GSWP-2: Multimodel Analysis and Implications for Our Perception of the Land Surface

2006 ◽  
Vol 87 (10) ◽  
pp. 1381-1398 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Xiang Gao ◽  
Mei Zhao ◽  
Zhichang Guo ◽  
Taikan Oki ◽  
...  
Keyword(s):  
Land Surface ◽  
Good Description ◽  
Regional Scale ◽  
Co2 Concentration ◽  
Atmospheric Measurements ◽  
Modeling Tools ◽  
Sources And Sinks ◽  
Spatial Gradients ◽  
Continental Scale ◽  
Regional Flow

Quantification of sources and sinks of carbon at global and regional scales requires not only a good description of the land sources and sinks of carbon, but also of the synoptic and mesoscale meteorology. An experiment was performed in Les Landes, southwest France, during May–June 2005, to determine the variability in concentration gradients and fluxes of CO2 The CarboEurope Regional Experiment Strategy (CERES; see also http://carboregional.mediasfrance.org/index) aimed to produce aggregated estimates of the carbon balance of a region that can be meaningfully compared to those obtained from the smallest downscaled information of atmospheric measurements and continental-scale inversions. We deployed several aircraft to sample the CO2 concentration and fluxes over the whole area, while fixed stations observed the fluxes and concentrations at high accuracy. Several (mesoscale) meteorological modeling tools were used to plan the experiment and flight patterns. Results show that at regional scale the relation between profiles and fluxes is not obvious, and is strongly influenced by airmass history and mesoscale flow patterns. In particular, we show from an analysis of data for a single day that taking either the concentration at several locations as representative of local fluxes or taking the flux measurements at those sites as representative of larger regions would lead to incorrect conclusions about the distribution of sources and sinks of carbon. Joint consideration of the synoptic and regional flow, fluxes, and land surface is required for a correct interpretation. This calls for an experimental and modeling strategy that takes into account the large spatial gradients in concentrations and the variability in sources and sinks that arise from different land use types. We briefly describe how such an analysis can be performed and evaluate the usefulness of the data for planning of future networks or longer campaigns with reduced experimental efforts.

scholarly journals Detecting regional variability in sources and sinks of carbon dioxide: a synthesis

2009 ◽  
Vol 6 (1) ◽  
pp. 2331-2355 ◽  
Author(s):  
A. J. Dolman ◽  
C. Gerbig ◽  
J. Noilhan ◽  
C. Sarrat ◽  
F. Miglieta
Keyword(s):  
Carbon Balance ◽  
Regional Scale ◽  
Concentration Field ◽  
Co2 Concentration ◽  
Future Research ◽  
Model Errors ◽  
Regional Variability ◽  
Sources And Sinks ◽  
Induced Flow ◽  
Made In

Abstract. The papers of this special issue are put into the context of progress made in experiments and modelling aimed at understanding the carbon balance at regional scale. Mesoscale meteorological effects such as seas breezes and topographically induced flow have the potential to generate significant heterogeneities in the CO2 concentration fields. This has consequences for the interpretation or inverse modelling, of sources and sinks from these concentrations. Results of experiments executed in South West France in 2005 and 2007 are described and subsequent analysis of modelling results. Overall we conclude that we now have capability to model with mesoscale models realistic CO2 concentration fields, within the constraint of other model errors, such as in boundary layer characteristics. We show that progress has been made in inverting concentration field at regional scale and indicate the direction of future research efforts.

scholarly journals Comparison of different evaporation estimates over the African continent

2013 ◽  
Vol 10 (7) ◽  
pp. 8421-8465 ◽  
Author(s):  
P. Trambauer ◽  
E. Dutra ◽  
S. Maskey ◽  
M. Werner ◽  
F. Pappenberger ◽  
...  
Keyword(s):  
Land Surface ◽  
Hydrological Model ◽  
Regional Scale ◽  
African Continent ◽  
Land Surface Models ◽  
Continental Scale ◽  
Actual Evaporation ◽  
Balance Approach ◽  
Surface Models ◽  
Energy Balance Approach

Abstract. Evaporation is a key process in the water cycle, with implications ranging from water management, to weather forecast and climate change assessments. The estimation of continental evaporation fluxes is complex and typically relies on continental-scale hydrological or land-surface models. However, it appears that most global or continental-scale hydrological models underestimate evaporative fluxes in some regions of Africa, and as a result overestimate stream flow. Other studies suggest that land-surface models may overestimate evaporative fluxes. In this study, we computed actual evaporation for the African continent using a continental version of the global hydrological model PCR-GLOBWB, which is based on a water balance approach. Results are compared with other independently computed evaporation products: the evaporation results from the ECMWF reanalysis ERA-Interim and ERA-Land (both based on the energy balance approach), the MOD16 evaporation product, and the GLEAM product. Three other alternative versions of the PCR-GLOBWB hydrological model were also considered. This resulted in eight products of actual evaporation, which were compared in distinct regions of the African continent spanning different climatic regimes. Annual totals, spatial patterns and seasonality were studied and compared through visual inspection and statistical methods. The comparison shows that the representation of irrigation areas has an insignificant contribution to the actual evaporation at a continental scale with a 0.5° spatial resolution. The choice of meteorological forcing data has a larger effect on the evaporation results, especially in the case of the precipitation input as different precipitation input resulted in significantly different evaporation in some of the studied regions. ERA-Interim evaporation is generally the highest of the selected products followed by ERA-Land evaporation. The satellite based products (GLEAM and MOD16) do not show regular behaviour when compared to the other products, though this depends on the region and the season considered. The results from this study allow for a better understanding of the differences between products in each climatic region. Through an improved understanding of the causes of differences between these products and their uncertainty, this study provides information to improve the quality of evaporation products for the African continent and, consequently, leads to improved water resources assessments at regional scale.

scholarly journals Atmospheric inversion for cost effective quantification of city CO<sub>2</sub> emissions

2015 ◽  
Vol 15 (21) ◽  
pp. 30693-30756 ◽  
Author(s):  
L. Wu ◽  
G. Broquet ◽  
P. Ciais ◽  
V. Bellassen ◽  
F. Vogel ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Power Plants ◽  
Energy Use ◽  
Residential Buildings ◽  
Co2 Concentration ◽  
Road Transport ◽  
Inversion Method ◽  
Atmospheric Measurements ◽  
Atmospheric Inversion

Abstract. Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44 % of global energy-related CO2, and are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25 m a.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (~ 12 million inhabitants and 11.4 Tg C emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5 % (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by ~ 42 % but still corresponds to an annual uncertainty that is two times larger than the target of 5 %. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32 % for commercial and residential buildings, by 33 % for road transport and by 18 % for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15 % 2-sigma annual uncertainty for dispersed building emissions, and 18 % for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus deliver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments).

scholarly journals Mesoscale modelling of the CO<sub>2</sub> interactions between the surface and the atmosphere applied to the April 2007 CERES field experiment

2009 ◽  
Vol 6 (4) ◽  
pp. 633-646 ◽  
Author(s):  
C. Sarrat ◽  
J. Noilhan ◽  
P. Lacarrère ◽  
E. Ceschia ◽  
P. Ciais ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Mesoscale Model ◽  
Regional Scale ◽  
Co2 Concentration ◽  
Surface Model ◽  
Model Errors ◽  
Spatial Integration ◽  
Area Index ◽  
Aircraft Observations

Abstract. This paper describes a numerical interpretation of the April 2007, CarboEurope Regional Experiment Strategy (CERES) campaign, devoted to the study of the CO2 cycle at the regional scale. Four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model, coupled to ISBA-A-gs land surface model. The main result of this paper is to show how aircraft observations of CO2 concentration have been used to identify surface model errors and to calibrate the CO2 driving component of the surface model. In fact, the comparisons between modelled and observed CO2 concentrations within the Atmospheric Boundary Layer (ABL) allow to calibrate and correct not only the parameterization of respired CO2 fluxes by the ecosystem but also the Leaf Area Index (LAI) of the dominating land cover. After this calibration, the paper describes systematic comparisons of the model outputs with numerous data collected during the CERES campaign, in April 2007. For instance, the originality of this paper is the spatial integration of the comparisons. In fact, the aircraft observations of CO2 concentration and fluxes and energy fluxes are used for the model validation from the local to the regional scale. As a conclusion, the CO2 budgeting approach from the mesoscale model shows that the winter croplands are assimilating more CO2 than the pine forest, at this stage of the year and this case study.

scholarly journals Improving the Evapotranspiration Estimation under Cloudy Condition by Extending the Ts-VI Triangle Model

2021 ◽  
Vol 13 (8) ◽  
pp. 1516
Author(s):  
Boyang Li ◽  
Yaokui Cui ◽  
Xiaozhuang Geng ◽  
Huan Li
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Energy Exchange ◽  
Vegetation Index ◽  
Regional Scale ◽  
Reconstruction Algorithm ◽  
Heihe River ◽  
Main Process ◽  
In Situ Data

Evapotranspiration (ET) of soil-vegetation system is the main process of the water and energy exchange between the atmosphere and the land surface. Spatio-temporal continuous ET is vitally important to agriculture and ecological applications. Surface temperature and vegetation index (Ts-VI) triangle ET model based on remote sensing land surface temperature (LST) is widely used to monitor the land surface ET. However, a large number of missing data caused by the presence of clouds always reduces the availability of the main parameter LST, thus making the remote sensing-based ET estimation unavailable. In this paper, a method to improve the availability of ET estimates from Ts-VI model is proposed. Firstly, continuous LST product of the time series is obtained using a reconstruction algorithm, and then, the reconstructed LST is applied to the estimate ET using the Ts-VI model. The validation in the Heihe River Basin from 2009 to 2011 showed that the availability of ET estimates is improved from 25 days per year (d/yr) to 141 d/yr. Compared with the in situ data, a very good performance of the estimated ET is found with RMSE 1.23 mm/day and R2 0.6257 at point scale and RMSE 0.32 mm/day and R2 0.8556 at regional scale. This will improve the understanding of the water and energy exchange between the atmosphere and the land surface, especially under cloudy conditions.

scholarly journals Evaluating Downscaling Factors of Microwave Satellite Soil Moisture Based on Machine Learning Method

2021 ◽  
Vol 13 (1) ◽  
pp. 133
Author(s):  
Hao Sun ◽  
Yajing Cui
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Land Surface ◽  
Regional Scale ◽  
Support Vector ◽  
Machine Learning Method ◽  
Learning Method ◽  
Feed Forward Neural Network ◽  
Comparative Performance ◽  
Geographical Factors

Downscaling microwave remotely sensed soil moisture (SM) is an effective way to obtain spatial continuous SM with fine resolution for hydrological and agricultural applications on a regional scale. Downscaling factors and functions are two basic components of SM downscaling where the former is particularly important in the era of big data. Based on machine learning method, this study evaluated Land Surface Temperature (LST), Land surface Evaporative Efficiency (LEE), and geographical factors from Moderate Resolution Imaging Spectroradiometer (MODIS) products for downscaling SMAP (Soil Moisture Active and Passive) SM products. This study spans from 2015 to the end of 2018 and locates in the central United States. Original SMAP SM and in-situ SM at sparse networks and core validation sites were used as reference. Experiment results indicated that (1) LEE presented comparative performance with LST as downscaling factors; (2) adding geographical factors can significantly improve the performance of SM downscaling; (3) integrating LST, LEE, and geographical factors got the best performance; (4) using Z-score normalization or hyperbolic-tangent normalization methods did not change the above conclusions, neither did using support vector regression nor feed forward neural network methods. This study demonstrates the possibility of LEE as an alternative of LST for downscaling SM when there is no available LST due to cloud contamination. It also provides experimental evidence for adding geographical factors in the downscaling process.

scholarly journals Optimization of the Local Split-Window Algorithm for FY-4A Land Surface Temperature Retrieval

2019 ◽  
Vol 11 (17) ◽  
pp. 2016
Author(s):  
Lijuan Wang ◽  
Ni Guo ◽  
Wei Wang ◽  
Hongchao Zuo
Keyword(s):  
Surface Temperature ◽  
Diurnal Variation ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Regional Scale ◽  
Pso Algorithm ◽  
Variation Characteristics ◽  
Split Window Algorithm ◽  
Mean Square Errors

FY-4A is a second generation of geostationary orbiting meteorological satellite, and the successful launch of FY-4A satellite provides a new opportunity to obtain diurnal variation of land surface temperature (LST). In this paper, different underlying surfaces-observed data were applied to evaluate the applicability of the local split-window algorithm for FY-4A, and the local split-window algorithm parameters were optimized by the artificial intelligent particle swarm optimization (PSO) algorithm to improve the accuracy of retrieved LST. Results show that the retrieved LST can efficiently reproduce the diurnal variation characteristics of LST. However, the estimated values deviate hugely from the observed values when the local split-window algorithms are directly used to process the FY-4A satellite data, and the root mean square errors (RMSEs) are approximately 6K. The accuracy of the retrieved LST cannot be effectively improved by merely modifying the emissivity-estimated model or optimizing the algorithm. Based on the measured emissivity, the RMSE of LST retrieved by the optimized local split-window algorithm is reduced to 3.45 K. The local split-window algorithm is a simple and easy retrieval approach that can quickly retrieve LST on a regional scale and promote the application of FY-4A satellite data in related fields.

scholarly journals Distribution of Gaseous 12CO2, 13CO2, and 14CO2 in the Sub-Soil Unsaturated Zone of the Western US Great Plains

Radiocarbon ◽  
1983 ◽  
Vol 25 (2) ◽  
pp. 315-346 ◽  
Author(s):  
D C Thorstenson ◽  
E P Weeks ◽  
Herbert Haas ◽  
D W Fisher
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Unsaturated Zone ◽  
Diffusion Theory ◽  
The United States ◽  
Atmospheric Gases ◽  
Sources And Sinks ◽  
Western Us ◽  
Partial Pressures ◽  
Western Great Plains

Data on the depth distribution of the major atmospheric gases and the abundance of gaseous 12CO2, 13CO2, and 14CO2 in the subsoil unsaturated zone have been obtained from several sites in the western Great Plains of the United States. Sample profiles range from land surface to depths of 50m. Although each site must be considered on an individual basis, several general statements can be made regarding the profiles. 1) Diffusion of these gaseous molecules through the unsaturated zone is an important transport mechanism. 2) As predicted by diffusion theory, depth profiles of the various isotopic species of CO2 differ substantially from one another, depending on individual sources and sinks such as root respiration and oxidation of organic carbon at depth. 3) In general, post-bomb (> 100% modern) 14C activities are not observed in the deep unsaturated zone, in contrast to diffusion model predictions. 4) In spite of generally decreasing 14C activities with depth, absolute partial pressures of 14CO2 in the subsoil unsaturated zone are 1–2 orders of magnitude higher than the partial pressure of 14CO2 in the atmosphere.

Climate as the great equalizer of continental-scale erosion

2021 ◽  
Author(s):  
Gilby Jepson ◽  
Barbara Carrapa ◽  
Jack Gillespie ◽  
Ran Feng ◽  
Peter DeCelles ◽  
...  
Keyword(s):  
Central Asia ◽  
Regional Scale ◽  
Continental Scale ◽  
Active Tectonic ◽  
Tectonically Active ◽  
High Precipitation ◽  
Tectonic Boundaries ◽  
Great Equalizer ◽  
Tian Shan

&lt;p&gt;Central Asia is one of the most tectonically active and orographically diverse regions in the world and is the location of the highest topography on Earth resulting from major plate tectonic collisional events. Yet the role of tectonics versus climate on erosion remains one of the greatest debates of our time. We present the first regional scale analysis of 2526 published low-temperature thermochronometric dates from Central Asia spanning the Altai-Sayan, Tian Shan, Tibet, Pamir, and Himalaya. We compare these dates to tectonic processes (proximity to tectonic boundaries, crustal thickness, seismicity) and state-of-the-art paleoclimate simulations in order to constrain the relative influences of climate and tectonics on the topographic architecture and erosion of Central Asia. Predominance of pre-Cenozoic ages in much of the interior of central Asia suggests that significant topography was created prior to the India-Eurasia collision and implies limited subsequent erosion. Increasingly young cooling ages are associated with increasing proximity to active tectonic boundaries, suggesting a first-order control of tectonics on erosion. However, areas that have been sheltered from significant precipitation for extensive periods of time retain old cooling ages. This suggests that ultimately climate is the great equalizer of erosion. Climate plays a key role by enhancing erosion in areas with developed topography and high precipitation such as the Tian Shan and Altai-Sayan during the Mesozoic and the Himalaya during the Cenozoic. Older thermochronometric dates are associated with sustained aridity following more humid periods.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document