomes more an issue of how to define an expected number of days to be lost to rain, it is relatively easy to create the weather calendar after you know from where to pull down the data.

I liked your use of bins to have a better picture of the distribution curve; I did not use it because it is easier to create the chart without the use of bins, a small saving.

The fact that nobody joined us makes me believe that the requirement to look for weather data is overlooked by the great majority of schedulers.

Because the Monte Carlo functionality in Spider is new I still got to learn how to use it. After I looked for some references I found Primavera Risk methodology in agreement with I believe is correct modeling with the probable exception on what distribution curve they are suggesting and making available. It is not that I knew about the difference between normal and log-normal distribution curves, I learned about it yesterday. As I told you I am not a mathematician and do not believe many schedulers at home are mathematicians, most probably a project engineer required to do it  as part of his many other functions.

Even when the available data only provides 50 points per monthly histogram it shows from year to year there can be significant variation in the number of days with rainfall above any given threshold. I do not believe this is enough to consider it statistically enough for considering valid for purposes of contractual use.

I believe in the value the models provide even in the lack of precision. In the same way I believe in the models of NOAA when tracking a hurricane, every year they improve on the quality of early warning saving lives and money. Here they are heroes, on hurricane season they bring the hurricane hunters, provide us with much needed information the satellites nor the buoys can provide.

I would like your comments about how to model the effect of other weather events like hurricanes and the frequent storms that do not make it a hurricane but that can bring more flooding than some hurricanes. I believe the initial rain effect is considered under the NOA statistics so it should be a matter of using a different methodology for this purposes. A random trigger that will have an impact after the initial rain impact, of several days or even weeks in case of a hurricane. Although considered as "acts of god" in our contracts they have their impact and are of interest.

I would dare to say impact of events such as flooding or consecutive rain days can be localized. In most of my jobs the effect of flooding have been none with the exception of a river water intake for a potable water plant and some works on an irrigation canal. For these jobs impact of these events are frequent and must be considered. Again I believe it shall be the sole responsibility of the Contractor to make the assumptions and bear the responsibility of his own planning.

Again many thanks for your assistance.

Rafael.

Dennis,

RE: IMO it should be the responsibility of the contractors to develop these 'weather calendars', they are the ones with the data and the exposure. If I was a dues paying member of AGC, CII, or other contractor organizations, I would expect them to provide this data. Why would you expect the owners to perform these studies? That aside, and assuming that "Depart from normal" is the monthly standard deviation, and the .1" is the appropriate target, and you have the other monthly data, then you have all you need to construct your OPRA Weather Calendar. If any of those assumptions are not correct then you will have to do it yourself. Also, assumes that we are using current data.

• By not being clear as to the threshold they make it impossible to know what is the Contractor Risk, if they specify 0.10 in as the threshold they are making it as if 30% of the time is expected to be a day lost to rain with the effect that all risk  is for practical purposes kept on the Contractor unless a Hurricane occurs.
• I do not recall a direct hurricane hit for August of 2012 but the rain data says 13 days with rainfall above 0.10 in close to 50% of the whole month lost to rain, such claim would be ridiculous.
• 
• Maybe the AGC provide the data but the contracts call for the use of NOAA Data. If I were an AGC member I would suggest no single day are expected to be lost to rain shifting all risk away from the Contractor.

RE: NOAA provides the raw data at no cost, which is about what I would expect. Since individual needs will vary - what rate constitutes a rain day, a snow day, a hot day, a cold day, etc. - I can see where this might be onerous. That said, the Australian Board of Meterology seems to be providing this data. If such a query could be constructed that could extract this data, it is beyond my capabilities. I would gladly work with anyone who might be able to do the proper programming that would incorporate various user specific filters - assumes Access using CSV data.

• Such query could be constructed easily by using easy to use database software. It is a matter of providing the tables in a usable format that can be easily consolidated and queried.

RE: Does your company collect rain day data - actual days lost to rain on its various projects? If they do, it will be useful when trying to validate the models. Whatever we construct may not have any predictive value if it cannot be properly validated.

• I work on my own but will take a look at some schedule updates of my clients, the information is there if I still have access to the files on old P3 and SureTrak format. What you propose makes 100% sense to me although it will be from another regions the data I might have. I have a Guaynabo Job, where it rains twice as much, it is at the center of our rain corridor.

For purpose of getting the methodology we can waive the issue on fairness for the moment, we can assume all risk is on the Contractor and agree on whatever threshold. Latter on once we agree on the methodology then we can go back to the issue on the threshold selection.

Best regards,

Rafael

Dennis,

Definitively I find it onerous for any owner to require each construction contractor to do this tedious research by themselves. Washing their hands and throwing all the burden on the contractors makes it impossible to make any claim that under other rules would not be onerous, rules our parents used decades ago.

Too much theory but disconnected from the real world, so disconnected that I fear most of the practice that is based on averages is flawed. Using average number of rain days per month will overwhelmingly yield average years and will not take into account the un-average. But the un-average happen every four years and must be considered.

If you end up modeling only average monthly conditions the calculations will miss when near critical activities become critical because of days lost to rain. This is the reason why Monte Carlo is used, because if we only use averages the statistic will be wrong.

I believe there is a possibility 90% of suggested procedures are flawed by missing this point, an error of 50 years ago, if history repeats again it would be a double shame if an error using Monte Carlo models that were developed to prevent it.

The following illustrates the data I am looking for, I need it just for the 12 months of the year for the last 30 years, not much 360 tables. Missing intermediate values between Days >= 0.10 and 0.50 so it falls short of my needs. Will consider looking at the daily reports, 360 days x 30 years, just 10,950 reports for every town a contractor does business, a piece of cake. Well every other contractor bidding on the same job should be doing it.

RE: It might be useful to compare our individual results. I am using the hourly precipitation data from NOAA for San Juan International Airport for the date range of 01Jan67 to 10Aug12 (~45 years). If there is an Excel maven out there that could automate the totaling of number of days per month (see below - cut and paste between programs does not always work well). In this case, there are 11 days for Jan67, 6 days for Feb67, 4 days for Mar67, and 4 days for Apr67.....This has to be done for each month of each of the 45 years. This becomes tedious. If anyone has suggestions to simplify the process, I would appreciate it.

Maybe using database software all the data can be imported to a single database file and a single query can do it. I find it difficult to understand why the files are not available in a consolidated CSV format for the public to download all or part of it. In a tabular format easy to consolidate and query. We have hundreds of universities and research centers, not to mention hundreds of thousands of contractors that might also need the data, maybe we are looking in the wrong way, or maybe someone is profiting by selling the data, data that shall be of easy access and free for the general public. Because the NOAA reference is in almost all Federal and State Government contracts it is supposed to be a piece of cake, we must be doing something wrong on how we are pulling down the data.

Best Regards

Rafael

Dennis,

I edited a prior posting and included the following for which I would like to hear your comments.

• As you can see I am questioning myself about the threshold limit to define what will predict days lost to rain as well as the use of average monthly days lost to rain instead of using a distribution. Using only averages can led us to the flaw of averages as extreme years will be ruled out in our Monte Carlo model if we limit the model to the use of averages.

Stephen,

I agree with you and maybe because linear extrapolation can yield unrealistic results I would assign more weight to the last ten years. Perhaps a weight of one to the first 20 years and a weight of 2 to the last ten, making it as if 40 years.

I prefer clear rules for contract terms and leaving the use of probabilistic models to the party who takes the most risk, your suggestion makes much sense, if there is a trend it will take it somehow into consideration if not nothing will be lost. 

Regards,
Rafael

I agree with Mike and would like to add.

• Don't forget it also rains during non work hours during regular work days.
• At times when it rain at night does not matter, at times rain at night matters for a couple of days even if it does not rains again.
• If you work two 8 hours shifts the probabilities of being impacted by rain are greater than if you work a single shift.
• If it rains 3 consecutive days the soil get saturated and might have a greater impact than if it rains on alternate days.
• We have several weather patterns; rain due to wind blowing inland during the day, from sea toward the mountains and rain due to low pressure systems some coming from the East during June and rain systems due to cold fronts from the west during December. These systems can get our soils saturated and will have a greater impact than rain on alternate days.

It does not matter if the parties share or not the risk of weather patter under clear rules, rain will still happen and will have an impact. It is very complicated but shall not stop us from looking for better methods to estimate impact.

As you can see I am questioning myself about the threshold limit to define what will predict days lost to rain as well as the use of average monthly days lost to rain instead of using a distribution. Using only averages can led us to the flaw of averages as extreme years will be ruled out in our Monte Carlo model if we limit the model to the use of averages.

With the purpose to start exploring the procedure until I find what data is necessary I created the following fictitious data. I learned that there is a possibility that 30 years is not much for the distribution statistics. I believe it might be that rain is not so random as to make it a normal distribution. It is possible some months we experience dry weather and others a rain pattern and that the occurrence of in between is not so common, only the observations will tell us. Sometime we have "el niño", the boy, and sometime we have "la niña" the girl. Perhaps these shall also be considered into the equation.

The most arbitrary value is on what amount of rain will represent a good predictor of days lost to rain. My fear is that it can be manipulated for the benefit of either side.