Global Sea Ice Research Articles

High temporal resolution estimations of the Arctic sea ice albedo during the melting and refreezing periods of the years 2003-2011

Methods for estimating seasonal and long term trends of the Arctic sea ice albedo are of growing importance to cryosphere and climate studies. Remote sensing of the sea ice albedo has hitherto been carried out using optical satellite instruments. However, the measured data is often insufficient in late summer and fall because of clouds and low solar elevations. Therefore, new methods are a prerequisite for realistic estimations for the global sea ice albedo over the whole melting–refreezing period. Here, we show that a new microwave based sea ice albedo estimation method alleviates problems of optical instruments, offering new albedo data especially during the refreezing periods even on a daily basis. In this study we present detailed weekly and daily albedo progress over the whole Arctic sea ice area from June to September for the period of 2003–2011, estimated using the microwave method.

Multiscale modeling of coastal, shelf, and global ocean dynamics

In contemporary ocean science, modeling systems that inte-grate understanding of complex multiscale phenomena andutilize efficient numerics are paramount. Many of today'sfundamental ocean science questions involve multiple scalesand multiple dynamics. A new generation of modeling sys-tems would allow to study such questions quantitatively bybeing less restrictive dynamically and more efficient numeri-cally than more traditional systems.Suchmultiscaleoceanmodelingisthethemeofthistopicalcollection.Twolargeinternational workshopswereorganizedonthistheme,oneinCambridge,USA(IMUM2010),andonein Bremerhaven, Germany (IMUM2011). Contributions fromthe scientific community were encouraged on all aspects ofmultiscale ocean modeling from ocean science and dynamicsto the development of new computational methods and sys-tems. Building on previous meetings (e.g., Deleersnijder andLermusiaux 2008; Deleersnijder et al. 2010), the workshopdiscussionsandthefinalcontributionstothetopicalcollectionare summarized next.Thescientificapplicationdomainsdiscussedandpresentedranged from estuaries to the global ocean, including coastalregionsandshelfseas.Multi-resolutionmodelingofphysical,biological, chemical, and sea ice processes as well as air–seainteractions were described. The multiscale dynamics consid-ered involved hydrostatic, non-hydrostatic, turbulent, and seasurface processes.Computational results and discussions emphasized multi-resolution simulations using unstructured and structuredmeshes,aimingtowidentherange ofresolvedscalesinspaceand time. They included finite volume and finite elementspatial discretizations, high-order schemes, preconditioners,solver issues, grid generation, adaptive modeling, data assim-ilation,couplingwithatmosphericorbiogeochemicalmodels,and distributed computing. The advantages of using unstruc-tured meshes and related approaches in particular multi-gridembedding, nesting systems, wavelets, and other multiscaledecompositions were discussed. Techniques for the study ofmulti-resolution results, visualization, optimization, modelevaluations,anduncertaintyquantificationwerealsoexamined.1 Multiscale interdisciplinary dynamicsA number of manuscripts in the topical collection focus onmultiscale interdisciplinary dynamics, specifically oceanphysics and ice interactions, physical–biogeochemical inter-actions, and physical–sediment–coast interactions.

Southern Ocean warming and increased ice shelf basal melting in the twenty-first and twenty-second centuries based on coupled ice-ocean finite-element modelling

We utilise a global finite-element sea ice–ocean model (FESOM), focused on the Antarctic marginal seas, to analyse projections of ice shelf basal melting in a warmer climate. Ice shelf–ocean interaction is described using a three-equation system with a diagnostic computation of temperature and salinity at the ice–ocean interface. A tetrahedral mesh with a minimumhorizontal resolution of 4 km and hybrid vertical coordinates is used. Ice shelf draft, cavity geometry, and global ocean bathymetry have been derived from the RTopo-1 data set. The model is forced with the atmospheric output from two climate models: (1) the Hadley Centre Climate Model (HadCM3) and (2) Max Planck Institute’s ECHAM5/MPI-OM coupled climate model. Results from experiments forced with their twentieth century output are used to evaluate the modelled present-day ocean state. Sea ice coverage is largely realistic in both simulations; modelled ice shelf basal melt rates compare well with observations in both cases, but are consistently smaller for ECHAM5/MPI-OM. Projections for future ice shelf basal melting are computed using atmospheric output for the Intergovernmental Panel on Climate Change (IPCC) scenarios E1 and A1B. In simulations forced with ECHAM5 data, trends in ice shelf basal melting are small. In contrast, decreasing convection along the Antarctic coast in HadCM3 scenarios leads to a decreasing salinity on the continental shelf and to intrusions of warm deep water of open ocean origin. In the case of the Filchner–Ronne Ice Shelf (FRIS), this water reaches deep into the cavity, so that basal melting increases by a factor of 4 to 6 compared to the present value of about 90 Gt/year. By the middle of the twenty-second century, FRIS becomes the dominant contributor to total ice shelf basal mass loss in these simulations. Our results indicate that the surface freshwater fluxes on the continental shelves may be crucial for the future of especially the large cold water ice shelves in the Southern Ocean.

A model reconstruction of the Antarctic sea ice thickness and volume changes over 1980–2008 using data assimilation

Sea ice variability in the Southern Ocean has a complex spatio-temporal structure. In a global warming context, the Antarctic sea ice cover has slightly expanded over the recent decades. This increase in sea ice extent results, however, from the sum of positive and negative regional trends and is influenced by a wide range of modes of climate variability. An additional view on sea ice thickness and volume changes would improve our understanding. Still, no large-scale multi-decadal well-sampled record of Antarctic sea ice thickness exists to date. To address this issue, we assimilate real sea ice concentration data into the ocean–sea ice model NEMO-LIM2 using an ensemble Kalman filter and demonstrate the positive impacts on the global sea ice cover. This paper reports the 1980–2008 evolution (monthly anomalies, trends plus their uncertainty ranges) of sea ice volume and thickness in different sectors of the Southern Ocean. We find that the global Antarctic sea ice volume has risen at a pace of 355±338km3/decade (5.6±5.3%/decade) during this period, with an increase in the Ross and Weddell Seas (150±124 and 209±362km3/decade, respectively) and a decrease in the Amundsen–Bellingshausen Seas (-45±54km3/decade). Sea ice volume anomalies co-vary well with extent anomalies, and exhibit yearly to decadal fluctuations. The results stress the need to analyze sea ice changes at the regional level first and then at the hemispheric level.

The Initiation of Modern “Soft Snowball” and “Hard Snowball” Climates in CCSM3. Part I: The Influences of Solar Luminosity, CO2 Concentration, and the Sea Ice/Snow Albedo Parameterization

Abstract The “Snowball Earth” hypothesis, proposed to explain the Neoproterozoic glacial episodes in the period 750–580 million years ago, suggested that the earth was globally covered by ice/snow during these events. This study addresses the problem of the forcings required for the earth to enter such a state of complete glaciation using the Community Climate System Model, version 3 (CCSM3). All of the simulations performed to address this issue employ the geography and topography of the present-day earth and are employed to explore the combination of factors consisting of total solar luminosity, CO2 concentration, and sea ice/snow albedo parameterization that would be required for such an event to occur. The analyses demonstrate that the critical conditions beyond which runaway ice–albedo feedback will lead to global freezing include 1) a 10%–10.5% reduction in solar radiation with preindustrial greenhouse gas concentrations; 2) a 6% reduction in solar radiation with 17.5 ppmv CO2; or 3) 6% less solar radiation and 286 ppmv CO2 if sea ice albedo is equal to or greater than 0.60 with a snow albedo of 0.78, or if sea ice albedo is 0.58 with a snow albedo equal to or greater than 0.80. These bifurcation points are very sensitive to the sea ice and snow albedo parameterizations. Moreover, “soft Snowball” solutions are found in which tropical open water oceans stably coexist with year-round snow-covered low-latitude continents, implying that tropical continental ice sheets would actually be present. The authors conclude that a “soft Snowball” is entirely plausible, in which the global sea ice fraction may reach as high as 76% and sea ice margins may extend to 10°S(N) latitudes.

Daily, Global, High-Resolution SST and Sea Ice Reanalysis for 1985–2007 Using the OSTIA System

Abstract A sea surface temperature (SST) and sea ice reanalysis has been produced at the Met Office based on the Operational SST and Sea Ice Analysis (OSTIA) system. The OSTIA reanalysis produces daily, high-resolution, global foundation SST and sea ice concentration fields from 1 January 1985 to 31 December 2007. The SST reanalysis uses reprocessed satellite and in situ observations that are assimilated using a multiscale optimal-interpolation-type scheme similar to that used in the near-real-time OSTIA system. Validation of the SST analysis using assimilated in situ observation-minus-background statistics shows that the accuracy of the analysis increases throughout the reanalysis period; the global root-mean-square difference is approximately 0.50 K by 2007. This approach to validation is supported in the recent period by results from comparisons with independent near-surface Argo data against which a global standard deviation error of 0.55 K was calculated. Assessment of the OSTIA reanalysis at high latitudes demonstrates that the SST and sea ice fields are more consistent with one another in the Southern Hemisphere than in the Northern Hemisphere. Comparison of the sea ice extents to those in a similar reanalysis shows OSTIA to have larger extents in the Northern Hemisphere, and the Southern Hemisphere extents are similar. The OSTIA reanalysis SSTs are shown to be regionally comparable with similar reanalyses, with the largest differences occurring at high latitudes in the summer hemisphere. Differences are observed around the ice edge and in regions with high SST gradients. The OSTIA reanalysis provides a valuable high-resolution addition to the satellite period SST data record that makes use of the (Advanced) Along-Track Scanning Radiometer [(A)ATSR] multimission data.

Is the climate response to CO2 emissions path dependent?

Recent studies with coupled climate‐carbon cycle models suggest that global mean temperature change is proportional to cumulative CO2 emissions, independent of the timing of those emissions. This finding has prompted the suggestion that climate stabilization targets, such as the 2°C target adopted by the Copenhagen Accord, can be expressed in terms of cumulative CO2 emissions. Here we examine the simulated response of a range of global and regional climate variables to the same cumulative CO2 emissions (2500 PgC) released along different pathways using a complex Earth system model. We find that the response of most surface climate variables is largely independent of the emissions pathway once emissions cease, with the exception of variables with response timescales of centuries, such as ocean heat content and thermosteric sea level rise. Peak responses of many climate variables, such as global mean temperature, precipitation and sea ice, are also largely independent of the emissions pathway, except for scenarios with cumulative emissions overshoot which require net removal of CO2 from the atmosphere. By contrast, peak responses of atmospheric CO2 and surface ocean pH are found to be dependent on the emissions pathway. We conclude that a CO2mitigation framework based on cumulative emissions is well suited for limiting changes in many impact‐relevant climate variables, but is less effective in avoiding impacts directly associated with atmospheric CO2, whose peak response is dependent on the rate of emissions.

Tuning the climate of a global model

During a development stage global climate models have their properties adjusted or tuned in various ways to best match the known state of the Earth's climate system. These desired properties are observables, such as the radiation balance at the top of the atmosphere, the global mean temperature, sea ice, clouds and wind fields. The tuning is typically performed by adjusting uncertain, or even non‐observable, parameters related to processes not explicitly represented at the model grid resolution. The practice of climate model tuning has seen an increasing level of attention because key model properties, such as climate sensitivity, have been shown to depend on frequently used tuning parameters. Here we provide insights into how climate model tuning is practically done in the case of closing the radiation balance and adjusting the global mean temperature for the Max Planck Institute Earth System Model (MPI‐ESM). We demonstrate that considerable ambiguity exists in the choice of parameters, and present and compare three alternatively tuned, yet plausible configurations of the climate model. The impacts of parameter tuning on climate sensitivity was less than anticipated.

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap is undertaken preparatory to extending the 1979-2007 National Aeronautics and Space Administration (NASA) Goddard Space Flight Center NASA Team algorithm time series of global sea ice extents and areas. The 1979-2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in northern hemisphere (NH) sea ice extents is - 0.0156%, with a standard deviation (SD) of the differences of 0.6204%, and the yearly mean difference in NH sea ice areas is 0.5433%, with an SD of 0.3519%. For the southern hemisphere, the yearly mean difference in sea ice extents is 0.0304% ±0.4880%, and the mean difference in sea ice areas is 0.1550% ±0.3753%. This F13/F17 intercalibration enables the extension of the 29-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available.

Pan‐Arctic simulation of coupled nutrient‐sulfur cycling due to sea ice biology: Preliminary results

A dynamic model is constructed for interactive silicon, nitrogen, sulfur processing in and below Arctic sea ice, by ecosystems residing in the lower few centimeters of the distributed pack. A biogeochemically active bottom layer supporting sources/sinks for the pennate diatoms is appended to thickness categories of a global sea ice code. Nutrients transfer from the ocean mixed layer to drive algal growth, while sulfur metabolites are reinjected from the ice interface. Freeze, flux, flush and melt processes are linked to multielement geocycling for the entire high‐latitude regime. Major element kinetics are optimized initially to reproduce chlorophyll observations, which extend across the seasons. Principal influences on biomass are solute exchange velocity at the solid interface, optical averaging in active ice and cell retention against ablation. The sulfur mechanism encompasses open water features such as accumulation of particulate dimethyl sulfoniopropionate, grazing and other disruptive releases, plus bacterial/enzymatic conversion to volatile dimethyl sulfide. For baseline settings, the mixed layer trace gas distribution matches sparging measurements where they are available. However, concentrations rise to well over 10 nM in remote, unsampled locations. Peak contributions are supported by ice grazing, mortality and fractional melting. The model bottom layer adds substantially to a ring maximum of reduced sulfur chemistry that may be dominant across the marginal Arctic environment. Sensitivity tests on this scenario include variation of cell sulfur composition and remineralization, routings/chemical time scales, and the physical dimension of water layers. An alternate possibility that peripheral additions are small cannot be excluded from the outcomes. It is concluded that seagoing dimethyl sulfide data are far too sparse at the present time to distinguish sulfur‐ice production levels.

Sea ice properties in the Bohai Sea measured by MODIS-Aqua: 1. Satellite algorithm development

Based on the fact that sea ice reflectance drops significantly in the shortwave infrared (SWIR) wavelengths, black pixel assumption is assessed for three SWIR bands for the Moderate Resolution Imaging Spectroradiometer (MODIS)–at 1240, 1640, and 2130nm—over the sea ice in the Bohai Sea in order to carry out atmospheric correction for deriving sea ice reflectance spectra. For the SWIR 1240nm band, there is usually a small (but non-negligible) reflectance contribution over sea ice. Although there is a slight sea ice reflectance contribution at the MODIS 1640nm band over sporadic land-fast or hummock ice, the black pixel assumption is generally valid with the MODIS bands 1640 and 2130nm in the Bohai Sea. Thus, the SWIR-based atmospheric correction algorithm using MODIS bands at 1640 and 2130nm can be conducted to derive sea ice optical properties in the region. Based on spectral features of the sea ice reflectance, a regionally optimized ice-detection algorithm is proposed. This regional algorithm shows considerable improvements in detecting sea ice over the Bohai Sea region, compared with a previous MODIS global sea ice detection algorithm. The sea ice coverage as identified in the new algorithm matches very well with the sea ice coverage from both the MODIS true color image and the imagery from the Interactive Multisensor Snow and Ice Mapping System (IMS).

North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE): Statistical Modeling and Sensitivity to Sea Surface Temperature Changes

Abstract This study focuses on the statistical modeling of the power dissipation index (PDI) and accumulated cyclone energy (ACE) for the North Atlantic basin over the period 1949–2008, which are metrics routinely used to assess tropical storm activity, and their sensitivity to sea surface temperature (SST) changes. To describe the variability exhibited by the data, four different statistical distributions are considered (gamma, Gumbel, lognormal, and Weibull), and tropical Atlantic and tropical mean SSTs are used as predictors. Model selection, both in terms of significant covariates and their functional relation to the parameters of the statistical distribution, is performed using two penalty criteria. Two different SST datasets are considered [the Met Office’s Global Sea Ice and Sea Surface Temperature dataset (HadISSTv1) and NOAA’s extended reconstructed SST dataset (ERSSTv3b)] to examine the sensitivity of the results to the input data. The statistical models presented in this study are able to well describe the variability in the observations according to several goodness-of-fit diagnostics. Both tropical Atlantic and tropical mean SSTs are significant predictors, independently of the SST input data, penalty criterion, and tropical storm activity metric. The application of these models to centennial reconstructions and seasonal forecasting is illustrated. The sensitivity of North Atlantic tropical cyclone frequency, duration, and intensity is examined for both uniform and nonuniform SST changes. Under uniform SST warming, these results indicate that there is a modest sensitivity of intensity, and a decrease in tropical storm and hurricane frequencies. On the other hand, increases in tropical Atlantic SST relative to the tropical mean SST suggest an increase in the intensity and frequency of North Atlantic tropical storms and hurricanes.

Analysis of Local Air–Sea Interaction in East Asia Using a Regional Air–Sea Coupled Model

Abstract A regional air–sea coupled climate model based on the third regional climate model (RegCM3) and the regional oceanic model [the Princeton Ocean Model (POM)] is used to analyze the local air–sea interaction over East Asia in this study. The results indicate that the simulated sea surface temperature (SST) of the coupled model RegCM3–POM is reasonably accurate, and that the spatial pattern and temporal variation are consistent with that of the Global Sea Ice and Sea Surface Temperature dataset (GISST). The correlation between the SST and the atmospheric variables shows that the uncoupled model RegCM3 forced by the given SST cannot reproduce the real-time and SST lag correlation between SST and precipitation, and between SST and surface wind speed, whereas the relationship in the coupled model RegCM3–POM is reasonably accurate. RegCM3–POM reflects the air–sea interaction in the South China Sea and western Pacific Ocean, where the SST lead correlation is the inverse of the SST lag correlation between SST and precipitation, and strong winds bring warm water to the midlatitudes, so the correlation between wind speed and SST is negative in low latitudes and positive in the Kuroshio area. The uncoupled model fails to reproduce the effect of the atmosphere on the ocean. The further study on air–sea interaction in the South China Sea indicates that the earlier warm seawater corresponds to strong sensible heat flux, evaporation, precipitation, and weak net solar radiation, and the early strong sensible heat flux, evaporation, wind at the 10-m level, and weak net solar radiation cause the cold SST.

Greenland Sea sea ice variability over 1979–2007 and its link to the surface atmosphere

Mean winter Arctic sea ice concentration based on passive microwave observations for the period 1979-2007 are analyzed to examine the variability of the western Nordic Seas marginal ice zone (MIZ). A principal component analysis performed on this regional domain shows that the interannual variability is dominated by a mode which captures more than 70% of the total variance and shows only moderate correlation with the leading mode of global Northern Hemisphere sea ice variability. This mode appears to be related to a pattern of sea level pressure (SLP) anomaly centered on the MIZ with large scale signature resembling the canonical pattern of the North Atlantic Oscillation (NAO). Still this leading mode of SIC variability shows a weak temporal correlation with the NAO index. Taking into account the intrinsic spatial asymmetry found between the two phases of the NAO based on a weather regimes analysis, composite SIC fields are constructed which indeed suggest a preferential response of the Greenland Sea SIC variability to negative NAO-like patterns of SLP. The SLP pattern is consistent with a response of the sea ice margin to the strength of the northerly winds along eastern Greenland. A weak pattern of surface air temperature anomalies also emerges in the central Greenland Sea which occurs, at least partly, as a response of the surface atmosphere to sea ice concentrations changes. Higher order modes of winter SIC variability emerge based on a shorter winter season. One mode has much resemblance with the Odden/Nordbukta pattern while another one exhibits a significant signature in the center of the Greenland Sea convective gyre. The Odden/Nordbukta mode shows a more symmetric relation to the NAO than the leading SIC mode. Linear regression analysis consistently suggests some link between this mode and the ice area flux through Fram Strait.

Large‐scale modeling of primary production and ice algal biomass within arctic sea ice in 1992

An ice ecosystem model was coupled to a global dynamic sea ice model to assess large‐scale variability of primary production and ice algal biomass within arctic sea ice. The component models are the Physical Ecosystem Model (PhEcoM) ice ecosystem model and the Los Alamos Sea Ice Model (CICE). Simulated annual arctic sea ice primary production was 15.1 Tg C; within the range of 9 to 73 Tg C estimated using in situ data. The amount of C fixed was >3 Tg C month−1 for March, April, and May. The Bering Sea, Arctic Ocean basins, and the Canadian Archipelago/Baffin Bay were the most productive regions on an annual basis, contributing approximately 24, 18, and another 18%, respectively. High production in the Bering Sea was due to high daily production rates, while the large sea ice coverage in the Canadian Archipelago/Baffin Bay and, in particular, the Arctic Ocean basins resulted in their considerable contribution to sea ice primary production. The simulated trends, patterns, and seasonality of ice algae agree reasonably well with very limited observations. In the model, ice growth rate controls the availability of nutrients to sea ice algae, such that ocean nutrient supply is of secondary importance to ice algal growth. The numerical model results suggest that ice melt rate, which determines the proportional rate of ice algal release, controls the termination of the bloom on large scales. The model described advances the role of sea ice algae in biogeochemical cycling within global climate models.

A relationship between the aerodynamic and physical roughness of winter sea ice

AbstractA bulk flux algorithm predicts the turbulent surface fluxes of momentum and sensible and latent heat from mean measured or modelled meteorological variables. The bulk flux algorithm resulting from data collected over winter sea ice during SHEBA, the experiment to study the Surface Heat Budget of the Arctic Ocean, failed, however, in its first trial to predict the turbulent momentum flux over sea ice in the Antarctic. This result suggests that the main parameter for predicting the momentum flux, the aerodynamics roughness length z0, does not respond just to the friction velocity, as in the SHEBA algorithm, but is closely related to the physical roughness of snow‐covered sea ice and may need to be site‐specific. I investigate this idea with simultaneous measurements of z0 and the physical roughness of the surface, ξ, at Ice Station Weddell. The metric ξ derives from surveys of surface elevation and is related to but always less than the standard deviation in surface elevation. On combining the z0–ξ pairs from Ice Station Weddell with similar data obtained over Arctic sea ice, I show that the Arctic and Antarctic z0–ξ data lie along a continuum such that measuring ξ could provide a means for estimating a site‐specific z0 for any global sea ice surface. Backscatter data from satellite‐borne synthetic aperture radar might provide a remotely sensed estimate of ξ. Copyright © 2011 Royal Meteorological Society

Sea surface temperature cooling mode in the Pacific cold tongue

Long‐term variability in sea surface temperature (SST) in the equatorial Pacific and its relationship with global warming were investigated using three SST data sets (Hadley Center Global Sea Ice and Sea Surface Temperature, extended reconstruction sea surface temperature, and Kaplan), atmospheric fields from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis, and subsurface sea temperature from the Simple Ocean Data Assimilation data set. A cooling mode in the equatorial Pacific cold tongue is evident in all three SST data sets for two periods: 1870–2007 and 1948–2007. This cooling, which is indicated by the second empirical orthogonal function mode, is characterized by cooling in the Pacific cold tongue and warming elsewhere in the tropical Pacific. Its principal component time series is highly correlated with global mean surface temperature combining air temperature and SST. In association with the SST cooling mode, atmospheric fields and subsurface sea temperature are coupled in the tropical Pacific during recent decades. Moreover, for the coupled models in the 20th century run (20C3M), obtained from the Intergovernmental Panel on Climate Change Fourth Assessment Report database, those with realistic features of El Niño‐Southern Oscillation (ENSO) events can well show the cooling mode. However, the cooling mode is not shown in these coupled models in a preindustrial scenario with no forcing attributed to global warming. Results from observations and models suggest that the cooling mode is very likely caused by global warming. This conclusion is supported by a hypothesis that considers dynamic effects in the equatorial Pacific Ocean in response to global warming.

The NCEP Climate Forecast System Reanalysis

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system. CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research. Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.

Physical Climate Response to a Reduction of Anthropogenic Climate Forcing

Abstract Recent research indicates that the warming of the climate system resulting from increased greenhouse gas (GHG) emissions over the next century will persist for many centuries after the cessation of these emissions, principally because of the persistence of elevated atmospheric carbon dioxide (CO2) concentrations and their attendant radiative forcing. However, it is unknown whether the responses of other components of the climate system—including those related to Greenland and Antarctic ice cover, the Atlantic thermohaline circulation, the West African monsoon, and ecosystem and human welfare—would be reversed even if atmospheric CO2 concentrations were to recover to 1990 levels. Here, using a simple set of experiments employing a current-generation numerical climate model, the authors examine the response of the physical climate system to decreasing CO2 concentrations following an initial increase. Results indicate that many characteristics of the climate system, including global temperatures, precipitation, soil moisture, and sea ice, recover as CO2 concentrations decrease. However, other components of the Earth system may still exhibit nonlinear hysteresis. In these experiments, for instance, increases in stratospheric water vapor, which initially result from increased CO2 concentrations, remain present even as CO2 concentrations recover. These results suggest that identification of additional threshold behaviors in response to human-induced global climate change should focus on subcomponents of the full Earth system, including cryosphere, biosphere, and chemistry.

Physical Climate Response to a Reduction of Anthropogenic Climate Forcing

Recent research indicates that the warming of the climate system resulting from increased greenhouse gas (GHG) emissions over the next century will persist for many centuries after the cessation of these emissions, principally because of the persistence of elevated atmospheric carbon dioxide (CO2) concentrations and their attendant radiative forcing. However, it is unknown whether the responses of other components of the climate system—including those related to Greenland and Antarctic ice cover, the Atlantic thermohaline circulation, the West African monsoon, and ecosystem and human welfare—would be reversed even if atmospheric CO2 concentrations were to recover to 1990 levels. Here, using a simple set of experiments employing a current-generation numerical climate model, the authors examine the response of the physical climate system to decreasing CO2 concentrations following an initial increase. Results indicate that many characteristics of the climate system, including global temperatures, precipitation, soil moisture, and sea ice, recover as CO2 concentrations decrease. However, other components of the Earth system may still exhibit nonlinear hysteresis. In these experiments, for instance, increases in stratospheric water vapor, which initially result from increased CO2 concentrations, remain present even as CO2 concentrations recover. These results suggest that identification of additional threshold behaviors in response to human-induced global climate change should focus on subcomponents of the full Earth system, including cryosphere, biosphere, and chemistry.