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.

[1]  Kevin W. Manning,et al.  The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins , 2011 .

[2]  Dennis P. Lettenmaier,et al.  Noah LSM Snow Model Diagnostics and Enhancements , 2010 .

[3]  Zong-Liang Yang,et al.  Evaluating Enhanced Hydrological Representations in Noah LSM over Transition Zones: Implications for Model Development , 2009 .

[4]  Zong-Liang Yang,et al.  Impacts of vegetation and groundwater dynamics on warm season precipitation over the Central United States , 2009 .

[5]  R. Maxwell,et al.  Interdependence of groundwater dynamics and land-energy feedbacks under climate change , 2008 .

[6]  G. Niu,et al.  Model performance, model robustness, and model fitness scores: A new method for identifying good land‐surface models , 2008 .

[7]  R. Maxwell,et al.  Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model , 2008 .

[8]  A. Slater,et al.  A multimodel simulation of pan-Arctic hydrology , 2007 .

[9]  Zong-Liang Yang,et al.  An observation-based formulation of snow cover fraction and its evaluation over large North American river basins , 2007 .

[10]  G. Grell,et al.  Regional Climate Model Simulation of U.S.–Mexico Summer Precipitation Using the Optimal Ensemble of Two Cumulus Parameterizations , 2007 .

[11]  G. Niu,et al.  Interannual variation in biogenic emissions on a regional scale , 2007 .

[12]  D. Verseghy,et al.  Class—A Canadian land surface scheme for GCMS. I. Soil model , 2007 .

[13]  T. W. Horst,et al.  Description and Evaluation of the Characteristics of the NCAR High-Resolution Land Data Assimilation System , 2007 .

[14]  Ying Fan,et al.  Incorporating water table dynamics in climate modeling: 1. Water table observations and equilibrium water table simulations , 2007 .

[15]  S. Sorooshian,et al.  Multi-model ensemble hydrologic prediction using Bayesian model averaging , 2007 .

[16]  Zong-Liang Yang,et al.  Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data , 2007 .

[17]  Randal D. Koster,et al.  Do Global Models Properly Represent the Feedback between Land and Atmosphere? , 2006, Journal of Hydrometeorology.

[18]  Zhichang Guo,et al.  Evaluation of the Second Global Soil Wetness Project soil moisture simulations: 1. Intermodel comparison , 2006 .

[19]  Naota Hanasaki,et al.  GSWP-2 Multimodel Analysis and Implications for Our Perception of the Land Surface , 2006 .

[20]  Zong-Liang Yang,et al.  Effects of Frozen Soil on Snowmelt Runoff and Soil Water Storage at a Continental Scale , 2006 .

[21]  D. Lawrence,et al.  GLACE: The Global Land-Atmosphere Coupling Experiment. Part I: Overview , 2006 .

[22]  Taikan Oki,et al.  GLACE: The Global Land–Atmosphere Coupling Experiment. Part II: Analysis , 2006, Journal of Hydrometeorology.

[23]  Zong-Liang Yang,et al.  A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models , 2005 .

[24]  Elfatih A. B. Eltahir,et al.  Representation of Water Table Dynamics in a Land Surface Scheme. Part I: Model Development , 2005 .

[25]  Zong-Liang Yang,et al.  Effects of vegetation canopy processes on snow surface energy and mass balances , 2004 .

[26]  Dong-Jun Seo,et al.  Towards the characterization of streamflow simulation uncertainty through multimodel ensembles , 2004 .

[27]  D. Lawrence,et al.  Regions of Strong Coupling Between Soil Moisture and Precipitation , 2004, Science.

[28]  Reed M. Maxwell,et al.  On the Development of a Coupled Land Surface and Groundwater Model , 2004 .

[29]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[30]  Zong-Liang Yang,et al.  MODELING LAND SURFACE PROCESSES IN SHORT-TERM WEATHER AND CLIMATE STUDIES , 2004 .

[31]  Peter E. Thornton,et al.  Technical Description of the Community Land Model (CLM) , 2004 .

[32]  J. D. Tarpley,et al.  Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model , 2003 .

[33]  Lifeng Luo,et al.  Snow process modeling in the North American Land Data Assimilation System (NLDAS): 1. Evaluation of model‐simulated snow cover extent , 2003 .

[34]  Yongkang Xue,et al.  Impact of parameterizations in snow physics and interface processes on the simulation of snow cover and runoff at several cold region sites , 2003 .

[35]  Mark A. Friedl,et al.  Modeling the effects of three‐dimensional vegetation structure on surface radiation and energy balance in boreal forests , 2003 .

[36]  Zhenghui Xie,et al.  A new parameterization for surface and groundwater interactions and its impact on water budgets with the variable infiltration capacity (VIC) land surface model , 2003 .

[37]  R. Dickinson,et al.  The Common Land Model , 2003 .

[38]  A. Pitman,et al.  The CHAmeleon Surface Model: description and use with the PILPS phase 2(e) forcing data , 2003 .

[39]  G. Niu,et al.  The Versatile Integrator of Surface and Atmosphere processes: Part 1. Model description , 2003 .

[40]  D. Mocko,et al.  Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS phase 2(e) - 1: Experiment description and summary intercomparisons , 2003 .

[41]  R. Essery,et al.  Sublimation of Snow from Coniferous Forests in a Climate Model , 2003 .

[42]  A. Pitman.  The evolution of, and revolution in, land surface schemes designed for climate models , 2003 .

[43]  Lifeng Luo,et al.  Snow process modeling in the north american Land Data Assimilation System (NLDAS): 2. Evaluation of model simulated snow water equivalent : GEWEX Continental-Scale International Project, Part 3 (GCIP3) , 2003 .

[44]  A. J. Pitmana,et al.  The CHAmeleon Surface Model : description and use with the PILPS phase 2 ( e ) forcing data , 2003 .

[45]  G. Lindström,et al.  Soil frost and runoff at Svartberget, northern Sweden—measurements and model analysis , 2002 .

[46]  P. Milly,et al.  A Model-Based Investigation of Soil Moisture Predictability and Associated Climate Predictability , 2002 .

[47]  G. Grell,et al.  A generalized approach to parameterizing convection combining ensemble and data assimilation techniques , 2002 .

[48]  Christopher B. Field,et al.  Nitrogen Controls on Climate Model Evapotranspiration , 2002 .

[49]  Martin Wild,et al.  A new snow cover fraction parametrization for the ECHAM4 GCM , 2001 .

[50]  Praveen Kumar,et al.  Topographic Influence on the Seasonal and Interannual Variation of Water and Energy Balance of Basins in North America , 2001 .

[51]  Praveen Kumar,et al.  A catchment‐based approach to modeling land surface processes in a general circulation model: 1. Model structure , 2000 .

[52]  Gregory J. McCabe,et al.  Differences in topographic characteristics computed from 100- and 1000-m resolution digital elevation model data , 2000 .

[53]  James B. Shanley,et al.  The effect of frozen soil on snowmelt runoff at Sleepers River, Vermont† , 1999 .

[54]  K. Mitchell,et al.  A parameterization of snowpack and frozen ground intended for NCEP weather and climate models , 1999 .

[55]  Yongkang Xue,et al.  A simple snow-atmosphere-soil transfer model , 1999 .

[56]  R. Pielke,et al.  Seasonal weather prediction as an initial value problem , 1999 .

[57]  Soroosh Sorooshian,et al.  Comparative Analyses of Physically Based Snowmelt Models for Climate Simulations , 1999 .

[58]  C. E. Desborough,et al.  Surface energy balance complexity in GCM land surface models , 1999 .

[59]  Suxia Liu,et al.  Evaluation of Global Soil Wetness Project Soil Moisture Simulations , 1999 .

[60]  Lisa J. Graumlich,et al.  Interactive Canopies for a Climate Model , 1998 .

[61]  John W. Pomeroy,et al.  Measurements and modelling of snow interception in the boreal forest , 1998 .

[62]  Eric F. Wood,et al.  The Effect of Soil Thermal Conductivity Parameterization on Surface Energy Fluxes and Temperatures , 1998 .

[63]  Alan K. Betts,et al.  FIFE Surface Climate and Site-Average Dataset 1987–89 , 1998 .

[64]  K. Mitchell,et al.  Impact of Atmospheric Surface-layer Parameterizations in the new Land-surface Scheme of the NCEP Mesoscale Eta Model , 1997 .

[65]  Zong-Liang Yang,et al.  Validation of the Snow Submodel of the Biosphere-Atmosphere Transfer Scheme with Russian Snow Cover and Meteorological Observational Data , 1997 .

[66]  H. Mooney,et al.  Modeling the Exchanges of Energy, Water, and Carbon Between Continents and the Atmosphere , 1997, Science.

[67]  David Rind,et al.  An Efficient Approach to Modeling the Topographic Control of Surface Hydrology for Regional and Global Climate Modeling , 1997 .

[68]  Zong-Liang Yang,et al.  Description of the Biosphere-Atmosphere Transfer Scheme (BATS) for the Soil Moisture Workshop and evaluation of its performance , 1996 .

[69]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[70]  K. Mitchell,et al.  Simple water balance model for estimating runoff at different spatial and temporal scales , 1996 .

[71]  Y. Xue,et al.  Modeling of land surface evaporation by four schemes and comparison with FIFE observations , 1996 .

[72]  B. Bonan,et al.  A Land Surface Model (LSM Version 1.0) for Ecological, Hydrological, and Atmospheric Studies: Technical Description and User's Guide , 1996 .

[73]  Marc Lynch-Stieglitz,et al.  The development and validation of a simple snow model for the GISS GCM , 1994 .

[74]  J. Famiglietti,et al.  Multiscale modeling of spatially variable water and energy balance processes , 1994 .

[75]  Ann Henderson-Sellers,et al.  Biosphere-atmosphere transfer scheme(BATS) version 1e as coupled to the NCAR community climate model , 1993 .

[76]  Piers J. Sellers,et al.  Relations between surface conductance and spectral vegetation indices at intermediate (100 m2 to 15 km2) length scales , 1992 .

[77]  R. Koster,et al.  Modeling the land surface boundary in climate models as a composite of independent vegetation stands , 1992 .

[78]  G. Collatz,et al.  Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants , 1992 .

[79]  E. Brun,et al.  A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting , 1992, Journal of Glaciology.

[80]  D. Verseghy,et al.  CLASS-A Canadian Land Surface Scheme for GCMs , 1993 .

[81]  R. Jordan.  A One-dimensional temperature model for a snow cover : technical documentation for SNTHERM.89 , 1991 .

[82]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[83]  Piers J. Sellers,et al.  A Simplified Biosphere Model for Global Climate Studies , 1991 .

[84]  Keith Beven,et al.  On hydrologic similarity: 2. A scaled model of storm runoff production , 1987 .

[85]  H. Pan,et al.  Interaction between soil hydrology and boundary-layer development , 1987 .

[86]  I. E. Woodrow,et al.  A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions , 1987 .

[87]  P. Sellers.  Canopy reflectance, photosynthesis and transpiration , 1985 .

[88]  H. Pan,et al.  A two-layer model of soil hydrology , 1984 .

[89]  M. Ek,et al.  The Influence of Atmospheric Stability on Potential Evaporation , 1984 .

[90]  R. Dickinson.  Land Surface Processes and Climate—Surface Albedos and Energy Balance , 1983 .

[91]  W. Brutsaert.  Evaporation into the atmosphere , 1982 .

[92]  K. Beven,et al.  A physically based, variable contributing area model of basin hydrology , 1979 .

[93]  J. Deardorff.  Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation , 1978 .

[94]  P. Jarvis.  The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[95]  E. Anderson,et al.  A point energy and mass balance model of a snow cover , 1975 .