115 resultados para High-resolution measurements
Resumo:
The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project, using PRACE (Partnership for Advanced Computing in Europe) resources, constructed and ran an ensemble of atmosphere-only global climate model simulations, using the Met Office Unified Model GA3 configuration. Each simulation is 27 years in length for both the present climate and an end-of-century future climate, at resolutions of N96 (130 km), N216 (60 km) and N512 (25 km), in order to study the impact of model resolution on high impact climate features such as tropical cyclones. Increased model resolution is found to improve the simulated frequency of explicitly tracked tropical cyclones, and correlations of interannual variability in the North Atlantic and North West Pacific lie between 0.6 and 0.75. Improvements in the deficit of genesis in the eastern North Atlantic as resolution increases appear to be related to the representation of African Easterly Waves and the African Easterly Jet. However, the intensity of the modelled tropical cyclones as measured by 10 m wind speed remain weak, and there is no indication of convergence over this range of resolutions. In the future climate ensemble, there is a reduction of 50% in the frequency of Southern Hemisphere tropical cyclones, while in the Northern Hemisphere there is a reduction in the North Atlantic, and a shift in the Pacific with peak intensities becoming more common in the Central Pacific. There is also a change in tropical cyclone intensities, with the future climate having fewer weak storms and proportionally more stronger storms
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The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.
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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.
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The Madden–Julian Oscillation (MJO) is the chief source of tropical intra-seasonal variability, but is simulated poorly by most state-of-the-art GCMs. Common errors include a lack of eastward propagation at the correct frequency and zonal extent, and too small a ratio of eastward- to westward-propagating variability. Here it is shown that HiGEM, a high-resolution GCM, simulates a very realistic MJO with approximately the correct spatial and temporal scale. Many MJO studies in GCMs are limited to diagnostics which average over a latitude band around the equator, allowing an analysis of the MJO’s structure in time and longitude only. In this study a wider range of diagnostics is applied. It is argued that such an approach is necessary for a comprehensive analysis of a model’s MJO. The standard analysis of Wheeler and Hendon (Mon Wea Rev 132(8):1917–1932, 2004; WH04) is applied to produce composites, which show a realistic spatial structure in the MJO envelopes but for the timing of the peak precipitation in the inter-tropical convergence zone, which bifurcates the MJO signal. Further diagnostics are developed to analyse the MJO’s episodic nature and the “MJO inertia” (the tendency to remain in the same WH04 phase from one day to the next). HiGEM favours phases 2, 3, 6 and 7; has too much MJO inertia; and dies out too frequently in phase 3. Recent research has shown that a key feature of the MJO is its interaction with the diurnal cycle over the Maritime Continent. This interaction is present in HiGEM but is unrealistically weak.
Resumo:
High-resolution simulations over a large tropical domain (∼20◦S–20◦N and 42◦E–180◦E) using both explicit and parameterized convection are analyzed and compared during a 10-day case study of an active Madden-Julian Oscillation (MJO) event. In Part II, the moisture budgets and moist entropy budgets are analyzed. Vertical subgrid diabatic heating profiles and vertical velocity profiles are also compared; these are related to the horizontal and vertical advective components of the moist entropy budget which contribute to gross moist stability, GMS, and normalized GMS (NGMS). The 4-km model with explicit convection and good MJO performance has a vertical heating structure that increases with height in the lower troposphere in regions of strong convection (like observations), whereas the 12-km model with parameterized convection and a poor MJO does not show this relationship. The 4-km explicit convection model also has a more top-heavy heating profile for the troposphere as a whole near and to the west of the active MJO-related convection, unlike the 12-km parameterized convection model. The dependence of entropy advection components on moisture convergence is fairly weak in all models, and differences between models are not always related to MJO performance, making comparisons to previous work somewhat inconclusive. However, models with relatively good MJO strength and propagation have a slightly larger increase of the vertical advective component with increasing moisture convergence, and their NGMS vertical terms have more variability in time and longitude, with total NGMS that is comparatively larger to the west and smaller to the east.
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BACKGROUND: Mealybugs (Hemiptera: Coccoidea: Pseudococcidae) are key vectors of badnaviruses, including Cacao Swollen Shoot Virus (CSSV) the most damaging virus affecting cacao (Theobroma cacao L.). The effectiveness of mealybugs as virus vectors is species dependent and it is therefore vital that CSSV resistance breeding programmes in cacao incorporate accurate mealybug identification. In this work the efficacy of a CO1-based DNA barcoding approach to species identification was evaluated by screening a range of mealybugs collected from cacao in seven countries. RESULTS: Morphologically similar adult females were characterised by scanning electron microscopy and then, following DNA extraction, were screened with CO1 barcoding markers. A high degree of CO1 sequence homology was observed for all 11 individual haplotypes including those accessions from distinct geographical regions. This has allowed for the design of a High Resolution Melt (HRM) assay capable of rapid identification of the commonly encountered mealybug pests of cacao. CONCLUSIONS: HRM Analysis (HRMA) readily differentiated between mealybug pests of cacao that can not necessarily be identified by conventional morphological analysis. This new approach, therefore, has potential to facilitate breeding for resistance to CSSV and other mealybug transmitted diseases.
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The North Atlantic Ocean subpolar gyre (NA SPG) is an important region for initialising decadal climate forecasts. Climate model simulations and palaeo climate reconstructions have indicated that this region could also exhibit large, internally generated variability on decadal timescales. Understanding these modes of variability, their consistency across models, and the conditions in which they exist, is clearly important for improving the skill of decadal predictions — particularly when these predictions are made with the same underlying climate models. Here we describe and analyse a mode of internal variability in the NA SPG in a state-of-the-art, high resolution, coupled climate model. This mode has a period of 17 years and explains 15–30% of the annual variance in related ocean indices. It arises due to the advection of heat content anomalies around the NA SPG. Anomalous circulation drives the variability in the southern half of the NA SPG, whilst mean circulation and anomalous temperatures are important in the northern half. A negative feedback between Labrador Sea temperatures/densities and those in the North Atlantic Current is identified, which allows for the phase reversal. The atmosphere is found to act as a positive feedback on to this mode via the North Atlantic Oscillation which itself exhibits a spectral peak at 17 years. Decadal ocean density changes associated with this mode are driven by variations in temperature, rather than salinity — a point which models often disagree on and which we suggest may affect the veracity of the underlying assumptions of anomaly-assimilating decadal prediction methodologies.
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Medicanes or “Mediterranean hurricanes” represent a rare and physically unique type of Mediterranean mesoscale cyclone. There are similarities with tropical cyclones with regard to their development (based on the thermodynamical disequilibrium between the warm sea and the overlying troposphere) and their kinematic and thermodynamical properties (medicanes are intense vortices with a warm core and even a cloud-free eye). Although medicanes are smaller and their wind speeds are lower than in tropical cyclones, the severity of their winds can cause substantial damage to islands and coastal areas. Concern about how human-induced climate change will affect extreme events is increasing. This includes the future impacts on medicanes due to the warming of the Mediterranean waters and the projected changes in regional atmospheric circulation. However, most global climate models do not have high enough spatial resolution to adequately represent small features such as medicanes. In this study, a cyclone tracking algorithm is applied to high resolution global climate model data with a horizontal grid resolution of approximately 25 km over the Mediterranean region. After a validation of the climatology of general Mediterranean mesoscale cyclones, changes in medicanes are determined using climate model experiments with present and future forcing. The magnitude of the changes in the winds, frequency and location of medicanes is assessed. While no significant changes in the total number of Mediterranean mesoscale cyclones are found, medicanes tend to decrease in number but increase in intensity. The model simulation suggests that medicanes tend to form more frequently in the Gulf of Lion–Genoa and South of Sicily.
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A new generation of high-resolution (1 km) forecast models promises to revolutionize the prediction of hazardous weather such as windstorms, flash floods, and poor air quality. To realize this promise, a dense observing network, focusing on the lower few kilometers of the atmosphere, is required to verify these new forecast models with the ultimate goal of assimilating the data. At present there are insufficient systematic observations of the vertical profiles of water vapor, temperature, wind, and aerosols; a major constraint is the absence of funding to install new networks. A recent research program financed by the European Union, tasked with addressing this lack of observations, demonstrated that the assimilation of observations from an existing wind profiler network reduces forecast errors, provided that the individual instruments are strategically located and properly maintained. Additionally, it identified three further existing European networks of instruments that are currently underexploited, but with minimal expense they could deliver quality-controlled data to national weather services in near–real time, so the data could be assimilated into forecast models. Specifically, 1) several hundred automatic lidars and ceilometers can provide backscatter profiles associated with aerosol and cloud properties and structures with 30-m vertical resolution every minute; 2) more than 20 Doppler lidars, a fairly new technology, can measure vertical and horizontal winds in the lower atmosphere with a vertical resolution of 30 m every 5 min; and 3) about 30 microwave profilers can estimate profiles of temperature and humidity in the lower few kilometers every 10 min. Examples of potential benefits from these instruments are presented.
Resumo:
Sea surface temperature (SST) data are often provided as gridded products, typically at resolutions of order 0.05 degrees from satellite observations to reduce data volume at the request of data users and facilitate comparison against other products or models. Sampling uncertainty is introduced in gridded products where the full surface area of the ocean within a grid cell cannot be fully observed because of cloud cover. In this paper we parameterise uncertainties in SST as a function of the percentage of clear-sky pixels available and the SST variability in that subsample. This parameterisation is developed from Advanced Along Track Scanning Radiometer (AATSR) data, but is applicable to all gridded L3U SST products at resolutions of 0.05-0.1 degrees, irrespective of instrument and retrieval algorithm, provided that instrument noise propagated into the SST is accounted for. We also calculate the sampling uncertainty of ~0.04 K in Global Area Coverage (GAC) Advanced Very High Resolution Radiometer (AVHRR) products, using related methods.
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The co-polar correlation coefficient (ρhv) has many applications, including hydrometeor classification, ground clutter and melting layer identification, interpretation of ice microphysics and the retrieval of rain drop size distributions (DSDs). However, we currently lack the quantitative error estimates that are necessary if these applications are to be fully exploited. Previous error estimates of ρhv rely on knowledge of the unknown "true" ρhv and implicitly assume a Gaussian probability distribution function of ρhv samples. We show that frequency distributions of ρhv estimates are in fact highly negatively skewed. A new variable: L = -log10(1 - ρhv) is defined, which does have Gaussian error statistics, and a standard deviation depending only on the number of independent radar pulses. This is verified using observations of spherical drizzle drops, allowing, for the first time, the construction of rigorous confidence intervals in estimates of ρhv. In addition, we demonstrate how the imperfect co-location of the horizontal and vertical polarisation sample volumes may be accounted for. The possibility of using L to estimate the dispersion parameter (µ) in the gamma drop size distribution is investigated. We find that including drop oscillations is essential for this application, otherwise there could be biases in retrieved µ of up to ~8. Preliminary results in rainfall are presented. In a convective rain case study, our estimates show µ to be substantially larger than 0 (an exponential DSD). In this particular rain event, rain rate would be overestimated by up to 50% if a simple exponential DSD is assumed.
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This paper describes the development and basic evaluation of decadal predictions produced using the HiGEM coupled climate model. HiGEM is a higher resolution version of the HadGEM1 Met Office Unified Model. The horizontal resolution in HiGEM has been increased to 1.25◦ × 0.83◦ in longitude and latitude for the atmosphere, and 1/3◦ × 1/3◦ globally for the ocean. The HiGEM decadal predictions are initialised using an anomaly assimilation scheme that relaxes anomalies of ocean temperature and salinity to observed anomalies. 10 year hindcasts are produced for 10 start dates (1960, 1965,..., 2000, 2005). To determine the relative contributions to prediction skill from initial conditions and external forcing, the HiGEM decadal predictions are compared to uninitialised HiGEM transient experiments. The HiGEM decadal predictions have substantial skill for predictions of annual mean surface air temperature and 100 m upper ocean temperature. For lead times up to 10 years, anomaly correlations (ACC) over large areas of the North Atlantic Ocean, the Western Pacific Ocean and the Indian Ocean exceed values of 0.6. Initialisation of the HiGEM decadal predictions significantly increases skill over regions of the Atlantic Ocean,the Maritime Continent and regions of the subtropical North and South Pacific Ocean. In particular, HiGEM produces skillful predictions of the North Atlantic subpolar gyre for up to 4 years lead time (with ACC > 0.7), which are significantly larger than the uninitialised HiGEM transient experiments.
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A powerful way to test the realism of ocean general circulation models is to systematically compare observations of passive tracer concentration with model predictions. The general circulation models used in this way cannot resolve a full range of vigorous mesoscale activity (on length scales between 10–100 km). In the real ocean, however, this activity causes important variability in tracer fields. Thus, in order to rationally compare tracer observations with model predictions these unresolved fluctuations (the model variability error) must be estimated. We have analyzed this variability using an eddy‐resolving reduced‐gravity model in a simple midlatitude double‐gyre configuration. We find that the wave number spectrum of tracer variance is only weakly sensitive to the distribution of (large scale slowly varying) tracer sources and sinks. This suggests that a universal passive tracer spectrum may exist in the ocean. We estimate the spectral shape using high‐resolution measurements of potential temperature on an isopycnal in the upper northeast Atlantic Ocean, finding a slope near k −1.7 between 10 and 500 km. The typical magnitude of the variance is estimated by comparing tracer simulations using different resolutions. For CFC‐ and tritium‐type transient tracers the peak magnitude of the model variability saturation error may reach 0.20 for scales shorter than 100 km. This is of the same order as the time mean saturation itself and well over an order of magnitude greater than the instrumental uncertainty.
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Ground-based observations of dayside auroral forms and magnetic perturbations in the arctic sectors of Svalbard and Greenland, in combination with the high-resolution measurements of ionospheric ion drift and temperature by the EISCAT radar, are used to study temporal/spatial structures of cusp-type auroral forms in relation to convection. Large-scale patterns of equivalent convection in the dayside polar ionosphere are derived from the magnetic observations in Greenland and Svalbard. This information is used to estimate the ionospheric convection pattern in the vicinity of the cusp/cleft aurora. The reported observations, covering the period 0700-1130 UT, on January 11, 1993, are separated into four intervals according to the observed characteristics of the aurora and ionospheric convection. The morphology and intensity of the aurora are very different in quiet and disturbed intervals. A latitudinally narrow zone of intense and dynamical 630.0 nm emission equatorward of 75 degrees MLAT, was observed during periods of enhanced antisunward convection in the cusp region. This (type 1 cusp aurora) is considered to be the signature of plasma entry via magnetopause reconnection at low magnetopause latitudes, i.e. the low-latitude boundary layer (LLB I,). Another zone of weak 630.0 nm emission (type 2 cusp aurora) was observed to extend up to high latitudes (similar to 79 degrees MLAT) during relatively quiet magnetic conditions, when indications of reverse (sunward) convection was observed in the dayside polar cap. This is postulated to be a signature of merging between a northward directed IMF (B-z > 0) and the geomagnetic field poleward of the cusp. The coexistence of type 1 and 2 auroras was observed under intermediate circumstances. The optical observations from Svalbard and Greenland were also used to determine the temporal and spatial evolution of type 1 auroral forms, i.e. poleward-moving auroral events occurring in the vicinity of a rotational convection reversal in the early post-noon sector. Each event appeared as a local brightening at the equatorward boundary of the pre-existing type 1 cusp aurora, followed by poleward and eastward expansions of luminosity. The auroral events were associated with poleward-moving surges of enhanced ionospheric convection and F-layer ion temperature as observed by the EISCAT radar in Tromso. The EISCAT ion flow data in combination with the auroral observations show strong evidence for plasma flow across the open/closed field line boundary.