P. Hazenberg

A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling

Earths terrestrial near-subsurface environment can be divided into relatively porous layers of soil, intact regolith, and sedimentary deposits above unweathered bedrock. Variations in the thicknesses of these layers control the hydrologic and biogeochemical responses of landscapes. Currently, Earth System Models approximate the thickness of these relatively permeable layers above bedrock as uniform globally, despite the fact that their thicknesses vary systematically with topography, climate, and geology. To meet the need for more realistic input data for models, we developed a high-resolution gridded global data set of the average thicknesses of soil, intact regolith, and sedimentary deposits within each 30 arcsec (∼1 km) pixel using the best available data for topography, climate, and geology as input. Our data set partitions the global land surface into upland hillslope, upland valley bottom, and lowland landscape components and uses models optimized for each landform type to estimate the thicknesses of each subsurface layer. On hillslopes, the data set is calibrated and validated using independent data sets of measured soil thicknesses from the U.S. and Europe and on lowlands using depth to bedrock observations from groundwater wells in the U.S. We anticipate that the data set will prove useful as an input to regional and global hydrological and ecosystems models.

Radar rainfall estimation of stratiform winter precipitation in the Belgian Ardennes

[1]xa0Radars are known for their ability to obtain a wealth of information about spatial storm field characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar rainfall estimates starts to decrease at relatively close ranges. In the current study, the hydrological potential of weather radar is analyzed during a winter half-year for the hilly region of the Belgian Ardennes. A correction algorithm is proposed which corrects the radar data for errors related to attenuation, ground clutter, anomalous propagation, the vertical profile of reflectivity (VPR), and advection. No final bias correction with respect to rain gauge data was implemented because such an adjustment would not add to a better understanding of the quality of the radar data. The impact of the different corrections is assessed using rainfall information sampled by 42 hourly rain gauges. The largest improvement in the quality of the radar data is obtained by correcting for ground clutter. The impact of VPR correction and advection depends on the spatial variability and velocity of the precipitation system. Overall during the winter period, the radar underestimates the amount of precipitation as compared to the rain gauges. Remaining differences between both instruments can be attributed to spatial and temporal variability in the type of precipitation, which has not been taken into account.

Global Multimodel Analysis of Drought in Runoff for the Second Half of the Twentieth Century

During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on a global scale. A multimodel ensemble analysis was carried outtoevaluate if 10 such large-scale models agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runofffrom 10 global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures.

A hybrid-3D hillslope hydrological model for use in Earth system models

Hillslope-scale rainfall-runoff processes leading to a fast catchment response are not explicitly included in land surface models (LSMs) for use in earth system models (ESMs) due to computational constraints. This study presents a hybrid-3D hillslope hydrological model (h3D) that couples a 1-D vertical soil column model with a lateral pseudo-2D saturated zone and overland flow model for use in ESMs. By representing vertical and lateral responses separately at different spatial resolutions, h3D is computationally efficient. The h3D model was first tested for three different hillslope planforms (uniform, convergent and divergent). We then compared h3D (with single and multiple soil columns) with a complex physically based 3-D model and a simple 1-D soil moisture model coupled with an unconfined aquifer (as typically used in LSMs). It is found that simulations obtained by the simple 1-D model vary considerably from the complex 3-D model and are not able to represent hillslope-scale variations in the lateral flow response. In contrast, the single soil column h3D model shows a much better performance and saves computational time by 2-3 orders of magnitude compared with the complex 3-D model. When multiple vertical soil columns are implemented, the resulting hydrological responses (soil moisture, water table depth, and base flow along the hillslope) from h3D are nearly identical to those predicted by the complex 3-D model, but still saves computational time. As such, the computational efficiency of the h3D model provides a valuable and promising approach to incorporating hillslope-scale hydrological processes into continental and global-scale ESMs.

Testing the hybrid‐3‐D hillslope hydrological model in a controlled environment

Hillslopes are important for converting rainfall into runoff, influencing the terrestrial dynamics of the Earths climate system. Recently, we developed a hybrid-3-D (h3D) hillslope hydrological model that gives similar results as a full 3-D hydrological model but is up to 2–3 orders of magnitude faster computationally. Here h3D is assessed using a number of recharge-drainage experiments within the Landscape Evolution Observatory (LEO) with accurate and high-resolution (both temporally and spatially) observations of the inputs, outputs, and storage dynamics of several hillslopes. Such detailed measurements are generally not available for real-world hillslopes. Results show that the h3D model captures the observed storage, base flow, and overland flow dynamics of both the larger LEO and the smaller miniLEO hillslopes very well. Sensitivity tests are also performed to understand h3Ds difficulty in representing the height of the saturated zone close to the seepage face of the miniLEO hillslope. Results reveal that a temporally constant parameters set is able to simulate the response of the miniLEO for each individual event. However, when one focuses on the saturated zone dynamics at 0.15 m from the seepage face, a stepwise evolution of the optimal model parameter for the saturated lateral conductivity parameter of the gravel layer occurs. This evolution might be related to the migration of soil particles within the hillslope. However, it is currently unclear whether and where this takes place (in the seepage face or within the parts of the loamy sand soil).

Implementing and Evaluating Variable Soil Thickness in the Community Land Model, Version 4.5 (CLM4.5)

This work was supported by DOE (DE-SC0006773), NASA (NNX13AK82A), and NSF (AGS-0944101). L. R. Leung was supported by the DOE Office of Science Biological and Environmental Research Earth System Modeling program. Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. We thank the Jet Propulsion Laboratory for providing the GRACE data, which were processed by Sean Swenson under support from the NASA MEaSUREs Program. High-performance computing support was provided by NCARs Computational and Information Systems Laboratory, sponsored by the National Science Foundation, through computing time on Yellowstone (http://n2t.net/ark:/85065/d7wd3xhc) and on The University of Arizona Research Computing

Unified Formulation of Single- and Multimoment Normalizations of the Raindrop Size Distribution Based on the Gamma Probability Density Function

AbstractThis study offers a unified formulation of single- and multimoment normalizations of the raindrop size distribution (DSD), which have been proposed in the framework of scaling analyses in the literature. The key point is to consider a well-defined “general distribution” g(x) as the probability density function (pdf) of the raindrop diameter scaled by a characteristic diameter Dc. The two-parameter gamma pdf is used to model the g(x) function. This theory is illustrated with a 3-yr DSD time series collected in the Cevennes region, France. It is shown that three DSD moments (M2, M3, and M4) make it possible to satisfactorily model the DSDs, both for individual spectra and for time series of spectra. The formulation is then extended to the one- and two-moment normalization by introducing single and dual power-law models. As compared with previous scaling formulations, this approach explicitly accounts for the prefactors of the power-law models to yield a unique and dimensionless g(x), whatever the sc...

A Hydrometeorological Perspective on the Karakoram Anomaly Using Unique Valley-Based Synoptic Weather Observations

Glaciers in the eastern Hindukush, western Karakoram and northwestern Himalayan mountain ranges of Northern Pakistan are not responding to global warming in the same manner as their counterparts elsewhere. Their retreat rates are less than the global average, and some are either stable or growing. Various investigations have questioned the role of climatic factors in regards to this anomalous behavior, widely referred to as ‘The Karakoram Anomaly’. Here, for the first time, we present a hydro-meteorological perspective based on five decades of synoptic weather observations collected by the meteorological network of Pakistan. Analysis of this unique data set indicates that increased regional scale humidity, cloud cover, and precipitation, along with decreased net radiation, near-surface wind speed, potential evapotranspiration and river flow, especially during the summer season, represent a substantial change in the energy, mass and momentum fluxes that are facilitating the establishment of the Karakoram Anomaly.