The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record from the ESA Climate Change Initiative

Abstract. We present the new GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record which has been created within the framework of the European Space Agency's Climate Change Initiative (ESA-CCI). Total ozone column observations – based on the GOME-type Direct Fitting version 3 algorithm – from GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY), and GOME-2 have been combined into one homogeneous time series, thereby taking advantage of the high inter-sensor consistency. The data record spans the 15-year period from March 1996 to June 2011 and it contains global monthly mean total ozone columns on a 1° × 1° grid. Geophysical ground-based validation using Brewer, Dobson, and UV-visible instruments has shown that the GTO-ECV level 3 data record is of the same high quality as the equivalent individual level 2 data products that constitute it. Both absolute agreement and long-term stability are excellent with respect to the ground-based data, for almost all latitudes apart from a few outliers which are mostly due to sampling differences between the level 2 and level 3 data. We conclude that the GTO-ECV data record is valuable for a variety of climate applications such as the long-term monitoring of the past evolution of the ozone layer, trend analysis and the evaluation of Chemistry–Climate Model simulations.

Download Full-text

The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record from the ESA Climate Change Initiative

Atmospheric Measurement Techniques ◽

10.5194/amt-8-3923-2015 ◽

2015 ◽

Vol 8 (9) ◽

pp. 3923-3940 ◽

Cited By ~ 17

Author(s):

M. Coldewey-Egbers ◽

D. G. Loyola ◽

M. Koukouli ◽

D. Balis ◽

J.-C. Lambert ◽

...

Keyword(s):

Climate Change ◽

Total Ozone ◽

Climate Model ◽

Change Initiative ◽

Climate Variable ◽

Individual Level ◽

Data Record ◽

Level 3 ◽

Level 2

Abstract. We present the new GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record which has been created within the framework of the European Space Agency's Climate Change Initiative (ESA-CCI). Total ozone column observations – based on the GOME-type Direct Fitting version 3 algorithm – from GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY), and GOME-2 have been combined into one homogeneous time series, thereby taking advantage of the high inter-sensor consistency. The data record spans the 15-year period from March 1996 to June 2011 and it contains global monthly mean total ozone columns on a 1°× 1° grid. Geophysical ground-based validation using Brewer, Dobson, and UV–visible instruments has shown that the GTO-ECV level 3 data record is of the same high quality as the equivalent individual level 2 data products that constitute it. Both absolute agreement and long-term stability are excellent with respect to the ground-based data, for almost all latitudes apart from a few outliers which are mostly due to sampling differences between the level 2 and level 3 data. We conclude that the GTO-ECV data record is valuable for a variety of climate applications such as the long-term monitoring of the past evolution of the ozone layer, trend analysis and the evaluation of chemistry–climate model simulations.

Download Full-text

Quality assessment of the Ozone_cci Climate Research Data Package (release 2017) – Part 1: Ground-based validation of total ozone column data products

Atmospheric Measurement Techniques ◽

10.5194/amt-11-1385-2018 ◽

2018 ◽

Vol 11 (3) ◽

pp. 1385-1402 ◽

Cited By ~ 12

Author(s):

Katerina Garane ◽

Christophe Lerot ◽

Melanie Coldewey-Egbers ◽

Tijl Verhoelst ◽

Maria Elissavet Koukouli ◽

...

Keyword(s):

Total Ozone ◽

Data Sets ◽

Short Term ◽

Climate Research ◽

Data Record ◽

Level 3 ◽

Mean Differences ◽

Ozone Column ◽

Level 2

Abstract. The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a level-3 data record, which combines individual sensor products into one single cohesive record covering the 22-year period from 1995 to 2016, generated in the frame of the European Space Agency's Climate Change Initiative Phase II. It is based on level-2 total ozone data produced by the GODFIT (GOME-type Direct FITting) v4 algorithm as applied to the GOME/ERS-2, OMI/Aura, SCIAMACHY/Envisat and GOME-2/Metop-A and Metop-B observations. In this paper we examine whether GTO-ECV meets the specific requirements set by the international climate–chemistry modelling community for decadal stability long-term and short-term accuracy. In the following, we present the validation of the 2017 release of the Climate Research Data Package Total Ozone Column (CRDP TOC) at both level 2 and level 3. The inter-sensor consistency of the individual level-2 data sets has mean differences generally within 0.5 % at moderate latitudes (±50°), whereas the level-3 data sets show mean differences with respect to the OMI reference data record that span between −0.2 ± 0.9 % (for GOME-2B) and 1.0 ± 1.4 % (for SCIAMACHY). Very similar findings are reported for the level-2 validation against independent ground-based TOC observations reported by Brewer, Dobson and SAOZ instruments: the mean bias between GODFIT v4 satellite TOC and the ground instrument is well within 1.0 ± 1.0 % for all sensors, the drift per decade spans between −0.5 % and 1.0 ± 1.0 % depending on the sensor, and the peak-to-peak seasonality of the differences ranges from ∼ 1 % for GOME and OMI to ∼ 2 % for SCIAMACHY. For the level-3 validation, our first goal was to show that the level-3 CRDP produces findings consistent with the level-2 individual sensor comparisons. We show a very good agreement with 0.5 to 2 % peak-to-peak amplitude for the monthly mean difference time series and a negligible drift per decade of the differences in the Northern Hemisphere of −0.11 ± 0.10 % decade−1 for Dobson and +0.22 ± 0.08 % decade−1 for Brewer collocations. The exceptional quality of the level-3 GTO-ECV v3 TOC record temporal stability satisfies well the requirements for the total ozone measurement decadal stability of 1–3 % and the short-term and long-term accuracy requirements of 2 and 3 %, respectively, showing a remarkable inter-sensor consistency, both in the level-2 GODFIT v4 and in the level-3 GTO-ECV v3 datasets, and thus can be used for longer-term analysis of the ozone layer, such as decadal trend studies, chemistry–climate model evaluation and data assimilation applications.

Download Full-text

Quality assessment of the Ozone_cci Climate Research Data Package (release 2017): 1. Ground-based validation of total ozone column data products

10.5194/amt-2017-378 ◽

2017 ◽

Cited By ~ 2

Author(s):

Katerina Garane ◽

Christophe Lerot ◽

Melanie Coldewey-Egbers ◽

Tijl Verhoelst ◽

Irene Zyrichidou ◽

...

Keyword(s):

Total Ozone ◽

Data Sets ◽

Short Term ◽

Climate Research ◽

Data Record ◽

Level 3 ◽

Mean Differences ◽

Ozone Column ◽

Level 2

Abstract. The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a Level-3 data record, which combines individual sensor products into one single cohesive record covering the 22 year period from 1995 to 2017, generated in the frame of the European Space Agency's Climate Change Initiative Phase-II. It is based on Level-2 total ozone data produced by the GODFIT v4 algorithm as applied to the GOME/ERS-2, OMI/Aura, SCIAMACHY/Envisat and GOME-2/MetopA and /MetopB observations. In this paper we examine whether GTO-ECV meets the specific requirements set by the international climate-chemistry modelling community for decadal stability, long-term and short term accuracy. In the following, we present the validation of the 2017 release of the Climate Research Data Package Total Ozone Column (CRDP TOC), both at Level-2 and Level-3. The individual Level-2 data sets show excellent inter-sensor consistency with mean differences generally within 0.5 % at moderate latitudes (±50°), whereas the Level-3 data sets show mean differences with respect to the OMI reference data record that span between −0.2 ± 0.9 % (for GOME-2B) and 1.0 ± 1.4&htinsp;% (for SCIAMACHY). Very similar findings are reported for the Level-2 validation against independent ground-based TOC observations reported by Brewer, Dobson and SAOZ instruments; the mean bias between GODFIT v4 satellite TOC and ground instrument is well within 1.0 ± 1.0 % for all sensors, the drift per decade spans between −0.5 % to 1.0 ± 1.0 % depending on the sensor, and the peak-to-peak seasonality of the differences ranges between ~ 1 % for GOME and OMI, to ~ 2 % for SCIAMACHY. For the Level-3 validation, as a first step the aim was to show that the Level-3 CRDP produces consistent findings as the Level-2 individual sensor comparisons. We show an excellent agreement with 0.5 to 2 % peak-to-peak amplitude for the monthly mean difference time series and a negligible drift per decade in the Northern Hemisphere differences at −0.11 ± 0.10 % per decade for Dobson and +0.22 ± 0.08 % per decade for Brewer collocations. The exceptional quality of the Level-3 GTO-ECV v3 TOC record temporal stability well satisfies the requirements for the total ozone measurement decadal stability of between 1–3 % and the short term and long-term accuracy requirements of 2 % and 3 % respectively, showing an excellent inter-sensor consistency both in the Level-2 GODFIT v4 as well as in the Level-3 GTO-ECV v3 datasets and thus can be used for longer term analysis of the ozone layer, such as decadal trend studies, chemistry-climate model evaluation and data assimilation applications.

Download Full-text

Development of a microwave-based precipitation climate data record for the Copernicus Climate Change Service

10.5194/egusphere-egu2020-18636 ◽

2020 ◽

Author(s):

Giulia Panegrossi ◽

Paolo Sanò ◽

Leonardo Bagaglini ◽

Daniele Casella ◽

Elsa Cattani ◽

...

Keyword(s):

Neural Network ◽

Climate Change ◽

Satellite Observations ◽

Passive Microwave ◽

Monthly Precipitation ◽

Climate Data ◽

Data Record ◽

Level 3 ◽

Climate Data Record ◽

Level 2

Within the Copernicus Climate Change Service (C3S), the Climate Data Store (CDS) built by ECMWF will provide open and free access to global and regional products of Essential Climate Variables (ECV) based on satellite observations spanning several decades, amongst other things. Given its significance in the Earth system and particularly for human life, the ECV precipitation will be of major interest for users of the CDS.C3S strives to include as many established, high-quality data sets as possible in the CDS. However, it also intends to offer new products dedicated for first-hand publication in the CDS. One of these products is a climate data record based on merging satellite observations of daily and monthly precipitation by both passive microwave (MW) sounders (AMSU-B/MHS) and imagers (SSMI/SSMIS) on a 1&#176;x1&#176; spatial grid in order to improve spatiotemporal satellite coverage of the globe.The MW sounder observations will be obtained using, as input data, the FIDUCEO Fundamental Climate data Record (FCDR) for AMSU-B/MHS in a new global algorithm developed specifically for the project based on the Passive microwave Neural network Precipitation Retrieval approach (PNPR; San&#242; et al., 2015), adapted for climate applications (PNPR-CLIM). The algorithm consists of two Artificial Neural Network-based modules, one for precipitation detection, and one for precipitation rate estimate, trained on a global observational database built from Global Precipitation Measurement-Core Observatory (GPM-CO) measurements. The MW imager observations by SSM/I and SSMIS will be adopted from the Hamburg Ocean Atmosphere Fluxes and Parameters from Satellite data (HOAPS; Andersson et al., 2017), based on the CM SAF SSM/I and SSMIS FCDR (Fennig et al., 2017). The Level 2 precipitation rate estimates from MW sounders and imagers are combined through a newly developed merging module to obtain Level 3 daily and monthly precipitation and generate the 18-year precipitation CDR (2000-2017).Here, we present the status of the Level 2 product&#8217;s development. We carry out a Level-2 comparison and present first results of the merged Level-3 precipitation fields. Based on this, we assess the product&#8217;s expected plausibility, coverage, and the added value of merging the MW sounder and imager observations.ReferencesAnderssonet al., 2017, DOI:10.5676/EUM_SAF_CM/HOAPS/V002Fennig, et al., 2017, DOI:10.5676/EUM_SAF_CM/FCDR_MWI/V003San&#242;, P., et al., 2015, DOI: 10.5194/amt-8-837-2015

Download Full-text

ESA CCI and C3S Soil Moisture: latest product updates and climate assessments

10.5194/egusphere-egu2020-19198 ◽

2020 ◽

Author(s):

Wouter Dorigo ◽

Wolfgang Preimesberger ◽

Adam Pasik ◽

Alexander Gruber ◽

Leander Moesinger ◽

...

Keyword(s):

Climate Change ◽

Soil Moisture ◽

European Space Agency ◽

Climate Data ◽

Change Initiative ◽

Space Agency ◽

Data Store ◽

Climate Data Record ◽

Level 2

As part of the European Space Agency (ESA) Climate Change Initiative (CCI) a more than 40 year long climate data record (CDR) is produced by systematically combining Level-2 datasets from separate missions. Combining multiple level 2 datasets into a single consistent long-term product combines the advantages of individual missions and allows deriving a harmonised long-term record with optimal spatial and temporal coverage. The current version of ESA CCI Soil Moisture includes a PASSIVE (radiometer-based) dataset covering the period 1978 to 2019, an ACTIVE (scatterometer-based) product covering the period 1991-2019 and a COMBINED product (1978-2019).&#160;The European Commission&#8217;s Copernicus Climate Changes Service (C3S) uses the ESA CCI soil moisture algorithm to produce similar climate data records from near-real-time Level-2 data streams.&#160; These products are continuously extended within 10 days after data acquisition and instantaneously made available through the C3S Climate Data Store. In addition to a daily product, monthly aggregates as well as a dekadal (10-days) products are produced.In this presentation we give an overview of the latest developments of the ESA CCI and C3S Soil Moisture datasets, which include the integration of SMAP and various algorithmic updates, and use the datasets to assess the hydrological conditions of 2019 with respect to a 30-year historical baseline.The development of the ESA CCI products has been supported by ESA&#8217;s Climate Change Initiative for Soil Moisture (Contract No. 4000104814/11/I-NB and 4000112226/14/I-NB). The Copernicus Climate Change Service (C3S) soil moisture product is funded by the Copernicus Climate Change Service implemented by ECMWF through C3S 312b Lot 7 Soil Moisture service.

Download Full-text

A study of long-term climate change in a simple seasonal nonlinear climate model

Climate Dynamics ◽

10.1007/bf00210580 ◽

1991 ◽

Vol 6 (1) ◽

pp. 35-41 ◽

Cited By ~ 2

Author(s):

R Q Lin ◽

H Kreiss ◽

W J Kuang ◽

L Y Leung

Keyword(s):

Climate Change ◽

Climate Model

Download Full-text

Forestry of Serbia - achievement of Millenium Goals in the era of climate change and globalization

Glasnik Sumarskog fakulteta ◽

10.2298/gsf14s1089o ◽

2014 ◽

pp. 89-112 ◽

Cited By ~ 1

Author(s):

Sasa Orlovic ◽

Milan Drekic ◽

Bratislav Matovic ◽

Leopold Poljakovic-Pajnik ◽

Mirjana Stevanov ◽

...

Keyword(s):

Social Sciences ◽

Climate Change ◽

Forest Ecosystems ◽

European Beech ◽

Novi Sad ◽

Experimental Trials ◽

Level 2 ◽

Term Monitoring ◽

Forest Institutions

This paper is a review presenting research results on the forest ecosystems of Serbia that are carried out at the Institute of Lowland Forestry and Environment (University of Novi Sad, Serbia) in the context of climate change and globalisation. The review displays results of the long-term monitoring of the forest ecosystems, where the data were obtained at the permanent experimental trials of IPC-Forests (level 2) and the iLTER's network. All findings are systematically divided according to the research disciplines and the most important tree species (poplar, willow, oak, wild cherry and European beech). Also the aspects of social sciences are included (meaning evaluating forest institutions in the first place). This review is meant to contribute inputs to the ongoing discussion about the achievement of the Millenium Goals of Sustainable Development in the context of Serbian forestry.

Download Full-text

Estimation of Water Storage Changes in Small Endorheic Lakes in Northern Kazakhstan; The Effect of Climate Change and Anthropogenic Influences

10.20944/preprints201712.0045.v1 ◽

2017 ◽

Author(s):

Vadim Yapiyev ◽

Kanat Samarkhanov ◽

Dauren Zhumabayev ◽

Nazym Tulegenova ◽

Saltanat Jumassultanova ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Water Resources ◽

Water Balance ◽

Climate Model ◽

Human Impacts ◽

Water Storage ◽

Minor Importance ◽

Climatic Data

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

Download Full-text

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Geoscientific Model Development ◽

10.5194/gmd-9-3461-2016 ◽

2016 ◽

Vol 9 (9) ◽

pp. 3461-3482 ◽

Cited By ~ 251

Author(s):

Brian C. O'Neill ◽

Claudia Tebaldi ◽

Detlef P. van Vuuren ◽

Veronika Eyring ◽

Pierre Friedlingstein ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

21St Century ◽

Integrated Assessment ◽

Climate Model ◽

Model Intercomparison ◽

Wide Range ◽

Scenario Model ◽

Intercomparison Project

Abstract. Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.

Download Full-text

Long-Term Variations in the Pixel-to-Pixel Variability of NOAA AVHRR SST Fields from 1982 to 2015

Remote Sensing ◽

10.3390/rs11070844 ◽

2019 ◽

Vol 11 (7) ◽

pp. 844 ◽

Cited By ~ 1

Author(s):

Fan Wu ◽

Peter Cornillon ◽

Lei Guan ◽

Katherine Kilpatrick

Keyword(s):

Quality Data ◽

Retrieval Algorithm ◽

Ocean Fronts ◽

Noaa Avhrr ◽

Data Record ◽

Along Track ◽

Level 2 ◽

Very High ◽

Significant Effort

Sea surface temperature (SST) fields obtained from the series of space-borne five-channel Advanced Very High Resolution Radiometers (AVHRRs) provide the longest continuous time series of global SST available to date (1981–present). As a result, these data have been used for many studies and significant effort has been devoted to their careful calibration in an effort to provide a climate quality data record. However, little attention has been given to the local precision of the SST retrievals obtained from these instruments, which we refer to as the pixel-to-pixel (p2p) variability, a characteristic important in the ability to resolve structures such as ocean fronts characterized by small gradients in the SST field. In this study, the p2p variability is estimated for Level-2 SST fields obtained with the Pathfinder retrieval algorithm for AVHRRs on NOAA-07, 9, 11, 12 and 14-19. These estimates are stratified by year, season, day/night and along-scan/along-track. The overall variability ranges from 0.10 K to 0.21 K. For each satellite, the along-scan variability is between 10 and 20% smaller than the along-track variability (except for NOAA-16 nighttime for which it is approximately 30% smaller) and the summer and fall σ s are between 10 and 15% smaller than the winter and spring σ s. The differences between along-track and along-scan are attributed to the way in which the instrument has been calibrated. The seasonal differences result from the T 4 − T 5 term in the Pathfinder retrieval algorithm. This term is shown to be a major contributor to the p2p variability and it is shown that its impact could be substantially reduced without a deleterious effect on the overall p2p σ of the resulting products by spatially averaging it as part of the retrieval process. The AVHRR/3s (NOAA-15 through 19) were found to be relatively stable with trends in the p2p variability of at most 0.015 K/decade.

Download Full-text