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N. Gedney and P. M. Cox

Abstract

Improving the treatment of subgrid-scale soil moisture variations is recognized as a priority for the next generation of land surface schemes. Here, the impact of an improved representation of subgrid-scale soil moisture heterogeneity on global climate model (GCM) simulations of current and future climates is carried out using Version three of the Hadley Centre Atmospheric Climate Model (HadAM3) coupled to the Met Office Surface Exchange Scheme (MOSES). MOSES was adapted to make use of the rainfall runoff model TOPMODEL algorithms, which relate the local water table depth to the grid box mean water table depth, assuming that subgrid-scale topography is the primary cause of soil moisture heterogeneity. This approach was also applied to produce a novel model for wetland area, which can ultimately be used to interactively model methane emissions from wetlands. The modified scheme was validated offline by forcing with near-surface Global Soil Wetness Project (GSWP) data, and online within the HadAM3 global climate model. In both cases it was found to improve the present-day simulation of runoff and produce realistic distributions of global wetland area. (Precipitation was also improved in the online simulation.) The new scheme results in substantial differences in the modeled sensitivity of runoff to climate change, with implications for the modeling of hydrological impacts.

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P. M. Kuhn and S. K. Cox

Abstract

By varying the amount of water vapor as input to the radiative power transfer equation, assuming a constant carbon dioxide and varying ozone distribution, it is possible to infer stratospheric water vapor from broadband observations of downward irradiance. The procedure is iterative in that downward observed and calculated irradiances, at several levels for each of several radiometric soundings, are brought within the limits of a convergence criterion. This is accomplished by successively reducing an initial over-estimate of the stratospheric mixing ratio, defined by a power law, until the sum of the squared differences of observed and calculated irradiances is minimized. The sum includes all levels of the sounding.

Results for a continental area during winter months indicate that the stratospheric water vapor content from 50 mb upward to 10 mb decreases from approximately 20 to 3 parts per million. For tropical Guam and Canton Island the corresponding magnitudes are larger, decreasing from 21 to 4 ppm. The standard deviation of the mean for all pressure levels is approximately 1.0 ppm. Adding deviation to the values inferred should give an upper bound to the water vapor content. The average mixing ratio for the continental stations between 25 and 10 mb is 5.7 ppm with a standard deviation of the mean of 0.8 ppm. Since the infrared radiative emission and attenuation of aerosols is inseparable from emission and attenuation of the atmospheric gases when measured with a broad response radiometer, these mixing ratio results would be reduced by the presence of aerosols. In view of apparent aerosol contamination we have made no inferences below 50 mb (21 km). The results may be said to be an upper bound to the actual quantity of water vapor, favoring an increasingly dry stratospheric profile.

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M. C. Gregg, C. S. Cox, and P. W. Hacker

Abstract

Temperature profiles were made, during a period of calm weather in early autumn, in the center of the subtropical gyre in the North Pacific with free-fall microstructure instruments as well as with commerical salinity-temperature-depth recorders. In the depth range of 0.2–2 km the data records show irregularly spaced regions of strong gradients separated by sections with weak gradients, but otherwise lack conspicuous features. The general impression is one of strong stratification and only very weak levels of turbulence. Spectra of the gradient records from the upper kilometer exhibit distinct changes in slope at about 10−2 cycle per meter (cpm) and at 10 cpm. These changes in slope are interpreted as the scales at which different types of features dominate the vertical temperature profile: the nearly exponential mean profile is the principal feature for K<10−2 cpm, while for 10−2<K<2 cpm the irregularly spaced structures in the stratification are the principal contributors to the spectra. Wavenumbers >10 cpm have been identified as the micro-structure range and are characterized by a gradient spectrum which rises with increasing wavenumber until diffusion cuts off the temperature fluctuations. The levels of vertical microstructure activity are much lower than found at similar depths in the California Current, and unlike nearshore waters, little horizontal microstructure is found for scales <10 cm. Estimates of the vertical temperature diffusion coefficient Kz from these records are much lower than those predicted by the diffusive thermocline models. However, the data are as yet too limited to regard this as a general conclusion for the central gyre region.

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R. L. H. Essery, M. J. Best, R. A. Betts, P. M. Cox, and C. M. Taylor

Abstract

A land surface scheme that may be run with or without a tiled representation of subgrid heterogeneity and includes an implicit atmospheric coupling scheme is described. Simulated average surface air temperatures and diurnal temperature ranges in a GCM using this surface model are compared with climatology. Surface tiling is not found to give a clear improvement in the simulated climate but offers more flexibility in the representation of heterogeneous land surface processes. Using the same meteorological forcing in offline simulations using versions of the surface model with and without tiling, the tiled model gives slightly lower winter temperatures at high latitudes and higher summer temperatures at midlatitudes. When the surface model is coupled to a GCM, reduced evaporation in the tiled version leads to changes in cloud cover and radiation at the surface that enhance these differences.

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A. Anav, P. Friedlingstein, M. Kidston, L. Bopp, P. Ciais, P. Cox, C. Jones, M. Jung, R. Myneni, and Z. Zhu

Abstract

The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.

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N. Gedney, P. M. Cox, H. Douville, J. Polcher, and P. J. Valdes

Abstract

The impact of land surface representation on GCM simulations of climate change is analyzed using eight climate change experiments, carried out with four GCMs each utilizing two different land surface schemes (LSSs). In the regions studied (Amazonia, the Sahel, and southern Europe) the simulations differ markedly in terms of their predicted changes in evapotranspiration and soil moisture. These differences are only partly as a result of differences in the predicted changes in precipitation and available energy. A simple “bucket model” characterization of each LSS demonstrates that the different hydrological sensitivities are also strongly dependent on properties of the LSS, most notably the runoff, which occurs when evaporation is marginally soil moisture limited. This parameter, “Y c,” varies significantly among the LSSs, and influences both the soil moisture in the 1 × CO2 control climate, and the sensitivity of both evaporation and soil moisture to climate change. It is concluded that uncertainty in the predicted changes in surface hydrology is more dependent on such gross features of the runoff versus soil moisture curve than on the detailed treatment of evapotranspiration.

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Christopher J. Cox, David D. Turner, Penny M. Rowe, Matthew D. Shupe, and Von P. Walden

Abstract

The radiative properties of clouds are related to cloud microphysical and optical properties, including water path, optical depth, particle size, and thermodynamic phase. Ground-based observations from remote sensors provide high-quality, long-term, continuous measurements that can be used to obtain these properties. In the Arctic, a more comprehensive understanding of cloud microphysics is important because of the sensitivity of the Arctic climate to changes in radiation. Eureka, Nunavut (80°N, 86°25′W, 10 m), Canada, is a research station located on Ellesmere Island. A large suite of ground-based remote sensors at Eureka provides the opportunity to make measurements of cloud microphysics using multiple instruments and methodologies. In this paper, cloud microphysical properties are presented using a retrieval method that utilizes infrared radiances obtained from an infrared spectrometer at Eureka between March 2006 and April 2009. These retrievals provide a characterization of the microphysics of ice and liquid in clouds with visible optical depths between 0.25 and 6, which are a class of clouds whose radiative properties depend greatly on their microphysical properties. The results are compared with other studies that use different methodologies at Eureka, providing context for multimethod perspectives. The authors’ findings are supportive of previous studies, including seasonal cycles in phase and liquid particle size, weak temperature–phase dependencies, and frequent occurrences of supercooled water. Differences in microphysics are found between mixed-phase and single-phase clouds for both ice and liquid. The Eureka results are compared with those obtained using a similar retrieval technique during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment.

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Matthew D. Shupe, David D. Turner, Von P. Walden, Ralf Bennartz, Maria P. Cadeddu, Benjamin B. Castellani, Christopher J. Cox, David R. Hudak, Mark S. Kulie, Nathaniel B. Miller, Ryan R. Neely III, William D. Neff, and Penny M. Rowe

Cloud and atmospheric properties strongly influence the mass and energy budgets of the Greenland Ice Sheet (GIS). To address critical gaps in the understanding of these systems, a new suite of cloud- and atmosphere-observing instruments has been installed on the central GIS as part of the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project. During the first 20 months in operation, this complementary suite of active and passive ground-based sensors and radiosondes has provided new and unique perspectives on important cloud–atmosphere properties.

High atop the GIS, the atmosphere is extremely dry and cold with strong near-surface static stability predominating throughout the year, particularly in winter. This low-level thermodynamic structure, coupled with frequent moisture inversions, conveys the importance of advection for local cloud and precipitation formation. Cloud liquid water is observed in all months of the year, even the particularly cold and dry winter, while annual cycle observations indicate that the largest atmospheric moisture amounts, cloud water contents, and snowfall occur in summer and under southwesterly flow. Many of the basic structural properties of clouds observed at Summit, Greenland, particularly for low-level stratiform clouds, are similar to their counterparts in other Arctic regions.

The ICECAPS observations and accompanying analyses will be used to improve the understanding of key cloud–atmosphere processes and the manner in which they interact with the GIS. Furthermore, they will facilitate model evaluation and development in this data-sparse but environmentally unique region.

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P. Friedlingstein, P. Cox, R. Betts, L. Bopp, W. von Bloh, V. Brovkin, P. Cadule, S. Doney, M. Eby, I. Fung, G. Bala, J. John, C. Jones, F. Joos, T. Kato, M. Kawamiya, W. Knorr, K. Lindsay, H. D. Matthews, T. Raddatz, P. Rayner, C. Reick, E. Roeckner, K.-G. Schnitzler, R. Schnur, K. Strassmann, A. J. Weaver, C. Yoshikawa, and N. Zeng

Abstract

Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C.

All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.

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T. J. Ansell, P. D. Jones, R. J. Allan, D. Lister, D. E. Parker, M. Brunet, A. Moberg, J. Jacobeit, P. Brohan, N. A. Rayner, E. Aguilar, H. Alexandersson, M. Barriendos, T. Brandsma, N. J. Cox, P. M. Della-Marta, A. Drebs, D. Founda, F. Gerstengarbe, K. Hickey, T. Jónsson, J. Luterbacher, Ø. Nordli, H. Oesterle, M. Petrakis, A. Philipp, M. J. Rodwell, O. Saladie, J. Sigro, V. Slonosky, L. Srnec, V. Swail, A. M. García-Suárez, H. Tuomenvirta, X. Wang, H. Wanner, P. Werner, D. Wheeler, and E. Xoplaki

Abstract

The development of a daily historical European–North Atlantic mean sea level pressure dataset (EMSLP) for 1850–2003 on a 5° latitude by longitude grid is described. This product was produced using 86 continental and island stations distributed over the region 25°–70°N, 70°W–50°E blended with marine data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The EMSLP fields for 1850–80 are based purely on the land station data and ship observations. From 1881, the blended land and marine fields are combined with already available daily Northern Hemisphere fields. Complete coverage is obtained by employing reduced space optimal interpolation. Squared correlations (r2) indicate that EMSLP generally captures 80%–90% of daily variability represented in an existing historical mean sea level pressure product and over 90% in modern 40-yr European Centre for Medium-Range Weather Forecasts Re-Analyses (ERA-40) over most of the region. A lack of sufficient observations over Greenland and the Middle East, however, has resulted in poorer reconstructions there. Error estimates, produced as part of the reconstruction technique, flag these as regions of low confidence. It is shown that the EMSLP daily fields and associated error estimates provide a unique opportunity to examine the circulation patterns associated with extreme events across the European–North Atlantic region, such as the 2003 heat wave, in the context of historical events.

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