Institution
Geophysical Fluid Dynamics Laboratory
Facility•Princeton, New Jersey, United States•
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.
Topics: Climate model, Climate change, Sea surface temperature, Tropical cyclone, Thermohaline circulation
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a coupled atmosphere-wave model by perturbing the sea surface temperatures (SSTs) with anomalies generated by the Working Group on Coupled Modeling (WGCM) phase 3 of the Coupled model Intercomparison Project (CMIP3) coupled models that use the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4)/Special Report on Emissions Scenarios A1B (SRES A1b) scenario late in the twenty-first century.
Abstract: Surface wind (U10) and significant wave height (Hs) response to global warming are investigated using a coupled atmosphere–wave model by perturbing the sea surface temperatures (SSTs) with anomalies generated by the Working Group on Coupled Modeling (WGCM) phase 3 of the Coupled Model Intercomparison Project (CMIP3) coupled models that use the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4)/Special Report on Emissions Scenarios A1B (SRES A1B) scenario late in the twenty-first century.Several consistent changes were observed across all four realizations for the seasonal means: robust increase of U10 and Hs in the Southern Ocean for both the austral summer and winter due to the poleward shift of the jet stream; a dipole pattern of the U10 and Hs with increases in the northeast sector and decreases at the midlatitude during boreal winter in the North Atlantic due to the more frequent occurrence of the positive phases of the North Atlantic Oscillation (NAO); and strong de...
71 citations
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TL;DR: In this article, seven coupled model intercomparison Project Phase 5 (CMIP5) models using interactive dust emission schemes are examined against satellite-derived dust optical depth (DOD) during 2004-2016.
Abstract: . Dust aerosol plays an important role in the climate system by
affecting the radiative and energy balances. Biases in dust modeling may
result in biases in simulating global energy budget and regional climate. It
is thus very important to understand how well dust is simulated in the
Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Here seven
CMIP5 models using interactive dust emission schemes are examined against
satellite-derived dust optical depth (DOD) during 2004–2016. It is found that multi-model mean can largely capture the global spatial
pattern and zonal mean of DOD over land in present-day climatology in MAM and
JJA. Global mean land DOD is underestimated by −25.2 % in MAM to
−6.4 % in DJF. While seasonal cycle, magnitude, and spatial pattern are
generally captured by the multi-model mean over major dust source regions such as
North Africa and the Middle East, these variables are not so well represented
by most of the models in South Africa and Australia. Interannual variations
in DOD are not captured by most of the models or by the multi-model mean.
Models also do not capture the observed connections between DOD and local
controlling factors such as surface wind speed, bareness, and precipitation.
The constraints from surface bareness are largely underestimated while the
influences of surface wind and precipitation are overestimated. Projections of DOD change in the late half of the 21st century under the
Representative Concentration Pathways 8.5 scenario in which the multi-model
mean is compared with that projected by a regression model. Despite the
uncertainties associated with both projections, results show some
similarities between the two, e.g., DOD pattern over North Africa in DJF and
JJA, an increase in DOD in the central Arabian Peninsula in all seasons, and
a decrease over northern China from MAM to SON.
71 citations
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TL;DR: In this article, the authors use a global ocean biogeochemical general circulation model developed at GFDL and Princeton to examine the effect of iron fertilization on the long-term biological response to iron addition.
Abstract: . While nutrient depletion scenarios have long shown that the high-latitude High Nutrient Low Chlorophyll (HNLC) regions are the most effective for sequestering atmospheric carbon dioxide, recent simulations with prognostic biogeochemical models have suggested that only a fraction of the potential drawdown can be realized. We use a global ocean biogeochemical general circulation model developed at GFDL and Princeton to examine this and related issues. We fertilize two patches in the North and Equatorial Pacific, and two additional patches in the Southern Ocean HNLC region north of the biogeochemical divide and in the Ross Sea south of the biogeochemical divide. We evaluate the simulations using observations from both artificial and natural iron fertilization experiments at nearby locations. We obtain by far the greatest response to iron fertilization at the Ross Sea site, where sea ice prevents escape of sequestered CO2 during the wintertime, and the CO2 removed from the surface ocean by the biological pump is carried into the deep ocean by the circulation. As a consequence, CO2 remains sequestered on century time-scales and the efficiency of fertilization remains almost constant no matter how frequently iron is applied as long as it is confined to the growing season. The second most efficient site is in the Southern Ocean. The North Pacific site has lower initial nutrients and thus a lower efficiency. Fertilization of the Equatorial Pacific leads to an expansion of the suboxic zone and a striking increase in denitrification that causes a sharp reduction in overall surface biological export production and CO2 uptake. The impacts on the oxygen distribution and surface biological export are less prominent at other sites, but nevertheless still a source of concern. The century time scale retention of iron in this model greatly increases the long-term biological response to iron addition as compared with simulations in which the added iron is rapidly scavenged from the ocean.
71 citations
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TL;DR: In this paper, the authors show that the intermediate depths in the low latitudes, Northwest Atlantic, and parts of the Arctic Ocean become younger under global warming, and that the decreases result from changes in the relative contributions of old deep waters and younger surface waters.
Abstract: . Since the upper ocean takes up much of the heat added to the earth system by anthropogenic global warming, one would expect that global warming would lead to an increase in stratification and a decrease in the ventilation of the ocean interior. However, multiple simulations in global coupled climate models using an ideal age tracer which is set to zero in the mixed layer and ages at 1 yr/yr outside this layer show that the intermediate depths in the low latitudes, Northwest Atlantic, and parts of the Arctic Ocean become younger under global warming. This paper reconciles these apparently contradictory trends, showing that the decreases result from changes in the relative contributions of old deep waters and younger surface waters. Implications for the tropical oxygen minimum zones, which play a critical role in global biogeochemical cycling are considered in detail.
71 citations
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TL;DR: In this paper, the authors used a "perfect model" experimental design in which high-resolution dynamical climate model output is used as a surrogate for both past and future observations, and found that while SD in general adds considerable value, in certain well-defined circumstances it can produce highly erroneous results.
Abstract: Statistical downscaling (SD) is commonly used to provide information for the assessment of climate change impacts. Using as input the output from large-scale dynamical climate models and observation-based data products, SD aims to provide a finer grain of detail and to mitigate systematic biases. It is generally recognized as providing added value. However, one of the key assumptions of SD is that the relationships used to train the method during a historical period are unchanged in the future, in the face of climate change. The validity of this assumption is typically quite difficult to assess in the normal course of analysis, as observations of future climate are lacking. We approach this problem using a “perfect model” experimental design in which high-resolution dynamical climate model output is used as a surrogate for both past and future observations.We find that while SD in general adds considerable value, in certain well-defined circumstances it can produce highly erroneous results. Furthe...
71 citations
Authors
Showing all 546 results
Name | H-index | Papers | Citations |
---|---|---|---|
Alan Robock | 90 | 346 | 27022 |
Isaac M. Held | 88 | 215 | 37064 |
Larry W. Horowitz | 85 | 253 | 28706 |
Gabriel A. Vecchi | 84 | 282 | 31597 |
Toshio Yamagata | 83 | 294 | 27890 |
Li Zhang | 81 | 727 | 26684 |
Ronald J. Stouffer | 80 | 153 | 56412 |
David Crisp | 79 | 328 | 18440 |
Thomas L. Delworth | 76 | 178 | 26109 |
Syukuro Manabe | 76 | 129 | 25366 |
Stephen M. Griffies | 68 | 202 | 18065 |
John Wilson | 66 | 487 | 22041 |
Arlene M. Fiore | 65 | 168 | 17368 |
John P. Dunne | 64 | 189 | 17987 |
Raymond T. Pierrehumbert | 62 | 192 | 14685 |