Application of Generalized Likelihood Uncertainty Estimation (GLUE) at different temporal scales to reduce the uncertainty level in modelled river flows

ABSTRACT

In this study, the distributed catchment-scale model, DiCaSM, was applied on five catchments across the UK. Given its importance, river flow was selected to study the uncertainty in streamflow prediction using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology at different timescales (daily, monthly, seasonal and annual). The uncertainty analysis showed that the observed river flows were within the predicted bounds/envelope of 5% and 95% percentiles. These predicted river flow bounds contained most of the observed river flows, as expressed by the high containment ratio, CR. In addition to CR, other uncertainty indices – bandwidth B, relative bandwidth RB, degrees of asymmetry S and T, deviation amplitude D, relative deviation amplitude RD and the R factor – also indicated that the predicted river flows have acceptable uncertainty levels. The results show lower uncertainty in predicted river flows when increasing the timescale from daily to monthly to seasonal, with the lowest uncertainty associated with annual flows.     

The Filament Disappearance of 7 May 1992 (the Ebi)

The 7 May 1992 filament disappearance in the low corona is analyzed. The cool and hot components of this event are studied, using H, soft X-ray and radio data. We first show the general effect of the disparition brusque (DB) on the life of the filament, which was a quiescent filament in the vicinity of an active region, and then give the history of the development of the 7 May event. The main stages of the event are: (i) the formation of hot arches spanning the cool filament; (ii) rise of the filament, with plasma ejection into the corona, in which we note some spreading of loops from the main body, with two distinct rising velocity phases of the H filament; (iii) formation of X-ray arches below the filament, the foot points of the arcades being two-ribbon H flare patches. The dynamics of H and X-rays features are given.     

Toward an Ecological Explanation of Agricultural Unemployment in Bangladesh

Cultural ecology theoretical framework was found suitable to explain unemployment in agriculture in three villages in Bangladesh. Path analysis and multiple regression statistics were used to examine the direct, indirect, and total effects of eight independent human, social, environmental, and technology variables as well as their aggregate contribution on agricultural unemployment. The multiple regression model explains 86.2% of the total variation in unemployment in agriculture; they were followed by environmental constraints and labor saving technology variables.     

Macrobenthic composition of the southeast continental shelf of India

Macrobenthic faunal composition was studied at six different depth ranges (30–50, 51–75, 76–100, 101–150, 151–175 and >176 m) in five transects (off Karaikkal, Parangipettai, Cuddalore‐SIPCOT, Cheyyur and Chennai) in the continental shelf of southeast coast of India. Eleven diverse taxa were found, comprising 113 species of polychaetes, 14 species of bivalves, 10 species of amphipods and ‘others’ (five tanaids, five crabs, four isopods, three echinoderms, two shrimps, two cnidarians, two fishes and one cephalochordate). Polychaetes were the dominant taxa, constituting 88.5% of the total abundance and 30.7% of the total biomass. The number of species (seven per 0.2 m² at >176 m depth range in Chennai to 46 per 0.2 m² at 30–50 m in Cheyyur), abundance (216 per 0.2 m² at >176 m in Karaikkal to 353 per 0.2 m² at 30–50 m in Cheyyur) and biomass (0.09 g per 0.2 m² at 151–175 m in Karaikkal and 4.6 g per 0.2 m² at 30–50 m in Cheyyur) of macrobenthos decreased with increase in depth. DO decreased gradually from 30 m depth; beyond 150 m, the decrease was pronounced due to the presence of the oxygen minimum zone. Using the distance based linear model (DISTLM), it was found that the environmental variables explained about 73.3% of the total variability in macrofaunal distribution. The heavy metals cobalt and mercury, as well as water pressure (proxy for depth), showed a significant relationship with macrofauna, explaining respectively 9, 7.3 and 7% of the total variability. The contribution of other variables was smaller.     

Source Sector Contributions to Aerosol Levels in Pakistan

Urban air pollution in Pakistan is a serious challenge and it causes significant damage to human health and ecosystems. This paper presents a modelling study using the Weather Research and Forecasting Model coupled with Chemistry(WRF-Chem) to simulate the spatial distributions and temporal variations of aerosol concentrations over Pakistan, focusing on contributions of domestic emission sectors(transport, industry, residential, and energy) to mass concentrations of sulfate(SO2–4), nitrate(NO–3), ammonium(NH+4), black carbon(BC), and organic carbon(OC) during the months of January, April, July, and October in 2010. Sensitivity studies indicate that, averaged over January, April, July, and October of 2010, energy and industry sectors have the largest contributions to SO2–4 concentrations, each of which contributes about 10%?20% to SO2– 4over the polluted eastern Pakistan. The contributions from residential and transport sectors to NO–3 concentrations reach 40%?50% in central Pakistan. The residential sector has the highest contribution of 50%–80% to BC and OC loading in northeastern and southern Pakistan. Examination of sector contributions to aerosol levels in Lahore, the most polluted city in Pakistan, suggests that reductions in emissions in the residential sector should be an efficient measure for improving particulate matter air quality in this region.     

A multi-proxy reconstruction of spatial and temporal variations in Asian summer temperatures over the last millennium

To investigate climate variability in Asia during the last millennium, the spatial and temporal evolution of summer (June–July–August; JJA) temperature in eastern and south-central Asia is reconstructed using multi-proxy records and the regularized expectation maximization (RegEM) algorithm with truncated total least squares (TTLS), under a point-by-point regression (PPR) framework. The temperature index reconstructions show that the late 20th century was the warmest period in Asia over the past millennium. The temperature field reconstructions illustrate that temperatures in central, eastern, and southern China during the 11th and 13th centuries, and in western Asia during the 12th century, were significantly higher than those in other regions, and comparable to levels in the 20th century. Except for the most recent warming, all identified warm events showed distinct regional expressions and none were uniform over the entire reconstruction area. The main finding of the study is that spatial temperature patterns have, on centennial time-scales, varied greatly over the last millennium. Moreover, seven climate model simulations, from the Coupled Model Intercomparison Project Phase 5 (CMIP5), over the same region of Asia, are all consistent with the temperature index reconstruction at the 99 % confidence level. Only spatial temperature patterns extracted as the first empirical orthogonal function (EOF) from the GISS-E2-R and MPI-ESM-P model simulations are significant and consistent with the temperature field reconstruction over the past millennium in Asia at the 90 % confidence level. This indicates that both the reconstruction and the simulations depict the temporal climate variability well over the past millennium. However, the spatial simulation or reconstruction capability of climate variability over the past millennium could be still limited. For reconstruction, some grid points do not pass validation tests and reveal the need for more proxies with high temporal resolution, accurate dating, and sensitive temperature signals, especially in central Asia and before AD 1400.