Designing AfriCultuReS services to support food security in Africa

ABSTRACT: Earth observation (EO) data are increasingly being used to monitor vegetation and detect plant growth anomalies due to water stress, drought, or pests, as well as to monitor water availability, weather conditions, disaster risks, land use/land cover changes and to evaluate soil degradation. Satellite data are provided regularly by worldwide organizations, covering a wide variety of spatial, temporal and spectral characteristics. In addition, weather, climate and crop growth models provide early estimates of the expected weather and climatic patterns and yield, which can be improved by fusion with EO data. The AfriCultuReS project is capitalizing on the above to contribute towards an integrated agricultural monitoring and early warning system for Africa, supporting decision making in the field of food security. The aim of this article is to present the design of EO services within the project, and how they will support food security in Africa. The services designed cover the users' requirements related to climate, drought, land, livestock, crops, water, and weather. For each category of services, results from one case study are presented. The services will be distributed to the stakeholders and are expected to provide a continuous monitoring framework for early and accurate assessment of factors affecting food security in Africa.This paper is part of the AfriCultuReS project "Enhancing Food Security in African Agricultural Systems with the Support of Remote Sensing", which received funding from the European Union's Horizon 2020 Research and Innovation Framework Programme under grant agreement No. 77465

Investigating the representation of heatwaves from an ensemble of km-scale regional climate simulations within CORDEX-FPS convection

Heatwaves (HWs) are high-impact phenomena stressing both societies and ecosystems. Their intensity and frequency are expected to increase in a warmer climate over many regions of the world. While these impacts can be wide-ranging, they are potentially influenced by local to regional features such as topography, land cover, and urbanization. Here, we leverage recent advances in the very high-resolution modelling required to elucidate the impacts of heatwaves at these fine scales. Further, we aim to understand how the new generation of km-scale regional climate models (RCMs) modulates the representation of heatwaves over a well-known climate change hot spot. We analyze an ensemble of 15 convection-permitting regional climate model (CPRCM, ~ 2–4 km grid spacing) simulations and their driving, convection-parameterized regional climate model (RCM, ~ 12–15 km grid spacing) simulations from the CORDEX Flagship Pilot Study on Convection. The focus is on the evaluation experiments (2000–2009) and three subdomains with a range of climatic characteristics. During HWs, and generally in the summer season, CPRCMs exhibit warmer and drier conditions than their driving RCMs. Higher maximum temperatures arise due to an altered heat flux partitioning, with daily peaks up to ~ 150 W/m$^{2}$ larger latent heat in RCMs compared to the CPRCMs. This is driven by a 5–25% lower soil moisture content in the CPRCMs, which is in turn related to longer dry spell length (up to double). It is challenging to ascertain whether these differences represent an improvement. However, a point-scale distribution-based maximum temperature evaluation, suggests that this CPRCMs warmer/drier tendency is likely more realistic compared to the RCMs, with ~ 70% of reference sites indicating an added value compared to the driving RCMs, increasing to 95% when only the distribution right tail is considered. Conversely, a CPRCMs slight detrimental effect is found according to the upscaled grid-to-grid approach over flat areas. Certainly, CPRCMs enhance dry conditions, with knock-on implications for summer season temperature overestimation. Whether this improved physical representation of HWs also has implications for future changes is under investigation

Precipitation frequency in Med-CORDEX and EURO-CORDEX ensembles from 0.44° to convection-permitting resolution: impact of model resolution and convection representation

Recent studies using convection-permitting (CP) climate simulations have demonstrated a step-change in the representation of heavy rainfall and rainfall characteristics (frequency-intensity) compared to coarser resolution Global and Regional climate models. The goal of this study is to better understand what explains the weaker frequency of precipitation in the CP ensemble by assessing the triggering process of precipitation in the different ensembles of regional climate simulations available over Europe. We focus on the statistical relationship between tropospheric temperature, humidity and precipitation to understand how the frequency of precipitation over Europe and the Mediterranean is impacted by model resolution and the representation of convection (parameterized vs. explicit). We employ a multi-model data-set with three different resolutions (0.44°, 0.11° and 0.0275°) produced in the context of the MED-CORDEX, EURO-CORDEX and the CORDEX Flagship Pilot Study "Convective Phenomena over Europe and the Mediterranean" (FPSCONV). The multi-variate approach is applied to all model ensembles, and to several surface stations where the integrated water vapor (IWV) is derived from Global Positioning System (GPS) measurements. The results show that all model ensembles capture the temperature dependence of the critical value of IWV (IWVcv), above which an increase in precipitation frequency occurs, but the differences between the models in terms of the value of IWVcv, and the probability of its being exceeded, can be large at higher temperatures. The lower frequency of precipitation in convection-permitting simulations is not only explained by higher temperatures but also by a higher IWVcv necessary to trigger precipitation at similar temperatures, and a lower probability to exceed this critical value. The spread between models in simulating IWVcv and the probability of exceeding IWVcv is reduced over land in the ensemble of models with explicit convection, especially at high temperatures, when the convective fraction of total precipitation becomes more important and the influence of the representation of entrainment in models thus becomes more important. Over lowlands, both model resolution and convection representation affect precipitation triggering while over mountainous areas, resolution has the highest impact due to orography-induced triggering processes. Over the sea, since lifting is produced by large-scale convergence, the probability to exceed IWVcv does not depend on temperature, and the model resolution does not have a clear impact on the results

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution. Part I: Evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40 at 12 km to ∼ −3 at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales. © 2021, The Author(s)

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales

Managing the Intermittency of Wind Energy Generation in Greece

This paper performs a comprehensive analysis of the wind energy potential of onshore regions in Greece with emphasis on quantifying the volume risk and the spatial covariance structure. Optimization techniques are employed to derive efficient wind capacity allocation plans (also known as generation portfolios) incorporating different yield aspirations. The generation profile of minimum variance and other optimal portfolios along the efficient frontier are subject to rigorous evaluation using a fusion of descriptive and statistical methods. In particular, principal component analysis is employed to estimate factor models and investigate the spatiotemporal properties of wind power generation, providing valuable insights into the persistence of volume risk. The overarching goal of the study is to employ a set of statistical and mathematical programming tools guiding investors, aggregators and policy makers in their selection of wind energy generating assets. The findings of this research challenge the effectiveness of current policies and industry practices, offering a new perspective on wind energy harvesting with a focus on the management of volume risk

Sensitivity of a mediterranean tropical-like cyclone to physical parameterizations

The accurate prediction of Mediterranean tropical-like cyclones, or medicanes, is an important challenge for numerical weather prediction models due to their significant adverse impact on the environment, life, and property. The aim of this study is to investigate the sensitivity of an intense medicane, which formed south of Sicily on 7 November 2014, to the microphysical, cumulus, and boundary/surface layer schemes. The non-hydrostatic Weather Research and Forecasting model (version 3.7.1) is employed. A symmetric cyclone with a deep warm core, corresponding to a medicane, develops in all of the experiments, except for the one with the Thompson microphysics. There is a significant sensitivity of different aspects of the simulated medicane to the physical parameterizations. Its intensity is mainly influenced by the boundary/surface layer scheme, while its track is mainly influenced by the representation of cumulus convection, and its duration is mainly influenced by microphysical parameterization. The modification of the drag coefficient and the roughness lengths of heat and moisture seems to improve its intensity, track, and duration. The parameterization of shallow convection, with explicitly resolved deep convection, results in a weaker medicane with a shorter lifetime. An optimum combination of physical parameterizations in order to simulate all of the characteristics of the medicane does not seem to exist. © 2018 by the authors

Designing AfriCultuReS services to support food security in Africa

Earth Observation (EO) data are increasingly being used to monitor vegetation and detect plant growth anomalies due to water stress, drought, or pests, as well as to monitor water availability, weather conditions, disaster risks, land-use/land-cover changes and to evaluate soil degradation. Satellite data are provided regularly by worldwide organizations, covering a wide variety of spatial, temporal and spectral characteristics. In addition, climate and crop growth models provide early estimates of the expected weather patterns and yield, which can be improved by fusion with EO data. The project “AfriCultuReS” is capitalizing on the above to contribute towards an integrated agricultural monitoring and early warning system for Africa, supporting decision making in the field of food security. The aim of this paper is to present the design of EO services within the project, and how they will support food security in Africa. The designed services cover the users' requirements related to climate, drought, land, livestock, crops, water, and weather. For each category of services, results from one case study are presented. The services will be distributed to the stakeholders and are expected to provide a continuous monitoring framework for early and accurate assessment of factors affecting food security in Africa