scholarly journals On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems?

2019 ◽  
Author(s):  
Brendan Byrne ◽  
Dylan B. A. Jones ◽  
Kimberly Strong ◽  
Saroja M. Polavarapu ◽  
Anna B. Harper ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Net Ecosystem Exchange ◽  
Terrestrial Ecosystems ◽  
Atmospheric Co2 ◽  
Strong Correlations ◽  
Climate Anomalies ◽  
Temperature And Precipitation ◽  
The Tropics ◽  
Emergent Constraint ◽  
The Impact

Abstract. Interannual variations in temperature and precipitation impact the carbon balance of terrestrial ecosystems, leaving an imprint in atmospheric CO2. Quantifying the impact of climate anomalies on the net ecosystem exchange (NEE) of terrestrial ecosystems can provide a constraint to evaluate terrestrial biosphere models against, and may provide an emergent constraint on the response of terrestrial ecosystems to climate change. We investigate the spatial scales over which interannual variability in NEE can be constrained using atmospheric CO2 observations from the Greenhouse Gases Observing Satellite (GOSAT). NEE anomalies are calculated by performing a series of inversion analyses using the GEOS-Chem model to assimilate GOSAT observations. Monthly NEE anomalies are compared to proxies, variables which are associated with anomalies in the terrestrial carbon cycle, and to upscaled NEE estimates from FLUXCOM. Strong agreement is found in the timing of anomalies in the GOSAT flux inversions with soil temperature and FLUXCOM. Strong correlations are obtained (P  RNINO3.4) in the tropics on continental and larger scales, and in the northern extratropics on sub-continental scales during the summer (R2 ≥ 0.49). These results, in addition to a series of observing system simulation experiments that were conducted, provide evidence that GOSAT flux inversions can isolate anomalies in NEE on continental and larger scales. However, in both the tropics and northern extratropics, the agreement between the inversions and the proxies/FLUXCOM is sensitive to the flux inversion configuration. Our results suggest that regional scales are likely the minimum scales that can be resolved in the tropics using GOSAT observations, but obtaining robust NEE anomaly estimates on these scales may be difficult.

scholarly journals On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems?

2019 ◽  
Vol 19 (20) ◽  
pp. 13017-13035 ◽  
Author(s):  
Brendan Byrne ◽  
Dylan B. A. Jones ◽  
Kimberly Strong ◽  
Saroja M. Polavarapu ◽  
Anna B. Harper ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Spatial Scales ◽  
Net Ecosystem Exchange ◽  
Terrestrial Ecosystems ◽  
Atmospheric Co2 ◽  
Terrestrial Biosphere ◽  
Climate Anomalies ◽  
Temperature And Precipitation ◽  
The Tropics ◽  
The Impact

Abstract. Interannual variations in temperature and precipitation impact the carbon balance of terrestrial ecosystems, leaving an imprint in atmospheric CO2. Quantifying the impact of climate anomalies on the net ecosystem exchange (NEE) of terrestrial ecosystems can provide a constraint to evaluate terrestrial biosphere models against and may provide an emergent constraint on the response of terrestrial ecosystems to climate change. We investigate the spatial scales over which interannual variability in NEE can be constrained using atmospheric CO2 observations from the Greenhouse Gases Observing Satellite (GOSAT). NEE anomalies are calculated by performing a series of inversion analyses using the GEOS-Chem adjoint model to assimilate GOSAT observations. Monthly NEE anomalies are compared to “proxies”, variables that are associated with anomalies in the terrestrial carbon cycle, and to upscaled NEE estimates from FLUXCOM. Statistically significant correlations (P<0.05) are obtained between posterior NEE anomalies and anomalies in soil temperature and FLUXCOM NEE on continental and larger scales in the tropics, as well as in the northern extratropics on subcontinental scales during the summer (R2≥0.49), suggesting that GOSAT measurements provide a constraint on NEE interannual variability (IAV) on these spatial scales. Furthermore, we show that GOSAT flux inversions are generally better correlated with the environmental proxies and FLUXCOM NEE than NEE anomalies produced by a set of terrestrial biosphere models (TBMs), suggesting that GOSAT flux inversions could be used to evaluate TBM NEE fluxes.

scholarly journals Implementation and validation of a new irrigation scheme in the ISBA land surface model

2021 ◽  
Author(s):  
Arsène Druel ◽  
Simon Munier ◽  
Anthony Mucia ◽  
Clément Albergel ◽  
Jean-Christophe Calvet
Keyword(s):  
Land Surface ◽  
Vegetation Type ◽  
Spatial Scales ◽  
Terrestrial Ecosystems ◽  
Moisture Stress ◽  
Surface Model ◽  
Irrigation Scheme ◽  
Area Index ◽  
Natural Processes ◽  
The Impact

Abstract. With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited, especially in the representation of the impact of agriculture on land surface variables. This is particularly true for agro-hydrological processes related to a strong human control on freshwater. While most LSMs consider natural processes only, the development of human-related processes, e.g. crop phenology and irrigation in LSMs, is key. In this study we present the implementation of a new irrigation scheme in the ISBA (Interaction between Soil, Biosphere, and Atmosphere) LSM. This highly flexible scheme is designed to account for various configurations and can be applied at different spatial scales. For each vegetation type within a model grid cell, three irrigation systems can be used at the same time. A limited number of parameters are used to control (1) the amount of water used for irrigation, (2) irrigation triggering (based on the soil moisture stress) and (3) crop seasonality (emergence, harvesting). After a presentation of the simulations of the new scheme at a plot scale, an evaluation is proposed over Nebraska (USA). This region is chosen for its high irrigation density and because independent observations of irrigation practices can be used to verify the simulated irrigation amounts. The ISBA simulations with and without the irrigation scheme are compared to different satellite-based observations. The comparison shows that the irrigation scheme improves the simulated vegetation variables such as leaf area index and gross primary productivity and other variables largely impacted by irrigation such as evapotranspiration and land surface temperature. In addition to a better representation of land surface processes, the results point to potential applications of this new version of the ISBA model for water resource monitoring and climate change impact studies.

scholarly journals An Interpretation of Cloud Overlap Statistics

2015 ◽  
Vol 72 (8) ◽  
pp. 2877-2889 ◽  
Author(s):  
Adrian M. Tompkins ◽  
Francesca Di Giuseppe
Keyword(s):  
Spatial Scales ◽  
Physical Phenomenon ◽  
Cloud System ◽  
Length Scale ◽  
Clear Sky ◽  
Data Truncation ◽  
Sampling Scale ◽  
The Tropics ◽  
The Impact ◽  
Fractal Cloud

Abstract Observational studies have shown that the vertical overlap of cloudy layers separated by clear sky can exceed that of the random overlap assumption, suggesting a tendency toward minimum overlap. In addition, the rate of decorrelation of vertically continuous clouds with increasing layer separation is sensitive to the horizontal scale of the cloud scenes used. The authors give a heuristic argument that these phenomena result from data truncation, where overcast or single cloud layers are removed from the analysis. This occurs more frequently as the cloud sampling scale falls progressively below the typical cloud system scale. The postulate is supported by sampling artificial cyclic and subsequently more realistic fractal cloud scenes at various length scales. The fractal clouds indicate that the degree of minimal overlap diagnosed in previous studies for discontinuous clouds could result from sampling randomly overlapped clouds at spatial scales that are 30%–80% of the cloud system scale. Removing scenes with cloud cover exceeding 50% from the analysis reduces the impact of data truncation, with discontinuous clouds not minimally overlapped and the decorrelation of continuous clouds less sensitive to the sampling scale. Using CloudSat–CALIPSO data, a decorrelation length scale of approximately 4.0 km is found. In light of these results, the previously documented dependence of overlap decorrelation length scale on latitude is not entirely a physical phenomenon but can be reinterpreted as resulting from sampling cloud systems that increase significantly in size from the tropics to midlatitudes using a fixed sampling scale.

scholarly journals Prior biosphere model impact on global terrestrial CO<sub>2</sub> fluxes estimated from OCO-2 retrievals

2019 ◽  
Vol 19 (20) ◽  
pp. 13267-13287 ◽  
Author(s):  
Sajeev Philip ◽  
Matthew S. Johnson ◽  
Christopher Potter ◽  
Vanessa Genovesse ◽  
David F. Baker ◽  
...  
Keyword(s):  
Transport Model ◽  
Net Ecosystem Exchange ◽  
Co2 Flux ◽  
Inverse Model ◽  
Chemical Transport Model ◽  
Error Statistics ◽  
Prior Model ◽  
The Tropics ◽  
Biosphere Model ◽  
The Impact

Abstract. This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC yr−1). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

scholarly journals Empirically Derived Sensitivity of Vegetation to Climate across Global Gradients of Temperature and Precipitation

2017 ◽  
Vol 30 (15) ◽  
pp. 5835-5849 ◽  
Author(s):  
Gregory R. Quetin ◽  
Abigail L. S. Swann
Keyword(s):  
Water Demand ◽  
Ecosystem Functioning ◽  
Spatial Scales ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Atmospheric Water ◽  
Temperature And Precipitation ◽  
Two Factors ◽  
Climate Interactions ◽  
Climate Space

The natural composition of terrestrial ecosystems can be shaped by climate to take advantage of local environmental conditions. Ecosystem functioning (e.g., interaction between photosynthesis and temperature) can also acclimate to different climatological states. The combination of these two factors thus determines ecological–climate interactions. A global empirical map of the sensitivity of vegetation to climate is derived using the response of satellite-observed greenness to interannual variations in temperature and precipitation. Mechanisms constraining ecosystem functioning are inferred by analyzing how the sensitivity of vegetation to climate varies across climate space. Analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate at large spatial scales. In hot and wet locations, vegetation is greener in warmer years despite temperatures likely exceeding thermally optimum conditions. However, sunlight generally increases during warmer years, suggesting that the increased stress from higher atmospheric water demand is offset by higher rates of photosynthesis. The sensitivity of vegetation transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm yr−1 °C−1, twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate.

scholarly journals Genetic structure in the endosymbiont Breviolum ‘muscatinei’ is correlated with geographical location, environment and host species

2021 ◽  
Vol 288 (1946) ◽  
pp. 20202896
Author(s):  
Brendan H. Cornwell ◽  
Luis Hernández
Keyword(s):  
Genetic Structure ◽  
Host Species ◽  
Isolation By Distance ◽  
Spatial Scales ◽  
Geographical Location ◽  
Wide Range ◽  
Genetic Patterns ◽  
Coral Reef Ecosystems ◽  
The Tropics ◽  
The Impact

Corals and cnidarians form symbioses with dinoflagellates across a wide range of habitats from the tropics to temperate zones. Notably, these partnerships create the foundation of coral reef ecosystems and are at risk of breaking down due to climate change. This symbiosis couples the fitness of the partners, where adaptations in one species can benefit the holobiont. However, the scales over which each partner can match their current—and future—environment are largely unknown. We investigated population genetic patterns of temperate anemones ( Anthopleura spp.) and their endosymbiont Breviolum ‘muscatinei’ , across an extensive geographical range to identify the spatial scales over which local adaptation is possible. Similar to previously published results, two solitary host species exhibited isolation by distance across hundreds of kilometres. However, symbionts exhibited genetic structure across multiple spatial scales, from geographical location to depth in the intertidal zone, and host species, suggesting that symbiont populations are more likely than their hosts to adaptively mitigate the impact of increasing temperatures.

Climate-forced changes of bio-productivity of Belorussian terrestrial ecosystems

2019 ◽  
pp. 77-88
Author(s):  
S. A. Lysenko
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Terrestrial Ecosystems ◽  
Vegetation Period ◽  
Climatic Trend ◽  
Vegetation Growth ◽  
Current Century ◽  
The Impact

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.

scholarly journals Scale dependence of galaxy biasing investigated by weak gravitational lensing: An assessment using semi-analytic galaxies and simulated lensing data

2018 ◽  
Vol 613 ◽  
pp. A15 ◽  
Author(s):  
Patrick Simon ◽  
Stefan Hilbert
Keyword(s):  
Gravitational Lensing ◽  
Spatial Scales ◽  
Scale Dependence ◽  
Reconstruction Technique ◽  
Weak Gravitational Lensing ◽  
Physical Scale ◽  
The Galaxy ◽  
Galaxy Bias ◽  
The Impact ◽  
Lens Galaxies

Galaxies are biased tracers of the matter density on cosmological scales. For future tests of galaxy models, we refine and assess a method to measure galaxy biasing as a function of physical scalekwith weak gravitational lensing. This method enables us to reconstruct the galaxy bias factorb(k) as well as the galaxy-matter correlationr(k) on spatial scales between 0.01hMpc−1≲k≲ 10hMpc−1for redshift-binned lens galaxies below redshiftz≲ 0.6. In the refinement, we account for an intrinsic alignment of source ellipticities, and we correct for the magnification bias of the lens galaxies, relevant for the galaxy-galaxy lensing signal, to improve the accuracy of the reconstructedr(k). For simulated data, the reconstructions achieve an accuracy of 3–7% (68% confidence level) over the abovek-range for a survey area and a typical depth of contemporary ground-based surveys. Realistically the accuracy is, however, probably reduced to about 10–15%, mainly by systematic uncertainties in the assumed intrinsic source alignment, the fiducial cosmology, and the redshift distributions of lens and source galaxies (in that order). Furthermore, our reconstruction technique employs physical templates forb(k) andr(k) that elucidate the impact of central galaxies and the halo-occupation statistics of satellite galaxies on the scale-dependence of galaxy bias, which we discuss in the paper. In a first demonstration, we apply this method to previous measurements in the Garching-Bonn Deep Survey and give a physical interpretation of the lens population.

scholarly journals Response of altitudinal vegetation belts of the Tianshan Mountains in northwestern China to climate change during 1989–2015

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Zhang ◽  
Lu-yu Liu ◽  
Yi Liu ◽  
Man Zhang ◽  
Cheng-bang An
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Global Climate ◽  
Animal Husbandry ◽  
Forest Tree ◽  
Tianshan Mountains ◽  
Northwestern China ◽  
Temperature And Precipitation ◽  
Altitudinal Belts ◽  
The Impact

AbstractWithin the mountain altitudinal vegetation belts, the shift of forest tree lines and subalpine steppe belts to high altitudes constitutes an obvious response to global climate change. However, whether or not similar changes occur in steppe belts (low altitude) and nival belts in different areas within mountain systems remain undetermined. It is also unknown if these, responses to climate change are consistent. Here, using Landsat remote sensing images from 1989 to 2015, we obtained the spatial distribution of altitudinal vegetation belts in different periods of the Tianshan Mountains in Northwestern China. We suggest that the responses from different altitudinal vegetation belts to global climate change are different. The changes in the vegetation belts at low altitudes are spatially different. In high-altitude regions (higher than the forest belts), however, the trend of different altitudinal belts is consistent. Specifically, we focused on analyses of the impact of changes in temperature and precipitation on the nival belts, desert steppe belts, and montane steppe belts. The results demonstrated that the temperature in the study area exhibited an increasing trend, and is the main factor of altitudinal vegetation belts change in the Tianshan Mountains. In the context of a significant increase in temperature, the upper limit of the montane steppe in the eastern and central parts will shift to lower altitudes, which may limit the development of local animal husbandry. The montane steppe in the west, however, exhibits the opposite trend, which may augment the carrying capacity of pastures and promote the development of local animal husbandry. The lower limit of the nival belt will further increase in all studied areas, which may lead to an increase in surface runoff in the central and western regions.

scholarly journals Projected Changes in Climate Extremes Using CMIP6 Simulations Over SREX Regions

2021 ◽  
Vol 5 (3) ◽  
pp. 481-497
Author(s):  
Mansour Almazroui ◽  
Fahad Saeed ◽  
Sajjad Saeed ◽  
Muhammad Ismail ◽  
Muhammad Azhar Ehsan ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Extreme Events ◽  
First Century ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Temperature And Precipitation ◽  
Projected Change ◽  
Twenty First Century ◽  
Projected Changes ◽  
The Tropics

AbstractThis paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

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