| Records |
| Author |
Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G. |
| Title |
Markov chain as a model of daily total precipitation and a prediction of future natural events |
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Conference Article |
| Year |
2015 |
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Abbreviated Journal |
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| Keywords |
ft_macsur; MACSUR or FACCE acknowledged. |
| Abstract |
The size of arable crop yields depends on many weather factors, such as precipitation and air temperature during the vegetation period. When studying the relation between yields and precipitation, not only the total amount of precipitation, but also the occurrence of long periods without precipitation must be taken into account. The paper [Bojar et al., 2014] demonstrated that barley yield significantly statistically depends on the length of the series of days without precipitation. This paper attempts to analyse the statistical data on daily precipitation totals recorded during the January – December periods in the years 1971 – 2013 at the weather station of the University of Science and Technology in Bydgoszcz, Faculty of Agriculture and Biotechnology, in the Research Centre located in an agricultural area in the Mochle township, situated 17 kilometres from Bydgoszcz. The primary statistical operation in the study is an attempt to estimate the Markov chain order. To this end, two criteria of chain order determination are applied: BIC (Bayesian information criterion, Schwarz 1978) and AIC (Akaike information criterion, Akaike 1974). Both are based on the log-likelihood functions for transition probability of the Markov chain constructed on certain data series. Statistical analysis of precipitation totals data leads to the conclusion that both AIC and BIC indicate the 2nd order for the studied Markov chain. The proposed method of estimating the variability of precipitation occurrence in the future will be utilised to improve region-related bio-physical and economical models, and to assess the risk of extreme events in the context of growing climate hazards. It will serve as basis for a search in agriculture for solutions mitigating those hazards. |
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Braunschweig (Germany) |
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FACCE MACSUR Joint Workshops October 2015, 2015-10-27 to 2015-10-30, Braunschweig |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4236 |
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| Author |
Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G. |
| Title |
Markov chain as a model of daily total precipitation and a prediction of future natural events |
Type |
Conference Article |
| Year |
2015 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
ft_macsur; MACSUR or FACCE acknowledged. |
| Abstract |
The size of arable crop yields depends on many weather factors, such as precipitation and air temperature during the vegetation period. When studying the relation between yields and precipitation, not only the total amount of precipitation, but also the occurrence of long periods without precipitation must be taken into account. The paper [Bojar et al., 2014] demonstrated that barley yield significantly statistically depends on the length of the series of days without precipitation. This paper attempts to analyse the statistical data on daily precipitation totals recorded during the January – December periods in the years 1971 – 2013 at the weather station of the University of Science and Technology in Bydgoszcz, Faculty of Agriculture and Biotechnology, in the Research Centre located in an agricultural area in the Mochle township, situated 17 kilometres from Bydgoszcz. The primary statistical operation in the study is an attempt to estimate the Markov chain order. To this end, two criteria of chain order determination are applied: BIC (Bayesian information criterion, Schwarz 1978) and AIC (Akaike information criterion, Akaike 1974). Both are based on the log-likelihood functions for transition probability of the Markov chain constructed on certain data series. Statistical analysis of precipitation totals data leads to the conclusion that both AIC and BIC indicate the 2nd order for the studied Markov chain. The proposed method of estimating the variability of precipitation occurrence in the future will be utilised to improve region-related bio-physical and economical models, and to assess the risk of extreme events in the context of growing climate hazards. It will serve as basis for a search in agriculture for solutions mitigating those hazards. |
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Braunschweig (Germany) |
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FACCE MACSUR Joint Workshops October 2015, 2015-10-27 to 2015-10-30, Braunschweig |
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Approved |
no |
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MA @ admin @ |
Serial |
4395 |
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| Author |
Roggero, P.P. |
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Oristano, Sardinia, Italy: Winners and losers from climate change in agriculture: a case study in the Mediterranean basin |
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Conference Article |
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2015 |
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6 |
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Sp6-7 |
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CropM |
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Focus questions • How to support effective adaptive responses to CC and stimulate proactive attitudes of farmers, policymakers & researchers? • How to co-construct the nature of the issues about CC adaptation? The «Oristanese» case study • Very diversified agricultural district in a Mediterranean context o Irrigated and rainfed farming systems o Variety of cropping systems, intensity levels, farm size • Multiple stakeholders o Cooperative agro-food system o Producers’ organizations (rice, horticulture) o Variety of extensive pastoral systems Emerging outcome • The dairy cattle coop is developing a new win-win pathway linking hi-input dairy cattle farming with low input beef cattle grazing systems • The local government is investing in the EIP for supporting the local beef production chain to reduce meat imports and enhance pasture biodiversity and ecosystem services (eg wildfire prevention) Emerging challenges Adaptive responses as co-evolution pathways • design social learning spaces for researchers, stakeholders and policy makers • combining integrated assessment modeling and social learning facilitation |
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Brussels |
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Climate-change impacts on farming systems in the next decades — why worry when you have CAP? A FACCE MACSUR workshop for policymakers, 2015-05-06 to 2015-05-06, Brussels |
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Approved |
no |
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MA @ admin @ |
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2750 |
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Virkajärvi, P.; Lehtonen, H.; Järvenranta, K. |
| Title |
Regional impacts of climate change, observations and projections. Finnish Pilot study: North Savo region |
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Conference Article |
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2015 |
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6 |
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SP6-5 |
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Regional adjustment of regulation is important (eg. water protection) Due to expected growing yield potential fertilisation restrictions need adjustmentNitrate directive restricts efficient and sustainable grass productionGreening practices have only slight – and partly negative – impact on ruminant production (permanent grassland not suitable for northern conditions)Inefficient markets for agricultural land cause difficulties for farms that are increasing their productionCapitalisation of area payments to land prices + incentives for extensification (e.g. nature management and other set aside schemes under pillar 2) fit better part-time crop farms, not full-time livestock farmsthey express frustration on weak land supplyProduction based support for suckler cows and (dairy originated) beef production is vital for producersNo significant increase in production expected, budgetary limits of coupled supports No Label |
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Brussels |
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Climate-change impacts on farming systems in the next decades: Why worry when you have CAP? A workshop for decisionmakers., 2015-05-06, Brussels |
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no |
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MA @ admin @ |
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2882 |
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Brouwer, F.; Sinabell, F. |
| Title |
Three years of collaboration in TradeM – Agricultural markets and prices |
Type |
Conference Article |
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2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
6 |
Issue |
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SP6-4 |
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Some farmers may claim that climate change adaptation is easy compared to the difficulties caused by policiesAction based on weather observations only, is insufficient for farmers to respond to climate change. Researchers need support from farmers in understanding the responses in practice.Policies might be too slow to respond to needs for change in agriculture. Winners and losers seem to be observed everywhere.The impacts of climate change is heterogeneous among farm types and regionsEffects beyond 2050 remain largely unclear, mainly because the effects of extreme events are not consideredVariability of yields is important to farm incomes, but most studies only consider average changesFarmers are ready to design their site-specific adaptation response providing that new knowledge and learning spaces are available. A learning process based on integrated models, assessment of short- and long-term effects, is needed for farmers to adapt to climate change, price fluctuations and policy change. No Label |
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Brussels |
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Climate-change impacts on farming systems in the next decades: Why worry when you have CAP? A FACCE MACSUR workshop for policymakers |
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Approved |
no |
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MA @ admin @ |
Serial |
2343 |
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