Sentences with phrase «weather data because»

They fail with weather data because money goes to political climate research.

Not exact matches

The study will continue through spring 2018, Finnair said, because it wants to collect data when travelers are carrying heavy winter coats and when they are traveling lighter in warmer weather.

Among the biggest bureaucratic challenges faced by the UK Space Agency is its management of applications for new satellites, which are viewed as critical because of their ability to provide data on the environment, climate, weather, security agriculture, coastal management and disaster mitigation.

Because the balloons are less than 12 pounds, they save money and hassle by sidestepping a requirement for licensing by the Federal Aviation Administration, which waives the rule for small balloons that gather weather data.

Drawing on PM2.5 data from five diplomatic posts in China, a 2015 study in Atmospheric Environment revealed previously unknown variations in PM2.5 levels; for instance, in Beijing the particles tended to peak around midnight and bottom out in spring, because of weather patterns.

The result is «a nearly 100 percent chance» of a gap in weather and climate data used by NOAA and the military, Glackin said, because the JPSS - 1 satellite won't be ready to replace its predecessor, the NPP satellite that launched last month, before it stops functioning.

Cowtan's version differs because it compensates for missing data from areas with few weather stations, like the Arctic.

Because there were much fewer weather stations collecting temperature data in Finland for the earlier portion of the time series, the researchers also used temperature data from neighboring Sweden, Norway and Russia.

Examining the fresh crater could provide data on how space weathering affects Mercury's heavily pockmarked surface — but this crater is too small to see from Earth, and the Hubble Space Telescope can't look at Mercury because it would have to point at the sun.

Further, because we have data from many years, we can compare students in years with many weather - related cancellations to students in the same school in previous or subsequent years with fewer cancellations.

Re # 31: It is quite certain that weather is a largely non-linear (AKA chaotic) process and / or that weather patterns are emergent, that is, they can not be reconstructed from their constituents because the data needed is not exact enough in quantity and quality.

The system could also, I think, be used to check some weather and climate theories against historical temperature data, because (a) it handles incomplete temperature data, (b) it provides a structure (the model) in which such theories can be represented, and (c) it provides ratings for evaluation of the theories.

In the long run, much of the economic growth of developed economies is likely to involve less energy - intensive sectors because of demand - side factors such as 1) the amount of stuff people can physically manage is limited (even with rented storage space), 2) migration to areas where the weather is more moderate will continue, 3) increased urbanization and population density reduces energy consumption per capita, 4) there is a lot of running room to decrease the energy consumption of our electronic devices (e.g., switching to clockless microprocessors, not that I'm predicting that specific innovation), 5) telecommunication will substitute for transportation on the margin, 6) cheaper and better data acquisition and processing will enable less wasteful routing and warehousing of material goods, and 7) aging populations will eventually reduce the total amount (local plus distant) of travel per person per year.

Rainfall rates derived from satellite data have a long legacy in operational weather forecasting because their information complements ground observations such as weather radar and rain gauges.

Scientists do not have a good sense of the current trends, because until a few years ago, data came from only a few ground - based weather stations.

«Actually, with the exception of 1998 — a «blip» year when temperatures spiked because of a strong «El Nino» effect (the cyclical warming of the southern Pacific that affects weather around the world)-- the data on the Met Office's and CRU's own websites show that global temperatures have been flat, not for ten, but for the past 15 years.

We know that every bit of weather is caused by purely physical activity, but our models of weather behaviour are imperfect because we do not have all the theoretically possible data.

People like Jim Hansen and Gavin Schmidt who sit up at the top of the climate food chain and take data from these weather stations at face value and then use it to extrapolate to nearby grid cells because there are no other nearby stations in the Arctic really need to get out more and see what the measuring environment is like.

As long as climatologists extrapolate temperature data from Seattle, or Toronto to show temperatures in the arctic, because we «just don't have enough weather stations,» the question will never go away.

Here are my climate change predictions bases on my own model (which I won't share with anybody because they might either try and take the credit for it or try and find something wrong with it) and on no data at all beyond vague memories of weather I have experienced and what I remember reading.

Because we don't use bulk cooking methods; we cook the data one weather station at a time.

Similarly to weather forecasting, efforts can be made to setup a model to match initial conditions at a certain point in time but they are likely to break down pretty quickly because we lack the quantity and quality of data to be precise enough in the setup (and possibly because the chosen model does not accurately produce variability similar to that observed on Earth).

If temperatures rose because previously rural weather stations were swallowed up by expanding megalopolises then some doubt is cast on whether that data supports theories of human - caused global warming.

This argument maintains that much recorded climate data is inherently unreliable because most weather instruments are in or near cities, which produce their own heat; so the rapid warming measured over the last century could be just a record of urbanisation.

AR5 3.2.2.3 says of it «Overall, the SST data should be regarded as more reliable because averaging of fewer samples is needed for SST than for HadMAT to remove synoptic weather noise.

«Actually, with the exception of 1998 — a «blip» year when temperatures spiked because of a strong El Niño effect (the cyclical warming of the southern Pacific that affects weather around the world)-- the data on the Met Office's and CRU's own websites show that global temperatures have been flat, not for 10, but for the past 15 years.»

Because the satellite data measure an average temperature through a depth of several kilometres in the atmosphere, they would be expected to compare better with upper - air measurements taken using weather balloons and radiosondes than they would with measurements at the surface.

Assuming that temperature is rising and that this is because of GHG effects (not arguing otherwise, just stating the givens), one would do well to look at data from other worlds in our solar system to determine where the «wild» weather is — and it is in the colder places, not the hotter ones.

I wonder why only five weather stations out of ~ 6000 were chosen... - gavin] Because in all probability there are only five rural, continental US stations with data from 1905 to 2003 which can be guaranteed to have not to have suffered changes in building cover, vegetation, irrigation,..

They come to genuinely believe weather equals climate, and all the usual climate myths, because they think AGW is a giant liberal conspiracy, so none of the data can be trusted and you do nt need to apply logical analysis because its all a conspiracy and fake data and equations anyway.

John Christy, the scientist and interviewee on whose work this latter claim is based, seems to have forgotten that he had written in a US Climate Change Science Program report: «This significant discrepancy [between lower and upper atmosphere warming] no longer exists because errors in the satellite and radiosonde [weather balloon instrument] data have been identified and corrected.

The forced orthogonality of the oomponents introduces a false pattern because the source data (weather and climate data) are spatially correlated.

«We expected about 50 percent stronger response in the atmosphere because of El Nino,» Karl told reporters, explaining that there was «very little response in the satellite and weather balloon data.»

UAH from their satellite data are suggesting that this is a more accurate record than the global temperature records because of UHI not being properly allowed for in urban weather stations records (supported by NASA 3 yr research on UHI).

I've never seen the raw data from the AIRS satellite survey, (I did see downloadable files but couldn't get them to work), but their conclusion was that CO2 was not well - mixed in the atmosphere, it was lumpy, and they would have to re-think the data because the wind, local weather and other wind systems, had to be included in understanding CO2 distribution.

After Climate gate (we will destroy data rather than release it) Himalaygate (a chance telephone conversation ends up with the WWF) Tempest gate (actually we could not find any statistically significant data) and now it apears that the base temperature data is open to question because cold weather stations were excluded from later studies in both Russia and Canada.