Guo Yue Niu

The common land model

The Common Land Model (CLM) was developed for community use by a grassroots collaboration of scientists who have an interest in making a general land model available for public use and further development. The major model characteristics include enough unevenly spaced layers to adequately represent soil temperature and soil moisture, and a multilayer parameterization of snow processes; an explicit treatment of the mass of liquid water and ice water and their phase change within the snow and soil system; a runoff parameterization following the TOPMODEL concept; a canopy photo synthesis-conductance model that describes the simultaneous transfer of CO2 and water vapor into and out of vegetation; and a tiled treatment of the subgrid fraction of energy and water balance. CLM has been extensively evaluated in offline mode and coupling runs with the NCAR Community Climate Model (CCM3). The results of two offline runs, presented as examples, are compared with observations and with the simulation of three other la...

The community Noah land surface model with multiparameterization options (Noah‐MP): 1. Model description and evaluation with local‐scale measurements

[1] This first paper of the two‐part series describes the objectives of the community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah‐MP). The Noah‐MP’s performance is evaluated at various local sites using high temporal frequency data sets, and results show the advantages of using multiple optional schemes to interpret the differences in modeling simulations. The second paper focuses on ensemble evaluations with long‐term regional (basin) and global scale data sets. The enhanced conceptual realism includes (1) the vegetation canopy energy balance, (2) the layered snowpack, (3) frozen soil and infiltration, (4) soil moisture‐groundwater interaction and related runoff production, and (5) vegetation phenology. Sample local‐scale validations are conducted over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site, the W3 catchment of Sleepers River, Vermont, and a French snow observation site. Noah‐MP shows apparent improvements in reproducing surface fluxes, skin temperature over dry periods, snow water equivalent (SWE), snow depth, and runoff over Noah LSM version 3.0. Noah‐MP improves the SWE simulations due to more accurate simulations of the diurnal variations of the snow skin temperature, which is critical for computing available energy for melting. Noah‐MP also improves the simulation of runoff peaks and timing by introducing a more permeable frozen soil and more accurate simulation of snowmelt. We also demonstrate that Noah‐MP is an effective research tool by which modeling results for a given process can be interpreted through multiple optional parameterization schemes in the same model framework.

Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data

Received 17 May 2006; revised 24 October 2006; accepted 26 December 2006; published 7 April 2007. [1] Groundwater interacts with soil moisture through the exchanges of water between the unsaturated soil and its underlying aquifer under gravity and capillary forces. Despite its importance, groundwater is not explicitly represented in climate models. This paper developed a simple groundwater model (SIMGM) by representing recharge and discharge processes of the water storage in an unconfined aquifer, which is added as a single integration element below the soil of a land surface model. We evaluated the model against the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage change (DS) data. The modeled total water storage (including unsaturated soil water and groundwater) change agrees fairly well with GRACE estimates. The anomaly of the modeled groundwater storage explains most of the GRACE DS anomaly in most river basins where the water storage is not affected by snow water or frozen soil. For this reason, the anomaly of the modeled water table depth agrees well with that converted from the GRACE DS in most of the river basins. We also investigated the impacts of groundwater dynamics on soil moisture and evapotranspiration through the comparison of SIMGM to an additional model run using gravitational free drainage (FD) as the model’s lower boundary condition. SIMGM produced much wetter soil profiles globally and up to 16% more annual evapotranspiration than FD, most obviously in arid-to-wet transition regions.

The Rhône-Aggregation Land Surface Scheme Intercomparison Project: An Overview

The Rhone-Aggregation (Rhone-AGG) Land Surface Scheme (LSS) intercomparison project is an initiative within the Global Energy and Water Cycle Experiment (GEWEX)/Global Land-Atmosphere System Study (GLASS) panel of the World Climate Research Programme (WCRP). It is a intermediate step leading up to the next phase of the Global Soil Wetness Project (GSWP) (Phase 2), for which there will be a broader investigation of the aggregation between global scales (GSWP-1) and the river scale. This project makes use of the Rhone modeling system, which was developed in recent years by the French research community in order to study the continental water cycle on a regional scale. The main goals of this study are to investigate how 15 LSSs simulate the water balance for several annual cycles compared to data from a dense observation network consisting of daily discharge from over 145 gauges and daily snow depth from 24 sites, and to examine the impact of changing the spatial scale on the simulations. The overall evapotranspiration, runoff, and monthly change in water storage are similarly simulated by the LSSs, however, the differing partitioning among the fluxes results in very different river discharges and soil moisture equilibrium states. Subgrid runoff is especially important for discharge at the daily timescale and for smaller-scale basins. Also, models using an explicit treatment of the snowpack compared better with the observations than simpler composite schemes. Results from a series of scaling experiments are examined for which the spatial resolution of the computational grid is decreased to be consistent with large-scale atmospheric models. The impact of upscaling on the domain-averaged hydrological components is similar among most LSSs, with increased evaporation of water intercepted by the canopy and a decrease in surface runoff representing the most consistent inter-LSS responses. A significant finding is that the snow water equivalent is greatly reduced by upscaling in all LSSs but one that explicitly accounts for subgrid-scale orography effects on the atmospheric forcing.

Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 1: Experiment description and summary intercomparisons

Abstract Twenty-one land-surface schemes (LSSs) participated in the Project for Intercomparison of Land-surface Parameterizations (PILPS) Phase 2(e) experiment, which used data from the Torne–Kalix Rivers in northern Scandinavia. Atmospheric forcing data (precipitation, air temperature, specific humidity, wind speed, downward shortwave and longwave radiation) for a 20-year period (1979–1998) were provided to the 21 participating modeling groups for 218 1/4° grid cells that represented the study domain. The first decade (1979–1988) of the period was used for model spin-up. The quality of meteorologic forcing variables is of particular concern in high-latitude experiments and the quality of the gridded dataset was assessed to the extent possible. The lack of sub-daily precipitation, underestimation of true precipitation and the necessity to estimate incoming solar radiation were the primary data concerns for this study. The results from two of the three types of runs are analyzed in this, the first of a three-part paper: (1) calibration–validation runs—calibration of model parameters using observed streamflow was allowed for two small catchments (570 and 1300 km2), and parameters were then transferred to two other catchments of roughly similar size (2600 and 1500 km2) to assess the ability of models to represent ungauged areas elsewhere; and 2) reruns—using revised forcing data (to resolve problems with apparent underestimation of solar radiation of approximately 36%, and certain other problems with surface wind in the original forcing data). Model results for the period 1989–1998 are used to evaluate the performance of the participating land-surface schemes in a context that allows exploration of their ability to capture key processes spatially. In general, the experiment demonstrated that many of the LSSs are able to capture the limitations imposed on annual latent heat by the small net radiation available in this high-latitude environment. Simulated annual average net radiation varied between 16 and 40 W/m2 for the 21 models, and latent heat varied between 18 and 36 W/m2. Among-model differences in winter latent heat due to the treatment of aerodynamic resistance appear to be at least as important as those attributable to the treatment of canopy interception. In many models, the small annual net radiation forced negative sensible heat on average, which varied among the models between −11 and 9 W/m2. Even though the largest evaporation rates occur in the summer (June, July and August), model-predicted snow sublimation in winter has proportionately more influence on differences in annual runoff volume among the models. A calibration experiment for four small sub-catchments of the Torne–Kalix basin showed that model parameters that are typically adjusted during calibration, those that control storage of moisture in the soil column or on the land surface via ponding, influence the seasonal distribution of runoff, but have relatively little impact on annual runoff ratios. Similarly, there was no relationship between annual runoff ratios and the proportion of surface and subsurface discharge for the basin as a whole.

2005 drought event in the Amazon River basin as measured by GRACE and estimated by climate models

[1] Satellite gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) provide new quantitative measures of the 2005 extreme drought event in the Amazon river basin, regarded as the worst in over a century. GRACE measures a significant decrease in terrestrial water storage (TWS) in the central Amazon basin in the summer of 2005, relative to the average of the 5 other summer periods in the GRACE era. In contrast, data-assimilating climate and land surface models significantly underestimate the drought intensity. GRACE measurements are consistent with accumulated precipitation data from satellite remote sensing and are also supported by in situ water-level data from river gauge stations. This study demonstrates the unique potential of satellite gravity measurements in monitoring large-scale severe drought and flooding events and in evaluating advanced climate and land surface models.

Simulation of high latitude hydrological processes in the Torne–Kalix basin: PILPS Phase 2(e): 2: Comparison of model results with observations

Model results from 21 land-surface schemes (LSSs) designed for use in numerical weather prediction and climate models are compared with each other and with observations in the context of the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) Phase 2(e) model intercomparison experiment. This experiment focuses on simulations of land-surface water and energy fluxes in the 58,000-km2 Torne and Kalix river systems in northern Scandinavia, during the period 1989–1998. All models participating in PILPS Phase 2(e) capture the broad dynamics of snowmelt and runoff, but large differences in snow accumulation and ablation, turbulent heat fluxes, and streamflow exist. The greatest among-model differences in energy and moisture fluxes in these high-latitude environments occur during the spring snowmelt period, reflecting different model parameterizations of snow processes. Differences in net radiation are governed by differences in the simulated radiative surface temperature during the winter months and by differences in surface albedo during the spring/early summer. Differences in net radiation are smallest during the late summer when snow is absent. Although simulated snow sublimation is small for most models, a few models show annual snow sublimation of about 100 mm. These differences in snow sublimation appear to be largely dependent on differences in snow surface roughness parameterizations. The models with high sublimation generally lose their snowpacks too early compared to observations and underpredict the annual runoff. Differences in runoff parameterizations are reflected in differences in daily runoff statistics. Although most models show a greater variability in daily streamflow than the observations, the models with the greatest variability (as much as double the observed variability), produce most of their runoff through fast response, surface runoff mechanisms. As a group, those models that took advantage of an opportunity to calibrate to selected small catchments and to transfer calibration results to the basin at large had a smaller bias and root mean squared error (RMSE) in daily streamflow simulations compared with the models that did not calibrate.

Impacts of vegetation and groundwater dynamics on warm season precipitation over the Central United States

becomes more discernable after 1 month. The model results suggest that the landatmosphere feedback is an important mechanism for summer precipitation over the Central United States. Vegetation growth and groundwater dynamics play a significant role in enhancing the persistence of intraseasonal precipitation in regional climate models. Their combined effects act to favor a stronger land-atmosphere feedback during the summer season. The simulated diurnal cycle of precipitation is improved by the WRF model with the augmented Noah LSM. Moreover, we found that the coupling between the soil moisture and the lifting condensation level (LCL) is enhanced by adding the two components to the WRF model. The impact of groundwater is significant when the soil moisture is relatively dry. This study suggests that incorporating vegetation and groundwater dynamics into a regional climate model would be especially beneficial for seasonal precipitation forecast in the transition zones.

Improving land-surface model hydrology: Is an explicit aquifer model better than a deeper soil profile?

We use Monte Carlo analysis to show that explicit representation of an aquifer within a land-surface model (LSM) decreases the dependence of model performance on accurate selection of subsurface hydrologic parameters. Within the National Center for Atmospheric Research Community Land Model (CLM) we evaluate three parameterizations of vertical water flow: (1) a shallow soil profile that is characteristic of standard LSMs; (2) an extended soil profile that allows for greater variation in terrestrial water storage; and (3) a lumped, unconfined aquifer model coupled to the shallow soil profile. North American Land Data Assimilation System meteorological forcing data (1997–2005) drive the models as a single column representing Illinois, USA. The three versions of CLM are each run 22,500 times using a random sample of the parameter space for soil texture and key hydrologic parameters. Other parameters remain constant. Observation-based monthly changes in state-averaged terrestrial water storage (dTWS) are used to evaluate the model simulations. After single-criteria parameter exploration, the schemes are equivalently adept at simulating dTWS. However, explicit representation of groundwater considerably decreases the sensitivity of modeled dTWS to errant parameter choices. We show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a congruent set.

River Network Routing on the NHDPlus Dataset

AbstractThe mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into networks. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides streamflow observations at about 20 thousand gauges located on the NHDPlus river network. A river network model called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to autom...