922 resultados para precipitation experiments


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A number of transient climate runs simulating the last 120kyr have been carried out using FAMOUS, a fast atmosphere-ocean general circulation model (AOGCM). This is the first time such experiments have been done with a full AOGCM, providing a three-dimensional simulation of both atmosphere and ocean over this period. Our simulation thus includes internally generated temporal variability over periods from days to millennia, and physical, detailed representations of important processes such as clouds and precipitation. Although the model is fast, computational restrictions mean that the rate of change of the forcings has been increased by a factor of 10, making each experiment 12kyr long. Atmospheric greenhouse gases (GHGs), northern hemisphere ice sheets and variations in solar radiation arising from changes in the Earth's orbit are treated as forcing factors, and are applied either separately or combined in different experiments. The long-term temperature changes on Antarctica match well with reconstructions derived from ice-core data, as does variability on timescales longer than 10 kyr. Last Glacial Maximum (LGM) cooling on Greenland is reasonably well simulated, although our simulations, which lack ice-sheet meltwater forcing, do not reproduce the abrupt, millennial scale climate shifts seen in northern hemisphere climate proxies or their slower southern hemisphere counterparts. The spatial pattern of sea surface cooling at the LGM matches proxy reconstructions reasonably well. There is significant anti-correlated variability in the strengths of the Atlantic Meridional Overturning Circulation (AMOC) and the Antarctic Circumpolar Current (ACC) on timescales greater than 10kyr in our experiments. We find that GHG forcing weakens the AMOC and strengthens the ACC, whilst the presence of northern hemisphere ice-sheets strengthens the AMOC and weakens the ACC. The structure of the AMOC at the LGM is found to be sensitive to the details of the ice-sheet reconstruction used. The precessional component of the orbital forcing induces ~20kyr oscillations in the AMOC and ACC, whose amplitude is mediated by changes in the eccentricity of the Earth's orbit. These forcing influences combine, to first order, in a linear fashion to produce the mean climate and ocean variability seen in the run with all forcings.

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In this paper a look is taken at how the use of implant and electrode technology can be employed to create biological brains for robots, to enable human enhancement and to diminish the effects of certain neural illnesses. In all cases the end result is to increase the range of abilities of the recipients. An indication is given of a number of areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking a biological brain directly with computer technology. The emphasis is placed on practical scientific studies that have been and are being undertaken and reported on. The area of focus is the use of electrode technology, where either a connection is made directly with the cerebral cortex and/or nervous system or where implants into the human body are involved. The paper also considers robots that have biological brains in which human neurons can be employed as the sole thinking machine for a real world robot body.

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The observed decline in summer sea ice extent since the 1970s is predicted to continue until the Arctic Ocean is seasonally ice free during the 21st Century. This will lead to a much perturbed Arctic climate with large changes in ocean surface energy flux. Svalbard, located on the present day sea ice edge, contains many low lying ice caps and glaciers and is expected to experience rapid warming over the 21st Century. The total sea level rise if all the land ice on Svalbard were to melt completely is 0.02 m. The purpose of this study is to quantify the impact of climate change on Svalbard’s surface mass balance (SMB) and to determine, in particular, what proportion of the projected changes in precipitation and SMB are a result of changes to the Arctic sea ice cover. To investigate this a regional climate model was forced with monthly mean climatologies of sea surface temperature (SST) and sea ice concentration for the periods 1961–1990 and 2061–2090 under two emission scenarios. In a novel forcing experiment, 20th Century SSTs and 21st Century sea ice were used to force one simulation to investigate the role of sea ice forcing. This experiment results in a 3.5 m water equivalent increase in Svalbard’s SMB compared to the present day. This is because over 50 % of the projected increase in winter precipitation over Svalbard under the A1B emissions scenario is due to an increase in lower atmosphere moisture content associated with evaporation from the ice free ocean. These results indicate that increases in precipitation due to sea ice decline may act to moderate mass loss from Svalbard’s glaciers due to future Arctic warming.

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Determination of the local structure of a polymer glass by scattering methods is complex due to the number of spatial and orientational correlations, both from within the polymer chain (intrachain) and between neighbouring chains (interchain), from which the scattering arises. Recently considerable advances have been made in the structural analysis of relatively simple polymers such as poly(ethylene) through the use of broad Q neutron scattering data tightly coupled to atomistic modelling procedures. This paper presents the results of an investigation into the use of these procedures for the analysis of the local structure of a-PMMA which is chemically more complex with a much greater number of intrachain structural parameters. We have utilised high quality neutron scattering data obtained using SANDALS at ISIS coupled with computer models representing both the single chain and bulk polymer system. Several different modelling approaches have been explored which encompass such techniques as Reverse Monte Carlo refinement and energy minimisation and their relative merits and successes are discussed. These different approaches highlight structural parameters which any realistic model of glassy atactic PMMA must replicate.

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Observations and numerical modelling experiments provide evidence for links between variability in the Atlantic Meridional Overturning Circulation (AMOC) and global climate patterns. Reduction in the strength of the overturning circulation is thought to have played a key role in rapid climate change in the past and may have the potential to significantly influence climate change in the future, as noted in the last two IPCC assessment reports (2001, 2007). Both IPCC reports also highlighted the significant uncertainties that exist regarding the future behaviour of the AMOC under global warming. Model results suggest that changes in the AMOC can impact surface air temperature, precipitation patterns and sea level, particularly in areas bordering the North Atlantic, thus affecting human populations. Here current understanding of past, present and future change in the AMOC and the effects of such changes on climate are reviewed. The focus is on observations of the AMOC, how the AMOC influences climate and in what way the AMOC is likely to change over the next few decades and the 21st 34 century. The potential for decadal prediction of the AMOC is also discussed. Finally, the outstanding challenges and possible future directions for AMOC research are outlined.

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The Arctic is a region particularly susceptible to rapid climate change. General circulation models (GCMs) suggest a polar amplification of any global warming signal by a factor of about 1.5 due, in part, to sea ice feedbacks. The dramatic recent decline in multi-year sea ice cover lies outside the standard deviation of the CMIP3 ensemble GCM predictions. Sea ice acts as a barrier between cold air and warmer oceans during winter, as well as inhibiting evaporation from the ocean surface water during the summer. An ice free Arctic would likely have an altered hydrological cycle with more evaporation from the ocean surface leading to changes in precipitation distribution and amount. Using the U.K. Met Office Regional Climate Model (RCM), HadRM3, the atmospheric effects of the observed and projected reduction in Arctic sea ice are investigated. The RCM is driven by the atmospheric GCM HadAM3. Both models are forced with sea surface temperature and sea ice for the period 2061-2090 from the CMIP3 HadGEM1 experiments. Here we use an RCM at 50km resolution over the Arctic and 25km over Svalbard, which captures well the present-day pattern of precipitation and provides a detailed picture of the projected changes in the behaviour of the oceanic-atmosphere moisture fluxes and how they affect precipitation. These experiments show that the projected 21stCentury sea ice decline alone causes large impacts to the surface mass balance (SMB) on Svalbard. However Greenland’s SMB is not significantly affected by sea ice decline alone, but responds with a strongly negative shift in SMB when changes to SST are incorporated into the experiments. This is the first study to characterise the impact of changes in future sea ice to Arctic terrestrial cryosphere mass balance.

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We have developed a new Bayesian approach to retrieve oceanic rain rate from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), with an emphasis on typhoon cases in the West Pacific. Retrieved rain rates are validated with measurements of rain gauges located on Japanese islands. To demonstrate improvement, retrievals are also compared with those from the TRMM/Precipitation Radar (PR), the Goddard Profiling Algorithm (GPROF), and a multi-channel linear regression statistical method (MLRS). We have found that qualitatively, all methods retrieved similar horizontal distributions in terms of locations of eyes and rain bands of typhoons. Quantitatively, our new Bayesian retrievals have the best linearity and the smallest root mean square (RMS) error against rain gauge data for 16 typhoon overpasses in 2004. The correlation coefficient and RMS of our retrievals are 0.95 and ~2 mm hr-1, respectively. In particular, at heavy rain rates, our Bayesian retrievals outperform those retrieved from GPROF and MLRS. Overall, the new Bayesian approach accurately retrieves surface rain rate for typhoon cases. Accurate rain rate estimates from this method can be assimilated in models to improve forecast and prevent potential damages in Taiwan during typhoon seasons.

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Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled(CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates. There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5 simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 %/K for simulations and 3-4 %/K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Niño Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (75% precipitation percentile), the precipitation response is ~13-15%/K for GPCP and ~5%/K for models while trends in P are 2.4%/decade for GPCP, 0.6% /decade for CMIP5 and 0.9%/decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

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Recent extreme precipitation events have caused widespread flooding to the UK. The prediction of the intensity of such events in a warmer climate is important for adaption strategies against future events. This study highlights the importance of using high-resolution models to predict these events. Using a high-resolution GCM it is shown that extreme precipitation events are predicted to become more frequent under the IPCC A1B warming scenario. It is also shown that current forecast models have difficulty in predicting the location, timing and intensity of small scale precipitation in areas with significant orography.

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An analysis of the climate of precipitation extremes as simulated by six European regional climate models (RCMs) is undertaken in order to describe/quantify future changes and to examine/interpret differences between models. Each model has adopted boundary conditions from the same ensemble of global climate model integrations for present (1961–1990) and future (2071–2100) climate under the Intergovernmental Panel on Climate Change A2 emission scenario. The main diagnostics are multiyear return values of daily precipitation totals estimated from extreme value analysis. An evaluation of the RCMs against observations in the Alpine region shows that model biases for extremes are comparable to or even smaller than those for wet day intensity and mean precipitation. In winter, precipitation extremes tend to increase north of about 45°N, while there is an insignificant change or a decrease to the south. In northern Europe the 20-year return value of future climate corresponds to the 40- to 100-year return value of present climate. There is a good agreement between the RCMs, and the simulated change is similar to a scaling of present-day extremes by the change in average events. In contrast, there are large model differences in summer when RCM formulation contributes significantly to scenario uncertainty. The model differences are well explained by differences in the precipitation frequency and intensity process, but in all models, extremes increase more or decrease less than would be expected from the scaling of present-day extremes. There is evidence for a component of the change that affects extremes specifically and is consistent between models despite the large variation in the total response.

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An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km. The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10–50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency, precipitation intensity, and quantiles of the frequency distribution. For mean precipitation, the models reproduce the characteristics of the annual cycle and the spatial distribution. The domain mean bias varies between −23% and +3% in winter and between −27% and −5% in summer. Larger errors are found for other statistics. In summer, all models underestimate precipitation intensity (by 16–42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models. Similar intermodel differences are found for other European subregions. Interestingly, the model errors are very similar between the two models with the same dynamical core (but different parameterizations) and they differ considerably between the two models with similar parameterizations (but different dynamics). Despite considerable biases, the models reproduce prominent mesoscale features of heavy precipitation, which is a promising result for their use in climate change downscaling over complex topography.

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A precipitation downscaling method is presented using precipitation from a general circulation model (GCM) as predictor. The method extends a previous method from monthly to daily temporal resolution. The simplest form of the method corrects for biases in wet-day frequency and intensity. A more sophisticated variant also takes account of flow-dependent biases in the GCM. The method is flexible and simple to implement. It is proposed here as a correction of GCM output for applications where sophisticated methods are not available, or as a benchmark for the evaluation of other downscaling methods. Applied to output from reanalyses (ECMWF, NCEP) in the region of the European Alps, the method is capable of reducing large biases in the precipitation frequency distribution, even for high quantiles. The two variants exhibit similar performances, but the ideal choice of method can depend on the GCM/reanalysis and it is recommended to test the methods in each case. Limitations of the method are found in small areas with unresolved topographic detail that influence higher-order statistics (e.g. high quantiles). When used as benchmark for three regional climate models (RCMs), the corrected reanalysis and the RCMs perform similarly in many regions, but the added value of the latter is evident for high quantiles in some small regions.

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Keith DeRose has argued that context shifting experiments should be designed in a specific way in order to accommodate what he calls a ‘truth/falsity asymmetry’. I explain and critique DeRose's reasons for proposing this modification to contextualist methodology, drawing on recent experimental studies of DeRose's bank cases as well as experimental findings about the verification of affirmative and negative statements. While DeRose's arguments for his particular modification to contextualist methodology fail, the lesson of his proposal is that there is good reason to pay close attention to several subtle aspects of the design of context shifting experiments.

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The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena—an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models. In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden–Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena

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This paper explores the sensitivity of Atmospheric General Circulation Model (AGCM) simulations to changes in the meridional distribution of sea surface temperature (SST). The simulations are for an aqua-planet, a water covered Earth with no land, orography or sea-ice and with specified zonally symmetric SST. Simulations from 14 AGCMs developed for Numerical Weather Prediction and climate applications are compared. Four experiments are performed to study the sensitivity to the meridional SST profile. These profiles range from one in which the SST gradient continues to the equator to one which is flat approaching the equator, all with the same maximum SST at the equator. The zonal mean circulation of all models shows strong sensitivity to latitudinal distribution of SST. The Hadley circulation weakens and shifts poleward as the SST profile flattens in the tropics. One question of interest is the formation of a double versus a single ITCZ. There is a large variation between models of the strength of the ITCZ and where in the SST experiment sequence they transition from a single to double ITCZ. The SST profiles are defined such that as the equatorial SST gradient flattens, the maximum gradient increases and moves poleward. This leads to a weakening of the mid-latitude jet accompanied by a poleward shift of the jet core. Also considered are tropical wave activity and tropical precipitation frequency distributions. The details of each vary greatly between models, both with a given SST and in the response to the change in SST. One additional experiment is included to examine the sensitivity to an off-equatorial SST maximum. The upward branch of the Hadley circulation follows the SST maximum off the equator. The models that form a single precipitation maximum when the maximum SST is on the equator shift the precipitation maximum off equator and keep it centered over the SST maximum. Those that form a double with minimum on the equatorial maximum SST shift the double structure off the equator, keeping the minimum over the maximum SST. In both situations only modest changes appear in the shifted profile of zonal average precipitation. When the upward branch of the Hadley circulation moves into the hemisphere with SST maximum, the zonal average zonal, meridional and vertical winds all indicate that the Hadley cell in the other hemisphere dominates.