Cereal yield forecasting in Morocco using the CARAIB dynamic vegetation model driven by HadGEM2-AO projections

Food security, in Morocco as in many parts of the world, depends heavily on cereal production which fluctuates relying on weather conditions. In fact, Morocco has a production system for cereals which is dominated by rainfed. It is therefore necessary to further develop knowledge about climate change and strengthen forecasting systems for predicting the impacts of climate change.Our research, funded by a bilateral project of Wallonie-Bruxelles International, aims to study the response of cereal production to climate change, using the dynamic vegetation model CARAIB (CARbon Assimilation In the Biosphere) developed within the Unit for Modelling of Climate and Biogeochemical Cycles (UMCCB) of the University of Li&#232;ge. This spatial model includes crops and natural vegetation and may react dynamically to land use changes. Originally constructed to study vegetation dynamics and carbon cycle, it includes coupled hydrological, biogeochemical, biogeographical and fire modules. These modules respectively describe the exchange of water between the atmosphere, the soil and the vegetation, the photosynthetic production and the evolution of carbon stocks and fluxes in this vegetation-soil system. For crops, a specific module describes basic management parameters (sowing, harvest, rotation) and phenological phases.The simulations are performed across all Morocco using different input data. The three main cereal crops simulated include soft wheat, durum wheat and barley, they are grown in all provinces and all agro-ecological zones. Regarding climatic inputs, we&#8217;re using two sets of data: the first one is interpolated and bias-corrected fields from the climate model HadGEM2-AO for the historical period (1990-2005), in addition to three different Representative Concentration Pathway scenarios (RCP2.6, RCP4.5 and RCP8.5) from 2005 to 2100. The second one is high resolution (30 arc sec) gridded climate data derived from WorldClim combined with interpolated anomalies from CRU (Climatic Research Unit) over the historical period 1990 to 2018.After obtaining preliminary results for the past period, and in order to improve the prediction using the field data which are the observed yields, we performed a sensitivity analysis. We used the One-at-a-time (OAT) approach by moving one input variable, keeping others at their baseline (nominal) values, then, returning the variable to its nominal value, then repeating for each of the other inputs in the same way. Sensitivity may then be measured by monitoring changes in the output, using linear regression. The inputs studied are the initial value of carbon pool, leaf C/N ratio, water stress, sowing date, GDD harvest, stomatal conductance parameters, specific leaf area, and rooting depth.

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Simulating and analysing climate change impacts on crop yields in Morocco using the CARAIB dynamic vegetation model driven by Med-CORDEX projections

10.5194/egusphere-egu2020-11350 ◽

2020 ◽

Author(s):

Iliass Loudiyi ◽

Ingrid Jacquemin ◽

Bernard Tychon ◽

Louis Francois ◽

Mouanis Lahlou ◽

...

Keyword(s):

Climate Change ◽

Climate Model ◽

Crop Yields ◽

Heat Waves ◽

Arable Land ◽

Natural Vegetation ◽

Vegetation Model ◽

Soil System ◽

Sugar Beets ◽

Dynamic Vegetation Model

Morocco, by its geographical position and its climate, is strongly affected by climate change and presents an ever-increasing vulnerability. In fact, the country's economy, being very dependent on agriculture, would be greatly affected. It is therefore necessary to further develop knowledge about climate change and strengthen forcasting systems for predicting the impacts of climate change.The agriculture in Morocco is largely dominated by rainfed crops and therefore dependent on pluviometry.According to the report of the Moroccan Minister of Agriculture (Agriculture En Chiffres version 2019), about 59% of arable land is devoted to cereals, 16% to plantation crops (olives, almonds, citrus, grapes, dates), 5% to forage, 3% to vegetables, 5% to other crops (sugar beets, sugar cane, cotton and oilseeds), and 12% is fallow. In this project we are going to focus on cereals, olives, potatoes and sugar beets. Regarding the climate, Morocco is characterized by a wide variety of topographies ranging from mountains to plains, oasis and Saharan dunes. For this reason, the country experiences diverse climatic conditions with large spatial and intra- and inter-annual variability of precipitation. Morocco faces irregular rain patterns, cold spells and heat waves increasingly resulting in droughts, which significantly affects agriculture.Our research, funded by a bilateral project of Wallonie-Bruxelles International, aims to study the response of Moroccan agriculture to climate change, using the dynamic vegetation model CARAIB (CARbon Assimilation In the Biosphere) developed within the Unit for Modelling of Climate and Biogeochemical Cycles (UMCCB) of the University of Li&#232;ge. This spatial model includes crops and natural vegetation and may react dynamically to land use changes. Originally constructed to study vegetation dynamics and carbon cycle, it includes coupled hydrological, biogeochemical, biogeographical and fire modules. These modules respectively describe the exchange of water between the atmosphere, the soil and the vegetation, the photosynthetic production and the evolution of carbon stocks and fluxes in this vegetation-soil system. The biogeographical module describes, for natural vegetation, the establishment, growth, competition, mortality, and regeneration of plant species, as well as the occurrence and propagation of fires. For crops, a specific module describes basic management (sowing, harvest, rotation) and phenological phases. &#160;&#160;Model simulations are performed across north-west Morocco, where the crops activities are important, by using different input data. The timeline of simulations is divided in two periods: past (from 1901 to 2018) and future (from 2019 to 2100). For the past period, we are using high resolution (30 arc sec) gridded climate data derived from WorldClim (climatology) and interpolated anomalies from Climate Research Unit CRU (trend and variability). &#160;For the future period, we use interpolated and bias-corrected fields from a regional climate model (ALADIN-Climate) from the Med-CORDEX initiative run at a spatial resolution of 12 km and for three different Representative Concentration Pathway scenarios (RCP2.6, RCP4.5 and RCP8.5).

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The impact of climate change in wheat and barley yields in the Iberian Peninsula

Scientific Reports ◽

10.1038/s41598-021-95014-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Virgílio A. Bento ◽

Andreia F. S. Ribeiro ◽

Ana Russo ◽

Célia M. Gouveia ◽

Rita M. Cardoso ◽

...

Keyword(s):

Climate Change ◽

Iberian Peninsula ◽

Climate Model ◽

Global Climate Models ◽

Maximum Temperature ◽

Historical Period ◽

Early Winter ◽

Impact Of Climate Change ◽

The Impact ◽

Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

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Evaluating quantile-based bias adjustment methods for climate change scenarios

10.5194/hess-2021-498 ◽

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.

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Introducing an Irrigation Scheme to a Regional Climate Model: A Case Study over West Africa

Journal of Climate ◽

10.1175/jcli-d-13-00116.1 ◽

2014 ◽

Vol 27 (15) ◽

pp. 5708-5723 ◽

Cited By ~ 23

Author(s):

Marc P. Marcella ◽

Elfatih A. B. Eltahir

Keyword(s):

Heat Flux ◽

Land Cover ◽

West Africa ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Vegetation Model ◽

Irrigation Scheme ◽

Dynamic Vegetation Model ◽

Niger River

Abstract This article presents a new irrigation scheme and biome to the dynamic vegetation model, Integrated Biosphere Simulator (IBIS), coupled to version 3 of the Regional Climate Model (RegCM3-IBIS). The new land cover allows for only the plant functional type (crop) to exist in an irrigated grid cell. Irrigation water (i.e., negative runoff) is applied until the soil root zone reaches relative field capacity. The new scheme allows for irrigation scheduling (i.e., when to apply water) and for the user to determine the crop to be grown. Initial simulations show a large sensitivity of the scheme to soil texture types, how the water is applied, and the climatic conditions over the region. Application of the new scheme is tested over West Africa, specifically Mali and Niger, to simulate the potential irrigation of the Niger River. A realistic representation of irrigation of the Niger River is performed by constraining the land irrigated by the annual flow of the Niger River and the amount of arable land in the region as reported by the Food and Agriculture Organization of the United Nations (FAO). A 30-yr simulation including irrigated cropland is compared to a 30-yr simulation that is identical but with no irrigation of the Niger. Results indicate a significant greening of the irrigated land as evapotranspiration over the crop fields largely increases—mostly via increases in transpiration from plant growth. The increase in the evapotranspiration, or latent heat flux (by 65–150 W m−2), causes a significant decrease in the sensible heat flux while surface temperatures cool on average by nearly 5°C. This cooling is felt downwind, where average daily temperatures outside the irrigation are reduced by 0.5°–1.0°C. Likewise, large increases in 2-m specific humidity are experienced across the irrigated cropland (on the order of 5 g kg−1) but also extend farther north and east, reflecting the prevailing surface southwesterlies. Changes (decreases) in rainfall are found only over the irrigated lands of west Mali. The decrease in rainfall can be explained by the large surface cooling and collapse of the boundary layer (by approximately 500 m). Both lead to a reduction in the triggering of convection as the convective inhibition, or negative buoyant energy, is never breached. Nevertheless, the new scheme and land cover allows for a novel line of research that can accurately reflect the effects of irrigation on climate and the surrounding environment using a dynamic vegetation model coupled to a regional climate model.

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Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

10.5194/egusphere-egu21-12054 ◽

2021 ◽

Author(s):

Gaby S. Langendijk ◽

Diana Rechid ◽

Daniela Jacob

Keyword(s):

Climate Change ◽

Urban Areas ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Climate Change Impacts ◽

Regional Climate Models ◽

Climate Projections ◽

Climate Data ◽

Urban Rural

Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2&#176;C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.

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Projected Changes of Precipitation IDF Curves for Short Duration under Climate Change in Central Vietnam

Hydrology ◽

10.3390/hydrology5030033 ◽

2018 ◽

Vol 5 (3) ◽

pp. 33 ◽

Cited By ~ 7

Author(s):

Nguyen Tien Thanh ◽

Luca Dutto Aldo Remo

Keyword(s):

Climate Change ◽

Climate Model ◽

Southern Oscillation ◽

Regional Climate ◽

Extreme Weather Events ◽

Climate Data ◽

Rcp Scenarios ◽

Central Vietnam ◽

Idf Curves ◽

Projected Changes

In future years, extreme weather events are expected to frequently increase due to climate change, especially in the combination of climate change and events of El Niño–Southern Oscillation. This pays special attention to the construction of intensity–duration–frequency (IDF) curves at a tempo-spatial scale of sub-daily and sub-grid under a context of climate change. The reason for this is that IDF curves represent essential means to study effects on the performance of drainage systems, damps, dikes and reservoirs. Therefore, the objective of this study is to present an approach to construct future IDF curves with high temporo-spatial resolutions under climate change in central Vietnam, using the case of VuGia-ThuBon. The climate data of historical and future from a regional climate model RegCM4 forced by three global models MPI-ESM-MR, IPSL-CM5A-LR and ICHEC-EC-EARTH are used to re-grid the resolution of 10 km × 10 km grid spacing from 25 km × 25 km on the base of bilinear interpolation. A bias correction method is then applied to the finest resolution of a hydrostatic climate model for an ensemble of simulations. Furthermore, the IDF curves for short durations of precipitation are constructed for the historical climate and future climates under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, based on terms of correlation factors. The major findings show that the projected precipitation changes are expected to significantly increase by about 10 to 30% under the scenarios of RCP4.5 and RCP8.5. The projected changes of a maximum of 1-, 2-, and 3-days precipitation are expected to increase by about 30–300 mm/day. More importantly, for all return periods (i.e., 10, 20, 50, 100, and 200 years), IDF curves completely constructed for short durations of precipitation at sub-daily show an increase in intensities for the RCP4.5 and RCP8.5 scenarios.

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Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

10.20944/preprints201806.0155.v1 ◽

2018 ◽

Author(s):

Joanne Nightingale ◽

Folkert Boersma ◽

Jan-Peter Muller ◽

Steven Compernolle ◽

Jean-Christopher Lambert ◽

...

Keyword(s):

Climate Change ◽

Quality Assurance ◽

Climate Model ◽

Earth Observation ◽

Evidence Based ◽

The European Union ◽

Climate Data ◽

Area Index ◽

Data Products ◽

Reference Measurements

Data from Earth Observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts and manage natural resources. Policy makers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products as well as the reference measurements used to calibrate, validate or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service, the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite derived datasets by prototyping a robust, generic system for the implementation and evaluation of Quality Assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface Albedo, Leaf Area Index, FAPAR, NO2, HCHO and CO. Provision of standardized QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products their specific applications.

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Assessment of Impacts of Climate Change and Adaptation Measures for Maize Production in East Sikkim, India

Journal of Hydrology and Meteorology ◽

10.3126/jhm.v9i1.15579 ◽

2016 ◽

Vol 9 (1) ◽

pp. 15-27

Author(s):

Proloy Deb ◽

S. Babel

Keyword(s):

Climate Change ◽

Climate Model ◽

Global Climate Model ◽

Maize Yield ◽

Future Climate ◽

Yield Response ◽

Climate Data ◽

North East ◽

The Impact ◽

Impacts Of Climate Change

An investigation was carried out to assess the impacts of climate change on rainfed maize yield using a yield response to water stress model (AquaCrop) and to identify suitable adaptation options to minimize the negative impacts on maize yield in East Sikkim, North East India. Crop management and yield data was collected from the field experimental plots for calibration and validation of the model for the study area. The future climate data was developed for two IPCC emission scenarios A2 and B2 based on the global climate model HadCM3 with downscaling of climate to finer spatial resolution using the statistical downscaling model, SDSM. The impact study revealed that there is an expected reduction in maize yield of 12.8, 28.3 and 33.9% for the A2 scenario and 7.5, 19.9 and 29.9% for the B2 scenario during 2012-40, 2041-70 and 2071-99 respectively compared to the average yield simulated during the period of 1961-1990 with observed climate data. The maize yield of same variety under future climate can be maintained or improved from current level by changing planting dates, providing supplement irrigation and managing optimum nutrient.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.15-27

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Climate Data to Undertake Hygrothermal and Whole Building Simulations Under Projected Climate Change Influences for 11 Canadian Cities

Data ◽

10.3390/data4020072 ◽

2019 ◽

Vol 4 (2) ◽

pp. 72 ◽

Cited By ~ 4

Author(s):

Abhishek Gaur ◽

Michael Lacasse ◽

Marianne Armstrong

Keyword(s):

Climate Change ◽

Snow Cover ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Internal Variability ◽

Climatic Conditions ◽

Climate Data ◽

Wide Range ◽

The Future

Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance over current and projected future climates. Hygrothermal and whole building simulation models, which are important tools for assessing performance, require continuous climate records at high temporal frequencies of a wide range of climate variables for input into the kinds of models that relate to solar radiation, cloud-cover, wind, humidity, rainfall, temperature, and snow-cover. In this study, climate data that can be used to assess the performance of building envelopes under current and projected future climates, concurrent with 2 °C and 3.5 °C increases in global temperatures, are generated for 11 major Canadian cities. The datasets capture the internal variability of the climate as they are comprised of 15 realizations of the future climate generated by dynamically downscaling future projections from the CanESM2 global climate model and thereafter bias-corrected with reference to observations. An assessment of the bias-corrected projections suggests, as a consequence of global warming, future increases in the temperatures and precipitation, and decreases in the snow-cover and wind-speed for all cities.

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Impacts of Climate Change on the Hydro-Climate of Peninsular Malaysia

Water ◽

10.3390/w11091798 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1798 ◽

Cited By ~ 1

Author(s):

Ir. Mohd Zaki bin Mat Amin ◽

Ali Ercan ◽

Kei Ishida ◽

M. Levent Kavvas ◽

Z.Q. Chen ◽

...

Keyword(s):

Climate Change ◽

21St Century ◽

Climate Model ◽

Regional Climate ◽

Water Storage ◽

Peninsular Malaysia ◽

Soil Water Storage ◽

Historical Period ◽

Coastal Regions ◽

Impacts Of Climate Change

In this study, a regional climate model was used to dynamically downscale 15 future climate projections from three GCMs covering four emission scenarios (SRES B1, A1FI, A1B, A2) based on Coupled Model Intercomparison Project phase 3 (CMIP3) datasets to 6-km horizontal resolution over the whole Peninsular Malaysia. Impacts of climate change in the 21st century on the precipitation, air temperature, and soil water storage were assessed covering ten watersheds and twelve coastal regions. Then, by coupling a physical hydrology model with the regional climate model, the impacts of the climate change on river flows were assessed at the outlets of ten watersheds in Peninsular Malaysia. It was found that the increase in the 30-year mean annual precipitation from 1970–2000 to 2070–2100 will vary from 17.1 to 36.3 percent among the ten watersheds, and from 22.9 to 45.4 percent among twelve coastal regions. The ensemble average of the basin-average annual mean air temperature will increase about 2.52 °C to 2.95 °C from 2010 to 2100. In comparison to the historical period, the change in the 30-year mean basin-average annual mean soil water storage over the ten watersheds will vary from 0.7 to 10.9 percent at the end of 21st century, and that over the twelve coastal regions will vary from −1.7 to 15.8 percent. Ensemble averages of the annual mean flows of the 15 projections show increasing trends for the 10 watersheds, especially in the second half of the 21st century. In comparison to the historical period, the change in the 30-year average annual mean flows will vary from −2.1 to 14.3 percent in the early 21st century, 4.4 to 23.8 percent in the middle 21st century, and 19.1 to 45.8 percent in the end of 21st century.

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