Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Physicochemical and mineralogical characteristics of soil/saprolite cores from a field research site, Tennessee

Site characterization is an essential initial step in determining the feasibility of remedial alternatives at hazardous waste sites. Physicochemical and mineralogical characterization of U-contaminated soils in deeply weathered saprolite at Area 2 of the DOE Field Research Center (FRC) site, Oak Ridge, TN, was accomplished to examine the feasibility of bioremediation. Concentrations of U in soil–saprolite (up to 291 mg kg–1 in oxalate-extractable Uo) were closely related to low pH (ca. 4–5), high effective cation exchange capacity without Ca (64.7–83.2 cmolc kg–1), amorphous Mn content (up to 9910 mg kg–1), and the decreased presence of relative clay mineral contents in the bulk samples (i.e., illite 2.5–12 wt. %, average 32 wt. %). The pH of the fill material ranged from 7.0 to 10.5, whereas the pH of the saprolite ranged from 4.5 to 8. Uranium concentration was highest (about 300 mg kg–1) at around 6 m below land surface near the saprolite–fill interface. The pH of ground water at Area 2 tended to be between 6 and 7 with U concentrations of about 0.9 to 1.7 mg L–1. These site specific characteristics of Area 2, which has lower U and nitrate contamination levels and more neutral ground water pH compared with FRC Areas 1 and 3 (ca. 5.5 and

Binding site of AMPA-receptor allosteric modulator

The computer molecular docking of piperonyl acid piperidide (BDP) and some its analogs already known as ampakins was conducted for estimating their possible binding with AMPA-receptor glutamate domains in cyclothiazide binding area and for further design of new structures maximally complimentary to the receptor. On the base of the conducted docking it can be suggested that the binding site of BDP (amides of benzodioxane-6-carboxylic and piperonyl acids) analogs is located in AMPA-receptor cyclothiazide binding pocket. It is shown that formation of protein-ligand complexes of AMPA-receptor with benzodioxane-6-carboxylic and piperonyl acid derivatives, similarly to cyclothiazide, proceeds with interaction with Ser497, Leu751, which significance is confirmed by site-specific mutagenesis.