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NASA NTRS2021

Mapping Global Forest Age from Forest Inventories, Biomass and Climate Data

Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. However, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. This study provides a new global distribution of forest age circa 2010, estimated using a machine learning approach trained with more than 40 000 plots using forest inventory, biomass and climate data. First, an evaluation against the plot-level measurements of forest age reveals that the data-driven method has a relatively good predictive capacity of classifying old-growth vs. non-old-growth (precision = 0.81 and 0.99 for old-growth and non-old-growth, respectively) forests and estimating corresponding forest age estimates (NSE = 0.6 – Nash–Sutcliffe efficiency – and RMSE = 50 years – root-mean-square error). However, there are systematic biases of overestimation in young- and underestimation in old-forest stands, respectively. Globally, we find a large variability in forest age with the old-growth forests in the tropical regions of Amazon and Congo, young forests in China, and intermediate stands in Europe. Furthermore, we find that the regions with high rates of deforestation or forest degradation (e.g. the arc of deforestation in the Amazon) are composed mainly of younger stands. Assessment of forest age in the climate space shows that the old forests are either in cold and dry regions or warm and wet regions, while young–intermediate forests span a large climatic gradient. Finally, comparing the presented forest age estimates with a series of regional products reveals differences rooted in different approaches and different in situ observations and global-scale products. Despite showing robustness in cross-validation results, additional methodological insights on further developments should as much as possible harmonize data across the different approaches. The forest age dataset presented here provides additional insights into the global distribution of forest age to better understand the global dynamics in the forest water and carbon cycles. The forest age datasets are openly available at https://doi.org/10.17871/ForestAgeBGI.2021 (Besnard et al., 2021).

Simon Besnard↗

NASA NTRSDate not supplied

An Analysis of Fire Dynamics Inside and Outside Indigenous Territories and Protected Areas in a Brazilian Agricultural Frontier

Sustainable land management, including protected areas, is integral to conserving tropical ecosystems and reducing carbon emissions in the Brazilian Amazon. In disturbed Amazon landscapes fire is commonly used to clear land or old fields for agriculture or pastureland. Human-set fires are the most common driver of deforestation and carbon emissions in Amazonia. Evidence suggests that indigenous groups have also used fire for land management since Pre-Columbian times. However, when used unsustainably, fires in this biome can result in degradation of forest ecosystems, decreased ability to store carbon, and health impacts resulting from smoke and particulate matter. Due to the uptick in fire occurrences in 2019, more restrictions on fire use were implemented in 2019 and 2020. Presidential decrees 9.992/2019 and 10.424/2020 banned fire use completely for periods of 60 and 120 days respectively, except by indigenous communities or authorities. Despite these bans, fire use remained high in both years. In the state of Mato Grosso, agricultural activity and expansion influences the anthropogenic fire regime. Indigenous and protected areas cover approximately 25% of its land area.

remote sensing↗

NASA NTRS2022

Along-Orbit Analysis of GRACE Follow-On Inter-Satellite Laser Ranging Measurements for Sub-Monthly Surface Mass Variations

We examined the sensitivity of GRACE Follow-On (GRACE-FO) laser ranging interferometer (LRI) measurements to sub-monthly time-variable gravity (TVG) signals caused by transient, high-frequency mass changes in the Earth system. GRACE-FO LRI provides complementary inter-satellite ranging measurements with higher precision over a wider range of frequencies than the baseline K-band microwave ranging system. The common approach for studying mass variation relies on the inverted TVG or mascon solutions over a period of, for example, one month or 10 days which are adversely affected by temporal aliasing and/or smoothing. In this article, we present the alternative along-orbit analysis methodology in terms of line-of-sight gravity difference (LGD) to fully exploit the higher precision LRI measurements for examination of sub-monthly mass changes. The discrepancy between “instantaneous” LGD LRI observations and monthly mean LGD (from Level-2 data) at satellite altitude indicates the sub-monthly gravitational variability not captured by monthly-mean solutions. In conjunction with the satellite ocean altimetry observations, high frequency non-tidal atmosphere and ocean models, and hydrology models, we show that the LGD LRI observations detect the high-frequency oceanic mass variability in the Argentine Basin and the Gulf of Carpentaria, and sub-monthly variations in surface (river) water in the Amazon Basin. We demonstrate the benefits gained from repeat ground track analysis of GRACE-FO LRI data in the case of the Amazon surface water flow. The along-orbit analysis methodology based on LGD LRI time series presented here is especially suitable for quantifying temporal and spatial evolution of extreme, rapidly changing mass variations.

Khosro Ghobadi-Far↗

NASA NTRS2022

The Ozone–Climate Penalty Over South America and Africa By 2100

Climate change has the potential to increase surface ozone (O3) concentrations, known as the “ozone–climate penalty”, through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozone–climate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15 ppb (model range 12 to 18 ppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozone–climate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx-limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low-NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozone–climate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario.

Surface ozone↗

NASA NTRS2023

Structural Complexity Biases Vegetation Greenness Measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Vegetation indices↗

NASA NTRSDate not supplied

Cloud-Type Mean Cloud Properties and Associated Cloud Radiative Effects in the Tropical “Chimney” Zones Using 20 Years High-Resolution CERES Satellite Data

It has been well known that convection tends to be more intense over land than over ocean and continental convection generally contains wider cores that are protected from entrainment than their oceanic counterparts. How does this difference in convective intensity impact the rest of cloud types and associated cloud radiative effects (CREs)? We select five regions in the tropical “chimney” zones, with two regions over land (Africa and Amazon) and three regions over ocean (eastern and western Pacific, and Atlantic) to understand the differences in the cloud-type mean cloud properties and associated CREs using 20-years high-resolution (2x2 km2) CERES satellite data. The cloud types are based upon the ISCCP classification using the joint cloud-top pressure and cloud optical depth distribution. These five regions are compared to the entire tropics (25°S to 25°N). First, we compare the frequencies of occurrence of cloud types among the regions. Compared to the entire tropics, the “chimney” zones are cloudier, particularly, for cloud types with moderate cloud optical depths in the middle and upper troposphere. Except for the eastern Pacific region, the low-level cloud types are less abundant over land (due to higher boundary layers) and ocean (due to weaker lower-tropospheric subsidence). Over Africa, upper-level clouds are scarcer, due perhaps to weak production of convective anvils related to the drier atmosphere. Second, liquid water path (LWP) and ice water path (IWP) are compared among the regions. Compared to the entire tropics, mean LWPs for moderate cloud optical depths are higher for oceanic regions but lower for Africa while they are slightly lower in the lower troposphere but slightly higher in the middle troposphere for Amazon. Not surprisingly, mean IWPs are higher over land than over ocean, which is directly related to the difference in convective intensity. That is, the explanations to this result are the relatively weak convective intensity over the eastern Pacific and the abundance of anvil clouds over the western Pacific. Both reduce the mean IWPs. The CRE results are still being analyzed because the totally-clear grids (1° x 1°) of the CERES data product should be removed before taking a regional mean of clear-sky fluxes, which cause the wrong signs of CREs for a few cloud types.

cloud radiative effects↗

DOE OSTI2022

Improving sustainable tropical forest management with voluntary carbon markets

Due to a rapidly changing climate, voluntary carbon markets are gaining momentum and should be leveraged to improve and expand tropical sustainable forest management plans, limiting carbon emissions and enhancing critical carbon sinks. By sequestering more carbon than any other terrestrial ecosystem — ~1 Pg C yr –1 — tropical forests provide crucial natural climate solutions and opportunities in the evolving voluntary carbon market. Here, we argue that some issues with the current sustainable management of tropical forests can be addressed using carbon-focused sustainable forest management (SFM + C) to leverage financial resources for tropical forest carbon storage and sequestration. We suggest an extended harvest cycle in SFM + C and calculate an associated potential increase in aboveground carbon stocks of commercial timber of 1.26 Mg C ha –1 after each cycle in the Brazilian Amazon. The additional carbon storage due to a longer harvest cycle can generate carbon credits worth 152.6 (SD 9.2) US dollars per hectare in 40 years. Considering an average cost of 180 BRL per m3 of commercial timber delivered to the sawmill, an SFM + C plan with a 40-year cycle could generate 28.7% (SD 2.5) more profit than 35-year cycles by combining timber and carbon revenues. A robust carbon price could incentivize the further extension of harvest cycles, providing a monetary return that offsets the opportunity cost intrinsic to harvesting under longer cycles. Lastly, we highlight research needs to support tropical SFM + C, which can be part of a global collective effort to limit global warming to below 2 °C above pre-industrial levels.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Intense formation of secondary ultrafine particles from Amazonian vegetation fires and their invigoration of deep clouds and precipitation

New particle formation (NPF) in fire smoke is thought to be unlikely due to large condensation and coagulation sinks that scavenge molecular clusters. We analyze aircraft measurements over the Amazon and find that fires significantly enhance NPF and ultrafine particle (UFP < 50 nm diameter) numbers compared to background conditions, contrary to previous understanding. We identify that the nucleation of dimethylamine with sulfuric acid, which is aided by the formation of extremely low volatility organics in biomass-burning smoke, can overcome the large condensation and coagulation sinks and explain aircraft observations. We show that freshly formed clusters rapidly grow to UFP sizes through biomass-burning secondary organic aerosol formation, leading to a 10-fold increase in UFP number concentrations. Here, we find a contrasting effect of UFPs on deep convective clouds compared to the larger particles from primary emissions for the case investigated here. UFPs intensify the deep convective clouds and precipitation due to increased condensational heating, while larger particles delay and reduce precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The Impacts of Rotational Mixing on the Precipitation Simulated by a Convection Permitting Model

With increased availability of computational resources, regional and global scale convection-permitting model (CPM, Δx ~ 1–10 km) simulations are becoming more common. CPMs have improved accuracy in their representation of deep convection and mesoscale convective systems (MCSs) compared to coarser resolution models. However, CPMs still exhibit convective cloud and precipitation biases relative to observations, notably a lesser frequency of light precipitation rates and greater frequency of heavy precipitation rates. In this work we hypothesize that these CPM biases are related to under-resolved mixing between convective updrafts and their surrounding environment. To test this hypothesis, we introduce a parameterization to the Weather Research and Forecasting model (WRF) that adds a small angular rotation of the grid-scale flow about the axis perpendicular to the plane of convective drafts. This rotated flow is then allowed to alter advection of moisture and hydrometeors. The effects of such mixing on precipitation characteristics are evaluated in month-long 4-km grid spacing simulations over the Amazon. The enhanced mixing transports moisture and condensate from convective cores to other areas including downdrafts. This increases the frequency of low-precipitable water and light precipitation. It also decreases the frequency of intense precipitation from isolated deep convection and MCSs, increases cloud top temperatures, reduces radar echo-top heights, and increases overall precipitation by altering the relationship of precipitation with precipitable water, in better agreement with observations. The results suggest when optimized using multiple observations, such an approach may provide a path toward more accurate representation of convection and precipitation statistics in convection-permitting simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Hydrometeor Transport and the Stratiform Water Budget in Amazonian Mesoscale Convective Systems

A significant portion of precipitation falls within the stratiform regions of mesoscale convective systems (MCSs). These regions are formed from convective clouds that have either weakened and formed a horizontally stratified structure or have advected hydrometeors to form a trailing-stratiform region, with further precipitation growth promoted by in situ dynamical and microphysical processes. Green Ocean Amazon 2014/5 (GoAmazon2014/5) field campaign observations are used to quantify the stratiform water budget of six MCSs (three each from the wet and dry seasons) utilizing the framework from Leary and Houze, with an emphasis on the transfer of hydrometeors (C A ) from the convective to the stratiform regions. The storms were predominantly leading-line/trailing-stratiform MCSs, but two had embedded convection in the stratiform region, which can complicate water budget calculations. A pulse-like pattern with a mean interval of 21 min occurs in C A during each storm resulting from a lag between the initial convective updrafts and the subsequent hydrometeor transport and sedimentation in the stratiform region. Here, the peaks in C A were followed by peaks in hydrometeor growth associated with the mesoscale updraft (C mu ) in the stratiform region. Averaged over the six storms, the positive contributions of C A and C mu to the stratiform water budget were roughly equal, although storm-to-storm variations existed. Negative contributions from evaporation below cloud base in the mesoscale downdraft and detrainment from the stratiform region into the nonprecipitating anvil cloud and environment accounted for 53% and 21% of the sum of C A and C mu , respectively, resulting in a mean stratiform region precipitation efficiency of 26%.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Low diffusive methane emissions from the main channel of a large Amazonian run-of-the-river reservoir attributed to high methane oxidation

The global development of hydropower dams has rapidly expanded over the last several decades and has spread to historically non-impounded systems such as the Amazon River's main low land tributaries in Brazil. Despite the recognized significance of reservoirs to the global methane (CH4) emission, the processes controlling this emission remain poorly understood, especially in Tropical reservoirs. Here we evaluate CH4 dynamics in the main channel and downstream of the Santo Antônio hydroelectric reservoir, a large tropical run-of-the-river (ROR) reservoir in Amazonia. This study is intended to give a snapshot of the CH4 dynamics during the falling water season at the initial stage after the start of operations. Our results show substantial and higher CH4 production in reservoirs' littoral sediment than in the naturally flooded areas downstream of the dam. Despite the large production in the reservoir or naturally flooded areas, high CH4 oxidation in the main channel keep the concentration and fluxes of CH4 in the main channel low. Similar CH4 concentrations in the reservoir and downstream close to the dam suggest negligible degassing at the dam, but stable isotopic evidence indicates the presence of a less oxidized pool of CH4 after the dam. ROR reservoirs are designed to disturb the natural river flow dynamics less than traditional reservoirs. If enough mixing and oxygenation remain throughout the reservoir's water column, naturally high CH4 oxidation rates can also remain and limit the diffusive CH4 emissions from the main channel. Nevertheless, it is important to highlight that our results focused on emissions in the deep and oxygenated main channel. High emissions, mainly through ebullition, may occur in the vast and shallow areas represented by bays and tributaries. However, detailed assessments are still required to understand the impacts of this reservoir on the annual emissions of CH4.

Amazon, aquatic, biogeochemistry, carbon cycling, ↗

NASA NTRS2015

Structural Dynamics of Tropical Moist Forest Gaps

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest structure (top down) differ from traditional field measurements (bottom up), and necessitate clear-cut definitions unencumbered by the wisdom of a field observer. We offer a new definition of a forest gap that is driven by forest dynamics and consistent with precise ranging measurements from airborne lidar data and tall, multi-layered tropical forest structure. We used 1000 ha of multi-temporal lidar data (2008, 2012) at two sites, the Tapajos National Forest and Ducke Reserve, to study gap dynamics in the Brazilian Amazon. Here, we identified dynamic gaps as contiguous areas of significant growth, that correspond to areas greater than 10 sq m, with height less than 10 m. Applying the dynamic definition at both sites, we found over twice as much area in gap at Tapajos National Forest (4.8%) as compared to Ducke Reserve (2.0%). On average, gaps were smaller at Ducke Reserve and closed slightly more rapidly, with estimated height gains of 1.2 m y-1 versus 1.1 m y-1 at Tapajos. At the Tapajos site, height growth in gap centers was greater than the average height gain in gaps (1.3 m y-1 versus 1.1 m y-1). Rates of height growth between lidar acquisitions reflect the interplay between gap edge mortality, horizontal ingrowth and gap size at the two sites. We estimated that approximately 10% of gap area closed via horizontal ingrowth at Ducke Reserve as opposed to 6% at Tapajos National Forest. Height loss (interpreted as repeat damage and/or mortality) and horizontal ingrowth accounted for similar proportions of gap area at Ducke Reserve (13% and 10%, respectively). At Tapajos, height loss had a much stronger signal (23% versus 6%) within gaps. Both sites demonstrate limited gap contagiousness defined by an increase in the likelihood of mortality in the immediate vicinity ((is) approximately 6 m) of existing gaps.

Structural Dynamics of Tropical Moist Forest Gaps↗

NASA NTRS2018

Hosting Hyrax in the Cloud While Preserving the User Experience

Cloud object stores enable data providers to reduce costs and provide uniform data servers across organizational divisions. This talk will address how new capabilities provided by cloud computing can be used with existing software so that users get the benefits provided by cloud technology (access to data at lower cost, e.g.) without disrupting their existing workflow(s). We will address ways to reduce response latency often associated with Cloud object stores and ways to simulate the hierarchy of a POSIX file system using a key-value object store. This work is based an on-going NASA EED2 project to enhance the Hyrax data server for operation in the Amazon Web Services Cloud.

Hyrax server↗

NASA NTRS2019

OPeNDAP Clients, Aggregation and S3

In this talk, we will discuss our work for testing OPeNDAP client access of data stored in the Amazon S3 cloud storage using a set of common analysis tools including Panoply, Jupyter Notebooks with Python xarray, NCO command line tool package, ArcGIS, and GDAL. We will also discuss our ongoing work on improving performance in Hyrax aggregation functionality.

Amazon S3↗

NASA NTRSDate not supplied

Leveraging CSPP: Building a cloud based direct broadcast processing system

Reducing the time that it takes to have useful satellite information is very important because timely access allows for more informed decision making. This is especially true in time critical situations like disaster response and financial market analysis. One way to achieve reductions in the overall time between information capture and delivery to use the direct broadcast from weather satellites. In this work, we describe a state driven satellite information system that captures a satellite’s direct broadcast signal and uses cloud-based resources to provide end-user controlled processing. The system takes advantage of the reliability and customizability of Amazon Web Services to provide fast and reliable access to a system that takes the direct broadcast signal and leverages the CSPP software as well as dynamically supplied end-user processing modules to produce a user desired information product. Finally, we describe the development process and how a flexible design allowed for changes as the capabilities of the processing platform evolved and the lessons we learned from the process.

CSPP↗

DOE OSTI2021

Long-term single-column model intercomparison of diurnal cycle of precipitation over midlatitude and tropical land

General Circulation Models (GCMs) have for decades exhibited difficulties in modelling the diurnal cycle of precipitation (DCP). This issue can be related to inappropriate representation of the processes controlling sub-diurnal phenomena like convection. In this study, 11 single-column versions of GCMs are used to investigate the interactions between convection and environmental conditions, processes that control nocturnal convections, and the transition from shallow to deep convection on a diurnal time-scale. Long-term simulations are performed over two continental land sites: the Southern Great Plains (SGP) in the USA for 12 summer months from 2004 to 2015 and the Manacapuru site at the central Amazon (MAO) in Brazil for two full years from 2014 to 2015. The analysis is done on two regimes: afternoon convective regime and nocturnal precipitation regime. Most models produce afternoon precipitation too early, likely due to the missing transition of shallow-to-deep convection in these models. At SGP, the unified convection schemes better simulate the onset time of precipitation. At MAO, models produce the heating peak in a much lower level compared with observation, indicating too shallow convection in the models. For nocturnal precipitation, models that produce most of nocturnal precipitation all allow convection to be triggered above the boundary layer. This indicates the importance of model capability to detect elevated convection for simulating nocturnal precipitation. Sensitivity studies indicate that (a) nudging environmental variables towards observations has a minor impact on DCP, (b) unified treatment of shallow and deep convection and the capability to capture mid-level convection can help models better capture DCP, and (c) the interactions of the atmosphere with other components in the climate system (e.g. land) are also important for DCP simulations in coupled models. Finally, these results provide long-term statistical insights on which physical processes are essential in climate models to simulate DCP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Diurnal cycle of precipitation over the tropics and central United States: intercomparison of general circulation models

Diurnal precipitation is a fundamental mode of variability that climate models have difficulty in accurately simulating. Here, in this work, the diurnal cycle of precipitation (DCP) in participating climate models from the Global Energy and Water Exchanges' DCP project is evaluated over the tropics and central United States. Common model biases such as excessive precipitation over the tropics, too frequent light-to-moderate rain, and the failure to capture propagating convection in the central United States still exist. Over the central United States, the issues of too weak rainfall intensity in climate runs is well improved in their hindcast runs with initial conditions from numerical weather prediction analyses. But the improvement is minimal over the central Amazon. Incorporating the role of the large-scale environment in convective triggering processes helps resolve the phase-locking issue in many models where precipitation often incorrectly peaks near noon due to maximum insolation over land. Allowing air parcels to be lifted above the boundary layer improves the simulation of nocturnal precipitation which is often associated with the propagation of mesoscale systems. Including convective memory in cumulus parameterizations acts to suppress light-to-moderate rain and promote intense rainfall; however, it also weakens the diurnal variability. Simply increasing model resolution (with cumulus parameterizations still used) cannot fully resolve the biases of low-resolution climate models in DCP. The hierarchy modeling framework from this study is useful for identifying the missing physics in models and testing new development of model convective processes over different convective regimes.

58 GEOSCIENCES↗

DOE OSTI2025

The role of thermal stratification on the co‐spectral properties of momentum transport above an Amazonian forest

The influence of thermal stratification on the turbulent kinetic energy balance has been widely studied; however, its influence on the turbulent stress remains less explored in the presence of tall vegetated canopies and less ideal micrometeorological conditions. Here, the impact of thermal stratification on turbulent momentum flux is considered in the roughness sublayer (RSL) and the atmospheric surface layer (ASL) using the Amazon Tall Tower Observatory (ATTO) in Brazil. A scalewise co‐spectral budget (CSB) model is developed using standard closure schemes for the pressure–velocity decorrelation. The CSB revealed that the co‐spectrum ${F}_{wu}\left({k}_x\right)$ between longitudinal (u') and vertical (w') velocity fluctuations is impacted by the energy spectrum of the vertical velocity ${E}_{ww}\left({k}_x\right)$ and the much less studied longitudinal heat‐flux co‐spectrum ${F}_{u{\theta}_{\mathrm{v}}}\left({k}_x\right)$, where ${\theta}_{\mathrm{v}}^{\prime }$ are temperature fluctuations and ${k}_x$ is the longitudinal wavenumber. Under stable, very stable, and dynamic–convective conditions, the scaling exponent ${F}_{wu}\left({k}_x\right)$ in for the inertial subrange (ISR) scales is dominated by ${F}_{u{\theta}_{\mathrm{v}}}\left({k}_x\right)$ instead of ${E}_{ww}\left({k}_x\right)$. A near ${k}_x^{-7/3}$scaling in ${F}_{u{\theta}_{\mathrm{v}}}\left({k}_x\right)$ robust to large variations in thermal stratification is found, whereas the Kolmogorov ISR scaling for ${E}_{ww}\left({k}_x\right)\sim {k}_x^{-5/3}$ is not found. The scale‐dependent decorrelation time between u' and w' is dominated by ${\epsilon}^{-1/3}{k}_x^{-2/3}$ in the ISR, but is nearly constant for eddies larger than the vertical velocity integral scale, regardless of stability. Implications of these findings for generalized stability correction functions that are based on the turbulent stress budget instead of the turbulent kinetic energy budget are discussed.

canopy turbulence↗