Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions

Author(s):
Baró Pérez, A.; Diamond, M.S.; Bender, F.A.-M.; Devasthale, A.; Schwarz, M.; Savre, J.; Tonttila, J.; Kokkola, H.; Lee, H.; Painemal, D.; Ekman, A.M.L.
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 8
2024
DOI: 10.5194/acp-24-4591-2024
Abstract:
Biomass burning plumes are frequently transported over the southeast Atlantic (SEA) stratocumulus deck during the southern African fire season (June-O… Biomass burning plumes are frequently transported over the southeast Atlantic (SEA) stratocumulus deck during the southern African fire season (June-October). The plumes bring large amounts of absorbing aerosols and enhanced moisture, which can trigger a rich set of aerosol-cloud-radiation interactions with climatic consequences that are still poorly understood. We use large-eddy simulation (LES) to explore and disentangle the individual impacts of aerosols and moisture on the underlying stratocumulus clouds, the marine boundary layer (MBL) evolution, and the stratocumulus-to-cumulus transition (SCT) for three different meteorological situations over the southeast Atlantic during August 2017. For all three cases, our LES shows that the SCT is driven by increased sea surface temperatures and cloud-top entrainment as the air is advected towards the Equator. In the LES model, aerosol indirect effects, including impacts on drizzle production, have a small influence on the modeled cloud evolution and SCT, even when aerosol concentrations are lowered to background concentrations. In contrast, local semi-direct effects, i.e., aerosol absorption of solar radiation in the MBL, cause a reduction in cloud cover that can lead to a speed-up of the SCT, in particular during the daytime and during broken cloud conditions, especially in highly polluted situations. The largest impact on the radiative budget comes from aerosol impacts on cloud albedo: the plume with absorbing aerosols produces a total average 3gd of simulations. We find that the moisture accompanying the aerosol plume produces an additional cooling effect that is about as large as the total aerosol radiative effect. Overall, there is still a large uncertainty associated with the radiative and cloud evolution effects of biomass burning aerosols. A comparison between different models in a common framework, combined with constraints from in situ observations, could help to reduce the uncertainty. © 2024 Alejandro Baro Perez et al. more
Application Atmosphere CM-SAF Climate Data Records

Coastal wind retrievals from corrected QuikSCAT Normalized Radar Cross Sections

Author(s):
Grieco, G.; Portabella, M.; Stoffelen, A.; Verhoef, A.; Vogelzang, J.; Zanchetta, A.; Zecchetto, S.
Publication title: Remote Sensing of Environment
2024
 | Volume: 308
2024
DOI: 10.1016/j.rse.2024.114179
Abstract:
A new correction scheme named “noise regularization”, aiming at mitigating land contamination in SeaWinds scatterometer coastal Normalized Radar Cross… A new correction scheme named “noise regularization”, aiming at mitigating land contamination in SeaWinds scatterometer coastal Normalized Radar Cross Sections (σ0s) is presented. The scheme is based on an analytical Cumulative Distribution Function (CDF) matching technique. Its efficacy is demonstrated in a semi-enclosed basin of the Mediterranean Sea, both in the σ0 and wind field domains. Wind biases along the coasts disappear and the sampling improves by a factor of 3 within the first 10 km from the coastline. This figure is likely underestimated because of a non-optimal tuning of the a-posteriori quality control tests in coastal areas. Finally, wind retrievals are validated against those from a collocated Synthetic Aperture Radar (SAR) image acquired by the Envisat Advanced SAR (ASAR) offshore Norway. The agreement is very good in both speed and direction, and opens new perspectives on the use of SAR as a validation tool of coastal winds. © 2024 The Author(s) more
Atmosphere Climate Data Records NWP-SAF OSI-SAF Software for CDR development Validation

Comparison of Advanced Technology Microwave Sounder Biases Estimated Using Radio Occultation and Hurricane Florence (2018) Captured by NOAA-20 and S-NPP

Author(s):
Tian, Xiaoxu; Zou, Xiaolei
Publication title: Advances in Atmospheric Sciences
2020
 | Volume: 37 | Issue: 3
2020
DOI: 10.1007/s00376-019-9119-5
Abstract:
The second Advanced Technology Microwave Sounder (ATMS) was onboard the National Oceanic and Atmospheric Administration (NOAA)-20 satellite when launc… The second Advanced Technology Microwave Sounder (ATMS) was onboard the National Oceanic and Atmospheric Administration (NOAA)-20 satellite when launched on 18 November 2017. Using nearly six months of the earliest NOAA-20 observations, the biases of the ATMS instrument were compared between NOAA-20 and the Suomi National Polar-Orbiting Partnership (S-NPP) satellite. The biases of ATMS channels 8 to 13 were estimated from the differences between antenna temperature observations and model simulations generated from Meteorological Operational (MetOp)-A and MetOp-B satellites’ Global Positioning System (GPS) radio occultation (RO) temperature and water vapor profiles. It was found that the ATMS onboard the NOAA-20 satellite has generally larger cold biases in the brightness temperature measurements at channels 8 to 13 and small standard deviations. The observations from ATMS on both S-NPP and NOAA-20 are shown to demonstrate an ability to capture a less than 1-h temporal evolution of Hurricane Florence (2018) due to the fact that the S-NPP orbits closely follow those of NOAA-20. more
Application Atmosphere Climate Data Records ROM-SAF

Comparison of decadal global water vapor changes derived from independent satellite time series

Author(s):
Mieruch, S.; Schröder, M.; Noël, S.; Schulz, J.
Publication title: Journal of Geophysical Research: Atmospheres
2014
 | Volume: 119 | Issue: 22
2014
DOI: 10.1002/2014JD021588
Abstract:
We analyze trends in total column water vapor (TCWV) retrieved from independent satellite observations and retrieval schemes. GOME-SCIAMACHY (Global O… We analyze trends in total column water vapor (TCWV) retrieved from independent satellite observations and retrieval schemes. GOME-SCIAMACHY (Global Ozone Monitoring Experiment-SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) measurements are carried out in the visible part of the solar spectrum and present a partly cloud-corrected climatology that is available over land and ocean. The HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) product, provided by EUMETSAT's Satellite Application Facility on Climate Monitoring is based on passive microwave observations from the Special Sensor Microwave/Imager. It also includes the TCWV from cloudy pixels but is only available over oceans. The common observation time period is between 1996 and 2005. Due to the relatively short length of the period, the strong interannual variability with strong contributions from El Niño and La Niña events and the strong anomaly at the start of the common period, caused by the 1997/1998 El Niño, the observed trends should not be interpreted as long-term climate trends. After subtraction of average seasonality from monthly gridded data, a linear model and a level shift model have been fitted to the HOAPS and GOME-SCIAMACHY data, respectively. Autocorrelation and cross correlation of fit residuals are accounted for in assessing uncertainties in trends. The trends observed in both time series agree within uncertainty margins. This agreement holds true for spatial patterns, magnitudes, and global averages. The consistency increases confidence in the reliability of the trends because the methods, spectral range, and observation technique as well as the satellites and their orbits are completely independent of each other. The similarity of the trends in both data sets is an indication of sufficient stability in the observations for the time period of ≈ 10 years. more
Atmosphere CM-SAF Climate Data Records Validation

Comparison of long-term solar radiation trends from CM SAF satellite products with ground-based data at the Iberian Peninsula for the period 1985–2015

Author(s):
Montero-Martín, Javier; Antón, Manuel; Vaquero-Martínez, Javier; Sanchez-Lorenzo, Arturo
Publication title: Atmospheric Research
2020
 | Volume: 236
2020
DOI: 10.1016/j.atmosres.2019.104839
Abstract:
The aim of this work is to analyse the quality of long-term trends of surface incoming shortwave solar radiation (SIS) derived from two satellite data… The aim of this work is to analyse the quality of long-term trends of surface incoming shortwave solar radiation (SIS) derived from two satellite datasets from the EUMETSAT Satellite Application on Climate Monitoring (CM SAF): the SIS Data Set from the Advanced Very High-Resolution Radiometer (AVHRR) data, Edition 2 (CLARA-A2), and the SIS Data Set-Heliosat, Edition 2 (SARAH-2). In order to achieve this goal, reference ground-based SIS measurements recorded at 12 stations over the Iberian Peninsula for the period 1985–2015 are used in this study. Firstly, the two satellite datasets have been compared against ground-based SIS measurements at 12 surface sites, showing a good agreement (i.e., R = 0.83 in SARAH-2 and R = 0.80 in CLARA-A2 on an annual basis). However, the two satellite datasets substantially underestimate the SIS trends found for the ground-based measurements. Thus, while the ground-based SIS data reported trends between −0.5 and + 6.5 Wm−2decade−1 (with statistical significance at 95% level at most stations), the satellite datasets gave trends lower for all locations (without statistical significance); between −0.4 and + 3.8 Wm−2decade−1 for CLARA-A2, and between +0.2 and + 2.8 Wm−2decade−1 for SARAH-2. It is worth to mention that the seasonal analysis of the SIS trends for both ground-based and satellite data displays a reasonably good agreement in spring (i.e., high positive trends), in accordance with the notable decline in the cloudiness for this season in the study region. By contrast, satellite products exhibit smaller SIS anomalies than ground-based data in summer, particularly from the beginning 2000s, which could be related to well-known decrease in the aerosol load over the study region. more
Atmosphere CM-SAF Climate Data Records Validation

Comparison of profile total ozone from SBUV (v8.6) with GOME-type and ground-based total ozone for a 16-year period (1996 to 2011)

Author(s):
Chiou, E. W.; Bhartia, P. K.; McPeters, R. D.; Loyola, D. G.; Coldewey-Egbers, M.; Fioletov, V. E.; Van Roozendael, M.; Spurr, R.; Lerot, C.; Frith, S. M.
Publication title: Atmospheric Measurement Techniques
2014
 | Volume: 7 | Issue: 6
2014
DOI: 10.5194/amt-7-1681-2014
Abstract:
Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, na… Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile total ozone, (ii) GTO (GOME-type total ozone), and (iii) ground-based total ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0–30° S, 0–30° N, 50–30° S, and 30–60° N. It has been found that, on average, the differences in monthly zonal mean total ozone vary between −0.3 and 0.8 % and are well within 1%. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean total ozone vary between 0.6–0.7% and 2.8–3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4–0.6% and 2.2–3.5%. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4–2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1% yr−1 (−0.1 and 0.3 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multi-year total ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30–60° N from −5% in 1996 to −2% in 2010. In contrast, at 50–30° S and 30° S–30° N there has been a levelling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1%, but a slight increase has been found in the differences during the period 1996–2010. more
AC-SAF Atmosphere Climate Data Records Validation

Comparison of Satellite-Based and Ångström–Prescott Estimated Global Horizontal Irradiance under Different Cloud Cover Conditions in South African Locations

Author(s):
Mabasa, Brighton; Lysko, Meena D.; Moloi, Sabata J.
Publication title: Solar
2022
 | Volume: 2 | Issue: 3
2022
DOI: 10.3390/solar2030021
Abstract:
The study compares the performance of satellite-based datasets and the Ångström–Prescott (AP) model in estimating the daily global horizontal irradian… The study compares the performance of satellite-based datasets and the Ångström–Prescott (AP) model in estimating the daily global horizontal irradiance (GHI) for stations in South Africa. The daily GHI from four satellites (namely SOLCAST, CAMS, NASA SSE, and CMSAF SARAH) and the Ångström–Prescott (AP) model are evaluated by validating them against ground observation data from eight radiometric stations located in all six macro-climatological regions of South Africa, for the period 2014-19. The evaluation is carried out under clear-sky, all-sky, and overcast-sky conditions. CLAAS-2 cloud fractional coverage data are used to determine clear and overcast sky days. The observed GHI data are first quality controlled using the Baseline Surface Radiation Network methodology and then quality control of the HelioClim model. The traditional statistical benchmarks, namely the relative mean bias error (rMBE), relative root mean square error (rRMSE), relative mean absolute error (rMAE), and the coefficient of determination (R2) provided information about the performance of the datasets. Under clear skies, the estimated datasets showed excellent performance with maximum rMBE, rMAE, and rRMSE less than 6.5% and a minimum R2 of 0.97. In contrast, under overcast-sky conditions there was noticeably poor performance with maximum rMBE (24%), rMAE (29%), rRMSE (39%), and minimum R2 (0.74). For all-sky conditions, good correlation was found for SOLCAST (0.948), CMSAF (0.948), CAMS (0.944), and AP model (0.91); all with R2 over 0.91. The maximum rRMSE for SOLCAST (10%), CAMS (12%), CMSAF (12%), and AP model (11%) was less than 13%. The maximum rMAE for SOLCAST (7%), CAMS (8%), CMSAF (8%), and AP model (9%) was less than 10%, showing good performance. While the R2 correlations for the NASA SSE satellite-based GHI were less than 0.9 (0.896), the maximum rRMSE was 18% and the maximum rMAE was 15%, showing rather poor performance. The performance of the SOLCAST, CAMS, CMSAF, and AP models was almost the same in the study area. CAMS, CMSAF, and AP models are viable, freely available datasets for estimating the daily GHI at South African locations with quantitative certainty. The relatively poor performance of the NASA SSE datasets in the study area could be attributed to their low spatial resolution of 0.5° × 0.5° (~55 km × 55 km). The feasibility of the datasets decreased significantly as the proportion of sky that was covered by clouds increased. The results of the study could provide a basis/data for further research to correct biases between in situ observations and the estimated GHI datasets using machine learning algorithms. more
Application Atmosphere CM-SAF Climate Data Records

Comparison of surface solar irradiance from ground observations and satellite data (1990–2016) over a complex orography region (piedmont—Northwest Italy)

Author(s):
Manara, V.; Stocco, E.; Brunetti, M.; Diolaiuti, G.A.; Fugazza, D.; Pfeifroth, U.; Senese, A.; Trentmann, J.; Maugeri, M.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 23
2020
DOI: https://doi.org/10.3390/rs12233882
Abstract:
Climate Monitoring Satellite Application Facility (CM SAF) surface solar irradiance (SSI) products were compared with ground-based observations over t… Climate Monitoring Satellite Application Facility (CM SAF) surface solar irradiance (SSI) products were compared with ground-based observations over the Piedmont region (north-western Italy) for the period 1990–2016. These products were SARAH-2.1 (Surface Solar Radiation DataSet—Heliosat version 2.1) and CLARA-A2 (Cloud, Albedo and Surface Radiation dataset version A2). The aim was to contribute to the discussion on the representativeness of satellite SSI data including a focus on high-elevation areas. The comparison between SSI averages shows that for low OCI (orographic complexity index) stations, satellite series have higher values than corresponding ground-based observations, whereas for high OCI stations, SSI values for satellite records are mainly lower than for ground stations. The comparison between SSI anomalies highlights that satellite records have an excellent performance in capturing SSI day-to-day variability of ground-based low OCI stations. In contrast, for high OCI stations, the agreement is much lower, due to the higher uncertainty in both satellite and ground-based records. Finally, if the temporal trends are considered, average low-elevation ground-based SSI observations show a positive trend, whereas satellite records do not highlight significant trends. Focusing on high-elevation stations, the observed trends for ground-based and satellite records are more similar with the only exception of summer. This divergence seems to be due to the relevant role of atmospheric aerosols on SSI trends. more
Atmosphere CM-SAF Climate Data Records Validation

Consistency and structural uncertainty of multi-mission GPS radio occultation records

Author(s):
Steiner, Andrea K.; Ladstädter, Florian; Ao, Chi O.; Gleisner, Hans; Ho, Shu-Peng; Hunt, Doug; Schmidt, Torsten; Foelsche, Ulrich; Kirchengast, Gottfried; Kuo, Ying-Hwa; Lauritsen, Kent B.; Mannucci, Anthony J.; Nielsen, Johannes K.; Schreiner, William; Schwärz, Marc; Sokolovskiy, Sergey; Syndergaard, Stig; Wickert, Jens
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 5
2020
DOI: 10.5194/amt-13-2547-2020
Abstract:
Abstract. Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GC… Abstract. Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GCOS). Radio occultation (RO) data based on Global Positioning System (GPS) signals are available since 2001 from several satellite missions with global coverage, high accuracy, and high vertical resolution in the troposphere and lower stratosphere. We assess the consistency and long-term stability of multi-satellite RO observations for use as climate data records. As a measure of long-term stability, we quantify the structural uncertainty of RO data products arising from different processing schemes. We analyze atmospheric variables from bending angle to temperature for four RO missions, CHAMP, Formosat-3/COSMIC, GRACE, and Metop, provided by five data centers. The comparisons are based on profile-to-profile differences aggregated to monthly medians. Structural uncertainty in trends is found to be lowest from 8 to 25 km of altitude globally for all inspected RO variables and missions. For temperature, it is more
Atmosphere Climate Data Records ROM-SAF Validation
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