Contribution of the Sahel region to precipitation over the African continent

2021 ◽  
Author(s):  
Sofie te Wierik ◽  
Jessica Keune ◽  
Diego Miralles ◽  
Erik Cammeraat ◽  
Yael Artzy-Randrup ◽  
...  
Keyword(s):  
Forest Cover ◽  
Reanalysis Data ◽  
Congo Basin ◽  
Lagrangian Model ◽  
African Continent ◽  
Tropical Regions ◽  
Moisture Recycling ◽  
Precipitation Recycling ◽  
Interception Loss ◽  
Sahel Region

<p>Redistribution of evapotranspiration from land via atmospheric circulation is an important Earth system process. Globally, evapotranspiration contributes significantly to terrestrial rainfall, on both regional and more remote scales. In wet, tropical regions (e.g. the Congo basin), transpiration and interception loss from the dense forest cover are the primary drivers of moisture recycling, which plays a crucial role in preserving regional ecosystem functioning. However, for semi-arid and arid regions, our knowledge on the extent and significance of evapotranspiration for moisture recycling is still very limited, despite the significance this may have for addressing challenges of desertification in times of rapid environmental change. Considering this, we are taking the Sahel region as a case study and investigate its contribution to precipitation in the African continent. In addition, we specifically study what fraction of the precipitation originates from vegetation in the Sahel through transpiration and interception loss. Our study is based on simulated atmospheric moisture trajectories derived from the Lagrangian model FLEXPART with a 1-degree resolution, driven by ECMWF reanalysis data over 1980–2016. Preliminary results show (1) the temporal variability in the contribution of the region to precipitation in African drylands, and (2) a significant contribution of local precipitation recycling. We conclude that consideration of the naturally and anthropogenically-driven greening of the Sahel, as well as land use and land cover changes in the region, may have both local and far-reaching impacts via the transport of moisture through the atmosphere.</p>

scholarly journals High-resolution global atmospheric moisture connections from evaporation to precipitation

2020 ◽  
Author(s):  
Obbe A. Tuinenburg ◽  
Jolanda J. E. Theeuwen ◽  
Arie Staal
Keyword(s):  
Amazon Basin ◽  
Reanalysis Data ◽  
Congo Basin ◽  
Atmospheric Moisture ◽  
Moisture Recycling ◽  
Wind Speeds ◽  
Complete Dataset ◽  
Global Land ◽  
Land Recycling ◽  
Tracking Model

Abstract. A key Earth system process is the circulation of evaporated moisture through the atmosphere. Spatial connections between evaporation and precipitation affect the global and regional climates by redistributing water and latent heat. Through this atmospheric moisture recycling, land-cover changes influence regional precipitation patterns, with potentially far-reaching effects on human livelihoods and biome distributions across the globe. However, a globally complete dataset of atmospheric moisture flows from evaporation to precipitation has been lacking so far. Here we present a dataset of global atmospheric moisture recycling on both 0.5° and 1.0° spatial resolution. We simulated the moisture flows between each pair of cells across all land and oceans for 2008–2017 and present their monthly climatological means. We applied the Lagrangian moisture tracking model UTrack, which is forced with ERA5 reanalysis data on 25 atmospheric layers and hourly wind speeds and directions. Due to the global coverage of the simulations, a complete picture of both the upwind source areas of precipitation and downwind target areas of evaporation can be obtained. We show a number of statistics of global atmospheric moisture flows: land recycling, basin recycling, mean latitudinal and longitudinal flows, absolute latitudinal and longitudinal flows, and basin recycling for the 26 largest river basins. We find that, on average, 70 % of global land evaporation rains down over land, varying between 62 % and 74 % across the year; 51 % of global land precipitation has evaporated from land, varying between 36 % and 57 % across the year. Highest basin recycling occurs in the Amazon and Congo basins, with evaporation and precipitation recycling of 63 % and 36 % for the Amazon basin and 60 % and 47 % for the Congo basin. These statistics are examples of the potential usage of the dataset, which allows users to identify and quantify the moisture flows from and to any area on Earth, from local to global scales. The dataset is available at https://doi.pangaea.de/10.1594/PANGAEA.912710 (Tuinenburg et al., 2020).

scholarly journals High-resolution global atmospheric moisture connections from evaporation to precipitation

2020 ◽  
Vol 12 (4) ◽  
pp. 3177-3188
Author(s):  
Obbe A. Tuinenburg ◽  
Jolanda J. E. Theeuwen ◽  
Arie Staal
Keyword(s):  
Amazon Basin ◽  
Reanalysis Data ◽  
Congo Basin ◽  
Atmospheric Moisture ◽  
Moisture Recycling ◽  
Wind Speeds ◽  
Complete Dataset ◽  
Global Land ◽  
Land Recycling ◽  
Tracking Model

Abstract. A key Earth system process is the circulation of evaporated moisture through the atmosphere. Spatial connections between evaporation and precipitation affect the global and regional climates by redistributing water and latent heat. Through this atmospheric moisture recycling, land cover changes influence regional precipitation patterns, with potentially far-reaching effects on human livelihoods and biome distributions across the globe. However, a globally complete dataset of atmospheric moisture flows from evaporation to precipitation has been lacking so far. Here we present a dataset of global atmospheric moisture recycling on both 0.5∘ and 1.0∘ spatial resolution. We simulated the moisture flows between each pair of cells across all land and oceans for 2008–2017 and present their monthly climatological means. We applied the Lagrangian moisture tracking model UTrack, which is forced with ERA5 reanalysis data on 25 atmospheric layers and hourly wind speeds and directions. Due to the global coverage of the simulations, a complete picture of both the upwind source areas of precipitation and downwind target areas of evaporation can be obtained. We show a number of statistics of global atmospheric moisture flows: land recycling, basin recycling, mean latitudinal and longitudinal flows, absolute latitudinal and longitudinal flows, and basin recycling for the 26 largest river basins. We find that, on average, 70 % of global land evaporation rains down over land, varying between 62 % and 74 % across the year; 51 % of global land precipitation has evaporated from land, varying between 36 % and 57 % across the year. The highest basin recycling occurs in the Amazon and Congo basins, with evaporation and precipitation recycling of 63 % and 36 % for the Amazon basin and 60 % and 47 % for the Congo basin. These statistics are examples of the potential usage of the dataset, which allows users to identify and quantify the moisture flows from and to any area on Earth, from local to global scales. The dataset is available at https://doi.org/10.1594/PANGAEA.912710 (Tuinenburg et al., 2020).

scholarly journals Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Area ◽  
Tree Cover ◽  
Agricultural Crop ◽  
Forest Change ◽  
Alos Palsar ◽  
Tropical Regions ◽  
The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

scholarly journals State and evolution of the African rainforests between 1990 and 2010

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120300 ◽  
Author(s):  
Philippe Mayaux ◽  
Jean-François Pekel ◽  
Baudouin Desclée ◽  
François Donnay ◽  
Andrea Lupi ◽  
...  
Keyword(s):  
West Africa ◽  
Forest Cover ◽  
Central Africa ◽  
Congo Basin ◽  
Landsat Images ◽  
Deforestation Rate ◽  
Rural And Urban ◽  
Moderate Resolution ◽  
Underlying Causes ◽  
Moderate Resolution Imaging Spectroradiometer

This paper presents a map of Africa's rainforests for 2005. Derived from moderate resolution imaging spectroradiometer data at a spatial resolution of 250 m and with an overall accuracy of 84%, this map provides new levels of spatial and thematic detail. The map is accompanied by measurements of deforestation between 1990, 2000 and 2010 for West Africa, Central Africa and Madagascar derived from a systematic sample of Landsat images—imagery from equivalent platforms is used to fill gaps in the Landsat record. Net deforestation is estimated at 0.28% yr −1 for the period 1990–2000 and 0.14% yr −1 for the period 2000–2010. West Africa and Madagascar exhibit a much higher deforestation rate than the Congo Basin, for example, three times higher for West Africa and nine times higher for Madagascar. Analysis of variance over the Congo Basin is then used to show that expanding agriculture and increasing fuelwood demands are key drivers of deforestation in the region, whereas well-controlled timber exploitation programmes have little or no direct influence on forest-cover reduction at present. Rural and urban population concentrations and fluxes are also identified as strong underlying causes of deforestation in this study.

SECURITY DYNAMICS IN NORTH AFRICA AND SAHEL REGION IN THE FIRST HALF OF 2021

2021 ◽  
Vol 79 (2) ◽  
pp. 41-55
Author(s):  
Crăișor-Constantin IONIȚĂ
Keyword(s):  
North Africa ◽  
International Community ◽  
African Continent ◽  
Illegal Migration ◽  
Humanitarian Crisis ◽  
Regional Powers ◽  
Illegal Migrants ◽  
Sahel Region ◽  
Terrorist Acts

The first half of 2021 was marked by the continued spread of the Sars-CoV-2 virus throughout the African continent, by the desperate attempts of the UN and regional powers to implement the Ceasefire Agreement in Libya and keep security situation under control, and increasing the number of illegal migrants to Europe. The COVID-19 pandemic did not reduce terrorist acts in the Sahel region, nor did it stop the wave of small immigrant boats to Spain and Italy from Africa. But the coronavirus pandemic has led to the closure of many African borders, bringing the economies of those countries to the brink of bankruptcy and deteriorating the humanitarian situation in North Africa and the Sahel region. The international community has difficulty monitoring the situation in the area, especially the humanitarian crisis and illegal migration, which is seriously affecting security in its vicinity.

scholarly journals How robust are stratospheric age of air trends from different reanalyses?

2019 ◽  
Author(s):  
Felix Ploeger ◽  
Bernard Legras ◽  
Edward Charlesworth ◽  
Xiaolu Yan ◽  
Mohamadou Diallo ◽  
...  
Keyword(s):  
Climate Model ◽  
Decadal Variability ◽  
Reanalysis Data ◽  
Forced Response ◽  
Lagrangian Model ◽  
Current Generation ◽  
Transit Times ◽  
Age Variations ◽  
Dipole Pattern ◽  
Climate Model Simulations

Abstract. An accelerating Brewer-Dobson circulation (BDC) is a robust signal of climate change in model predictions but has been questioned by trace gas observations. We analyze stratospheric mean age of air and the full age spectrum as measures for the BDC and its trend. Age of air is calculated with the Chemical Lagrangian Model of the Stratosphere (CLaMS) driven by ERA-Interim, JRA-55 and MERRA-2 reanalysis data to assess the robustness of the representation of the BDC in current generation meteorological reanalyses. We find that climatological mean age significantly depends on the reanalysis, with JRA-55 showing the youngest and MERRA-2 the oldest mean age. Consideration of the age spectrum indicates that the older age for MERRA-2 is related to a stronger spectrum tail, likely related to weaker tropical upwelling and stronger recirculation. Seasonality of stratospheric transport is robustly represented in reanalyses, with similar mean age variations and age spectrum peaks. Long-term changes over 1989–2015 turn out to be similar for the reanalyses with mainly decreasing mean age accompanied by a shift of the age spectrum peak towards shorter transit times, resembling the forced response in climate model simulations to increasing greenhouse gas concentrations. For the shorter periods 1989–2001 and 2002–2015 age of air changes are less robust. Only ERA-Interim shows the hemispheric dipole pattern in age changes during 2002–2015 as viewed by recent satellite observations. Consequently, the representation of decadal variability of the BDC in current generation reanalyses appears less robust and a major uncertainty of modelling the BDC.

scholarly journals The national determinants of deforestation in sub-Saharan Africa

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120405 ◽  
Author(s):  
Thomas K. Rudel
Keyword(s):  
Forest Cover ◽  
Driving Forces ◽  
National Level ◽  
Congo Basin ◽  
Sub Saharan Africa ◽  
Small Scale ◽  
Urban Migration ◽  
Forest Cover Change ◽  
Level Data ◽  
Sub Saharan

For decades, the dynamics of tropical deforestation in sub-Saharan Africa (SSA) have defied easy explanation. The rates of deforestation have been lower than elsewhere in the tropics, and the driving forces evident in other places, government new land settlement schemes and industrialized agriculture, have largely been absent in SSA. The context and causes for African deforestation become clearer through an analysis of new, national-level data on forest cover change for SSA countries for the 2000–2005 period. The recent dynamic in SSA varies from dry to wet biomes. Deforestation occurred at faster rates in nations with predominantly dry forests. The wetter Congo basin countries had lower rates of deforestation, in part because tax receipts from oil and mineral industries in this region spurred rural to urban migration, declines in agriculture and increased imports of cereals from abroad. In this respect, the Congo basin countries may be experiencing an oil and mineral fuelled forest transition. Small farmers play a more important role in African deforestation than they do in southeast Asia and Latin America, in part because small-scale agriculture remains one of the few livelihoods open to rural peoples.

GLORIA observations of pollution tracers C2H6, C2H2, HCOOH, and PAN in the North Atlantic UTLS region

2020 ◽  
Author(s):  
Gerald Wetzel ◽  
Felix Friedl-Vallon ◽  
Norbert Glatthor ◽  
Jens-Uwe Grooß ◽  
Thomas Gulde ◽  
...  
Keyword(s):  
High Altitude ◽  
North Atlantic ◽  
Atmospheric Chemistry ◽  
Emission Spectra ◽  
Infrared Region ◽  
Reanalysis Data ◽  
Lagrangian Model ◽  
Back Trajectories ◽  
Source Regions ◽  
Research Aircraft

<p>The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an imaging Fourier transform spectrometer (iFTS) using a 2-dimensional detector array to record emission spectra in the mid-infrared region with high spatial resolution. GLORIA is operated on high altitude research aircraft, mainly in the limb observational geometry to measure vertical profiles of temperature and atmospheric trace species with high vertical resolution.</p><p>In autumn 2017, the Wave-driven ISentropic Exchange (WISE) aircraft campaign took place from Shannon (Ireland). Sixteen flights with the High Altitude and Long Range Research Aircraft (HALO) were performed between 31 August and 21 October 2017 over the eastern North Atlantic region.</p><p>GLORIA observations were analysed with regard to pollutant species like C<sub>2</sub>H<sub>6</sub>, C<sub>2</sub>H<sub>2</sub>, HCOOH, and PAN, which are produced at distinct source regions near the ground and transported to remote regions due to their atmospheric lifetime of several weeks. Enhanced volume mixing ratios of these molecules were detected along some parts of the flight track in the upper troposphere and lowermost stratosphere (UTLS).</p><p>Measured profiles of these species are compared to simulations from the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and reanalysis data from the Copernicus Atmosphere Monitoring Service (CAMS). Furthermore, emission tracers and back-trajectories from the Chemical Lagrangian Model of the Stratosphere (CLaMS) are used to analyse the source regions of these pollution events.</p>

scholarly journals A holistic framework to estimate the origins of atmospheric moisture and heat using a Lagrangian model

2021 ◽  
Author(s):  
Jessica Keune ◽  
Dominik L. Schumacher ◽  
Diego G. Miralles
Keyword(s):  
Bias Correction ◽  
Reanalysis Data ◽  
Lagrangian Model ◽  
Atmospheric Moisture ◽  
Lagrangian Models ◽  
Energy Conserving ◽  
Atmospheric Heat ◽  
Source And Sink ◽  
Different Climates ◽  
Source Receptor Relationships

Abstract. Despite the existing myriad of tools and models to assess atmospheric source–receptor relationships, their uncertainties remain largely unexplored and arguably stem from the scarcity of observations available for validation. Yet, Lagrangian models are increasingly used to determine the origin of precipitation and atmospheric heat, scrutinizing the changes in moisture and temperature along air parcel trajectories. Here, we present a holistic framework for the process-based evaluation of atmospheric trajectories to infer source–receptor relationships of both moisture and heat. The framework comprises three steps: (i) the diagnosis of moisture and heat from Lagrangian trajectories using multi-objective criteria to evaluate the accuracy and reliability of the fluxes, (ii) the attribution of sources following mass- and energy-conserving algorithms in order to establish source–receptor relationships, and (iii) the bias correction of diagnosed fluxes and the corresponding source–receptor relationships. Applying this framework to simulations from the Lagrangian model FLEXPART, driven with ERA-Interim reanalysis data, allows us to quantify the errors and uncertainties associated with the resulting source–receptor relationships for three cities in different climates (Beijing, Denver and Windhoek). Our results reveal large uncertainties inherent in the estimation of heat and precipitation origin with Lagrangian models, but they also demonstrate the synergistic impacts of source- and sink bias-corrections. The proposed framework paves the way for a cohesive assessment of the dependencies in source–receptor relationships.

scholarly journals Tracking the global flows of atmospheric moisture

2019 ◽  
Author(s):  
Obbe A. Tuinenburg ◽  
Arie Staal
Keyword(s):  
Vertical Mixing ◽  
Three Dimensional ◽  
Reanalysis Data ◽  
Point Sources ◽  
Atmospheric Moisture ◽  
Reanalysis Dataset ◽  
Considerable Uncertainty ◽  
Moisture Recycling ◽  
Trade Offs ◽  
Spatial Dimensions

Abstract. Many processes in hydrology and Earth system science relate to moisture recycling, the contribution of terrestrial evaporation to precipitation. For example, the effects of land-cover changes on regional rainfall regimes depend on this process. To study moisture recycling, a range of moisture tracking models are in use that are forced with output from atmospheric models, but differ in various ways. They can be Eulerian (grid-based) or Lagrangian (trajectory-based), have two or three spatial dimensions, and rely on a range of other assumptions. Which model is most suitable depends on the purpose of the study, but also on the quality and resolution of the data with which it is forced. Recently, the high-resolution ERA5 reanalysis dataset has become the state-of-the-art, paving the way for a new generation of moisture tracking models. However, it is unclear how the new data can best be used to obtain accurate estimates of atmospheric moisture flows. Here we develop a set of moisture tracking models forced with ERA5 data and systematically test their performance regarding continental evaporation recycling ratio, distances of moisture flows, and footprints of evaporation from seven point sources across the globe. We report simulation times to assess possible trade-offs between accuracy and speed. Three-dimensional Lagrangian models were most accurate and ran faster than Eulerian versions for tracking water from single grid cells. The rate of vertical mixing of moisture in the atmosphere was the greatest source of uncertainty in moisture tracking. We conclude that the recently improved resolution of atmospheric reanalysis data allows for more accurate moisture tracking results in a Lagrangian setting, but that considerable uncertainty regarding turbulent mixing remains. We present an efficient Lagrangian method to track atmospheric moisture flows from any location globally using ERA5 reanalysis data and make the code for this model publicly available.

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