| EUMETSAT

Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model

Author(s):

Im, U.; Tsigaridis, K.; Faluvegi, G.; Langen, P.L.; French, J.P.; Mahmood, R.; Thomas, M.A.; Von Salzen, K.; Thomas, D.C.; Whaley, C.H.; Klimont, Z.; Skov, H.; Brandt, Jø.

Publication title: Atmospheric Chemistry and Physics

2021

| Volume: 21 | Issue: 13

2021

DOI: 10.5194/acp-21-10413-2021

Abstract:

The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In… The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In order to study the effects of atmospheric aerosols in this warming, recent past (1990-2014) and future (2015-2050) simulations have been carried out using the GISS-E2.1 Earth system model to study the aerosol burdens and their radiative and climate impacts over the Arctic (>60 N), using anthropogenic emissions from the Eclipse V6b and the Coupled Model Intercomparison Project Phase 6 (CMIP6) databases, while global annual mean greenhouse gas concentrations were prescribed and kept fixed in all simulations. Results showed that the simulations have underestimated observed surface aerosol levels, in particular black carbon (BC) and sulfate (SO42-), by more than 50%, with the smallest biases calculated for the atmosphere-only simulations, where winds are nudged to reanalysis data. CMIP6 simulations performed slightly better in reproducing the observed surface aerosol concentrations and climate parameters, compared to the Eclipse simulations. In addition, simulations where atmosphere and ocean are fully coupled had slightly smaller biases in aerosol levels compared to atmosphere-only simulations without nudging. Arctic BC, organic aerosol (OA), and SO42- burdens decrease significantly in all simulations by 10%-60% following the reductions of 7%-78% in emission projections, with the Eclipse ensemble showing larger reductions in Arctic aerosol burdens compared to the CMIP6 ensemble. For the 2030-2050 period, the Eclipse ensemble simulated a radiative forcing due to aerosol-radiation interactions (RFARI) of -0.39±0.01Wm-2, which is -0.08Wm-2 larger than the 1990-2010 mean forcing (-0.32Wm-2), of which -0.24±0.01Wm-2 was attributed to the anthropogenic aerosols. The CMIP6 ensemble simulated a RFARI of -0.35 to -0.40Wm-2 for the same period, which is -0.01 to -0.06Wm-2 larger than the 1990-2010 mean forcing of -0.35Wm-2. The scenarios with little to no mitigation (worst-case scenarios) led to very small changes in the RFARI, while scenarios with medium to large emission mitigations led to increases in the negative RFARI, mainly due to the decrease in the positive BC forcing and the decrease in the negative SO42- forcing. The anthropogenic aerosols accounted for -0.24 to -0.26Wm-2 of the net RFARI in 2030-2050 period, in Eclipse and CMIP6 ensembles, respectively. Finally, all simulations showed an increase in the Arctic surface air temperatures throughout the simulation period. By 2050, surface air temperatures are projected to increase by 2.4 to 2.6C in the Eclipse ensemble and 1.9 to 2.6C in the CMIP6 ensemble, compared to the 1990-2010 mean. Overall, results show that even the scenarios with largest emission reductions leads to similar impact on the future Arctic surface air temperatures and sea-ice extent compared to scenarios with smaller emission reductions, implying reductions of greenhouse emissions are still necessary to mitigate climate change. © Copyright: more

Probabilistic cloud masking for the generation of CM SAF cloud climate data records from AVHRR and SEVIRI sensors

Author(s):

Karlsson, K.-G.; Johansson, E.; Håkansson, N.; Sedlar, J.; Eliasson, S.

Publication title: Remote Sensing

2020

| Volume: 12 | Issue: 4

2020

DOI: 10.3390/rs12040713

Abstract:

Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generat… Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generation, cloud screening must be balanced, so both false cloud-free and false cloudy retrievals are minimized. Many methods used in recent CDRs show signs of clear-conservative cloud screening leading to overestimated cloudiness. This study presents a new cloud screening approach for Advanced Very-High-Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery based on the Bayesian discrimination theory. The method is trained on high-quality cloud observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The method delivers results designed for optimally balanced cloud screening expressed as cloud probabilities together with information on for which clouds (minimum cloud optical thickness) the probabilities are valid. Cloud screening characteristics over 28 different Earth surface categories were estimated. Using independent CALIOP observations (including all observed clouds) in 2010 for validation, the total global hit rates for AVHRR data and the SEVIRI full disk were 82% and 85%, respectively. High-latitude oceans had the best performance, with a hit rate of approximately 93%. The results were compared to the CM SAF cLoud, Albedo, and surface RAdiation dataset from AVHRR data-second edition (CLARA-A2) CDR and showed general improvements over most global regions. Notably, the Kuipers' Skill Score improved, verifying a more balanced cloud screening. The new method will be used to prepare the new CLARA-A3 and CLAAS-3 (CLoud property dAtAset using SEVIRI, Edition 3) CDRs in the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project. © 2020 by the author. more

Atmosphere CM-SAF Climate Data Records Method

Projected Changes in Solar PV and Wind Energy Potential over West Africa: An Analysis of CORDEX-CORE Simulations

Author(s):

Ndiaye, A; Moussa, MS; Dione, C; Sawadogo, W; Bliefernicht, J; Dungall, L; Kunstmann, H

Publication title: ENERGIES

2022

| Volume: 15 | Issue: 24

2022

DOI: 10.3390/en15249602

Abstract:

Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power de… Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power demand and climate change mitigation. However, the future impacts of climate change on solar PV and the wind energy potential in the region are still unclear. This study investigates the expected future impacts of climate change on solar PV and wind energy potential over West Africa using an ensemble of three regional climate models (RCMs). Each RCM is driven by three global climate models (GCMs) from the new coordinated high-resolution output for regional evaluations (CORDEX-CORE) under the RCP8.5 scenario. Two projection periods were used: the near future (2021-2050) and the far future (2071-2100). For the model evaluation, reanalysis data from ERA5 and satellite-based climate data (SARAH-2) were used. The models and their ensemble mean (hereafter Mean) show acceptable performance for the simulations of the solar PV potential, the wind power density, and related variables with some biases. The Mean predicts a general decrease in the solar PV potential over the region of about -2% in the near future and -4% in the far future. The wind power density (WPD) is expected to increase by about 20% in the near future and 40% in the far future. The changes for solar PV potential seem to be consistent, although the intensity differs according to the RCM used. For the WPD, there are some discrepancies among the RCMs in terms of intensity and direction. This study can guide governments and policymakers in decision making for future solar and wind energy projects in the region. more

Application Atmosphere CM-SAF Climate Data Records

Present-Day Greenland Ice Sheet Climate and Surface Mass Balance in CESM2

Author(s):

van Kampenhout, L.; Lenaerts, J.T.M.; Lipscomb, W.H.; Lhermitte, S.; Noël, B.; Vizcaíno, M.; Sacks, W.J.; van den Broeke, M.R.

Publication title: Journal of Geophysical Research: Earth Surface

2020

| Volume: 125 | Issue: 2

2020

DOI: 10.1029/2019JF005318

Abstract:

The response of the Greenland Ice Sheet (GrIS) to a warmer climate is uncertain on long time scales. Climate models, such as those participating in th… The response of the Greenland Ice Sheet (GrIS) to a warmer climate is uncertain on long time scales. Climate models, such as those participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), are used to assess this uncertainty. The Community Earth System Model version 2.1 (CESM2) is a CMIP6 model capable of running climate simulations with either one-way coupling (fixed ice sheet geometry) or two-way coupling (dynamic geometry) to the GrIS. The model features prognostic snow albedo, online downscaling using elevation classes, and a firn pack to refreeze percolating melt water. Here we evaluate the representation of the GrIS surface energy balance and surface mass balance in CESM2 at 1° resolution with fixed GrIS geometry. CESM2 agrees closely with ERA-Interim reanalysis data for key controls on GrIS SMB: surface pressure, sea ice extent, 500 hPa geopotential height, wind speed, and 700 hPa air temperature. Cloudsat-CALIPSO data show that supercooled liquid-containing clouds are adequately represented, whereas comparisons to Moderate Resolution Imaging Spectroradiometer and CM SAF Cloud, Albedo, and Surface Radiation data set from Advanced Very High Resolution Radiometer data second edition data suggest that CESM2 underestimates surface albedo. The seasonal cycle and spatial patterns of surface energy balance and surface mass balance components in CESM2 agree well with regional climate model RACMO2.3p2, with GrIS-integrated melt, refreezing, and runoff bracketed by RACMO2 counterparts at 11 and 1 km. Time series of melt, runoff, and SMB show a break point around 1990, similar to RACMO2. These results suggest that GrIS SMB is realistic in CESM2, which adds confidence to coupled ice sheet-climate experiments that aim to assess the GrIS contribution to future sea level rise. ©2020. The Authors. more

Application CM-SAF Climate Data Records Cryosphere Validation

Projected loss of brown macroalgae and seagrasses with global environmental change

Author(s):

Manca, Federica; Benedetti-Cecchi, Lisandro; Bradshaw, Corey J. A.; Cabeza, Mar; Gustafsson, Camilla; Norkko, Alf M.; Roslin, Tomas V.; Thomas, David N.; White, Lydia; Strona, Giovanni

Publication title: Nature Communications

2024

| Volume: 15 | Issue: 1

2024

DOI: 10.1038/s41467-024-48273-6

Abstract:

Although many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity re… Although many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity remain relatively unexplored. In this work, we model global shifts in one of the most important marine functional groups—ecosystem-structuring macrophytes—and predict substantial end-of-century change. By modelling the future distribution of 207 brown macroalgae and seagrass species at high temporal and spatial resolution under different climate-change projections, we estimate that by 2100, local macrophyte diversity will decline by 3–4% on average, with 17 to 22% of localities losing at least 10% of their macrophyte species. The current range of macrophytes will be eroded by 5–6%, and highly suitable macrophyte habitat will be substantially reduced globally (78–96%). Global macrophyte habitat will shift among marine regions, with a high potential for expansion in polar regions. more

Application Atmosphere CM-SAF Climate Data Records Ocean

pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Author(s):

Jensen, Adam R.; Anderson, Kevin S.; Holmgren, William F.; Mikofski, Mark A.; Hansen, Clifford W.; Boeman, Leland J.; Loonen, Roel

Publication title: Solar Energy

2023

| Volume: 266

2023

DOI: 10.1016/j.solener.2023.112092

Abstract:

Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radia… Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radiation models, and validating irradiance datasets. However, lack of standardization in data formats and access interfaces across providers constitutes a major barrier to entry for new users. pvlib python’s iotools subpackage aims to solve this issue by providing standardized Python functions for reading local files and retrieving data from external providers. All functions follow a uniform pattern and return convenient data outputs, allowing users to seamlessly switch between data providers and explore alternative datasets. The pvlib package is community-developed on GitHub: https://github.com/pvlib/pvlib-python. As of pvlib python version 0.9.5, the iotools subpackage supports 12 different datasets, including ground measurement, reanalysis, and satellite-derived irradiance data. The supported ground measurement networks include the Baseline Surface Radiation Network (BSRN), NREL MIDC, SRML, SOLRAD, SURFRAD, and the US Climate Reference Network (CRN). Additionally, satellite-derived and reanalysis irradiance data from the following sources are supported: PVGIS (SARAH & ERA5), NSRDB PSM3, and CAMS Radiation Service (including McClear clear-sky irradiance). more

Atmosphere CM-SAF Climate Data Records Software for CDR development

Quality assessment and improvement of the EUMETSAT Meteosat Surface Albedo Climate Data Record

Author(s):

Lattanzio, A.; Fell, F.; Bennartz, R.; Trigo, I. F.; Schulz, J.

Publication title: Atmospheric Measurement Techniques

2015

| Volume: 8 | Issue: 10

2015

DOI: 10.5194/amt-8-4561-2015

Abstract:

Abstract. Surface albedo has been identified as an important parameter for understanding and quantifying the Earth's radiation budget. EUMETSAT genera… Abstract. Surface albedo has been identified as an important parameter for understanding and quantifying the Earth's radiation budget. EUMETSAT generated the Meteosat Surface Albedo (MSA) Climate Data Record (CDR) currently comprising up to 24 years (1982–2006) of continuous surface albedo coverage for large areas of the Earth. This CDR has been created within the Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) framework. The long-term consistency of the MSA CDR is high and meets the Global Climate Observing System (GCOS) stability requirements for desert reference sites. The limitation in quality due to non-removed clouds by the embedded cloud screening procedure is the most relevant weakness in the retrieval process. A twofold strategy is applied to efficiently improve the cloud detection and removal. The first step consists of the application of a robust and reliable cloud mask, taking advantage of the information contained in the measurements of the infrared and visible bands. Due to the limited information available from old radiometers, some clouds can still remain undetected. A second step relies on a post-processing analysis of the albedo seasonal variation together with the usage of a background albedo map in order to detect and screen out such outliers. The usage of a reliable cloud mask has a double effect. It enhances the number of high-quality retrievals for tropical forest areas sensed under low view angles and removes the most frequently unrealistic retrievals on similar surfaces sensed under high view angles. As expected, the usage of a cloud mask has a negligible impact on desert areas where clear conditions dominate. The exploitation of the albedo seasonal variation for cloud removal has good potentialities but it needs to be carefully addressed. Nevertheless it is shown that the inclusion of cloud masking and removal strategy is a key point for the generation of the next MSA CDR release. more

Climate Data Records EUM-Secr Land Validation

Radiance Simulations in Support of Climate Services

Author(s):

Poli, P.; Roebeling, R.; John, V.O.; Doutriaux-Boucher, M.; Schulz, J.; Lattanzio, A.; Petraityte, K.; Grant, M.; Hanschmann, T.; Onderwaater, J.; Sus, O.; Huckle, R.; Coppens, D.; Theodore, B.; August, T.; Simmons, A.J.; Bell, B.; Mittaz, J.; Hall, T.; Vidot, J.; Brunel, P.; Johnson, J.E.; Zamkoff, E.B.; Al-Jazrawi, A.F.; Esfandiari, A.E.; Gerasimov, I.V.; Kobayashi, S.

Publication title: Earth and Space Science

2023

| Volume: 10 | Issue: 10

2023

DOI: 10.1029/2023EA002868

Abstract:

Climate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates ho… Climate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates how the development and the uptake of F(C)DR benefit from radiance simulations, using reanalyses and radiative transfer models. We identify three classes of applications, with examples for each application class. The first application is to validate assumptions during F(C)DR development. Hereto we show the value of applying advanced quality controls to geostationary European (Meteosat) images. We also show the value of a cloud mask to study the spatio-temporal coherence of the impact of the Mount Pinatubo volcanic eruption between Advanced Very High Resolution Radiometer (AVHRR) and the High-resolution Infrared Radiation Sounder (HIRS) data. The second application is to assess the coherence between reanalyses and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI-1) flown on a Soviet satellite in 1979. We also present a first attempt to estimate the random uncertainties from this instrument. Finally, we investigate how advanced bias correction can help to improve the coherence between reanalysis and Nimbus-3 Medium-Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform F(C)DR users about particular quality aspects. We show how simulations can help to make a better-informed use of the corresponding F(C)DR, taking as examples the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the Meteosat Second Generation (MSG) imager, and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Water Vapor Profiler (SSM/T-2). © 2023 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. more

Application Atmosphere CM-SAF Climate Data Records EUM-Secr NWP-SAF

Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

Author(s):

Nightingale, Joanne; Boersma, Klaas; Muller, Jan-Peter; Compernolle, Steven; Lambert, Jean-Christopher; Blessing, Simon; Giering, Ralf; Gobron, Nadine; De Smedt, Isabelle; Coheur, Pierre; George, Maya; Schulz, Jörg; Wood, Alexander

Publication title: Remote Sensing

2018

| Volume: 10 | Issue: 8

2018

DOI: 10.3390/rs10081254

Abstract:

Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of… Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts, and manage natural resources. Policymakers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products, as well as the reference measurements used to calibrate, validate, or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite-derived datasets, by prototyping a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface albedo, leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO). The provision of standardised QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products and their specific applications. more

AC-SAF Application Atmosphere EUM-Secr International cooperation Land Validation

Quantifying Daytime Heating Biases in Marine Air Temperature Observations from Ships

Author(s):

Cropper, TE; Berry, DI; Cornes, RC; Kent, EC

Publication title: JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY

2023

| Volume: 40 | Issue: 4

2023

DOI: 10.1175/JTECH-D-22-0080.1

Abstract:

Marine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the… Marine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the vessels. This makes unadjusted daytime observations unsuitable for many applications including for the monitoring of long-term temperature change over the oceans. In this paper a physics -based approach is used to estimate this heating bias in ship observations from ICOADS. Under this approach, empirically determined coefficients represent the energy transfer terms of a heat budget model that quantifies the heating bias and is applied as a function of cloud cover and the relative wind speed over individual ships. The coefficients for each ship are derived from the anomalous diurnal heating relative to nighttime air temperature. Model coefficients, cloud cover, and relative wind speed are then used to estimate the heating bias ship by ship and generate nighttime-equivalent time series. A variety of methodological approaches were tested. Application of this method enables the inclusion of some daytime observations in climate records based on marine air temperatures, allowing an earlier start date and giving an increase in spatial coverage compared to existing records that exclude daytime observations.SIGNIFICANCE STATEMENT: Currently, the longest available record of air temperature over the oceans starts in 1880. We present an approach that enables observations of air temperatures over the oceans to be used in the creation of long-term climate records that are presently excluded. We do this by estimating the biases inherent in daytime tem-perature reports from ships, and adjust for these biases by implementing a numerical heat-budget model. The adjust-ment can be applied to the variety of ship types present in observational archives. The resulting adjusted temperatures can be used to create a more spatially complete record over the oceans, that extends further back in time, potentially into the late eighteenth century. more

Application Atmosphere CM-SAF Climate Data Records

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