An Empirical Latent Heat Flux Parameterization for the Noah Land Surface Model

Abstract

Proper partitioning of the surface energy fluxes that drive the evolution of the planetary boundary layer in numerical weather prediction models requires an accurate representation of initial land surface conditions. Unfortunately, soil temperature and moisture observations are unavailable in most areas and routine daily estimates of vegetation coverage and biomass are not easily available. This gap in observational capabilities seriously hampers the evaluation and improvement of land surface parameterizations, since model errors likely relate to improper initial conditions as much as to inaccuracies in the parameterizations. Two unique datasets help to overcome these difficulties. First, 1-km fractional vegetation coverage and leaf area index values can be derived from biweekly maximum normalized difference vegetation index composites obtained from daily observations by the Advanced Very High Resolution Radiometer onboard NOAA satellites. Second, the Oklahoma Mesonet supplies multiple soil temperature and moisture measurements at various soil depths each hour. Combined, these two datasets provide significantly improved initial conditions for a land surface model and allow an evaluation of the accuracy of the land surface model with much greater confidence than previously. Forecasts that both include and neglect these unique land surface observations are used to evaluate the value of these two data sources to land surface initializations. The dense network of surface observations afforded by the Oklahoma Mesonet, including surface flux data derived from special sensors, provides verification of the model results, which indicate that predicted latent heat fluxes still differ from observations by as much as 150 W m 22. This result provides a springboard for assessing parameterization errors within the model. A new empirical parameterization developed using principal-component regression reveals simple relationships between latent heat flux and other surface observations. Periods of very dry conditions observed across Oklahoma are used advantageously to derive a parameterization for evaporation from bare soil. Combining this parameterization with an empirical canopy transpiration scheme yields improved sensible and latent heat flux forecasts and better partitioning of the surface energy budget. Surface temperature and mixing ratio forecasts show improvement when compared with observations.

Assessing uncertainties in the Noah‐MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign

“…It is common to use daytime [ Zhang et al, ; Chen et al, ; Godfrey and Stensrud, ] or midday flux observations [ Chen and Zhang, ] for evaluating LSM results. Therefore, only the midday RMSE values between model results and observed surface heat fluxes were used for evaluating model performance to mitigate uncertainties in flux measurements, following the approach used by Trier et al [], Chen and Zhang [], and Zhang et al [].…”

Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin

“…Additionally, the calibration of these parameters can become problematic when moving from local scales to regional scales, and more effective models are required for calibrating regional scale models [ Kalma et al ., ]. Hence, often simplifications are made by assigning heuristic parameter values to complex parameterizations [ Godfrey and Stensrud , ; Gutmann and Small , ]. In fact, improvement of simplified parameter values is still part of the ongoing efforts to improve both prognostic [ Wei et al ., ] and diagnostic models [ Mu et al ., ], while diagnostic models often have fewer parameters that cannot be directly observed and/or validated at regional scales.…”

The integrated urban land model

“…Evapotranspiration (ET) is one of the most important parameters in land surface model [Wang and Dickinson, 2012]; because it links energy balance and water balance of land surface. Plenty of parameterization schemes were developed to parameterize the ET [Godfrey and Stensrud, 2010;Jung et al, 2010;Lawrence et al, 2011;Mueller et al, 2011;Tang and Riley, 2013], but seldom of them considered the soil inner layers evaporation. In the semiarid and arid regions, soil inner evaporation is very important and occupies a considerable proportion in total soil evaporation.…”