Journal articles on the topic 'Atmospheric temperature Western Australia Mathematical models'
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1
Loikith, Paul C., J. David Neelin, Joyce Meyerson, and Jacob S. Hunter. "Short Warm-Side Temperature Distribution Tails Drive Hot Spots of Warm Temperature Extreme Increases under Near-Future Warming." Journal of Climate 31, no. 23 (December 2018): 9469–87. http://dx.doi.org/10.1175/jcli-d-17-0878.1.
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Regions of shorter-than-Gaussian warm-side temperature anomaly distribution tails are shown to occur in spatially coherent patterns in global reanalysis. Under such conditions, future warming may be manifested in more complex ways than if the underlying distribution were close to Gaussian. For example, under a uniform warm shift, the simplest prototype for future warming, a location with a short tail would experience a greater increase in extreme warm exceedances relative to a fixed threshold compared to if the distribution were Gaussian. The associated societal and environmental impacts make realistic representation of these short tails an important target for climate models. Global evaluation of the ability for a suite of global climate models (GCMs) contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests that most models approximately capture the principal observed coherent regions of short tails. This suggests the underlying dynamics and physics occur on scales resolved by the models, and helps build confidence in model simulations of extremes. Furthermore, most GCMs show more rapid future increases in exceedances of the historical 95th percentile in regions exhibiting short tails in the historical climate. These regions, where the ratio of exceedances projected by the GCM compared to that expected from a Gaussian sometimes exceeds 1.5, are termed hot spots. Prominent hot spots include western North America, Central America, a broad swath of northwestern Eurasia, and the Indochina Peninsula during boreal winter. During boreal summer, central and western Australia, parts of southern Africa, and portions of central South America are major hot spots.
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Andrys, Julia, Thomas J. Lyons, and Jatin Kala. "Multidecadal Evaluation of WRF Downscaling Capabilities over Western Australia in Simulating Rainfall and Temperature Extremes." Journal of Applied Meteorology and Climatology 54, no. 2 (February 2015): 370–94. http://dx.doi.org/10.1175/jamc-d-14-0212.1.
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AbstractThe authors evaluate a 30-yr (1981–2010) Weather Research and Forecast (WRF) Model regional climate simulation over the southwest of Western Australia (SWWA), a region with a Mediterranean climate, using ERA-Interim boundary conditions. The analysis assesses the spatial and temporal characteristics of climate extremes, using a selection of climate indices, with an emphasis on metrics that are relevant for forestry and agricultural applications. Two nested domains at 10- and 5-km resolution are examined, with the higher-resolution simulation resolving convection explicitly. Simulation results are compared with a high-resolution, gridded observational dataset that provides daily rainfall, minimum temperatures, and maximum temperatures. Results show that, at both resolutions, the model is able to simulate the daily, seasonal, and annual variation of temperature and precipitation well, including extreme events. The higher-resolution domain displayed significant performance gains in simulating dry-season convective precipitation, rainfall around complex terrain, and the spatial distribution of frost conditions. The high-resolution domain was, however, influenced by grid-edge effects in the southwestern margin, which reduced the ability of the domain to represent frontal rainfall along the coastal region. On the basis of these results, the authors feel confident in using the WRF Model for regional climate simulations for the SWWA, including studies that focus on the spatial and temporal representation of climate extremes. This study provides a baseline climatological description at a high resolution that can be used for impact studies and will also provide a benchmark for climate simulations driven by general circulation models.
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Hope, Pandora, Kevin Keay, Michael Pook, Jennifer Catto, Ian Simmonds, Graham Mills, Peter McIntosh, James Risbey, and Gareth Berry. "A Comparison of Automated Methods of Front Recognition for Climate Studies: A Case Study in Southwest Western Australia." Monthly Weather Review 142, no. 1 (January 1, 2014): 343–63. http://dx.doi.org/10.1175/mwr-d-12-00252.1.
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Abstract The identification of extratropical fronts in reanalyses and climate models is an important climate diagnostic that aids dynamical understanding and model verification. This study compares six frontal identification methods that are applied to June and July reanalysis data over the Central Wheatbelt of southwest Western Australia for 1979–2006. Much of the winter rainfall over this region originates from frontal systems. Five of the methods use automated algorithms. These make use of different approaches, based on shifts in 850-hPa winds (WND), gradients of temperature (TGR) and wet-bulb potential temperature (WPT), pattern matching (PMM), and a self-organizing map (SOM). The sixth method was a manual synoptic technique (MAN). On average, about 50% of rain days were associated with fronts in most schemes (although methods PMM and SOM exhibited a lower percentage). On a daily basis, most methods identify the same systems more than 50% of the time, and over the 28-yr period the seasonal time series correlate strongly. The association with rainfall is less clear. The WND time series of seasonal frontal counts correlate significantly with Central Wheatbelt rainfall. All automated methods identify fronts on some days that are classified as cutoff lows in the manual analysis, which will impact rainfall correlations. The front numbers identified on all days by the automated methods decline from 1979 to 2006 (but only the TGR and WPT trends were significant at the 10% level). The results here highlight that automated techniques have value in understanding frontal behavior and can be used to identify the changes in the frequency of frontal systems through time.
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Drushka, Kyla, Janet Sprintall, Sarah T. Gille, and Susan Wijffels. "In Situ Observations of Madden–Julian Oscillation Mixed Layer Dynamics in the Indian and Western Pacific Oceans." Journal of Climate 25, no. 7 (March 28, 2012): 2306–28. http://dx.doi.org/10.1175/jcli-d-11-00203.1.
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Abstract The boreal winter response of the ocean mixed layer to the Madden–Julian oscillation (MJO) in the Indo-Pacific region is determined using in situ observations from the Argo profiling float dataset. Composite averages over numerous events reveal that the MJO forces systematic variations in mixed layer depth and temperature throughout the domain. Strong MJO mixed layer depth anomalies (>15 m peak to peak) are observed in the central Indian Ocean and in the far western Pacific Ocean. The strongest mixed layer temperature variations (>0.6°C peak to peak) are found in the central Indian Ocean and in the region between northwest Australia and Java. A heat budget analysis is used to evaluate which processes are responsible for mixed layer temperature variations at MJO time scales. Though uncertainties in the heat budget are on the same order as the temperature trend, the analysis nonetheless demonstrates that mixed layer temperature variations associated with the canonical MJO are driven largely by anomalous net surface heat flux. Net heat flux is dominated by anomalies in shortwave and latent heat fluxes, the relative importance of which varies between active and suppressed MJO conditions. Additionally, rapid deepening of the mixed layer in the central Indian Ocean during the onset of active MJO conditions induces significant basin-wide entrainment cooling. In the central equatorial Indian Ocean, MJO-induced variations in mixed layer depth can modulate net surface heat flux, and therefore mixed layer temperature variations, by up to ~40%. This highlights the importance of correctly representing intraseasonal mixed layer depth variations in climate models in order to accurately simulate mixed layer temperature, and thus air–sea interaction, associated with the MJO.
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Su, Chun-Hsu, Nathan Eizenberg, Dörte Jakob, Paul Fox-Hughes, Peter Steinle, Christopher J. White, and Charmaine Franklin. "BARRA v1.0: kilometre-scale downscaling of an Australian regional atmospheric reanalysis over four midlatitude domains." Geoscientific Model Development 14, no. 7 (July 12, 2021): 4357–78. http://dx.doi.org/10.5194/gmd-14-4357-2021.
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Abstract. Regional reanalyses provide a dynamically consistent recreation of past weather observations at scales useful for local-scale environmental applications. The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of kilometre-scale (1–4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realize the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four midlatitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind, and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of the intensity and timing of precipitation during the thunderstorm seasons in NSW and spatial patterns of sub-daily rain fields during storm events. BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, as well as underestimation of light rain occurrence. As a hindcast-only system, BARRA-C largely inherits the domain-averaged bias pattern from BARRA-R but does produce different climatological extremes for temperature and precipitation. An added-value analysis of temperature and precipitation extremes shows that BARRA-C provides additional skill over BARRA-R when compared to gridded observations. The spatial patterns of BARRA-C warm temperature extremes and wet precipitation extremes are more highly correlated with observations. BARRA-C adds value in the representation of the spatial pattern of cold extremes over coastal regions but remains biased in terms of magnitude.
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Garfinkel, Chaim I., Ori Adam, Efrat Morin, Yehoudah Enzel, Eilat Elbaum, Maya Bartov, Dorita Rostkier-Edelstein, and Uri Dayan. "The Role of Zonally Averaged Climate Change in Contributing to Intermodel Spread in CMIP5 Predicted Local Precipitation Changes." Journal of Climate 33, no. 3 (February 1, 2020): 1141–54. http://dx.doi.org/10.1175/jcli-d-19-0232.1.
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AbstractWhile CMIP5 models robustly project drying of the subtropics and more precipitation in the tropics and subpolar latitudes by the end of the century, the magnitude of these changes in precipitation varies widely across models: for example, some models simulate no drying in the eastern Mediterranean while others simulate more than a 50% reduction in precipitation relative to the model-simulated present-day value. Furthermore, the factors leading to changes in local subtropical precipitation remain unclear. The importance of zonal-mean changes in atmospheric structure for local precipitation changes is explored in 42 CMIP5 models. It is found that up to half of the local intermodel spread over the Mediterranean, northern Mexico, East Asia, southern Africa, southern Australia, and southern South America is related to the intermodel spread in large-scale processes such as the magnitude of globally averaged surface temperature increases, Hadley cell widening, polar amplification, stabilization of the tropical upper troposphere, or changes in the polar stratosphere. Globally averaged surface temperature increases account for intermodel spread in land subtropical drying in the Southern Hemisphere but are not important for land drying adjacent to the Mediterranean. The factors associated with drying over the eastern Mediterranean and western Mediterranean differ, with stabilization of the tropical upper troposphere being a crucial factor for the former only. Differences in precipitation between the western and eastern Mediterranean are also evident on interannual time scales. In contrast, the global factors examined here are unimportant over most of the United States, and more generally over the interior of continents. Much of the rest of the spread can be explained by variations in local relative humidity, a proxy also for zonally asymmetric circulation and thermodynamic changes.
7
Инишева, Л. И., Е. В. Порохина, М. А. Сергеева, and К. И. Кобак. "ТОРФЯНЫЕ БОЛОТА И ИХ БИОСФЕРНАЯ РОЛЬ." Biosfera 11, no. 3 (February 5, 2020): 1. http://dx.doi.org/10.24855/biosfera.v11i3.509.
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Bogs occupy a significant part of territory in Russia. In the present article, the main factors of formation of peat bogs and their functions in the biosphere are discussed as exemplified with pineal-bushy-mossy biocenoses in Western Siberia. Carbon balance during periods differing in climatic conditions are analyzed. Field observations and mathematical models of peat accretion suggest that net carbon accumulation takes place in bogs of several types. In may be expected that in the forthcoming decades the current climatic conditions will, upon increasing temperature and atmospheric precipitates, result in the activation of bog formation and peat accumulation in the north of Russia, including West Siberia.
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Oliver, Eric C. J., Simon J. Wotherspoon, Matthew A. Chamberlain, and Neil J. Holbrook. "Projected Tasman Sea Extremes in Sea Surface Temperature through the Twenty-First Century." Journal of Climate 27, no. 5 (February 24, 2014): 1980–98. http://dx.doi.org/10.1175/jcli-d-13-00259.1.
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AbstractOcean climate extremes have received little treatment in the literature, aside from coastal sea level and temperatures affecting coral bleaching. Further, it is notable that extremes (e.g., temperature and precipitation) are typically not well represented in global climate models. Here, the authors improve dynamically downscaled ocean climate model estimates of sea surface temperature (SST) extremes in the Tasman Sea off southeastern Australia using satellite remotely sensed observed extreme SSTs and the simulated marine climate of the 1990s. This is achieved using a Bayesian hierarchical model in which the parameters of an extreme value distribution are modeled by linear regression onto the key marine climate variables (e.g., mean SST, SST variance, etc.). The authors then apply this fitted model, essentially a form of bias correction, to the marine climate projections for the 2060s under an A1B emissions scenario. They show that the extreme SSTs are projected to increase in the Tasman Sea in a nonuniform way. The 50-yr return period extreme SSTs are projected to increase by up to 2°C over the entire domain and by up to 4°C in a hotspot located in the central western portion of the Tasman Sea, centered at a latitude ~500 km farther south than the projected change in mean SST. The authors show that there is a greater than 50% chance that annual maximum SSTs will increase by at least 2°C in this hotspot and that this change is significantly different than that which might be expected because of random chance in an unchanged climate.
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Hague, Ben, Karl Braganza, and David Jones. "Effects of heat extremes on wheat yields in Australia." Journal of Southern Hemisphere Earth Systems Science 66, no. 3 (2016): 314. http://dx.doi.org/10.1071/es16021.
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Many agricultural studies have identified that wheat yield is sensitive to seasonal rainfall and extreme high temperatures. We investigate the impact of extreme heat events, in particular on wheat yields in South-East Australia (SEA) and South-West Western Australia (SWWA).We define a 'heat-day' as a day where the daily maximum temperature exceeds the 1911–2013 90th percentile for the respective calendar month. We find that the number of heat-days has experienced statistically significant increases across most months across much of Australia, particularly in South Australia, Western Australia, the Northern Territory and Tasmania. The trends are especially marked in winter, including in key wheat-growing regions. The temperatures recorded on these hottest days have also shown a statistically significant increase over the last 100 years.We find that, while wheat yields are more strongly correlated with rainfall than with the number of heat-days, there is substantial evidence to suggest that during drought conditions wheat yields are sensitive to the number of heat-days recorded in August and September in SEA and September and October in SWWA. Extreme heat and rainfall have a stronger association with below-average yields than above-average yields.Extreme temperatures and rainfall in these regions are related to major Australian climate drivers which form the basis of seasonal prediction models and are important for natural variability and long-term climate change. Here we assess the degree to which wheat yields in both regions can be related to the El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Southern Annular Mode (SAM). We find that positive IOD events and El Niño events are both associated with reductions in wheat yields in SEA, but that the co-incidence of these events have no additional wheat yield reductions than would be expected if either a positive IOD or El Niño event occurs. The average annual wheat yield loss associated with El Niño state and/or positive IOD state in SEA is estimated to around sixteen to twenty one per cent.This paper provides insights into the historical relationships between wheat yields, extreme heat and climatic modes of variability in Australia, and discusses the possibilities for changes in wheat yields under a future climate change scenario.
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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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Brown, Josephine R., Aurel F. Moise, Robert Colman, and Huqiang Zhang. "Will a Warmer World Mean a Wetter or Drier Australian Monsoon?" Journal of Climate 29, no. 12 (June 10, 2016): 4577–96. http://dx.doi.org/10.1175/jcli-d-15-0695.1.
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Abstract Multimodel mean projections of the Australian summer monsoon show little change in precipitation in a future warmer climate, even under the highest emission scenario. However, there is large uncertainty in this projection, with model projections ranging from around a 40% increase to a 40% decrease in summer monsoon precipitation. To understand the source of this model uncertainty, a set of 33 climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5) is divided into groups based on their future precipitation projections (DRY, MID, and WET terciles). The DRY model mean has enhanced sea surface temperature (SST) warming across the equatorial Pacific, with maximum increases in precipitation in the western equatorial Pacific. The DRY model mean also has a large cold bias in present day SSTs in this region. The WET model mean has the largest warming in the central and eastern equatorial Pacific, with precipitation increases over much of Australia. These results suggest lower confidence for projections of reduced monsoon precipitation because of the influence of model SST biases on the SST warming pattern and precipitation response. The precipitation changes for the DRY and WET models are also decomposed into dynamic and thermodynamic components. The component due to spatial shifts in the location of convergence and precipitation is responsible for most of the difference between DRY and WET models. As spatial shifts in precipitation are closely associated with patterns of SST change, reducing uncertainty in model SST warming patterns will be crucial to improved projections of Australian monsoon precipitation.
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Biello, Joseph A., and Andrew J. Majda. "A New Multiscale Model for the Madden–Julian Oscillation." Journal of the Atmospheric Sciences 62, no. 6 (June 1, 2005): 1694–721. http://dx.doi.org/10.1175/jas3455.1.
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Abstract A multiscale model of the MJO is developed here that accounts, in a simplified fashion, for both the upscale transfer from synoptic to planetary scales of momentum and temperature from wave trains of thermally driven equatorial synoptic-scale circulations in a moving convective envelope as well as direct mean heating on planetary scales. This model involves idealized thermally driven congestus synoptic-scale fluctuations in the eastern part of the moving wave envelope and convective superclusters in the western part of the envelope. The model self-consistently reproduces qualitatively many of the detailed structural features of the planetary circulation in the observations of the MJO, including the vertical structure in both the westerly onset region and the strong westerly wind burst region, as well as the horizontal quadrupole planetary vortex structure. The westerly midlevel inflow in the strong westerly region and the quadrupole vortex are largely produced in the model by the upscale transport of momentum to the planetary scales, while the midlevel easterly jet in the westerly onset region is substantially strengthened by this process. The role of wave trains of tilted organized synoptic-scale circulations is crucial for this fidelity with observations. The appeal of the multiscale models developed below is their firm mathematical underpinnings, simplicity, and analytic tractability while remaining self-consistent with many of the features of the observational record.
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Hoerling, Martin, Jon Eischeid, and Judith Perlwitz. "Regional Precipitation Trends: Distinguishing Natural Variability from Anthropogenic Forcing." Journal of Climate 23, no. 8 (April 15, 2010): 2131–45. http://dx.doi.org/10.1175/2009jcli3420.1.
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Abstract In this study, the nature and causes for observed regional precipitation trends during 1977–2006 are diagnosed. It is found that major features of regional trends in annual precipitation during 1977–2006 are consistent with an atmospheric response to observed sea surface temperature (SST) variability. This includes drying over the eastern Pacific Ocean that extends into western portions of the Americas related to a cooling of eastern Pacific SSTs, and broad increases in rainfall over the tropical Eastern Hemisphere, including a Sahelian rainfall recovery and increased wetness over the Indo–West Pacific related to North Atlantic and Indo–West Pacific ocean warming. It is further determined that these relationships between SST and rainfall change are generally not symptomatic of human-induced emissions of greenhouse gases (GHGs) and aerosols. The intensity of regional trends simulated in climate models using observed time variability in greenhouse gases, tropospheric sulfate aerosol, and solar and volcanic aerosol forcing are appreciably weaker than those observed and also weaker than those simulated in atmospheric models using only observed SST forcing. The pattern of rainfall trends occurring in response to such external radiative forcing also departs significantly from observations, especially a simulated increase in rainfall over the tropical Pacific and southeastern Australia that are opposite in sign to the actual drying in these areas. Additional experiments illustrate that the discrepancy between observed and GHG-forced rainfall changes during 1977–2006 results mostly from the differences between observed and externally forced SST trends. Only weak rainfall sensitivity is found to occur in response to the uniform distribution of SST warming that is induced by GHG and aerosol forcing, whereas the particular pattern of the observed SST change that includes an increased SST contrast between the east Pacific and the Indian Ocean, and strong regional warming of the North Atlantic Ocean, was a key driver of regional rainfall trends. The results of this attribution study on the causes for 1977–2006 regional rainfall changes are used to discuss prediction challenges including the likelihood that recent rainfall trends might persist.
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Parracho, Ana C., Olivier Bock, and Sophie Bastin. "Global IWV trends and variability in atmospheric reanalyses and GPS observations." Atmospheric Chemistry and Physics 18, no. 22 (November 15, 2018): 16213–37. http://dx.doi.org/10.5194/acp-18-16213-2018.
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Abstract. This study investigates the means, variability, and trends in integrated water vapour (IWV) from two modern reanalyses (ERA-Interim and MERRA-2) from 1980 to 2016 and ground-based GPS data from 1995 to 2010. It is found that the mean distributions and inter-annual variability in IWV in the reanalyses and GPS are consistent, even in regions of strong gradients. ERA-Interim is shown to exhibit a slight moist bias in the extra-tropics and a slight dry bias in the tropics (both on the order of 0.5 to 1 kg m−2) compared to GPS. ERA-Interim is also generally drier than MERRA-2 over the ocean and within the tropics. Differences in variability and trends are pointed out at a few GPS sites. These differences can be due to representativeness errors (for sites located in coastal regions and regions of complex topography), gaps and inhomogeneities in the GPS series (due to equipment changes), or potential inhomogeneities in the reanalyses (due to changes in the observing system). Trends in IWV and surface temperature in ERA-Interim and MERRA-2 are shown to be consistent, with positive IWV trends generally correlated with surface warming, but MERRA-2 presents a more general global moistening trend compared to ERA-Interim. Inconsistent trends are found between the two reanalyses over Antarctica and most of the Southern Hemisphere, and over central and northern Africa. The uncertainty in current reanalyses remains quite high in these regions, where few in situ observations are available, and the spread between models is generally important. Inter-annual and decadal variations in IWV are also shown to be strongly linked with variations in the atmospheric circulation, especially in arid regions, such as northern Africa and Western Australia, which add uncertainty in the trend estimates, especially over the shorter period. In these regions, the Clausius–Clapeyron scaling ratio is found not to be a good humidity proxy for inter-annual variability and decadal trends.
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Meinke, H., P. S. Carberry, H. A. Cleugh, P. L. Poulton, and J. N. G. Hargreaves. "Modelling crop growth and yield under the environmental changes induced by windbreaks 1. Model development and validation." Australian Journal of Experimental Agriculture 42, no. 6 (2002): 875. http://dx.doi.org/10.1071/ea02019.
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Yield advantages of crops grown behind windbreaks have often been reported, but underlying principles responsible for such changes and their long-term consequences on crop productivity and hence farm income have rarely been quantified. Physiologically and physically sound simulation models could help to achieve this quantification. Hence, the APSIM systems model, which is based on physiological principles such as transpiration efficiency and radiation use efficiency (termed here APSIMTE), and the Soil Canopy Atmosphere Model (SCAM), which is based on the Penman–Monteith equation but includes a full surface energy balance, were employed in developing an approach to quantify such windbreak effects. This resulted in a modified APSIM version (APSIMEO), containing the original Penman equation and a calibration factor to account for crop- and site-specific differences, which were tested against field data and simulations from both the standard APSIMTE and SCAM models. The APSIMEO approach was tested against field data for wheat and mungbean grown in artificial enclosures in south-east Queensland and in south-east Western Australia. For these sheltered conditions, daily transpiration demand estimates from APSIMEO compared closely to SCAM. As the APSIMEO approach needed to be calibrated for individual crops and environments, average transpiration demand for open field conditions predicted by APSIMEO for a given site was adjusted to equal that obtained using APSIMTE by modifying a calibration parameter β. For wheat, a β-value of 1.0 resulted in best fits for Queensland, while for Western Australia a value of 0.85 was necessary. For mungbean a value of 0.92 resulted in the best fit (Qld). Biomass and yields simulated by APSIMTE and the calibration APSIMEO for wheat and mungbean grown in artificial enclosures were generally distributed around the 1:1 line, with R2 values ranging from 0.92 to 0.97. Finally, APSIMEO was run at 2 sites using long-term climate data to assess the likely year-to-year variability of windbreak effects on crop yields. Assuming a 70% reduction in wind speed as representing the maximum potential windbreak effect, the average yield improvement for the Queensland site was 13% for wheat and 3% for mungbean. For wheat at the WA site the average yield improvement from reduced wind speed was 5%. In any year, however, effects varied from negative, neutral to positive, highlighting the highly variable nature of the expression of windbreak effects. This study has shown how physical and biological modelling approaches can be combined to aid our understanding of systems processes. Both the environmental physics perspective and the biological perspective have shortcomings when issues that sit at the interface of both approaches need to be addressed. While the physical approach has clear advantages when investigating changes in physical parameters such as wind speed, vapour pressure deficit (VPD), temperature or the energy balance of the soil–plant–atmosphere continuum, it cannot deal with complex, biological systems adequately. Conversely, the crop physiological approach can handle such biological interactions in a scientific and robust way while certain atmospheric processes are not considered. The challenge was not to try and capture all these effects in 1 model, but rather to structure a modelling approach in a way that allowed for inclusion of such processes where necessary.