Sentences with phrase «global average cloud»

Apparently, the global average cloud cover must not have a dramatic effect on the global average clear - sky optical thickness..

«The global average cloud cover declined about 1.56 % over 39 years (1979 to 2009) or ~ 0.4 % / decade, primarily in middle latitudes at middle and high levels (Eastman & Warren, 2012).

We're just beginning to collect data on global average cloud height.

This will become evident soon as observations of global average cloud height become available.

The increase in the global average temperature anomaly and the divergence of land and sea surface temperatures also coincided with two significant changes in global average cloud cover.

«The global average cloud cover declined about 1.56 % over 39 years (1979 to 2009) or ~ 0.4 % / decade, primarily in middle latitudes at middle and high levels (Eastman & Waren, 2012).

That was due to increased global moisture content, decreased global average cloud cover and decreased sea ice extent at high latitudes.

Not exact matches

Changes in the number of cosmic rays hitting the atmosphere due to changes in solar activity can not explain global warming, as average cosmic ray intensities have been increasing since 1985 even as the world has warmed — the opposite of what should happen if cosmic rays produce climate - cooling clouds.

Aerosols are already known to reduce global warming: The vast clouds of sulfates thrown up in the 1991 eruption of Mount Pinatubo in the Philippines, for example, reduced average global temperatures by about half a degree Celsius.

«Global mean time series of surface - and satellite - observed low - level and total cloud cover exhibit very large discrepancies, however, implying that artifacts exist in one or both data sets... The surface - observed low - level cloud cover time series averaged over the global ocean appears suspicious because it reports a very large 5 % - sky - cover increase between 1952 andGlobal mean time series of surface - and satellite - observed low - level and total cloud cover exhibit very large discrepancies, however, implying that artifacts exist in one or both data sets... The surface - observed low - level cloud cover time series averaged over the global ocean appears suspicious because it reports a very large 5 % - sky - cover increase between 1952 andglobal ocean appears suspicious because it reports a very large 5 % - sky - cover increase between 1952 and 1997.

Using monthly - averaged global satellite records from the International Satellite Cloud Climatology Project (ISCCP [5]-RRB- and the MODerate Resolution Imaging Spectroradiometer (MODIS) in conjunction with Sea Surface Temperature (SST) data from the National Oceanic and Atmospheric (NOAA) extended and reconstructed SST (ERSST) dataset [7] we have examined the reliability of long - term cloud measuremCloud Climatology Project (ISCCP [5]-RRB- and the MODerate Resolution Imaging Spectroradiometer (MODIS) in conjunction with Sea Surface Temperature (SST) data from the National Oceanic and Atmospheric (NOAA) extended and reconstructed SST (ERSST) dataset [7] we have examined the reliability of long - term cloud measuremcloud measurements.

For example, episodic deviations in cloud and snow cover, dust and smoke, etc, will have some radiative effect that could cause some global average temperature change.

Thus there is convection within the troposphere that (to a first approximation) tends to sustain some lapse rate profile within the layer — that itself can vary as a function of climate (and height, location, time), but given any relative temperature distribution within the layer (including horizontal and temporal variations and relationship to variable CSD contributors (water vapor, clouds)-RRB-, the temperature of the whole layer must shift to balance radiative fluxes into and out of the layer (in the global time averae, and in the approximation of zero global time average convection above the troposphere), producing a PRt2 (in the global time average) equal to RFt2.

«Our results suggest that, in contrast to other proposals to increase planetary albedo, offsetting mean global warming by reducing marine cloud droplet size does not necessarily lead to a drying, on average, of the continents.

There can / will be local and regional, latitudinal, diurnal and seasonal, and internal variability - related deviations to the pattern (in temperature and in optical properties (LW and SW) from components (water vapor, clouds, snow, etc.) that vary with weather and climate), but the global average effect is at least somewhat constrained by the global average vertical distribution of solar heating, which requires the equilibrium net convective + LW fluxes, in the global average, to be sizable and upward at all levels from the surface to TOA, thus tending to limit the extent and magnitude of inversions.)

Furthermore since modelers tweak cloud parameters to match global albedo and achieve energy balance, and because the AR4 models achieve a good match to global average surface temperatures, there are at least partially compensating errors elsewhere in the models for both albedo and temperature.

... Conclusions Since 1950, global average temperature anomalies have been driven firstly, from 1950 to 1987, by a sustained shift in ENSO conditions, by reductions in total cloud cover (1987 to late 1990s) and then a shift from low cloud to mid and high - level cloud, with both changes in cloud cover being very widespread.

Matthew, it's (+ / --RRB- 4 W / m ^ 2 and is the average annual global long - wave cloud forcing error made by CMIP5 climate models.

Pat Frank: Matthew, it's (+ / --RRB- 4 W / m ^ 2 and is the average annual global long - wave cloud forcing error made by CMIP5 climate models.

Here's an illustration: the Figure below shows what happens when the average ± 4 Wm - 2 long - wave cloud forcing error of CMIP5 climate models [1], is propagated through a couple of Community Climate System Model 4 (CCSM4) global air temperature projections.

(3) This cloud cover reaction is a rapid, positive feedback with respect to TSI, and a slow negative feedback with respect to global average surface temperature.

I merely propagate the global annual average long - wave cloud forcing error made by CMIP5 climate models, in annual steps through a projection.

C40 Cities Climate Leadership Group, 12 California, 7, 68, 102, 128, 169 - 170, 187, 196, 232 - 234, 245 California Energy Commission, 232 Cambridge Media Environment Programme (CMEP), 167 - 168 Cambridge University, 102 Cameron, David, 11, 24, 218 Cameroon, 25 Campbell, Philip, 165 Canada, 22, 32, 64, 111, 115, 130, 134, 137, 156 - 157, 166, 169, 177, 211, 222, 224 - 226, 230, 236, 243 Canadian Meteorological and Oceanographic Society (CMOS), 15 Cap - and - trade, 20, 28, 40 - 41, 44, 170, 175 allowances (permits), 41 - 42, 176, 243 Capitalism, 34 - 35, 45 Capps, Lois, 135 Car (see vehicle) Carbon, 98, 130 Carbon Capture and Storage (CCS), 192 Carbon Capture and Storage Association, 164 Carbon credits (offsets), 28 - 29, 42 - 43, 45 Carbon Cycle, 80 - 82 Carbon dioxide (CO2), 9, 18, 23, 49 - 51, 53, 55, 66 - 67, 72 - 89, 91, 98 - 99, 110, 112, 115, 118, 128 - 132, 137, 139, 141 - 144, 152, 240 emissions, 12, 18 - 25, 28 - 30, 32 - 33, 36 - 38, 41 - 44, 47, 49, 53, 55, 71 - 72, 74, 77 - 78, 81 - 82, 108 - 109, 115, 132, 139, 169, 186, 199 - 201, 203 - 204, 209 - 211, 214, 217, 219, 224, 230 - 231, 238, 241, 243 - 244 Carbon Dioxide Analysis Center, 19 Carbon Expo, 42 Carbon, footprint, 3, 13, 29, 35, 41, 45, 110, 132 tax, 20, 44, 170 trading, 13, 20, 40, 43, 44, 176, 182 Carbon monoxide (CO), 120 Carbon Reduction Commitment (CRC), 44 Carlin, George, 17 Carter, Bob, 63 Carter, Jimmy, 186, 188 Cato Institute, 179 CBS, 141, 146 Center for Disease Control, 174 Center for the Study of Carbon Dioxide and Global Change, 62, 139 Centre for Policy Studies, 219 CERN (European Organization for Nuclear Research), 96 Chavez, Hugo, 34 Chicago Tribune, 146 China, 29, 32 - 33, 60 - 62, 120, 169, 176, 187 - 188, 211, 216, 225 - 226, 242 - 243 China's National Population and Planning Commission, 33 Chinese Academy of Sciences, 60 Chirac, Jacques, 36 Chlorofluorocarbons, 42 - 43, 50 Choi, Yong - Sang, 88 Christy, John, 105 Churchill, Winston, 214, 220 Chu, Steven, 187 Citibank (Citigroup), 40, 176 Clean Air Act, 85, 128 - 129 Clean Development Mechanism, 42 Climate Action Partnership, 14 Climate alarm, 4, 13, 21, 32, 35, 38, 56, 102 - 103, 115 - 117, 120, 137, 156, 168, 173, 182 Climate Audit, 66 Climate change, adaptation, 39, 110, 112 mitigation, 16, 39, 110 Climate Change and the Failure of Democracy, 34 Climate Change: Picturing the Science, 121 Climate Change Reconsidered, 242 Climate conference, 38 Cancun, 18, 29, 36 - 37, 124 - 125, 242 Copenhagen, 33, 36, 109, 125, 156, 158, 175, 241 - 242 Durban, 13, 36 - 37, 166, 242 - 243 Climategate, 2, 67, 152, 158 - 170, 180, 182, 242 Climate Protection Agreement, 12 Climate Research Unit (CRU), 48, 67, 120, 147, 152 - 153, 158 - 160, 162 - 163, 165 - 167, 169 Climate Science Register, 142 Climatism, definition, 2, 7 Clinton, Bill, 176, 178 Clinton Global Initiative, 176 CLOUD project, 96 Club of Rome, 21, 186 CO2Science, 59, 61 - 62, 66, 131 Coal, 19 - 20, 39 - 41, 80, 126, 128 - 129, 175, 185 - 186, 188 - 190, 192 - 196, 199 - 201, 209, 214, 217, 219, 222, 229 Coase, Ronald, 145 Coca - Cola, 138 Cogley, Graham, 156 Cohen, David, 220 Colorado State University, 117, 181 Columbia University, 7 Columbus, Christopher, 58 Computer models, 16, 51 - 53, 56, 67, 72, 74,77 - 79, 82, 87, 89 - 91, 94, 105, 110 - 111, 120, 124, 138 - 140, 168, 171,173, 181, 238, 240, 246 Conference on the Changing Atmosphere, 15 Consensus, scientific, 12 Copenhagen Business School, 134 Coral, 53 Corporate Average Fuel Economy, 22 - 23 Cosmic Rays, 72, 93 - 99, 180 Credit Suisse, 176 Crow, Cheryl, 30 Crowley, Tom, 167 Cuadrilla Resources, 224 - 225 Curry, Judith, 164, 167 Cycles, natural, 3, 16, 57, 62 - 63, 66 - 69, 72, 80, 99, 103, 138, 238, 240 Milankovich, 62, 67, 80 Cyprus, 134 Czech Republic, 12, 37

-- 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).

The 1991 volcanic eruptions (Pinatubo, Hudson) injected 23 Megatonnes of SO2 into the stratosphere, leaving a sulfurous cloud that circled the globe for about 2 years before finally settling out (together with a large quantity of fine particulate matter which rapidly settled out) The sulfurous cloud caused average global temperatures to drop by 0.55 deg.

The two solar cycles from 1976 to 1996 had a stronger solar magnetic field with more GCR deflection leading to 3 % less average cosmic ray flux, fewer shading clouds, and the global warming scare.

What nobody knows is how you would take a putative tiny variation in said GCR flux measuring on average 6 particles per cm ^ 2 per second and turn it into a global effect — especially one that only made clouds during the daytime.

The impact of these changes in cloud cover can account for the variations in HadCRUT4 global average temperature anomalies and the divergence between land and sea temperatures.

But again such global averages are of little value: regional observations should be related to the regional cloud coverage and albedo and possibly to changes of the strength of surface currents.

76) Dr Roy Spencer, a principal research scientist at the University of Alabama in Huntsville, has indicated that out of the 21 climate models tracked by the IPCC the differences in warming exhibited by those models is mostly the result of different strengths of positive cloud feedback — and that increasing CO2 is insufficient to explain global - average warming in the last 50 to 100 years.

2 * the radiation from the surface that has escaped absorption by water vapor, clouds and CO2 (global average 20 W / m ²),

The solar heating of the surface is mostly carried away by evaporation, with some convection and some radiation arriving to the cosmos after escaping absorption by water vapor and clouds, for a global average of about 20 W / m ².

Our long - term analysis of MISR data finds no statistically significant correlations between cosmic rays and global albedo or globally averaged cloud height, and no evidence for any regional or lagged correlations.

Maybe it all averages out, but if there are any cloud cover changes as discussed at that BH article then there might be warming or cooling that is not about «global warming» per se (as anything related to CO2).

Hartmnn derived an average cloud radiative forcing of -27.6 W / m ^ 2 — a net cooling — as the overall average effect of clouds on global climate.

Essentially, it's the average cloud forcing error made by CMIP5 - level GCMs, when they were used to hindcast 20 years of satellite observations of global cloud cover (1985 - 2005).

I don't think he did anything with cloud height or cloud cover, so I'm confused by your question, but either way the plots reflect monthly global average data with a 12 running mean applied to smooth out the seasonal cycle.

The ± 4 Wm ^ -2 is the average of the errors the models made in hindcasting global cloud forcing.

Global mean cloud properties averaged over the period 1986 - 1993 are: cloud amount = 0.675 ± 0.012, cloud top temperature = 261.5 ± 2.8 K, and cloud optical thickness = 3.7 ± 0.3, where the plus - minus values are the rms deviations of global monthly mean values from their long - term avGlobal mean cloud properties averaged over the period 1986 - 1993 are: cloud amount = 0.675 ± 0.012, cloud top temperature = 261.5 ± 2.8 K, and cloud optical thickness = 3.7 ± 0.3, where the plus - minus values are the rms deviations of global monthly mean values from their long - term avglobal monthly mean values from their long - term average.

Bottom, the top left US NAS panel showing the global 20th century air temperature hindcast, but now with uncertainty bars from propagated ± 4 Wm - 2 CMIP5 average cloud forcing error.

We disagree with this conclusion, arguing that when cloud properties are considered as a global average (Fig. 3) or over areas of frequent cloud cover (Fig. 4), the strong anti-correlation between low and middle - to - high level cloud is both clear, and statistically significant.

[A] now - classic set of General Circulation Model (GCM) experiments ¬ produced global average surface temperature changes (due to doubled atmospheric CO2 concentration) ranging from 1.9 °C to 5.4 °C, simply by altering the way that cloud radiative properties were treated in the model.

How do clouds change their annual average global albedo spontaneously when their individual lifetime is minutes to hours?

Bear in mind that the representation of clouds in climate models (and of the water vapour which is intimately involved with cloud formation) is such as to amplify the forecast global warming from increasing atmospheric carbon dioxide — on average over most of the models — by a factor of about three (5).

The global average forcing is about — 15 to — 20 W m - 2 and thus clouds have a major cooling effect on the planet.

The global cloud cover averages around 0.68 when analyzing clouds with optical depth larger than 0.1.

And Miskolczi calculates the global average optical thickness of the atmosphere — without clouds — at 1.87.

Increased equatorial insolation due to reduced Easterly Wave SC cloud mass, promoting increased northern hemisphere evaporation and precipitation resulting in a hiatus on a global averaging basis, but regional specific cause - and - effect variability?

Obviously, we are currently in transition and our global atmospheric cell structures are going to shift rapidly with broadly expanding Hadley cell and collapsing Arctic cell leading to meridional migration of average cloud cover and reduced albedo.

If the counter argument is that these changes are a response to Global Warming - it would be really good to see a graph showing what the models predicted / hindcast on average for the global cloud Global Warming - it would be really good to see a graph showing what the models predicted / hindcast on average for the global cloud global cloud cover.