Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Evaluation of ozone and water vapor fields from the ECMWF reanalysis ERA-40 during 1991-1999 in comparison with UARS satellite and MOZAIC aircraft observations

[ 1] The European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) ozone and water vapor reanalysis fields during the 1990s have been compared with independent satellite data from the Halogen Occultation Experiment (HALOE) and Microwave Limb Sounder (MLS) instruments on board the Upper Atmosphere Research Satellite (UARS). In addition, ERA-40 has been compared with aircraft data from the Measurements of Ozone and Water Vapour by Airbus In-Service Aircraft (MOZAIC) program. Overall, in comparison with the values derived from the independent observations, the upper stratosphere in ERA-40 has about 5 - 10% more ozone and 15 - 20% less water vapor. This dry bias in the reanalysis appears to be global and extends into the middle stratosphere down to 40 hPa. Most of the discrepancies and seasonal variations between ERA-40 and the independent observations occur within the upper troposphere over the tropics and the lower stratosphere over the high latitudes. ERA-40 reproduces a weaker Antarctic ozone hole, and of less vertical extent, than the independent observations; values in the ozone maximum in the tropical stratosphere are lower for the reanalysis. ERA-40 mixing ratios of water vapor are considerably larger than those for MOZAIC, typically by 20% in the tropical upper troposphere, and they may exceed 60% in the lower stratosphere over high latitudes. The results imply that the Brewer-Dobson circulation in the ECMWF reanalysis system is too fast, as is also evidenced by deficiencies in the way ERA-40 reproduces the water vapor "tape recorder'' signal in the tropical stratosphere. Finally, the paper examines the biases and their temporal variation during the 1990s in the way ERA-40 compares to the independent observations. We also discuss how the evaluation results depend on the instrument used, as well as on the version of the data.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model.

1. There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6. Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Excess open solar magnetic flux from satellite data: 1. Analysis of the third perihelion Ulysses pass

We use the third perihelion pass by the Ulysses spacecraft to illustrate and investigate the “flux excess” effect, whereby open solar flux estimates from spacecraft increase with increasing heliocentric distance. We analyze the potential effects of small-scale structure in the heliospheric field (giving fluctuations in the radial component on timescales smaller than 1 h) and kinematic time-of-flight effects of longitudinal structure in the solar wind flow. We show that the flux excess is explained by neither very small-scale structure (timescales < 1 h) nor by the kinematic “bunching effect” on spacecraft sampling. The observed flux excesses is, however, well explained by the kinematic effect of larger-scale (>1 day) solar wind speed variations on the frozen-in heliospheric field. We show that averaging over an interval T (that is long enough to eliminate structure originating in the heliosphere yet small enough to avoid cancelling opposite polarity radial field that originates from genuine sector structure in the coronal source field) is only an approximately valid way of allowing for these effects and does not adequately explain or account for differences between the streamer belt and the polar coronal holes.

Excess open solar magnetic flux from satellite data: 2. A survey of kinematic effects

We investigate the “flux excess” effect, whereby open solar flux estimates from spacecraft increase with increasing heliocentric distance. We analyze the kinematic effect on these open solar flux estimates of large-scale longitudinal structure in the solar wind flow, with particular emphasis on correcting estimates made using data from near-Earth satellites. We show that scatter, but no net bias, is introduced by the kinematic “bunching effect” on sampling and that this is true for both compression and rarefaction regions. The observed flux excesses, as a function of heliocentric distance, are shown to be consistent with open solar flux estimates from solar magnetograms made using the potential field source surface method and are well explained by the kinematic effect of solar wind speed variations on the frozen-in heliospheric field. Applying this kinematic correction to the Omni-2 interplanetary data set shows that the open solar flux at solar minimum fell from an annual mean of 3.82 × 1016 Wb in 1987 to close to half that value (1.98 × 1016 Wb) in 2007, making the fall in the minimum value over the last two solar cycles considerably faster than the rise inferred from geomagnetic activity observations over four solar cycles in the first half of the 20th century.

Forest fire plumes over the North Atlantic: p-TOMCAT model simulations with aircraft and satellite measurements from the ITOP/ICARTT campaign

Intercontinental Transport of Ozone and Precursors (ITOP) (part of International Consortium for Atmospheric Research on Transport and Transformation (ICARTT)) was an intense research effort to measure long-range transport of pollution across the North Atlantic and its impact on O3 production. During the aircraft campaign plumes were encountered containing large concentrations of CO plus other tracers and aerosols from forest fires in Alaska and Canada. A chemical transport model, p-TOMCAT, and new biomass burning emissions inventories are used to study the emissions long-range transport and their impact on the troposphere O3 budget. The fire plume structure is modeled well over long distances until it encounters convection over Europe. The CO values within the simulated plumes closely match aircraft measurements near North America and over the Atlantic and have good agreement with MOPITT CO data. O3 and NOx values were initially too great in the model plumes. However, by including additional vertical mixing of O3 above the fires, and using a lower NO2/CO emission ratio (0.008) for boreal fires, O3 concentrations are reduced closer to aircraft measurements, with NO2 closer to SCIAMACHY data. Too little PAN is produced within the simulated plumes, and our VOC scheme's simplicity may be another reason for O3 and NOx model-data discrepancies. In the p-TOMCAT simulations the fire emissions lead to increased tropospheric O3 over North America, the north Atlantic and western Europe from photochemical production and transport. The increased O3 over the Northern Hemisphere in the simulations reaches a peak in July 2004 in the range 2.0 to 6.2 Tg over a baseline of about 150 Tg.