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At least 181 records · Page 10

Surface Radiation Budget (SRB) Release 2.5 QC Longwave 3 hourly Data in Native Format (SRB_REL2.5_QCLW_3HRLY)

This data set contains average surface downward longwave flux, surface net longwave flux, and surface longwave cloud radiative forcing at three hourly intervals for each day for the entire glob between 07/01/1983 and 06/30/2005. These LW surface radiative parameters were derived with the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3-hourly; Temporal_Resolution_Range=3-hourly].

SURFACE DOWNWARD LONGWAVE FLUX↗

Soil surface CO2 fluxes and the carbon budget of a grassland

Measurements of soil surface CO2 fluxes are reported for three sites within the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) area, and simple empirical equations are fit to the data to provide predictions of soil fluxes from environmental observations. A prototype soil chamber, used to make the flux measurements, is described and tested by comparing CO2 flux measurements to a 40-L chamber, a 1-m/cu chamber, and eddy correlation. Results suggest that flux measurements with the prototype chamber are consistent with measurements by other methods to within about 20 percent. A simple empirical equation based on 10-cm soil temperature, 0- to 10-cm soil volumetric water content, and leaf area index predicts the soil surface CO2 flux with a rms error of 1.2 micro-mol sq m/s for all three sites. Further evidence supports using this equation to evaluate soil surface CO2 during the 1987 FIFE experiment. The soil surface CO2 fluxes when averaged over 24 hours are comparable to daily gross canopy photosynthetic rates. For 6 days of data the net daily accumulation of carbon is about 0.6 g CO2 sq m/d; this is only a few percent of the daily gross accumulation of carbon by photosynthesis. As the soil became drier in 1989, the net accumulation of carbon by the prairie increased, suggesting that the soil flux is more sensitive to temperature and drought than the photosynthetic fluxes.

Norman, J. M.↗

A Grad-Shafranov model for compact quasisymmetric stellarators

A Grad-Shafranov equation (GSE) valid for compact quasisymmetric stellarators is derived by an asymptotic expansion around a vacuum field carried to first order. We obtain an equation for the existence of flux surfaces leading up to the GSE. The flux surface label must simultaneously satisfy the existence equation and the GSE, which generally leads to an overdetermined problem. We show how the overdetermined problem can be resolved within our model for a class of hybrid devices similar to that studied by Henneberg and Plunk [Phys. Rev. Res. 6, L022052 (2024)]. We are also able to solve the existence equation for flux surfaces analytically in the most general case by introducing a special coordinate system. This will enable us to carry out an optimization seeking to minimize the error in our GSE while obeying the flux surface existence equation, which will allow us to find solutions outside the class of hybrid devices. This will allow for a coarse-grained approximate search in the space of quasisymmetric equilibria that should be faster than a conventional stellarator optimization. Nevertheless, it would still be necessary to fine-tune the approximate solutions using conventional tools to obtain a more precise optimized equilibrium.

Nikulsin, N. (ORCID:0000000318611777)↗

The influence of surface heat fluxes on the growth of idealized monsoon depressions

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.

54 ENVIRONMENTAL SCIENCES↗

Outer atmospheres of cool stars. II - Mg II flux profiles and chromospheric radiative loss rates

International Ultraviolet Explorer high-resolution spectra of the Mg II lines at 2796, 2803 A in 15 stars of spectral type G2-M2 including a wide range of luminosities are presented. These spectra are calibrated in absolute flux units at earth and at the stellar surface, and the chromospheric radiative loss rates in the Mg II lines are compared with corresponding rates in the Ca II H, K, and 8542 lines. The ratio of Mg II surface flux to total surface flux is found to be independent of stellar luminosity and thus gravity; may decrease slowly with decreasing effective temperature, and increases with decreasing period among RS Canum Venaticorum binaries. The factor of 10 range in this ratio at each effective temperature may be due to differences in the fractional surface area covered by plages and may indicate that stars of all luminosity classes have chromospheric plages. In this small data sample no evidence is found that the Mg II line surface fluxes indicate whether a star possesses a transition region and hot corona.

Basri, G. S.↗

Towards a More Realistic Representation of NASA CERES-derived Surface Radiative Fluxes during Polar Night: A Comparison with the MOSAiC Field Campaign

The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. We further examine this source of error by examining selected case studies in which the disagreements in radiative fluxes and clouds are large.

J Brant Dodson↗

Upper ocean mixing, surface heat fluxes, and heat content variability in the upper 150 m during Hurricane Laura (2020)

Observations (from thermistor sensors and a hurricane glider) and model-based temperature were used to answer questions including the following: 1) What physical and environmental conditions explain the rapid intensification of Hurricane Laura? 2) How did the pre-existing warm mixed layer at Stone mooring (StM) influence the degree of cooling in the mixed layer? 3) How did vertical mixing, surface heat fluxes, and advective processes collectively shape the mixed layer heat evolution at StM? Observations measured by thermistor sensors showed that Hurricane Laura induced a cooling of -1.2oC in the mixed layer when Hurricane Laura’s wind speed increased to 47 m/s on 26 August. This contrasts with the -1.04oC mixed layer temperature change estimated from model-based temperature. At StM, the presence of a 31oC warm mixed layer and elevated heat content (60-80kJ/cm2) effectively preconditioned the upper ocean ahead of Hurricane Laura’s passage. After Hurricane Laura passed, turbulent mixing associated with the storm transported the heat anomalies downward into subsurface layers. In addition, this study shows that a surface heat flux of 5.04 kJ/cm2 supported the intensity of Hurricane Laura as it traversed over the StM. Using a mixed layer heat balance model, this study shows that entrainment flux and surface flux mostly contributed to the observed change in the mixed layer temperature.

Tsai, Senam↗

Remote sounding of surface radiative fluxes in cirrus cloudy conditions

It has been long recognized that radiation and radiation perturbations play a critical role in the climate system. Surface radiative fluxes are useful parameters for monitoring global change, for understanding of the effects of clouds on the radiation field, and for improving parameterization of surface sensible and latent heat fluxes. Monitoring of the radiation budget at the top of the atmosphere has been one of the prime satellite programs for the last 30 years. However, monitoring radiative fluxes at the surface over the globe from space cannot be performed in a direct way at the present time. In particular, since clouds are the prime regulators of the radiative fluxes, uncertainties in the retrieved cloud parameters, which are inputs to radiative transfer models, can introduce significant errors in the computed radiative fluxes. Thus, remote sounding of surface radiative fluxes in cloudy conditions requires the development of both satellite cloud retrieval scheme and radiation models. In this paper, we present results of computed surface radiative fluxes in cirrus cloudy conditions using a cirrus cloud retrieval scheme and a detailed radiative transfer program. Comparisons have been made between the computed surface radiative fluxes and the ground-based radiometer measurements obtained during FIRE-II-IFO, which was carried out near Coffeyville, Kansas, during November and December, 1991.

Ou, S. C.↗

Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.

Steffen, K.↗

Large scale surface heat fluxes

The heat flux through the ocean surface, Q, is the sum of the net radiation at the surface, the latent heat flux into the atmosphere, and the sensible heat flux into the atmosphere (all fluxes positive upwards). A review is presented of the geographical distribution of Q and its constituents, and the current accuracy of measuring Q by ground based measurements (both directly and by 'bulk formulae') is assessed. The relation of Q to changes of oceanic heat content, heat flux, and SST is examined and for each of these processes, the accuracy needed for Q is discussed. The needed accuracy for Q varies from process to process, varies geographically, and varies with the time and space scale considered.

Sarachik, E. S.↗

Towards A More Realistic Representation of Nasa Ceres-Derived Surface Radiative Fluxes During Polar Night: A Comparison With the Mosaic Field Campaign

The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable.

J. Brant Dodson↗

Surface energy fluxes at Central Florida during the convection and precipitation electrification experiment

One of the objectives of CaPE is to better understand the convective process in central and south Florida during the warm season. The energy and moisture exchanges between the surface and the atmosphere are closely related to this process. Some recent studies have shown that the surface energy balance plays an important role in the climatic fields (Shukla and Mintz, 1982; Sud and Smith, 1985; Sato et. al, 1989). Surface energy fluxes and related surface processes such as evapotranspiration and sensible heat transfer directly effect the temperature, humidity, cloud formation and precipitation. For example, mesoscale circulation around a discontinuity in vegetation type were shown to be stronger with wet soil than with dry soil using an evapotranspiration model (Pinty et. al, 1989). In order to better describe the processes in the atmosphere at various scales and improve our ability of modeling and predicting weather related events, it is crucial to understand the mechanism of surface energy transfer in relation to atmospheric events. Surface energy flux measurements are required to fully understand the interactions between the atmosphere and the surface.

Nie, D.↗

Surface Turbulent Fluxes Over Pack Ice Inferred from TOVS Observations

A one-dimensional, atmospheric boundary layer model is coupled to a thermodynamic ice model to estimate the surface turbulent fluxes over thick sea ice. The principal forcing parameters in this time-dependent model are the air temperature, humidity, and wind speed at a specified level (either at 2 m or at 850 mb) and the downwelling surface radiative fluxes. The free parameters. are the air temperature, humidity, and wind speed profiles below the specified level, the surface skin temperature, the ice temperature profile, and the surface turbulent fluxes. The goal is to determine how well we can estimate the turbulent surface heat and momentum fluxes using forcing parameters from atmospheric temperatures and radiative fluxes retrieved from the TIROS-N Operational Vertical Sounder (TOVS) data. Meteorological observations from the Lead Experiment (LeadEx, April 1992) ice camp are used to validate turbulent fluxes computed with the surface observations and the results are used to compare with estimates based on radio-sonde observations or with estimates based on TOVS data. We find that the TOVS-based estimates of the stress are significantly more accurate than those found with a constant geostrophic drag coefficient, with a root-mean-square error about half as large. This improvement is due to stratification effects included in the boundary layer model. The errors in the sensible heat flux estimates, however, are large compared to the small mean values observed during the field experiment.

Lindsay, R. W.↗

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

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.

Agricultural Sciences↗

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗

On the Relationship Between CYGNSS Surface Heat Fluxes and the Life Cycle of Low-Latitude Ocean Extratropical Cyclones

Surface latent and sensible heat fluxes are important for extratropical cyclone evolution and intensification. Because extratropical cyclone genesis often occurs at low-latitude, CYGNSS surface latent and sensible heat flux retrievals are composited to provide a mean picture of their spatial distribution in low-latitude oceanic extratropical cyclones. CYGNSSn heat fluxes are not affected by heavy precipitation and offer observations of storms with frequent revisit times. Consistent with prior results obtained for cyclones in the Gulf Stream region, the fluxes are strongest in the wake of the cold fronts, and weakest to negative in the warm sector in advance of the cold fronts. As cyclone strength increases, or mean precipitable water decreases, the maximum in surface heat fluxes increases while the minimum decreases. This impacts the changes in fluxes during cyclone intensification: the post-cold frontal surface heat flux maximum increases due to the increase in near surface winds. During cyclone dissipation, the fluxes in this sector decrease, due to the decrease in winds and in temperature and humidity contrast. The warm sector minimum decreases throughout the entire cyclone lifetime and is mostly driven by sea-air temperature and humidity contrast changes. However, during cyclone dissipation, the surface heat fluxes increase along the cold front in a narrow band to the east, independently from changes in the cyclone characteristics. This suggests that, during cyclone dissipation, energy transfers from the ocean to the atmosphere are linked to frontal in addition to synoptic-scale processes.

CYGNSS↗

A program of data synthesis from the ALSEP/CPLEE ALSEP/SIDE, and Explorer 35 magnetometer to investigate lunar terminator and nightside particle fluxes and surface interactions

Lunar nightside electron fluxes were studied with the aid of the ALSEP/CPLEE and other instruments. The flux events were shown to be due to (a) electrons propagating upstream from the earth's bow shock, (b) electrons thermalized and scattered to the lunar surface by disturbances along the boundary of the lunar solarwind cavity, and (c) solar wind electrons scattered to the lunar surface by lunar limb shocks and/or compressional disturbances. These electrons were identified as a cause of the high night surface negative potentials observed in tha ALSEP/SIDE ion data. A study was also made of the shadowing of magnetotail plasma sheet electrons by interactions between the lunar body and the ambient magnetic field and by interactions between charged particles and lunar remnant magnetic fields. These shadowing effects were shown to modify lunar surface and near-lunar potential distributions.

Reasoner, D. L.↗