1. POSTER TEMPLATE BY: www.PosterPresentations.com Development of a Unified Land Model Ben Livneh 1, Dennis. P. Lettenmaier 1, Pedro Restrepo 2. 1) University of Washington Department of Civil and Environmental Engineering Box 352700, Seattle, WA 98195. 2) NOAA National Weather Service Office of Hydrologic Development, Silver Spring, MD 20910-. ABSTRACT Accurate partitioning of precipitation into evapotranspiration and runoff, and more generally estimation of the surface water balance, is crucial both for hydrologic forecasting and numerical weather and climate prediction. One important aspect of this issue is the partitioning of evapotranspiration into soil evaporation, canopy evaporation, and plant transpiration, which in turn has implications for other terms in the surface water balance. In the first part of the study, we tested several well known land surface models in multi-year simulations over the continental U.S. Among the models, which included the Variable Infiltration Capacity (VIC) model, the Community Land Model (CLM), the Noah Land Surface Model (Noah LSM), and the NASA Catchment model, there were substantial variations in the partitioning. These results motivated a more detailed evaluation, using data for 5 catchments that were a part of the Model Parameter Estimation Experiment (MOPEX), in addition to a set of flux stations from the Ameriflux network. The selection of basins and flux stations were made so as to provide a robust cross-section of hydro-climatic regimes under which to test model performance. In this portion of the study, we evaluated a unified land model (ULM) which is a merger of the NWS Sacramento Soil Moisture Accounting model (SAC-SMA), which is used operationally for flood and seasonal streamflow prediction, and the Noah LSM, which is the land scheme used in NOAA’s suite of weather and climate prediction models. Our overall objective is to leverage the operational strengths of each model, specifically to improve streamflow prediction and soil moisture states within the Noah LSM framework, and to add a vegetation component to the SAC-SMA model. At the flux stations, we examine the diurnal cycle of modeled fluxes of sensible, latent, and ground heat as they compare with observations during the warm season (to remove the influence of snow model), as well as the daily variations of soil moisture. At the basin scale, monthly estimates of streamflow are compared with naturalize flow data, to assess model skill in capturing seasonal peaks and low flow periods. Altogether, model tests were performed at each scale to understand model sensitivities and parameterizations and to suggest physics upgrades to advance model performance. Introduction and Motivation Average monthly total ET (mm) during summer: 1980 – 1995 (JJA) Although differences certainly exist, total ET amongst models is very comparable on average. This is particularly significant, given the fairly diverse set of model parameterizations and assumptions in the computation individual components of model ET. Location of test basins, flux sites and preliminary streamflow analysis (1980 – 1990) Comparison of simulated and observed diurnal surface fluxes Seasonal soil moisture analysis References The major objective of this work is to develop a model that will make improved estimates of land surface and hydrological processes, through the merger of two models which are used operationally. Although the SAC model generally performs much better than Noah from a hydrologic prediction standpoint (Figure 1), it does not compute surface energy fluxes, and hence, cannot be run in a coupled mode with atmospheric models Albeit a vast amount of research has been done on parameter estimation for the SAC model, which could ideally be transferable to ULM. Additionally, recent improvements to the Noah snow (Livneh et al., 2009) model has made it more suitable to be coupled with atmospheric models, since accurate prediction of snow cover has a strong control over surface flux estimation and radiative partitioning. The motivation of this work therefore, is to establish a model that is well grounded in hydrology, while having the capability to also be run in the coupled-model environment. Selecting an appropriate ET scheme required careful consideration, as disparities exist among models (Figure2, Figure 3). The general breakdown of model structure is described in Figure 4. Sensitivity testing was done to further quantify the role of model interaction on land surface states and fluxes Examining individual ET components reveals a noticable disparity between modeled quantities. Bare-soil evaporation, in this case is nearly zero for the VIC model since it is largely parameterized as having complete-vegetation coverage, while the SAC model derives all of its total ET from soil evaporation as it does not consider vegetation. CLM provides considerable throughfall which enables elevated soil evaporation in the West, while Noah follows a pattern consistent with its satellite-based monthly greenness maps, and the Catchment model shows artifacts of both greenness and leaf-area-index (LAI) patterns. Fraction of total ET from soil evaporation during summer: 1980 – 1995 (JJA) Schematic of proposed model merger for ULM Noah + SAC = ULM + = The merged model preserves the land surface components from the Noah model, including its: 1. snow model (Livneh et al., 2009); 2. snow and snow-free albedo formulations; 3. frozen soil scheme and soil heat flux terms; 4. vegetation parameterization (utilizing monthly greenness maps) and root layer distribution; and 5. Potential evapotranspiration computation. The SAC model contributes its conceptual soil moisture storage zones, with tension and free water zones that prescribe surface runoff, interflow and baseflow. The essential link between the models lies in how ET is extracted from the soil (through the vegetation roots and bare-soil). Figure 1: Peaks-over-threshold analysis, showing the much improved streamflow prediction capability of SAC versus Noah; 30 year model simulations for the Colorado River above Grand Junction Cumulative Probability Shown to the left is one of many seasonal soil moisture plots. This plot typifies a Mediterranean type summer (from the Blodgett forest site) in which very little precipitation falls, causing the soil moisture to gradually decrease throughout the warm season. A marked difference between simulated and observed soil moisture in this case is the non-linear decrease in observations beginning in June, which is approximated linearly by both models. This mechanism is actively being investigated, specifically soil moisture behavior between the field capacity and wilting point of the soil and examining ways to capture this nonlinearity as it pertains to root water uptake and direct soil evaporation. VIC CLM Noah Catchment SAC VIC CLM Noah Catchment SAC Burnash, R.J.C., 1995. The NWS river forecast system—catchment modeling. In: Singh, V.P. (Ed), Computer Models of Watershed Hydrology, Water Resources Publications, Highlands ranch, CO, pp. 311–366. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296. Livneh B, Xia Y, Mitchell KE, Ek MB, Lettenmaier DP (2009) Noah LSM Snow Model Diagnostics and Enhancements. Journal of Hydrometeorology: In Press Mitchell, K.E. et al., 2001: The Community Noah Land Surface Model (LSM) – User’s Guide (v2.2), available at http://www.emc.ncep.noaa.gov/mmb/gcp/noahlsm/README_2.2.htm. (Figure 5, Figure 6). Current and future validation for ET partitioning is being done on several additional test sites (Figure 7). Noah SAC Observed Peaks (ft 3 /s) Map showing (green) basins of interest and (red) Ameriflux sites. Basins were selected across a wide hydroclimatic gradient where quality streamflow data exist, while flux towers were selected based on data quality and proximity (where possible) to selected basins. Fluxes are shown above for two sites during alternate warm season periods. The diurnal cycle of sensible and latent heat are capture quite well in both cases, where Noah and ULM are more similar at the Blodgett site. Ground heat flux is troublesome, particularly at the Niwot Ridge high elevation site, where timing and magnitudes are incorrect. Albeit, quality measurements are difficult to obtain in this respect, so this remains an open challenging to model. Model performance is shown above for selected basins as 10 year average monthly streamflow. In most cases the ULM behaves at some intermediate point between its two parent models, given the different equilibrium state that develops with the merged parameterizations.An important difference between SAC and Noah, ULM is the influence of snow model (SNOW-17 vs. the Livneh et al., 2010 updated snow model, respectively). This was a major reason for focusing the latter part of the study on warm season performance. ULM Noah SAC Observed Yampa R. near Maybell, CO Snowmelt dominated – 8830 km 2 Snoqualmie R. near Carnation, WA snowmelt dominated basin – 1560 km 2 Feather R. near Oroville Dam, CA snowmelt/winter-precip. dominated basin – 9390 km 2 Niwot Ridge, CO Flux station Avg. diurnal fluxes 21 June – 21 Sept. 2006 ULM Noah Observed Blodgett Forest, CA Flux station Avg. diurnal fluxes 21 Aug – 21 Sept. 2001 ULM Noah Observed