Evaluation of Surface Fluxes in ERA-Interim Using Flux Tower Data

2016 ◽  
Vol 29 (4) ◽  
pp. 1573-1582 ◽  
Author(s):  
Chunlüe Zhou ◽  
Kaicun Wang
Keyword(s):  
Spatial Scales ◽  
Surface Air Temperature ◽  
Environmental Parameters ◽  
Turbulent Fluxes ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
High Density ◽  
Net Radiation ◽  
Broadleaf Forest ◽  
Deciduous Broadleaf Forest

Abstract Surface air temperature Ta is largely determined by surface net radiation Rn and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations by comparison of absolute flux values are of limited help because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data, and imperfect parameterizations. This study further evaluates the relationships of LE and H with Rn and environmental parameters, including Ta, relative humidity (RH), and wind speed (WS), using ERA-Interim data at a 0.125° × 0.125° grid with observations at AmeriFlux sites from 1998 to 2012. The results demonstrate ERA-Interim can roughly reproduce the absolute values of environmental parameters, radiation, and turbulent fluxes. The model performs well in simulating the correlation of LE and H with Rn, except for the notable correlation overestimation of H against Rn over high-density vegetation (e.g., deciduous broadleaf forest, grassland, and cropland). The sensitivity of LE to Rn in the model is similar to that observed, but that of H to Rn is overestimated by 24.2%. Over the high-density vegetation, the correlation coefficient between H and Ta is overestimated by over 0.2, whereas that between H and WS is underestimated by over 0.43. The sensitivity of H to Ta is overestimated by 0.72 W m−2 °C−1, whereas that of H to WS in the model is underestimated by 16.15 W m−2 (m s−1)−1 over all of the sites. The model cannot accurately capture the responses of evaporative fraction [EF; EF = LE / (LE + H)] to Rn and environmental parameters. This calls for major research efforts to improve the intrinsic parameterizations of turbulent fluxes, particularly over high-density vegetation.

scholarly journals Spatial Distribution of Global Landscape Evaporation in the Early Twenty-First Century by Means of a Generalized Complementary Approach

2020 ◽  
Vol 21 (2) ◽  
pp. 287-298 ◽  
Author(s):  
Wilfried Brutsaert ◽  
Lei Cheng ◽  
Lu Zhang
Keyword(s):  
Spatial Distribution ◽  
Wind Speed ◽  
Land Surface ◽  
Spatial Scales ◽  
Surface Air Temperature ◽  
Aridity Index ◽  
Routine Data ◽  
Net Radiation ◽  
Atmospheric Conditions ◽  
Near Surface

AbstractA generalized implementation of the complementary principle was applied to estimate global land surface evaporation and its spatial distribution. The single parameter in the method was calibrated as a function of aridity index, mainly on the basis of runoff and precipitation data for 524 catchments in different parts of the world. The spatial distribution of annual evaporation from Earth’s land surfaces for 2001–13 was then calculated at a spatial resolution of 0.5°, by means of an available global net radiation dataset (commonly referred to as CERES SYN1deg-Day) and a global forcing dataset (referred to as CRU-NCEP v7) for near-surface temperature, humidity, wind speed, and air pressure. The results are shown to agree with reliable previous estimates by more elaborate methods. The global average evaporation for 2001–13 was found to be 472.65 mm a−1 or 36.96 W m−2. The present method should allow not only future updates but also retroactive historical analyses with routine data of net radiation, near-surface air temperature, humidity, wind speed, and precipitation; its main advantage is that the environmental aridity is deduced from atmospheric conditions and requires no knowledge of surface characteristics, such as soil moisture, vegetation, and terrain, which are highly variable and often difficult to quantify at larger spatial scales. Because they are strictly measurement based, the results can serve also as a reality check for different aspects of climate and related models.

scholarly journals Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

2021 ◽  
Author(s):  
Hibiki M. Noda ◽  
Hiroyuki Muraoka ◽  
Kenlo Nishida Nasahara
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Spectral Reflectance ◽  
Canopy Structure ◽  
Terrestrial Ecosystems ◽  
Optical Remote Sensing ◽  
Canopy Reflectance ◽  
Broadleaf Forest ◽  
Leaf Optical Properties ◽  
Deciduous Broadleaf Forest

AbstractThe need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.

scholarly journals Midwinter melts in the Canadian prairies: energy balance and hydrological effects

2019 ◽  
Vol 23 (4) ◽  
pp. 1867-1883 ◽  
Author(s):  
Igor Pavlovskii ◽  
Masaki Hayashi ◽  
Daniel Itenfisu
Keyword(s):  
Surface Runoff ◽  
Hydrological Cycle ◽  
Remote Sensing Data ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Net Radiation ◽  
Present Climate ◽  
Canadian Prairies ◽  
Energy Inputs ◽  
Hydrological Effects

Abstract. Snowpack accumulation and depletion are important elements of the hydrological cycle in the Canadian prairies. The surface runoff generated during snowmelt is transformed into streamflow or fills numerous depressions driving the focussed recharge of groundwater in this dry setting. The snowpack in the prairies can undergo several cycles of accumulation and depletion in a winter. The timing of the melt affects the mechanisms of snowpack depletion and their hydrological implications. The effects of midwinter melts were investigated at four instrumented sites in the Canadian prairies. Unlike net radiation-driven snowmelt during spring melt, turbulent sensible heat fluxes were the dominant source of energy inputs for midwinter melt occurring in the period with low solar radiation inputs. Midwinter melt events affect several aspects of hydrological cycle with lower runoff ratios than subsequent spring melt events, due to their role in the timing of the focussed recharge. Remote sensing data have shown that midwinter melt events regularly occur under the present climate throughout the Canadian prairies, indicating applicability of the study findings throughout the region.

scholarly journals The West Coast Thermal Trough: Mesoscale Evolution and Sensitivity to Terrain and Surface Fluxes

2013 ◽  
Vol 141 (8) ◽  
pp. 2869-2896 ◽  
Author(s):  
Matthew C. Brewer ◽  
Clifford F. Mass ◽  
Brian E. Potter
Keyword(s):  
High Pressure ◽  
West Coast ◽  
Energy Equation ◽  
Potential Temperature ◽  
Wrf Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
The West ◽  
Surface Heat Fluxes ◽  
Thermodynamic Energy

Abstract Despite the significant impacts of the West Coast thermal trough (WCTT) on West Coast weather and climate, questions remain regarding its mesoscale structure, origin, and dynamics. Of particular interest is the relative importance of terrain forcing, advection, and surface heating on WCTT formation and evolution. To explore such questions, the 13–16 May 2007 WCTT event was examined using observations and simulations from the Weather Research and Forecasting (WRF) Model. An analysis of the thermodynamic energy equation for these simulations was completed, as well as sensitivity experiments in which terrain or surface fluxes were removed or modified. For the May 2007 event, vertical advection of potential temperature is the primary driver of local warming and WCTT formation west of the Cascades. The downslope flow that drives this warming is forced by easterly flow associated with high pressure over British Columbia, Canada. When the terrain is removed from the model, the WCTT does not form and high pressure builds over the northwest United States. When the WCTT forms on the east side of the Cascades, diabatic heating dominates over the other terms in the thermodynamic energy equation, with warm advection playing a small role. If surface heat fluxes are neglected, an area of low pressure remains east of the Cascades, though it is substantially attenuated.

scholarly journals Large-Eddy Simulation and Single-Column Modeling of Thermally Stratified Wind Turbine Arrays for Fully Developed, Stationary Atmospheric Conditions

2015 ◽  
Vol 32 (6) ◽  
pp. 1144-1162 ◽  
Author(s):  
Adrian Sescu ◽  
Charles Meneveau
Keyword(s):  
Thermal Stratification ◽  
Layer Structure ◽  
Potential Temperature ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Shear Stresses ◽  
Column Model ◽  
Large Eddy ◽  
Single Column ◽  
Single Column Model

AbstractEffects of atmospheric thermal stratification on the asymptotic behavior of very large wind farms are studied using large-eddy simulations (LES) and a single-column model for vertical distributions of horizontally averaged field variables. To facilitate comparisons between LES and column modeling based on Monin–Obukhov similarity theory, the LES are performed under idealized conditions of statistical stationarity in time and fully developed conditions in space. A suite of simulations are performed for different thermal stratification levels and the results are used to evaluate horizontally averaged vertical profiles of velocity, potential temperature, vertical turbulent momentum, and heat flux. Both LES and the model show that the stratification significantly affects the atmospheric boundary layer structure, its height, and the surface fluxes. However, the effects of the wind farm on surface heat fluxes are found to be relatively small in both LES and the single-column model. The surface fluxes are the result of two opposing trends: an increase of mixing in wakes and a decrease in mixing in the region below the turbines due to reduced momentum fluxes there for neutral and unstable cases, or relatively unchanged shear stresses below the turbines in the stable cases. For the considered cases, the balance of these trends yields a slight increase in surface flux magnitude for the stable and near-neutral unstable cases, and a very small decrease in flux magnitude for the strongly unstable cases. Moreover, thermal stratification is found to have a negligible effect on the roughness scale as deduced from the single-column model, consistent with the expectations of separation of scale.

scholarly journals Analysis and Prediction of Gap Dynamics in a Secondary Deciduous Broadleaf Forest of Central Japan Using Airborne Multi-LiDAR Observations

2020 ◽  
Vol 13 (1) ◽  
pp. 100
Author(s):  
Kazuho Araki ◽  
Yoshio Awaya
Keyword(s):  
Linear Regression Analysis ◽  
Light Detection And Ranging ◽  
Lidar Data ◽  
Gap Dynamics ◽  
Central Japan ◽  
Broadleaf Forest ◽  
Strong Linear Correlation ◽  
Using Data ◽  
Deciduous Broadleaf Forest ◽  
Lidar Observations

Gaps are important for growth of vegetation on the forest floor. However, monitoring of gaps in large areas is difficult. Airborne light detection and ranging (LiDAR) data make precise gap mapping possible. We formulated a method to describe changes in gaps by time-series tracking of gap area changes using three digital canopy height models (DCHMs) based on LiDAR data collected in 2005, 2011, and 2016 over secondary deciduous broadleaf forest. We generated a mask that covered merging or splitting of gaps in the three DCHMs and allowed us to identify their spatiotemporal relationships. One-fifth of gaps merged with adjacent gaps or split into several gaps between 2005 and 2016. Gap shrinkage showed a strong linear correlation with gap area in 2005, via lateral growth of gap-edge trees between 2005 and 2016, as modeled by a linear regression analysis. New gaps that emerged between 2005 and 2011 shrank faster than gaps present in 2005. A statistical model to predict gap lifespan was developed and gap lifespan was mapped using data from 2005 and 2016. Predicted gap lifespan decreased greatly due to shrinkage and splitting of gaps between 2005 and 2016.

scholarly journals Challenges in Modeling Turbulent Heat Fluxes to Snowpacks in Forest Clearings

2018 ◽  
Vol 19 (10) ◽  
pp. 1599-1616 ◽  
Author(s):  
Jonathan P. Conway ◽  
John W. Pomeroy ◽  
Warren D. Helgason ◽  
Nicholas J. Kinar
Keyword(s):  
Heat Exchange ◽  
Surface Temperature ◽  
Latent Heat ◽  
Turbulent Fluxes ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Snow Surface ◽  
Turbulent Heat Exchange ◽  
Uncertainty Estimates ◽  
Model Tuning

Abstract Forest clearings are common features of evergreen forests and produce snowpack accumulation and melt differing from that in adjacent forests and open terrain. This study has investigated the challenges in specifying the turbulent fluxes of sensible and latent heat to snowpacks in forest clearings. The snowpack in two forest clearings in the Canadian Rockies was simulated using a one-dimensional (1D) snowpack model. A trade-off was found between optimizing against measured snow surface temperature or snowmelt when choosing how to specify the turbulent fluxes. Schemes using the Monin–Obukhov similarity theory tended to produce negatively biased surface temperature, while schemes that enhanced turbulent fluxes, to reduce the surface temperature bias, resulted in too much melt. Uncertainty estimates from Monte Carlo experiments showed that no realistic parameter set could successfully remove biases in both surface temperature and melt. A simple scheme that excludes atmospheric stability correction was required to successfully simulate surface temperature under low wind speed conditions. Nonturbulent advective fluxes and/or nonlocal sources of turbulence are thought to account for the maintenance of heat exchange in low-wind conditions. The simulation of snowmelt was improved by allowing enhanced latent heat fluxes during low-wind conditions. Caution is warranted when snowpack models are optimized on surface temperature, as model tuning may compensate for deficiencies in conceptual and numerical models of radiative, conductive, and turbulent heat exchange at the snow surface and within the snowpack. Such model tuning could have large impacts on the melt rate and timing of the snow-free transition in simulations of forest clearings within hydrological and meteorological models.

scholarly journals Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Case Studies ◽  
Air Temperature ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Aircraft Observation ◽  
Near Surface ◽  
Boundary Layer Height ◽  
Small Scales

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

Subcloud and Cloud-Base Latent Heat Fluxes during Shallow Cumulus Convection

2019 ◽  
Vol 77 (3) ◽  
pp. 1081-1100 ◽  
Author(s):  
Neil P. Lareau
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Latent Heat ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Cloud Base ◽  
Cumulus Convection ◽  
Mixing Ratio ◽  
Convective Boundary ◽  
Water Vapor Mixing Ratio

Abstract Doppler and Raman lidar observations of vertical velocity and water vapor mixing ratio are used to probe the physics and statistics of subcloud and cloud-base latent heat fluxes during cumulus convection at the ARM Southern Great Plains (SGP) site in Oklahoma, United States. The statistical results show that latent heat fluxes increase with height from the surface up to ~0.8Zi (where Zi is the convective boundary layer depth) and then decrease to ~0 at Zi. Peak fluxes aloft exceeding 500 W m−2 are associated with periods of increased cumulus cloud cover and stronger jumps in the mean humidity profile. These entrainment fluxes are much larger than the surface fluxes, indicating substantial drying over the 0–0.8Zi layer accompanied by moistening aloft as the CBL deepens over the diurnal cycle. We also show that the boundary layer humidity budget is approximately closed by computing the flux divergence across the 0–0.8Zi layer. Composite subcloud velocity and water vapor anomalies show that clouds are linked to coherent updraft and moisture plumes. The moisture anomaly is Gaussian, most pronounced above 0.8Zi and systematically wider than the velocity anomaly, which has a narrow central updraft flanked by downdrafts. This size and shape disparity results in downdrafts characterized by a high water vapor mixing ratio and thus a broad joint probability density function (JPDF) of velocity and mixing ratio in the upper CBL. We also show that cloud-base latent heat fluxes can be both positive and negative and that the instantaneous positive fluxes can be very large (~10 000 W m−2). However, since cloud fraction tends to be small, the net impact of these fluxes remains modest.

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