Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

Download Full-text

Modeling the Effect of Desert Urbanization on Local Climate and Natural Dust Generation: A Case Study for Erbil, Iraq

Urban Science ◽

10.3390/urbansci4040046 ◽

2020 ◽

Vol 4 (4) ◽

pp. 46

Author(s):

Sherzad T. Tahir ◽

Huei-Ping Huang

Keyword(s):

Land Surface ◽

Numerical Models ◽

Surface Wind ◽

Surface Fluxes ◽

Slight Reduction ◽

Rapid Urbanization ◽

Near Surface ◽

Local Climate ◽

Surface Dust ◽

Dust Generation

This study uses a suite of meteorological and land-surface models to quantify the changes in local climate and surface dust fluxes associated with desert urbanization. Formulas connecting friction velocity and soil moisture to dust generation are used to quantify surface fluxes for natural wind-blown dust. The models are used to conduct a series of simulations for the desert city of Erbil across a period of rapid urbanization. The results show significant nighttime warming and weak but robust daytime cooling associated with desert urbanization. A slight reduction in near-surface wind speed is also found in the areas undergoing urbanization. These findings are consistent with previous empirical and modeling studies on other desert cities. Numerical models and empirical formulas are used to produce climatological maps of surface dust fluxes as a function of season, and for the pre- and post-urbanization eras. This framework can potentially be used to bridge the gap in observation on the trends in local dust generation associated with land-use changes and urban expansions.

Download Full-text

Flux Replacement as a Method to Diagnose Coupled Land–Atmosphere Model Feedback

Journal of Hydrometeorology ◽

10.1175/jhm-384.1 ◽

2004 ◽

Vol 5 (6) ◽

pp. 1034-1048 ◽

Cited By ~ 12

Author(s):

Paul A. Dirmeyer ◽

Mei Zhao

Keyword(s):

Surface State ◽

Land Surface ◽

Climate Model ◽

Initial Conditions ◽

Systematic Errors ◽

Surface Fluxes ◽

Boreal Summer ◽

Near Surface ◽

Soil Wetness ◽

The Impact

Abstract The potential role of the land surface state in improving predictions of seasonal climate is investigated with a coupled land–atmosphere climate model. Climate simulations for 18 boreal-summer seasons (1982–99) have been conducted with specified observed sea surface temperature (SST). The impact on prediction skill of the initial land surface state (interannually varying versus climatological soil wetness) and the effect of errors in downward surface fluxes (precipitation and longwave/shortwave radiation) over land are investigated with a number of parallel experiments. Flux errors are addressed by replacing the downward fluxes with observed values in various combinations to ascertain the separate roles of water and energy flux errors on land surface state variables, upward water and energy fluxes from the land surface, and the important climate variables of precipitation and near-surface air temperature. Large systematic errors are found in the model, which are only mildly alleviated by the specification of realistic initial soil wetness. The model shows little skill in simulating seasonal anomalies of precipitation, but it does have skill in simulating temperature variations. Replacement of the downward surface fluxes has a clear positive impact on systematic errors, suggesting that the land–atmosphere feedback is helping to exacerbate climate drift. Improvement in the simulation of year-to-year variations in climate is even more evident. With flux replacement, the climate model simulates temperature anomalies with considerable skill over nearly all land areas, and a large fraction of the globe shows significant skill in the simulation of precipitation anomalies. This suggests that the land surface can communicate climate anomalies back to the atmosphere, given proper meteorological forcing. Flux substitution appears to have the largest benefit to improving precipitation skill over the Northern Hemisphere midlatitudes, whereas use of realistic land surface initial conditions improves skill to significant levels over regions of the Southern Hemisphere. Correlations between sets of integrations show that the model has a robust and systematic global response to SST anomalies.

Download Full-text

Characterization of Turbulent Latent and Sensible Heat Flux Exchange between the Atmosphere and Ocean in MERRA

Journal of Climate ◽

10.1175/jcli-d-11-00029.1 ◽

2012 ◽

Vol 25 (3) ◽

pp. 821-838 ◽

Cited By ~ 19

Author(s):

J. Brent Roberts ◽

Franklin R. Robertson ◽

Carol A. Clayson ◽

Michael G. Bosilovich

Keyword(s):

Surface Wind ◽

Turbulent Fluxes ◽

Surface Fluxes ◽

Spatiotemporal Variability ◽

Western Boundary ◽

Spatial And Temporal Variability ◽

Sensible Heat ◽

Near Surface ◽

Heat And Moisture ◽

The Impact

Abstract Turbulent fluxes of heat and moisture across the atmosphere–ocean interface are fundamental components of the earth’s energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere–ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) product in terms of its turbulent surface fluxes. This assessment employs a large dataset of directly measured turbulent fluxes as well as other turbulent surface flux datasets. The spatial and temporal variability of the surface fluxes are examined in terms of their annual-mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of the incremental analysis update tendencies. It is found that MERRA turbulent surface fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm-track regions. The assimilation of observations generally acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds.

Download Full-text

Examining the Interaction of Growing Crops with Local Climate Using a Coupled Crop–Climate Model

Journal of Climate ◽

10.1175/2008jcli2494.1 ◽

2009 ◽

Vol 22 (6) ◽

pp. 1393-1411 ◽

Cited By ~ 34

Author(s):

Tom Osborne ◽

Julia Slingo ◽

David Lawrence ◽

Tim Wheeler

Keyword(s):

Climate Variability ◽

Crop Yield ◽

Land Surface ◽

Climate Models ◽

Climate Model ◽

Crop Growth ◽

Surface Fluxes ◽

Near Surface ◽

Local Climate ◽

The Impact

Abstract This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

Download Full-text

Application of Bulk Richardson Parameterizations of Surface Fluxes to Heterogeneous Land Surfaces

Monthly Weather Review ◽

10.1175/mwr-d-21-0047.1 ◽

2021 ◽

Author(s):

Temple R. Lee ◽

Michael Buban ◽

Tilden P. Meyers

Keyword(s):

Heat Flux ◽

Land Surface ◽

Similarity Theory ◽

Weather Prediction ◽

Surface Wind ◽

Sensible Heat Flux ◽

Surface Heterogeneity ◽

Surface Fluxes ◽

Near Surface ◽

Surface Atmosphere

AbstractMonin-Obukhov Similarity Theory (MOST) has long been used to represent surface-atmosphere exchange in numerical weather prediction (NWP) models. However, recent work has shown that bulk Richardson (Rib) parameterizations, rather than traditional MOST formulations, better represent near-surface wind, temperature, and moisture gradients. So far this work has only been applied to unstable atmospheric regimes. In this study, we extended Rib parameterizations to stable regimes and developed parameterizations for the friction velocity (u*), sensible heat flux (H), and latent heat flux (E) using datasets from the Land-Atmosphere Feedback Experiment (LAFE). We tested our new Rib parameterizations using datasets from the Verification of the Origins of Rotation in Tornadoes Experiment-Southeast (VORTEX-SE) and compared the new Rib parameterizations with traditional MOST parameterizations and MOST parameterizations obtained using the LAFE datasets. We found that fitting coefficients in the MOST parameterizations developed from LAFE datasets differed from the fitting coefficients in classical MOST parameterizations which we attributed to the land surface heterogeneity present in the LAFE domain. Regardless, the new Rib parameterizations performed just as well as and, in some instances better, than the classical MOST parameterizations and the MOST parameterizations developed from the LAFE datasets. The improvement was most evident for H, particularly for H under unstable conditions, which was based on a better 1:1 relationship between the parameterized and observed values. These findings provide motivation to transition away from MOST and to implement bulk Richardson parameterizations into NWP models to represent surface-atmosphere exchange.

Download Full-text

Evaluating the role of soil physical properties on simulated land-atmosphere interactions over South Africa using coupled atmosphere-hydrological modeling

10.5194/egusphere-egu21-9418 ◽

2021 ◽

Author(s):

Zhenyu Zhang ◽

Patrick Laux ◽

Joël Arnault ◽

Jianhui Wei ◽

Jussi Baade ◽

...

Keyword(s):

South Africa ◽

Physical Properties ◽

Land Degradation ◽

Land Surface ◽

Soil Physical Properties ◽

Near Surface ◽

Soil Database ◽

Global Soil ◽

The Impact

Land degradation with its direct impact on vegetation, surface soil layers and land surface albedo, has great relevance with the climate system. Assessing the climatic and ecological effects induced by land degradation requires a precise understanding of the interaction between the land surface and atmosphere. In coupled land-atmosphere modeling, the low boundary conditions impact the thermal and hydraulic exchanges at the land surface, therefore regulates the overlying atmosphere by land-atmosphere feedback processes. However, those land-atmosphere interactions are not convincingly represented in coupled land-atmosphere modeling applications. It is partly due to an approximate representation of hydrological processes in land surface modeling. Another source of uncertainties relates to the generalization of soil physical properties in the modeling system. This study focuses on the role of the prescribed physical properties of soil in high-resolution land surface-atmosphere simulations over South Africa. The model used here is the hydrologically-enhanced Weather Research and Forecasting (WRF-Hydro) model. Four commonly used global soil datasets obtained from UN Food and Agriculture Organization (FAO) soil database, Harmonized World Soil Database (HWSD), Global Soil Dataset for Earth System Model (GSDE), and SoilGrids dataset, are incorporated within the WRF-Hydro experiments for investigating the impact of soil information on land-atmosphere interactions. The simulation results of near-surface temperature, skin temperature, and surface energy fluxes are presented and compared to observational-based reference dataset. It is found that simulated soil moisture is largely influenced by soil texture features, which affects its feedback to the atmosphere.

Download Full-text

Dome effect of black carbon and its key influencing factors: A one-dimensional modelling study

10.5194/acp-2017-967 ◽

2017 ◽

Author(s):

Zilin Wang ◽

Xin Huang ◽

Aijun Ding

Keyword(s):

Boundary Layer ◽

Air Pollution ◽

Black Carbon ◽

Rural Areas ◽

Land Surface ◽

Critical Role ◽

Aerosol Layer ◽

Near Surface ◽

Haze Pollution ◽

The Impact

Abstract. Black carbon (BC) has been identified to play a critical role in aerosol-planet boundary layer (PBL) interaction and further deterioration of near-surface air pollution in megacities, which has been named as its dome effect. However, the impacts of key factors that influence this effect, such as the vertical distribution and aging processes of BC, and also the underlying land surface, have not been quantitatively explored yet. Here, based on available in-situ measurements of meteorology and atmospheric aerosols together with the meteorology-chemistry online coupled model, WRF-Chem, we conduct a set of parallel simulations to quantify the roles of these factors in influencing the BC's dome effect and surface haze pollution, and discuss the main implications of the results to air pollution mitigation in China. We found that the impact of BC on PBL is very sensitive to the altitude of aerosol layer. The upper level BC, especially those near the capping inversion, is more essential in suppressing the PBL height and weakening the turbulence mixing. The dome effect of BC tends to be significantly intensified as BC aerosol mixed with scattering aerosols during winter haze events, resulting in a decrease of PBL height by more than 25 %. In addition, the dome effect is more substantial (up to 15 %) in rural areas than that in the urban areas with the same BC loading, indicating an unexpected regional impact of such kind of effect to air quality in countryside. This study suggests that China's regional air pollution would greatly benefit from BC emission reductions, especially those from the elevated sources from the chimneys and also the domestic combustions in rural areas, through weakening the aerosol-boundary layer interactions that triggered by BC.

Download Full-text

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

Geoscientific Model Development ◽

10.5194/gmd-9-1959-2016 ◽

2016 ◽

Vol 9 (5) ◽

pp. 1959-1976 ◽

Cited By ~ 14

Author(s):

Chun Zhao ◽

Maoyi Huang ◽

Jerome D. Fast ◽

Larry K. Berg ◽

Yun Qian ◽

...

Keyword(s):

Air Quality ◽

Volatile Organic Compounds ◽

Organic Compounds ◽

Land Surface ◽

Aerosol Formation ◽

Biogenic Volatile Organic Compounds ◽

Vegetation Map ◽

Near Surface ◽

Volatile Organic ◽

The Impact

Abstract. Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Download Full-text

The Effects of Assimilating Conventional and ATOVS Data on Forecasted Near-Surface Wind with WRF-3DVAR

Monthly Weather Review ◽

10.1175/mwr-d-14-00038.1 ◽

2015 ◽

Vol 143 (1) ◽

pp. 153-164 ◽

Cited By ~ 13

Author(s):

Feimin Zhang ◽

Yi Yang ◽

Chenghai Wang

Keyword(s):

Data Assimilation ◽

Surface Wind ◽

Lower Atmosphere ◽

Observation Data ◽

Initial Field ◽

Infrared Observation ◽

Forecast Performance ◽

Near Surface ◽

The Impact ◽

Positive Effect

Abstract In this paper, the Weather Research and Forecasting (WRF) Model with the three-dimensional variational data assimilation (WRF-3DVAR) system is used to investigate the impact on the near-surface wind forecast of assimilating both conventional data and Advanced Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (ATOVS) radiances compared with assimilating conventional data only. The results show that the quality of the initial field and the forecast performance of wind in the lower atmosphere are improved in both assimilation cases. Assimilation results capture the spatial distribution of the wind speed, and the observation data assimilation has a positive effect on near-surface wind forecasts. Although the impacts of assimilating ATOVS radiances on near-surface wind forecasts are limited, the fine structure of local weather systems illustrated by the WRF-3DVAR system suggests that assimilating ATOVS radiances has a positive effect on the near-surface wind forecast under conditions that ATOVS radiances in the initial condition are properly amplified. Assimilating conventional data is an effective approach for improving the forecast of the near-surface wind.

Download Full-text

High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

10.5194/egusphere-egu2020-17855 ◽

2020 ◽

Author(s):

Benjamin Fersch ◽

Alfonso Senatore ◽

Bianca Adler ◽

Joël Arnault ◽

Matthias Mauder ◽

...

Keyword(s):

Boundary Layer ◽

Land Surface ◽

Hydrological Modeling ◽

Weather Prediction ◽

Surface Model ◽

Near Surface ◽

Ground Heat Flux ◽

The Impact ◽

Fully Coupled ◽

Regional Water

The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km&#178;) and Rott (55 km&#178;) river catchments in southern Germany, covering a five month period (Jun&#8211;Oct 2016).The sensitivity of 7 land surface parameters is tested using the Latin-Hypercube One-factor-At-a-Time (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent Parameter Estimation and Uncertainty Analysis software (PEST).The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.

Download Full-text