scholarly journals Verification of Land–Atmosphere Coupling in Forecast Models, Reanalyses, and Land Surface Models Using Flux Site Observations

2018 ◽  
Vol 19 (2) ◽  
pp. 375-392 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Liang Chen ◽  
Jiexia Wu ◽  
Chul-Su Shin ◽  
Bohua Huang ◽  
...  
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Model Development ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Model Systems ◽  
Shortwave Radiation ◽  
Spatial And Temporal Variability ◽  
Near Surface ◽  
Flux Tower

Abstract This study compares four model systems in three configurations (LSM, LSM + GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly underrepresent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land–atmosphere coupling) and may overrepresent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally underrepresent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly, and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Although the models validate better against Bowen-ratio-corrected surface flux observations, which allow for closure of surface energy balances at flux tower sites, it is not clear whether the corrected fluxes are more representative of actual fluxes. The analysis illuminates targets for coupled land–atmosphere model development, as well as the value of long-term globally distributed observational monitoring.

scholarly journals Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>

2016 ◽  
Vol 9 (11) ◽  
pp. 5523-5533 ◽  
Author(s):  
Sander van der Laan ◽  
Swagath Manohar ◽  
Alex Vermeulen ◽  
Fred Bosveld ◽  
Harro Meijer ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Activity Concentration ◽  
Regional Scale ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Spatial And Temporal Variability ◽  
Single Pair ◽  
The South ◽  
Practical Applications ◽  
Soil Flux

Abstract. We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values  > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method.

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

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

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.

scholarly journals High resolution land surface fluxes from satellite data (HOLAPS v1.0): evaluation and uncertainty assessment

2015 ◽  
Vol 8 (12) ◽  
pp. 10783-10841
Author(s):  
A. Loew ◽  
J. Peng ◽  
M. Borsche
Keyword(s):  
Surface Energy ◽  
Latent Heat ◽  
Satellite Data ◽  
Land Surface ◽  
Global Solar Radiation ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Radiation ◽  
Water Fluxes ◽  
Essential Components

Abstract. Surface water and energy fluxes are essential components of the Earth system. Surface latent heat fluxes provide major energy input to the atmosphere. Despite the importance of these fluxes, state-of-the-art datasets of surface energy and water fluxes largely differ. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high resolved flux estimates at the global scale (HOLAPS). The framework maximizes the usage of existing long-term satellite data records and ensures internally consistent estimates of the surface radiation and water fluxes. The manuscript introduces the technical details of the developed framework and provides results of a comprehensive sensitivity and evaluation study. Overall the results indicate very good agreement with in situ observations when compared against 49 FLUXNET stations worldwide. Largest uncertainties of latent heat flux and net radiation were found to result from uncertainties in the global solar radiation flux obtained from satellite data products.

scholarly journals Development of a Unified Land Model for Prediction of Surface Hydrology and Land–Atmosphere Interactions

2011 ◽  
Vol 12 (6) ◽  
pp. 1299-1320 ◽  
Author(s):  
Ben Livneh ◽  
Pedro J. Restrepo ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
A Priori ◽  
Model Performance ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Frozen Soil ◽  
Surface Model ◽  
Soil Moisture Accounting

Abstract A unified land model (ULM) is described that combines the surface flux parameterizations in the Noah land surface model (used in most of NOAA’s coupled weather and climate models) with the Sacramento Soil Moisture Accounting model (Sac; used for hydrologic prediction within the National Weather Service). The motivation was to develop a model that has a history of strong hydrologic performance while having the ability to be run in the coupled land–atmosphere environment. ULM takes the vegetation, snow model, frozen soil, and evapotranspiration schemes from Noah and merges them with the soil moisture accounting scheme from Sac. ULM surface fluxes, soil moisture, and streamflow simulations were evaluated through comparisons with observations from the Ameriflux (surface flux), Illinois Climate Network (soil moisture), and Model Parameter Estimation Experiment (MOPEX; streamflow) datasets. Initially, a priori parameters from Sac and Noah were used, which resulted in ULM surface flux simulations that were comparable to those produced by Noah (Sac does not predict surface energy fluxes). ULM with the a priori parameters had streamflow simulation skill that was generally similar to Sac’s, although it was slightly better (worse) for wetter (more arid) basins. ULM model performance using a set of parameters identified via a Monte Carlo search procedure lead to substantial improvements relative to the a priori parameters. A scheme for transfer of parameters from streamflow simulations to nearby flux and soil moisture measurement points was also evaluated; this approach did not yield conclusive improvements relative to the a priori parameters.

scholarly journals Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain

2017 ◽  
Vol 145 (12) ◽  
pp. 4727-4745 ◽  
Author(s):  
Elena Tomasi ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
Massimiliano de Franceschi
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Winter Season ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Shortwave Radiation ◽  
Land Use Classification ◽  
Near Surface ◽  
Thermal Inversion ◽  
Alpine Valley

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.

Estimating Land Surface Energy Budgets From Space: Review and Current Efforts at the University of Wisconsin—Madison and USDA–ARS

2004 ◽  
Vol 85 (1) ◽  
pp. 65-78 ◽  
Author(s):  
George R. Diak ◽  
John R. Mecikalski ◽  
Martha C. Anderson ◽  
John M. Norman ◽  
William P. Kustas ◽  
...  
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Research Effort ◽  
Surface Fluxes ◽  
Integrated System ◽  
Energy Budgets ◽  
University Of Wisconsin ◽  
The University ◽  
Meteorological Satellite ◽  
Large Research

Since the advent of the meteorological satellite, a large research effort within the community of earth scientists has been directed at assessing the components of the land surface energy balance from space. The development of these techniques from first efforts to the present time are reviewed, and the integrated system used to estimate the radiative and turbulent land surface fluxes is described. This system is now running in real time over the continental United States at a resolution of 10 km, producing daily and time-integrated flux components.

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

Urban Science ◽  
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.

Long-Term Climate and Derived Surface Hydrology and Energy Flux Data for Mexico: 1925–2004

2007 ◽  
Vol 20 (9) ◽  
pp. 1936-1946 ◽  
Author(s):  
Chunmei Zhu ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
North American ◽  
Land Surface ◽  
Surface Fluxes ◽  
The Other ◽  
Shortwave Radiation ◽  
Infiltration Capacity ◽  
Time Step ◽  
Downward Longwave Radiation

Abstract Studying the role of land surface conditions in the Mexican portion of the North American monsoon system (NAMS) region has been a challenge due to the paucity of long-term observations. A long-term gridded observation-based climate dataset suitable for forcing land surface models, as well as model-derived land surface states and fluxes for a domain consisting of all of Mexico, is described. The datasets span the period of January 1925–October 2004 at 1/8° spatial resolution at a subdaily (3 h) time step. The simulated runoff matches the observations plausibly over most of the 14 small river basins spanning all of Mexico, which suggests that long-term mean evapotranspiration is realistically reproduced. On this basis, and given the physically based model parameterizations of soil moisture and energy fluxes, the other surface fluxes and state variables such as soil moisture should be represented reasonably. In addition, a comparison of the surface fluxes from this study is performed with North American Regional Reanalysis (NARR) data on a seasonal mean basis. The results indicate that downward shortwave radiation is generally smaller than in the NARR data, especially in summer. Net radiation, on the other hand, is somewhat larger in the Variable Infiltration Capacity (VIC) hydrological model than in the NARR data for much of the year over much of the domain. The differences in radiative and turbulent fluxes are attributed to (i) the parameterization used in the VIC forcings for solar and downward longwave radiation, which links them to the daily temperature and temperature range, and (ii) differences in the land surface parameterizations used in VIC and the NCEP–Oregon State University–U.S. Air Force–NWS/Hydrologic Research Lab (Noah) land scheme used in NARR.

scholarly journals Model Estimates of Land-Driven Predictability in a Changing Climate from CCSM4

2013 ◽  
Vol 26 (21) ◽  
pp. 8495-8512 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Sanjiv Kumar ◽  
Michael J. Fennessy ◽  
Eric L. Altshuler ◽  
Timothy DelSole ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Climate Models ◽  
Temporal Structure ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Ensemble Forecasts ◽  
Climate System Model ◽  
Subsurface Soil

Abstract The climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future settings. Predictability is defined in terms of the model's ability to predict its own interannual variability. Predictability from the land surface in this model is relatively weak compared to estimates from other climate models but has much of the same spatial and temporal structure found in previous studies. Several factors appear to contribute to the weakness, including a low correlation between surface fluxes and subsurface soil moisture, less soil moisture memory (lagged autocorrelation) than other models or observations, and relative insensitivity of the atmospheric boundary layer to surface flux variations. Furthermore, subseasonal cyclical behavior in plant phenology for tropical grasses introduces spurious unrealistic predictability at low latitudes during dry seasons. Despite these shortcomings, intriguing changes in predictability are found. Areas of historical land use change appear to have experienced changes in predictability, particularly where agriculture expanded dramatically into the Great Plains of North America, increasing land-driven predictability there. In a warming future climate, land–atmosphere coupling strength generally increases, but added predictability does not always follow; many other factors modulate land-driven predictability.

scholarly journals Assessment of MERRA-2 Land Surface Energy Flux Estimates

2018 ◽  
Vol 31 (2) ◽  
pp. 671-691 ◽  
Author(s):  
Clara S. Draper ◽  
Rolf H. Reichle ◽  
Randal D. Koster
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Longwave Radiation ◽  
Research Unit ◽  
Surface Energy Budget ◽  
Shortwave Radiation ◽  
Boreal Summer ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Global Land

In the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) system the land is forced by replacing the model-generated precipitation with observed precipitation before it reaches the surface. This approach is motivated by the expectation that the resultant improvements in soil moisture will lead to improved land surface latent heating (LH). Here aspects of the MERRA-2 land surface energy budget and 2-m air temperatures [Formula: see text] are assessed. For global land annual averages, MERRA-2 appears to overestimate the LH (by 5 W m−2), the sensible heating (by 6 W m−2), and the downwelling shortwave radiation (by 14 W m−2) while underestimating the downwelling and upwelling (absolute) longwave radiation (by 10–15 W m−2 each). These results differ only slightly from those for NASA’s previous reanalysis, MERRA. Comparison to various gridded reference datasets over boreal summer (June–August) suggests that MERRA-2 has particularly large positive biases (>20 W m−2) where LH is energy limited and that these biases are associated with evaporative fraction biases rather than radiation biases. For time series of monthly means during boreal summer, the globally averaged anomaly correlations [Formula: see text] with reference data were improved from MERRA to MERRA-2, for LH (from 0.39 to 0.48 vs Global Land Evaporation Amsterdam Model data) and the daily maximum T2m (from 0.69 to 0.75 vs Climatic Research Unit data). In regions where [Formula: see text] is particularly sensitive to the precipitation corrections (including the central United States, the Sahel, and parts of South Asia), the changes in the [Formula: see text] [Formula: see text] are relatively large, suggesting that the observed precipitation influenced the [Formula: see text] performance.

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