416 resultados para EXTRATROPICAL CYCLONES


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We investigate the scaling between precipitation and temperature changes in warm and cold climates using six models that have simulated the response to both increased CO2 and Last Glacial Maximum (LGM) boundary conditions. Globally, precipitation increases in warm climates and decreases in cold climates by between 1.5%/°C and 3%/°C. Precipitation sensitivity to temperature changes is lower over the land than over the ocean and lower over the tropical land than over the extratropical land, reflecting the constraint of water availability. The wet tropics get wetter in warm climates and drier in cold climates, but the changes in dry areas differ among models. Seasonal changes of tropical precipitation in a warmer world also reflect this “rich get richer” syndrome. Precipitation seasonality is decreased in the cold-climate state. The simulated changes in precipitation per degree temperature change are comparable to the observed changes in both the historical period and the LGM.

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The occurrence of destructive mesoscale ‘polar low’ cyclones in the subpolar North Atlantic is projected to decline under anthropogenic change, due to an increase in atmospheric static stability. This letter reports on the role of changes in ocean circulation in shaping the atmospheric stability. In particular, the Atlantic Meridional Overturning Circulation (AMOC) is projected to weaken in response to anthropogenic forcing, leading to a local minimum in warming in this region. The reduced warming is restricted to the lower troposphere, hence contributing to the increase in static stability. Linear correlation analysis of the CMIP3 climate model ensemble suggests that around half of the model uncertainty in the projected stability response arises from the varied response of the AMOC between models.

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The summertime variability of the extratropical storm track over the Atlantic sector and its links to European climate have been analysed for the period 1948–2011 using observations and reanalyses. The main results are as follows. (1) The dominant mode of the summer storm track density variability is characterized by a meridional shift of the storm track between two distinct paths and is related to a bimodal distribution in the climatology for this region. It is also closely related to the Summer North Atlantic Oscillation (SNAO). (2) A southward shift is associated with a downstream extension of the storm track and a decrease in blocking frequency over the UK and northwestern Europe. (3) The southward shift is associated with enhanced precipitation over the UK and northwestern Europe and decreased precipitation over southern Europe (contrary to the behaviour in winter). (4) There are strong ocean–atmosphere interactions related to the dominant mode of storm track variability. The atmosphere forces the ocean through anomalous surface fluxes and Ekman currents, but there is also some evidence consistent with an ocean influence on the atmosphere, and that coupled ocean–atmosphere feedbacks might play a role. The ocean influence on the atmosphere may be particularly important on decadal timescales, related to the Atlantic Multidecadal Oscillation (AMO).

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The impact of El Nino–Southern Oscillation (ENSO) on atmospheric Kelvin waves and associated tropical convection is investigated using the ECMWF Re-Analysis, NOAA outgoing longwave radiation (OLR), and the analysis technique introduced in a previous study. It is found that the phase of ENSO has a substantial impact on Kelvin waves and associated convection over the equatorial central-eastern Pacific. El Nino (La Nina) events enhance (suppress) variability of the upper-tropospheric Kelvin wave and the associated convection there, both in extended boreal winter and summer. The mechanism of the impact is through changes in the ENSO-related thermal conditions and the ambient flow. In El Nino years, because of SST increase in the equatorial central-eastern Pacific, variability of eastward-moving convection, which is mainly associated with Kelvin waves, intensifies in the region. In addition, owing to the weakening of the equatorial eastern Pacific westerly duct in the upper troposphere in El Nino years, Kelvin waves amplify there. In La Nina years, the opposite occurs. However, the stronger westerly duct in La Nina winters allows more NH extratropical Rossby wave activity to propagate equatorward and force Kelvin waves around 200 hPa, partially offsetting the in situ weakening effect of the stronger westerlies on the waves. In general, in El Nino years Kelvin waves are more convectively and vertically coupled and propagate more upward into the lower stratosphere over the central-eastern Pacific. The ENSO impact in other regions is not clear, although in winter over the eastern Indian and western Pacific Oceans Kelvin waves and their associated convection are slightly weaker in El Nino than in La Nina years.

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The warm conveyor belt (WCB) of an extratropical cyclone generally splits into two branches. One branch (WCB1) turns anticyclonically into the downstream upper-level tropospheric ridge, while the second branch (WCB2) wraps cyclonically around the cyclone centre. Here, the WCB split in a typical North Atlantic cold-season cyclone is analysed using two numerical models: the Met Office Unified Model and the COSMO model. The WCB flow is defined using off-line trajectory analysis. The two models represent the WCB split consistently. The split occurs early in the evolution of the WCB with WCB1 experiencing maximum ascent at lower latitudes and with higher moisture content than WCB2. WCB1 ascends abruptly along the cold front where the resolved ascent rates are greatest and there is also line convection. In contrast, WCB2 remains at lower levels for longer before undergoing saturated large-scale ascent over the system's warm front. The greater moisture in WCB1 inflow results in greater net potential temperature change from latent heat release, which determines the final isentropic level of each branch. WCB1 also exhibits lower outflow potential vorticity values than WCB2. Complementary diagnostics in the two models are utilised to study the influence of individual diabatic processes on the WCB. Total diabatic heating rates along the WCB branches are comparable in the two models with microphysical processes in the large-scale cloud schemes being the major contributor to this heating. However, the different convective parameterisation schemes used by the models cause significantly different contributions to the total heating. These results have implications for studies on the influence of the WCB outflow in Rossby wave evolution and breaking. Key aspects are the net potential temperature change and the isentropic level of the outflow which together will influence the relative mass going into each WCB branch and the associated negative PV anomalies at the tropopause-level flow.

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The relationship between biases in Northern Hemisphere (NH) atmospheric blocking frequency and extratropical cyclone track density is investigated in 12 CMIP5 climate models to identify mechanisms underlying climate model biases and inform future model development. Biases in the Greenland blocking and summer Pacific blocking frequencies are associated with biases in the storm track latitudes while biases in winter European blocking frequency are related to the North Atlantic storm track tilt and Mediterranean cyclone density. However, biases in summer European and winter Pacific blocking appear less related with cyclone track density. Furthermore, the models with smaller biases in winter European blocking frequency have smaller biases in the cyclone density in Europe, which suggests that they are different aspects of the same bias. This is not found elsewhere in the NH. The summer North Atlantic and the North Pacific mean CMIP5 track density and blocking biases might therefore have different origins.

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Forecasts of precipitation and water vapor made by the Met Office global numerical weather prediction (NWP) model are evaluated using products from satellite observations by the Special Sensor Microwave Imager/Sounder (SSMIS) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) for June–September 2011, with a focus on tropical areas (308S–308N). Consistent with previous studies, the predicted diurnal cycle of precipitation peaks too early (by ;3 h) and the amplitude is too strong over both tropical ocean and land regions. Most of the wet and dry precipitation biases, particularly those over land, can be explained by the diurnal-cycle discrepancies. An overall wet bias over the equatorial Pacific and Indian Oceans and a dry bias over the western Pacific warmpool and India are linked with similar biases in the climate model, which shares common parameterizations with the NWP version. Whereas precipitation biases develop within hours in the NWP model, underestimates in water vapor (which are assimilated by the NWP model) evolve over the first few days of the forecast. The NWP simulations are able to capture observed daily-to-intraseasonal variability in water vapor and precipitation, including fluctuations associated with tropical cyclones.

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Polar lows are maritime meso-cyclones associated with intense surface wind speeds and oceanic heat fluxes at high latitudes. The ability of the ERA-Interim (ERAI) reanalysis to represent polar lows in the North Atlantic is assessed by comparing ERAI and the ECMWF operational analysis for the period 2008-2011. First, the representation of a set of satellite observed polar lows over the Norwegian and Barents Seas in the operational analysis and ERAI is analysed. Then, the possibility of directly identifying and tracking the polar lows in the operational analysis and ERAI is explored using a tracking algorithm based on 850 hPa vorticity with objective identification criteria on cyclone dynamical intensity and atmospheric static stability. All but one of the satellite observed polar lows with a lifetime of at least 6 hours have an 850 hPa vorticity signature of a co-located mesocyclone in both the operational analysis and ERAI for most of their life cycles. However, the operational analysis has vorticity structures that better resemble the observed cloud patterns and stronger surface wind speed intensities compared to those in ERAI. By applying the objective identification criteria, about 55% of the satellite observed polar lows are identified and tracked in ERAI, while this fraction increases to about 70% in the operational analysis. Particularly in ERAI, the remaining observed polar lows are mainly not identified because they have too weak wind speed and vorticity intensity compared to the tested criteria. The implications of the tendency of ERAI to underestimate the polar low dynamical intensity for future studies of polar lows is discussed.

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Model studies do not agree on future changes in tropical cyclone (TC) activity on regional scales. We aim to shed further light on the distribution, frequency, intensity, and seasonality of TCs that society can expect at the end of the twenty-first century in the Southern hemisphere (SH). Therefore, we investigate TC changes simulated by the atmospheric model ECHAM5 with T213 (~60 km) horizontal resolution. We identify TCs in present-day (20C; 1969–1990) and future (21C; 2069–2100) time slice simulations, using a tracking algorithm based on vorticity at 850 hPa. In contrast to the Northern hemisphere (NH), where tropical storm numbers reduce by 6 %, there is a more dramatic 22 % reduction in the SH, mainly in the South Indian Ocean. While an increase of static stability in 21C may partly explain the reduction in tropical storm numbers, stabilization cannot alone explain the larger SH drop. Large-scale circulation changes associated with a weakening of the Tropical Walker Circulation are hypothesized to cause the strong decrease of cyclones in the South Indian Ocean. In contrast the decrease found over the South Pacific appears to be partly related to increased vertical wind shear, which is possibly associated with an enhanced meridional sea surface temperature gradient. We find the main difference between the hemispheres in changes of the tropical cyclones of intermediate strength with an increase in the NH and a decrease in the SH. In both hemispheres the frequency of the strongest storms increases and the frequency of the weakest storms decreases, although the increase in SH intense storms is marginal.

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Within the SPARC Data Initiative, the first comprehensive assessment of the quality of 13 water vapor products from 11 limb-viewing satellite instruments (LIMS, SAGE II, UARS-MLS, HALOE, POAM III, SMR, SAGE III, MIPAS, SCIAMACHY, ACE-FTS, and Aura-MLS) obtained within the time period 1978-2010 has been performed. Each instrument's water vapor profile measurements were compiled into monthly zonal mean time series on a common latitude-pressure grid. These time series serve as basis for the "climatological" validation approach used within the project. The evaluations include comparisons of monthly or annual zonal mean cross sections and seasonal cycles in the tropical and extratropical upper troposphere and lower stratosphere averaged over one or more years, comparisons of interannual variability, and a study of the time evolution of physical features in water vapor such as the tropical tape recorder and polar vortex dehydration. Our knowledge of the atmospheric mean state in water vapor is best in the lower and middle stratosphere of the tropics and midlatitudes, with a relative uncertainty of. 2-6% (as quantified by the standard deviation of the instruments' multiannual means). The uncertainty increases toward the polar regions (+/- 10-15%), the mesosphere (+/- 15%), and the upper troposphere/lower stratosphere below 100 hPa (+/- 30-50%), where sampling issues add uncertainty due to large gradients and high natural variability in water vapor. The minimum found in multiannual (1998-2008) mean water vapor in the tropical lower stratosphere is 3.5 ppmv (+/- 14%), with slightly larger uncertainties for monthly mean values. The frequently used HALOE water vapor data set shows consistently lower values than most other data sets throughout the atmosphere, with increasing deviations from the multi-instrument mean below 100 hPa in both the tropics and extratropics. The knowledge gained from these comparisons and regarding the quality of the individual data sets in different regions of the atmosphere will help to improve model-measurement comparisons (e.g., for diagnostics such as the tropical tape recorder or seasonal cycles), data merging activities, and studies of climate variability.

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Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.

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Observations of turbulent fluxes of momentum, heat and moisture from low-level aircraft data are presented. Fluxes are calculated using the eddy covariance technique from flight legs typically ∼40 m above the sea surface. Over 400 runs of 2 min (∼12 km) from 26 flights are evaluated. Flight legs are mainly from around the British Isles although a small number are from around Iceland and Norway. Sea-surface temperature (SST) observations from two on-board sensors (the ARIES interferometer and a Heimann radiometer) and a satellite-based analysis (OSTIA) are used to determine an improved SST estimate. Most of the observations are from moderate to strong wind speed conditions, the latter being a regime short of validation data for the bulk flux algorithms that are necessary for numerical weather prediction and climate models. Observations from both statically stable and unstable atmospheric boundary-layer conditions are presented. There is a particular focus on several flights made as part of the DIAMET (Diabatic influence on mesoscale structures in extratropical storms) project. Observed neutral exchange coefficients are in the same range as previous studies, although higher for the momentum coefficient, and are broadly consistent with the COARE 3.0 bulk flux algorithm, as well as the surface exchange schemes used in the ECMWF and Met Office models. Examining the results as a function of aircraft heading shows higher fluxes and exchange coefficients in the across-wind direction, compared to along-wind (although this comparison is limited by the relatively small number of along-wind legs). A multi-resolution spectral decomposition technique demonstrates a lengthening of spatial scales in along-wind variances in along-wind legs, implying the boundary-layer eddies are elongated in the along-wind direction. The along-wind runs may not be able to adequately capture the full range of turbulent exchange that is occurring because elongation places the largest eddies outside of the run length.

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Extreme variability of the winter- and spring-time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond five days and into the sub-seasonal range (0-30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecasts skill by 5-7% in the extratropics on sub-seasonal timescales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context.

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This study assesses the influence of the El Niño–Southern Oscillation (ENSO) on global tropical cyclone activity using a 150-yr-long integration with a high-resolution coupled atmosphere–ocean general circulation model [High-Resolution Global Environmental Model (HiGEM); with N144 resolution: ~90 km in the atmosphere and ~40 km in the ocean]. Tropical cyclone activity is compared to an atmosphere-only simulation using the atmospheric component of HiGEM (HiGAM). Observations of tropical cyclones in the International Best Track Archive for Climate Stewardship (IBTrACS) and tropical cyclones identified in the Interim ECMWF Re-Analysis (ERA-Interim) are used to validate the models. Composite anomalies of tropical cyclone activity in El Niño and La Niña years are used. HiGEM is able to capture the shift in tropical cyclone locations to ENSO in the Pacific and Indian Oceans. However, HiGEM does not capture the expected ENSO–tropical cyclone teleconnection in the North Atlantic. HiGAM shows more skill in simulating the global ENSO–tropical cyclone teleconnection; however, variability in the Pacific is overpronounced. HiGAM is able to capture the ENSO–tropical cyclone teleconnection in the North Atlantic more accurately than HiGEM. An investigation into the large-scale environmental conditions, known to influence tropical cyclone activity, is used to further understand the response of tropical cyclone activity to ENSO in the North Atlantic and western North Pacific. The vertical wind shear response over the Caribbean is not captured in HiGEM compared to HiGAM and ERA-Interim. Biases in the mean ascent at 500 hPa in HiGEM remain in HiGAM over the western North Pacific; however, a more realistic low-level vorticity in HiGAM results in a more accurate ENSO–tropical cyclone teleconnection.

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During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series for Germany are quantified based on potential losses using empirical models. Two reanalysis data sets and observations from German weather stations are considered for 30 winters. Histograms of events exceeding selected return levels (1-, 2- and 5-year) are derived. Return periods of historical storm series are estimated based on the Poisson and the negative binomial distributions. Over 4000 years of general circulation model (GCM) simulations forced with current climate conditions are analysed to provide a better assessment of historical return periods. Estimations differ between distributions, for example 40 to 65 years for the 1990 series. For such less frequent series, estimates obtained with the Poisson distribution clearly deviate from empirical data. The negative binomial distribution provides better estimates, even though a sensitivity to return level and data set is identified. The consideration of GCM data permits a strong reduction of uncertainties. The present results support the importance of considering explicitly clustering of losses for an adequate risk assessment for economical applications.