Simple measures of climate, soil properties and plant traits predict national scale grassland soil carbon stocks

1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Uniqueness of signature for simple curves

We propose a topological approach to the problem of determining a curve from its iterated integrals. In particular, we prove that a family of terms in the signature series of a two dimensional closed curve with finite p-variation, 1≤p<2, are in fact moments of its winding number. This relation allows us to prove that the signature series of a class of simple non-smooth curves uniquely determine the curves. This implies that outside a Chordal SLEκ null set, where 0<κ≤4, the signature series of curves uniquely determine the curves. Our calculations also enable us to express the Fourier transform of the n-point functions of SLE curves in terms of the expected signature of SLE curves. Although the techniques used in this article are deterministic, the results provide a platform for studying SLE curves through the signatures of their sample paths.

Simple piecewise geodesic interpolation of simple and Jordan curves with applications

We explicitly construct simple, piecewise minimizing geodesic, arbitrarily fine interpolation of simple and Jordan curves on a Riemannian manifold. In particular, a finite sequence of partition points can be specified in advance to be included in our construction. Then we present two applications of our main results: the generalized Green’s theorem and the uniqueness of signature for planar Jordan curves with finite p -variation for 1⩽p<2.

Sea-breeze dynamics and convection initiation: the influence of convective parameterization in weather and climate model biases

There are some long-established biases in atmospheric models that originate from the representation of tropical convection. Previously, it has been difficult to separate cause and effect because errors are often the result of a number of interacting biases. Recently, researchers have gained the ability to run multiyear global climate model simulations with grid spacings small enough to switch the convective parameterization off, which permits the convection to develop explicitly. There are clear improvements to the initiation of convective storms and the diurnal cycle of rainfall in the convection-permitting simulations, which enables a new process-study approach to model bias identification. In this study, multiyear global atmosphere-only climate simulations with and without convective parameterization are undertaken with the Met Office Unified Model and are analyzed over the Maritime Continent region, where convergence from sea-breeze circulations is key for convection initiation. The analysis shows that, although the simulation with parameterized convection is able to reproduce the key rain-forming sea-breeze circulation, the parameterization is not able to respond realistically to the circulation. A feedback of errors also occurs: the convective parameterization causes rain to fall in the early morning, which cools and wets the boundary layer, reducing the land–sea temperature contrast and weakening the sea breeze. This is, however, an effect of the convective bias, rather than a cause of it. Improvements to how and when convection schemes trigger convection will improve both the timing and location of tropical rainfall and representation of sea-breeze circulations.

Evaluation of a polynya flux model by means of thermal infrared satellite estimates

We test the ability of a two-dimensional flux model to simulate polynya events with narrow open-water zones by comparing model results to ice-thickness and ice-production estimates derived from thermal infrared Moderate Resolution Imaging Spectroradiometer (MODIS) observations in conjunction with an atmospheric dataset. Given a polynya boundary and an atmospheric dataset, the model correctly reproduces the shape of an 11 day long event, using only a few simple conservation laws. Ice production is slightly overestimated by the model, owing to an underestimated ice thickness. We achieved best model results with the consolidation thickness parameterization developed by Biggs and others (2000). Observed regional discrepancies between model and satellite estimates might be a consequence of the missing representation of the dynamic of the thin-ice thickening (e.g. rafting). We conclude that this simplified polynya model is a valuable tool for studying polynya dynamics and estimating associated fluxes of single polynya events.

On the parameterization of turbulent surface fluxes over heterogeneous sea ice surfaces

Turbulent surface fluxes of momentum and sensible and latent heat as well as surface temperature, air temperature, air humidity, and wind speed were measured by the German Falcon research aircraft over the marginal ice zone (MIZ) of the northern Baltic Sea and the Fram Strait. Applying the bulk formulas and the stability functions to the measurements, the roughness lengths for momentum z0, sensible heat zT, and latent heat zq were calculated. As mean values over a wide range of sea ice conditions, we obtain z0 = 5 � 10�4 m, zT = 1 � 10�8 m, and zq = 1 � 10�7 m. These correspond to the following mean values (± standard deviations) of neutral transfer coefficients reduced to 10 m height, CDN10 = (1.9 ± 0.8) � 10�3, CHN10 = (0.9 ± 0.3) � 10�3, and CEN10 = (1.0 ± 0.2) � 10�3. An average ratio of z0/zT � 104 was observed over the range of 10�6 m < z0 < 10�2 m and differs from previously published results over compact sea ice (10�1 < z0/zT < 103). Other observational results over heterogeneous sea ice do not exist. However, our z0/zT ratio approximately agrees with observations over heterogeneous land surfaces. Flux parameterizations based on commonly used roughness lengths ratios (z0 = zT = zq) overestimate the surface heat fluxes compared to our measurements by more than 100%.

Sensitivity of resolved and parameterized surface drag to changes in resolution and parameterization

The relative contribution of resolved and parameterized surface drag towards balancing the atmospheric angular momentum flux convergence (AMFC), and their sensitivity to horizontal resolution and parameterization, are investigated in an atmospheric model. This sensitivity can be difficult to elucidate in free-running climate models, in which the AMFC varies with changing climatologies and, as a result, the relative contributions of surface terms balancing the AMFC also vary. While the sensitivity question has previously been addressed using short-range forecasts, we demonstrate that a nudging framework is an effective method for constraining the AMFC. The Met Office Unified Model is integrated at three horizontal resolutions ranging from 130 km (N96) to 25 km (N512) while relaxing the model’s wind and temperature fields towards the ERAinterim reanalysis within the altitude regions of maximum AMFC. This method is validated against short range forecasts and good agreement is found. These experiments are then used to assess the fidelity of the exchange between parameterized and resolved orographic torques with changes in horizontal resolution. Although the parameterized orographic torque reduces substantially with increasing horizontal resolution, there is little change in resolved orographic torque over 20N to 50N. The tendencies produced by the nudging routine indicate that the additional drag at lower horizontal resolution is excessive. When parameterized orographic blocking is removed at the coarsest of these resolutions, there is a lack of compensation, and even compensation of the opposite sense, by the boundary layer and resolved torques which is particularly pronounced over 20N to 50N. This study demonstrates that there is strong sensitivity in the behaviour of the resolved and parameterized surface drag over this region.

Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3)

The Plant–Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic scheme only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant–Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant–Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

The role of convective parameterization in the simulation of a cyclone over the South Atlantic

Numerical simulations are carried out to examine the role of the Kuo and Kain-Fritsch (KF) cumulus parameterization schemes and dry dynamics on a cyclone development, in a weak baroclinic atmosphere, over subtropical South Atlantic Ocean. The initial phase of the cyclone development is investigated with a coarse horizontal mesh (75 km) and when the cyclone reaches the mature stage two different horizontal resolutions are used (75 and 25 km). The best performance simulation for the cyclone initial phase occurs when the Kuo convective scheme is applied, and this may be attributed to a greater diabatic warming in the troposphere. On the other hand, the dry simulation is not capable of simulating the correct location and intensity of the cyclone in its initial phase. During the mature phase, a cyclone over deepening occurs in the Kuo scheme experiment associated with larger latent heat release in a deep vertical column. The presence of downdraft currents in the KF scheme, which acts to cool and dry the lower levels, is essential to stabilize the atmosphere and to reproduce the nearest observation cyclone deepening rate. The largest cyclone deepening is found in the Kuo scheme high resolution experiment. This suggests that the KF convective scheme is less sensitive to the horizontal grid resolution. It was also revealed that the diabatic processes are crucial to simulate the observed features of this marine cyclone over subtropical region.

Seasonal drought stress in the Amazon: Reconciling models and observations

The Amazon Basin is crucial to global circulatory and carbon patterns due to the large areal extent and large flux magnitude. Biogeophysical models have had difficulty reproducing the annual cycle of net ecosystem exchange (NEE) of carbon in some regions of the Amazon, generally simulating uptake during the wet season and efflux during seasonal drought. In reality, the opposite occurs. Observational and modeling studies have identified several mechanisms that explain the observed annual cycle, including: (1) deep soil columns that can store large water amount, (2) the ability of deep roots to access moisture at depth when near-surface soil dries during annual drought, (3) movement of water in the soil via hydraulic redistribution, allowing for more efficient uptake of water during the wet season, and moistening of near-surface soil during the annual drought, and (4) photosynthetic response to elevated light levels as cloudiness decreases during the dry season. We incorporate these mechanisms into the third version of the Simple Biosphere model (SiB3) both singly and collectively, and confront the results with observations. For the forest to maintain function through seasonal drought, there must be sufficient water storage in the soil to sustain transpiration through the dry season in addition to the ability of the roots to access the stored water. We find that individually, none of these mechanisms by themselves produces a simulation of the annual cycle of NEE that matches the observed. When these mechanisms are combined into the model, NEE follows the general trend of the observations, showing efflux during the wet season and uptake during seasonal drought.

Effects of intensity and positional predictability of a visual stimulus on simple reaction time

The influence of visual stimuli intensity on manual reaction time (RT) was investigated under two different attentional settings: high (Experiment 1) and low (Experiment 2) stimulus location predictability. These two experiments were also run under both binocular and monocular viewing conditions. We observed that RT decreased as stimulus intensity increased. It also decreased as the viewing condition was changed from monocular to binocular as well as the location predictability shifted from low to high. A significant interaction was found between stimulus intensity and viewing condition, but no interaction was observed between neither of these factors and location predictability. These findings support the idea that the stimulus intensity effect arises from purely sensory, pre-attentive mechanisms rather than deriving from more efficient attentional capture. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

M-deformations of A-simple germs from R(n) to R(n+1)

All A-simple corank-1 germs from R(n) to R(n+1), where n not equal 4, have an M-deformation, that is a deformation in which the maximal numbers of isolated stable singular points are simultaneously present in the image.