scholarly journals Comparing climate change perceptions and meteorological data in rural West Africa to improve the understanding of household decisions to migrate

2020 ◽  
Author(s):  
Florence De Longueville ◽  
Pierre Ozer ◽  
François Gemenne ◽  
Sabine Henry ◽  
Ole Mertz ◽  
...  
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Meteorological Data ◽  
Change Perceptions ◽  
Household Decisions

Climate change and food security in tropical West Africa – a dynamic-statistical modelling approach

Erdkunde ◽  
2008 ◽  
Vol 62 (2) ◽  
pp. 101-115 ◽  
Author(s):  
Heiko Paeth ◽  
Arcade Capo-Chichi ◽  
Wilfried Endlicher
Keyword(s):  
Climate Change ◽  
Food Security ◽  
West Africa ◽  
Statistical Modelling ◽  
Modelling Approach

scholarly journals Climate Variability Since 1970 and Farmers’ Observations in Northern Ghana

2016 ◽  
Vol 5 (2) ◽  
pp. 41 ◽  
Author(s):  
Emmanuel Nyadzi
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Water Conservation ◽  
Crop Production ◽  
Meteorological Data ◽  
Northern Region ◽  
Northern Ghana ◽  
Climate Variability And Change ◽  
Urban Centers ◽  
Access To Credit

<p>The study examines how farmers’ observations of climate variability and change correspond with 42 years (1970-2011) meteorological data of temperature and rainfall. It shows how farmers in the Northern Region of Ghana adjust to the changing climate and explore the various obstacles that hinder the implementation of their adaptation strategies. With the help of an extension officer, 200 farmers from 20 communities were randomly selected based on their farming records. Temperatures over the last four decades (1970-2009) increased at a rate of 0.04 (± 0.41) ˚C and 0.3(± 0.13)˚C from 2010-2011 which is consistent to the farmers (82.5%) observations. Rainfall within the districts are characterised by inter-annual and monthly variability. It experienced an increased rate of 0.66 (± 8.30) mm from 1970-2009, which was inconsistent with the farmers (81.5%) observation. It however decreased from 2010-2011 at a huge rate of -22.49 (±15.90) mm which probably was the reason majority of the respondents claim rainfall was decreasing. Only 64.5% of the respondents had adjusted their farming activities because of climate variability and change. They apply fertilizers and pesticides, practice soil and water conservation, and irrigation for communities close to dams. Respondents desire to continue their current adaptation methods but may in the future consider changing crop variety, water-harvesting techniques, change crop production to livestock keeping, and possibly migrate to urban centers. Lack of climate change education, low access to credit and agricultural inputs are some militating factors crippling the farmers’ effort to adapt to climate change.</p>

scholarly journals Climate change impact on streamflow in a tropical basin of Ghana, West Africa

2021 ◽  
Vol 34 ◽  
pp. 100805
Author(s):  
Alfred Awotwi ◽  
Thompson Annor ◽  
Geophrey K. Anornu ◽  
Jonathan Arthur Quaye-Ballard ◽  
Jacob Agyekum ◽  
...  
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Climate Change Impact ◽  
Change Impact

Parameter transferability between multiple gridded input datasets challenges hydrological model performance under changing climate

2021 ◽  
Author(s):  
Moctar Dembélé ◽  
Bettina Schaefli ◽  
Grégoire Mariéthoz
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Model Performance ◽  
Hydrologic Model ◽  
Hydrological Modelling ◽  
Climate Change Scenarios ◽  
Depth Analysis ◽  
Input Dataset

&lt;p&gt;The diversity of remotely sensed or reanalysis-based rainfall data steadily increases, which on one hand opens new perspectives for large scale hydrological modelling in data scarce regions, but on the other hand poses challenging question regarding parameter identification and transferability under multiple input datasets. This study analyzes the variability of hydrological model performance when (1) a set of parameters is transferred from the calibration input dataset to a different meteorological datasets and reversely, when (2) an input dataset is used with a parameter set, originally calibrated for a different input dataset.&lt;/p&gt;&lt;p&gt;The research objective is to highlight the uncertainties related to input data and the limitations of hydrological model parameter transferability across input datasets. An ensemble of 17 rainfall datasets and 6 temperature datasets from satellite and reanalysis sources (Demb&amp;#233;l&amp;#233; et al., 2020), corresponding to 102 combinations of meteorological data, is used to force the fully distributed mesoscale Hydrologic Model (mHM). The mHM model is calibrated for each combination of meteorological datasets, thereby resulting in 102 calibrated parameter sets, which almost all give similar model performance. Each of the 102 parameter sets is used to run the mHM model with each of the 102 input datasets, yielding 10404 scenarios to that serve for the transferability tests. The experiment is carried out for a decade from 2003 to 2012 in the large and data-scarce Volta River basin (415600 km2) in West Africa.&lt;/p&gt;&lt;p&gt;The results show that there is a high variability in model performance for streamflow (mean CV=105%) when the parameters are transferred from the original input dataset to other input datasets (test 1 above). Moreover, the model performance is in general lower and can drop considerably when parameters obtained under all other input datasets are transferred to a selected input dataset (test 2 above). This underlines the need for model performance evaluation when different input datasets and parameter sets than those used during calibration are used to run a model. Our results represent a first step to tackle the question of parameter transferability to climate change scenarios. An in-depth analysis of the results at a later stage will shed light on which model parameterizations might be the main source of performance variability.&lt;/p&gt;&lt;p&gt;Demb&amp;#233;l&amp;#233;, M., Schaefli, B., van de Giesen, N., &amp; Mari&amp;#233;thoz, G. (2020). Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa. Hydrology and Earth System Sciences (HESS). https://doi.org/10.5194/hess-24-5379-2020&lt;/p&gt;

scholarly journals Effect of Global-GAP Policy on Climate Change Perceptions of Smallholder French Beans Farmers in Central and Eastern Regions, Kenya

Climate ◽  
2017 ◽  
Vol 5 (2) ◽  
pp. 27 ◽  
Author(s):  
Peter Otieno ◽  
Chris Ogutu ◽  
John Mburu ◽  
Rose Nyikal
Keyword(s):  
Climate Change ◽  
French Beans ◽  
Change Perceptions

scholarly journals Nature-based tourism operators’ perceptions and adaptation to climate change in Hwange National Park, Zimbabwe

2018 ◽  
Vol 42 (42) ◽  
pp. 115-127 ◽  
Author(s):  
William Mushawemhuka ◽  
Jayne M. Rogerson ◽  
Jarkko Saarinen
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
National Park ◽  
Empirical Studies ◽  
Tourism Industry ◽  
Adaptation To Climate Change ◽  
Economic Role ◽  
Change Perceptions ◽  
Hwange National Park ◽  
Adaptation Practices

Abstract Climate and weather are important resources for tourism. In particular, nature-based tourism activities and operations are largely dependent on and affected by environmental conditions and changes. Due to the significant socio-economic role of the nature-based tourism and the tourism industry, in general, in the region of southern Africa it is important to understand the dynamics between the industry and climate change. A key aspect of this understanding are perceptions and adaptation preparedness of tourism operators towards the estimated impact of climate change. There is a dearth of empirical studies on climate change perceptions and adaptation in nature-based tourism operations across southern Africa and specifically from Zimbabwe. This research gap is addressed in this article which provides an exploratory analysis of the nature of climate change adaptation practices occurring in southern Africa using evidence from Hwange National Park, Zimbabwe.

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

scholarly journals Simulation of future climate scenarios and the impact on the water availability in southern Brazil

2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Water Availability ◽  
Meteorological Data ◽  
Future Climate ◽  
Climate Scenarios ◽  
Southern Brazil ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
The Impact

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context

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