scholarly journals Estimates of European uptake of CO<sub>2</sub> inferred from GOSAT X<sub>CO<sub>2</sub></sub> retrievals: sensitivity to measurement bias inside and outside Europe

2016 ◽  
Vol 16 (3) ◽  
pp. 1289-1302 ◽  
Author(s):  
L. Feng ◽  
P. I. Palmer ◽  
R. J. Parker ◽  
N. M. Deutscher ◽  
D. G. Feist ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Alternative Hypothesis ◽  
Co2 Flux ◽  
Total Carbon ◽  
Co2 Uptake ◽  
In Situ Data ◽  
Erroneous Estimate ◽  
Measurement Biases ◽  
Scanning Imaging

Abstract. Estimates of the natural CO2 flux over Europe inferred from in situ measurements of atmospheric CO2 mole fraction have been used previously to check top-down flux estimates inferred from space-borne dry-air CO2 column (XCO2) retrievals. Several recent studies have shown that CO2 fluxes inferred from XCO2 data from the Japanese Greenhouse gases Observing SATellite (GOSAT) and the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) have larger seasonal amplitudes and a more negative annual net CO2 balance than those inferred from the in situ data. The cause of this elevated European uptake of CO2 is still unclear, but some recent studies have suggested that this is a genuine scientific phenomenon. Here, we put forward an alternative hypothesis and show that realistic levels of bias in GOSAT data can result in an erroneous estimate of elevated uptake over Europe. We use a global flux inversion system to examine the relationship between measurement biases and estimates of CO2 uptake from Europe. We establish a reference in situ inversion that uses an Ensemble Kalman Filter (EnKF) to assimilate conventional surface mole fraction observations and XCO2 retrievals from the surface-based Total Carbon Column Observing Network (TCCON). We use the same EnKF system to assimilate two independent versions of GOSAT XCO2 data. We find that the GOSAT-inferred European terrestrial biosphere uptake peaks during the summer, similar to the reference inversion, but the net annual flux is 1.40 ± 0.19 GtC a−1 compared to a value of 0.58 ± 0.14 GtC a−1 for our control inversion that uses only in situ data. To reconcile these two estimates, we perform a series of numerical experiments that assimilate observations with added biases or assimilate synthetic observations for which part or all of the GOSAT XCO2 data are replaced with model data. We find that for our global flux inversions, a large portion (60–90 %) of the elevated European uptake inferred from GOSAT data in 2010 is due to retrievals outside the immediate European region, while the remainder can largely be explained by a sub-ppm retrieval bias over Europe. We use a data assimilation approach to estimate monthly GOSAT XCO2 biases from the joint assimilation of in situ observations and GOSAT XCO2 retrievals. The inferred biases represent an estimate of systematic differences between GOSAT XCO2 retrievals and the inversion system at regional or sub-regional scales. We find that a monthly varying bias of up to 0.5 ppm can explain an overestimate of the annual sink of up to 0.20 GtC a−1. Our results highlight the sensitivity of CO2 flux estimates to regional observation biases, which have not been fully characterized by the current observation network. Without further dedicated measurements we cannot prove or disprove that European ecosystems are taking up a larger-than-expected amount of CO2. More robust inversion systems are also needed to infer consistent fluxes from multiple observation types.

scholarly journals Elevated uptake of CO<sub>2</sub> over Europe inferred from GOSAT X<sub>CO<sub>2</sub></sub> retrievals: a real phenomenon or an artefact of the analysis?

2015 ◽  
Vol 15 (2) ◽  
pp. 1989-2011 ◽  
Author(s):  
L. Feng ◽  
P. I. Palmer ◽  
R. J. Parker ◽  
N. M. Deutscher ◽  
D. G. Feist ◽  
...  
Keyword(s):  
Co2 Flux ◽  
Total Carbon ◽  
Co2 Uptake ◽  
In Situ Data ◽  
A Value ◽  
Co2 Balance ◽  
Real Phenomenon ◽  
Retrieval Bias ◽  
Annual Flux

Abstract. Estimates of the natural CO2 flux over Europe inferred from in situ measurements of atmospheric CO2 mole fraction have been used previously to check top-down flux estimates inferred from space-borne dry-air CO2 column (XCO2) retrievals. Recent work has shown that CO2 fluxes inferred from XCO2 data from the Japanese Greenhouse gases Observing SATellite (GOSAT) have a larger seasonal amplitude and a more negative annual net CO2 balance than those inferred from the in situ data. The causes of this enhanced European CO2 uptake have since become the focus of recent studies. We show this elevated uptake over Europe could largely be explained by mis-fitting data due to regional biases. We establish a reference in situ inversion that uses an Ensemble Kalman Filter (EnKF) to assimilate surface flask data and the XCO2 data from the surface-based Total Carbon Column Observing Network (TCCON). The same EnKF system is also used to assimilate two, independent versions of GOSAT XCO2 data. We find that the GOSAT-inferred European terrestrial biosphere uptake peaks during the summer, similar to the reference inversion, but the net annual flux is 1.18 ± 0.1 GtC a−1 compared to a value of 0.56 ± 0.1 GtC a−1 for our control inversion that uses only in situ data. To reconcile these two estimates, we have performed a series of numerical experiments that assimilate observations with biases or assimilate synthetic observations for which part or all of the GOSAT XCO2 data are replaced with model data. We find that 50–80% of the elevated European uptake in 2010 inferred from GOSAT data is due to retrievals outside the immediate European region, while most of the remainder can be explained by a sub-ppm retrieval bias over Europe. We have used data assimilation techniques to estimate monthly GOSAT XCO2 biases from the joint assimilation of in situ observations and GOSAT XCO2 retrievals. We find a monthly varying bias of up to 0.5 ppm can explain an overestimate of the annual sink of up to 0.18 GtC a−1.

scholarly journals Retrieval of atmospheric CH<sub>4</sub> vertical information from TCCON FTIR spectra

2019 ◽  
Author(s):  
Minqiang Zhou ◽  
Bavo Langerock ◽  
Mahesh Kumar Sha ◽  
Nicolas Kumps ◽  
Christian Hermans ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Distinct Species ◽  
Satellite Observations ◽  
Total Carbon ◽  
Systematic Uncertainties ◽  
Time Period ◽  
Accuracy And Precision ◽  
Retrieval Software ◽  
Total Column

Abstract. TCCON (Total Carbon Column Observing Network) column-averaged dry air mole fraction of CH4 (XCH4) measurements have been widely used to validate satellite observations and to estimate model simulations. The GGG2014 code is the standard TCCON retrieval software performing a profile scaling retrieval. In order to obtain several vertical information in addition to total column, in this study, the SFIT4 retrieval code is applied to retrieve CH4 mole fraction vertical profile using TCCON spectra (SFIT4TCCON) at six sites (Ny-Ålesund, Sodankylä, Bialystok, Bremen, Orléans and St Denis) during the time period of 2016−2017. The retrieval strategy of SFIT4TCCON is investigated. The degree of freedom for signal of the SFIT4TCCON retrieval is about 2.4, with two distinct species of information in the troposphere and in the stratosphere. The averaging kernel and error budget of the SFIT4TCCON retrieval are presented. The data accuracy and precision of the SFIT4TCCON retrievals, including the total column and two partial columns (in the troposphere and stratosphere), are estimated by TCCON standard retrievals, ground-based in situ measurements, ACE-FTS satellite observations, TCCON proxy data and AirCore measurements. By comparison against TCCON standard retrievals, it is found that the retrieval uncertainty of SFIT4TCCON XCH4 is similar to that of TCCON standard retrievals with the systematic uncertainty within 0.35 % and the random uncertainty about 0.5 %. The tropospheric and stratospheric XCH4 from SFIT4TCCON retrievals are assessed by comparing with AirCore measurements at Sodankylä, and there is a 1.2 % overestimation in the SFIT4TCCON tropospheric XCH4 and a 4.0 % underestimation in the SFIT4TCCON stratospheric XCH4, which are within the systematic uncertainties of SFIT4TCCON retrieved partial columns in the troposphere and stratosphere, respectively.

scholarly journals Four years of global carbon cycle observed from OCO-2 version 9 and in situ data, and comparison to OCO-2 v7

2021 ◽  
Author(s):  
Hélène Peiro ◽  
Sean Crowell ◽  
Andrew Schuh ◽  
David F. Baker ◽  
Chris O'Dell ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Total Carbon ◽  
Tropical Africa ◽  
Times Series ◽  
In Situ Data ◽  
The Times ◽  
Carbon Dioxide Co2 ◽  
The Tropics ◽  
The Impact

Abstract. The Orbiting Carbon Observatory 2 (OCO-2) satellite has been provided information to estimate carbon dioxide (CO2) fluxes at global and regional scales since 2014 through the combination of CO2 retrievals with top-down atmospheric inversion methods. Column average CO2 dry air mole fraction retrievals has been constantly improved. A bias correction has been applied in the OCO-2 version 9 retrievals compared to the previous OCO-2 version 7r improving data accuracy and coverage. We study an ensemble of ten atmospheric inversions all characterized by different transport models, data assimilation algorithm and prior fluxes using first OCO-2 v7 in 2015-2016 and then OCO-2 version 9 land observations for the longer period 2015- 2018. Inversions assimilating in situ (IS) measurements have been also used to provide a baseline against which to compare the satellite-driven results. The times series at different scales (going from global to regional scales) of the models emissions are analyzed and compared to each experiments using either OCO-2 or IS data. We then evaluate the inversion ensemble based on dataset from TCCON, aircraft, and in-situ observations, all independent from assimilated data. While we find a similar constraint of global total carbon emissions between the ensemble spread using IS and both OCO-2 retrievals, differences between the two retrieval versions appear over regional scales and particularly in tropical Africa. A difference in the carbon budget between v7 and v9 is found over this region which seems to show the impact of corrections applied in retrievals. However, the lack of data in the tropics limits our conclusions and the estimation of carbon emissions over tropical Africa require further analysis.

scholarly journals The role of phytoplankton dynamics in the seasonal and interannual variability of carbon in the subpolar North Atlantic – a modeling study

2012 ◽  
Vol 5 (3) ◽  
pp. 683-707 ◽  
Author(s):  
S. R. Signorini ◽  
S. Häkkinen ◽  
K. Gudmundsson ◽  
A. Olsen ◽  
A. M. Omar ◽  
...  
Keyword(s):  
Functional Groups ◽  
Mixed Layer Depth ◽  
Co2 Flux ◽  
Early Spring ◽  
Biogeochemical Model ◽  
Co2 Uptake ◽  
Biological Interactions ◽  
In Situ Data ◽  
Phytoplankton Functional Groups ◽  
The Impact

Abstract. We developed an ecosystem/biogeochemical model system, which includes multiple phytoplankton functional groups and carbon cycle dynamics, and applied it to investigate physical-biological interactions in Icelandic waters. Satellite and in situ data were used to evaluate the model. Surface seasonal cycle amplitudes and biases of key parameters (DIC, TA, pCO2, air-sea CO2 flux, and nutrients) are significantly improved when compared to surface observations by prescribing deep water values and trends, based on available data. The seasonality of the coccolithophore and "other phytoplankton" (diatoms and dinoflagellates) blooms is in general agreement with satellite ocean color products. Nutrient supply, biomass and calcite concentrations are modulated by light and mixed layer depth seasonal cycles. Diatoms are the most abundant phytoplankton, with a large bloom in early spring and a secondary bloom in fall. The diatom bloom is followed by blooms of dinoflagellates and coccolithophores. The effect of biological changes on the seasonal variability of the surface ocean pCO2 is nearly twice the temperature effect, in agreement with previous studies. The inclusion of multiple phytoplankton functional groups in the model played a major role in the accurate representation of CO2 uptake by biology. For instance, at the peak of the bloom, the exclusion of coccolithophores causes an increase in alkalinity of up to 4 μmol kg−1 with a corresponding increase in DIC of up to 16 μmol kg−1. During the peak of the bloom in summer, the net effect of the absence of the coccolithophores bloom is an increase in pCO2 of more than 20 μatm and a reduction of atmospheric CO2 uptake of more than 6 mmol m−2 d−1. On average, the impact of coccolithophores is an increase of air-sea CO2 flux of about 27%. Considering the areal extent of the bloom from satellite images within the Irminger and Icelandic Basins, this reduction translates into an annual mean of nearly 1500 tonnes C yr−1.

Was Australia a sink or source of carbon dioxide in 2015? Data assimilation using OCO-2 satellite data

2020 ◽  
Author(s):  
Yohanna Villalobos ◽  
Peter Rayner ◽  
Steven Thomas ◽  
Jeremy Silver
Keyword(s):  
Satellite Data ◽  
Transport Model ◽  
Carbon Sink ◽  
In Situ Measurements ◽  
Surface Fluxes ◽  
Total Carbon ◽  
Cereal Crops ◽  
Continental Scale ◽  
In Situ Data

&lt;p&gt;Estimates of the net CO&lt;sub&gt;2&lt;/sub&gt; flux at a continental scale are essential to building up confidence in the global carbon budget. In this study, we present the assimilation of the satellite data from the Orbiting Carbon Observatory-2 (OCO-2) (land nadir and glint data) to estimate the Australian CO&lt;sub&gt;2&lt;/sub&gt; surface fluxes for 2015. We used the Community Multiscale Air Quality (CMAQ) model and a four-dimensional variational scheme. Our preliminary results suggest that Australia was a slight carbon sink during 2015 of -0.15 +- 0.11 PgC y&lt;sup&gt;-1&lt;/sup&gt; compared to the prior estimate of 0.13 +- 0.55 PgC y&lt;sup&gt;-1&lt;/sup&gt;. The monthly seasonal cycle shows there was not a good agreement between the prior and posterior fluxes in 2015. Our monthly posterior estimates suggest that from May to August, Australia was a sink of CO&lt;sub&gt;2&lt;/sub&gt; and that from October to December, it was a source of CO&lt;sub&gt;2&lt;/sub&gt; compared to the prior estimates, which showed an opposite sign. To understand these results more deeply, we aggregated the CO&lt;sub&gt;2&lt;/sub&gt; surface fluxes into six categories using Land Cover Type Product the Moderate Resolution Imaging Spectroradiometer (MODIS) and divided them into two areas (north and south). Our posterior fluxes aggregated in the southern and northern Australia indicates that most of the uptake of CO&lt;sub&gt;2&lt;/sub&gt; is driven by grasses and cereal crops. Grasses and cereal crops in these two regions represent -0.11 +- 0.027 and -0.06 +- 0.05 PgC/y respectively. In the southern region, the monthly time series of this category shows that this uptake occurs mainly from June to September, whereas in the north, it occurs from January to March. We evaluate our posterior CO&lt;sub&gt;2&lt;/sub&gt; concentration against The Total Carbon Column Observing Network (TCCON) and in-situ measurements.&amp;#160; We use the TCCON stations from Darwin, Wollongong, and Lauder (in New Zealand). Amongst the in-situ measurements, we considered stations located at Gunn Point (near Darwin), Cape Grim (in Tasmania) and Iron Bark and Burncluith (in Queensland). Analysis of the monthly biases indicates that CO&lt;sub&gt;2&lt;/sub&gt; concentration simulated by posterior fluxes are in better agreement with TCCON data compared to in-situ measurements. In general, monthly mean biases in TCCON Darwin are improved by almost 70 per cent. Lauder and Wollongong stations are strongly affected by ocean fluxes which have small prior uncertainty in this inversion. Biases are hence not much improved here. We verify this by relating bias to wind direction. If the winds come from the ocean, fluxes over Australia are less constrained by OCO-2 data. Biases against in situ data are generally not improved by assimilation, suggesting either problems with the transport model or an inability for OCO-2 data to constrain fluxes at scales relevant to these measurements.&lt;/p&gt;

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

2017 ◽  
Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  
Keyword(s):  
Satellite Data ◽  
Wind Wave ◽  
Arctic Region ◽  
Web Gis ◽  
The Arctic ◽  
Flexible Tool ◽  
In Situ Data ◽  
Current State ◽  
Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

scholarly journals CO<sub>2</sub> flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

2007 ◽  
Vol 4 (6) ◽  
pp. 1005-1025 ◽  
Author(s):  
L. Kutzbach ◽  
J. Schneider ◽  
T. Sachs ◽  
M. Giebels ◽  
H. Nykänen ◽  
...  
Keyword(s):  
Linear Regression ◽  
Nonlinear Regression ◽  
Co2 Flux ◽  
Exponential Model ◽  
Co2 Uptake ◽  
Co2 Fluxes ◽  
Closed Chamber ◽  
Exponential Regression ◽  
Closure Time ◽  
Over Time

Abstract. Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

scholarly journals CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals

2021 ◽  
Vol 13 (15) ◽  
pp. 2996
Author(s):  
Qinwei Zhang ◽  
Mingqi Li ◽  
Maohua Wang ◽  
Arthur Paul Mizzi ◽  
Yongjian Huang ◽  
...  
Keyword(s):  
United States ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Co2 Flux ◽  
Total Carbon ◽  
Mean Bias Error ◽  
Bias Error ◽  
Parallel Experiment ◽  
Concentration Measurements ◽  
Global Stocktake

High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr−1) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr−1, standard deviation: 0.29 Pg C yr−1, 9 models in total) and CT2017 (1.19 Pg C yr−1). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m−2 d−1, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.

scholarly journals Critical Dynamics of Defects and Mechanisms of Damage-Failure Transitions in Fatigue

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2554
Author(s):  
Oleg Naimark ◽  
Vladimir Oborin ◽  
Mikhail Bannikov ◽  
Dmitry Ledon
Keyword(s):  
Fatigue Damage ◽  
Kinetic Equations ◽  
Experimental Methodology ◽  
Preliminary Deformation ◽  
Scaling Properties ◽  
In Situ Data ◽  
Number Of Cycles ◽  
Fish Eye ◽  
Very High

An experimental methodology was developed for estimating a very high cycle fatigue (VHCF) life of the aluminum alloy AMG-6 subjected to preliminary deformation. The analysis of fatigue damage staging is based on the measurement of elastic modulus decrement according to “in situ” data of nonlinear dynamics of free-end specimen vibrations at the VHCF test. The correlation of fatigue damage staging and fracture surface morphology was studied to establish the scaling properties and kinetic equations for damage localization, “fish-eye” nucleation, and transition to the Paris crack kinetics. These equations, based on empirical parameters related to the structure of the material, allows us to estimate the number of cycles for the nucleation and advance of fatigue crack.

scholarly journals Measuring and inferring the ice thickness distribution of four glaciers in the Tien Shan, Kyrgyzstan

2020 ◽  
pp. 1-18
Author(s):  
Lander Van Tricht ◽  
Philippe Huybrechts ◽  
Jonas Van Breedam ◽  
Johannes J. Fürst ◽  
Oleg Rybak ◽  
...  
Keyword(s):  
Cross Validation ◽  
Thickness Distribution ◽  
Tien Shan ◽  
Ice Thickness ◽  
Ice Volume ◽  
In Situ Data ◽  
Radio Echo Sounding ◽  
Thickness Measurements ◽  
Tien Shan Mountains

Abstract Glaciers in the Tien Shan mountains contribute considerably to the fresh water used for irrigation, households and energy supply in the dry lowland areas of Kyrgyzstan and its neighbouring countries. To date, reconstructions of the current ice volume and ice thickness distribution remain scarce, and accurate data are largely lacking at the local scale. Here, we present a detailed ice thickness distribution of Ashu-Tor, Bordu, Golubin and Kara-Batkak glaciers derived from radio-echo sounding measurements and modelling. All the ice thickness measurements are used to calibrate three individual models to estimate the ice thickness in inaccessible areas. A cross-validation between modelled and measured ice thickness for a subset of the data is performed to attribute a weight to every model and to assemble a final composite ice thickness distribution for every glacier. Results reveal the thickest ice on Ashu-Tor glacier with values up to 201 ± 12 m. The ice thickness measurements and distributions are also compared with estimates composed without the use of in situ data. These estimates approach the total ice volume well, but local ice thicknesses vary substantially.

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