Sentences with phrase «global average values»

Have you ever wanted a simple way to output global average values for each year from a series of monthly climate model output files?

An impact of a comet 200 meters in diameter 100 years ago, or a comet 500 meters in diameter 2,000 years ago, could have supplied sufficient methane to account for the currently observed global average value of 10 ppbv.

3 Variations in the CO2 forcing function (& presumably all the GHGs) are also based on a yearly global average value, so that there is also no daily or seasonal variation included in the models, let alone north - south variations.

-- 1.87 is the clear - sky, or the all - sky annual mean infrared optical thickness; — if clear - sky, how the cloudless cases were selected out from the radiosonde data set; — if it is the clear + cloudy (all - sky), how did he get it as global average value, when the cloud infrared optical depth is infinite (in half of the cases); — if 1.87 is for all - sky, how much is the clear - sky value (if he got it).

Finds a positive rate of TC intensification over all basins from 64 kt to first peak of intensity maxima (global average value = 104 kt)

That is, if a 5 - deg latitude by 5 - deg longitude grid does not have a temperature anomaly value in a given month, it is not included in the global average value of HADCRUT4.

Not exact matches

Global stocks represented by the MSCI World Index, consisting of a market value — weighted average of the performance of about 1,350 securities on the stock exchange of selected countries.

The Global Economic Policy Uncertainty (EPU) Index is calculated as the GDP - weighted average of monthly EPU index values for the U.S., Canada, Brazil, Chile, the U.K., Germany, Italy, Spain, France, the Netherlands, Russia, India, China, South Korea, Japan, Ireland and Australia, using GDP data from the International Monetary Fund's (IMF) World Economic Outlook Database.

Global bioplastics for the packaging industry is forecast to grow from 2017 — 2022 at an annual average rate of 17 % to a market value of almost $ 7.2 billion, according to a Smithers Pira report.

You can see that Iran expends 2.5 % of its GDP with military expenditure (just a bit more than the global average of 2.3 %), and the specific value (in 2015 US$) is US$ 10.265 billion.

IPCC estimates, using the best and longest record available, show that the difference between the 1986 - 2005 global average temperature value used in most of the Panel's projections, and pre-industrial global average temperature, is 0.61 °C (0.55 - 0.67).

In their latest paper, published in the February issue of Nature Geoscience, Dr Philip Goodwin from the University of Southampton and Professor Ric Williams from the University of Liverpool have projected that if immediate action isn't taken, Earth's global average temperature is likely to rise to 1.5 °C above the period before the industrial revolution within the next 17 - 18 years, and to 2.0 °C in 35 - 41 years respectively if the carbon emission rate remains at its present - day value.

There are some caveats with their study: The global climate models (GCMs) do not reproduce the 1930 - 1940 Arctic warm event very well, and the geographical differences in a limited number of grid - boxes in the observations and the GCMs may have been erased through taking the average value over the 90 - degree sectors.

«The consensus is that a doubling of atmospheric CO2 from its pre-industrial revolution value would result in an average global temperature rise of (3.0 ± 1.5) °C.»

Third, using a «semi-empirical» statistical model calibrated to the relationship between temperature and global sea - level change over the last 2000 years, we find that, in alternative histories in which the 20th century did not exceed the average temperature over 500-1800 CE, global sea - level rise in the 20th century would (with > 95 % probability) have been less than 51 % of its observed value.

If long - term global warming is to be limited to a maximum of 2 °C elsius above preindustrial values, average annual per - capita emissions in industrialized nations will have to be reduced by around 80 - 95 % below 1990 levels by 2050.

The Advisor has contractually agreed to waive its fees and / or reimburse expenses at least through April 30, 2019 to the extent necessary to ensure that the total operating expenses do not exceed 1.20 % of the Investor Class's average daily net assets and 0.95 % of the Institutional Class's average daily net assets for the Chautauqua Global Growth Fund, 1.20 % of the Investor Class's average daily net assets and 0.95 % of the Institutional Class's average daily net assets for the Chautauqua International Growth Fund, 1.10 % of the Investor Class's average daily net assets and 0.85 % of the Institutional Class's average daily net assets for the Baird MidCap Fund, 1.20 % of the Investor Class's average daily net assets and 0.95 % of the Institutional Class's average daily net assets for the Baird Small / Mid Cap Value Fund, and 1.25 % of the Investor Class's average daily net assets and 1.00 % of the Institutional Class's average daily net assets for the Baird SmallCap Value Fund.

Global stocks represented by the MSCI World Index, consisting of a market value — weighted average of the performance of about 1,350 securities on the stock exchange of selected countries.

> Value: We value Honors points at about 0.4 cents each based on an average global room rate of around $ 100 and 20 - 30,000 points for a Category 4 award nValue: We value Honors points at about 0.4 cents each based on an average global room rate of around $ 100 and 20 - 30,000 points for a Category 4 award nvalue Honors points at about 0.4 cents each based on an average global room rate of around $ 100 and 20 - 30,000 points for a Category 4 award night.

Based on current positioning, we expect the All Asset strategies to benefit from the following return tailwinds: a stable to rising breakeven inflation rate, appreciating EM currencies, convergence of EM - to - U.S. cyclically adjusted price / earnings (CAPE) ratios toward longer - term averages, and appreciation of global value stocks from today's elevated discounts toward longer - term norms.

The FPA Global Value Strategy will seek to provide above - average capital appreciation over the long term while attempting to minimize the risk of capital losses by investing in well - run, financially robust, high - quality businesses around the world, in both developed and emerging markets.

We value global equity markets as the sum of dividend yield and growth in earnings, capturing market return in a constant - yield environment, as well as considering the reversion of CAPE to its long - term average.3

Its largest equivalent positions were in the Vanguard Value ETF (VTV; average weight of 46.7 %), iShares Core U.S. Value ETF (IUSV, formerly IWW; 15.3 %), Vanguard Financials ETF (VFH; 10.9 %), iShares Morningstar Large - Cap ETF (JKD; 5.0 %), iShares Global Financials ETF (IXG; 3.8 %), and iShares Transportation Average ETF (IYT; average weight of 46.7 %), iShares Core U.S. Value ETF (IUSV, formerly IWW; 15.3 %), Vanguard Financials ETF (VFH; 10.9 %), iShares Morningstar Large - Cap ETF (JKD; 5.0 %), iShares Global Financials ETF (IXG; 3.8 %), and iShares Transportation Average ETF (IYT; Average ETF (IYT; 3.8 %).

In a 2004 update, the late Lou Lowenstein showed again that the returns over time of ten value funds (including our own First Eagle Global) were much above average.

As a Platinum Card Member, you can enjoy access to the Global Lounge Collection, the only credit card airport lounge access program that includes proprietary lounge locations around the world.Receive complimentary benefits with an average total value of $ 550 with Fine Hotels & Resorts.

CONCLUSION The values for the global climate sensitivity published by the IPCC cover a range from 2.1 ̊C — 4.4 ̊C with an average value of 3.2 ̊C, which is seven times larger than that predicted here.

There are some caveats with their study: The global climate models (GCMs) do not reproduce the 1930 - 1940 Arctic warm event very well, and the geographical differences in a limited number of grid - boxes in the observations and the GCMs may have been erased through taking the average value over the 90 - degree sectors.

[Response: While the raw data at any one station at any one time obviously doesn't change, the value for any regional or global average in the past is always an estimate since there isn't a perfect network of measurements across the whole area.

There is no modelling of any orbital variations in incoming energy, either daily, yearly or long term Milankovitch variations, based on the assumption that a global yearly average value has a net zero change over the year which is imposed on the energy forcing at the TOA and the QFlux boundary etc..

Thus, the simplest thing to do is to: a) construct a time series of annual global temperature averages, add a random component to each year (value drawn from a gaussian with the given standard deviation and mean zero).

My amateur spreadsheet tracking and projecting the monthly NASA GISS values suggests that while 2018 and 2019 are likely to be cooler than 2017, they may also be the last years on Earth with global average land and ocean surface temperature anomaly below 1C above pre-industrial average (using 1850 - 1900 proxy).

C is not constant for the dT» / dt equation to apply because heat penetrates through different parts of the climate system (different depths of the ocean in particular) over different time scales (also, if T» is supposed to be at some reference location or the global average at some vertical level, T» at other locations will vary; C will have to be an effective C value, the heat per unit change in the T» at the location (s) where T» occurs)

the problem is that this definition implicitly assumes that the global, time average surface temperature is a definite single valued function of the radiative average forcing, which is far from being true since there are considerable horizontal heat transfer modifying the latitudinal repartition of temperature: the local vertical radiative budget is NOT verified.

One solution which has different assumptions than what is used to define the HadCRUT4 global values, would be to calculate the zonal means first and then area weight those — which assumes that missing data warms at the same rate as the local zonal average as opposed to the global means.

For example, if this contribution were to grow linearly with global average temperature change, the upper ranges of sea level rise for SRES scenarios shown in Table SPM - 3 would increase by 0.1 m to 0.2 m. Larger values can not be excluded, but understanding of these effects is too limited to assess their likelihood or provide a best estimate or an upper bound for sea level rise.

In the North Atlantic, the measured values differ markedly from the average global warming: the subpolar Atlantic (an area about half the size of the USA, south of Greenland) has hardly warmed up and in some cases even cooled down, contrary to the global warming trend.

For example, the latest (fifth) assessment report from the U.N.'s Intergovernmental Panel on Climate Change (IPCC) projects that the global average sea level rise over the course of the 21st century would be in the range of 10 to 32 inches, with a mean value of about 19 inches.

Present estimates are that limiting the increase in global average surface temperature to no more than 2 — 2.5 °C above its 1750 value of approximately 15 °C will be required to avoid the most catastrophic, but certainly not all, consequences of climate change.

I said the global temperatures will trend down when my low value average solar parameters are met following 10 years of sub-solar activity in general.

For the purposes of this report, radiative forcing is further defined as the change relative to the year 1750 and, unless otherwise noted, refers to a global and annual average value.

Systematic errors are likely to dominate most estimates of global average change: published values and error bars should be used very cautiously.

El Nino events can temporarily significantly bump the global average surface temperature up from the value it would have been if ENSO was neural, and that the amount of the bump depends upon the timing, strength, and duration?

If we look at the GISS dataset (I'm using [raw GHCN + USHCN corrections] at the moment) as a matrix of year - months x stations, how should one go about getting the data into a single global average annual series, given that there's so many missing values?

Applied Statistics, Spurious Correlations, Cumulative Values, Moving Averages, Moving Window, Degrees of Freedom, Information Theory, Time Series, Data Analysis, Climate Change, Global Warming, Hurricane Trends

So far, I can think of two ways to produce a single global series (a row method and a column method, if you will): (1) average all the available data over all stations by year - month, disregarding any missing values, then average the monthly series by year to get average annual; (2) average each station by year, omitting any years for each station where there are one or more months missing in the station's data, then average over all the stations by year.

It is still the case that observations are more - or-less in the middle of the model simulations, but it can now be seen that the range of simulated values for absolute global average temperature is pretty large (~ 2.5 C).

[2] Ferenc M. Miskolczi, «The stable stationary value of the Earth's global average atmospheric greenhouse - gas optical thickness» E&E 21 (4): 243 - 262 (2010)

The NCAR 2000 black carbon global emission is set at the average of the GISS and GFDL 2000 values, and follows this scaling in the future, for illustrative purposes.

However modelling also indicates that if we continue with our emissions today, by the end of the 21st century, CO2 levels could be between three and four times the pre-industrial values, and global average temperature as much as 6 °C higher.

Hemispheric and global averages as monthly and annual values are available as separate files»