Do You Think A Ten Day Forecast Is Accurate Or Completely Opposite

Sometimes I think the best place to be would be completely by yourself, secluded up in the mountains with no other people. Does anyone else agree?

I’ve been hiking, mountaineering, and getting lost in the wilderness for almost 30 years. Some of it with strangers, friends, family, and alone on solo treks. The longest that i’ve went solo was in Denali National Park for 10 days.Those 10 days were a revelation. In the absence of people, I encountered Grizzly bears, Dall Sheep, and all kinds of wildlife and we communicated with each other. I talked to myself after day 2, carrying on these conversations.The experience was hard at first, but eventually found some comfort with silence and being this small insignificant element to the environment around me.I spent half a day watching a Grizzly mother breastfed it’s cub. There were so many experiences I wanted to share with those I loved. They could never be there, in that moment with me, to experience what I did.On day 10, I hiked back to the road and the Denali backpacker bus pulled up. I had never been so happy to see people in my life. It took ten days in the wilderness to realize how much I missed them. These strangers in a bus. It didn’t matter that we didn’t know each other. Soon I was excitedly showing them pictures on my camera and telling them about that all my adventures.People can be assholes. They can betray your trust and turn their backs on you. I hate relying on them because i’ve been hurt so many times by them. It’s part of the reason why I wanted to be alone. People can be awesome too. They can save your life, in more ways than one. They can be incredibly generous and surprising and beautiful. We can’t stay away from them for very long. We just need an occasional reminder that only aloneness can provide.

Meteorology: Why is still so hard to predict weather accurately and precisely?

As you're leaving for your office, you peep outside the window and see that its not raining. You decide not to carry the raincoat as it adds extra carriage.You head to the parking, and kick-start that bike you so adore. A couple of minutes into the journey, the rain begins. You reach the office completely drenched.This was just an example from our everyday lives. I was just trying to explain how weather is a very unpredictable phenomenon.Mathematics and statistics have helped us understand the physics involved in atmospheric phenomena. This has allowed us to predict beforehand for the convenience of the society.What should be understood is that we cannot play god. Nature will always have an upper hand. No matter how much we predict, nature will always have a couple of surprises for us.That being said, the IMD hasn't been that bad lately, actually their current forecasts are really good.Their cyclone warnings have been accurate and precise in the past few years. Had the IMD not given advance warnings, storms like Phailin and Hudhud would have left behind huge loss of lives. It is the Regional Specialized Meteorological Centre for the North Indian Ocean cyclone basin, and this honor is bestowed upon by none other than the World Meteorological Organisation (WMO).The monsoon long range forecasts end up to be near-perfect, thanks to recent advancement in research and advanced computing capabilities.There is no debate for accuracy. Being a national agency the recorded temperatures/rainfall adhere to international standards. They don't just happen to be a WMO recognised agency.What the problem is:Lack of good weather coverage. India has reached a point where it can have a 24x7 weather reporting television channel, like the United States does.Lack of awareness among the common public. Weather does not matter to us unless we are affected by it.Lack of faith in the agency among the common public. This question wouldn't have been asked otherwise.

Can climate models accurately predict Climate Change? How?

There is broad disagreement upon whether or not climate is a chaotic process or not. If it is, it would not be able to be modeled. Think 10-day forecasts of weather if you want an analogy to a closely related chaotic system that is really hard to model. Besides, accurate modeling requires a detailed understanding of the starting state of the conditions being modeled. Since the current state of the climate is hardly known, since most of the processes relevant to it occur at the micro-scale (e.g. droplet formation in a cloud, etc.) it is difficult to imagine how a climate model could ever be accurate. How many trillion monitoring stations would be required? How could anyone simultaneously measure the exact state of a system as mind-bogglingly complex as Earth’s climate? Perhaps a computer the size of a planet?? (Hitchhiker’s Guide to the Galaxy)…So even if it were NOT a chaotic system, the computational and measurement hurdles are ENORMOUS!!. Existing climate models have attempted to deal with these uncertainties by using “approximations” (guesses) in “29-adjustable parameter models”. These include many dubious guesses such as the often ignored but fundamental assumption that water vapor concentration will increase in lock-step with CO2 concentrations and thereby increase the Greenhouse Effect by 3 times over CO2 alone. This one has already been strongly disproven (not surprising - there are too many options for water vapor to “rain out”).The Existing “Guess-work” climate models have performed pretty marginally in “hind-casting” (they don’t get the 1930–1940s “dust-bowl” temperature right) but really poorly in future predictions. If you want proof, check out Jim Hansen’s 1988 testimony before Congress where he over predicted temperatures increases by almost a factor of 2, despite CO2 increases largely in keeping with his original prediction. Those models ALSO assume that ALL of the temperature changes were human-derived (foolish since huge temperature changes are evident over all time scales from natural variation). If guess-work climate models are not capable of predicting the future successfully, then the guesses were wrong. That is how science SHOULD be done. It is scary that so many people do not know this. The power of propaganda is a fearsome thing.The Hansen forecasts 30 years laterWith Perspective, we may yet emerge from the Darkness.Ian in Vancouver

How objective is IEA, when they release statistics and forecasts?

IEA statistics are generally considered to be reliable.  The OECD, the organization which controls the IEA, isn't very partisan in any sense of the word and tends to be taken quite seriously by those interested in the subject.  Their forecasts are respected, and along with the BP Energy Outlook and the publications of the U.S. Energy Information Administration (part of the U.S. Department of Energy) are probably the holy trinity of publicly available, comprehensive reports covering the oil and gas industry.   By the way, the OECD and the IEA under it are not affiliated with the UN, a common misconception that seems to make people unwilling to believe it. That being said, IEA forecasts can come under criticism from those who care about such things since their forecasting methodology can be a little hand-wavey.  I haven't looked seriously at their forecasts for quite a while, but I can comment on what I remember.  First, IEA tends to predict something close to the status quo, and frequently reverses itself.  Second, IEA forecasts tend to work on a country-by-country basis for demand and supply estimates, and then they balance the supply and demand by more-or-less arbitrarily designating a swing producer that will either increase or reduce output.  In past years, this was usually Saudi Arabia - meaning that this behavior was a reasonable assumption - but I remember that the year before I stopped really following things they had changed it to Iraq instead, which seemed and still seems inexplicable given the lack of a track record of reducing or increasing output for market management reasons (as opposed to economic and political stability reasons, which Iraq had and has in spades).  I expect they've changed again given the multinational Iran deal and the recent fall in price. All in all though, I wouldn't criticize that methodology too much, considering it's a difficult enough prospect to do a global supply-demand balance as it is, but we should recognize the inaccuracies that might come out of such forecasts.

Which polls are correct? Some say Trump beats Hillary, others say she wins by double digits, which ones should you put the most trust in?

I would not fully trust any poll in a Presidential Election that takes a national sample  That is because electing a U.S. President is not done through a direct national vote but by each state and the District of Columbia selecting electors to the Electoral College based on the popular vote in that particular state/District.  Therefore it is 51 separate elections.  State by state polls are bit more accurate.  However, the U.S. electorate is rather fluid so it's best to ignore polls and wait for the results.  I know that's not popular in this "Get it firs, get it fast, get it now" world we seem to live.  However, that way you're more likely to get it right.  Also, depending on the polling organization and the way the questions are worded, that may influence the result of the poll.  Rassmussen, which just said Trump was 2 points ahead of Clinton nationwide (see above as to why that is meaningless) generally polls towards the more "conservative" candidate.  CNN/ORC, on the other hand, says Clinton is up by 13 points. < At the starting gate: Clinton leads Trump by double-digits > However, if you read the actual po0lling data, you may come to a different conclusion.  < CNN/ORC poll results: General election matchups >Once again,k I would give a wary eye to any nationwide sampling poll and look at polling done on a by-state/District basis.