Surface-based temperature inversions (SBIs) occur frequently over Antarctica and play an important role in climate and weather. Antarctic SBIs are exa…Surface-based temperature inversions (SBIs) occur frequently over Antarctica and play an important role in climate and weather. Antarctic SBIs are examined during the austral spring of 2010 using measurements from dropsondes, ERA-Interim Atmospheric Reanalysis Model, and the recently released version 6 of the Infrared Atmospheric Sounding Interferometer (IASI) level 2 product. A SBI detection algorithm is applied to temperature profiles from these data sets. The results will be used to determine if satellite and reanalysis products can accurately characterize SBIs, and if so, then they may be used to study SBIs outside of the spring 2010 study period. From the dropsonde data, SBIs occur in 20% of profiles over sea ice and 54% of profiles over land. IASI and ERA-Interim surface air temperatures are found to be significantly warmer than dropsonde observations at high plateau regions, while IASI surface air temperatures are colder over sea ice. IASI and ERA-Interim have a cold bias at nearly all levels above the surface when compared to the dropsonde. SBIs are characterized by their frequency, depth, and intensity. It is found that SBIs are more prevalent, deeper, and more intense over the continent than over sea ice, especially at higher surface elevations. Using IASI and ERA-Interim data the detection algorithm has a high probability of detection of SBIs but is found to severely overestimate the depth and underestimate the intensity for both data sets. These overestimation and underestimation are primarily due to the existence of extremely shallow inversion layers that neither satellite nor reanalysis products can resolve.more
A method for reducing the impact of noise in the 3.7 micron spectral channel in climate data records derived from coarse resolution (4 km) global meas…A method for reducing the impact of noise in the 3.7 micron spectral channel in climate data records derived from coarse resolution (4 km) global measurements from the Advanced Very High Resolution Radiometer (AVHRR) data is presented. A dynamic size-varying median filter is applied to measurements guided by measured noise levels and scene temperatures for individual AVHRR sensors on historic National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites in the period 1982–2001. The method was used in the preparation of the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data—Second Edition (CLARA-A2), a cloud climate data record produced by the EUMETSAT Satellite Application Facility for Climate Monitoring (CM SAF), as well as in the preparation of the corresponding AVHRR-based datasets produced by the European Space Agency (ESA) Climate Change Initiative (CCI) project ESA-CLOUD-CCI. The impact of the noise filter was equivalent to removing an artificial decreasing trend in global cloud cover of 1–2% per decade in the studied period, mainly explained by the very high noise levels experienced in data from the first satellites in the series (NOAA-7 and NOAA-9).more
The study evaluated the impact of climate change on incoming solar radiation (RSDS) in West Africa by comparing observed data from the CMSAF solar pro…The study evaluated the impact of climate change on incoming solar radiation (RSDS) in West Africa by comparing observed data from the CMSAF solar products (SARAH and CLARA-A1) for the period 1983–2019 with simulated data from the AFR-CORDEX models (RegCM-4.7 and CCCma-canRCM4) for the historical period (1983–2004) and various RCP emission scenarios (2.6, 4.5, 8.5) for 2005–2099. The values of the RCP in parentheses signify the level of increasing radiative forcings due to varying emission controls. Assessment metrics like correlation coefficient (R), Taylor Skill Score (TSS), and root mean square errors (RMSE) were employed for comparative analysis on annual and seasonal timescales. The analyses revealed annual mean RSDS intensities of 256.22 for SARAH, 238.53 for CLARA-A1, 270.81 for Historical, 270.26 for RCP 2.6, 255.90 for RCP 4.5, and 271.93 for the RCP 8.5 scenarios in watts per square metres. The TSS analyses showed average agreement values between observed CMSAF and simulated AFR-CORDEX solar radiation with values of 0.8450 and 0.8575 with historical, 0.8750 and 0.8600 with RCP 2.6, 0.9025 and 0.8550 with RCP 4.5, and 0.8675 and 0.8525 with RCP 8.5 scenarios for SARAH and CLARA-A1 respectively. All the metrics showed better agreement with SARAH than CLARA-A1, likely due to the associated cloud influence on CLARA-A1. Notably, the CORDEX-CCCma-canRCM4 model under RCP 4.5 demonstrated the highest accuracy, with an average correlation of 0.82 and a mean TSS of 0.90 against the SARAH reference dataset. The results suggest the AFR-CORDEX model, particularly the CCCma-canRCM4 for RCP 4.5 scenario, could reliably predict solar radiation and inform climate change impacts on solar energy potential in West Africa under moderate emission conditions.more
Soil moisture (SM) affects weather through its impact on surface flux partitioning, influencing vertical atmospheric profiles and circulations driven …Soil moisture (SM) affects weather through its impact on surface flux partitioning, influencing vertical atmospheric profiles and circulations driven by differential surface heating. In West Africa, observational studies point to a dominant negative SM-precipitation feedback, where dry soils help to initiate and maintain convection. In this context, serious concerns exist about the ability of models with parameterised convection to simulate this observed sensitivity of daytime convection to SM. Here, we evaluate the effect of initial SM perturbations in a short-range ensemble forecast over West Africa, comparing the UK Met Office Global and Regional Ensemble Prediction System (MOGREPS) with parameterised convection (GLOB-ENS) to its regional convection-permitting counterpart (CP-ENS). Results from both models suggest SM perturbations introduce considerable spread into daytime evaporative fraction (EF) and near-surface temperatures. This spread is still evident on Day 3 of the forecast. Both models also show a tendency to increased afternoon rainfall frequency over negative EF anomalies, reproducing the observed feedback. However, this effect is more pronounced in CP-ENS than GLOB-ENS, which illustrates the potential for process-based forecast improvements at convection-permitting scales. Finally, we identify persistent biases in rainfall caused by land cover mapping issues in the operational GLOB-ENS setup, emphasising the need for careful evaluation of different mapping strategies for land cover.more
Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operationa…Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operational numerical weather prediction models account for aerosol direct effects by using climatological mean concentrations and neglect indirect effects. This simplification may lead to shortcomings in model forecasts during outbreaks of Saharan dust towards Europe, when climatological mean dust concentrations deviate strongly from actual concentrations. This study investigates errors in model analyses and short-range forecasts during such events. We investigate a pronounced dust event in March 2021 using the pre-operational ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) with prognostic calculation of dust and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model, which deploys a dust climatology. We compare model analysis and forecast with measurements from satellite and in situ instruments. We find that inclusion of prognostic aerosol and direct radiative effects from dust improves forecasts of surface radiation during clear-sky conditions. However, dust-induced cirrus clouds are strongly underestimated, highlighting the importance of representing indirect effects adequately. These findings are corroborated by systematic quantification of forecast errors against satellite measurements. For this we construct an event catalogue with 49 dust days over Central Europe between January 2018 and March 2022. We classify model cells by simulated and observed cloudiness and simulated dustiness in the total atmospheric column. We find significant overestimations of brightness temperature for cases with dust compared with cases without dust. For surface shortwave radiation, we find median overestimations of 6.2% during cloudy conditions with dust optical depth greater than 0.1, however these are not significant compared with cloudy conditions without dust. Our findings show that the pre-operational ICON-ART and the operational IFS model still do not reproduce cloudiness adequately during events with Saharan dust over Central Europe. Missing implementations of prognostic dust, particularly of indirect effects on cloud formation, lead to significant underestimations of cloudiness and potentially overestimations of surface radiation.more
Multi-energy systems can improve the performance of traditional energy systems, where energy carriers and sectors are decoupled, in terms of economic,…Multi-energy systems can improve the performance of traditional energy systems, where energy carriers and sectors are decoupled, in terms of economic, environmental, and social sustainability, measured as the total cost of energy, emissions per energy demand, and self-sufficiency, respectively. This study assesses the impact that policy mechanisms can have in enabling these sustainability benefits. A mixed-integer linear problem is implemented, which optimizes the design and operation of multi-energy systems to minimize the total annual cost of supplying energy to residential end-users. Four policy types are tested for a Swiss case study, namely a feed-in tariff, an investment support mechanism, a carbon tax, and a regulation-based carbon cap. To assess how the policy impact varies between different end-users, we distinguish between passive consumers, that cannot access subsidies, and prosumers, who can. In our case study, subsidies, such as a feed-in tariff and an investment support mechanism, decrease the cost of energy for prosumers by up to 10%, but increase the cost for consumers by up to 33%, which points to the need of including energy equity considerations when designing policies. The carbon cap and the carbon tax impact all end-users equally, and tend to perform better in terms of reducing emissions. Emission reductions of up to 60% and 39% are observed for the carbon cap and carbon tax, respectively. The feed-in tariff and carbon cap perform best in fostering self-sufficiency and achieve balanced energy autonomy for high policy levels, revealing a trade-off between the different sustainability dimensions.more