Sentences with phrase «in observational datasets»

Thorne et al. (2007) suggested that the absence of the mid-tropospheric warming might be attributable to uncertainties in the observed record: however, Douglass et al. (2007) responded with a detailed statistical analysis demonstrating that the absence of the projected degree of warming is significant in all observational datasets.

Po Chedley say: «The apparent model - observational difference for tropical upper tropospheric warming represents an important problem, but it is not clear whether the difference is a result of common biases in GCMs, biases in observational datasets, or both.»

9.4.1.3.2 Upper tropospheric temperature trends Most climate model simulations show a larger warming in the tropical troposphere than is found in observational datasets (e.g., (McKitrick et al., 2010)(Santer et al., 2012)-RRB-.

The experts you selectively quote say» it is not clear whether the difference is a result of common biases in GCMs, biases in observational datasets, or both», whereas you make your own conclusion and suggest that the radiosonde are correct and everything else is wrong.

So what we are really interested in is the waiting time to the next unambiguous record i.e. a record that is at least 0.1 ºC warmer than the previous one (so that it would be clear in all observational datasets).

Not exact matches

«We overcame this challenge by trying to push the observational science to the highest resolutions, allowing us to more readily compare observations across datasets,» said Nicholas Schmerr, the study's co-author and an assistant research scientist in geology at the University of Maryland.

... Even in the satellite era — the best observed period in Earth's climate history — there are significant uncertainties in key observational datasets.

Thus my plea to the modelers: please mention the name of the observational dataset in your legend.

In short, irrespective of what observational dataset was used — it's likely that an estimate of forced response made in 2014 would be biased cold, which on its own would translate to an overestimate of the available budget of about 40GtIn short, irrespective of what observational dataset was used — it's likely that an estimate of forced response made in 2014 would be biased cold, which on its own would translate to an overestimate of the available budget of about 40Gtin 2014 would be biased cold, which on its own would translate to an overestimate of the available budget of about 40GtC.

There are very good scientific reasons for using observational datasets that fill in data sparse regions in many analyses — I will continue using them — but we should be aware of not only their strengths but also of their weaknesses.

We also checked that using different observational datasets (NOAA, Berkeley, GISTEMP) gave similar results (results shown in Extended Data).

Part of the story here is that it is this very sort of very careful work done by John Kennedy and Phil Jones and other colleagues working on these datasets that has allowed us to start challenging the models and our understanding in such a detailed way — in some ways it is quite remarkable that the observational data is now good enough to identify this level of detail in how the climate varies and changes.

Using the SFZ 2008 tar file archive data in combination with the deep - ocean diagnostic model and control - run data used in SFZ 2008, and a deep - ocean diagnostic observational trend calculated from the Levitus et al 2005 dataset, I can produce broadly similar climate parameter PDFs to those in the Forest 2006 main results (Figure 2: GSOLSV, κsfc = 16, uniform prior), with a peak climate sensitivity around S = 3.

The surface and upper air temperature observational datasets are continually revised and then made obsolete, so obtaining the data used in a study carried out using 10 year old data is not very practicable.

In summary, I have copies of datasets used in two studies related to Forest 2006, both of which should contain the same temperature data as used in Forest 2006 (save for the deep - ocean observational dataIn summary, I have copies of datasets used in two studies related to Forest 2006, both of which should contain the same temperature data as used in Forest 2006 (save for the deep - ocean observational datain two studies related to Forest 2006, both of which should contain the same temperature data as used in Forest 2006 (save for the deep - ocean observational datain Forest 2006 (save for the deep - ocean observational data).

Morice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones, 2012: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset.

Observational analyses do suggest a link between heavy precipitation and storm surge, but the available dataset was too short to explore the statistical relationships in a relevant part of the frequency distribution.

Monitoring changes in Australia's climate requires observational datasets that are not only good quality, but also homogeneous through time.

... Even in the satellite era — the best observed period in Earth's climate history — there are significant uncertainties in key observational datasets.

I note that both the gridded model and observational datasets used in our IJoC paper are freely available to researchers.

You should have no problem in accessing exactly the same model and observational datasets that we employed.

For the thirty - year period 1979 to 2009 the observational datasets find in the tropical lower troposphere (LT) a warming trend of 0.07 °C to 0.15 °C per decade.

For the thirty - year period 1979 to 2009 (sometimes updated through 2010 or 2011), the various observational datasets find, in the tropical lower troposphere (LT, see Chapter 2 for definition), an average warming trend ranging from 0.07 °C to 0.15 °C per decade.

Because the differences between the various observational estimates are largely systematic and structural (Chapter 2; Mears et al., 2011), the uncertainty in the observed trends can not be reduced by averaging the observations as if the differences between the datasets were purely random.

Morice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset, J. Geophys.

This study addresses the challenge by undertaking a formal detection and attribution analysis of SCE changes based on several observational datasets with different structural characteristics, in order to account for the substantial observational uncertainty.

Non-stationarity in the observational / reanalysis datasets complicated the evaluation of downscaling performance.

Which is pretty much exactly what I wrote in my original response with a few additional details about reconciling the differences between observational datasets.

«Evidence for climate change in the satellite cloud record» «Cloud feedback mechanisms and their representation in global climate models» «A net decrease in the Earth's cloud, aerosol, and surface 340 nm reflectivity during the past 33 yr (1979 — 2011)» «New observational evidence for a positive cloud feedback that amplifies the Atlantic Multidecadal Oscillation» «Impact of dataset choice on calculations of the short - term cloud feedback»

While such models lack adequate observational datasets of subsurface soil properties and / or geology, it is clear that the time scale for deep permafrost thaw is measured in centuries, not years.

They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming2, 3.

«Using state - of - the - art observational datasets and results from a large archive of computer mode simulations, a consortium of scientists from 12 different institutions has resolved a long - standing conundrum in climate science»

, which are in fact the excess of AFari + aci over RFari, need adjusting (scaling down by (0.73 − 0.4) / (0.9 − 0.4), all years) to obtain a forcing dataset based on a purely observational estimate of aerosol AF rather than the IPCC's composite estimate.

The greater rate of warming in the tropical mid-troposphere that is projected by general - circulation models is absent in this and all other observational datasets, whether satellite or radiosonde.

The first panel shows the raw «spaghetti» projections, with different observational datasets in black and the different emission scenarios (RCPs) shown in colours.

The basic observational result seems to be similar to what we can produce but use of slightly different datasets, such as the EBAF CERES dataset, changes the results to be somewhat less in magnitude.