Pete Falloon

The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model’s physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year. Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This license does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510–758 ppm of CO2), vegetation carbon increases by 52–477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Enhancing the carbon sink in European agricultural soils: including trace gas fluxes in estimates of carbon mitigation potential.

The possibility that the carbon sink in agricultural soils can be enhanced has taken on great political significance since the Kyoto Protocol was finalised in December 1997. The Kyoto Protocol allows carbon emissions to be offset by demonstrable removal of carbon from the atmosphere. Thus, forestry activities (Article 3.3) and changes in the use of agricultural soils (Article 3.4) that are shown to reduce atmospheric CO2levels may be included in the Kyoto emission reduction targets. The European Union is committed to a reduction in CO2 emissions to 92% of baseline (1990) levels during the first commitment period (2008–2012). We have shown recently that there are a number of agricultural land-management changes that show some potential to increase the carbon sink in agricultural soils and others that allow alternative forms of carbon mitigation (i.e. through fossil fuel substitution), but the options differ greatly in their potential for carbon mitigation. The changes examined were, (a) switching all animal manure use to arable land, (b) applying all sewage sludge to arable land, (c) incorporating all surplus cereal straw, (d) conversion to no-till agriculture, (e) use of surplus arable land to de-intensify 1/3 of current intensive crop production (through use of 1/3 grass/arable rotations), (f) use of surplus arable land to allow natural woodland regeneration, and (g) use of surplus arable land for bioenergy crop production. In this paper, we attempt for the first time to assess other (non-CO2) effects of these land-management changes on (a) the emission of the other important agricultural greenhouse gases, methane and nitrous oxide, and (b) other aspects of the ecology of the agroecosystems. We find that the relative importance of trace gas fluxes varies enormously among the scenarios. In some such as the sewage sludge, woodland regeneration and bioenergy production scenarios, the inclusion of trace gases makes only a small (<10%) difference to the CO2-C mitigation potential. In other cases, for example the no-till, animal manure and agricultural de-intensification scenarios, trace gases have a large impact, sometimes halving or more than doubling the CO2-C mitigation potential. The scenarios showing the greatest increase when including trace gases are those in which manure management changes significantly. In the one scenario (no-till) where the carbon mitigation potential was reduced greatly, a small increase in methane oxidation was outweighed by a sharp increase in N2O emissions. When these land-management options are combined to examine the whole agricultural land area of Europe, most of the changes in mitigation potential are small, but depending upon assumptions for the animal manure scenario, the total mitigation potential either increases by about 20% or decreases by about 10%, shifting the mitigation potential of the scenario from just above the EUs 8% Kyoto emission reduction target (98.9 Tg C y−1) to just below it. Our results suggest that (a) trace gas fluxes may change the mitigation potential of a land management option significantly and should always be considered alongside CO2-C mitigation potentials and (b) agricultural management options show considerable potential for carbon mitigation even after accounting for trace gas fluxes.

First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble

Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global scale. As an indicator of flood hazard we looked at changes in the 30-y return level of 5-d average peak flows under representative concentration pathway RCP8.5 at the end of this century. Not everywhere does climate change result in an increase in flood hazard: decreases in the magnitude and frequency of the 30-y return level of river flow occur at roughly one-third (20–45%) of the global land grid points, particularly in areas where the hydrograph is dominated by the snowmelt flood peak in spring. In most model experiments, however, an increase in flooding frequency was found in more than half of the grid points. The current 30-y flood peak is projected to occur in more than 1 in 5 y across 5–30% of land grid points. The large-scale patterns of change are remarkably consistent among impact models and even the driving climate models, but at local scale and in individual river basins there can be disagreement even on the sign of change, indicating large modeling uncertainty which needs to be taken into account in local adaptation studies.

Modelling refractory soil organic matter

Most models for the turnover of soil organic matter (SOM) include a compartment that is either considered inert, or has a very slow turnover time (refractory SOM; RSOM). The RSOM content of soils varies markedly between sites, and knowledge of its size and variability are essential for determining whether soils behave as sources or sinks of atmospheric CO2. It has also been suggested that the accurate specification of RSOM pools is essential to modelling studies, and that uncertainty in estimates of the size of RSOM pool could be a major source of error in modelling soil organic C. In this paper, current SOM models are reviewed, and approaches to modelling RSOM and its significance are discussed. Simulations of SOM turnover for the Rothamsted Broadbalk winter wheat experiment using the Rothamsted C model and CENTURY are presented as examples.

Climate change impacts on global agriculture

Based on predicted changes in the magnitude and distribution of global precipitation, temperature and river flow under the IPCC SRES A1B and A2 scenarios, this study assesses the potential impacts of climate change and CO2 fertilization on global agriculture. The analysis uses the new version of the GTAP-W model, which distinguishes between rainfed and irrigated agriculture and implements water as an explicit factor of production for irrigated agriculture. Future climate change is likely to modify regional water endowments and soil moisture. As a consequence, the distribution of harvested land will change, modifying production and international trade patterns. The results suggest that a partial analysis of the main factors through which climate change will affect agricultural productivity provide a false appreciation of the nature of changes likely to occur. Our results show that global food production, welfare and GDP fall in the two time periods and SRES scenarios. Higher food prices are expected. No matter which SRES scenario is preferred, we find that the expected losses in welfare are significant. These losses are slightly larger under the SRES A2 scenario for the 2020s and under the SRES A1B scenario for the 2050s. The results show that national welfare is influenced both by regional climate change and climate-induced changes in competitiveness.

Regional projections of North Indian climate for adaptation studies

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes.

EuroSOMNET – a European database of long-term experiments on soil organic matter: the WWW metadatabase

Since 1997, the EuroSOMNET project, funded by the EU-ENRICH programme, has assembled a metadatabase, and separate experimental databases, of European long-term experiments that investigate changes in soil organic matter. In this paper, we describe the WWW-based metadatabase, which is a product of this project. The database holds detailed records of 110 long-term soil organic matter experiments, giving a wide geographical coverage of Europe, and includes experiments from the European part of the former Soviet Union, many of which have not been available previously. For speed of access, records are stored as hyper-text mark-up language (HTML) files. In this paper, we describe the metadatabase, the experiments for which records are held, the information stored about each experiment, and summarize the main characteristics of these experiments. Details from the metadatabase have already been used to examine regional trends in soil organic matter in Germany and eastern Europe, to construct and calibrate a regional statistical model of humus balance in Russia, to examine the effects of climatic conditions on soil organic matter dynamics, to estimate the potential for carbon sequestration in agricultural soils in Europe, and to test and improve soil organic matter models. The EuroSOMNET metadatabase provides information applicable to a wide range of agricultural and environmental questions and can be accessed freely via the EuroSOMNET home page at URL: http://www.iacr.bbsrc.ac.uk/aen/eusomnet/index.htm.

Validation of River Flows in HadGEM1 and HadCM3 with the TRIP River Flow Model

AbstractThe Total Runoff Integrating Pathways (TRIP) global river-routing scheme in the third climate configuration of the Met Office Unified Model (HadCM3) and the newer Hadley Centre Global Environmental Model version 1 (HadGEM1) general circulation models (GCMs) have been validated against long-term average measured river discharge data from 40 stations on 24 major river basins from the Global Runoff Data Centre (GRDC). TRIP was driven by runoff produced directly by the two GCMs in order to assess both the skill of river flows produced within GCMs in general and to test this as a method for validating large-scale hydrology in GCMs. TRIP predictions of long-term-averaged annual discharge were improved at 28 out of 40 gauging stations on 24 of the world’s major rivers in HadGEM1 compared to HadCM3, particularly for low- and high-latitude basins, with predictions ranging from “good” (within 20% of observed values) to “poor” (biases exceeding 50%). For most regions, the modeled annual average river flows t...

Ensembles and uncertainty in climate change impacts

The increasing use of multi-member climate model ensembles for making future climate impact assessments presents both opportunities for understanding uncertainties, and challenges for interpreting the results. We outline current approaches to assessing uncertainties in climate impacts, statistical methods for assessing uncertainties, issues regarding model integration and complexity, and ways in which uncertainty frameworks can be used to inform adaptation decisions, with case studies focused on agriculture. Finally, we highlight future research needs and provide recommendations for making further progress.