Role of Vertical Resolution in Numerical Models Towards the Intensification,Structure and Track of Tropical Cyclones

The impact of vertical resolution on the evolution and movement of tropical cyclones was studied using NCAR MM5 model with a horizontal resolution of 9 km. Four numerical experiments were performed with different vertical resolutions, that is, with 23 vertical levels as control experiment, and 36 vertical levels with high resolution in the lower troposphere, 33 vertical levels with high resolution in the upper troposphere and 46 vertical levels with increased vertical resolution throughout the troposphere as relative to base experiment. The results indicate that increased vertical resolution in the lower troposphere produces efficient intensification and better structure in terms of eye and eyewall. Increased vertical resolution at lower levels improves the prediction of vertical shear of horizontal wind. Experiments with high resolution in the lower troposphere and high resolution throughout the troposphere simulate better track up to 72 hours.     

A Dynamical Statistical Model for Prediction of a Tropical Cyclone

A dynamical statistical method is applied for operational forecasting of the Bay of Bengal tropical cyclone “Nargis” of April–May 2008. The method consists of three forecast components, namely (a) analysis of Genesis Potential Parameter (GPP) and maximum potential intensity, (b) track prediction, and (c) 12 hourly intensity prediction for forecasts up to 72 hours. The results of the study showed that GPP could provide necessary predictive signal at early stages of development on the further intensification of the low pressure system into a tropical cyclone. The landfall forecast position errors by different operational numerical models (NWP) showed landfall position errors ranging from 10 km to 150 km and landfall time error ranges from 6 hours early to 6 hours delay. The dynamical statistical model is capable to provide 12 hourly nearly realistic intensity forecasts up to 60 hours of forecast.     

The Sunda Shelf—A Submerged Amazon Basin?

A crucial and debatable issue in paleoclimatology is the change of terrestrial vegetation and the role of its carbon storage in glacial cycles. In the modern world, the Amazon Basin hosts the largest tropical rainforest and plays a major role of carbon sink, but during the glacial times another large tropical rainforest must have formed in the then emerged Sunda Shelf, SE Asia, and significantly changed the global carbon cycling. Accordingly, ocean drilling expeditions to the Sunda Shelf are being proposed in order to investigate the sea level changes, evolution of river network, vegetation and carbon storage, as well as biogeography of the tropical region over the last millions of years.     

Effects of sampling effort on the estimation of spatial gradients in a tropical reservoir impacted by an oil refinery

We investigated the effects of increase in sampling effort (30-1043 sampling points) on the accuracy of assessment of the spatial patterns of surface-water quality in a eutrophic tropical reservoir. The investigation was carried out during the dry season, when previous investigations showed that the spatial heterogeneity is more stable. A multi-parameter Yellow Springs Instruments probe coupled to a TechGeo D-GPS was used. This system is equipped to measure and store in a continuous recording mode, several physical and chemical parameters linked to geographical coordinates obtained with a precision of less than 1 m. We used different geostatistical approaches to determine the optimal number of sampling points required to reflect the real spatial patterns of water quality in the system. This approach was tested in a small tropical reservoir (Ibirité) that receives effluents from an oil refinery (the state-owned REGAP oil refinery, PETROBRAS) located near the city of Belo Horizonte. The study showed not only that the spatial patterns of water quality are significantly affected by sampling effort but also it was demonstrated that the establishment of an adequate sampling program is a critical point for the precise identification of source points of pollution. The results of this investigation enabled us to demonstrate the potential uses and limits of this method for rapid assessment of the water quality of lakes and reservoirs that receive external inputs of water contaminants or nutrients.     

Land use and topography as predictors of nutrient levels in a tropical catchment

The influence of landscape on nutrient concentration and yield was analyzed in a tropical catchment, the Guare River in northern Venezuela. Spatial and temporal variation in nitrate, SRP and total P were determined in 15 sites located along the river mainstem and tributaries. Higher nitrate concentrations and yields were reported from upper sites and both decreased in the downstream direction along the river mainstem. These trends appear to be related to more pronounced slopes and larger proportions of agricultural and forest lands in subcatchments located in the upper part of the basin, and dense algal mats in the lower reaches. Nitrate values were higher during periods of high discharge, suggesting that nitrate is primarily transported by shallow subsurface flow. SRP represented between 60 and 80% of total P. Phosphorus concentrations were homogeneous along the river mainstem and showed little seasonal variation, while yields were higher in the upper basin. Multiple regression identified slope, runoff and agriculture as primary predictors of nitrate and phosphorus across the watershed, which suggests that both natural and anthropogenic landscape characteristics have a strong influence on nutrient levels in the Guare catchment.     

Effective typhoon characteristics and their effects on hourly reservoir inflow forecasting

This paper describes the identification of effective typhoon characteristics and the development of a new type of hourly reservoir inflow forecasting model with the effective typhoon characteristics. Firstly, a comparison of support vector machines (SVMs), which is a novel kind of neural networks (NNs), and back-propagation networks (BPNs) is made to select an appropriate NN-based model. The results show that SVM-based models are more appropriate than BPN-based models because of their higher accuracy and much higher efficiency. In addition, effective typhoon characteristics for improving forecasting performance are identified from all the collected typhoon information. Then the effective typhoon characteristics (the position of the typhoon and the distance between the typhoon center and the reservoir) are added to the proposed SVM-based models. Next, a performance comparison of models with and without effective typhoon characteristics is conducted to clearly highlight the effects of effective typhoon characteristics on hourly reservoir inflow forecasting. To reach a just conclusion, the performance is evaluated by cross validation, and the improvement in performance due to the addition of effective typhoon characteristics is tested by paired comparison t-tests at the 5% significance level. The results confirm that effective typhoon characteristics do improve the forecasting performance and the improvement increases with increasing lead-time, especially when the rainfall data are not available. For four- to six-hour ahead forecasts, the improvement due to the addition of effective typhoon characteristics increases from 3% to 18% and from 10% to 113% for Categories I (rainfall data are available) and II (rainfall data are not available), respectively. In conclusion, effective typhoon characteristics are recommended as key inputs for reservoir inflow forecasting during typhoons. The proposed SVM-based models with effective typhoon characteristics are expected to provide more accurate forecasts than BPN-based models. The proposed modeling technique is also expected to be useful to support reservoir operation systems and other disaster warning systems.     

Location offarm woodlands in Denmark: a quantification of the results of the scheme for field afforestation in Ribe and Vejle counties

The article analyses the results of the scheme for field afforestation (EU-regulation 2080/92) in Denmark. The purpose is twofold, firstly to document the afforestation on arable land taking place both within the scheme and outside the scheme for field afforestation. The former is documented in Ribe and Vejle counties whereas the latter is documented in three smaller areas: Varde, Vorbasse, and Vejle. Secondly, the article argues that in order to evaluate the afforestation not only the location within designated areas hut also the spatial parameters and configuration of new woodlands must be considered. Two methods -'forest-pictures' and ‘gradient-pictures’-are presented and applied in order to quantify the spatial configuration of new woodlands in the landscape.     

African Environment and Development: Rhetoric,Programs, Realities

Tropical deforestation is widely believed to directly influence the climate at a number of scales. Yet while much has been written about the tropical forest-climate relationship, there is little empirical evidence showing if and how local and regional climates are modified by deforestation. This study presents the results of an analysis of deforestation and climate change in a rain forest in southern Mexico. Records from 18 climate stations in the Selva Lacandona of Chiapas, Mexico were examined and related to an analysis of deforestation based on Landsat images. The area surrounding some stations has been deforested since the stations were established, while the area surroundings others has remained forested. Strong climatic trends were generally evident at the deforested stations, including decreases in the average daily maximum temperature and temperature range. No precipitation changes were observed. A comparison of the results with microclimatic experiments and modeling studies suggests that the climatic impacts of deforestation are overgeneralized at the local scale. Landscape heterogeneity appears to influence the biophysical mechanisms linking tropical forests and climate, and should be explicitly represented in modeling studies.     

Forthcoming events

Tropical cyclones (hurricanes and typhoons) produce high winds that can generate waves capable of damaging coral reefs. As cyclones frequently pass through northeast Australia's Great Barrier Reef (GBR), it is important to understand how the spatial distribution of reef damage changes over time. However, direct measurements of wave damage, or even wave heights or wind speeds, are rare within the GBR. An important factor in estimating whether cyclone damage was possible is the magnitude and duration of high‐energy wind and waves. Thus, before the spatio‐temporal dynamics of past cyclone damage can be modelled, it is necessary to reconstruct the spread, intensity, and duration of high‐energy conditions during individual cyclones. This was done every hour along the track taken by each of 85 cyclones that passed near the GBR from 1969 to 2003, by implementing a cyclone wind hindcasting model directly within a raster GIS using cyclone data available from the Australian Bureau of Meteorology. Three measures of cyclone energy (maximum wind speed—MAX, duration of gales—GALES, and continuous duration of gales—CGALES) were derived from these data. For three cyclones, where field data documenting actual reef damage from cyclone‐generated waves were available, the predictive ability of each measure was assessed statistically. All three performed better in predicting reef damage at sites surveyed along the high‐energy reef front than those surveyed along the more protected reef back. MAX performed best for cyclone Joy (r ² = 0.5), while CGALES performed best for cyclones Ivor (r ² = 0.23) and Justin (r ² = 0.48). Using thresholds for MAX and GALES obtained via comparison with field data of damage, it was possible to produce a preliminary prediction of the risk of wave damage across the GBR from each of the 85 cyclones. The results suggest that while up to two‐thirds of the GBR was at risk from some damage for 30–50% of the time series (～18 out of 35 years), only scattered areas of the region were at risk more frequently than that.     

The Record-breaking Mei-yu in 2020 and Associated Atmospheric Circulation and Tropical SST Anomalies※

The record-breaking mei-yu in the Yangtze-Huaihe River valley (YHRV) in 2020 was characterized by an early onset, a delayed retreat, a long duration, a wide meridional rainbelt, abundant precipitation, and frequent heavy rainstorm processes. It is noted that the East Asian monsoon circulation system presented a significant quasi-biweekly oscillation (QBWO) during the mei-yu season of 2020 that was associated with the onset and retreat of mei-yu, a northward shift and stagnation of the rainbelt, and the occurrence and persistence of heavy rainstorm processes. Correspondingly, during the mei-yu season, the monsoon circulation subsystems, including the western Pacific subtropical high (WPSH), the upper-level East Asian westerly jet, and the low-level southwesterly jet, experienced periodic oscillations linked with the QBWO. Most notably, the repeated establishment of a large southerly center, with relatively stable latitude, led to moisture convergence and ascent which was observed to develop repeatedly. This was accompanied by a long-term duration of the mei-yu rainfall in the YHRV and frequent occurrences of rainstorm processes. Moreover, two blocking highs were present in the middle to high latitudes over Eurasia, and a trough along the East Asian coast was also active, which allowed cold air intrusions to move southward through the northwestern and/or northeastern paths. The cold air frequently merged with the warm and moist air from the low latitudes resulting in low-level convergence over the YHRV. The persistent warming in the tropical Indian Ocean is found to be an important external contributor to an EAP/PJ-like teleconnection pattern over East Asia along with an intensified and southerly displaced WPSH, which was observed to be favorable for excessive rainfall over YHRV.