scholarly journals Analysis of climate variability and droughts in East Africa using high-resolution climate data products

2020 ◽  
Vol 186 ◽  
pp. 103130 ◽  
Author(s):  
Solomon H. Gebrechorkos ◽  
Stephan Hülsmann ◽  
Christian Bernhofer
Keyword(s):  
High Resolution ◽  
Climate Variability ◽  
East Africa ◽  
Climate Data ◽  
Data Products

Validation of tropospheric NO2 columns measurements from GOME-2, OMI and TROPOMI using MAX-DOAS and direct-sun network observations with focus on dilution effects

2020 ◽  
Author(s):  
Gaia Pinardi ◽  
Michel Van Roozendael ◽  
François Hendrick ◽  
Nicolas Theys ◽  
Steven Compernolle ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Data ◽  
Climate Data ◽  
Site Location ◽  
Data Products ◽  
One Year ◽  
Dilution Effects ◽  
The Impact ◽  
Climate Data Record

<p>Ground-based remote sensing MAX-DOAS and Pandora direct-sun instruments measuring in the UV-Vis spectral region are nowadays widely used to monitor atmospheric NO<sub>2</sub> columns. Owing to the multiple geometries used, these techniques can differentiate total, tropospheric and stratospheric NO<sub>2</sub> content and  therefore provide an appropriate source of correlative data for the validation of satellite instruments such as GOME-2, OMI and TROPOMI.</p><p>In this study we combine ground-based remote sensing correlative measurements available from over 40 sites distributed worldwide to address the validation of GOME-2, OMI and TROPOMI data products. For GOME-2, we concentrate on the GDP operational product generated within the EUMETSAT AC SAF project and on the climate data record generated within the EU QA4ECV project, while for OMI we address both the TEMIS and QA4ECV data products. Regarding TROPOMI, the operational OFFL product is considered. To derive tropospheric NO<sub>2</sub> columns from direct-sun total NO<sub>2</sub> data, we use estimates of the stratospheric contribution available from each satellite data product.</p><p>A negative bias is generally found between the different satellite data products and the ground-based tropospheric NO<sub>2</sub> measurements, which is mostly prominent in urban sites characterized by strong localized emission sources (up to about -32% to -45%, e.g. for OMI TEMIS and GOME-2 GDP vs MAX-DOAS ensemble). In an attempt to quantify and correct for the horizontal dilution happening around urban stations (due to diffusion and transport and to the spatial averaging of high resolution structures), we use high-resolution gridded NO<sub>2</sub> maps obtained from one year of QA4ECV data. Results from applying this dilution correction show a clear improvement of the agreement between GOME-2 and OMI data at polluted urban locations. Further, the impact of the satellite ground pixel size (GOME-2 40x80km², OMI 13x24km²) and site location is investigated.</p>

scholarly journals Climate Variability in Central Europe during the Last 2500 Years Reconstructed from Four High-Resolution Multi-Proxy Speleothem Records

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 166
Author(s):  
Sarah Waltgenbach ◽  
Dana F. C. Riechelmann ◽  
Christoph Spötl ◽  
Klaus P. Jochum ◽  
Jens Fohlmeister ◽  
...  
Keyword(s):  
Trace Elements ◽  
High Resolution ◽  
Climate Variability ◽  
Little Ice Age ◽  
Medieval Warm Period ◽  
Warm Period ◽  
Ice Age ◽  
Cold Period ◽  
Cave System ◽  
Dark Ages

The Late Holocene was characterized by several centennial-scale climate oscillations including the Roman Warm Period, the Dark Ages Cold Period, the Medieval Warm Period and the Little Ice Age. The detection and investigation of such climate anomalies requires paleoclimate archives with an accurate chronology as well as a high temporal resolution. Here, we present 230Th/U-dated high-resolution multi-proxy records (δ13C, δ18O and trace elements) for the last 2500 years of four speleothems from Bunker Cave and the Herbstlabyrinth cave system in Germany. The multi-proxy data of all four speleothems show evidence of two warm and two cold phases during the last 2500 years, which coincide with the Roman Warm Period and the Medieval Warm Period, as well as the Dark Ages Cold Period and the Little Ice Age, respectively. During these four cold and warm periods, the δ18O and δ13C records of all four speleothems and the Mg concentration of the speleothems Bu4 (Bunker Cave) and TV1 (Herbstlabyrinth cave system) show common features and are thus interpreted to be related to past climate variability. Comparison with other paleoclimate records suggests a strong influence of the North Atlantic Oscillation at the two caves sites, which is reflected by warm and humid conditions during the Roman Warm Period and the Medieval Warm Period, and cold and dry climate during the Dark Ages Cold period and the Little Ice Age. The Mg records of speleothems Bu1 (Bunker Cave) and NG01 (Herbstlabyrinth) as well as the inconsistent patterns of Sr, Ba and P suggests that the processes controlling the abundance of these trace elements are dominated by site-specific effects rather than being related to supra-regional climate variability.

scholarly journals A new pan-European dataset for gridded daily average wind speed based on in-situ observations

2021 ◽  
Author(s):  
Jouke de Baar ◽  
Gerard van der Schrier ◽  
Irene Garcia-Marti ◽  
Else van den Besselaar
Keyword(s):  
Spatial Distribution ◽  
High Resolution ◽  
Cross Validation ◽  
Data Sets ◽  
Optimal Prediction ◽  
Auxiliary Variables ◽  
Climate Data ◽  
Ensemble Spread ◽  
Wind Fields

<p><strong>Objective</strong></p><p>The purpose of the European Copernicus Climate Change Service (C3S) is to support society by providing information about the past, present and future climate. For the service related to <em>in-situ</em> observations, one of the objectives is to provide high-resolution (0.1x0.1 and 0.25x0.25 degrees) gridded wind speed fields. The gridded wind fields are based on ECA&D daily average station observations for the period 1970-2020.</p><p><strong>Research question</strong> </p><p>We address the following research questions: [1] How efficiently can we provide the gridded wind fields as a statistically reliable ensemble, in order to represent the uncertainty of the gridding? [2] How efficiently can we exploit high-resolution geographical auxiliary variables (e.g. digital elevation model, terrain roughness) to augment the station data from a sparse network, in order to provide gridded wind fields with high-resolution local features?</p><p><strong>Approach</strong></p><p>In our analysis, we apply greedy forward selection linear regression (FSLR) to include the high-resolution effects of the auxiliary variables on monthly-mean data. These data provide a ‘background’ for the daily estimates. We apply cross-validation to avoid FSLR over-fitting and use full-cycle bootstrapping to create FSLR ensemble members. Then, we apply Gaussian process regression (GPR) to regress the daily anomalies. We consider the effect of the spatial distribution of station locations on the GPR gridding uncertainty.</p><p>The goal of this work is to produce several decades of daily gridded wind fields, hence, computational efficiency is of utmost importance. We alleviate the computational cost of the FSLR and GPR analyses by incorporating greedy algorithms and sparse matrix algebra in the analyses.</p><p><strong>Novelty</strong>   </p><p>The gridded wind fields are calculated as a statistical ensemble of realizations. In the present analysis, the ensemble spread is based on uncertainties arising from the auxiliary variables as well as from the spatial distribution of stations.</p><p>Cross-validation is used to tune the GPR hyper parameters. Where conventional GPR hyperparameter tuning aims at an optimal prediction of the gridded mean, instead, we tune the GPR hyperparameters for optimal prediction of the gridded ensemble spread.</p><p>Building on our experience with providing similar gridded climate data sets, this set of gridded wind fields is a novel addition to the E-OBS climate data sets.</p>

scholarly journals A 40-year global dataset of visible channel remote sensing reflectances and coccolithophore bloom occurrence derived from the Advanced Very High Resolution Radiometer catalogue

2018 ◽  
Author(s):  
Benjamin R. Loveday ◽  
Timothy Smyth
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Atmospheric Correction ◽  
Global Ocean ◽  
Climate Data ◽  
Ancillary Data ◽  
Remote Sensing Reflectance ◽  
Data Files ◽  
Climate Data Record ◽  
Very High

Abstract. A consistently calibrated 40-year length dataset of visible channel remote sensing reflectance has been derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor global time-series. The dataset uses as its source the Pathfinder Atmospheres – Extended (PATMOS-x) v5.3 Climate Data Record (CDR) for top-of-atmosphere (TOA) visible channel reflectances. This paper describes the theoretical basis for the atmospheric correction procedure and its subsequent implementation, including the necessary ancillary data files used and quality flags applied, in order to determine remote sensing reflectance. The resulting dataset is produced at daily, and archived at monthly, resolution, on a 0.1° × 0.1° grid at https://doi.pangaea.de/10.1594/PANGAEA.892175. The primary aim of deriving this dataset is to highlight regions of the global ocean affected by highly reflective blooms of the coccolithophorid Emiliania Huxleyi over the past 40 years.

Sign in / Sign up

Export Citation Format

Share Document