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Sonic anemometers from Physics Site-3 and Site-9 provide wind components and virtual temperature. The energy balance Bowen ratio (EBBR) station at Physics site-3 provides measurements of the surface fluxes of latent and sensible heat, net radiation, and surface soil heat flux.
Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in large-scale atmospheric models.
The aim of the research was to investigate the relationship between wind, waves, and radar backscatter from water surface. To this end, three field experiments with periods of 2 to 4 weeks were carried out during summer months in 1988, 1989 and 1990. For these periods, the University of Washington group provided (1) environmental parameters such as wind speed, wind stress, and atmospheric stratification through measurements of surface fluxes (of momentum, sensible heat and latent heat) and of air and water temperatures; and (2) wave height spectra including both the dominant waves and the short gravity-capillary waves. Surface flux measurements were performed by using our well tested instruments: a K-Gill twin propeller-vane anemometer and a fast response thermocouple psychrometer. Wave heights were measured by a resistance wire wave gauge. The University of Kansas group was responsible for the operation of the microwave radars.
The eddy correlation (ECOR) flux measurement system provides in situ, half-hour measurements of surface turbulent fluxes of momentum, sensible heat, latent heat, and carbon dioxide (CO 2 ) at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility sites. ARM’s ECORs also historically measured methane fluxes at Utqiaġvik and Oliktok Point, Alaska. The fluxes are obtained with the eddy covariance technique, which involves correlation of the vertical wind component with the horizontal wind component, the air temperature, the water vapor density, and the CO 2 concentration.
Spatial variation of some parameters measured on two aircraft flying 100-km box and 200-km triangular patterns at low levels in the atmospheric boundary layer during the Joint Air Sea Interaction Experiment in the North Atlantic was studied. The variation should be representative of summer conditions in mid-latitude oceans. The variance density of remotely sensed sea surface temperature, corrected for sky reflection, is found to depend on the one-dimensional wave number raised to the power of approximately -5/3. Nonuniform clouds add low-frequency variance to observations of a downward looking radiometer and result in steeper slope of the spectra of uncorrected sea surface temperature. Turbulent fluxes of momentum, sensible heat, and moisture were determined with the bulk formulae from the parameters (wind speed, temperature, specific humidity, and sea surface temperature) measured from the aircraft. The averages of these fluxes over each flight leg were compared with the fluxes determined from the parameters averaged over the same leg. The difference is negligible, showing that spatially averaged observations, such as those from spaceborne sensors, can be used in the bulk formulae to evaluate the fluxes.
This data contains output from the pumphouse eddy covariance tower that includes shortwave radiation, longwave radiation, net radiation, air temperature, relative humidity, as well as sensible, latent, and ground heat fluxes. Also included is calculated evapotranspiration from the latent heat flux and the latent heat of vaporization. All data are on a daily timestep and displayed in Mountain Time. The data has been processed, and Quality Assurance / Quality Control (QA/QC) was done, but any daily gaps in the data have not been filled in. This research was funded by the Department of Energy and performed as part of the Watershed Function Scientific Focus Area. This research aimed to constrain evapotranspiration in a high-elevation catchment.The dataset includes one comma-separated values (CSV) data file (EddyCovariance_MeteorlogicalVariables_CrestedButtePumphouse.csv). Additionally, three metadata CSV files are included: (1) location metadata file (locations.csv), which contains location metadata and coordinates; (2) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
Surface evaluation of sensible and latent heat flux densities and the components of the radiation balance were desired for various vegetative surfaces during the ASCOT84 experiment to compare with modeled results and to relate these values to drainage winds. Five battery operated data systems equipped with sensors to determine the above values were operated for 105 station days during the ASCOT84 experiment. The Bowen ratio energy balance technique was used to partition the available energy into the sensible and latent heat flux densities. A description of the sensors and battery operated equipment used to collect and process the data is presented. In addition, improvements and modifications made since the 1984 experiment are given. Details of calculations of soil heat flow at the surface and an alternate method to calculate sensible and latent heat flux densities are provided.
Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.
Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.
The annual energy budget of the Arctic Ocean is characterized by a net heat loss at the air-sea interface that is balanced by oceanic heat transport into the Arctic. The energy loss at the air-sea interface is due to the combined effects of radiative, sensible, and latent heat fluxes. The inflow of heat by the ocean can be divided into two components: the transport of water masses of different temperatures between the Arctic and the Atlantic and Pacific Oceans and the export of sea ice, primarily through Fram Strait. Two 150-year simulations (1950-2099) of a global climate model are used to examine how this balance might change if atmospheric greenhouse gases (GHGs) increase. One is a control simulation for the present climate with constant 1950 atmospheric composition, and the other is a transient experiment with observed GHGs from 1950 to 1990 and 0.5% annual compounded increases of CO2 after 1990. For the present climate the model agrees well with observations of radiative fluxes at the top of the atmosphere, atmospheric advective energy transport into the Arctic, and surface air temperature. It also simulates the seasonal cycle and summer increase of cloud cover and the seasonal cycle of sea-ice cover. In addition, the changes in high-latitude surface air temperature and sea-ice cover in the GHG experiment are consistent with observed changes during the last 40 and 20 years, respectively. Relative to the control, the last 50-year period of the GHG experiment indicates that even though the net annual incident solar radiation at the surface decreases by 4.6 W(per square meters) (because of greater cloud cover and increased cloud optical depth), the absorbed solar radiation increases by 2.8 W(per square meters) (because of less sea ice). Increased cloud cover and warmer air also cause increased downward thermal radiation at the surface so that the net radiation into the ocean increases by 5.0 Wm-2. The annual increase in radiation into the ocean, however, is compensated by larger increases in sensible and latent heat fluxes out of the ocean. Although the net energy loss from the ocean surface increases by 0.8 W (per square meters), this is less than the interannual variability, and the increase may not indicate a long-term trend. The seasonal cycle of heat fluxes is significantly enhanced. The downward surface heat flux increases in summer (maximum 2 of 19 W per square meters or 23% in June) while the upward heat flux increases in winter (maximum of 16 W per square meters or 28% in November). The increased downward flux in summer is due to a combination of increases in absorbed solar and thermal radiation and smaller losses of sensible and latent heat. The increased heat loss in winter is due to increased sensible and latent heat fluxes, which in turn are due to reduced sea-ice cover. On the other hand, the seasonal cycle of surface air temperature is damped, as there is a large increase in winter temperature but little change in summer.
A number of preliminary concepts for the measurement or inference of fluxes across the air-sea interface through remote sensing are proposed. All the methods are achievable from aircraft with state-of-the-art technology. Only one is now ready for space implementation. The focus is on cold outbreaks. Sensible (latent) heat flux is inferred from the difference between initial surface air temperature (vapor mixing ratio) and the downwind SST (and corresponding saturation mixing ratio). The downwind growth rate of the PBL as measured by lidar also provides estimates of surface heating and the cross-inversion entrainment velocity. The lidar also provides a measure of the depth of the inversion and its penetration by surface-forced convection; this permits estimates of the surface heat flux. Lidar and radiometric measurements of cloud top height and temperature provide means of deducing the temperature sounding downstream so that heating is computed with the aid of a known sounding upstream.
Woody encroachment has contributed to documented changes world-wide and locally in the southwestern U.S. Specifically, in North Texas rangelands encroaching mesquite (Prosopis glandulosa var. glandulosa) a known N-fixing species has caused changes in aboveground biomass. While measurements of aboveground plant production are relatively common, measures of soil N availability are scarce and vary widely. N trace gas emissions (nitric and nitrous oxide) flom soils reflect patterns in current N cycling rates and availability as they are stimulated by inputs of organic and inorganic N. Quantification of N oxide emissions from savanna soils may depend upon the spatial distribution of woody plant canopies, and specifically upon the changes in N availability and cycling and subsequent N trace gas production as influenced by the shift from herbaceous to woody vegetation type. The main goal of this research was to determine whether remotely sensible parameters of vegetation structure and soil type could be used to quantify biogeochemical changes in N at local, landscape and regional scales. To accomplish this goal, field-based measurements of N trace gases were carried out between 2000-2001, encompassing the acquisition of imaging spectrometer data from the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) on September 29, 2001. Both biotic (vegetation type and soil organic N) and abiotic (soil type, soil pH, temperature, soil moisture, and soil inorganic N) controls were analyzed for their contributions to observed spatial and temporal variation in soil N gas fluxes. These plot level studies were used to develop relationships between spatially extensive, field-based measurements of N oxide fluxes and remotely sensible aboveground vegetation and soil properties, and to evaluate the short-term controls over N oxide emissions through intensive field wetting experiments. The relationship between N oxide emissions, remotely-sensed parameters (vegetation cover, and soil type), and physical controls (soil moisture, and temperature) permitted the regional scale quantification of soil N oxides emissions. Landscape scale analysis linking N oxide emissions with cover change revealed an alleviation from N limitation following mesquite invasion. This study demonstrated the advantage of using N trace gases as a measure of ecosystem N availability combined with remote sensing to characterize the spatial heterogeneity in ecosystem parameters at a scale commensurate with field-based measurements of these properties. Woody vegetation encroachment provided an opportunity to capitalize on detection of the remotely-sensible parameter of woody cover as it relates to belowground biogeochemical processes that determine N trace gas production. The first spatially-explicit estimates of NO flux were calculated based on Prosopis fractional cover derived from high resolution remote sensing estimates of fractional woody cover (< 4 m) for a 120 sq km region of North Texas. An assessment of both N stocks and fluxes from the study revealed an alleviation of N limitation at this site experiencing recent woody encroachment. Many arid and semi-arid regions of the world are experiencing woody invasions, often of N-fixing species. The issue of woody encroachment is in the center of an ecological and political debate. Improving the links between biogeochemical processes and remote sensing of ecosystem properties will improve our understanding of biogeochemical processes at the regional scale, thus providing a means to address issues of land-use and land-cover change.
The BOREAS AFM-3 team used the NCAR Electra aircraft data to make measurements of the fluxes of momentum, sensible and latent heat, carbon dioxide, and ozone over the entire BOREAS region to tie together measurements made in both the SSA and the NSA in 1994. These data were also used to study the planetary boundary layer using both in situ and remote sensing measurements. This data set contains both the aircraft flux and the moving window data. These data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were sigmficantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-china peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and gradient, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation apd associated moisture transport and convection.
The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were significantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-China peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and merit, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation and associated moisture transport and convection.
This study explores the effect of surface sensible and latent heat fluxes on monsoon depressions using a series of idealized convection-permitting simulations. Each experiment is initialized with a small-amplitude wave that is allowed to grow within an environment representative of the South Asian monsoon. Comparing experiments with and without interactive surface heat fluxes, it is found that these fluxes enhance the growth of the simulated vortices. Without interactive surface fluxes, the strengthening period is short and the vortices fail to reach intensities characteristic of stronger monsoon depressions. Using a large set of experiments in which the vertical and meridional shear are systematically varied, it is found that surface heat fluxes enhance intensity the most when the upper-level shear is weak, the lower-level shear and associated moist static energy (MSE) gradient are sufficiently steep, and the lower-level meridional shear is strong. Here, these experiments reveal two different regimes of convection-coupled monsoon depression growth: one in which convection is driven by MSE advection and one in which it is driven by surface heat fluxes and quasigeostrophic forcing for ascent. Both regimes require sufficiently strong meridional shear to achieve initial growth by barotropic instability.
Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production.
The surface heat budgets, sea surface temperature (SST), clouds and winds in the tropical western Pacific are analyzed and compared for the periods April-June 1998 and 1999. The spring of 1998 is in the later phase of a strong El Nino, whereas the spring of 1999 is in a period of a La Nina. The surface shortwave (SW) and longwave (LW) radiative fluxes are retrieved from Japanese Geostationary Meteorological Satellite radiance measurements, while the surface turbulent fluxes (latent and sensible heat) are derived from SSM/I-Inferred surface air humidity and winds. The SST and sea-air temperature differences are taken from NCEP/NCAR reanalysis. Deep convection is inferred from the outgoing longwave radiation of NOAA's polar-orbiting satellites. The longitudinal shift in maximum SST, deep convection and winds during El Nino and La Nina have a large impact on the spatial distribution of surface heating. Changes in clouds between these two periods have a large impact on the monthly-mean radiative heating, exceeding 60 W m(exp -2) over large oceanic regions. Similarly, the differences in wind speeds and SST have a large impact on the latent cooling, exceeding 40 W m(exp -2) over large oceanic areas. However, the maximum impacts on radiative and latent heat fluxes occur in different regions. The regions of maximum impact on radiative fluxes coincide with the regions of maximum change in clouds, whereas regions of maximum impact on turbulent heat fluxes coincide with the regions of maximum change in trade winds. The time-evolution of SST in relation to that of surface heat fluxes and winds are investigated and compared between the two El Nino and La Nina periods. In regions where wind speeds (or wind stresses) are large, the change in SST agrees well with the change in the net surface heating, indicating a deep ocean mixed layer associated with strong trade winds. On the other hand, in regions where radiative fluxes are large, the change in SST does not agree well with the change in the net surface heating, indicating the importance of solar radiation penetrating through the bottom of the shadow ocean mixed layer.