The "Global Aridity Index and Potential Evapotranspiration Database - Version 3" (Global-AI_PET_v3) provides high-resolution (30 arc-seconds) global hydro-climatic data averaged (1970-2000) monthly and yearly, based upon the FAO Penman-Monteith Reference Evapotranspiration (ET0) equation. An overview of the methods used to implement the Penman-Monteith equation geospatially and a technical evaluation of the results is provided. Results were compared for technical validation with weather station data from the FAO "CLIMWAT 2.0 for CROPWAT" (ET0: r2 = 0.85; AI: r2 = 0.90) and the U.K. "Climate Research Unit: Time Series v 4.04" (ET0: r2 = 0.89; AI: r2 = 0.83), while showing significant differences to an earlier version of the database. The current version of the Global-AI_PET_v3 supersedes previous versions, showing a higher correlation to real world weather station data. Developed using the generally agreed upon standard methodology for estimation of reference ET0, this database and notably, the accompanying source code, provide a robust tool for a variety of scientific applications in an era of rapidly changing climatic conditions. 

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Version 3 of the Global Aridity Index and Potential Evapotranspiration Database

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Abstract Two regional climate models (RCMs) participating in the CORDEX–Coordinated Output for Regional Evaluations (CORDEX-CORE) project feature a dipole-type rainfall bias during March–May (MAM) and September–November (SON) over central equatorial Africa (CEA), consisting of positive bias in west central equatorial Africa (WCEA) and negative bias in east central equatorial Africa (ECEA). One is the Regional Model version 2015 (REMO2015) and the other is the fourth version of the Regional Climate Model (RegCM4-v7). RCMs are nested in three Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5), and in the reanalysis ERA-Interim, at ∼25-km spacing grid resolution. This study highlights misrepresented underlying physical processes associated with these rainfall biases through a process-based evaluation. Both RCMs produce a weaker Congo basin cell, associated with a weaker land–ocean zonal surface pressure gradient. Consequently, less water vapor enters the region, and little is transported from WCEA to ECEA, resulting in higher moisture availability in the west than in the east. This leads to an unevenly distributed moisture across the region, favoring a stronger atmospheric instability in WCEA where the moist static energy (MSE) anomalously increases through an enhanced latent static energy (LSE). Moisture arrives at a slower pace in ECEA, associated with the weak cell’s strength. The intensity of ascent motions in response to the orographic constraint is weak to destabilize atmospheric stability in the lower layers, necessary for initiating deep convection. Therefore, the convection is shallow in ECEA related to underestimating the MSE due to the reduced LSE. 

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Mechanisms of Rainfall Biases in Two CORDEX-CORE Regional Climate Models at Rainfall Peaks over Central Equatorial Africa

CO2 emission from soil in silage maize irrigated with wastewater under deficit irrigation in direct sowing practice

Detection and projection of climatic comfort changes in China mainland in a warming world

The community land model version 4.5 provides two ways for treating the vegetation cover changes (a static versus an interactive) and two runoff schemes for tracking the soil moisture changes. In this study, we examined the sensitivity of the simulated boreal summer potential evapotranspiration (PET) to the aforementioned options using a regional climate model. Three different experiments with each one covering 16 years have been performed. The two runoff schemes were designated as SIMTOP (TOP) and variable infiltration capacity (VIC). Both runoff schemes were coupled to the carbon–nitrogen (CN) module, thus the vegetation status can be influenced by soil moisture changes. Results show that vegetation cover changes alone affect considerably the simulated 2-m mean air temperature (T2M). However, they do not affect the global incident solar radiation (RSDS) and PET. Conversely to the vegetation cover changes alone, the vegetation-runoff systems affect both the T2M and RSDS. Therefore, they considerably affect the simulated PET. Also, the CN-VIC overestimates the PET more than the CN-TOP compared to the Climatic Research Unit observational dataset. In comparison with the static vegetation case and CN-VIC, the CN-TOP shows the least bias of the simulated PET. Overall, our results show that the vegetation-runoff system is relevant in constraining the PET, though the CN-TOP can be recommended for future studies concerning the PET of tropical Africa.

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On the Influence of Vegetation Cover Changes and Vegetation-Runoff Systems on the Simulated Summer Potential Evapotranspiration of Tropical Africa Using RegCM4

Potential impact of 1.5, 2 and 3 °C global warming levels on heat and discomfort indices changes over Central Africa

Shoreline changes have been a major environmental concern to coastal geomorphologists, engineers’ as well coastal ecologists as a result increased alteration in the ecological system of many coasts of the world. It is causing major coastal structure damage and requires harbour dredging. The current study aimed at integrating remote sensing, geographical information system, and statistical methods to monitor and quantify spatio-temporal shoreline dynamics along Ilaje Local Government, Ondo State, Nigeria over 31 years (1986–2017). Four multi-temporal and spectral Landsat satellite images were used to examine the shoreline changes for a long-term period (1986–2017), besides three short-term time intervals. Images were classified using supervised classification to map the land use land cover changes in the study area. Integrating the Digital Shoreline Analysis System version 4.3 tool within ArcGIS facilitated the quantification of shoreline changes via the End-Point Rate and Net Shoreline Movement statistical techniques. The study revealed a coastal length of about 80 km with both accretion and erosion processes actively shown along the coastline. About 40 km of the coastline was found to be accreting with an average of + 1.08 m/year followed by 35.4 km of coastal erosion with an average of − 1.40 m/year and 4.6 km of the coast more or less appears stable. The overall shoreline changes fall within high accretion (> + 1 to ≤  + 2) to high erosion (< − 1 to ≥ - 2) of shoreline classification. The results show significant erosion, which could impact high economic, social, and environmental costs. The study provides baseline information on shoreline dynamism in the coastline areas of Ilaje Ondo State which will serve as a veritable data for the sustainable control of coastal erosion in the study area and other shoreline with similar characteristics.

Spatio-temporal Analysis of Shoreline Positional Change of Ondo State Coastline Using Remote Sensing and GIS: A Case Study of Ilaje Coastline at Ondo State in Nigeria

Ismaila Diallo

Papers

On the Influence of Vegetation Cover Changes and Vegetation-Runoff Systems on the Simulated Summer Potential Evapotranspiration of Tropical Africa Using RegCM4

Potential impact of 1.5, 2 and 3 °C global warming levels on heat and discomfort indices changes over Central Africa

Spatio-temporal Analysis of Shoreline Positional Change of Ondo State Coastline Using Remote Sensing and GIS: A Case Study of Ilaje Coastline at Ondo State in Nigeria

Atmospheric water budget over the West African monsoon region in a regional climate model: The sensitivity of different lateral boundary conditions