An analysis on the concentration characteristics of PM2.5 in Seoul,Korea from 2005 to 2012

PM2.5 is a big issue as it is considerably more harmful than other sizes of particulate matter. World Health Organization (WHO) recommends 25 μg m^?3 as the daily average concentration, and 10 μg m^?3 per day as an annual average. To keep up with global trends, it is first necessary to understand the current status and characteristics of PM2.5 concentrations in Korea. Using the PM2.5 data measured by Seoul Metropolitan City from November 2005 to March 2012, the author analyzed its statistical characteristics and correlations with other air pollutants. For the time period from 2005 to 2012, the annual average concentration of PM2.5 was 27 μg m^?3, three times the WHO standard. Also, the daily average PM2.5 concentration of 215 days per year also exceeded the WHO standard. However, the number days exceeding the Korean daily average standard of 50 μg m^?3 to be enacted in 2014 was only three. PM2.5 concentration had a high correlation (r = 0.84) with PM10, and also showed high correlations with gaseous pollutants, such as SO₂, NO₂, and CO, but not O₃. This study suggests that the Korean government should strengthen their standard to match the criteria used by WHO.     

Characteristics of rainfall systems accompanied with Changma front at Chujado in Korea

The rainy season from June to July in the East Asia is called the Changma in Korea, the Meiyu in China, or the Baiu in Japan. The mesoscale convective systems which occur near a front frequently lead to severe weather phenomenon such as localized gust and heavy rainfall. An intensive field experiment was conducted at Chujado (33.95°N, 126.28°E) to find out the characteristics of the precipitating system using information such as the raindrop size distribution, kinematic features during a Changma period between June 21 2007 and July 11 2007. Different characteristics of three identified rainfall cases in a Changma frontal precipitation system occurred from 5 to 6 July in 2007 at Chujado area have been identified. Based on the radar reflectivity and raingage at Chujado, each rainfall system maintained for 7 hours, 4 hours, and 9 hours, respectively. According to the analysis of a total vertical wind shear (TVWS) and a directional vertical wind shear (DVWS), the temperature gradient was the strongest near the surface and both warm and cold advections were occurred in all cases but at different levels. The deep warm advection was related to the longer rainfall lifetime and stronger rainrate, but smaller raindrop size. The unstable atmospheric condition, which has cold advection at the surface and warm advection in higher level, caused the larger size diameter of raindrop. The echo top height of 30 dBZ was around 6 km in the two rainfall systems and around 4 km in the other one. The number concentrations of raindrop has turning point at the drop size of 2 mm in diameter. The stronger (weaker) updraft and downdraft were also related to the decreased number concentration of smaller (larger) size drops and increased that of the larger (smaller) drops.     

Seasonality in the relationship between El Nino and Indian Ocean dipole

The seasonal change in the relationship between El Nino and Indian Ocean dipole (IOD) is examined using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), and the twentieth century simulations (20c3m) from the Geophysical Fluid Dynamics Laboratory Coupled Model, version 2.1. It is found that, both in ERA-40 and the model simulations, the correlation between El Nino (Nino3 index) and the eastern part of the IOD (90?C110°E; 10°S-equator) is predominantly positive from January to June, and then changes to negative from July to December. Correlation maps of atmospheric and oceanic variables with respect to the Nino3 index are constructed for each season in order to examine the spatial structure of their seasonal response to El Nino. The occurrence of El Nino conditions during January to March induces low-level anti-cyclonic circulation anomalies over the southeastern Indian Ocean, which counteracts the climatological cyclonic circulation in that region. As a result, evaporation decreases and the southeastern Indian Ocean warms up as the El Nino proceeds, and weaken the development of a positive phase of an IOD. This warming of the southeastern Indian Ocean associated with the El Nino does not exist past June because the climatological winds there develop into the monsoon-type flow, enhancing the anomalous circulation over the region. Furthermore, the development of El Nino from July to September induces upwelling in the southeastern Indian Ocean, thereby contributing to further cooling of the region during the summer season. This results in the enhancement of a positive phase of an IOD. Once the climatological circulation shifts from the boreal summer to winter mode, the negative correlation between El Nino and SST of the southeastern Indian Ocean changes back to a positive one.     

How predictable is the northern hemisphere summer upper-tropospheric circulation?

The retrospective forecast skill of three coupled climate models (NCEP CFS, GFDL CM2.1, and CAWCR POAMA 1.5) and their multi-model ensemble (MME) is evaluated, focusing on the Northern Hemisphere (NH) summer upper-tropospheric circulation along with surface temperature and precipitation for the 25-year period of 1981–2005. The seasonal prediction skill for the NH 200-hPa geopotential height basically comes from the coupled models’ ability in predicting the first two empirical orthogonal function (EOF) modes of interannual variability, because the models cannot replicate the residual higher modes. The first two leading EOF modes of the summer 200-hPa circulation account for about 84% (35.4%) of the total variability over the NH tropics (extratropics) and offer a hint of realizable potential predictability. The MME is able to predict both spatial and temporal characteristics of the first EOF mode (EOF1) even at a 5-month lead (January initial condition) with a pattern correlation coefficient (PCC) skill of 0.96 and a temporal correlation coefficient (TCC) skill of 0.62. This long-lead predictability of the EOF1 comes mainly from the prolonged impacts of El Niño-Southern Oscillation (ENSO) as the EOF1 tends to occur during the summer after the mature phase of ENSO. The second EOF mode (EOF2), on the other hand, is related to the developing ENSO and also the interdecadal variability of the sea surface temperature over the North Pacific and North Atlantic Ocean. The MME also captures the EOF2 at a 5-month lead with a PCC skill of 0.87 and a TCC skill of 0.67, but these skills are mainly obtained from the zonally symmetric component of the EOF2, not the prominent wavelike structure, the so-called circumglobal teleconnection (CGT) pattern. In both observation and the 1-month lead MME prediction, the first two leading modes are accompanied by significant rainfall and surface air temperature anomalies in the continental regions of the NH extratropics. The MME’s success in predicting the EOF1 (EOF2) is likely to lead to a better prediction of JJA precipitation anomalies over East Asia and the North Pacific (central and southern Europe and western North America).     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

Climate Change and Winter Wheat Management: A Modelling Scenario for South-Eastern England

Crop models are useful tools for assessing the impact of climate change on crop production. The dynamic crop-growth model, CERES-Wheat is used to examine crop management responses, including yield, under six climate change scenarios for the years 2025 and 2050 on the Estate of Imperial College at Wye, Kent, U.K. Sensitivity analysis shows a dry matter yield decrease in response to increases in temperature alone. CERES-Wheat was then constrained to assess the crop performance under water-limited production scenarios with different soils, and the results show that crop grain yield actually increases, largely due to CO₂ fertilisation leading to increased rates of photosynthesis. Different management practices (planting dates and nitrogen application) were applied to find the best adaptation strategies. In general, `early' sowing (10th September) had the highest simulated yield, and `late' sowing (10th November) the lowest. For the soils tested, the highest and sustained crop production was obtained from Hamble soils (silt loam) compared with either the Fyfield (sandy) or Denchworth (clay). Adding nitrogen and other fertilisers would likely be necessary to take full advantage of the CO₂ fertilisationeffect and to compensate, in some cases, for yield losses caused by climate change where water shortage becomes serious.     

The 1786 earthquake-triggered landslide dam and subsequent dam-break flood on the Dadu River, southwestern China — Reply

A short reply to discussion by Chanson.     

The differential geography of housing affordability in Sydney: a disaggregated approach

ABSTRACT

Despite extensive studies being devoted to housing affordability in Australia, few have investigated housing affordability at a disaggregated level. This is in spite of the fact that there are existing socio-economic and demographic disparities across different regions of a city. This study aims to fill this gap by examining housing affordability in Sydney, a city that is characterised by diverse demographic and socio-economic mix, from a sub-city perspective. Two dimensions of affordability are assessed from 1991 to 2016: entry-level and ongoing housing affordability. The study finds that entry-level housing remains extremely unaffordable in all regions of Greater Sydney, although the level of unaffordability varies across regions. Specifically, the deterioration in housing affordability is more obvious in low-income regions such as Western Sydney. In addition, the ongoing housing affordability of those who have entered the market improves considerably within 5–10 years, although there are significant variations between different regions. Importantly, residents in low-income regions such as Western Sydney take a longer period to improve their ongoing affordability. The findings of differential geography of housing affordability have some profound policy implications. Policymakers should consider the disparities across different regions by formulating a more targeted and regionally balanced housing policy.     

The granite problem as exposed in the southern Snake Range,Nevada

A geochemically and mineralogically diverse group of granitoids is present within an area of 900 km² in the southern Snake Range of eastern Nevada. The granitoids exposed range in age from Jurassic through Cretaceous to Oligocene and include two calcic intrusions, two different types of two-mica granites, and aplites. The younger intrusions appear to have been emplaced at progressively more shallow depths. All of these granitoid types are represented elsewhere in the eastern Great Basin, but the southern Snake Range is distinguished by the grouping of all these types within a relatively small area. The Jurassic calcic pluton of the Snake Creek-Williams Canyon area displays large and systematic chemical and mineralogical zonation over a horizontal distance of five km. Although major element variations in the pluton compare closely with Daly's average andesite-dacite-rhyolite over an SiO₂ range of 63 to 76 percent, trace element (Rb, Sr, Ba) variations show that the zonation is the result of in situ fractional crystallization, with the formation of relatively mafic cumulates on at least one wall of the magma chamber. Models of trace element and isotopic data indicate that relatively little assimilation took place at the level of crystallization. Nonetheless, an initial ⁸⁷Sr/⁸⁶Sr value of 0.7071 and δ ¹⁸O values of 10.2 to 12.2 permil suggest a lower crustal magma that was contaminated by upper crustal clastic sedimentary rocks before crystallization. The involvement of mantle-derived magmas in its genesis is difficult to rule out. Two other Jurassic plutons show isotopic and chemical similarities to the Snake Creek-Williams Canyon pluton. Cretaceous granites from eastern Nevada that contain phenocrystic muscovite are strongly peraluminous, and have high initial Sr-isotope ratios and other features characteristic of S-type granitoids. They were probably derived from Proterozoic metasediments and granite gneisses that comprise the middle crust of this region. Another group of granitoids (including the Tertiary aplites) show chemical, mineralogic, and isotopic characteristics intermediate between the first two groups and may have been derived by contamination of magmas from the lower crust by the midcrustal metasediments.