Assessment of the global toxicity of marine sediments from the Dakar peninsula (Senegal, West Africa) - Amidou Sonko; Dalyal Copin; Patrice Brehmer; Cheikh Diop; Guillaume Constantin De Magny; Mamadou Fall; Yoba Kande; Patricia Moulin; Naby Souleymane Faye; Saliou Faye; Isabelle Linossier; Gaël Le Pennec (Environmental Monitoring and Assessment, 2023)

Land cover changes and their biogeophysical effects on climate - Rezaul Mahmood; Roger A. Pielke; Kenneth G. Hubbard; Dev Niyogi; Paul A. Dirmeyer; Clive McAlpine; Andrew M. Carleton; Robert Hale; Samuel Gameda; Adriana Beltrán‐Przekurat; Bruce Baker; Richard McNider; et al. (International Journal of Climatology, 2014)
Land cover changes ( LCCs ) play an important role in the climate system. Research over recent decades highlights the impacts of these changes on atmospheric temperature, humidity, cloud cover, circulation, and precipitation. These impacts range from the local‐ and regional‐scale to sub‐continental and global‐scale. It has been found that the impacts of regional‐scale LCC in one area may also be manifested in other parts of the world as a climatic teleconnection. In light of these findings, this article provides an overview and synthesis of some of the most notable types of LCC and their impacts on climate. These LCC types include agriculture, deforestation and afforestation, desertification, and urbanization. In addition, this article provides a discussion on challenges to, and future research directions in, assessing the climatic impacts of LCC .

Temperature and equivalent temperature over the United States (1979–2005) - Souleymane Fall; Noah S. Diffenbaugh; Dev Niyogi; Roger A. Pielke; Gilbert Rochon (International Journal of Climatology, 2010)
Temperature ( T ) and equivalent temperature ( T E ) trends over the United States from 1979 to 2005 and their correlation to land cover types are investigated using National Centers for Environmental Prediction North American Regional Reanalysis data, the Advanced Very High Resolution Radiometer (AVHRR) land use/cover classification, the National Land Cover Database (NLCD) 1992–2001 Retrofit Land Cover Change and the Normalised Difference Vegetation Index (NDVI) derived from AVHRR. Even though most of the magnitude of T E is explained by T , the moisture component induces larger trends and variability of T E relative to T . The contrast between pronounced temporal and spatial differences between T and T E at the near‐surface level (2 m) and minor‐to‐no differences at 300–200 mb is a consistent pattern. This study therefore demonstrates that in addition to temperature, atmospheric heat content may help to quantify the differences between surface and tropospheric heating trends, and hence the impact of land cover types on the surface temperature changes. Correlations of T and T E with NDVI reveal that T E shows a stronger relationship to vegetation cover than T , especially during the growing season, with values that are significantly different and of opposite signs (−0.31 for T vs NDVI; 0.49 for T E vs NDVI). Our results suggest that land cover types influence both moisture availability and temperature in the lower atmosphere and that T E is larger in areas with higher physical evaporation and transpiration rates. As a result, T E can be used as an additional metric for analysing near‐surface heating trends with respect to land cover types. Moreover, T E can be tested as a complementary variable for assessing the impact of land surface and boundary layer processes in re‐analysis and weather/climate model studies. Copyright © 2010 Royal Meteorological Society

Impacts of land use land cover on temperature trends over the continental United States: assessment using the North American Regional Reanalysis - Souleymane Fall; Dev Niyogi; Alexander Gluhovsky; Roger A. Pielke; Eugenia Kalnay; Gilbert Rochon (International Journal of Climatology, 2010)
We investigate the sensitivity of surface temperature trends to land use land cover change (LULC) over the conterminous United States (CONUS) using the observation minus reanalysis (OMR) approach. We estimated the OMR trends for the 1979–2003 period from the US Historical Climate Network (USHCN), and the NCEP‐NCAR North American Regional Reanalysis (NARR). We used a new mean square differences (MSDs)‐based assessment for the comparisons between temperature anomalies from observations and interpolated reanalysis data. Trends of monthly mean temperature anomalies show a strong agreement, especially between adjusted USHCN and NARR ( r = 0.9 on average) and demonstrate that NARR captures the climate variability at different time scales. OMR trend results suggest that, unlike findings from studies based on the global reanalysis (NCEP/NCAR reanalysis), NARR often has a larger warming trend than adjusted observations (on average, 0.28 and 0.27 °C/decade respectively). OMR trends were found to be sensitive to land cover types. We analysed decadal OMR trends as a function of land types using the Advanced Very High Resolution Radiometer (AVHRR) and new National Land Cover Database (NLCD) 1992–2001 Retrofit Land Cover Change. The magnitude of OMR trends obtained from the NLDC is larger than the one derived from the ‘static’ AVHRR. Moreover, land use conversion often results in more warming than cooling. Overall, our results confirm the robustness of the OMR method for detecting non‐climatic changes at the station level, evaluating the impacts of adjustments performed on raw observations, and most importantly, providing a quantitative estimate of additional warming trends associated with LULC changes at local and regional scales. As most of the warming trends that we identify can be explained on the basis of LULC changes, we suggest that in addition to considering the greenhouse gases–driven radiative forcings, multi‐decadal and longer climate models simulations must further include LULC changes. Copyright © 2009 Royal Meteorological Society

Best management practices for corporate, academic and governmental transfer of sustainable technologies to developing countries - Gilbert L. Rochon; Dev Niyogi; Souleymane Fall; Joseph E. Quansah; Larry Biehl; Bereket Araya; Chetan Maringanti; Angel Torres Valcarcel; Lova Rakotomalala; Hildred S. Rochon; Bertin Hilaire Mbongo; Thierno Thiam (Clean Technologies and Environmental Policy, 2010)

A Simple Reclassification Method for Correcting Uncertainty in Land Use/Land Cover Data Sets Used with Land Surface Models - Joseph G. Alfieri; Dev Niyogi; Margaret A. LeMone; Fei Chen; Souleymane Fall (Pure and Applied Geophysics, 2007)

Application of weather prediction models for hazard mitigation planning: a case study of heavy off-season rains in Senegal - Souleymane Fall; Dev Niyogi; U. C. Mohanty; Anil Kumar (Natural Hazards, 2007)

The spatiotemporal climate variability over Senegal and its relationship to global climate - Souleymane Fall; Fredrick H. M. Semazzi; Dev Dutta S. Niyogi; Richard O. Anyah; Jared Bowden (International Journal of Climatology, 2006)
Climate variability over Senegal (West Africa) and its relationship to global climate are examined for the period 1979–1998. Monthly observed rainfall for 20 stations and monthly CPC merged analysis precipitation (CMAP) over Senegal were averaged for the months of June, July, August, and September in order to generate seasonal rainfall totals for the wet season, as well as climate indices averaged over the study period. The spatial distribution patterns are mapped and analyzed using ArcGIS Spatial Analyst. Rainfall distribution over Senegal is dominated by a N–S gradient. To investigate the climate variability over Senegal, an empirical orthogonal function (EOF) analysis is performed for the 1979–1998 period, using rain‐gauge and CMAP rainfall data over Senegal, and CMAP data only for West Africa. The first West African mode agrees strongly with Lamb's rainfall index. One of our major findings is that EOF2 for West Africa is well correlated with EOF1 for rainfall in Senegal. This relationship is supported by the projection of winds on the EOF2 mode by the National Centers for Environmental Prediction (NCEP), as well as the grid‐point correlation between the time series of EOF2 over West Africa and the Atlantic sea‐surface temperature (SST). The typical circulation associated with positive anomalies over Senegal is a moisture convergence, which takes place over the Guinea Gulf, in conjunction with the warm waters in this area. The time series for rainfall over Senegal show positive correlations with the South Atlantic SST. Over the Pacific Ocean, the greatest correlation coefficients (up to −0.72) are observed during the April–July period, which provide a modest possibility of predicting Senegal's rainy season. Given the specificity of coastal West Africa, the traditional indices used by policy makers and end users for the whole Sahel–Sudan region will not work for Senegal. The CMAP data are robust and suitable for analyses over West Africa. On the basis of its reliability, CMAP data has proven to be a good validation for analyses based on rain‐gauge precipitation. Copyright © 2006 Royal Meteorological Society