Description and Evaluation of the Characteristics of the NCAR High-Resolution Land Data Assimilation System

TLDR

HRLDAS was developed at NCAR to initialize land‑state variables of the coupled WRF–LSM for high‑resolution applications. This paper describes key characteristics of an uncoupled high‑resolution land data assimilation system (HRLDAS) and evaluates 18‑month numerical experiments in two nested domains (12‑ and 4‑km grid spacing) during 2001–2002 within the International H2O Project. HRLDAS and coupled WRF share the same grid, land‑surface model, land use, soil texture, terrain height, vegetation fields, and parameters, allowing direct initialization of WRF–LSM without conversion, while atmospheric forcing was benchmarked against Oklahoma Mesonet data and the system’s sensitivity to typical forcing errors was examined. HRLDAS requires 8–10 months to reach quasi‑equilibrium when initialized from other models and is highly dependent on soil texture, yet surface heat fluxes equilibrate within 3 months for most textures; finescale soil moisture, temperature, and surface heat fluxes agree well with Oklahoma Mesonet and IHOP_2002 field data, and a case study shows high correlation between HRLDAS evaporation and low‑level water vapor derived from radar.

Abstract

Abstract This paper describes important characteristics of an uncoupled high-resolution land data assimilation system (HRLDAS) and presents a systematic evaluation of 18-month-long HRLDAS numerical experiments, conducted in two nested domains (with 12- and 4-km grid spacing) for the period from 1 January 2001 to 30 June 2002, in the context of the International H2O Project (IHOP_2002). HRLDAS was developed at the National Center for Atmospheric Research (NCAR) to initialize land-state variables of the coupled Weather Research and Forecasting (WRF)–land surface model (LSM) for high-resolution applications. Both uncoupled HRDLAS and coupled WRF are executed on the same grid, sharing the same LSM, land use, soil texture, terrain height, time-varying vegetation fields, and LSM parameters to ensure the same soil moisture climatological description between the two modeling systems so that HRLDAS soil state variables can be used to initialize WRF–LSM without conversion and interpolation. If HRLDAS is initialized with soil conditions previously spun up from other models, it requires roughly 8–10 months for HRLDAS to reach quasi equilibrium and is highly dependent on soil texture. However, the HRLDAS surface heat fluxes can reach quasi-equilibrium state within 3 months for most soil texture categories. Atmospheric forcing conditions used to drive HRLDAS were evaluated against Oklahoma Mesonet data, and the response of HRLDAS to typical errors in each atmospheric forcing variable was examined. HRLDAS-simulated finescale (4 km) soil moisture, temperature, and surface heat fluxes agreed well with the Oklahoma Mesonet and IHOP_2002 field data. One case study shows high correlation between HRLDAS evaporation and the low-level water vapor field derived from radar analysis.