A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

Long-term simulations in watershed hydrology, soil and nutrient transport, and sustainability of agricultural production systems require long-term weather records that are often not available at the location of interest. Generation of synthetic daily weather data is a common approach to augment limited weather observations. Here a synthetic daily weather generation model (called SYNTOR) is described. SYNTOR fulfills the traditional role of generating alternative weather realizations that have statistical properties similar to those of the parent historical weather it is intended to simulate. In addition, it has the capability to simulate daily weather records for climate change scenarios and storm intensification due to climate change. The various model components are briefly summarized and an application is presented for semi-arid climate conditions in west-central Oklahoma. SYNTOR generated daily weather compared well with observed weather values. Climate change is simulated by adjusting weather generation parameters to reflect the changed mean monthly weather values of climate projections. Storm intensification is approximated by increasing the top 10 percentile of storm distribution by a predefined amount based on previous studies of trends in United States precipitation. Further evaluation of published storm intensification values and associated uncertainties and spatial variability is recommended.

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Assessment of Climate Change Impacts on Reference Evapotranspiration and Simulation of Daily Weather Data Using SIMETAW

Journal of Irrigation and Drainage Engineering ◽

10.1061/(asce)ir.1943-4774.0000669 ◽

2014 ◽

Vol 140 (2) ◽

pp. 04013012 ◽

Cited By ~ 3

Author(s):

Meisam Ebrahimpour ◽

Nozar Ghahreman ◽

Morteza Orang

Keyword(s):

Climate Change ◽

Reference Evapotranspiration ◽

Climate Change Impacts ◽

Weather Data ◽

Daily Weather ◽

Daily Weather Data

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Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria

The Journal of Agricultural Science ◽

10.1017/s0021859616000083 ◽

2016 ◽

Vol 154 (7) ◽

pp. 1153-1170 ◽

Cited By ~ 3

Author(s):

E. EBRAHIMI ◽

A. M. MANSCHADI ◽

R. W. NEUGSCHWANDTNER ◽

J EITZINGER ◽

S. THALER ◽

...

Keyword(s):

Climate Change ◽

Management Practices ◽

Crop Management ◽

Weather Data ◽

Climate Change Scenarios ◽

Management Scenarios ◽

Global Circulation Models ◽

Daily Weather Data ◽

Eastern Austria ◽

The Impact

SUMMARYClimate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.

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Impact of climate change on harvest security and biomass yield of two timothy ley harvesting systems in Norway

The Journal of Agricultural Science ◽

10.1017/s0021859612001013 ◽

2013 ◽

Vol 152 (2) ◽

pp. 205-216 ◽

Cited By ~ 12

Author(s):

T. PERSSON ◽

M. HÖGLIND

Keyword(s):

Climate Change ◽

Biomass Yield ◽

Phleum Pratense ◽

Future Climate ◽

Weather Data ◽

Future Climate Change ◽

Daily Weather ◽

Daily Weather Data ◽

Dry Spell ◽

Harvesting Regime

SUMMARYPredicted future climate changes in northern Europe include increased air temperature and altered precipitation patterns. There is a lack of knowledge about potential climate change effects on the biomass yield and security of agricultural crops. The present study determined the potential impact of future climate change on the yield and harvest security of timothy (Phleum pratense L.). Harvest security was assessed using data on accumulated precipitation and the length of dry spell period within the 7 days after cutting. Timothy production as a function of weather, soil and management practices was simulated using the LINGRA model for the periods 1961–90, 2046–65 and 2080–99, and the locations Apelsvoll, Ås, Sola, Tromsø and Værnes in Norway and harvest systems with 600 and 800 °C days between cuts. One hundred years of daily weather data were generated with the LARS-WG tool, using future daily weather data sets based on 12 Global Climate Models. Total seasonal biomass yield varied between 690 g dry matter (DM)/m2 for the 800 °C days harvesting regime in the period 1961–90 at Tromsø and 1548 g DM/m2 for the same harvesting regime in the period 2046–65 at Sola. In general, the biomass was higher in the two future periods than in 1961–90 across locations and harvesting regimes, mainly owing to more cuts per season. Accumulated precipitation after cutting varied between 12·2 mm after the first cut for the 600 °C days harvesting regime in the period 1961–90 at Værnes and 42·5 mm after the fourth cut in the 800 °C days harvesting regime in the period 2080–99 at Sola. The longest duration of dry spell 7 days after pre-planned harvest varied between 1·8 days after the fourth cut at Sola in the 600 °C days harvesting regime for the period 2080–99, and 3·9 days after the first cut at Ås in the 800 °C days harvesting regime for the period 2046–65. Potential consequences of these results are discussed.

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Downscaling climate change scenarios for apple pest and disease modeling in Switzerland

Earth System Dynamics Discussions ◽

10.5194/esdd-2-493-2011 ◽

2011 ◽

Vol 2 (2) ◽

pp. 493-529 ◽

Cited By ~ 3

Author(s):

M. Hirschi ◽

S. Stoeckli ◽

M. Dubrovsky ◽

C. Spirig ◽

P. Calanca ◽

...

Keyword(s):

Climate Change ◽

Fire Blight ◽

Codling Moth ◽

Weather Data ◽

Climate Change Scenarios ◽

Climate Conditions ◽

Pests And Diseases ◽

Daily Weather Data ◽

The Future ◽

The Impact

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously not affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology depending on actual weather conditions and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1 % on average today to over 60 % in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g., insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.

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Downscaling climate change scenarios for apple pest and disease modeling in Switzerland

Earth System Dynamics ◽

10.5194/esd-3-33-2012 ◽

2012 ◽

Vol 3 (1) ◽

pp. 33-47 ◽

Cited By ~ 26

Author(s):

M. Hirschi ◽

S. Stoeckli ◽

M. Dubrovsky ◽

C. Spirig ◽

P. Calanca ◽

...

Keyword(s):

Climate Change ◽

Fire Blight ◽

Codling Moth ◽

Weather Data ◽

Climate Change Scenarios ◽

Climate Conditions ◽

Pests And Diseases ◽

Daily Weather Data ◽

The Future ◽

The Impact

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously non-affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology, depending on actual weather conditions, and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1% on average today to over 60% in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g. insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.

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Evaluating and Adapting Climate Change Impacts on Rice Production in Indonesia: A Case Study of the Keduang Subwatershed, Central Java

Environments ◽

10.3390/environments8110117 ◽

2021 ◽

Vol 8 (11) ◽

pp. 117

Author(s):

Andrianto Ansari ◽

Yu-Pin Lin ◽

Huu-Sheng Lur

Keyword(s):

Climate Change ◽

Rice Yield ◽

Rice Production ◽

Calibration Coefficient ◽

Weather Data ◽

Climate Change Scenarios ◽

Impact Of Climate Change ◽

Central Java ◽

Daily Weather Data ◽

The Impact

Predicting the effect of climate change on rice yield is crucial as global food demand rapidly increases with the human population. This study combined simulated daily weather data (MarkSim) and the CERES-Rice crop model from the Decision Support System for Agrotechnology Transfer (DSSAT) software to predict rice production for three planting seasons under four climate change scenarios (RCPs 2.6, 4.5, 6.0, and 8.5) for the years 2021 to 2050 in the Keduang subwatershed, Wonogiri Regency, Central Java, Indonesia. The CERES-Rice model was calibrated and validated for the local rice cultivar (Ciherang) with historical data using GenCalc software. The model evaluation indicated good performance with both calibration (coefficient of determination (R2) = 0.89, Nash–Sutcliffe efficiency (NSE) = 0.88) and validation (R2 = 0.87, NSE = 0.76). Our results suggest that the predicted changing rainfall patterns, rising temperature, and intensifying solar radiation under climate change can reduce the rice yield in all three growing seasons. Under RCP 8.5, the impact on rice yield in the second dry season may decrease by up to 11.77% in the 2050s. Relevant strategies associated with policies based on the results were provided for decision makers. Furthermore, to adapt the impact of climate change on rice production, a dynamic cropping calendar, modernization of irrigation systems, and integrated plant nutrient management should be developed for farming practices based on our results in the study area. Our study is not only the first assessment of the impact of climate change on the study site but also provides solutions under projected rice shortages that threaten regional food security.

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Simulating the Impact of Climate Change on Rice Phenology and Grain Yield in Irrigated Drylands of Central Asia

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0182.1 ◽

2013 ◽

Vol 52 (9) ◽

pp. 2033-2050 ◽

Cited By ~ 17

Author(s):

K. P. Devkota ◽

A. M. Manschadi ◽

M. Devkota ◽

J. P. A. Lamers ◽

E. Ruzibaev ◽

...

Keyword(s):

Climate Change ◽

Grain Yield ◽

Central Asia ◽

Growth And Yield ◽

Weather Data ◽

Rice Grain ◽

Climate Change Scenarios ◽

Rice Varieties ◽

Daily Weather Data ◽

The Impact

AbstractRice is the second major food crop in central Asia. Climate change may greatly affect the rice production in the region. This study quantifies the effects of projected increases in temperature and atmospheric CO2 concentration on the phenological development and grain yield of rice using the “ORYZA2000” simulation model. The model was parameterized and validated on the basis of datasets from three field experiments with three widely cultivated rice varieties under various seeding dates in the 2008–09 growing seasons in the Khorezm region of Uzbekistan. The selected rice varieties represent short-duration (SD), medium-duration (MD), and long-duration (LD) maturity types. The model was linked with historical climate data (1970–99) and temperatures and CO2 concentrations projected by the Intergovernmental Panel on Climate Change for the B1 and A1F1 scenarios for the period 2040–69 to explore rice growth and yield formation at eight emergence dates from early May to mid-July. Simulation results with historical daily weather data reveal a close relationship between seeding date and rice grain yield. Optimal emergence dates were 25 June for SD, 5 June for MD, and 26 May for LD varieties. Under both climate change scenarios, the seeding dates could be delayed by 10 days. Increased temperature and CO2 concentration resulted in higher rice grain yields. However, seeding rice before and after the optimal seeding dates reduced crop yield and yield stability significantly because of spikelet sterility induced by both high and low temperatures. As the grain yield of SD varieties could be adversely affected by climate change, rice breeding programs for central Asia should focus on developing appropriate heat-tolerant MD and LD varieties.

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Short Communication: Climate change and biofuel wheat: A case study of southern Saskatchewan

Canadian Journal of Plant Science ◽

10.4141/cjps2011-192 ◽

2012 ◽

Vol 92 (3) ◽

pp. 421-425 ◽

Cited By ~ 13

Author(s):

Hong Wang ◽

Yong He ◽

Budong Qian ◽

Brian McConkey ◽

Herb Cutforth ◽

...

Keyword(s):

Climate Change ◽

Grain Yield ◽

Short Communication ◽

Weather Data ◽

Yield Reduction ◽

Climate Change Scenarios ◽

Communication Climate ◽

Stochastic Weather Generator ◽

Ipcc Sres

Wang, H., He, Y., Qian, B., McConkey, B., Cutforth, H., McCaig, T., McLeod, G., Zentner, R., DePauw, R., Lemke, R., Brandt, K., Liu, T., Qin, X., White, J., Hunt, T. and Hoogenboom, G. 2012. Short Communication: Climate change and biofuel wheat: A case study of southern Saskatchewan. Can. J. Plant Sci. 92: 421–425. This study assessed potential impacts of climate change on wheat production as a biofuel crop in southern Saskatchewan, Canada. The Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) was used to simulate biomass and grain yield under three climate change scenarios (CGCM3 with the forcing scenarios of IPCC SRES A1B, A2 and B1) in the 2050s. Synthetic 300-yr weather data were generated by the AAFC stochastic weather generator for the baseline period (1961–1990) and each scenario. Compared with the baseline, precipitation is projected to increase in every month under all three scenarios except in July and August and in June for A2, when it is projected to decrease. Annual mean air temperature is projected to increase by 3.2, 3.6 and 2.7°C for A1B, A2 and B1, respectively. The model predicted increases in biomass by 28, 12 and 16% without the direct effect of CO2 and 74, 55 and 41% with combined effects (climate and CO2) for A1B, A2 and B1, respectively. Similar increases were found for grain yield. However, the occurrence of heat shock (>32°C) will increase during grain filling under the projected climate conditions and could cause severe yield reduction, which was not simulated by DSSAT-CSM. This implies that the future yield under climate scenarios might have been overestimated by DSSAT-CSM; therefore, model modification is required. Several measures, such as early seeding, must be taken to avoid heat damages and take the advantage of projected increases in temperature and precipitation in the early season.

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Integrated assessment of impact of water resources of important river basins in Eastern India under projected climate conditions

Global NEST Journal ◽

10.30955/gnj.001658 ◽

2015 ◽

Vol 17 (3) ◽

pp. 594-606 ◽

Cited By ~ 5

Keyword(s):

Climate Change ◽

Water Resources ◽

Catchment Area ◽

River Basins ◽

Weather Data ◽

Distributed Hydrological Model ◽

Eastern India ◽

Impact Of Climate Change ◽

Daily Weather Data ◽

The Impact

<div> <p>The impact of climate change on water resources through increased evaporation combined with regional changes in precipitation characteristics has the potential to affect mean runoff, frequency and intensity of floods and droughts, soil moisture and water supply for irrigation and hydroelectric power generation. The Ganga-Brahmaputra-Meghna (GBM) system is the largest in India with a catchment area of about 110Mha, which is more than 43% of the cumulative catchment area of all the major rivers in the country. The river Damodar is an important sub catchment of GBM basin and its three tributaries- the Bokaro, the Konar and the Barakar form one important tributary of the Bhagirathi-Hughli (a tributary of Ganga) in its lower reaches. The present study is an attempt to assess the impacts of climate change on water resources of the four important Eastern River Basins namely Damodar, Subarnarekha, Mahanadi and Ajoy, which have immense importance in industrial and agricultural scenarios in eastern India. A distributed hydrological model (HEC-HMS) has been used on the four river basins using HadRM2 daily weather data for the period from 2041 to 2060 to predict the impact of climate change on water resources of these river systems. </p> </div> <p> </p>

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