Sentences with phrase «aerosol data from»

Aerosol data from the North Slope of Alaska are provided through a collaborative effort with the National Oceanic and Atmospheric Administration's (NOAA) Earth System Research Laboratory.

Not exact matches

Cloud - to - ground lightning (CG) flash data from the National Lightning Detection Network matched against satellite - mapped aerosol plumes imply that thunderstorms forming in smoke - contaminated air masses generated large amounts of lightning with positive polarity (+ CGs).

The international team examined vertical wind motion, or updrafts, and aerosol concentration data from one of these stations from March to May 2014.

In the new work, Surabi Menon of the NASA Goddard Institute for Space Studies and colleagues used aerosol data collected from 46 ground stations in China to assess four different climate modeling scenarios.

Combined with measurements from an instrument aboard NASA's Calipso satellite — another member of the A-Train — the data from Glory's APS will allow scientists to understand how different types of aerosols are distributed throughout the layers of the atmosphere.

These particles pose health risks to populations, especially to the medically vulnerable, By infusing CATS data directly into aerosol models, data from CATS can make a difference in tracking and responding to impacts of similar events in the future.

Such predictions can only benefit from the relative wealth of data concerning aerosols that scientists have recently collected.

And since the researchers are still analyzing data collected over the past few years, a clearer picture of aerosol behavior might yet still emerge from the haze.

According to a report that used INDOEX data and was published last month in Science, aerosols from man - made pollution may also play a role in weakening the planet's water supply.

Sieving through the data from CALIPSO — a satellite jointly launched by France and the U.S. — they found a thick layer of aerosols between 13 and 18 kilometers above sea level over a large area stretching across the eastern Mediterranean Sea, northern India and western China.

Data gathered at a site near Tsukuba, Japan, show that about a third of stratospheric aerosols — much of them from small volcanoes — sit below 15 kilometers.

Using climate models and data collected about aerosols and meteorology over the past 30 years, the researchers found that air pollution over Asia — much of it coming from China — is impacting global air circulations.

Scientists use data from the SGP to learn about cloud, aerosol, and atmospheric processes, which in turn leads to improvements in models of the Earth's climate.

Scientists are involved in the evaluation of global - scale climate models, regional studies of the coupled atmosphere / ocean / ice systems, regional severe weather detection and prediction, measuring the local and global impact of the aerosols and pollutants, detecting lightning from space and the general development of remotely - sensed data bases.

Given the increasing availability of aerosol composition data collected from aircraft, the team expects that their approach can be successfully applied to improve understanding of a wide range of sophisticated processes and phenomena related to aerosols, including how properties evolve with time and the dynamic interactions between aerosols and clouds.

The team gathered simulated data of the two more variable biogenic aerosols separately, taking sulfate concentrations from a suite of computer models called AeroCom.

Analyses of the ground and aircraft data performed by Setyan et al. (2012), Shilling et al. (2013), and Kleinman et al. (2016) showed that organic aerosol production increased when human - caused emissions from Sacramento mixed with air rich in isoprene, an organic compound wafting from many plants that originate in the area's foothills.

The upper tail is particularly long in studies using diagnostics based on large - scale mean data because separation of the greenhouse gas response from that to aerosols or climate variability is more difficult with such diagnostics (Andronova and Schlesinger, 2001; Gregory et al., 2002a; Knutti et al., 2002, 2003).

Forster and Gregory (2006) estimate ECS based on radiation budget data from the ERBE combined with surface temperature observations based on a regression approach, using the observation that there was little change in aerosol forcing over that time.

Research aircraft outfitted with aerosol probes and sensors obtained data from the sky above Manaus during the GoAmazon research campaign.

But models are not tuned to the trends in surface temperature, and as Gavin noted before (at least for the GISS model), the aerosol amounts are derived from simulations using emissions data and direct effects determined by changes in concentrations.

If you «use all of the data» you can't detect any change in trend from forcings known to make a difference (e.g. sulfate aerosols, which peaked in the 1940 - 1970 range from US sources and again later from Chinese).

As I said to Andy Revkin (and he published on his blog), the additional decade of temperature data from 2000 onwards (even the AR4 estimates typically ignored the post-2000 years) can only work to reduce estimates of sensitivity, and that's before we even consider the reduction in estimates of negative aerosol forcing, and additional forcing from black carbon (the latter being very new, is not included in any calculations AIUI).

Concentration at stabilization including GHGs and aerosols (2008 = 395 ppm) Peaking year of CO 2 emissions Change in CO 2 emissions in 2050 (percent of 2000 emissions) 2.0 -2.4350-400445-4902000-2015 − 85 to − 50 2.4 -2.8400-440490-5352000-2020 − 60 to − 30 2.8 -3.2440-485535-5902010-2030 − 30 to +5 3.2 -4.0485-570590-7102020-2060 +10 to +60 4.0 -4.9570-660710-8552050-2080 +25 to +85 4.9 -6.1660-790855-11302060-2090 +90 to +140 Data from: IPCC, 2007: Synthesis Report.

One year boundary layer aerosol size distribution data from five Nordic background stations.

The meeting included focus sessions on computational methods for modeling and handling large amounts of data, characterizing uncertainty, research on dust and aerosols, soils, urban systems and individual topics that are too numerous to list, from science communication and stellar astrophysics to biogeochemistry.

The short - term cooling imparted by volcanic aerosols is clearly non-anthropogenic, but these forcings are reasonably well known from relevant observational data.

Of the four variables, aerosols really make the difference in explaining temperature variations, so it would be important that aerosol values come from legitimate and verifiable data series.

It strikes me that the Arctic data also reflects the northern hemisphere accumulation of aerosols, while the Antarctic data is much less affected by aerosols, which we know affected NH temperatures from about 1940 - 1975.

The overwhelming uncertainty in determining TCR from historical data is the uncertainty about the historical net warming or cooling effects of aerosols as discussed in Lewis and Curry (2014).

For changes from 1861 - 1900 to 1957 - 1994, with non-aerosol forcing change = 1.41: ocean heat change 0.08 (new Levitus data): temperature change = 0.31 it computes aerosol forcing = -0.42 for a net forcing of 0.99 and a computed climate sensitivity of 1.3.

Add to that scaled monthly sunspot data to introduce the 0.1 deg C variations is surface temperature resulting from the solar cycle and add scaled monthly Stratospheric Aerosol Optical Depth data for dips and rebounds due to volcanic eruptions, and global surface temperature anomalies can be reproduced quite well.

The dataset starts within a few months from October 2001, and the initial Bourassa data were used as background aerosol optical depth following the Pinatubo decay.

Recent studies have shown that inverting such data allows for the potential of separating the retrieval of aerosol properties from ocean color monitoring in the visible part of the spectrum.

It is easy but somewhat speculative to invoke combinations of solar changes, aerosols (anthropogenic and volcanic), and internal climate modes to explain the deviations from a smoothly rising curve, and there are ample data to indicate these played a role.

But it is absolutely more accurate than modeled GCM data squished from manipulated records that require periodic convenient up and down changes in aerosol content in the world's atmosphere so the model output matches past manipulated temporarily records... aerosol measurements that have never been previously promoted until the constants in GCM models required year - by - year changes.

One of the most glaring examples is the correlation between model sensitivity and the amount of sulfate aerosols assumed as input (which keeps sensitive models from running away from the data).

TCR (1 + beta) extracted from HadCRUT4 data since 1850 is 1.8 C and only has the uncertainty of the global mean surface temperature measurement that you argue in Lewis and Curry (2014) is insignificant compared to the aerosol contribution uncertainty.

And of course, had he made such a comparison by presenting the data from previous years, it would have refuted and so prevented his conclusions, that volcanic aerosols suppressed the warming.

You mean to tell me a top climate scientist from Germany (where geoengineering in the skies is all too obvious) has not found in all his mountains of data the telltale signature of massive aerosol spraying occurring around the world 24/7?

Data on non-sulphur aerosols are sparse and highly speculative, but in terms of global sulphur emissions, these appear to have declined from a range of 75 ± 10 MtS in 1990 to 55 — 62 MtS in 2000.

Chowdhary, J., B. Cairns, and L.D. Travis, 2002: Case studies of aerosol retrievals over the ocean from multiangle, multispectral photopolarimetric remote sensing data.

The data and the statistical analysis does not provide the evidence that the so called «pause», a time period with a lower trend estimate than the longer - term trend estimate, was more than just a short - term fluctuation around the median warming trend, mostly due to short - term unforced internal variability in the Earth system (and some contribution from decreasing solar activity and increased reflecting aerosols in the atmosphere, counteracting the increased greenhose gas forcing to some degree), like the «acceleration» over the 16 - year period from 1992 to 2007 (e.g., UAH trend: 0.296 + / - 0.213 (2 sigma) deg.

So if at this point all GCMs hypothetically turned out to share similar flaws - e.g. regarding the unknowns for which there's essentially no data - the responses at the LGM of water vapour, clouds, aerosols etc - wouldn't that undermine validated model approaches to estimating climate sensitivity from even the LGM?

Foster and Rahmstorf characterize ENSO by using the Multivariate ENSO Index (MEI), aerosol optical thickness data (AOD) for volcanic activity, and solar irradiance data (from PMOD) to characterize solar activity.

In the article «Global atmospheric particle formation from CERN CLOUD measurements,» sciencemag.org, 49 authors concluded «Atmospheric aerosol nucleation has been studied for over 20 years, but the difficulty of performing laboratory nucleation - rate measurements close to atmospheric conditions means that global model simulations have not been directly based on experimental data.....

The black line, reconstructed from ISCCP satellite data, «is a purely statistical parameter that has little physical meaning as it does not account for the non-linear relations between cloud and surface properties and planetary albedo and does not include aerosol related albedo changes such as associated with Mt. Pinatubo, or human emissions of sulfates for instance» (Real Climate).

Myhre, G., N. Bellouin, T.F. Berglen, T.K. Berntsen, O. Boucher, A. Grini, I.S.A. Isaksen, M. Johnsrud, M.I. Mishchenko, F. Stordal, and D. Tanre, 2007: Comparison of the radiative properties and direct radiative effect of aerosols from a global aerosol model and remote sensing data over ocean.

Steve I think stratospheric aerosol optical depth can be derived from CALIPSO data (see Fig. 8.13 of AR5 Ch.

Ken, I agree your slope trends apart from Anthro aerosol, where I think you may have made some mistake, based on regressing on annual 1900 - 2005 data.