Geophysical Fluid Dynamics Laboratory

About: Geophysical Fluid Dynamics Laboratory is a facility organization based out in Princeton, New Jersey, United States. It is known for research contribution in the topics: Climate model & Climate change. The organization has 525 authors who have published 2432 publications receiving 264545 citations. The organization is also known as: GFDL.

Multimodel Assessment of Regional Surface Temperature Trends: CMIP3 and CMIP5 Twentieth-Century Simulations

Abstract: Regional surface temperature trends from phase 3 of the Coupled Model Intercomparison Project (CMIP3) and CMIP5 twentieth-century runs are compared with observations—at spatial scales ranging from global averages to individual grid points—using simulated intrinsic climate variability from preindustrial control runs to assess whether observed trends are detectable and/or consistent with the models' historical run trends. The CMIP5 models are also used to detect anthropogenic components of the observed trends, by assessing alternative hypotheses based on scenarios driven with either anthropogenic plus natural forcings combined, or with natural forcings only. Modeled variability is assessed via inspection of control run time series, standard deviation maps, spectral analyses, and low-frequency variance consistency tests. The models are found to provide plausible representations of internal climate variability, although there is room for improvement. The influence of observational uncertainty on the t...

Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years

Abstract: . A new long-term data record of Fram Strait sea ice area export from 1935 to 2014 is developed using a combination of satellite radar images and station observations of surface pressure across Fram Strait. This data record shows that the long-term annual mean export is about 880 000 km2, representing 10 % of the sea-ice-covered area inside the basin. The time series has large interannual and multi-decadal variability but no long-term trend. However, during the last decades, the amount of ice exported has increased, with several years having annual ice exports that exceeded 1 million km2. This increase is a result of faster southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Evaluating the trend onwards from 1979 reveals an increase in annual ice export of about +6 % per decade, with spring and summer showing larger changes in ice export (+11 % per decade) compared to autumn and winter (+2.6 % per decade). Increased ice export during winter will generally result in new ice growth and contributes to thinning inside the Arctic Basin. Increased ice export during summer or spring will, in contrast, contribute directly to open water further north and a reduced summer sea ice extent through the ice–albedo feedback. Relatively low spring and summer export from 1950 to 1970 is thus consistent with a higher mid-September sea ice extent for these years. Our results are not sensitive to long-term change in Fram Strait sea ice concentration. We find a general moderate influence between export anomalies and the following September sea ice extent, explaining 18 % of the variance between 1935 and 2014, but with higher values since 2004.

Model assessment of the role of natural variability in recent global warming

Abstract: SINCE the late nineteenth century, the global mean surface air temperature has been increasing at the rate of about 0.5 °C per century1–3, but our poor understanding of low-frequency natural climate variability has made it very difficult to determine whether the observed warming trend is attributable to the enhanced green-house effect associated with increased atmospheric concentrations of greenhouse gases4,5. Here we evaluate the observed warming trend using a 1,000-year time series of global temperature obtained from a mathematical model of the coupled ocean–atmosphere–land system. We find that the model approximately reproduces the magnitude of the annual to interdecadal variation in global mean surface air temperature. But throughout the simulated time series no temperature change as large as 0.5 °C per century is sustained for more than a few decades. Assuming that the model is realistic, these results suggest that the observed trend is not a natural feature of the interaction between the atmosphere and oceans. Instead, it may have been induced by a sustained change in the thermal forcing, such as that resulting from changes in atmospheric greenhouse gas concentrations and aerosol loading.

Modelling future changes in surface ozone: a parameterized approach

Abstract: This study describes a simple parameterization to estimate regionally averaged changes in surface ozone due to past or future changes in anthropogenic precursor emissions based on results from 14 global chemistry transport mod- els. The method successfully reproduces the results of full simulations with these models. For a given emission sce- nario it provides the ensemble mean surface ozone change, a regional source attribution for each change, and an esti- mate of the associated uncertainty as represented by the vari- ation between models. Using the Representative Concentra- tion Pathway (RCP) emission scenarios as an example, we show how regional surface ozone is likely to respond to emis- sion changes by 2050 and how changes in precursor emis- sions and atmospheric methane contribute to this. Surface ozone changes are substantially smaller than expected with the SRES A1B, A2 and B2 scenarios, with annual global mean reductions of as much as 2 ppb by 2050 vs. increases of 4-6 ppb under SRES, and this reflects the assumptions of more stringent precursor emission controls under the RCP scenarios. We find an average difference of around 5 ppb be- tween the outlying RCP 2.6 and RCP 8.5 scenarios, about 75 % of which can be attributed to differences in methane abundance. The study reveals the increasing importance of limiting atmospheric methane growth as emissions of other precursors are controlled, but highlights differences in mod- elled ozone responses to methane changes of as much as a factor of two, indicating that this remains a major uncertainty in current models.

Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC): A new data set of large‐area anomaly time series

Abstract: [1] A new data set containing large-scale regional mean upper air temperatures based on adjusted global radiosonde data is now available up to the present. Starting with data from 85 of the 87 stations adjusted for homogeneity by Lanzante, Klein and Seidel, we extend the data beyond 1997 where available, using a first differencing method combined with guidance from station metadata. The data set consists of temperature anomaly time series for the globe, the hemispheres, tropics (30N–30S) and extratropics. Data provided include annual time series for 13 pressure levels from the surface to 30 mbar and seasonal time series for three broader layers (850–300, 300–100 and 100–50 mbar). The additional years of data increase trends to more than 0.1 K/decade for the global and tropical midtroposphere for 1979–2004. Trends in the stratosphere are approximately 0.5 to 0.9 K/decade and are more negative in the tropics than for the globe. Differences between trends at the surface and in the troposphere are generally reduced in the new time series as compared to raw data and are near zero in the global mean for 1979–2004. We estimate the uncertainty in global mean trends from 1979 to 2004 introduced by the use of first difference processing after 1995 at less than 0.02–0.04 K/decade in the troposphere and up to 0.15 K/decade in the stratosphere at individual pressure levels. Our reliance on metadata, which is often incomplete or unclear, adds further, unquantified uncertainty that could be comparable to the uncertainty from the FD processing. Because the first differencing method cannot be used for individual stations, we also provide updated station time series that are unadjusted after 1997. The Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) data set will be archived and updated at NOAA’s National Climatic Data Center as part of its climate monitoring program.