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Journal articles on the topic "Meteorology, climatic change, Australia, temperature"
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Hudson, Debra, Oscar Alves, Harry H. Hendon, Eun-Pa Lim, Guoqiang Liu, Jing-Jia Luo, Craig MacLachlan, et al. "ACCESS-S1 The new Bureau of Meteorology multi-week to seasonal prediction system." Journal of Southern Hemisphere Earth Systems Science 67, no. 3 (2017): 132. http://dx.doi.org/10.1071/es17009.
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ACCESS-S1 will be the next version of the Australian Bureau of Meteorology's seasonal prediction system, due to become operational in early 2018. The multiweek and seasonal performance of ACCESS-S1 has been evaluated based on a 23-year hindcast set and compared to the current operational system, POAMA. The system has considerable enhancements compared to POAMA, including higher vertical and horizontal resolution of the component models and state-ofthe-art physics parameterisation schemes. ACCESS-S1 is based on the UK Met Office GloSea5-GC2 seasonal prediction system, but has enhancements to the ensemble generation strategy to make it appropriate for multi-week forecasting, and a larger ensemble size.ACCESS-S1 has markedly reduced biases in the mean state of the climate, both globally and over Australia, compared to POAMA. ACCESS-S1 also better predicts the early stages of the development of the El Niño Southern Oscillation (through the predictability barrier) and the Indian Ocean Dipole, as well as multi-week variations of the Southern Annular Mode and the Madden-Julian Oscillation — all important drivers of Australian climate variability. There is an overall improvement in the skill of the forecasts of rainfall, maximum temperature (Tmax) and minimum temperature (Tmin) over Australia on multi-week timescales compared to POAMA. On seasonal timescales the differences between the two systems are generally less marked. ACCESS-S1 has improved seasonal forecasts over Australia for the austral spring season compared to POAMA, with particularly good forecast reliability for rainfall and Tmax. However, forecasts of seasonal mean Tmax are noticeably less skilful over eastern Australia for forecasts of late autumn and winter compared to POAMA.The study has identified scope for improvement of ACCESS-S in the future, particularly 1) reducing rainfall errors in the Indian Ocean and Maritime Continent regions, and 2) initialising the land surface with realistic soil moisture rather than climatology. The latter impacts negatively on the skill of the temperature forecasts over eastern Australia and is being addressed in the next version of the system, ACCESS-S2.
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Hudson, Debra, Oscar Alves, Harry H. Hendon, Eun-Pa Lim, Guoqiang Liu, Jing-Jia Luo, Craig MacLachlan, et al. "Corrigendum to: ACCESS-S1: The new Bureau of Meteorology multi-week to seasonal prediction system." Journal of Southern Hemisphere Earth Systems Science 70, no. 1 (2020): 393. http://dx.doi.org/10.1071/es17009_co.
Full textAbstract:
ACCESS-S1 will be the next version of the Australian Bureau of Meteorology's seasonal prediction system, due to become operational in early 2018. The multiweek and seasonal performance of ACCESS-S1 has been evaluated based on a 23-year hindcast set and compared to the current operational system, POAMA. The system has considerable enhancements compared to POAMA, including higher vertical and horizontal resolution of the component models and state-ofthe-art physics parameterisation schemes. ACCESS-S1 is based on the UK Met Office GloSea5-GC2 seasonal prediction system, but has enhancements to the ensemble generation strategy to make it appropriate for multi-week forecasting, and a larger ensemble size.ACCESS-S1 has markedly reduced biases in the mean state of the climate, both globally and over Australia, compared to POAMA. ACCESS-S1 also better predicts the early stages of the development of the El Niño Southern Oscillation (through the predictability barrier) and the Indian Ocean Dipole, as well as multi-week variations of the Southern Annular Mode and the Madden-Julian Oscillation — all important drivers of Australian climate variability. There is an overall improvement in the skill of the forecasts of rainfall, maximum temperature (Tmax) and minimum temperature (Tmin) over Australia on multi-week timescales compared to POAMA. On seasonal timescales the differences between the two systems are generally less marked. ACCESS-S1 has improved seasonal forecasts over Australia for the austral spring season compared to POAMA, with particularly good forecast reliability for rainfall and Tmax. However, forecasts of seasonal mean Tmax are noticeably less skilful over eastern Australia for forecasts of late autumn and winter compared to POAMA.The study has identified scope for improvement of ACCESS-S in the future, particularly 1) reducing rainfall errors in the Indian Ocean and Maritime Continent regions, and 2) initialising the land surface with realistic soil moisture rather than climatology. The latter impacts negatively on the skill of the temperature forecasts over eastern Australia and is being addressed in the next version of the system, ACCESS-S2.
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Bettio, Lynette, John R. Nairn, Steven C. McGibbony, Pandora Hope, Andrew Tupper, and Robert J. B. Fawcett. "A heatwave forecast service for Australia." Proceedings of the Royal Society of Victoria 131, no. 1 (2019): 53. http://dx.doi.org/10.1071/rs19006.
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The Australian Bureau of Meteorology monitors, researches, predicts and communicates Australia’s weather and climate. Australia’s mean temperature has risen by over 1°C since 1910, leading to an increase in the frequency of extreme heat events. Extreme heat can profoundly impact human health, infrastructure and the environment. Research conducted at the Bureau and elsewhere shows that climate change is impacting the intensity and frequency of extreme heat events. One way that the Bureau has responded to this challenge is by providing a forecast service specifically targeted at identifying heatwaves. The heatwave service identifies areas expected to be impacted by three or more consecutive days of unusually high maximum and minimum temperatures on a national map. The service has been developed with clear impact-based categories of heatwave severity. This heatwave service is now available operationally on the Bureau’s website during the heatwave season (nominally November to March) and is proving a valuable tool for engaging the community, including emergency services, with forecasts and warnings of extreme heat.
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Hartigan, Joshua, Shev MacNamara, and Lance M. Leslie. "Comparing precipitation and temperature trends between inland and coastal locations." ANZIAM Journal 60 (July 17, 2019): C109—C126. http://dx.doi.org/10.21914/anziamj.v60i0.13967.
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Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature.
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Ly, Pham Thi, and Hoang Luu Thu Thuy. "Spatial distribution of hot days in north central region, Vietnam in the period of 1980-2013." VIETNAM JOURNAL OF EARTH SCIENCES 41, no. 1 (January 8, 2019): 36–45. http://dx.doi.org/10.15625/0866-7187/41/1/13544.
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Based on the data of daily maximum temperature in 26 meteorological stations in the North Center Region, Vietnam over the period of 1980 to 2013, the authors conducted the research on the spatial distribution of the number of hot days. The initial result shows that in general, in the north of the study area, the large number of hot days occurred in the plain, and tended to decrease westward and eastward. In the south, this number tends to increase from the west to the east. Especially, the largest number occurred in two areas: The Ma and Ca River's valleys (Thanh Hoa and Nghe An provinces) and the coastal areas (Thua Thien Hue province), creating two heat centers in Tuong Duong district, Nghe An province and Nam Dong district, Thua Thien Hue province.ReferencesAdina-Eliza Croitoru, Adrian Piticar, Antoniu-Flavius Ciupertea, Cristina FlorinaRosca, 2016 Changes in heat wave indices in Romania over the period 1961-2015. Global and Plantary Change 146. Journal homepage: www. Elsevier.com/locate/gloplacha.Chu Thi Thu Huong et al., 2010. Variations and trends in hot event in Vietnam from 1961-2007, VNU Journal of Science and Technology, 26(3S).Climate Council, 2014a. Angry Summer 2013/2014. Accessed at http://www.climatecouncil.org.au/ angry-summer.Climate Council, 2014b. Angry Summer 2013/2014. Accessed at http://www.climatecouncil.org.au/ angry-summer.CSIRO and BoM, 2012. State of the Climate 2012.CSIRO and Bureau of Meteorology, Melbourne.Accessed at http://www.csiro.au/Outcomes/ Climate/Understanding/State-of-the-Climate-2012.aspx.D'Ippoliti D., Michelozzi P., Marino C., De'Donato F., Menne B., Katsouyanni K., Kirchmayer U., Analitis A., Medina-Ramon M., Paldy A., Atkinson R., Kovats S., Bisanti L., Schneider A., Lefranc A., Iñiguez C., Perucci C., 2010. The impact of heat waves on mortality in 9 European cities: results from the EuroHEAT project. Environ. Health 9, 37. http://dx.doi.org/10.1186/1476-069X-9-37.Gerald A. Meehl, 1992. Effect of tropical topography on global climate, Ann. Rev. Earth Planet. Sci., 20, 85-112.Hayhoe K., Cayan D., Field C.B., Frumhoff P.C., Maurer E.P., Miller N.L., Moser S.C., Schneider S.H., Cahill K.N., Cleland E.E., Dale L., Drapek R., Hanemann R.M., lkstein L.S., Lenihan J., Lunch C.K., Neilson R.P., Sheridan S.C., Verville J.H., 2004. Emissions pathways, climate change, and impacts on California. PNAS, 101(34), 12422-12427.Ho Thi Minh Ha, Phan Van Tan, 2009. Trends and variations of extreme temperature in Vietnam in the period from 1961 to 2007, VNU Journal of Science and Technology, 25(3S).IPCC, 2007: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri R.K and Reisinger A. (eds.)]. IPCC, Geneva, Switzerland, 104p.IPCC, 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151p.Liu G., Zhang L., He B., Jin X., Zhang Q., Razafindrabe B., You H., 2015. Temporal changes in extreme high temperature, heat waves and relevant disasters in Nanjing metropolitan region, China. Nat. Hazards, 76, 1415–1430. http://dx.doi.org/10.1007/s11069-014-1556-y.Manton M.J et al., 2001. Trends in extreme daily temperature in Southeast Asia Rainfall ad and the South Pacific, J. Climatol. 21.Nairn J.R., Fawcett R.J.B., 2015. Int. J. Environ. Res. Public Health 12, 227–253. http://dx.doi.org/10.3390/ijerph120100227.Nguyen Duc Ngu, 2009. Climate Change Challenges to development, Journal of Economy and Environment, No. 1.Perkins S.E., Alexander L.V., 2013. On the measurement of heat waves. J. Clim. 26, 4500–4517. http://dx.doi.org/10.1175/JCLI-D-12-00383.1.Peterson T.C., Heim Jr. R.R., Hirsch R., Kaiser D.P., Brooks H., Diffenbaugh N.S., Dole R.M., Giovannettone J.P., Guirguis K., Karl T.R., Katz R.W., Kunkel K., Lettenmaier D., McCabe G.J., Paciorek C.J., Ryberg K.R., Schubert S., Silva V.B.S., Stewart B.C., Vecchia A.V., Villarini G., Vose R.S., Walsh J., Wehner M., Wolock D., Wolter K., Woodhouse C.A., Wuebbles D., 2013. Monitoring and understanding changes in heat waves, cold waves, floods, and droughts in the United States: state of knowledge. Bull. Amer. Meteor. Soc., 94, 821–834.Pham Thi Ly, Hoang Luu Thu Thuy, 2015. Variation of heat waves in the North Central Region over the period of 1980-2013, Journal of natural resources and environment, 9, 81-89.Phan Van Tan et al., 2010. Study impact of global climate change on extreme weather phenomena and factors in Vietnam, prediction and adaptation strategies. Project final report, KC 08.29/06-10, Hanoi University of Science.Spinoni J., Lakatos M., Szentimrey T., Bihari Z., Szalai S., Vogt J., Antofie T., 2015. Heat and cold waves trends in Carpathian Region from 1961 to 2010. Int. J. Climatol, 35, 4197–4209. http://dx.doi.org/10.1002/joc.4279.Toreti A., Desiato F., 2008.Temperature trends over Italy from 1961 to 2004, Theor. Appl. Climatol 91.Tran Cong Minh, 2007. Principle of meteorology and climate, Book, Public House of Hanoi National University.Tran Quang Duc, Trinh Lan Phuong, 2013. Changes of Hot day and Fohn Activities at Ha Tinh- Central Vietnam, VNU Journal of Science, Science and Technology, 29(2S).Trewin B., Smalley R., 2013.Changes in extreme temperature in Australia, 1910 to 2011. In: 19th AMOS National Conference, Melbourne, 11-13.Unal Y.S., Tan E., Mentes S.S., 2013. Summer heat waves over western Turkey between 1965 and 2006.Theor. Appl. Climatol, 112, 339–350. http://dx.doi.org/10.1007/s00704-012-0704-0.Will Steffen, 2015. Quantifying the impact of climate change on extreme heat in Australia. Published by the Climate Council of Australia Limited. ISBN: 978-0-9942453-1-1 (print) 978-0-9942453-0-4 (web).
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Shi, Li, Harry H. Hendon, Oscar Alves, Jing-Jia Luo, Magdalena Balmaseda, and David Anderson. "How Predictable is the Indian Ocean Dipole?" Monthly Weather Review 140, no. 12 (December 1, 2012): 3867–84. http://dx.doi.org/10.1175/mwr-d-12-00001.1.
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Abstract In light of the growing recognition of the role of surface temperature variations in the Indian Ocean for driving global climate variability, the predictive skill of the sea surface temperature (SST) anomalies associated with the Indian Ocean dipole (IOD) is assessed using ensemble seasonal forecasts from a selection of contemporary coupled climate models that are routinely used to make seasonal climate predictions. The authors assess predictions from successive versions of the Australian Bureau of Meteorology Predictive Ocean–Atmosphere Model for Australia (POAMA 15b and 24), successive versions of the NCEP Climate Forecast System (CFSv1 and CFSv2), the ECMWF seasonal forecast System 3 (ECSys3), and the Frontier Research Centre for Global Change system (SINTEX-F) using seasonal hindcasts initialized each month from January 1982 to December 2006. The lead time for skillful prediction of SST in the western Indian Ocean is found to be about 5–6 months while in the eastern Indian Ocean it is only 3–4 months when all start months are considered. For the IOD events, which have maximum amplitude in the September–November (SON) season, skillful prediction is also limited to a lead time of about one season, although skillful prediction of large IOD events can be longer than this, perhaps up to about two seasons. However, the tendency for the models to overpredict the occurrence of large events limits the confidence of the predictions of these large events. Some common model errors, including a poor representation of the relationship between El Niño and the IOD, are identified indicating that the upper limit of predictive skill of the IOD has not been achieved.
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Griesser, A. G., and C. M. Spillman. "Assessing the Skill and Value of Seasonal Thermal Stress Forecasts for Coral Bleaching Risk in the Western Pacific." Journal of Applied Meteorology and Climatology 55, no. 7 (July 2016): 1565–78. http://dx.doi.org/10.1175/jamc-d-15-0109.1.
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AbstractOver the last 30 years, coral reefs around the world have been under considerable stress because of increasing anthropogenic pressures, overfishing, pollution, and climate change. A primary stress factor is anomalously warm water events, which can cause mass coral bleaching and widespread reef damage. Forecasts of sea surface temperature (SST) and the associated risk of coral bleaching can assist managers, researchers, and other stakeholders in monitoring and managing coral reef resources. At the Australian Bureau of Meteorology, monthly forecasts of SST and thermal stress metrics have been developed that are based on a dynamical seasonal prediction system known as the Predictive Ocean Atmosphere Model for Australia (POAMA). To support the effective use of these forecasts in risk-based decision-making frameworks in the western and central tropical Pacific Ocean, the skill of these forecast tools in this region was assessed using several categorical forecast skill scores. It was found that the model provides SST forecasts with statistically significant skill up to 8 months in advance (correlation coefficient > 0.4; p = 0.05) across the region. The highest skill (r > 0.9) was achieved over the central equatorial Pacific Ocean, likely as a result of this region’s strong relationship with the El Niño–Southern Oscillation (ENSO). Potential forecast value was assessed using a simplified cost–loss ratio decision model, which indicated that POAMA’s seasonal hot-spot thermal stress forecasts can provide valuable information to reef management and policy makers in the western Pacific region.
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Zhang, Lifu, Na Qiao, Changping Huang, and Siheng Wang. "Monitoring Drought Effects on Vegetation Productivity Using Satellite Solar-Induced Chlorophyll Fluorescence." Remote Sensing 11, no. 4 (February 13, 2019): 378. http://dx.doi.org/10.3390/rs11040378.
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Around the world, the increasing drought, which is exacerbated by climate change, has significant impacts on vegetation carbon assimilation. Identifying how short-term climate anomalies influence vegetation productivity in a timely and accurate manner at the satellite scale is crucial to monitoring drought. Satellite solar-induced chlorophyll fluorescence (SIF) has recently been reported as a direct proxy of actual vegetation photosynthesis and has more advantages than traditional vegetation indices (e.g., the Normalized Difference Vegetation Index, NDVI and the Enhanced Vegetation Index, EVI) in monitoring vegetation vitality. This study aims to evaluate the feasibility of SIF in interpreting drought effects on vegetation productivity in Victoria, Australia, where heat stress and drought are often reported. Drought-induced variations in SIF and absorbed photosynthetically active radiation (APAR) estimations based on NDVI and EVI were investigated and validated against results indicated by gross primary production (GPP). We first compared drought responses of GPP and vegetation proxies (SIF and APAR) during the 2009 drought event, considering potential biome-dependency. Results showed that SIF exhibited more consistent declines with GPP losses induced by drought than did APAR estimations during the 2009 drought period in space and time, where APAR had obvious lagged responses compared with SIF, especially in evergreen broadleaf forest land. We then estimated the sensitivities of the aforementioned variables to meteorology anomalies using the ARx model, where memory effects were considered, and compared the correlations of GPP anomaly with the anomalies of vegetation proxies during a relatively long period (2007–2013). Compared with APAR, GPP and SIF are more sensitive to temperature anomalies for the general Victoria region. For crop land, GPP and vegetation proxies showed similar sensitivities to temperature and water availability. For evergreen broadleaf forest land, SIF anomaly was explained better by meteorology anomalies than APAR anomalies. GPP anomaly showed a stronger linear relationship with SIF anomaly than with APAR anomalies, especially for evergreen broadleaf forest land. We showed that SIF might be a promising tool for effectively evaluating short-term drought impacts on vegetation productivity, especially in drought-vulnerable areas, such as Victoria.
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Verbeke, T., J. Lathière, S. Szopa, and N. de Noblet-Ducoudré. "Impact of future land-cover changes on HNO<sub>3</sub> and O<sub>3</sub> surface dry deposition." Atmospheric Chemistry and Physics 15, no. 23 (December 9, 2015): 13555–68. http://dx.doi.org/10.5194/acp-15-13555-2015.
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Abstract. Dry deposition is a key component of surface–atmosphere exchange of compounds, acting as a sink for several chemical species. Meteorological factors, chemical properties of the trace gas considered and land surface properties are strong drivers of dry deposition efficiency and variability. Under both climatic and anthropogenic pressure, the vegetation distribution over the Earth has been changing a lot over the past centuries and could be significantly altered in the future. In this study, we perform a modeling investigation of the potential impact of land-cover changes between the present day (2006) and the future (2050) on dry deposition velocities at the surface, with special interest for ozone (O3) and nitric acid (HNO3), two compounds which are characterized by very different physicochemical properties. The 3-D chemistry-transport model LMDz-INCA is used, considering changes in vegetation distribution based on the three future projections, RCPs 2.6, 4.5 and 8.5, and present-day (2007) meteorology. The 2050 RCP 8.5 vegetation distribution leads to a rise of up to 7 % (+0.02 cm s−1) in the surface deposition velocity calculated for ozone (Vd,O3) and a decrease of −0.06 cm s−1 in the surface deposition velocity calculated for nitric acid (Vd,HNO3) relative to the present-day values in tropical Africa and up to +18 and −15 %, respectively, in Australia. When taking into account the RCP 4.5 scenario, which shows dramatic land-cover change in Eurasia, Vd,HNO3 increases by up to 20 % (annual-mean value) and reduces Vd,O3 by the same magnitude in this region. When analyzing the impact of surface dry deposition change on atmospheric chemical composition, our model calculates that the effect is lower than 1 ppb on annual-mean surface ozone concentration for both the RCP 8.5 and RCP 2.6 scenarios. The impact on HNO3 surface concentrations is more disparate between the two scenarios regarding the spatial repartition of effects. In the case of the RCP 4.5 scenario, a significant increase of the surface O3 concentration reaching locally by up to 5 ppb (+5 %) is calculated on average during the June–August period. This scenario also induces an increase of HNO3 deposited flux exceeding locally 10 % for monthly values. Comparing the impact of land-cover change to the impact of climate change, considering a 0.93 °C increase of global temperature, on dry deposition velocities, we estimate that the strongest increase over lands occurs in the Northern Hemisphere during winter, especially in Eurasia, by +50 % (+0.07 cm s−1) for Vd,O3 and +100 % (+0.9 cm s−1) for Vd,HNO3. However, different regions are affected by both changes, with climate change impact on deposition characterized by a latitudinal gradient, while the land-cover change impact is much more heterogeneous depending on vegetation distribution modification described in the future RCP scenarios. The impact of long-term land-cover changes on dry deposition is shown to be significant and to differ strongly from one scenario to another. It should therefore be considered in biosphere–atmospheric chemistry interaction studies in order to have a fully consistent picture.
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Broich, M., and M. G. Tulbure. "RESPONSE OF RIPARIAN VEGETATION IN AUSTRALIA"S LARGEST RIVER BASIN TO INTER AND INTRA-ANNUAL CLIMATE VARIABILITY AND FLOODING AS QUANTIFIED WITH LANDSAT AND MODIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 577–78. http://dx.doi.org/10.5194/isprs-archives-xli-b8-577-2016.
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Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M km<sup>2</sup>, as a case study. The MDB is the country’s primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999–2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. <br><br> We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. <br><br> Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a ‘boom’ and ‘bust’ cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. <br><br> Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the Mekong River Basin in Southeast Asia.
Dissertations / Theses on the topic "Meteorology, climatic change, Australia, temperature"
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Torok, Simon James. "The development of a high quality historical temperature data base for Australia." 1996. http://repository.unimelb.edu.au/10187/2407.
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A high quality, historical surface air temperature data set is essential for the reliable investigation of climate change and variability. In this study, such a data set has been prepared for Australia by adjusting raw mean annual temperature data for inhomogeneities associated with station relocations, changes in exposure, and other problems. Temperature records from long-term stations were collaborated from the set of all raw data held by the Australian Bureau of Meteorology. These long-term records were extended by combining stations and manually entering previously unused archived temperature measurements. An objective procedure was developed to determine the necessary adjustments, in conjunction with complementary statistical methods and station history documentation. The objective procedure involved creating a reference time series for each long-term station, from the median values at surrounding, well-correlated stations. Time series of annual mean maximum and mean minimum temperatures have been produced for 224 stations, and the adjusted dataset has been made available to the research community. The adjusted data are likely to be more representative of real climatic variations than raw data due to the removal of discontinuities. The adjusted data set has been compared with previously used temperature data sets, and data sets of other parameters. The adjusted data set provides adequate spatial coverage of Australia back to 1910. Additional adjusted data are available prior to this date at many stations. Trends in annual mean maximum, minimum, the mean of the maximum and minimum, and the range between the maximum and minimum, have been calculated at each site. Maximum and minimum temperatures have increased since about 1950, with minimum temperatures increasing faster than maximum temperatures.
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Pattanayak, Sonali. "A Hydroclimatological Change Detection and Attribution Study over India using CMIP5 Models." Thesis, 2015. http://etd.iisc.ernet.in/handle/2005/2761.
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As a result of increase in global average surface temperature, abnormalities in different hydroclimatic components such as evapotranspiration, stream flow and precipitation have been experienced. So investigation has to be carried out to assess the hidden abnormality subsisting in the hydroclimatological time series in the form of trend. This thesis broadly consists of following four parts. The first part comprises of a detailed review of various trend detection approaches. Approaches incorporating the effect of serial correlation for trend detection and interesting developments concerning various non parametric approaches are focused explicitly. Recent trends in annual, monthly, and seasonl (winter, pre-monsoon, monsoon and post-monsoon) Tmax and Tmin have been analyzed considering three time slots viz. 1901-2003, 1948-2003 and 1970-2003. For this purpose, time series of Tmax and Tmin of India as a whole and for seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) were originally considered. During the last three decades significant upward trend in Tmin is found to be present in all regions considered either at annual or seasonal level. Sequential Mann Kendall test revealed that most of the significant upward trends both in Tmax and Tmin began after 1970. The second part discusses about numerous climate models from both Coupled Model Inter comparison Project-5 and 3 (i.e. CMIP5, CMIP3) and their skills in simulating Indian climate and assessing their performance using various evaluation measures. Performances of climate models were evaluated for whole of India and over all the individual grid points covering India. The newly defined metric symbolized as Skill_All is an intersection of the three metrics i.e. Skill_r, Skill_s and Skill_rmse, is used for overall model evaluation analysis. A notable enhancement of Skill_All for CMIP5 over CMIP3 was found. After overall model evaluation study, Compromise Programming, a distance based decision making technique, was employed to rank the GCMs gridwise. Entropy method was employed to obtain weights of the chosen indicators. Group decision making methodology was used to arrive at a consensus based on the ranking pattern obtained by individual grid points. In the third part, a detailed detection and attribution (D&A) analysis is performed to determine the causes of changes in seasonal Tmax and Tmin during the period 1950-2005. This formal D&A exercise helps in providing better insight (than trend detection analysis) into the nature of the observed seasonal temperature changes. It was noticed that the emergence of observed trend was more pronounced in Tmin compared to Tmax. Although observed changes were not solely associated with one specific causative factor, most of the changes in Tmin are above the bounds of natural internal climate variability. Finally in the fourth part, to understand the climate change impact on the hydrological cycle, a spatiotemporal change detection study of potential evapotranspiration (PET) along with Tmax and Tmin over India has been performed. Climatology patterns for PET confirmed a greater PET rate during the month of March, April, May and June. A significant increasing trend in both Tmax and Tmin (Tmin being more) was observed in more number of grid points compared to PET. Significant positive trends in Tmax, Tmin and PET were observed over most of the grid points in the IP region. Heterogeneities existed in the spatiotemporal variability of PET over all India. This spatio-temporal change detection study would be helpful for present and future water resources management.
Books on the topic "Meteorology, climatic change, Australia, temperature"
1
Eddy, Richard L. Variability of wet and dry periods in the Upper Colorado River Basin and the possible effects of climate change and sensitivity of probable maximum precipitation estimates to climate change. Denver, Colo: U.S. Dept. of the Interior, Bureau of Reclamation, Denver Office, 1996.
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The warming papers: The scientific foundation for the climate change forecast. Hoboken: Wiley-Blackwell, 2011.
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Grotch, Stanley L. An intercomparison of general circulation model predictions of regional climate change: Presented at the International Conference on "Modelling of Global Climate Change and Variability," Hamburg, Federal Republic of Germany, September 1989. [Springfield, Va: Available from National Technical Information Service, 1990.
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United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Natural Resources, Agriculture Research, and Environment. The National Climate Program Act and global climate change: Hearings before the Subcommittee on Natural Resources, Agriculture Research, and Environment and the Subcommittee on International Scientific Cooperation of the Committee on Science, Space, and Technology, U.S. House of Representatives, One Hundredth Congress, first session, July 22, 23, 29; September 30, 1987. Washington: U.S. G.P.O., 1988.
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United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Natural Resources, Agriculture Research, and Environment. The National Climate Program Act and global climate change: Hearings before the Subcommittee on Natural Resources, Agriculture Research, and Environment and the Subcommittee on International Scientific Cooperation of the Committee on Science, Space, and Technology, U.S. House of Representatives, One Hundredth Congress, first session, July 22, 23, 29; September 30, 1987. Washington: U.S. G.P.O., 1988.
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United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Natural Resources, Agriculture Research, and Environment. The National Climate Program Act and global climate change: Hearings before the Subcommittee on Natural Resources, Agriculture Research, and Environment and the Subcommittee on International Scientific Cooperation of the Committee on Science, Space, and Technology, U.S. House of Representatives, One Hundredth Congress, first session, July 22, 23, 29; September 30, 1987. Washington: U.S. G.P.O., 1988.
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Library of Congress. Congressional Research Service. and United States. Congress. Senate. Committee on Agriculture, Nutrition, and Forestry., eds. Agriculture, forestry, and global climate change--a reader. Washington: U.S. G.P.O., 1989.
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Trends '93: A compendium of data on global change. Oak Ridge, Tenn: Carbon Dioxide Information Analysis Center, World Data Center-A for Atmospheric Trace Gases, Environmental Sciences Division, Oak Ridge National Laboratory, 1994.
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Shu, Geng, Cady Casey Walsh, and University of California Pacific Rim Program., eds. Climatic variation and change: Implications for agriculture in the Pacific Rim : proceedings : conferences held June 20-28, 1989, University of California, Davis, USA [and] September 24-28, 1990, University of Melbourne, Australia. Davis: Public Service Research and Dissemination Program, University of California, Davis, 1991.
Find full textBook chapters on the topic "Meteorology, climatic change, Australia, temperature"
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Buckley, B. M., E. R. Cook, M. J. Peterson, and M. Barbetti. "A Changing Temperature Response with Elevation for Lagarostrobos Franklinii in Tasmania, Australia." In Climatic Change at High Elevation Sites, 245–66. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8905-5_13.
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Fleming, James R. "John Tyndall, Svante Arrhenius, and Early Research on Carbon Dioxide and Climate." In Historical Perspectives on Climate Change. Oxford University Press, 1998. http://dx.doi.org/10.1093/oso/9780195078701.003.0011.
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In the second half of the nineteenth century two prominent scientists, working in two distinct specialties, identified the importance of atmospheric trace constituents as efficient absorbers of long-wave radiation and as factors in climatic control. John Tyndall conducted the first convincing experiments on the radiative properties of gases, demonstrating that “perfectly colorless and invisible gases and vapours” were able to absorb and emit radiant heat. Svante Arrhenius, in pursuing his interests in meteorology and cosmic physics, demonstrated that variations of atmospheric CO2 concentration could have a very great effect on the overall heat budget and surface temperature of the planet. It would be a mistake, however, to consider either of these individuals as direct forerunners or prophets of contemporary climate concerns. Each of them had extremely broad scientific interests and pursued climate-related research as one interest among many. Tyndall worked on absorption in the near infrared at temperatures far above those of the terrestrial environment. Arrhenius, who has recently gained renewed attention as the “father” of the theory of the greenhouse effect, held assumptions and produced results that are not continuous with present-day climate research. . . . The solar heat possesses, in a far higher degree than that of lime light, the power of crossing an atmosphere; but, when the heat is absorbed by the planet, it is so changed in quality that the rays emanating from the planet cannot get with the same freedom back into space. Thus the atmosphere admits of the entrance of the solar heat, but checks its exit; and the result is a tendency to accumulate heat at the surface of the planet. —John Tyndall (1859). . . John Tyndall was born in Leighlin Bridge, County Carlow, Ireland, on August 2, 1820, the son of a part-time shoemaker and constable. He attended the national school in Carlow and, at the age of eighteen, joined the Irish Ordnance Survey as a draftsman and surveyor. In 1842, as the Irish survey neared completion, Tyndall was transferred to the English Survey at Preston, Lancashire, but due to his protests against the survey’s oppressive policies and incompetent management, he was dismissed.