Climate trends in a specific Mediterranean viticultural area between 1950 and 2006

Aims: An analysis of climate data between 1950 and 2006 in the Hérault department, situated in the Mediterranean of France is presented.Methods and results: Data presented include the evolution of mean annual and seasonal temperatures, the Huglin index, total solar radiation, night freshness index, the distribution and efficiency of rainfall and potential evapotranspiration (pET). Results showed an increase in mean annual temperatures of +1.3 °C between 1980 and 2006 and an increase in the mean pET which was 900 mm / year since 1999. Also, harvest dates advanced by up to three weeks and sugar concentrations at harvest increased by up to 1.5 % potential alcohol.Conclusion: The indicators show that in this area certain climatic parameters have evolved over the period studied. Changes are observable in some of the parameters (notably temperature) for the last 30 years whereas others have evolved only in the past few years (e.g. pET). Therefore it is necessary to be circumspect in drawing conclusions on climate change in the area, particularly as regards the possible consequences for viticulture. However, at the plot level, it is clear that irrigation of the vines is becoming increasingly necessary in this region.Significance and impact of study: Climate is a major factor in vine cultivation and in the understanding of viticultural terroirs and wine typicality. The climate trends observed over a 50-year period are discussed in the viticultural context of a Mediterranean region. However, the interaction between climate change and technical progress in viticulture and oenology complicate the analysis over the time frame under consideration.

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Climate Change Patterns of Wild Blueberry Fields in Downeast, Maine over the Past 40 Years

Water ◽

10.3390/w13050594 ◽

2021 ◽

Vol 13 (5) ◽

pp. 594

Author(s):

Rafa Tasnim ◽

Francis Drummond ◽

Yong-Jiang Zhang

Keyword(s):

Climate Change ◽

Vegetation Index ◽

Potential Evapotranspiration ◽

Growing Season ◽

Spatial Average ◽

Climate Variables ◽

Threshold Values ◽

The Past ◽

Wild Blueberry ◽

Crop Health

Maine, USA is the largest producer of wild blueberries (Vaccinium angustifolium Aiton), an important native North American fruit crop. Blueberry fields are mainly distributed in coastal glacial outwash plains which might not experience the same climate change patterns as the whole region. It is important to analyze the climate change patterns of wild blueberry fields and determine how they affect crop health so fields can be managed more efficiently under climate change. Trends in the maximum (Tmax), minimum (Tmin) and average (Tavg) temperatures, total precipitation (Ptotal), and potential evapotranspiration (PET) were evaluated for 26 wild blueberry fields in Downeast Maine during the growing season (May–September) over the past 40 years. The effects of these climate variables on the Maximum Enhanced Vegetation Index (EVImax) were evaluated using Remote Sensing products and Geographic Information System (GIS) tools. We found differences in the increase in growing season Tmax, Tmin, Tavg, and Ptotal between those fields and the overall spatial average for the region (state of Maine), as well as among the blueberry fields. The maximum, minimum, and average temperatures of the studied 26 wild blueberry fields in Downeast, Maine showed higher rates of increase than those of the entire region during the last 40 years. Fields closer to the coast showed higher rates of warming compared with the fields more distant from the coast. Consequently, PET has been also increasing in wild blueberry fields, with those at higher elevations showing lower increasing rates. Optimum climatic conditions (threshold values) during the growing season were explored based on observed significant quadratic relationships between the climate variables (Tmax and Ptotal), PET, and EVImax for those fields. An optimum Tmax and PET for EVImax at 22.4 °C and 145 mm/month suggest potential negative effects of further warming and increasing PET on crop health and productivity. These climate change patterns and associated physiological relationships, as well as threshold values, could provide important information for the planning and development of optimal management techniques for wild blueberry fields experiencing climate change.

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Comparing precipitation and temperature trends between inland and coastal locations

ANZIAM Journal ◽

10.21914/anziamj.v60i0.13967 ◽

2019 ◽

Vol 60 ◽

pp. C109-C126 ◽

Cited By ~ 1

Author(s):

Joshua Hartigan ◽

Shev MacNamara ◽

Lance M Leslie

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Southern Oscillation ◽

Power Spectra ◽

Maximum Temperature ◽

P Value ◽

Wet Season ◽

Intergovernmental Panel ◽

The Past ◽

The Mean

Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature. References R. A., R. L. Kitching, F. Chiew, L. Hughes, P. C. D. Newton, S. S. Schuster, A. Tait, and P. Whetton. Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of Working Group II to the Fifth Assessment of the Intergovernmental Panel on Climate Change. Technical report, Intergovernmental Panel on Climate Change, 2014. URL https://www.ipcc.ch/report/ar5/wg2/. Bureau of Meteorology. Climate Glossary-Drought. URL http://www.bom.gov.au/climate/glossary/drought.shtml. K. M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. B. Am. Meteorol. Soc., 76:23912402, 1995. doi:10.1175/1520-0477(1995)0762391:CSDUWT>2.0.CO;2. M. B. Richman and L. M. Leslie. Uniqueness and causes of the California drought. Procedia Comput. Sci., 61:428435, 2015. doi:10.1016/j.procs.2015.09.181. M. B. Richman and L. M. Leslie. The 20152017 Cape Town drought: Attribution and prediction using machine learning. Procedia Comput. Sci., 140:248257, 2018. doi:10.1016/j.procs.2018.10.323.

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Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades

Remote Sensing ◽

10.3390/rs13204063 ◽

2021 ◽

Vol 13 (20) ◽

pp. 4063

Author(s):

Jie Xue ◽

Yanyu Wang ◽

Hongfen Teng ◽

Nan Wang ◽

Danlu Li ◽

...

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Dynamic Change ◽

Google Earth ◽

Arid Areas ◽

Climate Data ◽

Northern Margin ◽

The Past

Climate change has proven to have a profound impact on the growth of vegetation from various points of view. Understanding how vegetation changes and its response to climatic shift is of vital importance for describing their mutual relationships and projecting future land–climate interactions. Arid areas are considered to be regions that respond most strongly to climate change. Xinjiang, as a typical dryland in China, has received great attention lately for its unique ecological environment. However, comprehensive studies examining vegetation change and its driving factors across Xinjiang are rare. Here, we used the remote sensing datasets (MOD13A2 and TerraClimate) and data of meteorological stations to investigate the trends in the dynamic change in the Normalized Difference Vegetation Index (NDVI) and its response to climate change from 2000 to 2019 across Xinjiang based on the Google Earth platform. We found that the increment rates of growth-season mean and maximum NDVI were 0.0011 per year and 0.0013 per year, respectively, by averaging all of the pixels from the region. The results also showed that, compared with other land use types, cropland had the fastest greening rate, which was mainly distributed among the northern Tianshan Mountains and Southern Junggar Basin and the northern margin of the Tarim Basin. The vegetation browning areas primarily spread over the Ili River Valley where most grasslands were distributed. Moreover, there was a trend of warming and wetting across Xinjiang over the past 20 years; this was determined by analyzing the climate data. Through correlation analysis, we found that the contribution of precipitation to NDVI (R2 = 0.48) was greater than that of temperature to NDVI (R2 = 0.42) throughout Xinjiang. The Standardized Precipitation and Evapotranspiration Index (SPEI) was also computed to better investigate the correlation between climate change and vegetation growth in arid areas. Our results could improve the local management of dryland ecosystems and provide insights into the complex interaction between vegetation and climate change.

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Where the wild things are: Seasonal variation in caribou distribution in relation to climate change

Rangifer ◽

10.7557/2.25.4.1770 ◽

2005 ◽

Vol 25 (4) ◽

pp. 51 ◽

Cited By ~ 10

Author(s):

Philippa McNeil ◽

Don E. Russell ◽

Brad Griffith ◽

Anne Gunn ◽

Gary P. Kofinas

Keyword(s):

Climate Change ◽

Environmental Factor ◽

Rangifer Tarandus ◽

Early Summer ◽

Climatic Conditions ◽

Mitigation Measures ◽

Climate Data ◽

Climate Trends ◽

Migration Patterns ◽

Mining Sites

In this study, we develop a method to analyse the relationships between seasonal caribou distribution and climate, to estimate how climatic conditions affect interactions between humans and caribou, and ultimately to predict patterns of distribution relative to climate change. Satellite locations for the Porcupine (Rangifer tarandus granti) and Bathurst (R. t. groenlandicus) caribou herds were analysed for eight ecologically-defined seasons. For each season, two levels of a key environmental factor influencing caribou distribution were identified, as well as the best climate data available to indicate the factor's annual state. Satellite locations were grouped according to the relevant combination of season and environmental factor. Caribou distributions were compared for opposing environmental factors; this comparison was undertaken relative to hunting access for the Porcupine Herd and relative to exposure to mining activity for the Bathurst Herd. Expected climate trends suggest an overall increase in access to Porcupine caribou for Aklavik (NWT) hunters during the winter and rut seasons, for Venetie (Alaska) hunters during midsummer and fall migration and for Arctic Village (Alaska) during midsummer. Arctic Village may experience reduced availability with early snowfalls in the fall, but we expect there to be little directional shift in the spring migration patterns. For the Bathurst Herd, we expect that fewer caribou would be exposed to the mines during the winter, while more caribou would be exposed to the combined Ekati and Diavik mining zone in the early summer and to the Lupin-Jericho mining zone during the fall migration. If changes in climate cause an increased presence of caribou in the mining sites, monitoring and mitigation measures may need to be intensified.

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Relationship between seborrheic dermatitis and climate change: observational study (Preprint)

10.2196/preprints.17627 ◽

2019 ◽

Author(s):

Ömer Kutlu

Keyword(s):

Climate Change ◽

Seborrheic Dermatitis ◽

Winter Season ◽

Central Anatolia ◽

High Humidity ◽

Climate Data ◽

Uv Index ◽

Exact Etiology ◽

The Mean ◽

Health Registry

BACKGROUND The exact etiology of seborrheic dermatitis remains unclear and climate change is considered one of the possible triggering factors. OBJECTIVE The aim of this study was to investigate the correlation between seborrheic dermatitis and climate data including humidity, temperature, rainfall, atmospheric pressure, cloud, and UV index. METHODS The data were collected retrospectively from electronic health registry systems in Develi in the Central Anatolia region of Turkey, between August 2018- July 2019. The monthly seborrheic dermatitis incidence was calculated. Climate data for the relevant period were obtained. The correlation between seborrheic dermatitis incidence and climate data were analyzed. RESULTS The study included a total of 21588 patients applied to the Dermatology outpatient clinic. Seborrhoeic dermatitis was identified in 996 patients (4.61%). The mean age of the patients was 30.2±20.2 years. The seborrheic dermatitis incidence rate was highest in winter season (5.02%). There was a statistically significant positive correlation between high humidity (%), cloud (%) and seborrheic dermatitis incidence, while a negative correlation was between high temperature (°C) and seborrheic dermatitis incidence.(p<0.001, p=0.028, p=0.024, respectively) CONCLUSIONS Environmental factors such as high humidity, high cloud rate, and low temperature are important in the emergence of seborrheic dermatitis.

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Climate effects on vegetation vitality at the treeline of boreal forests of Mongolia

Biogeosciences ◽

10.5194/bg-15-1319-2018 ◽

2018 ◽

Vol 15 (5) ◽

pp. 1319-1333 ◽

Cited By ~ 7

Author(s):

Michael Klinge ◽

Choimaa Dulamsuren ◽

Stefan Erasmi ◽

Dirk Nikolaus Karger ◽

Markus Hauck

Keyword(s):

Climate Change ◽

Boreal Forest ◽

Human Impact ◽

Forest Type ◽

Forest Steppe ◽

Paleoenvironmental Reconstruction ◽

Climate Data ◽

Southern Boundary ◽

The Mean ◽

Limiting Parameters

Abstract. In northern Mongolia, at the southern boundary of the Siberian boreal forest belt, the distribution of steppe and forest is generally linked to climate and topography, making this region highly sensitive to climate change and human impact. Detailed investigations on the limiting parameters of forest and steppe in different biomes provide necessary information for paleoenvironmental reconstruction and prognosis of potential landscape change. In this study, remote sensing data and gridded climate data were analyzed in order to identify main distribution patterns of forest and steppe in Mongolia and to detect environmental factors driving forest development. Forest distribution and vegetation vitality derived from the normalized differentiated vegetation index (NDVI) were investigated for the three types of boreal forest present in Mongolia (taiga, subtaiga and forest–steppe), which cover a total area of 73 818 km2. In addition to the forest type areas, the analysis focused on subunits of forest and nonforested areas at the upper and lower treeline, which represent ecological borders between vegetation types. Climate and NDVI data were analyzed for a reference period of 15 years from 1999 to 2013. The presented approach for treeline delineation by identifying representative sites mostly bridges local forest disturbances like fire or tree cutting. Moreover, this procedure provides a valuable tool to distinguish the potential forested area. The upper treeline generally rises from 1800 m above sea level (a.s.l.) in the northeast to 2700 m a.s.l. in the south. The lower treeline locally emerges at 1000 m a.s.l. in the northern taiga and rises southward to 2500 m a.s.l. The latitudinal gradient of both treelines turns into a longitudinal one on the eastern flank of mountain ranges due to higher aridity caused by rain-shadow effects. Less productive trees in terms of NDVI were identified at both the upper and lower treeline in relation to the respective total boreal forest type area. The mean growing season temperature (MGST) of 7.9–8.9 ∘C and a minimum MGST of 6 ∘C are limiting parameters at the upper treeline but are negligible for the lower treeline. The minimum of the mean annual precipitation (MAP) of 230–290 mm yr−1 is a limiting parameter at the lower treeline but also at the upper treeline in the forest–steppe ecotone. In general, NDVI and MAP are lower in grassland, and MGST is higher compared to the corresponding boreal forest. One exception occurs at the upper treeline of the subtaiga and taiga, where the alpine vegetation consists of mountain meadow mixed with shrubs. The relation between NDVI and climate data corroborates that more precipitation and higher temperatures generally lead to higher greenness in all ecological subunits. MGST is positively correlated with MAP of the total area of forest–steppe, but this correlation turns negative in the taiga. The limiting factor in the forest–steppe is the relative humidity and in the taiga it is the snow cover distribution. The subtaiga represents an ecological transition zone of approximately 300 mm yr−1 precipitation, which occurs independently from the MGST. Since the treelines are mainly determined by climatic parameters, the rapid climate change in inner Asia will lead to a spatial relocation of tree communities, treelines and boreal forest types. However, a direct deduction of future tree vitality, forest composition and biomass trends from the recent relationships between NDVI and climate parameters is challenging. Besides human impact, it must consider bio- and geoecological issues like, for example, tree rejuvenation, temporal lag of climate adaptation and disappearing permafrost.

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New generation of U.S. satellite microwave sounder achieves high radiometric stability performance for reliable climate change detection

Science Advances ◽

10.1126/sciadv.aau0049 ◽

2018 ◽

Vol 4 (10) ◽

pp. eaau0049 ◽

Cited By ~ 6

Author(s):

Cheng-Zhi Zou ◽

Mitchell D. Goldberg ◽

Xianjun Hao

Keyword(s):

Climate Change ◽

Weather Forecasting ◽

Advanced Technology ◽

Trend Detection ◽

Measured Temperature ◽

Climate Data ◽

Climate Trends ◽

Temperature Trends ◽

Satellite Microwave ◽

New Generation

Observations from the satellite microwave sounders play a vital role in measuring the long-term temperature trends for climate change monitoring. Changes in diurnal sampling over time and calibration drift have been the main sources of uncertainties in the satellite-measured temperature trends. We examine observations from the first of a series of U.S. new generation of microwave sounder, the Advanced Technology Microwave Sounder (ATMS), which has been flying onboard the National Oceanic and Atmospheric Administration (NOAA)/NASA Suomi National Polar-orbiting Partnership (SNPP) environmental satellite since late 2011. The SNPP satellite has a stable afternoon orbit that has close to the same local observation time as NASA’s Aqua satellite that has been carrying the heritage microwave sounder, the Advanced Microwave Sounding Unit-A (AMSU-A), from 2002 until the present. The similar overpass timing naturally removes most of their diurnal differences. In addition, direct comparison of temperature anomalies between the two instruments shows little or no relative calibration drift for most channels. Our results suggest that both SNPP/ATMS and Aqua/AMSU-A instruments have achieved absolute stability in the measured atmospheric temperatures within 0.04 K per decade. This uncertainty is small enough to allow reliable detection of the temperature climate trends and help to resolve debate on relevant issues. We also analyze AMSU-A observations onboard the European MetOp-A satellite that has a stable morning orbit 8 hours apart from the SNPP overpass time. Their comparison reveals large asymmetric trends between day and night in the lower- and mid-tropospheric temperatures over land. This information could help to improve climate data records for temperature trend detection with improved accuracy. The SNPP satellite will be followed by four NOAA operational Joint Polar Satellite System (JPSS) satellites, providing accurate and stable measurement for decades to come. The primary mission of JPSS is for weather forecasting. Now, with the added feature of stable orbits, JPSS observations can also be used to monitor changes in climate with much lower uncertainty than the previous generation of NOAA operational satellites.

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ATTRICI v1.1 – counterfactual climate for impact attribution

Geoscientific Model Development ◽

10.5194/gmd-14-5269-2021 ◽

2021 ◽

Vol 14 (8) ◽

pp. 5269-5284

Author(s):

Matthias Mengel ◽

Simon Treu ◽

Stefan Lange ◽

Katja Frieler

Keyword(s):

Climate Change ◽

Climate Impact ◽

Climate Impacts ◽

General Definition ◽

Impact Model ◽

Climate Data ◽

Climate Trends ◽

Long Term Changes ◽

The Impact

Abstract. Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC Working Group II (WGII) a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system's behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause” (IPCC, 2014). Impact attribution following this definition remains a challenge because the counterfactual baseline, which characterizes the system behavior in the hypothetical absence of climate change, cannot be observed. Process-based and empirical impact models can fill this gap as they allow us to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.

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Glacier changes and climate trends derived from multiple sources in the data scarce Cordillera Vilcanota region, Southern Peruvian Andes

The Cryosphere Discussions ◽

10.5194/tcd-6-387-2012 ◽

2012 ◽

Vol 6 (1) ◽

pp. 387-426 ◽

Cited By ~ 4

Author(s):

N. Salzmann ◽

C. Huggel ◽

M. Rohrer ◽

W. Silverio ◽

B. G. Mark ◽

...

Keyword(s):

Air Temperature ◽

Specific Humidity ◽

Spatial And Temporal Variability ◽

Climate Data ◽

Climate Trends ◽

Multiple Sources ◽

Mountain Areas ◽

Peruvian Andes ◽

The Past ◽

Alpine Regions

Abstract. The role of glaciers as temporal water reservoirs is particularly pronounced in the (outer) tropics because of the very distinct wet-dry seasons. Rapid glacier retreat caused by climatic changes is thus a major concern and decision makers demand urgently for regional/local glacier evolution trends, ice mass estimates and runoff assessments. However, in remote mountain areas, spatial and temporal data coverage is typically very scarce and this is further complicated by a high spatial and temporal variability in regions with complex topography. Here, we present an approach on how to deal with these constraints. For the Cordillera Vilcanota (Southern Peruvian Andes), which is the second largest glacierised Cordillera in Peru (after the Cordillera Blanca) and also comprises the Quelccaya Ice Cap, we assimilate a comprehensive multi-decadal collection of available glacier and climate data from multiple sources (satellite images, meteorological station data and climate Reanalysis), and analyze them for respective changes in glacier area and volume and related trends in air temperature, precipitation and specific humidity. In general, the climate data show a moderate (compared to other alpine regions) increase in air temperature, weak and not significant trends for precipitation sums, and an increase in specific humidity at the 500 hPa level. The latter is consistent with observed increase in water vapour at the tropopause level during the past decades. It is likely that the increase in specific humidity played a major role in the observed massive ice loss of the Cordillera Vilcanota over the past decades.

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Influence of Climate Change on Food Crop Yield in Benin Republic

Journal of Agricultural Science ◽

10.5539/jas.v11n5p281 ◽

2019 ◽

Vol 11 (5) ◽

pp. 281 ◽

Cited By ~ 1

Author(s):

Fèmi E. Hounnou ◽

Houinsou Dedehouanou ◽

Afio Zannou ◽

Sofwaan Bakary ◽

Elisée F. Mahoussi

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Potential Evapotranspiration ◽

Least Square ◽

Irrigated Agriculture ◽

Climate Variables ◽

Staple Food ◽

Food Crop ◽

The Mean

World climate is projected to be more harmful and unforeseeable. A threefold combination of temperature, precipitation and potential evapotranspiration leads to climate change with a negative effect on staple food crop production. To understand the sensitivity of staple food crop yield to future change in climate, this paper uses the feasible generalized least square (FGLS) and heteroskedasticity and autocorrelation (HAC) consistent standard error techniques function to quantify the effects of climate variables on the mean and variance of crop yields. Data from FAOSTAT website and national institutions such as temperature, precipitation and crop areas cultivated for period 1961-2015 for Benin country are used. Climate variables are computed according to each crop growing season. The results showed that climate change could significantly influence the mean crop yields and could significantly affect the crop yield variability. The contribution of climate variables to crop yield varies across staple crop yields and they were predicted to decrease about 2025. In order to ensure food availability in the context of climate change, support to agricultural sector and especially to staple food crops production should be focused on seeds improvement by generating, developing and extending drought and flood-tolerant varieties. The results also implicate the promoting of irrigated agriculture.

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