298 resultados para Asian monsoon precipitation


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In this study the relationship between the North American monsoon, the Californian sea surface temperature (SST) cold pool, the Rocky Mountains and the North Pacific subtropical anticyclone is investigated using the Hadley Centre's atmospheric climate model, HadAM3. In 1996 Hoskins hypothesized that heating in the North American monsoon might be important for the maintenance of the summertime North Pacific subtropical anticyclone, since the monsoon heating may induce descent to the north-west of the monsoon in the descending eastern flank of the subtropical anticyclone. This descent is further enhanced by radiative cooling and is associated with equatorward surface winds parallel to the western coast of North America. These equatorward winds induce oceanic upwelling of cold water and contribute to the formation of the Californian SST cold pool, which may feed back on the anticyclone by further suppressing convection and inducing descent. More recently, Rodwell and Hoskins also investigated the global summer monsoon–subtropical anticyclone relationship. They examined the role that mountains play in impeding the progress of the low-level mid-latitude westerlies, either deflecting the westerlies northwards where they ascend along the sloping mid-latitude isentropes or deflecting them southwards forcing them to descend along the isentropes. In particular, the introduction of the Rockies into a primitive-equation model adiabatically induces descent in the eastern descending flank of the North Pacific subtropical anticyclone. These hypothesized mechanisms have been investigated using HadAM3, focusing on the possible suppression of convection by the Californian SST cold pool, the response of the North Pacific subtropical anticyclone to the strength of the North American monsoon and the ‘blocking’ of the mid-latitude westerlies by the Rocky Mountains. The role of the Rockies is examined by integrating the model with modified orography for the Rocky Mountains. Changing the height of the Rockies alters the circulation in a way consistent with the mechanism outlined above. Higher Rocky mountains force the westerlies southwards, inducing descent in the eastern flank of the subtropical anticyclone as the air descends along the sloping isentropes. The relationship between the North American monsoon and the North Pacific subtropical anticyclone is investigated by suppressing the monsoon in HadAM3. The suppression of the monsoon is accomplished by increasing the surface albedo over Mexico, which induces anomalous ascent on the eastward flank of the subtropical anticyclone and anomalous polewards surface winds along the western coast of the North American continent, also providing support for the above hypothesis. The removal of the Californian SST cold pool, however, has a statistically insignificant effect on the model, suggesting that in this model the feedback of the SST cold pool on the eastern flank of the anticyclone is weak.

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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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Hourly winter weather of the Last Glacial Maximum (LGM) is simulated using the Community Climate Model version 3 (CCM3) on a globally resolved T170 (75 km) grid. Results are compared to a longer LGM climatological run with the same boundary conditions and monthly saves. Hourly-scale animations are used to enhance interpretations. The purpose of the study is to explore whether additional insights into ice age conditions can be gleaned by going beyond the standard employment of monthly average model statistics to infer ice age weather and climate. Results for both LGM runs indicate a decrease in North Atlantic and increase in North Pacific cyclogenesis. Storm trajectories react to the mechanical forcing of the Laurentide Ice Sheet, with Pacific storms tracking over middle Alaska and northern Canada, terminating in the Labrador Sea. This result is coincident with other model results in also showing a significant reduction in Greenland wintertime precipitation – a response supported by ice core evidence. Higher-temporal resolution puts in sharper focus the close tracking of Pacific storms along the west coast of North America. This response is consistent with increased poleward heat transport in the LGM climatological run and could help explain “early” glacial warming inferred in this region from proxy climate records. Additional analyses shows a large increase in central Asian surface gustiness that support observational inferences that upper-level winds associated with Asian- Pacific storms transported Asian dust to Greenland during the LGM.

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The Asian region has become a focus of attention for investors in recent years. Due to the strong economic performance of the region, the higher expected returns in the area compared with Europe and the USA and the additional diversification benefits investment in the region would offer. Nonetheless many investors have doubts about the prudence of investing in such areas. In particular it may be felt that the expected returns offered in the countries of the Asian region are not sufficient to compensate investors for the increased risks of investing in such markets. These risks can be categorised into under four headings: investment risk, currency risk, political risk, and institutional risk. This paper analyses each of these risks in turn to see if they are sufficiently large to deter real estate investment in the region in general or in a particular country.

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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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The aim of this paper is to explore effects of macroeconomic variables on house prices and also, the lead-lag relationships of real estate markets to examine house price diffusion across Asian financial centres. The analysis is based on the Global Vector Auto-Regression (GVAR) model estimated using quarterly data for six Asian financial centres (Hong Kong, Tokyo, Seoul, Singapore, Taipei and Bangkok) from 1991Q1 to 2011Q2. The empirical results indicate that the global economic conditions play significant roles in shaping house price movements across Asian financial centres. In particular, a small open economy that heavily relies on international trade such as – Singapore and Tokyo - shows positive correlations between economy’s openness and house prices, consistent with the Balassa-Samuelson hypothesis in international trade. However, region-specific conditions do play important roles as determinants of house prices, partly due to restrictive housing policies and demand-supply imbalances, as found in Singapore and Bangkok.

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CONTEXT. Rattus tanezumi is a serious crop pest within the island of Luzon, Philippines. In intensive flood-irrigated rice field ecosystems of Luzon, female R. tanezumi are known to primarily nest within the tillers of ripening rice fields and along the banks of irrigation canals. The nesting habits of R. tanezumi in complex rice–coconut cropping systems are unknown. AIMS. To identify the natal nest locations of R. tanezumi females in rice–coconut systems of the Sierra Madre Biodiversity Corridor (SMBC), Luzon, during the main breeding season to develop a management strategy that specifically targets their nesting habitat. METHODS. When rice was at the booting to ripening stage, cage-traps were placed in rice fields adjacent to coconut habitat. Thirty breeding adult R. tanezumi females were fitted with radio-collars and successfully tracked to their nest sites. KEY RESULTS. Most R. tanezumi nests (66.7%) were located in coconut groves, five nests (16.7%) were located in rice fields and five nests (16.7%) were located on the rice field edge. All nests were located above ground level and seven nests were located in coconut tree crowns. The median distance of nest sites to the nearest rice field was 22.5m. Most nest site locations had good cover of ground vegetation and understorey vegetation, but low canopy cover. Only one nest location had an understorey vegetation height of less than 20 cm. CONCLUSIONS. In the coastal lowland rice–coconut cropping systems of the SMBC, female R. tanezumi showed a preference for nesting in adjacent coconut groves. This is contrary to previous studies in intensive flood-irrigated rice ecosystems of Luzon, where the species nests mainly in the banks of irrigation canals. It is important to understand rodent breeding ecology in a specific ecosystem before implementing appropriate management strategies. IMPLICATIONS. In lowland rice–coconut cropping systems, coconut groves adjacent to rice fields should be targeted for the 20 management of R. tanezumi nest sites during the main breeding season as part of an integrated ecologically based approach to rodent pest management.

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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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Idealised convection-permitting simulations are used to quantify the impact of embedded convection on the precipitation generated by moist flow over midlatitude mountain ridges. A broad range of mountain dimensions and moist stabilities are considered to encompass a spectrum of physically plausible flows. The simulations reveal that convection only enhances orographic precipitation in cap clouds that are otherwise unable to efficiently convert cloud condensate into precipitate. For tall and wide mountains (e.g. the Washington Cascades or the southern Andes), precipitate forms efficiently through vapour deposition and collection, even in the absence of embedded convection. When embedded convection develops in such clouds, it produces competing effects (enhanced condensation in updraughts and enhanced evaporation through turbulent mixing and compensating subsidence) that cancel to yield little net change in precipitation. By contrast, convection strongly enhances precipitation over short and narrow mountains (e.g. the UK Pennines or the Oregon Coastal Range) where precipitation formation is otherwise highly inefficient. Although cancellation between increased condensation and evaporation still occurs, the enhanced precipitation formation within the convective updraughts leads to a net increase in precipitation efficiency. The simulations are physically interpreted through non-dimensional diagnostics and relevant time-scales that govern advective, microphysical, and convective processes.

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Global climate and weather models tend to produce rainfall that is too light and too regular over the tropical ocean. This is likely because of convective parametrizations, but the problem is not well understood. Here, distributions of precipitation rates are analyzed for high-resolution UK Met Office Unified Model simulations of a 10 day case study over a large tropical domain (∼20°S–20°N and 42°E–180°E). Simulations with 12 km grid length and parametrized convection have too many occurrences of light rain and too few of heavier rain when interpolated onto a 1° grid and compared with Tropical Rainfall Measuring Mission (TRMM) data. In fact, this version of the model appears to have a preferred scale of rainfall around 0.4 mm h−1 (10 mm day−1), unlike observations of tropical rainfall. On the other hand, 4 km grid length simulations with explicit convection produce distributions much more similar to TRMM observations. The apparent preferred scale at lighter rain rates seems to be a feature of the convective parametrization rather than the coarse resolution, as demonstrated by results from 12 km simulations with explicit convection and 40 km simulations with parametrized convection. In fact, coarser resolution models with explicit convection tend to have even more heavy rain than observed. Implications for models using convective parametrizations, including interactions of heating and moistening profiles with larger scales, are discussed. One important implication is that the explicit convection 4 km model has temperature and moisture tendencies that favour transitions in the convective regime. Also, the 12 km parametrized convection model produces a more stable temperature profile at its extreme high-precipitation range, which may reduce the chance of very heavy rainfall. Further study is needed to determine whether unrealistic precipitation distributions are due to some fundamental limitation of convective parametrizations or whether parametrizations can be improved, in order to better simulate these distributions.

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Oxygen isotope records of stalagmites from China and Oman reveal a weak summer monsoon event, with a double-plunging structure, that started 8.21 ± 0.02 kyr B.P. An identical but antiphased pattern is also evident in two stalagmite records from eastern Brazil, indicating that the South American Summer Monsoon was intensified during the 8.2 kyr B.P. event. These records demonstrate that the event was of global extent and synchronous within dating errors of <50 years. In comparison with recent model simulations, it is plausible that the 8.2 kyr B.P. event can be tied in changes of the Atlantic Meridional Overturning Circulation triggered by a glacial lake draining event. This, in turn, affected North Atlantic climate and latitudinal position of the Intertropical Convergence Zone, resulting in the observed low-latitude monsoonal precipitation patterns.