A5021679464- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Particle physics theoretical and experimental studies
- Climate change impacts on agriculture
- Dark Matter and Cosmic Phenomena
- Crop Yield and Soil Fertility
- Atmospheric and Environmental Gas Dynamics
- Plant responses to elevated CO2
- Fire effects on ecosystems
- Rice Cultivation and Yield Improvement
- Particle Detector Development and Performance
- Computational Physics and Python Applications
- Greenhouse Technology and Climate Control
- Quantum Chromodynamics and Particle Interactions
- High-Energy Particle Collisions Research
- Hydrology and Watershed Management Studies
- Cryospheric studies and observations
- Climate change and permafrost
- Distributed and Parallel Computing Systems
- Meteorological Phenomena and Simulations
- Agricultural risk and resilience
- Cosmology and Gravitation Theories
- Ecology and Vegetation Dynamics Studies
- Atmospheric chemistry and aerosols
- Black Holes and Theoretical Physics
University of Exeter
2018-2024
Met Office
2015-2024
Thompson Rivers University
2024
Phillips Exeter Academy
2023
University of Bonn
2010-2014
University of Freiburg
2010-2011
Instituto de Física de Cantabria
2010-2011
Durham University
2006-2010
We describe the new developments in version 4 of public computer code HiggsBounds. HiggsBounds is a tool to test models with arbitrary Higgs sectors, containing both neutral and charged bosons, against published exclusion bounds from searches at LEP, Tevatron LHC experiments. From model predictions for masses, branching ratios, production cross sections total decay widths—which are specified by user input program—the calculates predicted signal rates search channels considered experimental...
Land surface models (LSMs) typically use empirical functions to represent vegetation responses soil drought. These largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal climate. We developed an analytical optimization model based on hydraulics (SOX) predict Coupling SOX the Joint UK Environment Simulator (JULES) LSM, we conducted a global evaluation of against leaf- and ecosystem-level observations. simulates leaf conductance climate for...
We report on recent developments in the public computer code HiggsBounds, which confronts arbitrary Higgs sector predictions with 95% C.L. exclusion limits from searches at LEP, Tevatron and LHC experiments.We discuss detail performance of Standard Model (SM) likeness test as implemented latest version HiggsBounds-3.8.0, whose outcome decides whether a search for SM boson can be applied to model beyond SM.Furthermore, we give preview features upcoming HiggsBounds-4.0.0 new program...
Abstract Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect that uncertainty specific potential impacts is demanding, since it requires a systematic survey both and models. We provide comprehensive evaluation projected crop yields for maize, spring winter wheat, rice, soybean, using suite nine models up to 45 CMIP5 34 CMIP6 projections three different forcing scenarios. To make this task computationally tractable, we use...
Abstract. Dynamic global vegetation models (DGVMs) are used for studying historical and future changes to the terrestrial carbon cycle. JULES (the Joint UK Land Environment Simulator) represents land surface in Hadley Centre climate Earth System Model. Recently number of plant functional types (PFTs) was expanded from five nine better represent diversity ecosystems. Here we introduce a more mechanistic representation dynamics TRIFFID, dynamic component JULES, which allows any PFTs compete...
Changes in rainfall amounts and patterns have been observed are expected to continue the near future with potentially significant ecological societal consequences. Modelling vegetation responses changes is thus crucial project water carbon cycles future. In this study, we present results of a new model-data intercomparison project, where tested ability 10 terrestrial biosphere models reproduce sensitivity ecosystem productivity at sites across globe, nine which, exclusion and/or irrigation...
Abstract. Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing management conditions not sampled the historical record new locations cultivation may shift. However, process-based models differ many critical details, their responses different interacting factors remain only poorly...
Abstract. Global studies of climate change impacts that use future model projections also require land surface changes. Simulated performance in Earth system models is often affected by the atmospheric models' biases, leading to errors projections. Here we run Joint UK Land Environment Simulator System configuration (JULES-ES) with Inter-Sectoral Impact Model Intercomparison Project second-phase (ISIMIP2b) bias-corrected data from four global (GCMs). The bias correction reduces impact biases...
Abstract Crop models are often used to project future crop yield under climate and global change typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed response types using impact surfaces along four drivers yield: carbon dioxide (C), temperature (T), water (W), nitrogen (N). help simulated responses per driver their combinations rather than aggregated changes yields as the result simultaneous various drivers. We find that models' sensitivities...
Abstract. Studies of climate change impacts on the terrestrial biosphere have been completed without recognition integrated nature biosphere. Improved assessment food and water security requires development use models not only representing each component but also their interactions. To meet this requirement Joint UK Land Environment Simulator (JULES) land surface model has modified to include a generic parametrisation annual crops. The new model, JULES-crop, is described evaluation at global...
The Met Office Hadley Centre's PRECIS regional climate modelling system has been used to generate a five member ensemble of projections for Africa over the 50 km resolution Coordinated Regional Downscaling Experiment-Africa domain. comprises downscaling subset perturbed physics global model (GCM) chosen exclude members unable represent African realistically and then capture spread in outcomes from remaining models. simulations were run December 1949 2100. (RCM) captures annual cycle...
Abstract. Drought is predicted to increase in the future due climate change, bringing with it myriad impacts on ecosystems. Plants respond drier soils by reducing stomatal conductance order conserve water and avoid hydraulic damage. Despite importance of plant drought responses for global carbon cycle local regional feedbacks, land surface models are unable capture observed soil moisture stress. We assessed impact stress simulated gross primary productivity (GPP) latent energy flux (LE)...
Abstract. Ozone (O3) pollution poses an escalating threat to rice production and food security in China, with concentrations projected rise under future climate scenarios. Accurately quantifying O3 impacts on is thus crucial for informed agricultural planning. This study the first utilise Free Air Concentration Enrichment (FACE) observations specific calibrating a crop model (JULES-crop) assessing of O3. FACE experiments, which involve growing crops natural field conditions while exposing...
Ozone (O3) threatens food security by reducing rice yields, a staple for half of the world’s population. While numerical research has shown negative impact O3 on through mathematical methods and crop models, existing global assessments have not incorporated data from rice-specific Free Air Concentration Enrichment (FACE) experiments into mechanical models that simulate interactions among phenology, physiology, O3. FACE are novel field with O3 distributed directly to crops...
Abstract. Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects future climate changes on yields. We describe here development emulators nine five crops using output from Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI 2 experiment is designed with explicit goal producing a structured training dataset emulator that samples across four dimensions relevant to yields: atmospheric carbon...
Abstract. Accurately representing the response of ecosystems to environmental change in land surface models (LSMs) is crucial making accurate predictions future climate. Many LSMs do not correctly capture plant respiration and growth fluxes, particularly extreme climatic events. This part due unrealistic assumption that total carbon expenditure (PCE) always equal gross accumulation by photosynthesis. We present evaluate a simple model labile storage utilisation (SUGAR) designed be integrated...
Abstract. The Land Variational Ensemble Data Assimilation Framework (LAVENDAR) implements the method of four-dimensional ensemble variational (4D-En-Var) data assimilation (DA) for land surface models. Four-dimensional negates often costly calculation a model adjoint required by traditional techniques (such as 4D-Var) optimizing parameters or state variables over time window observations. In this paper we present first application LAVENDAR, implementing framework with Joint UK Environment...
Abstract Soil moisture information is essential to monitoring of the intensity droughts, start rainy season, planting dates and early warnings yield losses. We assess spatial temporal trends drought over Brazilian semiarid region by combining soil observations from 360 stations, root zone a leading land surface model, vegetation health index remote sensing. The dataset was obtained network stations maintained National Center Monitoring Early Warning Natural Disasters (Cemaden), in Brazil....
Geoscientific models play a pivotal role in understanding global change impacts on the Earth system and are therefore highly relevant for decision-making. However, their complexity—including combination of pre-processing, modeling, post-processing workflows—poses significant challenges to reproducibility accessibility, even when adhering FAIR data principles.Here, we present insights from land surface modeling community, based survey 20 dynamic vegetation participating...