901 resultados para global nonhydrostatic model


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The response of the six major summer monsoon systems (the North American monsoon, the northern Africa monsoon, the Asia monsoon, the northern Australasian monsoon, the South America monsoon and the southern Africa monsoon) to mid-Holocene orbital forcing has been investigated using a coupled ocean–atmosphere general circulation model (FOAM), with the focus on the distinct roles of the direct insolation forcing and oceanic feedback. The simulation result is also found to compare well with the NCAR CSM. The direct effects of the change in insolation produce an enhancement of the Northern Hemisphere monsoons and a reduction of the Southern Hemisphere monsoons. Ocean feedbacks produce a further enhancement of the northern Africa monsoon and the North American monsoon. However, ocean feedbacks appear to weaken the Asia monsoon, although the overall effect (direct insolation forcing plus ocean feedback) remains a strengthened monsoon. The impact of ocean feedbacks on the South American and southern African monsoons is relatively small, and therefore these regions, especially the South America, experienced a reduced monsoon regime compared to present. However, there is a strong ocean feedback on the northern Australian monsoon that negates the direct effects of orbital changes and results in a strengthening of austral summer monsoon precipitation in this region. A new synthesis is made for mid-Holocene paleoenvironmental records and is compared with the model simulations. Overall, model simulations produce changes in regional climates that are generally consistent with paleoenvironmental observations.

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The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.

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This note describes a simple procedure for removing unphysical temporal discontinuities in ERA-Interim upper stratospheric global mean temperatures in March 1985 and August 1998 that have arisen due to changes in satellite radiance data used in the assimilation. The derived temperature adjustments (offsets) are suitable for use in stratosphere-resolving chemistry-climate models that are nudged (relaxed) to ERA-Interim winds and temperatures. Simulations using a nudged version of the Canadian Middle Atmosphere Model (CMAM) show that the inclusion of the temperature adjustments produces temperature time series that are devoid of the large jumps in 1985 and 1998. Due to its strong temperature dependence, the simulated upper stratospheric ozone is also shown to vary smoothly in time, unlike in a nudged simulation without the adjustments where abrupt changes in ozone occur at the times of the temperature jumps. While the adjustments to the ERA-Interim temperatures remove significant artefacts in the nudged CMAM simulation, spurious transient effects that arise due to water vapour and persist for about 5 yr after the 1979 switch to ERA-Interim data are identified, underlining the need for caution when analysing trends in runs nudged to reanalyses.

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Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.

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Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.

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Global syntheses of palaeoenvironmental data are required to test climate models under conditions different from the present. Data sets for this purpose contain data from spatially extensive networks of sites. The data are either directly comparable to model output or readily interpretable in terms of modelled climate variables. Data sets must contain sufficient documentation to distinguish between raw (primary) and interpreted (secondary, tertiary) data, to evaluate the assumptions involved in interpretation of the data, to exercise quality control, and to select data appropriate for specific goals. Four data bases for the Late Quaternary, documenting changes in lake levels since 30 kyr BP (the Global Lake Status Data Base), vegetation distribution at 18 kyr and 6 kyr BP (BIOME 6000), aeolian accumulation rates during the last glacial-interglacial cycle (DIRTMAP), and tropical terrestrial climates at the Last Glacial Maximum (the LGM Tropical Terrestrial Data Synthesis) are summarised. Each has been used to evaluate simulations of Last Glacial Maximum (LGM: 21 calendar kyr BP) and/or mid-Holocene (6 cal. kyr BP) environments. Comparisons have demonstrated that changes in radiative forcing and orography due to orbital and ice-sheet variations explain the first-order, broad-scale (in space and time) features of global climate change since the LGM. However, atmospheric models forced by 6 cal. kyr BP orbital changes with unchanged surface conditions fail to capture quantitative aspects of the observed climate, including the greatly increased magnitude and northward shift of the African monsoon during the early to mid-Holocene. Similarly, comparisons with palaeoenvironmental datasets show that atmospheric models have underestimated the magnitude of cooling and drying of much of the land surface at the LGM. The inclusion of feedbacks due to changes in ocean- and land-surface conditions at both times, and atmospheric dust loading at the LGM, appears to be required in order to produce a better simulation of these past climates. The development of Earth system models incorporating the dynamic interactions among ocean, atmosphere, and vegetation is therefore mandated by Quaternary science results as well as climatological principles. For greatest scientific benefit, this development must be paralleled by continued advances in palaeodata analysis and synthesis, which in turn will help to define questions that call for new focused data collection efforts.

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Mineral dust aerosols in the atmosphere have the potential to affect the global climate by influencing the radiative balance of the atmosphere and the supply of micronutrients to the ocean. Ice and marine sediment cores indicate that dust deposition from the atmosphere was at some locations 2–20 times greater during glacial periods, raising the possibility that mineral aerosols might have contributed to climate change on glacial-interglacial time scales. To address this question, we have used linked terrestrial biosphere, dust source, and atmospheric transport models to simulate the dust cycle in the atmosphere for current and last glacial maximum (LGM) climates. We obtain a 2.5-fold higher dust loading in the entire atmosphere and a twenty-fold higher loading in high latitudes, in LGM relative to present. Comparisons to a compilation of atmospheric dust deposition flux estimates for LGM and present in marine sediment and ice cores show that the simulated flux ratios are broadly in agreement with observations; differences suggest where further improvements in the simple dust model could be made. The simulated increase in high-latitude dustiness depends on the expansion of unvegetated areas, especially in the high latitudes and in central Asia, caused by a combination of increased aridity and low atmospheric [CO2]. The existence of these dust source areas at the LGM is supported by pollen data and loess distribution in the northern continents. These results point to a role for vegetation feedbacks, including climate effects and physiological effects of low [CO2], in modulating the atmospheric distribution of dust.

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The response of ten atmospheric general circulation models to orbital forcing at 6 kyr BP has been investigated using the BIOME model, which predicts equilibrium vegetation distribution, as a diagnostic. Several common features emerge: (a) reduced tropical rain forest as a consequence of increased aridity in the equatorial zone, (b) expansion of moisture-demanding vegetation in the Old World subtropics as a consequence of the expansion of the Afro–Asian monsoon, (c) an increase in warm grass/shrub in the Northern Hemisphere continental interiors in response to warming and enhanced aridity, and (d) a northward shift in the tundra–forest boundary in response to a warmer growing season at high northern latitudes. These broadscale features are consistent from model to model, but there are differences in their expression at a regional scale. Vegetation changes associated with monsoon enhancement and high-latitude summer warming are consistent with palaeoenvironmental observations, but the simulated shifts in vegetation belts are too small in both cases. Vegetation changes due to warmer and more arid conditions in the midcontinents of the Northern Hemisphere are consistent with palaeoenvironmental data from North America, but data from Eurasia suggests conditions were wetter at 6 kyr BP than today. The models show quantitatively similar vegetation changes in the intertropical zone, and in the northern and southern extratropics. The small differences among models in the magnitude of the global vegetation response are not related to differences in global or zonal climate averages, but reflect differences in simulated regional features. Regional-scale analyses will therefore be necessary to identify the underlying causes of such differences among models.

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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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The ability of the HiGEM climate model to represent high-impact, regional, precipitation events is investigated in two ways. The first focusses on a case study of extreme regional accumulation of precipitation during the passage of a summer extra-tropical cyclone across southern England on 20 July 2007 that resulted in a national flooding emergency. The climate model is compared with a global Numerical Weather Prediction (NWP) model and higher resolution, nested limited area models. While the climate model does not simulate the timing and location of the cyclone and associated precipitation as accurately as the NWP simulations, the total accumulated precipitation in all models is similar to the rain gauge estimate across England and Wales. The regional accumulation over the event is insensitive to horizontal resolution for grid spacings ranging from 90km to 4km. Secondly, the free-running climate model reproduces the statistical distribution of daily precipitation accumulations observed in the England-Wales precipitation record. The model distribution diverges increasingly from the record for longer accumulation periods with a consistent under-representation of more intense multi-day accumulations. This may indicate a lack of low-frequency variability associated with weather regime persistence. Despite this, the overall seasonal and annual precipitation totals from the model are still comparable to those from ERA-Interim.

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Combining satellite data, atmospheric reanalyses and climate model simulations, variability in the net downward radiative flux imbalance at the top of Earth's atmosphere (N) is reconstructed and linked to recent climate change. Over the 1985-1999 period mean N (0.34 ± 0.67 Wm–2) is lower than for the 2000-2012 period (0.62 ± 0.43 Wm–2, uncertainties at 90% confidence level) despite the slower rate of surface temperature rise since 2000. While the precise magnitude of N remains uncertain, the reconstruction captures interannual variability which is dominated by the eruption of Mt. Pinatubo in 1991 and the El Niño Southern Oscillation. Monthly deseasonalized interannual variability in N generated by an ensemble of 9 climate model simulations using prescribed sea surface temperature and radiative forcings and from the satellite-based reconstruction is significantly correlated (r ∼ 0.6) over the 1985-2012 period.

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Recent laboratory measurements show that absorption by the water vapour continuum in near-infrared windows may be about an order of magnitude higher than assumed in many radiation codes. The radiative impact of the continuum at visible and near-infrared wavelengths is examined for the present day and for a possible future warmer climate (with a global-mean total column water increase of 33%). The calculations use a continuum model frequently used in climate models (‘CKD’) and a continuum model where absorption is enhanced at wavelengths greater than 1 µm based on recent measurements (‘CAVIAR’). The continuum predominantly changes the partitioning between solar radiation absorbed by the surface and the atmosphere; changes in top-of-atmosphere net irradiances are smaller. The global-mean clear-sky atmospheric absorption is enhanced by 1.5 W m−2 (about 2%) and 2.8 W m−2 (about 3.5%) for CKD and CAVIAR respectively, relative to a hypothetical no-continuum case, with all-sky enhancements about 80% of these values. The continuum is, in relative terms, more important for radiation budget changes between the present day and a possible future climate. Relative to the no-continuum case, the increase in global-mean clear-sky absorption is 8% higher using CKD and almost 20% higher using CAVIAR; all-sky enhancements are about half these values. The effect of the continuum is estimated for the solar component of the water vapour feedback, the reduction in downward surface irradiance and precipitation change in a warmer world. For CKD and CAVIAR respectively, and relative to the no-continuum case, the solar component of the water vapour feedback is enhanced by about 4 and 9%, the change in clear-sky downward surface irradiance is 7 and 18% more negative, and the global-mean precipitation response decreases by 1 and 4%. There is a continued need for improved continuum measurements, especially at atmospheric temperatures and at wavelengths below 2 µm.

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The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/