One- and multi-component models of the upper photosphere based on molecular spectra

Non-LTE synthetic spectra derived from a detailed analysis of the formation of the CN (0, 0) λ13883 Å spectrum are compared with center-limb photoelectric spectra taken at Kitt Peak National Observatory. Kitt Peak National Observatory is operated by the Association of Universities for Research in Astronomy, Inc., under contract with the National Science Foundation. Significant non-LTE effects are found and the Kurucz, Altrock-Cannon, Mount-Linsky II, and HSRA models are compared. We derive a solar carbon abundance of A _c =8.30±0.10 for the Mount-Linsky model and A _c =8.40±0.10 for the Altrock-Cannon model, compared to the HSRA value of A _c =8.55±0.10, assuming a nitrogen abundance of logA _N=7.93. In addition we specify the regions of formation for the CN(0, 0) 3883.35 Å bandhead at disc center and limb.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

野生二粒小麦 Triticum dicoccoides抗杀锈病基因 YrH52分子定位的初步研究(英文)

主要对以色列野生二粒小麦赫尔蒙种群中分离获得的一个抗条锈病基因进行了分子定位研究 ,将源于赫尔蒙山具抗杀锈病的种系 T.dicoccides H52与普通的栽培种 Langdon进行杂交并创建了 F2 代遗传图。研究发现 H52种系抗条锈病的能力由一种显性基因控制 ,将其暂定名为 Yr H52。从 1 2 0个微卫星标记中 ,已经检测到来自亲本 91 %的多态性 ,而且从其中 56个微卫星分子标记中产生了 79个分离的位点 ,有 9个位点显示出了与 Yr H 52基因连锁 ,其重组率 0 .0 2～ 0 .3 5,遗传距离 2 .0 0～ 4 3 .3 7cm之间 ,L OD值 3 .56～ 54.2 2。由 1 0个微卫星位点和 Yr H52构建的染色体 1 B遗传图 ,其图距全长为 1 0 1 .5cm。Yr H52基因位于 Xgwm2 64 a和 Xgwm2 64 c之间 ,且与 Xgwm2 64 a、Xgwm1 8紧密连锁 ,两侧依次分别与 Xgwm1 3 1 a、Xgwm63 6b、Xgwm2 64 c、Xgwm4 0 3 a、Xgwm1 53、Xgwm550 a和 Xgwm1 2 4连锁。同时 ,Yr H52也与 REL P标记物 N or1紧密连锁 ,图距 1 .4 cm,L OD2 9.62。这显然与野生二粒小麦另一个抗条锈病基因 Yr1 5不同 ,研究证明 Yr1 5与 N or1图距是 1 1 .0 cm。     

Stream temperature sensitivity to climate warming in California’s Sierra Nevada: impacts to coldwater habitat

Water temperature influences the distribution, abundance, and health of aquatic organisms in stream ecosystems, so understanding the impacts of climate warming on stream temperature will help guide management and restoration. This study assesses climate warming impacts on stream temperatures in California’s west-slope Sierra Nevada watersheds, and explores stream temperature modeling at the mesoscale. We used natural flow hydrology to isolate climate induced changes from those of water operations and land use changes. A 21 year time series of weekly streamflow estimates from WEAP21, a spatially explicit rainfall-runoff model were passed to RTEMP, an equilibrium temperature model, to estimate stream temperatures. Air temperature was uniformly increased by 2°C, 4°C, and 6°C as a sensitivity analysis to bracket the range of likely outcomes for stream temperatures. Other meteorological conditions, including precipitation, were unchanged from historical values. Raising air temperature affects precipitation partitioning into snowpack, runoff, and snowmelt in WEAP21, which change runoff volume and timing as well as stream temperatures. Overall, stream temperatures increased by an average of 1.6°C for each 2°C rise in air temperature, and increased most during spring and at middle elevations. Viable coldwater habitat shifted to higher elevations and will likely be reduced in California. Thermal heterogeneity existed within and between basins, with the high elevations of the southern Sierra Nevada and the Feather River watershed most resilient to climate warming. The regional equilibrium temperature modeling approach used here is well suited for climate change analysis because it incorporates mechanistic heat exchange, is not overly data or computationally intensive, and can highlight which watersheds are less vulnerable to climate warming. Understanding potential changes to stream temperatures from climate warming will affect how fish and wildlife are managed, and should be incorporated into modeling studies, restoration assessments, and licensing operations of hydropower facilities to best estimate future conditions and achieve desired outcomes.     

An imaging spectrometric observatory for spacelab

The capability to measure nearly simultaneously the entire spectrum of atmospheric emission from the extreme ultraviolet to the near infrared, with relatively high spectral resolution and high sensitivity, while also obtaining global and altitude coverage, would provide a database from which significant advances could be made in our current understanding of the atmosphere and its processes. The large payload capacity of the shuttle orbiter offers the first opportunity to put such instrumentation into space. The Imaging Spectrometric Observatory (ISO) comprises an array of five spectrometers designed to make full use of the shuttle as an observing platform for remote sensing of the atmosphere. ISO covers the wavelength range 300–12000 Å at 2–7 Å resolution. Use of area array detectors (intensified-CCD's) permits simultaneous measurements of ～1000 Å at a time. The instrument is capable of scanning the entire wavelength range in less than 20 s, or dwelling on weaker features for longer periods of time. The detectors are two dimensional and permit spectral imaging in one direction and spatial imaging in the other. The spatial imaging and spatial scanning features permit measurement of altitude profiles, or mapping of strongly spatially varying features such as aurorae. The instrument is designed to allow versatility. The various functions are programmable and software controlled. The key subsystems are modular for convenient replacement or upgrading. It is anticipated that the instrument will have applications not only in the area of atmospheric science, but also in studies of the ionosphere and magnetosphere, and in support of active experiments to be performed in space.     

Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan

ABSTRACT

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing, positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and/or data are available to inform the model development process.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned     

Discussion of “Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers”

Citation Abrahart, R.J. & Mount, N.J. (2011) Discussion of “Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers by S.A. Mirgagheri et al. (2010, Hydrol. Sci. J. 55(7), 1175–1189).” Hydrol. Sci. J. 56(7), 1325–1329.