High-Resolution Land Data Assimilation System Research Articles

Localization and validation of an urbanized high-resolution land data assimilation system (u-HRLDAS)

This paper uses an urbanized high-resolution land data assimilation system (u-HRLDAS) to parameterize the urban land surface characteristics. The u-HRLDAS model is localized and developed in order to satisfy the need of the weather forecast in Beijing, China. The remote sensing data used to localize and drive u-HRLDAS include the soil type data and MODIS retrieved leaf area index (LAI) data. The evaporation and water depth for impervious surface in urban area are developed to improve the simulation of u-HRLDAS. The result of the urban weather forecast is used for the comparison based on the rapid update cycle system at Beijing Meteorological Bureau (BJ-RUC) without coupled with u-HRLDAS. The land surface temperature, land surface fluxes, and first layer soil moisture in several single sites and urban Beijing region by BJ-RUC are compared with u-HRLDAS after localization and development. The off-line simulation results indicate that compared with BJ-RUC, after the localization and development, u-HRLDAS can improve the simulation of land surface parameters and fluxes definitely.

The influence of the land surface on hydrometeorology and ecology: new advances from modeling and satellite remote sensing

The importance of land surface processes has long been recognized in hydrometeorology and ecology for they play a key role in climate and weather modeling. However, their quantification has been challenging due to the complex nature of the land surface amongst other reasons. One of the difficult parts in the quantification is the effect of vegetation that are related to land surface processes such as soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examine the effects of vegetation and its relationship with soil moisture on the simulated land–atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Finally, this study evaluates the model improvements for each simulation method.

Evaluation of a Photosynthesis-Based Canopy Resistance Formulation in the Noah Land-Surface Model

Accurately representing complex land-surface processes balancing complexity and realism remains one challenge that the weather modelling community is facing nowadays. In this study, a photosynthesis-based Gas-exchange Evapotranspiration Model (GEM) is integrated into the Noah land-surface model replacing the traditional Jarvis scheme for estimating the canopy resistance and transpiration. Using 18-month simulations from the High Resolution Land Data Assimilation System (HRLDAS), the impact of the photosynthesis-based approach on the simulated canopy resistance, surface heat fluxes, soil moisture, and soil temperature over different vegetation types is evaluated using data from the Atmospheric Radiation Measurement (ARM) site, Oklahoma Mesonet, 2002 International H2O Project (IHOP_2002), and three Ameriflux sites. Incorporation of GEM into Noah improves the surface energy fluxes as well as the associated diurnal cycle of soil moisture and soil temperature during both wet and dry periods. An analysis of midday, average canopy resistance shows similar day-to-day trends in the model fields as seen in observed patterns. Bias and standard deviation analyses for soil temperature and surface fluxes show that GEM responds somewhat better than the Jarvis scheme, mainly because the Jarvis approach relies on a parametrised minimum canopy resistance and meteorological variables such as air temperature and incident radiation. The analyses suggest that adding a photosynthesis-based transpiration scheme such as GEM improves the ability of the land-data assimilation system to simulate evaporation and transpiration under a range of soil and vegetation conditions.

Simulating the IHOP_2002 Fair-Weather CBL with the WRF-ARW–Noah Modeling System. Part II: Structures from a Few Kilometers to 100 km across

Abstract Fair-weather data along the May–June 2002 International H2O Project (IHOP_2002) eastern track and the nearby Argonne Boundary Layer Experiments (ABLE) facility in southeast Kansas are compared to numerical simulations to gain insight into how the surface influences convective boundary layer (CBL) structure, and to evaluate the success of the modeling system in replicating the observed behavior. Simulations are conducted for 4 days, using the Advanced Research version of the Weather Research and Forecasting (WRF) model coupled to the Noah land surface model (LSM), initialized using the High-Resolution Land Data Assimilation System (HRLDAS). Because the observations focus on phenomena less than 60 km in scale, the model is run with 1-km grid spacing, offering a critical look at high-resolution model behavior in an environment uncomplicated by precipitation. The model replicates the type of CBL structure on scales from a few kilometers to ∼100 km, but some features at the kilometer scales depend on the grid spacing. Mesoscale (tens of kilometers) circulations were clearly evident on 2 of the 4 days (30 May and 20 June), clearly not evident on 1 day (22 June), with the situation for the fourth day (17 June) ambiguous. Both observed and modeled surface-heterogeneity-generated mesoscale circulations are evident for 30 May. On the other hand, 20 June satellite images show north-northwest–south-southeast cloud streets (rolls) modulated longitudinally, presumably by tropospheric gravity waves oriented normal to the roll axis, creating northeast–southwest ridges and valleys spaced 50–100 km apart. Modeled cloud streets showed similar longitudinal modulation, with the associated two-dimensional structure having maximum amplitude above the CBL and no relationship to the CBL temperature distribution; although there were patches of mesoscale vertical velocity correlated with CBL temperature. On 22 June, convective rolls were the dominant structure in both model and observations. For the 3 days for which satellite images show cloud streets, WRF produces rolls with the right orientation and wavelength, which grows with CBL depth. Modeled roll structures appeared for the range of CBL depth to Obukhov length ratios (−zi/L) associated with rolls. However, sensitivity tests show that the roll wavelength is also related to the grid spacing, and the modeled convection becomes more cellular with smaller grid spacing.

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications

Abstract Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.

Nature of the Mesoscale Boundary Layer Height and Water Vapor Variability Observed 14 June 2002 during the IHOP_2002 Campaign

Abstract Mesoscale water vapor heterogeneities in the boundary layer are studied within the context of the International H2O Project (IHOP_2002). A significant portion of the water vapor variability in the IHOP_2002 occurs at the mesoscale, with the spatial pattern and the magnitude of the variability changing from day to day. On 14 June 2002, an atypical mesoscale gradient is observed, which is the reverse of the climatological gradient over this area. The factors causing this water vapor variability are investigated using complementary platforms (e.g., aircraft, satellite, and in situ) and models. The impact of surface flux heterogeneities and atmospheric variability are evaluated separately using a 1D boundary layer model, which uses surface fluxes from the High-Resolution Land Data Assimilation System (HRLDAS) and early-morning atmospheric temperature and moisture profiles from a mesoscale model. This methodology, based on the use of robust modeling components, allows the authors to tackle the question of the nature of the observed mesoscale variability. The impact of horizontal advection is inferred from a careful analysis of available observations. By isolating the individual contributions to mesoscale water vapor variability, it is shown that the observed moisture variability cannot be explained by a single process, but rather involves a combination of different factors: the boundary layer height, which is strongly controlled by the surface buoyancy flux, the surface latent heat flux, the early-morning heterogeneity of the atmosphere, horizontal advection, and the radiative impact of clouds.

Evaluation of the Noah Land Surface Model Using Data from a Fair-Weather IHOP_2002 Day with Heterogeneous Surface Fluxes

AbstractSources of differences between observations and simulations for a case study using the Noah land surface model–based High-Resolution Land Data Assimilation System (HRLDAS) are examined for sensible and latent heat fluxes H and LE, respectively; surface temperature Ts; and vertical temperature difference T0 − Ts, where T0 is at 2 m. The observational data were collected on 29 May 2002, using the University of Wyoming King Air and four surface towers placed along a sparsely vegetated 60-km north–south flight track in the Oklahoma Panhandle. This day had nearly clear skies and a strong north–south soil-moisture gradient, with wet soils and widespread puddles at the south end of the track and drier soils to the north. Relative amplitudes of H and LE horizontal variation were estimated by taking the slope of the least squares best-fit straight line ΔLE/ΔH on plots of time-averaged LE as a function of time-averaged H for values along the track. It is argued that observed H and LE values departing significantly from their slope line are not associated with surface processes and, hence, need not be replicated by HRLDAS. Reasonable agreement between HRLDAS results and observed data was found only after adjusting the coefficient C in the Zilitinkevich equation relating the roughness lengths for momentum and heat in HRLDAS from its default value of 0.1 to a new value of 0.5. Using C = 0.1 and adjusting soil moisture to match the observed near-surface values increased horizontal variability in the right sense, raising LE and lowering H over the moist south end. However, both the magnitude of H and the amplitude of its horizontal variability relative to LE remained too large; adjustment of the green vegetation fraction had only a minor effect. With C = 0.5, model-input green vegetation fraction, and our best-estimate soil moisture, H, LE, ΔLE/ΔH, and T0 − Ts, were all close to observed values. The remaining inconsistency between model and observations—too high a value of H and too low a value of LE over the wet southern end of the track—could be due to HRLDAS ignoring the effect of open water. Neglecting the effect of moist soils on the albedo could also have contributed.

Mean and Flux Horizontal Variability of Virtual Potential Temperature, Moisture, and Carbon Dioxide: Aircraft Observations and LES Study

Abstract The effects of the horizontal variability of surface properties on the turbulent fluxes of virtual potential temperature, moisture, and carbon dioxide are investigated by combining aircraft observations with large-eddy simulations (LESs). Daytime fair-weather aircraft measurements from the 2002 International H2O Project’s 45-km Eastern Track over mixed grassland and winter wheat in southeast Kansas reveal that the western part of the atmospheric boundary layer was warmer and drier than the eastern part, with higher values of carbon dioxide to the east. The temperature and specific humidity patterns are consistent with the pattern of surface fluxes produced by the High-Resolution Land Data Assimilation System. However, the observed turbulent fluxes of virtual potential temperature, moisture, and carbon dioxide, computed as a function of longitude along the flight track, do not show a clear east–west trend. Rather, the fluxes at 70 m above ground level related better to the surface variability quantified in terms of the normalized differential vegetation index (NDVI), with strong correlation between carbon dioxide fluxes and NDVI. A first attempt is made to estimate the ratios of the flux at the entrainment zone to the surface flux (entrainment ratios) as a function of longitude. The entrainment ratios averaged from these observations (βθυ ≈ 0.10, βq ≈ −2.4, and βCO2 ≈ −0.58) are similar to the values found from the homogeneous LES experiment with initial and boundary conditions similar to observations. To understand how surface flux heterogeneity influences turbulent fluxes higher up, a heterogeneous LES experiment is performed in a domain with higher sensible and lower latent heat fluxes in the western half compared to the eastern half. In contrast to the aircraft measurements, the LES turbulent fluxes show a difference in magnitude between the eastern and western halves at 70 and 700 m above ground level. Possible reasons for these differences between results from LES and aircraft measurements are discussed.

An integrated high-resolution hydrometeorological modeling testbed using LIS and WRF

Interactions between the atmosphere and the land surface have considerable influences on weather and climate. Coupled land–atmosphere systems that can realistically represent these interactions are thus critical for improving our understanding of the atmosphere-biosphere exchanges of energy, water, and their associated feedbacks. NASA's Land Information System (LIS) is a high-resolution land data assimilation system that integrates advanced land surface models, high-resolution satellite and observational data, data assimilation techniques, and high performance computing tools. LIS has been coupled to the Weather Research and Forecasting (WRF) model, enabling a high-resolution land–atmosphere modeling system. Synthetic simulations using the coupled LIS–WRF system demonstrates the interoperable use of land surface models, high-resolution land surface data and other land surface modeling tools through LIS. Real case study simulations for a June 2002 International H2O Project (IHOP) day is conducted by executing LIS first in an uncoupled manner to generate high-resolution soil moisture and soil temperature initial conditions. During the case study period, the land surface (LIS) and the atmospheric (WRF) models are executed in a coupled manner using the LIS–WRF system. The results from the simulations illustrate the impact of accurate, high-resolution land surface conditions on improving the prediction of clouds and precipitation. Thus, the coupled LIS–WRF system provides a testbed to enable studies in improving our understanding and predictability of regional and global water and energy cycles.

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

AbstractThis 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.

A Study of Convection Initiation in a Mesoscale Model Using High-Resolution Land Surface Initial Conditions

Abstract A coupled convection-resolving mesoscale atmosphere–land surface model (LSM) is used to investigate land surface–planetary boundary layer (PBL) interactions responsible for the initiation of deep, moist convection over the southern Great Plains of the United States on 19 June 1998. A high-resolution land data assimilation system provides initial conditions to the LSM, facilitating examination of soil moisture effects on forecasts of deep convection. During the late morning and early afternoon, the southwestern portion of a simulated southwest–northeast (SW–NE)-oriented surface water vapor gradient zone evolves into an intense dryline, unlike the northeastern portion, which remains relatively weak. Despite these regional differences, midafternoon convection initiation occurs within a ∼100-km-wide region of enhanced PBL depth along much of the SW–NE extent of the water vapor gradient zone. The afternoon PBL depth maximum results from a midmorning-to-early afternoon surface sensible heat flux maximu...