scholarly journals A global climatology of total columnar water vapour from SSM/I and MERIS

2014 ◽  
Vol 6 (1) ◽  
pp. 221-233 ◽  
Author(s):  
R. Lindstrot ◽  
M. Stengel ◽  
M. Schröder ◽  
J. Fischer ◽  
R. Preusker ◽  
...  
Keyword(s):  
Water Vapour ◽  
Near Infrared ◽  
Radiosonde Data ◽  
Microwave Range ◽  
Data Set ◽  
Uncertainty Estimates ◽  
Merging Process ◽  
Global Coverage ◽  
Land Surfaces ◽  
The Individual

Abstract. A global time series of total columnar water vapour from combined data of the Medium Resolution Imaging Spectrometer (MERIS) onboard ESA's Environmental Satellite (ENVISAT) and the Special Sensor Microwave/Imager (SSM/I) onboard the satellite series of the US Defense Meteorological Satellite Program (DMSP) is presented. The unique data set, generated in the framework of the ESA Data User Element (DUE) GlobVapour project, combines atmospheric water vapour observations over land and ocean, derived from measurements in the near-infrared and the microwave range, respectively. Daily composites and monthly means of total columnar water vapour are available as global maps on rectangular latitude–longitude grids with a spatial resolution of 0.05° × 0.05° over land and 0.5° × 0.5° over ocean for the years 2003 to 2008. The data are stored in NetCDF files and is fully compliant with the NetCDF Climate Forecast convention. Through the combination of high-quality microwave observations and near-infrared observations over ocean and land surfaces, respectively, the data set provides global coverage. The combination of both products is carried out such that the individual properties of the microwave and near-infrared products, in particular their uncertainties, are not modified by the merging process and are therefore well defined. Due to the global coverage and the provided uncertainty estimates this data set is potentially of high value for climate research. The SSM/I-MERIS TCWV data set is freely available via the GlobVapour project web page (www.globvapour.info) with associated doi:10.5676/DFE/WV_COMB/FP. In this paper, the details of the data set generation, i.e. the satellite data used, the retrieval techniques and merging approaches, are presented. The derived level 3 products are compared to global radiosonde data from the GCOS upper air network (GUAN), showing a high agreement with a root-mean-square deviation of roughly 4.4 kg m−2 and a small wet bias well below 1 kg m−2. Furthermore, the data set is shown to be free of seasonal biases. The consistency of the MERIS and SSM/I retrievals is demonstrated by applying the MERIS retrieval to sun glint areas over ocean.

scholarly journals A global climatology of total columnar water vapour from SSM/I and MERIS

2014 ◽  
Vol 7 (1) ◽  
pp. 59-88 ◽  
Author(s):  
R. Lindstrot ◽  
M. Stengel ◽  
M. Schröder ◽  
J. Fischer ◽  
R. Preusker ◽  
...  
Keyword(s):  
Water Vapour ◽  
Near Infrared ◽  
Radiosonde Data ◽  
Microwave Range ◽  
Data Set ◽  
Uncertainty Estimates ◽  
Global Coverage ◽  
Microwave Imager ◽  
Land Surfaces ◽  
The Individual

Abstract. A global time series of total columnar water vapour from combined data of the Medium Resolution Imaging Spectrometer (MERIS) onboard ESA's Environmental Satellite (ENVISAT) and the Special Sensor Microwave/Imager (SSM/I) onboard the satellite series of the US Defense Meteorological Satellite Program (DMSP) is presented. The unique dataset, generated in the framework of the ESA Data User Element (DUE) GlobVapour project, combines atmospheric water vapour observations over land and ocean, derived from measurements in the near infrared and the microwave range, respectively. Daily composites and monthly means of total columnar water vapour are available as global maps on rectangular latitude-longitude grids with a spatial resolution of 0.05° × 0.05° over land and 0.5° × 0.5° over ocean for the years 2003 to 2008. The data is stored in NetCDF files and is fully compliant with the NetCDF Climate Forecast convention. Through the combination of high quality microwave observations and near infrared observations over ocean and land surfaces, respectively, the dataset provides global coverage. The combination of both products is carried out such that the individual properties of the microwave and near-infrared products, in particular their uncertainties, are not changed and therefore well defined. Due to the global coverage and the provided uncertainty estimates this data set is potentially of high value for climate research. The SSM/I-MERIS TCWV data set is freely available via the GlobVapour project web page with associated doi (doi:10.5676/DFE/WV_COMB/FP). In this paper, the details of the dataset generation, i.e. the satellite data used, the retrieval techniques and merging approaches are presented. The derived level 3 products are compared to global radiosonde data from the GCOS upper air network (GUAN), showing a high agreement with a root mean square deviation of roughly 4.4 kg m−2 and a small wet bias well below 1 kg m−2. Furthermore, the data set is shown to be free of seasonal biases. The consistency of the MERIS and SSM/I retrievals is demonstrated by applying the MERIS retrieval to sun glint areas over ocean.

scholarly journals Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces

2021 ◽  
Vol 13 (5) ◽  
pp. 932
Author(s):  
René Preusker ◽  
Cintia Carbajal Henken ◽  
Jürgen Fischer
Keyword(s):  
Water Vapour ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Data Set ◽  
Uncertainty Estimates ◽  
Resolution Imaging ◽  
Retrieval Errors ◽  
Mean Square Errors ◽  
Total Column

A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m2 and root mean square errors (RMSE) between 1.35 and 3.26 kg/m2. This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m2 and 2.08 and 3.70 kg/m2, respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors.

scholarly journals HadISDH land surface multi-variable humidity and temperature record for climate monitoring

2014 ◽  
Vol 10 (6) ◽  
pp. 1983-2006 ◽  
Author(s):  
K. M. Willett ◽  
R. J. H. Dunn ◽  
P. W. Thorne ◽  
S. Bell ◽  
M. de Podesta ◽  
...  
Keyword(s):  
Water Vapour ◽  
Land Surface ◽  
Dew Point ◽  
Specific Humidity ◽  
Temperature Record ◽  
Data Set ◽  
Theoretical Understanding ◽  
Uncertainty Estimates ◽  
Warming World ◽  
The Tropics

Abstract. HadISDH.2.0.0 is the first gridded, multi-variable humidity and temperature in situ observations-only climate-data product that is homogenised and annually updated. It provides physically consistent estimates for specific humidity, vapour pressure, relative humidity, dew point temperature, wet bulb temperature, dew point depression and temperature. It is a monthly mean gridded (5° by 5°) product with uncertainty estimates that account for spatio-temporal sampling, climatology calculation, homogenisation and irreducible random measurement effects. It provides a tool for the long-term monitoring of a variety of humidity-related variables which have different impacts and implications for society. It is also useful for climate model evaluation and reanalyses validation. HadISDH.2.0.0 is shown to be in good agreement both with other estimates and with theoretical understanding. The data set is available from 1973 to the present. The theme common to all variables is of a warming world with more water vapour present in the atmosphere. The largest increases in water vapour are found over the tropics and the Mediterranean. Over the tropics and high northern latitudes the surface air over land is becoming more saturated. However, despite increasing water vapour over the mid-latitudes and Mediterranean, the surface air over land is becoming less saturated. These observed features may be due to atmospheric circulation changes, land–sea warming disparities and reduced water availability or changed land surface properties.

scholarly journals First data set of H<sub>2</sub>O/HDO columns from TROPOMI

2019 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Franziska Aemisegger ◽  
Dietrich G. Feist ◽  
...  
Keyword(s):  
Water Vapour ◽  
Short Wave ◽  
Total Carbon ◽  
A Posteriori ◽  
Vertical Column ◽  
Data Set ◽  
Blocking Anticyclone ◽  
Global Coverage ◽  
Reflectance Measurements

Abstract. This paper presents a new data set of vertical column densities of the water vapour isotopologues H2O and HDO retrieved from short-wave infrared (2.3 μm) reflectance measurements by the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite. TROPOMI features daily global coverage with a spatial resolution of up to 7 km × 7 km. The retrieval utilises a profile-scaling approach. The forward model neglects scattering, thus strict cloud filtering is necessary. For validation, recent ground-based water vapour isotopologue measurements by the Total Carbon Column Observing Network (TCCON) are employed. A comparison of TCCON δD with measurements by the project Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) for data prior to 2014 (where MUSICA data is available) shows a bias in TCCON δD estimates. As TCCON HDO is currently not validated, an overall correction of recent TCCON HDO data is derived based on this finding. The agreement between the corrected TCCON measurements and collocated TROPOMI observations is good with an average bias of (0.02 ± 2) · 1021 molec cm−2 in H2O and (−0.3 ± 7) · 1017 molec cm−2 in HDO, which corresponds to a bias of (−12 ± 17) ‰ in a posteriori δD. The use of the data set is demonstrated with a case study of a blocking anticyclone in northwestern Europe in July 2018 using single overpass data.

CLASSnmat: a new dataset of Night Marine Air Temperature back to 1880

2020 ◽  
Author(s):  
Richard Cornes ◽  
Elizabeth Kent ◽  
David Berry ◽  
John Kennedy
Keyword(s):  
Air Temperature ◽  
New Method ◽  
Grid Cells ◽  
Data Set ◽  
Warm Bias ◽  
Propagation Of Uncertainty ◽  
Uncertainty Estimates ◽  
Ocean Atmosphere ◽  
The Individual ◽  
Marine Air

&lt;p&gt;We describe the construction of a new global dataset of Night Marine Air Temperature (NMAT), which provides monthly 5-degree values of NMAT back to 1880 with associated uncertainty estimates. The new dataset (CLASSnmat) builds on the HadNMAT2 dataset, which was released in 2013. CLASSnmat uses the ship-based NMAT values from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS Release 3). However, a new method is used in CLASSnmat to remove duplicated values from the observations, and to infill missing ship identifiers. In addition, a revised method of correcting the warm-bias that occurs in the data during World 2 is applied, which allows the retention of more data than in HadNMAT2. As with its predecessor, the NMAT data in CLASSnmat are not interpolated to grid-cells devoid of observations, but a revised gridding method is used which improves the propagation of uncertainty from the individual measurements through to the gridded values. CLASSnmat is released with NMAT values corrected to 2, 10 and 20m height to allow direct comparison against other measures of temperature, e.g. land-based observations or reanalysis temperature values.&lt;/p&gt;

scholarly journals Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product

2020 ◽  
Vol 13 (2) ◽  
pp. 593-628 ◽  
Author(s):  
Michael J. Garay ◽  
Marcin L. Witek ◽  
Ralph A. Kahn ◽  
Felix C. Seidel ◽  
James A. Limbacher ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Horizontal Resolution ◽  
Science Data ◽  
Data Set ◽  
Earth Observing System ◽  
Uncertainty Estimates ◽  
Level 3 ◽  
Land Surfaces ◽  
Langley Research Center ◽  
Level 2

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational on the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Terra satellite since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version of the MISR aerosol products. The level 2 (swath) product, which is reported on a 4.4 km spatial grid, is designated as version 23 (V23) and contains retrieved aerosol optical depth (AOD) and aerosol particle property information derived from MISR's multi-angle observations over both land and water. The changes from the previous version of the algorithm (V22) have significant impacts on the data product and its interpretation. The V23 data set is created from two separate retrieval algorithms that are applied over dark water and land surfaces, respectively. Besides increasing the horizontal resolution to 4.4 km compared with the coarser 17.6 m resolution in V22 and streamlining the format and content, the V23 product has added geolocation information, pixel-level uncertainty estimates, and improved cloud screening. MISR data can be obtained from the NASA Langley Research Center Atmospheric Science Data Center at https://eosweb.larc.nasa.gov/project/misr/misr_table (last access: 11 October 2019). The version number for the V23 level 2 aerosol product is F13_0023. The level 3 (gridded) aerosol product is still reported at 0.5∘×0.5∘ spatial resolution with results aggregated from the higher-resolution level 2 data. The format and content at level 3 have also been updated to reflect the changes made at level 2. The level 3 product associated with the V23 level 2 product version is designated as F15_0032. Both the level 2 and level 3 products are now provided in NetCDF format.

scholarly journals Observing Water Vapour in the Planetary Boundary Layer from the Short-Wave Infrared

2018 ◽  
Vol 10 (9) ◽  
pp. 1469 ◽  
Author(s):  
Tim Trent ◽  
Hartmut Boesch ◽  
Peter Somkuti ◽  
Noëlle Scott
Keyword(s):  
Boundary Layer ◽  
Water Vapour ◽  
Planetary Boundary Layer ◽  
Short Wave ◽  
Electromagnetic Spectrum ◽  
Climate Data ◽  
Data Set ◽  
Near Surface ◽  
Land Surfaces ◽  
Shortwave Infrared

Water vapour is a key greenhouse gas in the Earth climate system. In this golden age of satellite remote sensing, global observations of water vapour fields are made from numerous instruments measuring in the ultraviolet/visible, through the infrared bands, to the microwave regions of the electromagnetic spectrum. While these observations provide a wealth of information on columnar, free-tropospheric and upper troposphere/lower stratosphere water vapour amounts, there is still an observational gap regarding resolved bulk planetary boundary layer (PBL) concentrations. In this study we demonstrate the ability of the Greenhouse Gases Observing SATellite (GOSAT) to bridge this gap from highly resolved measurements in the shortwave infrared (SWIR). These new measurements of near surface columnar water vapour are free of topographic artefacts and are interpreted as a proxy for bulk PBL water vapour. Validation (over land surfaces only) of this new data set against global radiosondes show low biases that vary seasonally between −2% to 5%. Analysis on broad latitudinal bands show biases between −3% and 2% moving from high latitudes to the equatorial regions. Finally, with the extension of the GOSAT program out to at least 2027, we discuss the potential for a new GOSAT PBL water vapour Climate Data Record (CDR).

scholarly journals The SPARC water vapour assessment II: Profile-to-profile comparisons of stratospheric and lower mesospheric water vapour data sets obtained from satellites

2018 ◽  
Author(s):  
Stefan Lossow ◽  
Farahnaz Khosrawi ◽  
Michael Kiefer ◽  
Kaley A. Walker ◽  
Jean-Loup Bertaux ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Data Sets ◽  
General Behaviour ◽  
Data Set ◽  
Observational Database ◽  
Comparison Results ◽  
Wide Range ◽  
The Individual ◽  
Mean Time

Abstract. Within the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), profile-to-profile comparisons of stratospheric and lower mesospheric water vapour were performed considering 33 data sets derived from satellite observations of 15 different instruments. These comparisons aimed to provide a picture of the typical biases and drifts in the observational database and to identify data set specific problems. The observational database typically exhibits the largest biases below 70 hPa, both in absolute and relative terms. The smallest biases are often found between 50 hPa and 5 hPa. Typically, they range from 0.25 ppmv to 0.5 ppmv (5 % to 10 %) in this altitude region, based on the 50 % percentile over the different comparison results. Higher up, the biases are overall increasing with altitude but this general behaviour is accompanied by considerable variations. Characteristic values vary between 0.3 ppmv and 1 ppmv (4 % to 20 %). Obvious data set specific bias issues are found for a number of data sets. In our work we performed a drift analysis for data sets overlapping for a period of at least 36 months. This assessment shows a wide range of drifts among the different data sets that are statistically significant at the 2σ uncertainty level. In general, the smallest drifts are found in the altitude range between about 30 hPa to 10 hPa. Histograms considering results from all altitudes indicate the largest occurrence for drifts between 0.05 ppmv decade−1 and 0.3 ppmv decade−1. Comparisons of our drift estimates to those derived from comparisons of zonal mean time series only exhibit statistically significant differences in slightly more than 3 % of the comparisons. Hence, drift estimates from profile-to-profile and zonal mean time series comparisons are largely interchangeable. Like for the biases, a number of data sets exhibit prominent drift issues. In our analyses we found that the large number of MIPAS data sets included in the assessment affects our general results as well as the bias summaries we provide for the individual data sets. This is because these data sets exhibit a relative similarity with respect to the remaining data sets, despite that they are based on different measurement modes and different processors implementing different retrieval choices. Because of that, we have by default considered an aggregation of the comparison results obtained from MIPAS data sets. Results without this aggregation are provided on multiple occasions to characterise the effects due to the numerous MIPAS data sets. Among other effects, they cause a reduction of the typical biases in the observational database.

scholarly journals The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

2015 ◽  
Vol 7 (2) ◽  
pp. 397-414 ◽  
Author(s):  
N. Courcoux ◽  
M. Schröder
Keyword(s):  
Water Vapour ◽  
Interpolation Method ◽  
Precipitable Water ◽  
Specific Humidity ◽  
Radiosonde Data ◽  
Digital Object Identifier ◽  
Precipitable Water Vapour ◽  
Data Set ◽  
Infrared Observation ◽  
Data Record

Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record was released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM~SAF). ATOVS observations from infrared and microwave sounders onboard the National Oceanic and Atmospheric Agency (NOAA)-15–19 satellites and EUMETSAT's Meteorological Operational (Metop-A) satellite have been consistently reprocessed to generate 13 years (1999–2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km × 90 km. The data set is referenced under the following digital object identifier (DOI): doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001. After preprocessing, a maximum likelihood solution scheme was applied to the observations to simultaneously infer temperature and water vapour profiles. In a post-processing step, an objective interpolation method (Kriging) was applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer-integrated precipitable water vapour (LPW) and layer mean temperature for five tropospheric layers between the surface and 200 hPa, as well as specific humidity and temperature at six tropospheric levels between 1000 and 200 hPa. To our knowledge, this is the first time that the ATOVS record (1998–now) has been consistently reprocessed (1999–2011) to retrieve water vapour. TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric Infrared Sounder (AIRS) version 5 satellite data record. TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are −0.2 and 3.3 kg m−2, respectively. For LPW, the maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. The maximum bias and RMSE are found at the lowest layer and are −0.7 and 2.5 kg m−2, respectively. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger, with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits improved quality and stability relative to the operational CM SAF products when compared to the TPW from GUAN radiosonde data over the period 2004–2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record; therefore, a variability analysis of the data record is not recommended for the time period from January 1999 to January 2001.

scholarly journals The SPARC water vapour assessment II: profile-to-profile comparisons of stratospheric and lower mesospheric water vapour data sets obtained from satellites

2019 ◽  
Vol 12 (5) ◽  
pp. 2693-2732 ◽  
Author(s):  
Stefan Lossow ◽  
Farahnaz Khosrawi ◽  
Michael Kiefer ◽  
Kaley A. Walker ◽  
Jean-Loup Bertaux ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Data Sets ◽  
General Behaviour ◽  
Data Set ◽  
Observational Database ◽  
Comparison Results ◽  
Wide Range ◽  
The Individual ◽  
Mean Time

Abstract. Within the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), profile-to-profile comparisons of stratospheric and lower mesospheric water vapour were performed by considering 33 data sets derived from satellite observations of 15 different instruments. These comparisons aimed to provide a picture of the typical biases and drifts in the observational database and to identify data-set-specific problems. The observational database typically exhibits the largest biases below 70 hPa, both in absolute and relative terms. The smallest biases are often found between 50 and 5 hPa. Typically, they range from 0.25 to 0.5 ppmv (5 % to 10 %) in this altitude region, based on the 50 % percentile over the different comparison results. Higher up, the biases increase with altitude overall but this general behaviour is accompanied by considerable variations. Characteristic values vary between 0.3 and 1 ppmv (4 % to 20 %). Obvious data-set-specific bias issues are found for a number of data sets. In our work we performed a drift analysis for data sets overlapping for a period of at least 36 months. This assessment shows a wide range of drifts among the different data sets that are statistically significant at the 2σ uncertainty level. In general, the smallest drifts are found in the altitude range between about 30 and 10 hPa. Histograms considering results from all altitudes indicate the largest occurrence for drifts between 0.05 and 0.3 ppmv decade−1. Comparisons of our drift estimates to those derived from comparisons of zonal mean time series only exhibit statistically significant differences in slightly more than 3 % of the comparisons. Hence, drift estimates from profile-to-profile and zonal mean time series comparisons are largely interchangeable. As for the biases, a number of data sets exhibit prominent drift issues. In our analyses we found that the large number of MIPAS data sets included in the assessment affects our general results as well as the bias summaries we provide for the individual data sets. This is because these data sets exhibit a relative similarity with respect to the remaining data sets, despite the fact that they are based on different measurement modes and different processors implementing different retrieval choices. Because of that, we have by default considered an aggregation of the comparison results obtained from MIPAS data sets. Results without this aggregation are provided on multiple occasions to characterise the effects due to the numerous MIPAS data sets. Among other effects, they cause a reduction of the typical biases in the observational database.

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