970 resultados para Rain and rainfall
Resumo:
Most of the dissolved organic carbon (DOC) exported from catchments is transported during storm events. Accurate assessments of DOC fluxes are essential to understand long-term trends in the transport of DOC from terrestrial to aquatic systems, and also the loss of carbon from peatlands to determine changes in the source/sink status of peatland carbon stores. However, many long-term monitoring programmes collect water samples at a frequency (e.g. weekly/monthly) less than the time period of a typical storm event (typically <1–2 days). As widespread observations in catchments dominated by organo-mineral soils have shown that both concentration and flux of DOC increases during storm events, lower frequency monitoring could result in substantial underestimation of DOC flux as the most dynamic periods of transport are missed. However, our intensive monitoring study in a UK upland peatland catchment showed a contrasting response to these previous studies. Our results showed that (i) DOC concentrations decreased during autumn storm events and showed a poor relationship with flow during other seasons; and that (ii) this decrease in concentrations during autumn storms caused DOC flux estimates based on weekly monitoring data to be over-estimated, rather than under-estimated, because of over rather than under estimation of the flow-weighted mean concentration used in flux calculations. However, as DOC flux is ultimately controlled by discharge volume, and therefore rainfall, and the magnitude of change in discharge was greater than the magnitude of decline in concentrations, DOC flux increased during individual storm events. The implications for long-term DOC trends are therefore contradictory, as increased rainfall could increase flux but cause an overall decrease in DOC concentrations from peatland streams. Care needs to be taken when interpreting long-term trends in DOC flux rather than concentration; as flux is calculated from discharge estimates, and discharge is controlled by rainfall, DOC flux and rainfall/discharge will always be well correlated.
Resumo:
The new HadKPP atmosphere–ocean coupled model is described and then used to determine the effects of sub-daily air–sea coupling and fine near-surface ocean vertical resolution on the representation of the Northern Hemisphere summer intra-seasonal oscillation. HadKPP comprises the Hadley Centre atmospheric model coupled to the K Profile Parameterization ocean-boundary-layer model. Four 30-member ensembles were performed that varied in oceanic vertical resolution between 1 m and 10 m and in coupling frequency between 3 h and 24 h. The 10 m, 24 h ensemble exhibited roughly 60% of the observed 30–50 day variability in sea-surface temperatures and rainfall and very weak northward propagation. Enhancing either only the vertical resolution or only the coupling frequency produced modest improvements in variability and only a standing intra-seasonal oscillation. Only the 1 m, 3 h configuration generated organized, northward-propagating convection similar to observations. Sub-daily surface forcing produced stronger upper-ocean temperature anomalies in quadrature with anomalous convection, which likely affected lower-atmospheric stability ahead of the convection, causing propagation. Well-resolved air–sea coupling did not improve the eastward propagation of the boreal summer intra-seasonal oscillation in this model. Upper-ocean vertical mixing and diurnal variability in coupled models must be improved to accurately resolve and simulate tropical sub-seasonal variability. In HadKPP, the mere presence of air–sea coupling was not sufficient to generate an intra-seasonal oscillation resembling observations.
Resumo:
This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4oC by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450ppm CO2e and leads to a 2oC increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.
Resumo:
Automatically extracting interesting objects from videos is a very challenging task and is applicable to many research areas such robotics, medical imaging, content based indexing and visual surveillance. Automated visual surveillance is a major research area in computational vision and a commonly applied technique in an attempt to extract objects of interest is that of motion segmentation. Motion segmentation relies on the temporal changes that occur in video sequences to detect objects, but as a technique it presents many challenges that researchers have yet to surmount. Changes in real-time video sequences not only include interesting objects, environmental conditions such as wind, cloud cover, rain and snow may be present, in addition to rapid lighting changes, poor footage quality, moving shadows and reflections. The list provides only a sample of the challenges present. This thesis explores the use of motion segmentation as part of a computational vision system and provides solutions for a practical, generic approach with robust performance, using current neuro-biological, physiological and psychological research in primate vision as inspiration.
Resumo:
A range of physiological parameters (canopy light transmission, canopy shape, leaf size, flowering and flushing intensity) were measured from the International Clone Trial, typically over the course of two years. Data were collected from six locations, these being: Brazil, Ecuador, Trinidad, Venezuela, Côte d’Ivoire and Ghana. Canopy shape varied significantly between clones, although it showed little variation between locations. Genotypic variation in leaf size was differentially affected by the growth location; such differences appeared to underlie a genotype by environment interaction in relation to canopy light transmission. Flushing data were recorded at monthly intervals over the course of a year. Within each location, a significant interaction was observed between genotype and time of year, suggesting that some genotypes respond to a greater extent than others to environmental stimuli. A similar interaction was observed for flowering data, where significant correlations were found between flowering intensity and temperature in Brazil and flowering intensity and rainfall in Côte d’Ivoire. The results demonstrate the need for local evaluation of cocoa clones and also suggest that the management practices for particular planting material may need to be fine-tuned to the location in which they are cultivated.
Resumo:
We present the updated Holocene section of the Sofular Cave record from the southernBlackSeacoast (northern Turkey); an area with considerably different present-day climate compared to that of the neighboring Eastern Mediterranean region. Stalagmite δ13C, growth rates and initial (234U/238U) ratios provide information about hydrological changes above the cave; and prove to be more useful than δ18O for deciphering Holocene climatic variations. Between ∼9.6 and 5.4 ka BP (despite a pause from ∼8.4 to 7.8 ka BP), the Sofular record indicates a remarkable increase in rainfall amount and intensity, in line with other paleoclimate studies in the Eastern Mediterranean. During that period, enhanced summertime insolation either produced much stronger storms in the following fall and winter through high sea surface temperatures, or it invoked a regional summer monsoon circulation and rainfall. We suggest that one or both of these climatic mechanisms led to a coupling of the BlackSea and the Mediterranean rainfall regimes at that time, which can explain the observed proxy signals. However, there are discrepancies among the Eastern Mediterranean records in terms of the timing of this wet period; implying that changes were probably not always occurring through the same mechanism. Nevertheless, the Sofular Cave record does provide hints and bring about new questions about the connection between regional and large scale climates, highlighting the need for a more extensive network of high quality paleoclimate records to better understand Holoceneclimate.
Resumo:
An automated cloud band identification procedure is developed that captures the meteorology of such events over southern Africa. This “metbot” is built upon a connected component labelling method that enables blob detection in various atmospheric fields. Outgoing longwave radiation is used to flag candidate cloud band days by thresholding the data and requiring detected blobs to have sufficient latitudinal extent and exhibit positive tilt. The Laplacian operator is used on gridded reanalysis variables to highlight other features of meteorological interest. The ability of this methodology to capture the significant meteorology and rainfall of these synoptic systems is tested in a case study. Usefulness of the metbot in understanding event to event similarities of meteorological features is demonstrated, highlighting features previous studies have noted as key ingredients to cloud band development in the region. Moreover, this allows the presentation of a composite cloud band life cycle for southern Africa events. The potential of metbot to study multiscale interactions is discussed, emphasising its key strength: the ability to retain details of extreme and infrequent events. It automatically builds a database that is ideal for research questions focused on the influence of intraseasonal to interannual variability processes on synoptic events. Application of the method to convergence zone studies and atmospheric river descriptions is suggested. In conclusion, a relation-building metbot can retain details that are often lost with object-based methods but are crucial in case studies. Capturing and summarising these details may be necessary to develop deeper process-level understanding of multiscale interactions.
Resumo:
A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective storms and rainfall distributions. The DYMECS project (Dynamical and Microphysical Evolution of Convective Storms) is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, we have gathered a large database of 3D storm structures on 40 convective days using the Chilbolton radar in southern England. We have related these structures to storm life-cycles derived by tracking features in the rainfall from the UK radar network, and compared them statistically to storm structures in the Met Office model, which we ran at horizontal grid length between 1.5 km and 100 m, including simulations with different subgrid mixing length. We also evaluated the scale and intensity of convective updrafts using a new radar technique. We find that the horizontal size of simulated convective storms and the updrafts within them is much too large at 1.5-km resolution, such that the convective mass flux of individual updrafts can be too large by an order of magnitude. The scale of precipitation cores and updrafts decreases steadily with decreasing grid lengths, as does the typical storm lifetime. The 200-m grid-length simulation with standard mixing length performs best over all diagnostics, although a greater mixing length improves the representation of deep convective storms.
Resumo:
The destructive environmental and socio-economic impacts of the El Niño/Southern Oscillation1, 2 (ENSO) demand an improved understanding of how ENSO will change under future greenhouse warming. Robust projected changes in certain aspects of ENSO have been recently established3, 4, 5. However, there is as yet no consensus on the change in the magnitude of the associated sea surface temperature (SST) variability6, 7, 8, commonly used to represent ENSO amplitude1, 6, despite its strong effects on marine ecosystems and rainfall worldwide1, 2, 3, 4, 9. Here we show that the response of ENSO SST amplitude is time-varying, with an increasing trend in ENSO amplitude before 2040, followed by a decreasing trend thereafter. We attribute the previous lack of consensus to an expectation that the trend in ENSO amplitude over the entire twenty-first century is unidirectional, and to unrealistic model dynamics of tropical Pacific SST variability. We examine these complex processes across 22 models in the Coupled Model Intercomparison Project phase 5 (CMIP5) database10, forced under historical and greenhouse warming conditions. The nine most realistic models identified show a strong consensus on the time-varying response and reveal that the non-unidirectional behaviour is linked to a longitudinal difference in the surface warming rate across the Indo-Pacific basin. Our results carry important implications for climate projections and climate adaptation pathways.
Resumo:
During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from seasonal forecast models to give a more detailed monthly outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of a monthly outlook column. This monthly outlook is an indication of the average likely conditions for that month and region and is not a definite prediction of weather impacts.
Resumo:
During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g. droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g. health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015 and SON 2015, a detailed monthly outlook from 5 modeling centres for Dec 2015 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of JF 2016 and MAM 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts.
Resumo:
During the summer and autumn of 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and Dec 2015, a detailed monthly outlook from 4 modeling centres for Jan 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of Feb 2016, MAM 2016 and Jun 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts.
Resumo:
During the summer and autumn of 2015, El Niño conditions in the east and central Pacific strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during the summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work, providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and DJ 2015/2016, a detailed monthly outlook from 5 modeling centres for Feb 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of MAM 2016 and JJ 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts. This report has been produced by University of Reading for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited.
Resumo:
During the summer and autumn of 2015, El Niño conditions in the east and central Pacific strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during the summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work, providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and DJF 2015/2016, a detailed monthly outlook from 5 modeling centres for Mar 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of AM 2016 and JJA 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts. This report has been produced by University of Reading for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited.
Resumo:
Mosquito diversity was determined in an area located on the southern limit of the Atlantic Forest on the north coast of Rio Grande of Sul State. Our major objective was to verify the composition, diversity, and temporal distribution of the mosquito fauna, and the influence of temperature and rainfall. Samplings were performed monthly between December, 2006 and December, 2008, in three biotopes: forest, urban area, and transition area, using CDC light traps and a Nasci vacuum. A total of 2,376 specimens was collected, from which 1,766 (74.32%) were identified as 55 different species belonging to ten genera. Culex lygrus, Aedes serratus, and Aedes nubilus were dominant (eudominant) and constant throughout samplings. The forest environment presented the highest species dominance (D(S) = 0.20), while the transition area showed the highest values of diversity (H` = 2.55) and evenness (J` = 0.85). These two environments were the most similar, according to the Morisita-Horn Index (I(M-H) = 0.35). Bootstrap estimates showed that 87.3% of the species occurring in the region were detected. The seasonal pattern showed a greater abundance of mosquitoes between May and October, indicating the period to intensify entomological surveillance in that area. Journal of Vector Ecology 36 (1): 175-186. 2011.