Surface thermal heterogeneities, dispersive fluxes and the conundrum of unaccounted statistical spatial inhomogeneities

2020 ◽  
Author(s):  
Marc Calaf ◽  
Travis Morrison ◽  
Fabien Margairaz ◽  
Alexei Perelet ◽  
Chad W. Higgins ◽  
...  
Keyword(s):  
Land Surface ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Lower Boundary ◽  
Surface Region ◽  
Surface Heterogeneity ◽  
Surface Energy Budget ◽  
Spatial Homogeneity ◽  
Near Surface ◽  
Dispersive Fluxes

<p>The use of Numerical Weather Prediction (NWP) models is ubiquitous in our daily lives, whether to decide what to wear, to plan for the weekend, invest on wind turbines, decide strategies for food security or to forecast atmosphere-driven natural disasters, to name a few. Currently, intrinsic to most NWP models is the assumption of spatial homogeneity at kilometer to sub-kilometer scales when, for example, classic similarity scaling relationships are applied to account for unresolved near-surface momentum, heat and mass exchanges. While advances in computation (and computing) are enabling finer grid resolutions in NWP, representing land-atmosphere exchange processes at the lower boundary remains a challenge (regardless of the numerical resolution but not independent from it). This is partially a result of the fact that land-surface heterogeneity exists at all spatial scales and its variability does not ‘average’ out with decreasing scales. Such variability need not rapidly blend away from the boundary and thereby impacts the spatial distribution of fluxes throughout the near-surface region of the atmosphere.</p><p>     While, the effects of spatial surface heterogeneities have long been minimized under the assumption of an existing blending length-scale, in this work evidence is presented of the consequential effect of such surface heterogeneities. Specifically, canonical experiments based on in-situ measurements and high-resolution numerical simulations quantify the effect of surface thermal heterogeneities on an otherwise homogeneous planar surface. Therefore, such near-canonical case describes inhomogeneous scalar transport in an otherwise planar homogeneous flow when thermal stratification is weak or absent. In this work, the interaction between the characteristic length scales of the surface heterogeneities, and the scales of resolved fluid dynamics transport is further unraveled. Dispersive fluxes naturally appear as a means to account for unresolved, and time-lasting advection fluxes generated by a-priori unresolved spatial thermal heterogeneities. Results illustrate that dispersive fluxes can represent as much as 40% of the total resolved advection flux under weak wind conditions, and remain relevant under strong winds. Furthermore, results of this work appear not to only be relevant in the treatment of unresolved heterogeneities in NWP models, but also in understanding the unresolved problem of surface energy budget closure.</p>

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

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.

scholarly journals The Effect of Soil and Vegetation Parameters in the ECMWF Land Surface Scheme

2004 ◽  
Vol 5 (6) ◽  
pp. 1131-1146 ◽  
Author(s):  
H. Richter ◽  
A. W. Western ◽  
F. H. S. Chiew
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Weather Prediction ◽  
Lower Boundary ◽  
Soil Parameters ◽  
Model Parameters ◽  
Lower Boundary Condition ◽  
Land Surface Scheme ◽  
Vegetation Parameters ◽  
Surface Scheme

Abstract Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999. VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.

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

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

<p>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 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>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.</p>

scholarly journals Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

2017 ◽  
Vol 56 (10) ◽  
pp. 2821-2844 ◽  
Author(s):  
Eun-Gyeong Yang ◽  
Hyun Mee Kim
Keyword(s):  
Relative Humidity ◽  
East Asia ◽  
Geopotential Height ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Lower Troposphere ◽  
Near Surface ◽  
Skill Scores ◽  
Regional Reanalysis

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

scholarly journals A fast visible-wavelength 3D radiative transfer model for numerical weather prediction visualization and forward modeling

2020 ◽  
Vol 13 (6) ◽  
pp. 3235-3261
Author(s):  
Steven Albers ◽  
Stephen M. Saleeby ◽  
Sonia Kreidenweis ◽  
Qijing Bian ◽  
Peng Xian ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Radiative Transfer ◽  
Numerical Weather Prediction ◽  
Land Surface ◽  
Weather Prediction ◽  
Lower Boundary ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Numerical Weather ◽  
Visible Wavelength

Abstract. Solar radiation is the ultimate source of energy flowing through the atmosphere; it fuels all atmospheric motions. The visible-wavelength range of solar radiation represents a significant contribution to the earth's energy budget, and visible light is a vital indicator for the composition and thermodynamic processes of the atmosphere from the smallest weather scales to the largest climate scales. The accurate and fast description of light propagation in the atmosphere and its lower-boundary environment is therefore of critical importance for the simulation and prediction of weather and climate. Simulated Weather Imagery (SWIm) is a new, fast, and physically based visible-wavelength three-dimensional radiative transfer model. Given the location and intensity of the sources of light (natural or artificial) and the composition (e.g., clear or turbid air with aerosols, liquid or ice clouds, precipitating rain, snow, and ice hydrometeors) of the atmosphere, it describes the propagation of light and produces visually and physically realistic hemispheric or 360∘ spherical panoramic color images of the atmosphere and the underlying terrain from any specified vantage point either on or above the earth's surface. Applications of SWIm include the visualization of atmospheric and land surface conditions simulated or forecast by numerical weather or climate analysis and prediction systems for either scientific or lay audiences. Simulated SWIm imagery can also be generated for and compared with observed camera images to (i) assess the fidelity and (ii) improve the performance of numerical atmospheric and land surface models. Through the use of the latter in a data assimilation scheme, it can also (iii) improve the estimate of the state of atmospheric and land surface initial conditions for situational awareness and numerical weather prediction forecast initialization purposes.

scholarly journals Microscale Numerical Prediction over Montreal with the Canadian External Urban Modeling System

2011 ◽  
Vol 50 (12) ◽  
pp. 2410-2428 ◽  
Author(s):  
Sylvie Leroyer ◽  
Stéphane Bélair ◽  
Jocelyn Mailhot ◽  
Ian B. Strachan
Keyword(s):  
Land Surface ◽  
Deterministic Model ◽  
Weather Prediction ◽  
Grid Size ◽  
Metropolitan Region ◽  
Balance Model ◽  
Surface Model ◽  
Limited Area ◽  
Computational Domain ◽  
Near Surface

AbstractThe Canadian urban and land surface external modeling system (known as urban GEM-SURF) has been developed to provide surface and near-surface meteorological variables to improve numerical weather prediction and to become a tool for environmental applications. The system is based on the Town Energy Balance model for the built-up covers and on the Interactions between the Surface, Biosphere, and Atmosphere land surface model for the natural covers. It is driven by coarse-resolution forecasts from the 15-km Canadian regional operational model. This new system was tested for a 120-m grid-size computational domain covering the Montreal metropolitan region from 1 May to 30 September 2008. The numerical results were first evaluated against local observations of the surface energy budgets, air temperature, and humidity taken at the Environmental Prediction in Canadian Cities (EPiCC) field experiment tower sites. As compared with the regional deterministic 15-km model, important improvements have been achieved with this system over urban and suburban sites. GEM-SURF’s ability to simulate the Montreal surface urban heat island was also investigated, and the radiative surface temperatures from this system and from two systems operational at the Meteorological Service of Canada were compared, that is, the 15-km regional deterministic model and the so-called limited-area model with 2.5-km grid size. Comparison of urban GEM-SURF outputs with remotely sensed observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals relatively good agreement for urban and natural areas.

scholarly journals Forecasting global atmospheric CO<sub>2</sub>

2014 ◽  
Vol 14 (9) ◽  
pp. 13909-13962 ◽  
Author(s):  
A. Agustí-Panareda ◽  
S. Massart ◽  
F. Chevallier ◽  
S. Boussetta ◽  
G. Balsamo ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Real Time ◽  
Diurnal Cycle ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Physical Models ◽  
Atmospheric Co2 ◽  
Co2 Fluxes ◽  
Near Surface ◽  
Forecasting System

Abstract. A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 satellite retrievals, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO2 forecast will be reduced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.

scholarly journals Characterizing the multi-scale spatial structure of land-atmosphere interactions with information theory

2011 ◽  
Vol 8 (2) ◽  
pp. 3435-3462 ◽  
Author(s):  
N. A. Brunsell ◽  
M. C. Anderson
Keyword(s):  
Information Theory ◽  
Heat Flux ◽  
Spatial Structure ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Vegetation Index ◽  
Spatial Scales ◽  
Near Surface ◽  
Multi Scale

Abstract. A more thorough understanding of the multi-scale spatial structure of land surface heterogeneity will enhance understanding of the relationships and feedbacks between land surface conditions, mass and energy exchanges between the surface and the atmosphere, and regional meteorological and climatological conditions. The objectives of this study were to (1) quantify which spatial scales are dominant in determining the evapotranspiration flux between the surface and the atmosphere and (2) to quantify how different spatial scales of atmospheric and surface processes interact for different stages of the phenological cycle. We used the ALEXI/DisALEXI model for three days (DOY 181, 229 and 245) in 2002 over the Ft. Peck Ameriflux site to estimate the latent heat flux from Landsat, MODIS and GOES satellites. We then applied a multiresolution information theory methodology to quantify these interactions across different spatial scales and compared the dynamics across the different sensors and different periods. We note several important results: (1) spatial scaling characteristics vary with day, but are usually consistent for a given sensor, but (2) different sensors give different scalings, and (3) the different sensors exhibit different scaling relationships with driving variables such as fractional vegetation and near surface soil moisture. In addition, we note that while the dominant length scale of the vegetation index remains relatively constant across the dates, but the contribution of the vegetation index to the derived latent heat flux varies with time. We also note that length scales determined from MODIS are consistently larger than those determined from Landsat. These results aid in identifying the dominant cross-scale nature of local to regional biosphere-atmosphere interactions.

La représentation des surfaces continentales pour la prévision numérique du temps

2020 ◽  
pp. 059
Author(s):  
Stéphane Bélair ◽  
Aaron Boone
Keyword(s):  
Land Surface ◽  
Weather Prediction ◽  
Physical Processes ◽  
Prognostic Variables ◽  
Near Surface ◽  
Land Data Assimilation ◽  
Surface Scheme ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Assimilation System

La représentation des processus physiques associés aux surfaces continentales, incluant les échanges de chaleur, d'humidité et de quantité de mouvement avec l'atmosphère, ainsi que l'analyse des conditions initiales pour ses principales variables influencent de manière substantielle la prévision atmosphérique près de la surface, en plus d'avoir un impact sur la production de nuages et des précipitations. Comment les surfaces continentales sont-elles représentées dans les modèles de prévision numérique du temps ? Quelles sont les problématiques propres à la prévision numérique du temps dans cette représentation ? Ces questions sont examinées dans cet article en utilisant des exemples tirées du modèle Isba (Interactions solbiosphère-atmosphère) développé à Météo-France et du système d'assimilation de surface du Service météorologique du Canada. The representation of physical processes over land, including heat, humidity, and momentum exchanges with the atmosphere, as well as accurate initialisation of its main prognostic variables, has a substantial influence on numerical prediction of the near-surface atmosphere and on the formation of clouds and precipitation. How are continental surfaces represented in numerical weather prediction (NWP) models? What are the scientific issues specif ic to NWP for this representation? These are questions examined in this study using examples from the Isba (Interactions Soil-Biosphere-Atmosphere) land surface scheme developed at Météo-France and the land data assimilation system from the Meteorological Service of Canada.

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