GFDL - Geophysical Fluid Dynamics Laboratory

Highlighted Papers

• Shevliakova, Elena, S. W. Pacala, Sergey Malyshev, G. C. Hurtt, P. C. D. Milly, J. P. Caspersen, Lori T. Sentman, J. P. Fisk, C. Wirth, and C. Crevoisier, 2009:  Carbon cycling under 300 years of land-use change: The importance of the secondary vegetation sink, Global Biogeochemical Cycles, 23, GB2022, doi:10.1029/2007GB003176. [ PDF]
  

  We have developed a dynamic land model (LM3V) able to simulate ecosystem
  dynamics and exchanges of water, energy, and CO2 between land and atmosphere.
  LM3V is specifically designed to address the consequences of land use and
  land management changes including cropland and pasture dynamics, shifting
  cultivation, logging, fire, and resulting patterns of secondary regrowth.
  Here we analyze the behavior of LM3V, forced with the output from the Geophysical
  Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation
  data, and four historic scenarios of land use change for 1700?2000. Our
  analysis suggests a net terrestrial carbon source due to land use activities
  from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference
  in the historic cropland distribution. This magnitude is substantially smaller
  than previous estimates from other models, largely due to our estimates
  of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating
  agricultural land clearing since the 1960s. For the 1990s, our estimates
  for the pastures’ carbon flux vary from a source of 0.37 to a sink of 0.15
  GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9
  GtC/a. Our process-based model suggests a smaller net deforestation source
  than earlier bookkeeping models because it accounts for decelerated net
  conversion of primary forest to agriculture and for stronger secondary vegetation
  regrowth in tropical regions. The overall uncertainty is likely to be higher
  than the range reported here because of uncertainty in the biomass recovery
  under changing ambient conditions, including atmospheric CO2 concentration,
  nutrients availability, and climate.

• Henson, S A., D Raitsos, John P Dunne, and A McQuatters-Gollop, November 2009: Decadal variability in biogeochemical models: Comparison with a 50-year ocean colour dataset. Geophysical Research Letters, 36(L21601), doi:10.1029/2009GL040874. 
  

  Assessing the skill of biogeochemical models to hindcast past variability
  is challenging, yet vital in order to assess their ability to predict biogeochemical
  change. However, the validation of decadal variability is limited by the
  sparsity of consistent, long-term biological datasets. The Phytoplankton
  Colour Index (PCI) product from the Continuous Plankton Recorder survey,
  which has been sampling the North Atlantic since 1948, is an example of
  such a dataset. Converting the PCI to chlorophyll values using SeaWiFS data
  allows a direct comparison with model output. Here we validate decadal variability
  in chlorophyll from the GFDL TOPAZ model. The model demonstrates skill at
  reproducing interannual variability, but cannot simulate the regime shifts
  evident in the PCI data. Comparison of the model output, data and climate
  indices highlights under-represented processes that it may be necessary
  to include in future biogeochemical models in order to accurately simulate
  decadal variability in ocean ecosystems.

• Henson, S A., John P Dunne, and Jorge L Sarmiento, April 2009: Decadal variability in North Atlantic phytoplankton blooms. Journal of Geophysical Research,
  114, C04013, doi:10.1029/2008JC005139. 
  

  The interannual to decadal variability in the timing and magnitude of the
  North Atlantic phytoplankton bloom is examined using a combination of satellite
  data and output from an ocean biogeochemistry general circulation model.
  The timing of the bloom as estimated from satellite chlorophyll data is
  used as a novel metric for validating the model’s skill. Maps of bloom timing
  reveal that the subtropical bloom begins in winter and progresses northward
  starting in May in subpolar regions. A transition zone, which experiences
  substantial interannual variability in bloom timing, separates the two regions.
  Time series of the modeled decadal (1959?2004) variability in bloom timing
  show no long-term trend toward earlier or delayed blooms in any of the three
  regions considered here. However, the timing of the subpolar bloom does
  show distinct decadal-scale periodicity, which is found to be correlated
  with the North Atlantic Oscillation (NAO) index. The mechanism underpinning
  the relationship is identified as anomalous wind-driven mixing conditions
  associated with the NAO. In positive NAO phases, stronger westerly winds
  result in deeper mixed layers, delaying the start of the subpolar spring
  bloom by 2?3 weeks. The subpolar region also expands during positive phases,
  pushing the transition zone further south in the central North Atlantic.
  The magnitude of the bloom is found to be only weakly dependent on bloom
  timing, but is more strongly correlated with mixed layer depth. The extensive
  interannual variability in the timing of the bloom, particularly in the
  transition region, is expected to strongly impact the availability of food
  to higher trophic levels.

• Christensen, V., C. J. Walters, R. Ahrens, J. Alder, J. Buszowski, L. B. Christensen, W. W. L. Cheung, John P Dunne, R. Froese, V. Karpouzi, K. Kaschner, K. Kearney, S. Lai, V. Lam, M. L. D. Palomares, A. Peters-Mason, C. Piroddi, Jorge L Sarmiento, J. Steenbeek, R. Sumaila, R. Watson, D. Zeller, and D. Pauly, 2009: Database-driven models of the world’s large marine ecosystems. Ecological Modelling, 220, 1984-1996.
  

  We present a new methodology for database-driven ecosystem model generation
  and apply the methodology to the world’s 66 currently defined Large Marine
  Ecosystems. The method relies on a large number of spatial and temporal
  databases, including FishBase, SeaLifeBase, as well as several other databases
  developed notably as part of the /Sea Around Us/ project. The models are
  formulated using the freely available Ecopath with Ecosim (EwE) modeling
  approach and software. We tune the models by fitting to available time series
  data, but recognize that the models represent only a first-generation of
  database-driven ecosystem models. We use the models to obtain a first estimate
  of fish biomass in the world’s LMEs. The biggest hurdles at present to further
  model development and validation are insufficient time series trend information,
  and data on spatial fishing effort.

• E. D. Galbraith, Anand Gnanadesikan, John P Dunne, and M. R. Hiscock, 2010: Regional impacts of iron-light colimitation in a global biogeochemical model. Biogeosciences, 7(3), 1043-1064. [ PDF ]
  

  Laboratory and field studies have revealed that iron has multiple roles
  in phytoplankton physiology, with particular importance for light-harvesting
  cellular machinery. However, although iron-limitation is explicitly included
  in numerous biogeochemical/ecosystem models, its implementation varies,
  and its effect on the efficiency of light harvesting is often ignored. Given
  the complexity of the ocean environment, it is difficult to predict the
  consequences of applying different iron limitation schemes. Here we explore
  the interaction of iron and nutrient cycles using a new, streamlined model
  of ocean biogeochemistry. Building on previously published parameterizations
  of photoadaptation and export production, the Biogeochemistry with Light
  Iron Nutrients and Gasses (BLING) model is constructed with only three explicit
  tracers but including macronutrient and micronutrient limitation, light
  limitation, and an implicit treatment of community structure. The structural
  simplicity of this computationally inexpensive model allows us to clearly
  isolate the global effects of iron availability on maximum light-saturated
  photosynthesis rates from those of photosynthetic efficiency. We find that
  the effect on light-saturated photosynthesis rates is dominant, negating
  the importance of photosynthetic efficiency in most regions, especially
  the cold waters of the Southern Ocean. The primary exceptions to this occur
  in iron-rich regions of the Northern Hemisphere, where high light-saturated
  photosynthesis rates cause photosynthetic efficiency to play a more important
  role. Additionally, we speculate that the small phytoplankton dominating
  iron-limited regions tend to have relatively high photosynthetic efficiency,
  such that iron-limitation has less of a deleterious effect on growth rates
  than would be expected from short-term iron addition experiments.

• Friedrichs, M. A. M., M. -E. Carr, Richard T. Barber, M. Scardi, D. Antione, R. A. Armstrong, I. Asanuma, M. J. Behrenfeld, E. T. Buitenhuis, F. Chai, J. R. Christian, A. M. Ciotti, S. C. Doney, M. Dowell, John P Dunne, B. Gentili, W. Gregg, N. Hoepffner, J. Ishizaka, T. Kameda, I. Lima, J. Marra, F. Mèlin, J. K. Moore, A. Morel, R. T. O’Malley, J. O’Reilly, V. S. Saba, M. Schmeltz, T. J. Smyth, J. Tjiputra, K. Waters, T. K. Westberry, and A. Winguth, 2009: Assessing the uncertainties of model estimates of primary productivity in the tropical Pacific Ocean. Journal of Marine Systems, 76(1-2), doi:10.1016/j.jmarsys.2008.05.010.
  

  Depth-integrated primary productivity (PP) estimates obtained from satellite
  ocean color-based models (SatPPMs) and those generated from biogeochemical
  ocean general circulation models (BOGCMs) represent a key resource for biogeochemical
  and ecological studies at global as well as regional scales. Calibration
  and validation of these PP models are not straightforward, however, and
  comparative studies show large differences between model estimates. The
  goal of this paper is to compare PP estimates obtained from 30 different
  models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting
  of not, vert, similar 1000 ^14 C measurements spanning more than a decade
  (1983?1996). Primary findings include: skill varied significantly between
  models, but performance was not a function of model complexity or type (i.e.
  SatPPM vs. BOGCM); nearly all models underestimated the observed variance
  of PP, specifically yielding too few low PP (< 0.2 g C m^- 2 d^- 1 ) values;
  more than half of the total root-mean-squared model?data differences associated
  with the satellite-based PP models might be accounted for by uncertainties
  in the input variables and/or the PP data; and the tropical Pacific database
  captures a broad scale shift from low biomass-normalized productivity in
  the 1980s to higher biomass-normalized productivity in the 1990s, which
  was not successfully captured by any of the models. This latter result suggests
  that interdecadal and global changes will be a significant challenge for
  both SatPPMs and BOGCMs. Finally, average root-mean-squared differences
  between in situ PP data on the equator at 140°W and PP estimates from the
  satellite-based productivity models were 58% lower than analogous values
  computed in a previous PP model comparison 6 years ago. The success of these
  types of comparison exercises is illustrated by the continual modification
  and improvement of the participating models and the resulting increase in
  model skill.

• Saba, V. S., M. A. M. Friedrichs, M. -E. Carr, D. Antoine, R. A. Armstrong, I. Asanuma, O. Aumont, N. R. Bates, M. J. Behrenfeld, V. Bennington, L. Bopp, J. Bruggeman, E. T. Buitenhuis, M. J. Church, A. M. Ciotti, S. C. Doney, M. Dowell, John P Dunne, S. Dutkiewicz, W. Gregg, N. Hoepffner, K. J. W. Hyde, J. Ishizaka, T. Kameda, D. M. Karl, I. Lima, M. W. Lomas, J. Marra, G. A. McKinley, F. Mèlin, J. K. Moore, A. Morel, J. O’Reilly, B. Salihoqlu, M. Scardi, T. J. Smyth, S. Tang, J. Tjiputra, J. Uitz, M. Vichi, K. Waters, and T. K. Westberry, A. Yool, 2010: Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT. Global Biogeochemical Cycles, 24, GB3020, doi:10.1029/2009GB003655. [ Abstract]
  

  The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models’ ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.

• Rodgers, K. B., R. M. Key, Anand Gnanadesikan, Jorge L Sarmiento, O Aumont, L. Bopp, S. C. Doney, John P Dunne, D. M. Glover, A. Ishida, M. Ishii, A. R. Jacobson, C. L. Monaco, E. Maier-Reimer, H. Mercier, N. Metzl, F. F. Pérez, A. F. Rios, R. Wanninkhof, P. Wetzel, C. D. Winn, and Y. Yamanaka, 2009: Using altimetry to help explain patchy changes in hydrographic carbon measurements. Journal of Geophysical Research, 114, C09013, doi:10.1029/2008JC005183.
  

  Here we use observations and ocean models to identify mechanisms driving
  large seasonal to interannual variations in dissolved inorganic carbon (DIC)
  and dissolved oxygen (O_2 ) in the upper ocean. We begin with observations
  linking variations in upper ocean DIC and O_2 inventories with changes in
  the physical state of the ocean. Models are subsequently used to address
  the extent to which the relationships derived from short-timescale (6 months
  to 2 years) repeat measurements are representative of variations over larger
  spatial and temporal scales. The main new result is that convergence and
  divergence (column stretching) attributed to baroclinic Rossby waves can
  make a first-order contribution to DIC and O_2 variability in the upper
  ocean. This results in a close correspondence between natural variations
  in DIC and O_2 column inventory variations and sea surface height (SSH)
  variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic
  part of the natural variability in the climate system and is elevated even
  in the absence of significant interannual variability in climate mode indices.
  The close correspondence between SSH and both DIC and O_2 column inventories
  for many regions suggests that SSH changes (inferred from satellite altimetry)
  may prove useful in reducing uncertainty in separating natural and anthropogenic
  DIC signals (using measurements from Climate Variability and Predictability’s
  CO_2 /Repeat Hydrography program).

• Findell, Kirsten L., Elena Shevliakova, P. C. D. Milly, and Ronald J. Stouffer, 2007: Modeled impact of anthropogenic land cover change on climate. Journal of Climate, 20(4), 3621-3634. [PDF]
  

  Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory?s
  climate model are used to investigate the impact of anthropogenic land cover
  change on climate. Regions of altered land cover include large portions
  of Europe, India, eastern China, and the eastern United States. Smaller
  areas of change are present in various tropical regions. This study focuses
  on the impacts of biophysical changes associated with the land cover change
  (albedo, root and stomatal properties, roughness length), which is almost
  exclusively a conversion from forest to grassland in the model; the effects
  of irrigation or other water management practices and the effects of atmospheric
  carbon dioxide changes associated with land cover conversion are not included
  in these experiments. The model suggests that observed land cover changes
  have little or no impact on globally averaged climatic variables (e.g.,
  2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover
  compared to a simulation with potential natural vegetation cover). Differences
  in the annual mean climatic fields analyzed did not exhibit global field
  significance. Within some of the regions of land cover change, however,
  there are relatively large changes of many surface climatic variables. These
  changes are highly significant locally in the annual mean and in most months
  of the year in eastern Europe and northern India. They can be explained
  mainly as direct and indirect consequences of model-prescribed increases
  in surface albedo, decreases in rooting depth, and changes of stomatal control
  that accompany deforestation.

• Dunne, John P.,Jorge L. Sarmiento, andAnand Gnanadesikan, 2007: A synthesis of global particle export from the surface ocean and cycling through the ocean interior and on the seafloor. Global Biogeochemical Cycles, 21, GB4006, doi:10.1029/2006GB002907.
  

  We present a new synthesis of the oceanic cycles of organic carbon, silicon,
  and calcium carbonate. Our calculations are based on a series of algorithms
  starting with satellite-based primary production and continuing with conversion
  of primary production to sinking particle flux, penetration of particle
  flux to the deep sea, and accumulation in sediments. Regional and global
  budgets from this synthesis highlight the potential importance of shelves
  and near-shelf regions for carbon burial. While a high degree of uncertainty
  remains, this analysis suggests that shelves, less than 50 m water depths
  accounting for 2% of the total ocean area, may account for 48% of the global
  flux of organic carbon to the seafloor. Our estimates of organic carbon
  and nitrogen flux are in generally good agreement with previous work while
  our estimates for CaCO_3 and SiO_2 fluxes are lower than recent work. Interannual
  variability in particle export fluxes is found to be relatively small compared
  to intra-annual variability over large domains with the single exception
  of the dominating role of El Niño-Southern Oscillation variability in the
  central tropical Pacific. Comparison with available sediment-based syntheses
  of benthic remineralization and burial support the recent theory of mineral
  protection of organic carbon flux through the deep ocean, pointing to lithogenic
  material as an important carrier phase of organic carbon to the deep seafloor.
  This work suggests that models which exclude the role of lithogenic material
  would underestimate the penetration of POC to the deep seafloor by approximately
  16?51% globally, and by a much larger fraction in areas with low productivity.
  Interestingly, atmospheric dust can only account for 31% of the total lithogenic
  flux and 42% of the lithogenically associated POC flux, implying that a
  majority of this material is riverine or directly erosional in origin.

• Gnanadesikan, Anand, and Ronald J. Stouffer, 2006: Diagnosing atmosphere-ocean general circulation model errors relevant to the terrestrial biosphere using the Köppen climate classification. Geophysical Research Letters, 33, L22701, doi:10.1029/2006GL028098. [PDF]
  

  Coupled atmosphere-ocean-land-sea ice climate models (AOGCMs) are often
  tuned using physical variables like temperature and precipitation with the
  goal of minimizing properties such as the root-mean-square error. As the
  community moves towards modeling the earth system, it is important to note
  that not all biases have equivalent impacts on biology. Bioclimatic classification
  systems provide means of filtering model errors so as to bring out those
  impacts that may be particularly important for the terrestrial biosphere.
  We examine one such diagnostic, the classic system of Köppen, and show that
  it can provide an ?early warning? of which model biases are likely to produce
  serious biases in the land biosphere. Moreover, it provides a rough evaluation
  criterion for the performance of dynamic vegetation models. State-of-the
  art AOGCMs fail to capture the correct Köppen zone in about 20?30% of the
  land area excluding Antarctica, and misassign a similar fraction to the
  wrong subzone.

• G.C. Hurtt, S. Frolking, M.G. Fearon, B. Moore III, Elena Shevliakova, Sergey Malyshev, S.W. Pacala, and R.A. Houghton, 2006: The underpinnings of land-use history: Three centuries of global gridded land-use transitions, wood harvest activity, and resulting secondary landscapes. Global Change Biology, 12(7), doi:10.1111/j.1365-2486.2006.01150.x.
• Westley, Marian B.., H. Yamagishi, B. N. Popp, and N. Yoshida, 2006: Nitrous oxide cycling in the Black Sea inferred from stable isoptope and isotopomer distributions. Deep-Sea Research II, 53(17-19), doi:10.1016/j.dsr2.2006.03.012.
  

  To accurately assess the impacts of human land use on the Earth system,
  information is needed on the current and historical patterns of land-use
  activities. Previous global studies have focused on developing reconstructions
  of the spatial patterns of agriculture. Here, we provide the first global
  gridded estimates of the underlying land conversions (land-use transitions),
  wood harvesting, and resulting secondary lands annually, for the period
  1700?2000. Using data-based historical cases, our results suggest that 42?68%
  of the land surface was impacted by land-use activities (crop, pasture,
  wood harvest) during this period, some multiple times. Secondary land area
  increased 10?44 × 106 km2 ; about half of this was forested. Wood harvest
  and shifting cultivation generated 70?90% of the secondary land by 2000;
  permanent abandonment and relocation of agricultural land accounted for
  the rest. This study provides important new estimates of globally gridded
  land-use activities for studies attempting to assess the consequences of
  anthropogenic changes to the Earth’s surface over time.