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.

Immersive Projection for biochemical pattern matching

In all biological processes, protein molecules and other small molecules interact to function and form transient macromolecular complexes. This interaction of two or more molecules can be described by a docking event. Docking is an important phase for structure-based drug design strategies, as it can be used as a method to simulate protein-ligand interactions. Various docking programs exist that allow automated docking, but most of them have limited visualization and user interaction. It would be advantageous if scientists could visualize the molecules participating in the docking process, manipulate their structures and manually dock them before submitting the new conformations to an automated docking process in an immersive environment, which can help stimulate the design/docking process. This also could greatly reduce docking time and resources. To achieve this, we propose a new virtual modelling/docking program, whereby the advantages of virtual modelling programs and the efficiency of the algorithms in existing docking programs will be merged.

Large-scale context for the UK floods in summer 2007

This paper shows how the rainfall distribution over the UK, in the three major events on 13-15 June, 25 June and 20 July 2007, was related to troughs in the upper-level flow, and investigates the relationship of these features to a persistent large-scale flow pattern which extended around the northern hemisphere and its possible origins. Remote influences can be mediated by the propagation of large-scale atmospheric waves across the northern hemisphere and also by the origins of the air-masses that are wrapped into the developing weather systems delivering the rain to the UK. These dynamical influences are examined using analyses and forecasts produced by a range of atmospheric models.

Geostatistical Tools for Validation of Satellite and NWP Model Rainfall

Influence of south Atlantic sea surface temperatures on rainfall variability and extremes over southern Africa

It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.

An ensemble approach to uncertainty estimation for satellite-based rainfall estimates

A Possible Influence of Equatorial Winds on the September 2002 Southern Hemisphere Sudden Warming Event

The stratospheric sudden warming in the Southern Hemisphere (SH) in September 2002 was unexpected for two reasons. First, planetary wave activity in the Southern Hemisphere is very weak, and midwinter warmings have never been observed, at least not since observations of the upper stratosphere became regularly available. Second, the warming occurred in a west phase of the quasi-biennial oscillation (QBO) in the lower stratosphere. This is unexpected because warmings are usually considered to be more likely in the east phase of the QBO, when a zero wind line is present in the winter subtropics and hence confines planetary wave propagation to higher latitudes closer to the polar vortex. At first, this evidence suggests that the sudden warming must therefore be simply a result of anomalously strong planetary wave forcing from the troposphere. However, recent model studies have suggested that the midwinter polar vortex may also be sensitive to the equatorial winds in the upper stratosphere, the region dominated by the semiannual oscillation. In this paper, the time series of equatorial zonal winds from two different data sources, the 40-yr ECMWF Re-Analysis (ERA) and the Met Office assimilated dataset, are reviewed. Both suggest that the equatorial winds in the upper stratosphere above 10 hPa were anomalously easterly in 2002. Idealized model experiments are described in which the modeled equatorial winds were relaxed toward these observations for various years to examine whether the anomalous easterlies in 2002 could influence the timing of a warming event. It is found that the 2002 equatorial winds speed up the evolution of a warming event in the model. Therefore, this study suggests that the anomalous easterlies in the 1–10-hPa region may have been a contributory factor in the development of the observed SH warming. However, it is concluded that it is unlikely that the anomalous equatorial winds alone can explain the 2002 warming event.

Uncertainties in future projections of extreme precipitation in the Indian monsoon region

Uncertainties in changes to the spatial distribution and magnitude of the heaviest extremes of daily monsoon rainfall over India are assessed in the doubled CO2 climate change scenarios in the IPCC Fourth Assessment Report. Results show diverse changes to the spatial pattern of the 95th and 99th subseasonal percentiles, which are strongly tied to the mean precipitation change during boreal summer. In some models, the projected increase in heaviest rainfall over India at CO2 doubling is entirely predictable based upon the surface warming and the Clausius–Clapeyron relation, a result which may depend upon the choice of convection scheme. Copyright © 2009 Royal Meteorological Society and Crown Copyright

Dynamics of potassium leaching on a hillslope grassland soil

There have been only a few studies of potassium (K) losses from grassland systems, and little is known about their dynamics, especially in relation to nitrogen (N) management. A study was performed during the autumn and winter of 1999 and 2000 to understand the effects of N and drainage on the dynamics of K leaching on a hillslope grassland soil in southwestern England. Two N application rates were studied (0 and 280 kg N ha(-1) yr(-1)), both with and without the drainage. Treatments receiving N also received farmyard manure (FM). Higher total K losses and K concentrations in the leachates were found in the N + FM treatments (150 and 185% higher than in 0 N treatments), which were related to K additions in the FM. Drainage reduced K losses by 35% because of an increase in dry matter production and a reduction in overland and preferential flow. The pattern of change in K concentration in the leachates was associated with preferential flow at the beginning of the drainage season and with matrix flow later in winter, and was best described by a double exponential curve. Rainfall intensity and the autumn application of FM were the main determinants of K losses by leaching. The study provided new insights into the relationships between soil hydrology, rainfall, and K leaching and its implications for grassland systems.

Hydrochemical variations and contaminant load in the Rio Tinto (Spain) during flood events

The aim of this work is to study the hydrochemical variations during flood events in the Rio Tinto, SW Spain. Three separate rainfall/flood events were monitored in October 2004 following the dry season. In general, concentrations markedly increased following the first event (Fe from 99 to 1130 mg/L; Q(max) = 0.78 m(3)/s) while dissolved loads peaked in the second event (Fe = 7.5 kg/s, Cu = 0.83 kg/s, Zn = 0.82 kg/s; Q(max) = 77 m(3)/s) and discharge in the third event (Q(max) = 127 m(3)/s). This pattern reflects a progressive depletion of metals and sulphate stored in the dry summer as soluble evaporitic salt minerals and concentrated pore fluids, with dilution by freshwater becoming increasingly dominant as the month progressed. Variations in relative concentrations were attributed to oxyhydroxysulphate Fe precipitation, to relative changes in the sources of acid mine drainage (e.g. salt minerals, mine tunnels, spoil heaps etc.) and to differences in the rainfall distributions along the catchment. The contaminant load carried by the river during October 2004 was enormous, totalling some 770 t of Fe, 420 t of Al, 100 t of Cu, 100 t of Zn and 71 t of Mn. This represents the largest recorded example of this flush-out process in an acid mine drainage setting. Approximately 1000 times more water and 1408 200 times more dissolved elements were carried by the river during October 2004 than during the dry, low-flow conditions of September 2004, highlighting the key role of flood Events in the annual pollutant transport budget of semi-arid and and systems and the need to monitor these events in detail in order to accurately quantify pollutant transport. (c) 2007 Elsevier B.V. All rights reserved.

Illustration of micro-scale advection using grid-pattern mini-lysimeters

Twenty-five small soil-filled perspex boxes arranged in a square, with dwarf sunflowers growing in them, were used to study micro-scale advection. Hydrological heterogeneity was introduced by applying two different amounts of irrigation water (low-irrigation, L, versus high-irrigation, H). The nine central boxes (4 H, 4 L and I bare box) were precision weighing lysimeters, yielding diurnal measurements of evaporation. After the onset of soil water stress, a large difference in latent heat flux (up to 4-fold) was observed between the lysimeters of the H and L treatments, mainly caused by large differences between H and L stomatal conductance values. This resulted in micro-advection, causing H soil-sunflower systems to evaporate well above equilibrium latent heat flux. The occurrence of micro-advective enhancement was reflected in large values of the Priestley-Taylor constant (often larger than 2.0) and generally negative values of sensible heat flux for the H treatment. (c) 2005 Elsevier B.V. All rights reserved.