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1.
The Noah model is a land surface model of the National Centers for Environmental Prediction. It has been widely used in regional coupled weather and climate models (i.e. Weather Research and Forecasting Model, Eta Mesoscale Model) and global coupled weather and climate models (i.e. National Centers for Environmental Prediction Global Forecast System, Climate Forecast System). Therefore, its continued improvement and development are keys to enhancing our weather and climate forecast ability and water and energy flux simulation accuracy. North American Land Data Assimilation System phase 1 (NLDAS‐1) experiments indicated that the Noah model exhibited substantial bias in latent heat flux, total runoff and land skin temperature during the warm season, and such bias can significantly affect coupled weather and climate models. This paper presents a study to improve the Noah model by adding model parameterization processes such as including seasonal factor on leaf area index and root distribution and selecting optimal model parameters. We compared simulated latent heat flux, mean annual runoff and land skin temperature from the Noah control and test versions with measured latent heat flux, land surface skin temperature, mean annual runoff and satellite‐retrieved land surface skin temperature. The results show that the test version significantly reduces biases in latent heat, total runoff and land skin temperature simulation. The test version has been used for the NLDAS phase 2 (NLDAS‐2) to produce 30‐year water flux, energy flux and state variable products to support the US drought monitor of National Integrated Drought Information System. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

2.
The North American Land Data Assimilation System project phase 2 (NLDAS‐2) has run four land surface models for a 30‐year (1979–2008) retrospective period. Land surface evapotranspiration (ET) is one of the most important model outputs from NLDAS‐2 for investigating land–atmosphere interaction or to monitor agricultural drought. Here, we evaluate hourly ET using in situ observations over the Southern Great Plains (Atmospheric Radiation Measurement/Cloud and Radiation Testbed network) for 1 January 1997–30 September 1999 and daily ET u‐sing in situ observations at the AmeriFlux network over the conterminous USA for an 8‐year period (2000–2007). The NLDAS‐2 models compare well against observations, with the National Centers for Environmental Prediction's Noah land surface model performing best, followed, in order, by the Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic models. Daily evaluation across the AmeriFlux network shows that for all models, performance depends on season and vegetation type; they do better in spring and fall than in winter or summer and better for deciduous broadleaf forest and grasslands than for croplands or evergreen needleleaf forest. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

3.
This study reports results from an analysis of the relationship between atmospheric forcing and model‐simulated water and energy fluxes for the North American Land Data Assimilation System Project Phase 2 (NLDAS‐2). The relationships between mean monthly precipitation and total runoff are stronger in the Sacramento (SAC) and variable infiltration capacity (VIC) models, which grew out of the hydrological community, than in the Noah and Mosaic models, which grew out of the soil‐vegetation‐atmosphere transfer (SVAT) community. The reverse is true for the relationship between mean monthly precipitation and evapotranspiration. In addition, surface energy fluxes in VIC are less sensitive to model forcing (except for air temperature) than those in the Noah and Mosaic model. Notwithstanding these general conclusions, the relationships between forcings and model‐simulated water and energy fluxes for all models vary for different seasons, variables, and regions. These findings will ultimately inspire a combination of SVAT‐type model energy components with hydrological model water components to develop a SVAT‐hydrology model to improve both evapotranspiration and total runoff simulations. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

4.
To improve simulations of regional‐scale snow processes and related cold‐season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth‐generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land‐surface model. One important cause for the underestimated SWE in Noah is its unrealistic land‐surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow‐season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near‐surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over‐predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5–CLM3 due to the lower evaporation resulting from the longer snow duration. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

5.
Land surface albedo plays an important role in the radiation budget and global climate models. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) provide 16‐day albedo product with 500‐m resolution every 8 days (MCD43A3). Some in‐situ albedo measurements were used as the true surface albedo values to validate the MCD43A3 product. As the 16‐day MODIS albedo retrievals do not include snow observations when there is ephemeral snow on the ground surface in a 16‐day period, comparisons between MCD43A3 and 16 day averages of field data do not agree well. Another reason is that the MODIS cannot detect the snow when the area is covered by clouds. The Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) data are not affected by weather conditions and are a good supplement for optical remote sensing in cloudy weather. When the surface is covered by ephemeral snow, the AMSR‐E data can be used as the additional information to retrieve the snow albedo. In this study, we developed an improved method by using the MODIS products and the AMSR‐E snow water equivalent (SWE) product to improve the MCD43A3 short‐time snow‐covered albedo estimation. The MODIS daily snow products MOD10A1 and MYD10A1 both provide snow and cloud information from observations. In our study region, we updated the MODIS daily snow product by combining MOD10A1 and MYD10A1. Then, the product was combined with the AMSR‐E SWE product to generate new daily snow‐cover and SWE products at a spatial resolution of 500 m. New SWE datasets were integrated into the Noah Land Surface Model snow model to calculate the albedo above a snow surface, and these values were then utilized to improve the MODIS 16‐day albedo product. After comparison of the results with in‐situ albedo measurements, we found that the new corrected 16‐day albedo can show the albedo changes during the short snowfall season. For example, from January 25 to March 14, 2007 at the BJ site, the albedo retrieved from snow‐free observations does not indicate the albedo changes affected by snow; the improved albedo conforms well to the in‐situ measurements. The correlation coefficient of the original MODIS albedo and the in‐situ albedo is 0.42 during the ephemeral snow season, but the correlation coefficient of the improved MODIS albedo and the in‐situ albedo is 0.64. It is concluded that the new method is capable of capturing the snow information from AMSR‐E SWE to improve the short‐time snow‐covered albedo estimation. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

6.
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7.
Recently, an effective and powerful approach for simulating seismic wave propagation in elastic media with an irregular free surface was proposed. However, in previous studies, researchers used the periodic condition and/or sponge boundary condition to attenuate artificial reflections at boundaries of a computational domain. As demonstrated in many literatures, either the periodic condition or sponge boundary condition is simple but much less effective than the well‐known perfectly matched layer boundary condition. In view of this, we intend to introduce a perfectly matched layer to simulate seismic wavefields in unbounded models with an irregular free surface. We first incorporate a perfectly matched layer into wave equations formulated in a frequency domain in Cartesian coordinates. We then transform them back into a time domain through inverse Fourier transformation. Afterwards, we use a boundary‐conforming grid and map a rectangular grid onto a curved one, which allows us to transform the equations and free surface boundary conditions from Cartesian coordinates to curvilinear coordinates. As numerical examples show, if free surface boundary conditions are imposed at the top border of a model, then it should also be incorporated into the perfectly matched layer imposed at the top‐left and top‐ right corners of a 2D model where the free surface boundary conditions and perfectly matched layer encounter; otherwise, reflections will occur at the intersections of the free surface and the perfectly matched layer, which is confirmed in this paper. So, by replacing normal second derivatives in wave equations in curvilinear coordinates with free surface boundary conditions, we successfully implement the free surface boundary conditions into the perfectly matched layer at the top‐left and top‐right corners of a 2D model at the surface. A number of numerical examples show that the perfectly matched layer constructed in this study is effective in simulating wave propagation in unbounded media and the algorithm for implementation of the perfectly matched layer and free surface boundary conditions is stable for long‐time wavefield simulation on models with an irregular free surface.  相似文献   

8.
The performance of temperature‐index melt models is particularly affected by the choice of near‐surface lapse rate used to determine the sum of positive daily temperatures at different elevations, and by the choice of factor used to relate this sum to the rate of melting. Data from the Langjökull ice cap are used in this study to quantify the influence of lapse‐rate and degree‐day factor variation on temperature‐index melt simulations. The lapse rate was significantly lower during summer than in spring or autumn, as a result of diabatic cooling, reducing boundary‐layer sensitivity to free‐air temperature change. The summer lapse rate was also significantly lower than the saturated adiabatic lapse rate. A sensitivity of approximately 600 mm water equivalent (w.e.) cumulative June–August melt per 0.1 °C 100 m–1 change in lapse rate was found across a 500‐m altitude range. The sensitivity to a 1‐mm w.e. °C–1 day–1 change in degree‐day factors varied more: from approximately 500 mm w.e. cumulative summer melt at low elevation to approximately 200 mm w.e. at high elevation, reflecting the decline in melt rates associated with the greater persistence of snow with increasing altitude. The determination of a degree‐day factor for snow is complicated by the densification of the ageing snowpack, but the application of a parameterization for near‐surface density on the basis of albedo helped account for the development of snow water equivalence. Lapse rate was parameterized as a function of standardized anomalies in 750 hPa reanalysis temperature and significantly improved the simulation of cumulative summer melt compared with models applying the saturated adiabatic lapse rate. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

9.
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10.
Rain‐on‐snow events have generated major floods around the world, particularly in coastal, mountainous regions. Most previous studies focused on a limited number of major rain‐on‐snow events or were based primarily on model results, largely due to a lack of long‐term records from lysimeters or other instrumentation for quantifying event water balances. In this analysis, we used records from five automated snow pillow sites in south coastal British Columbia, Canada, to reconstruct event water balances for 286 rain‐on‐snow events over a 10‐year period. For large rain‐on‐snow events (event rainfall >40 mm), snowmelt enhanced the production of water available for run‐off (WAR) by approximately 25% over rainfall alone. For smaller events, a range of antecedent and meteorological factors influenced WAR generation, particularly the antecedent liquid water content of the snowpack. Most large events were associated with atmospheric rivers. Rainfall dominated WAR generation during autumn and winter events, whereas snowmelt dominated during spring and summer events. In the majority of events, the sensible heat of rain contributed less than 10% of the total energy consumed by snowmelt. This analysis illustrated the importance of understanding the amount of rainfall occurring at high elevations during rain‐on‐snow events in mountainous regions.  相似文献   

11.
Using a coupled large‐eddy simulation–land surface model framework, the impact of two‐dimensional soil moisture heterogeneity on the cloudy boundary layer under varied free‐atmosphere stabilities is investigated. Specifically, the impacts of soil moisture heterogeneity length scale and heterogeneity in terms of soil moisture gradients on micrometeorological states, surface fluxes, boundary layer characteristics, and cloud development are examined. The results show that mesoscale circulations due to surface heterogeneity in soil moisture play an important role in transferring water vapour within the boundary layer and in regulating cloud distribution at the entrainment zone, which, in turn, provides feedbacks on boundary layer/surface energy budgets. The initial domain‐averaged soil moisture is identical for all homogenous and heterogeneous cases; however, the soil moisture heterogeneity in gradient and length scale between dry and wet regions has a significant impact on the estimates of near‐surface micrometeorological properties and surface fluxes, which further affect the boundary layer states and characteristics. Both liquid water potential temperature and liquid water mixing ratio increase with an increasing soil moisture gradient, whereas the amount of specific humidity decreases. Heterogeneity length scale and free atmosphere stability also amplify these impacts on the boundary layer structure and cloud formation. In a low atmospheric stability condition that potentially allows for a deeper boundary layer and a higher entrainment rate, cloud base height and cloud thickness significantly increase as the soil moisture gradient and length scale increase. Analysis to differentiate the influences of surface heterogeneity type (i.e. length scale vs gradient) shows that in general soil moisture gradient provides a larger impact than heterogeneity length scale, although the heterogeneity length scale is large enough to initiate circulation features responsible for differences in the coupled system between homogeneous and heterogeneous soil moisture cases. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

12.
Dennis G. Dye 《水文研究》2002,16(15):3065-3077
This study investigated variability and trends in the annual snow‐cover cycle in regions covering high‐latitude and high‐elevation land areas in the Northern Hemisphere. The annual snow‐cover cycle was examined with respect to the week of the last‐observed snow cover in spring (WLS), the week of the first‐observed snow cover in autumn (WFS), and the duration of the snow‐free period (DSF). The analysis used a 29‐year time‐series (1972–2000) of weekly, visible‐band satellite observations of Northern Hemisphere snow cover from NOAA with corrections applied by D. Robinson of Rutgers University Climate Laboratory. Substantial interannual variability was observed in WLS, WFS and DSF (standard deviations of 0·8–1·1, 0·7–0·9 and 1·0–1·4 weeks, respectively), which is related directly to interannual variability in snow‐cover area in the regions and time periods of snow‐cover transition. Over the nearly three‐decade study period, WLS shifted earlier by 3–5 days/decade as determined by linear regression analysis. The observed shifts in the annual snow‐cover cycle underlie a significant trend toward a longer annual snow‐free period. The DSF increased by 5–6 days/decade over the study period, primarily as a result of earlier snow cover disappearance in spring. The observed trends are consistent with reported trends in the timing and length of the active growing season as determined from satellite observations of vegetation greenness and the atmospheric CO2 record. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

13.
High‐resolution snow depth (SD) maps (1 × 1 m) obtained from terrestrial laser scanner measurements in a small catchment (0.55 km2) in the Pyrenees were used to assess small‐scale variability of the snowpack at the catchment and sub‐grid scales. The coefficients of variation are compared for various plot resolutions (5 × 5, 25 × 25, 49 × 49, and 99 × 99 m) and eight different days in two snow seasons (2011–2012 and 2012–2013). We also studied the relation between snow variability at the small scale and SD, topographic variables, small‐scale variability in topographic variables. The results showed that there was marked variability in SD, and it increased with increasing scales. Days of seasonal maximum snow accumulation showed the least small‐scale variability, but this increased sharply with the onset of melting. The coefficient of variation (CV) in snowpack depth showed statistically significant consistency amongst the various spatial resolutions studied, although it declined progressively with increasing difference between the grid sizes being compared. SD best explained the spatial distribution of sub‐grid variability. Topographic variables including slope, wind sheltering, sub‐grid variability in elevation, and potential incoming solar radiation were also significantly correlated with the CV of the snowpack, with the greatest correlation occurring at the 99 × 99 m resolution. At this resolution, stepwise multiple regression models explained more than 70% of the variance, whereas at the 25 × 25 m resolution they explained slightly more than 50%. The results highlight the importance of considering small‐scale variability of the SD for comprehensively representing the distribution of snowpack from available punctual information, and the potential for using SD and other predictors to design optimized surveys for acquiring distributed SD data. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

14.
For a patchy snow cover the advective heat transport and the near-surface boundary layer decoupling, which have an opposite effect on sensible heat transport onto the snow surface, are both expected to increase in magnitude. The main aim of this study is to investigate the effects of locally developing atmospheric stratification over a discontinuous snow cover which can result in a decoupling from the warm atmosphere. We are particularly interested in the effect of boundary layer decoupling on the net sensible heat flux into the snow. We therefore applied local eddy flux measurements over snow patches at three different heights above the snow surface. We identified wind velocity, turbulence intensity, fetch distance and topographical curvature as the main factors driving the boundary layer depth and the efficiency of advective heat transport to contribute to snow ablation. The atmospheric decoupling is thus shown to be a key mechanism in snow patch survival.  相似文献   

15.
In the Great Lakes basin of North America, annual run‐off is dominated by snowmelt. This snowmelt‐induced run‐off plays an important role within the hydrologic cycle of the basin, influencing soil moisture availability and driving the seasonal cycle of spring and summer lake levels. Despite this, relatively little is understood about the patterns and trends of snow ablation event frequency and magnitude within the Great Lakes basin. This study uses a gridded dataset of Canadian and United States surface snow depth observations to develop a regional climatology of snow ablation events from 1960 to 2009. An ablation event is defined as an interdiurnal snow depth decrease within an individual grid cell. A clear seasonal cycle in ablation event frequency exists within the basin and peak ablation event probability is latitudinally dependent. Most of the basin experiences peak ablation frequency in March, while the northern and southern regions of the basin experience respective peaks in April and February. An investigation into the interannual frequency of ablation events reveals ablation events significantly decrease within the northeastern and northwestern Lake Superior drainage basins and significantly increase within the eastern Lake Huron and Georgian Bay drainage basins. In the eastern Lake Huron and Georgian Bay drainage basins, larger ablation events are occurring more frequently, and a larger impact to the hydrology can be expected. Trends in ablation events are attributed primarily to changes in snowfall and snow depth across the region.  相似文献   

16.
Comprehensive snow depth data, collected using georadar and hand probing, were used for statistical analyses of snow depths inside 1 km grid cells. The sub‐grid cell spatial scale was 100 m. Statistical distribution functions were found to have varying parameters, and an attempt was made to connect these statistical parameters to different terrain variables. The results showed that the two parameters mean and standard deviation of snow depth were significantly related to the sub‐grid terrain characteristics. Linear regression models could explain up to 50% of the variation for both of the snowcover parameters mentioned. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

17.
Taking the Northern Xinjiang region as an example, we develop a snow depth model by using the Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E) horizontal and vertical polarization brightness temperature difference data of 18 and 36 GHz bands and in situ snow depth measurements from 20 climatic stations during the snow seasons November–March) of 2002–2005. This article proposes a method to produce new 5‐day snow cover and snow depth images, using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products and AMSR‐E snow water equivalent and daily brightness temperature products. The results indicate that (1) the brightness temperature difference (Tb18h–Tb36h) provides the most accurate and precise prediction of snow depth; (2) the snow, land and overall classification accuracies of the new images are separately 89.2%, 77.7% and 87.2% and are much better than those of AMSR‐E or MODIS products (in all weather conditions) alone; (3) the snow classification accuracy increases as snow depth increases; and (4) snow accuracies for different land cover types vary as 88%, 92.3%, 79.7% and 80.1% for cropland, grassland, shrub, and urban and built‐up, respectively. We conclude that the new 5‐day snow cover–snow depth images can provide both accurate cloud‐free snow cover extent and the snow depth dynamics, which would lay a scientific basis for water management and prevention of snow‐related disasters in this dry and cold pastoral area. After validations of the algorithms over other regions with different snow and climate conditions, this method would also be used for monitoring snow cover and snow depth elsewhere in the world. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

18.
Reliable estimation of the volume and timing of snowmelt runoff is vital for water supply and flood forecasting in snow‐dominated regions. Snowmelt is often simulated using temperature‐index (TI) models due to their applicability in data‐sparse environments. Previous research has shown that a modified‐TI model, which uses a radiation‐derived proxy temperature instead of air temperature as its surrogate for available energy, can produce more accurate snow‐covered area (SCA) maps than a traditional TI model. However, it is unclear whether the improved SCA maps are associated with improved snow water equivalent (SWE) estimation across the watershed or improved snowmelt‐derived streamflow simulation. This paper evaluates whether a modified‐TI model produces better streamflow estimates than a TI model when they are used within a fully distributed hydrologic model. It further evaluates the performance of the two models when they are calibrated using either point SWE measurements or SCA maps. The Senator Beck Basin in Colorado is used as the study site because its surface is largely bedrock, which reduces the role of infiltration and emphasizes the role of the SWE pattern on streamflow generation. Streamflow is simulated using both models for 6 years. The modified‐TI model produces more accurate streamflow estimates (including flow volume and peak flow rate) than the TI model, likely because the modified‐TI model better reproduces the SWE pattern across the watershed. Both models also produce better performance when calibrated with SCA maps instead of point SWE data, likely because the SCA maps better constrain the space‐time pattern of SWE.  相似文献   

19.
We report a methodology for reconstructing the daily snow depth distribution at high spatial resolution in a small Pyrenean catchment using time‐lapse photographs and snow depletion rates derived from an on‐site measuring meteorological station. The results were compared with the observed snow depth distribution, determined on a number of separate occasions using a terrestrial laser scanner (TLS). The time‐lapse photographs were projected onto a digital elevation model of the study site, and converted into snow presence/absence information. The melt‐out date (MOD; first occurrence of melt out after peak snow accumulation) was obtained from the projected photograph series. Commencing the backward reconstruction for each grid cell at the MOD, the method uses simulated snow depth depletion rates using a temperature index approach, which are extrapolated to the grid cells of the domain to arrive at the snow distribution of the previous day. Two variants of the reconstruction techniques were applied (1) using a spatially constant degree day factor (DDF) for calculating the daily expected snow depth depletion rate, and (2) allowing a spatially distributed DDF calculated from two consecutive TLS acquisitions compared to the snow depth depletion rate observed at the meteorological station. Validation revealed that both methods performed well (average R2 = 0.68; standard RMSE = 0.58), with better results obtained from the spatially distributed approach. Nevertheless, the spatially corrected DDF reconstruction, which requires TLS data, suggests that the constant DDF approach is an efficient, and for most applications sufficiently accurate and easily reproducible method. The results highlight the usefulness of time‐lapse photography for not only determining the snow covered area, but also for estimating the spatial distribution of snow depth. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

20.
Finite‐difference frequency‐domain modelling of seismic wave propagation is attractive for its efficient solution of multisource problems, and this is crucial for full‐waveform inversion and seismic imaging, especially in the three‐dimensional seismic problem. However, implementing the free surface in the finite‐difference method is nontrivial. Based on an average medium method and the limit theorem, we present an adaptive free‐surface expression to describe the behaviour of wavefields at the free surface, and no extra work for the free‐surface boundary condition is needed. Essentially, the proposed free‐surface expression is a modification of density and constitutive relation at the free surface. In comparison with a direct difference approximate method of the free‐surface boundary condition, this adaptive free‐surface expression can produce more accurate and stable results for a broad range of Poisson's ratio. In addition, this expression has a good performance in handling the lateral variation of Poisson's ratio adaptively and without instability.  相似文献   

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