Bred vectors of the Lorenz63 system

The breeding method has been widely used in studies of data assimilation, predictability and instabilities. The bred vectors(BVs), which are the nonlinear difference between the control and perturbed runs, represent the time-evolving rapidly growing errors in dynamic systems. The Lorenz(1963) model(hereafter Lorenz63 model) has chaotic dynamics similar to weather and climate. This study investigates the features of BVs of the Lorenz63 model and its impact on regime prediction of the Lorenz63 model. The results show that the Lorenz63 model has two different BVs for each breeding cycle, and the two BVs approach being identical when growth rate is high. The duration of the current and next regime is associated with the relative directions between the BV with high growth rate and the model trajectory.     

An Observed Connection Between Wintertime Temperature Anomalies over Northwest China and Weather Regime Transitions in North Atlantic

In this study, the association between wintertime temperature anomalies over Northwest China and the weather regime transitions in North Atlantic on synoptic scale is analyzed by using observational surface air temperature(SAT) data and atmospheric reanalysis data. Daily SAT anomaly and duration time are used in order to define SAT anomaly cases. Differences with regard to the circulation anomalies over the Ural Mountains and the upstream North Atlantic area are evident. It is found that the colder than normal SAT is caused by the enhanced Ural high and associated southward flow over Northwest China. Time-lagged composites reveal possible connections between the SAT anomalies and the different development phases of the North Atlantic Oscillation(NAO). The Ural highs tend to be strengthened during the negative phase of NAO(NAO–) to Atlantic ridge transition, which are closely related to the downstream-propagating Rossby wave activity. The opposite circulation patterns are observed in the warm SAT cases. A cyclonic circulation anomaly is distinctly enhanced over the Urals during the positive phase of NAO(NAO+) to Scandinavian blocking transition, which would cause warmer SAT over Northwest China. Further analyses suggest that the intensified zonal wind over North Atlantic would favor the NAO– to Atlantic ridge transition, while the weakened zonal wind may be responsible for the transition between NAO+ and Scandinavian blocking.     

西伯利亚板块东南缘晚古生代伸展体制新证据：东乌旗角闪辉长岩年代学及地球化学研究

为研究西伯利亚板块东南缘晚古生代板内伸展开始时间及地幔属性。基于1∶5万野外宏微观调查,采用LA-MC-ICP-MS锆石U-Pb定年法对分布于东乌旗西部的角闪石辉长岩进行了年龄测定和岩石地球化学测试。结果表明:角闪辉长岩主要由斜长石、角闪石和单斜辉石组成,锆石U-Pb年龄为280.8±1.5Ma,属早二叠世。地球化学数据显示:岩石具较高SiO2(48.87%~53.70%)、TiO2(0.73%~2.27%)、Al2O3(15.05%~16.69%)的含量,中等至较高的MgO(4.84%~9.25%)、FeOT(6.91%~10.47%)和较低的CaO(5.80%~7.94%)。富Na2O(2.75%~3.90%),贫K2O(1.01%~1.90%),为铁质—富铁质碱性和拉斑玄武岩系列岩石组合。稀土总量较高(∑REE为97.50×10-6~251.16×10-6),轻重稀土分异程度中等[(La/Yb)N=4.23~7.12],Eu异常不明显(δEu=0.85~0.98)。岩石富集大离子亲石元素(LILE)Ba、Sr、K等,相对亏损高场强元素(HFSE)Nb、Ta、Th等,高的Zr(87×10-6~289×10-6)和Zr/Y(4.03~7.66)比值,与板内幔源岩浆作用的产物一致。综上,我们认为角闪辉长岩为板内伸展构造体制下富集型地幔橄榄岩部分熔融形成的玄武质岩浆岩浆经分离结晶作用后形成的,标志着~280 Ma西伯利亚板块东南缘晚古生代造山过程进入到板内非造山阶段。     

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

Transpiration is an important component of soil water storage and stream‐flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro‐Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R² = 0·32 and 0·29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200–1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800–2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150–2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600–4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright © 2008 John Wiley & Sons, Ltd.     

Modeled impacts of changes in tundra snow thickness on ground thermal regime and heat flow to the atmosphere in Northernmost Alaska

Seasonal snow covers the tundra surface for up to nine months of each year on the Alaskan North Slope. Variations in the snow thickness could strongly influence the thermal regime of the underlying soil and permafrost, and the surface energy balance. The impacts of increases and decreases in the tundra snow thickness on the thermal regime of snow surface, active layer, and permafrost, and on the conductive heat flow to the atmosphere were investigated numerically, by using an improved surface energy balance approach based one-dimensional heat transfer model. The baseline inputs for the numerical model are mean daily meteorological data and surface albedos collected at Barrow, Alaska from 1995 through 1999. Based on a study for the long-term mean daily maximum and minimum snow thickness distributions at Barrow in the snow season of 1948 through 1997, a snow thickness factor was defined and five simulation cases were run for the snow season of 1997–1998 by changing the snow thickness factor. The modeled results indicate that changes in snow thickness have significant impacts on ground thermal regimes and conductive heat flow to the atmosphere. Decreasing the snow thickness by 50% led to the maximum ground temperature decrease of 1.48 °C at 0.29 m depth, and 0.72 °C at 3.0 m depth; the magnitude of the mean conductive heat flow to the atmosphere for December increase of 4.3 Wm^− 2. Increasing the snow thickness by 50% resulted in the maximum ground temperature increase of 1.44 °C at 0.29 m depth, and 0.66 °C at 3.0 m depth; the magnitude of the mean conductive heat flow to the atmosphere for December decrease of 1.57 W m^− 2. On an annual basis, variation in the snow thickness by 50%, the ground temperature variations of more than 0.25 °C occurred as deep as 8.0 m below the ground surface. The modeled results also show that changes in snow thickness have a relatively small influence on the snow surface temperature.     

How nature uses overland flow regime to maximize equilibrium detention storage and flood attenuation

Equilibrium detention storage is an important parameter as it has a proportional effect on flood attenuation. In this paper, based on the kinematic wave theory, a working formula for the equilibrium detention storage of an overland plane with upstream inflow has been derived. Since the flow regime over a concrete plane can vary throughout the entire range laminar to turbulent, this case has been selected to examine the effect of flow regime on the equilibrium detention storage. In the examination, the derived formula has been applied to four flow regimes: (a) laminar, (b) transitional, (c) near turbulent, and (d) turbulent. The examination shows that for planes with a small discharge, laminar flow gives the maximum detention storage. For planes with a medium discharge, transitional flow gives the maximum detention storage, and for planes with a large discharge, near turbulent flow gives the maximum detention storage. The flow regime can cause more than two‐fold increase in detention storage. All these results can be attributed to the respective flow resistance, and have been endorsed with analyses of the water surface profile and the rising limb of the hydrograph. Finally, relating the results to real‐life situations, it shows that the flow regime that gives the maximum detention storage is also the dominating flow regime in nature. Hence, extraordinarily, the flow regimes that exist in nature in fact provide maximum flood attenuation. Copyright © 2008 John Wiley & Sons, Ltd.     

Matching hydrologic response to measured effective hydraulic conductivity

The objective of this study was to test the practicability of defining hydrologic response units as combinations of soil, land use and topography for modelling infiltration at the hillslope and catchment scales. In an experimental catchment in the East African Highlands (Kwalei, Tanzania), three methods of measuring infiltration were compared for their ability to capture the spatial variability of effective hydraulic conductivity: the constant head (CH) method; the tension infiltration (TI) method; and the mini‐rainfall simulation (RS) method. The three methods yielded different probability distributions of effective hydraulic conductivity and suggested different types of hydrologic response units. Independently from these measurements, the occurrence of infiltration‐excess overland flow was monitored over an area of 6 ha by means of overland flow detectors. The observed pattern of overland flow occurrence did not match any of the patterns suggested by the infiltration measurements. Instead, clusters of spots with overland flow were practically independent from field borders. Geostatistical analysis of the overland flow confirmed the absence of spatial correlation for distances over 40 m. The RS method yielded the pattern closest to the observations, probably because the method simulated better the processes that trigger infiltration‐excess overland flow, i.e. soil sealing and infiltration through macroporosity. The RS hydrologic response unit correlated significantly with observed overland flow frequency. However, the location of clusters and ‘hot spots’ of overland flow remained largely unexplained by land use, soil and topographic variables. It is concluded that using such landscape variables to define hydrologic units may create artificial boundaries that do no correspond to physical realities, especially if the stochastic component within hydrologic units is neglected. Copyright © 2005 John Wiley & Sons, Ltd.     

Rapid simulated hydrologic response within the variably saturated near surface

Column and field experiments have shown that the hydrologic response to increases in rainfall rates can be more rapid than expected from simple estimates. Physics‐based hydrologic response simulation, with the Integrated Hydrology Model (InHM), is used here to investigate rapid hydrologic response, within the variably saturated near surface, to temporal variations in applied flux at the surface boundary. The factors controlling the speed of wetting front propagation are discussed within the Darcy–Buckingham conceptual framework, including kinematic wave approximations. The Coos Bay boundary‐value problem is employed to examine simulated discharge, pressure head, and saturation responses to a large increase in applied surface flux. The results presented here suggest that physics‐based simulations are capable of representing rapid hydrologic response within the variably saturated near surface. The new InHM simulations indicate that the temporal discretization and measurement precision needed to capture the rapid subsurface response to a spike increase in surface flux, necessary for both data‐based analyses and evaluation of physics‐based models, are smaller than the capabilities of the instrumentation deployed at the Coos Bay experimental catchment. Copyright © 2007 John Wiley & Sons, Ltd.     

Simulating hydrologic and hydraulic processes throughout the Amazon River Basin

Presented here is a model framework based on a land surface topography that can be represented with various degrees of resolution and capable of providing representative channel/floodplain hydraulic characteristics on a daily to hourly scale. The framework integrates two models: (1) a water balance model (WBM) for the vertical fluxes and stores of water in and through the canopy and soil layers based on the conservation of mass and energy, and (2) a routing model for the horizontal routing of surface and subsurface runoff and channel and floodplain waters based on kinematic and diffusion wave methodologies. The WBM is driven by satellite‐derived precipitation (TRMM_3B42) and air temperature (MOD08_M3). The model's use of an irregular computational grid is intended to facilitate parallel processing for applications to continental and global scales. Results are presented for the Amazon Basin over the period Jan 2001 through Dec 2005. The model is shown to capture annual runoff totals, annual peaks, seasonal patterns, and daily fluctuations over a range of spatial scales (>1, 000 to < 4·7M km²). For the period of study, results suggest basin‐wide total water storage changes in the Amazon vary by approximately + /? 5 to 10 cm, and the fractional components accounting for these changes are: root zone soil moisture (20%), subsurface water being routed laterally to channels (40%) and channel/floodplain discharge (40%). Annual variability in monthly water storage changes by + /? 2·5 cm is likely due to 0·5 to 1 month variability in the arrival of significant rainfall periods throughout the basin. Copyright © 2009 John Wiley & Sons, Ltd.     

Correlation dimension estimation of hydrological series and data size requirement: myth and reality/Estimation de la dimension de corrélation de séries hydrologiques et taille nécessaire du jeu de données: mythe et réalité

Abstract

The issue of data size (length) requirement for correlation dimension estimation continues to be the nucleus of criticisms on the (low) correlation dimensions reported for hydrological series. The present study addresses this issue from the viewpoints of both the existing theoretical guidelines and the practical reality. For this purpose, correlation dimension analysis is carried out for various data sizes from each of three types of series: (a) stochastic series (artificially generated using a random number generation technique); (b) chaotic series (artificially generated using the Henon map equation); and (c) hydrological series (real flow data observed on the Göta River in Sweden). The outcomes of the analysis of the (artificial) stochastic and chaotic series are used as a basis for interpreting the outcomes of the hydrological series. It is found that reliable dimension results for the stochastic and chaotic series are obtained even when the data size is only a few hundred points (i.e. no underestimation of dimension for small data sizes is visible), with no significant change in the scaling regimes (of the dimension plots) with respect to data size. This implies that the dimension results obtained for the hydrological series even with a few hundred points are also close to the actual ones. The insignificant difference in the scaling regimes for the various data sizes further supports this point. These results lead to the conclusions that: (1) the issue of data size requirement for correlation dimension estimation is more of a myth than reality; (2) the dimension estimates reported thus far for hydrological series could indeed be close to the actual ones (unless influenced by factors other than data size, e.g. delay time, noise, zeros, intermittency).