scholarly journals Generation of Synthetic Daily Weather for Climate Change Scenarios and Extreme Storm Intensification

2019 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Jurgen Garbrecht ◽  
X. C. Zhang ◽  
David Brown ◽  
Phillip Busteed
Keyword(s):  
Climate Change ◽  
Weather Data ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Generation Model ◽  
Traditional Role ◽  
Climate Conditions ◽  
Daily Weather ◽  
Daily Weather Data

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.

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

2015 ◽  
Vol 127 (3-4) ◽  
pp. 573-585 ◽  
Author(s):  
G. Duveiller ◽  
M. Donatelli ◽  
D. Fumagalli ◽  
A. Zucchini ◽  
R. Nelson ◽  
...  
Keyword(s):  
Climate Change ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Crop Modelling ◽  
Daily Weather ◽  
Daily Weather Data

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

2011 ◽  
Vol 2 (2) ◽  
pp. 493-529 ◽  
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.

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

2012 ◽  
Vol 3 (1) ◽  
pp. 33-47 ◽  
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.

scholarly journals Long-Term (2001–2020) Nutrient Transport from a Small Boreal Agricultural Watershed: Hydrological Control and Potential of Retention Ponds

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2731
Author(s):  
Sari Uusheimo ◽  
Tiina Tulonen ◽  
Jussi Huotari ◽  
Lauri Arvola
Keyword(s):  
Climate Change ◽  
Total Nitrogen ◽  
Total Phosphorus ◽  
Nutrient Loading ◽  
Nitrogen Loading ◽  
Agricultural Watershed ◽  
Weather Data ◽  
Pond System ◽  
Daily Weather Data

Agriculture contributes significantly to phosphorus and nitrogen loading in southern Finland. Climate change with higher winter air temperatures and precipitation may also promote loading increase further. We analyzed long-term nutrient trends (2001–2020) based on year-round weekly water sampling and daily weather data from a boreal small agricultural watershed. In addition, nutrient retention was studied in a constructed sedimentation pond system for two years. We did not find any statistically significant trends in weather conditions (temperature, precipitation, discharge, snow depth) except for an increase in discharge in March. Increasing trends in annual concentrations were found for nitrate, phosphate, and total phosphorus and total nitrogen. In fact, phosphate concentration increased in every season and nitrate concentration in other seasons except in autumn. Total phosphorus and total nitrogen concentrations increased in winter as well and total phosphorus also in summer. Increasing annual loading trend was found for total phosphorus, phosphate, and nitrate. Increasing winter loading was found for nitrate and total nitrogen, but phosphate loading increased in winter, spring, and summer. In the pond system, annual retention of total nitrogen was 1.9–4.8% and that of phosphorus 4.3–6.9%. In addition, 25–40% of suspended solids was sedimented in the ponds. Our results suggest that even small ponds can be utilized to decrease nutrient and material transport, but their retention efficiency varies between years. We conclude that nutrient loading from small boreal agricultural catchments, especially in wintertime, has already increased and is likely to increase even further in the future due to climate change. Thus, the need for new management tools to reduce loading from boreal agricultural lands becomes even more acute.

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

2016 ◽  
Vol 154 (7) ◽  
pp. 1153-1170 ◽  
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.

scholarly journals Water Quality Sustainability Evaluation under Uncertainty: A Multi-Scenario Analysis Based on Bayesian Networks

2019 ◽  
Vol 11 (17) ◽  
pp. 4764 ◽  
Author(s):  
Anna Sperotto ◽  
Josè Luis Molina ◽  
Silvia Torresan ◽  
Andrea Critto ◽  
Manuel Pulido-Velazquez ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Bayesian Networks ◽  
Climate Model ◽  
Future Climate Change ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Large Variability ◽  
Nutrient Loadings

With increasing evidence of climate change affecting the quality of water resources, there is the need to assess the potential impacts of future climate change scenarios on water systems to ensure their long-term sustainability. The study assesses the uncertainty in the hydrological responses of the Zero river basin (northern Italy) generated by the adoption of an ensemble of climate projections from 10 different combinations of a global climate model (GCM)–regional climate model (RCM) under two emission scenarios (representative concentration pathways (RCPs) 4.5 and 8.5). Bayesian networks (BNs) are used to analyze the projected changes in nutrient loadings (NO3, NH4, PO4) in mid- (2041–2070) and long-term (2071–2100) periods with respect to the baseline (1983–2012). BN outputs show good confidence that, across considered scenarios and periods, nutrient loadings will increase, especially during autumn and winter seasons. Most models agree in projecting a high probability of an increase in nutrient loadings with respect to current conditions. In summer and spring, instead, the large variability between different GCM–RCM results makes it impossible to identify a univocal direction of change. Results suggest that adaptive water resource planning should be based on multi-model ensemble approaches as they are particularly useful for narrowing the spectrum of plausible impacts and uncertainties on water resources.

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

2013 ◽  
Vol 152 (2) ◽  
pp. 205-216 ◽  
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.

scholarly journals Impacts of climate change on the first occurrence of the Light blight (Phytophthora infestans (Mont.) de Bary 1876)

2008 ◽  
Vol 56 (2) ◽  
pp. 267-276
Author(s):  
Zdeněk Žalud ◽  
M. Trnka ◽  
M. Dubrovský ◽  
E. Kocmánková
Keyword(s):  
Climate Change ◽  
Phytophthora Infestans ◽  
Crop Production ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Critical Number ◽  
State Institute ◽  
Climate Conditions ◽  
Global Circulation Models ◽  
Number Curve

The increase in the infestation pressure of various pathogens will be one the most important factors limiting the crop production under the future climate conditions. Weather driven NegFry model has been used for estimating future Phytophthora infestans occurrence at four experimental potato stations of the State Institute for Agriculture Supervision and Testing. Both the infestation dates of Phytophthora infestans occurrence and the shape of the critical number curve were analyzed using observed weather data as well as datasets constructed according to four climate change scenarios that were based on two global circulation models. The results show the shift of the infestation pressure to the beginning of the year and describe increasing trend of critical number reaching to detecting of the first Phyto­phtho­ra infestans occurrence for 2025 and 2050. Scenarios created according to HadCM and SRES – A2 seem to be more suitable for disease development.

scholarly journals ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan

2012 ◽  
Vol 370 (1962) ◽  
pp. 1121-1139 ◽  
Author(s):  
Toshichika Iizumi ◽  
Mikhail A. Semenov ◽  
Motoki Nishimori ◽  
Yasushi Ishigooka ◽  
Tsuneo Kuwagata
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Local Scale ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Emission Scenarios ◽  
Model Ensemble ◽  
Daily Weather Data

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981–2000 is assessed using several statistical tests and quantile–quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081–2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.

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