Effect of simulated rainfall during wheat seed development and maturation on subsequent seed longevity is reversible

Poor wheat seed quality in temperate regions is often ascribed to wet production environments. We investigated the possible effect of simulated rain during seed development and maturation on seed longevity in wheat (Triticum aestivum L.) cv. Tybalt grown in the field (2008, 2009) or a polythene tunnel house (2010). To mimic rain, the seed crops were wetted from above with the equivalent of 30mm (2008, 2009) or 25mm rainfall (2010) at different stages of seed development and maturation (17 to 58 DAA, days after 50% anthesis), samples harvested serially, and subsequent air-dry seed longevity estimated. No pre-harvest sprouting occurred. Seed longevity (p50, 50% survival period in experimental hermetic storage at 40°C with c. 15% moisture content) in field-grown controls increased during seed development and maturation attaining maxima at 37 (2008) or 44 DAA (2009); it declined thereafter. Immediate effects of simulated rain at 17-58 DAA in field studies (2008, 2009) on subsequent seed longevity were negative but small, e.g. a 1-4 d delay in seed quality improvement for treatments early in development but with no damage detected at final harvests. In rainfall-protected conditions (2010), simulated rain close to harvest maturity (55-56 DAA) reduced longevity immediately and substantially, with greater damage from two sequential days of wetting than one; again, later harvests provided evidence of recovery in subsequent longevity. In the absence of pre-harvest sprouting, the potentially deleterious effects of rainfall to wheat seed crops on subsequent seed longevity may be reversible in full or in part.

Recent observed and simulated changes in precipitation over Africa

Multiple observational data sets and atmosphere-only simulations from the Coupled Model Intercomparison Project Phase 5 are analyzed to characterize recent rainfall variability and trends over Africa focusing on 1983–2010. Data sets exhibiting spurious variability, linked in part to a reduction in rain gauge density, were identified. The remaining observations display coherent increases in annual Sahel rainfall (29 to 43 mm yr−1 per decade), decreases in March–May East African rainfall (−14 to −65 mm yr−1 per decade), and increases in annual Southern Africa rainfall (32 to 41 mm yr−1 per decade). However, Central Africa annual rainfall trends vary in sign (−10 to +39 mm yr−1 per decade). For Southern Africa, observed and sea surface temperature (SST)-forced model simulated rainfall variability are significantly correlated (r~0.5) and linked to SST patterns associated with recent strengthening of the Pacific Walker circulation.

Assessing the uncertainty associated with intermittent rainfall fields

[1] In many practical situations where spatial rainfall estimates are needed, rainfall occurs as a spatially intermittent phenomenon. An efficient geostatistical method for rainfall estimation in the case of intermittency has previously been published and comprises the estimation of two independent components: a binary random function for modeling the intermittency and a continuous random function that models the rainfall inside the rainy areas. The final rainfall estimates are obtained as the product of the estimates of these two random functions. However the published approach does not contain a method for estimation of uncertainties. The contribution of this paper is the presentation of the indicator maximum likelihood estimator from which the local conditional distribution of the rainfall value at any location may be derived using an ensemble approach. From the conditional distribution, representations of uncertainty such as the estimation variance and confidence intervals can be obtained. An approximation to the variance can be calculated more simply by assuming rainfall intensity is independent of location within the rainy area. The methodology has been validated using simulated and real rainfall data sets. The results of these case studies show good agreement between predicted uncertainties and measured errors obtained from the validation data.

Analysis of precipitation climatology simulated by high resolution coupled global models over the South America

The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.

Comparing tropical precipitation simulated by the Met Office NWP and climate models with satellite observations

Forecasts of precipitation and water vapor made by the Met Office global numerical weather prediction (NWP) model are evaluated using products from satellite observations by the Special Sensor Microwave Imager/Sounder (SSMIS) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) for June–September 2011, with a focus on tropical areas (308S–308N). Consistent with previous studies, the predicted diurnal cycle of precipitation peaks too early (by ;3 h) and the amplitude is too strong over both tropical ocean and land regions. Most of the wet and dry precipitation biases, particularly those over land, can be explained by the diurnal-cycle discrepancies. An overall wet bias over the equatorial Pacific and Indian Oceans and a dry bias over the western Pacific warmpool and India are linked with similar biases in the climate model, which shares common parameterizations with the NWP version. Whereas precipitation biases develop within hours in the NWP model, underestimates in water vapor (which are assimilated by the NWP model) evolve over the first few days of the forecast. The NWP simulations are able to capture observed daily-to-intraseasonal variability in water vapor and precipitation, including fluctuations associated with tropical cyclones.

The three-dimensional morphology of simulated and observed convective storms over southern England

A set of high-resolution radar observations of convective storms has been collected to evaluate such storms in the UK Met Office Unified Model during the DYMECS project (Dynamical and Microphysical Evolution of Convective Storms). The 3-GHz Chilbolton Advanced Meteorological Radar was set up with a scan-scheduling algorithm to automatically track convective storms identified in real-time from the operational rainfall radar network. More than 1,000 storm observations gathered over fifteen days in 2011 and 2012 are used to evaluate the model under various synoptic conditions supporting convection. In terms of the detailed three-dimensional morphology, storms in the 1500-m grid-length simulations are shown to produce horizontal structures a factor 1.5–2 wider compared to radar observations. A set of nested model runs at grid lengths down to 100m show that the models converge in terms of storm width, but the storm structures in the simulations with the smallest grid lengths are too narrow and too intense compared to the radar observations. The modelled storms were surrounded by a region of drizzle without ice reflectivities above 0 dBZ aloft, which was related to the dominance of ice crystals and was improved by allowing only aggregates as an ice particle habit. Simulations with graupel outperformed the standard configuration for heavy-rain profiles, but the storm structures were a factor 2 too wide and the convective cores 2 km too deep.

Simulated climate change impact on summer dissolved organic carbon release from peat and surface vegetation: implications for drinking water treatment

Uncertainty regarding changes in dissolved organic carbon (DOC) quantity and quality has created interest in managing peatlands for their ecosystem services such as drinking water provision. The evidence base for such interventions is, however, sometimes contradictory. We performed a laboratory climate manipulation using a factorial design on two dominant peatland vegetation types (Calluna vulgaris and Sphagnum Spp.) and a peat soil collected from a drinking water catchment in Exmoor National Park, UK. Temperature and rainfall were set to represent baseline and future conditions under the UKCP09 2080s high emissions scenario for July and August. DOC leachate then underwent standard water treatment of coagulation/flocculation before chlorination. C. vulgaris leached more DOC than Sphagnum Spp. (7.17 versus 3.00 mg g−1) with higher specific ultraviolet (SUVA) values and a greater sensitivity to climate, leaching more DOC under simulated future conditions. The peat soil leached less DOC (0.37 mg g−1) than the vegetation and was less sensitive to climate. Differences in coagulation removal efficiency between the DOC sources appears to be driven by relative solubilisation of protein-like DOC, observed through the fluorescence peak C/T. Post-coagulation only differences between vegetation types were detected for the regulated disinfection by-products (DBPs), suggesting climate change influence at this scale can be removed via coagulation. Our results suggest current biodiversity restoration programmes to encourage Sphagnum Spp. will result in lower DOC concentrations and SUVA values, particularly with warmer and drier summers.

Vertical structure and physical processes of the Madden-Julian oscillation: Linking hindcast fidelity to simulated diabatic heating and moistening

Many theories for the Madden-Julian oscillation (MJO) focus on diabatic processes, particularly the evolution of vertical heating and moistening. Poor MJO performance in weather and climate models is often blamed on biases in these processes and their interactions with the large-scale circulation. We introduce one of three components of a model-evaluation project, which aims to connect MJO fidelity in models to their representations of several physical processes, focusing on diabatic heating and moistening. This component consists of 20-day hindcasts, initialised daily during two MJO events in winter 2009-10. The 13 models exhibit a range of skill: several have accurate forecasts to 20 days' lead, while others perform similarly to statistical models (8-11 days). Models that maintain the observed MJO amplitude accurately predict propagation, but not vice versa. We find no link between hindcast fidelity and the precipitation-moisture relationship, in contrast to other recent studies. There is also no relationship between models' performance and the evolution of their diabatic-heating profiles with rain rate. A more robust association emerges between models' fidelity and net moistening: the highest-skill models show a clear transition from low-level moistening for light rainfall to mid-level moistening at moderate rainfall and upper-level moistening for heavy rainfall. The mid-level moistening, arising from both dynamics and physics, may be most important. Accurately representing many processes may be necessary, but not sufficient for capturing the MJO, which suggests that models fail to predict the MJO for a broad range of reasons and limits the possibility of finding a panacea.

An evaluation of the simulated water balance of Eurasia and northern Africa at 6000 yr B.P. using lake status data

Changes in the water balance of Eurasia and northern Africa in response to insolation forcing at 6000 y BP simulated by five atmospheric general circulation models have been compared with observations of changes in lake status. All of the simulations show enhancement of the Asian summer monsoon and of the high pressure cells over the Pacific and Central Asia and the Middle East, causing wetter conditions in northern India and southern China and drier conditions along the Chinese coast and west of the monsoon core. All of the models show enhancement of the African monsoon, causing wetter conditions in the zone between ca 10–20 °N. Four of the models show conditions wetter than present in southern Europe and drier than present in northern Europe. Three of the models show conditions similar to present in the mid-latitude continental interior, while the remaining models show conditions somewhat drier than present. The extent and location of each of the simulated changes varies between the models, as does the mechanism producing these changes. The lake data confirm some features of the simulations, but indicate discrepancies between observed and simulated climates. For example, the data show: (1) conditions wetter than present in central Asia, from India to northern China and Mongolia, indicating that the simulated Asian monsoon expansion is too small; (2) conditions wetter than present between ca. 10–30 °N in Africa, indicating that the simulated African monsoon expansion is too small; (3) that northern Europe was drier, but the area of significantly drier conditions was more localized (around the Baltic) than shown in the simulations; (4) that southern Europe was wetter than present, apparently consistent with the simulations, but pollen data suggest that this reflects an increase in summer rainfall whereas the models show winter precipitation, and (5) that the mid-latitude continental interior was generally wetter than present.

Dominant role of greenhouse-gas forcing in the recovery of Sahel rainfall

Sahelian summer rainfall, controlled by the West African monsoon, exhibited large-amplitude multidecadal variability during the twentieth century. Particularly important was the severe drought of the 1970s and 1980s, which had widespread impacts1–6. Research into the causes of this drought has identified anthropogenic aerosol forcing3,4,7 and changes in sea surface temperatures (SSTs; refs 1,2,6,8–11) as the most important drivers. Since the 1980s, there has been some recovery of Sahel rainfall amounts2–6,11–14, although not to the pre-drought levels of the 1940s and 1950s. Here we report on experiments with the atmospheric component of a state-of-the-art global climate model to identify the causes of this recovery. Our results suggest that the direct influence of higher levels of greenhouse gases in the atmosphere was the main cause, with an additional role for changes in anthropogenic aerosol precursor emissions. We find that recent changes in SSTs, although substantial, did not have a significant impact on the recovery. The simulated response to anthropogenic greenhouse-gas and aerosol forcing is consistent with a multivariate fingerprint of the observed recovery, raising confidence in our findings. Although robust predictions are not yet possible, our results suggest that the recent recovery in Sahel rainfall amounts is most likely to be sustained or amplified in the near term.

Effects of rain shelter or simulated rain during grain filling and maturation on subsequent wheat grain quality in the UK

The effects of simulated additional rain (ear wetting, 25 mm) or of rain shelter imposed at different periods after anthesis on grain quality at maturity and the dynamics of grain filling and desiccation were investigated in UK field-grown crops of wheat (Triticum aestivum L., cvar Tybalt) in 2011 and in 2012 when June–August rainfall was 255.0 and 214.6 mm, respectively, and above the decadal mean (157.4 mm). Grain filling and desiccation were quantified well by broken-stick regressions and Gompertz curves, respectively. Rain shelter for 56 (2011) or 70 d (2012) after anthesis, and to a lesser extent during late maturation only, resulted in more rapid desiccation and hence progress to harvest maturity whereas ear wetting had negligible effects, even when applied four times. Grain-filling duration was also affected as above in 2011, but with no significant effect in 2012. In both years, there were strong positive associations between final grain dry weight and duration of filling. The treatments affected all grain quality traits in 2011: nitrogen (N) and sulphur (S) concentrations, N:S ratio, sodium dodecyl sulphate (SDS) sedimentation volume, Hagberg Falling Number (HFN), and the incidence of blackpoint. Only N concentration and blackpoint were affected significantly by treatments in 2012. Rain shelter throughout grain filling reduced N concentration, whereas rain shelter reduced the incidence of blackpoint and ear wetting increased it. In 2011, rain shelter throughout reduced S concentration, increased N:S ratio and reduced SDS. Treatment effects on HFN were not consistent within or between years. Nevertheless, a comparison between the extreme treatment means in 2012 indicated damage from late rain combined with ear wetting resulted in a reduction of c. 0.7 s in HFN/mm August rainfall, whilst that between samples taken immediately after ear wetting at harvest maturity or 7 d later suggested recovery from damage to HFN upon re-drying in planta. Hence, the incidence of blackpoint was the only grain quality trait affected consistently by the diverse treatments. The remaining aspects of grain quality were comparatively resilient to rain incident upon developing and maturing ears of cvar Tybalt. No consistent temporal patterns of sensitivity to shelter or ear wetting were detected for any aspect of grain quality.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.