Climate change effects on hydrometeorological compound events over southern Norway

Compound events are characterized as a combination of multiple drivers and/or hazards which contributes to societal, economical or environmental risk. In southern Norway, hydrometeorological compound events can trigger severe floods, for instance the joint occurrence of rainfall and snowmelt in south-eastern Norway in 1995 and 2013. &#160;Due to this high impact, the investigation of compound events is important, but is hampered by some limiting factors. The multivariate character and the associated very rare occurrence of these events require a large database in order to conduct statistically robust investigations, whereas the available meteorological observations are too scarce in space and time. With this current study, we present a quantile-based framework to define and examine compound events within a single model initial condition large ensemble (SMILE). To overcome the limitation of data scarcity, we use 50 high-resolution climate simulations from the SMILE CRCM5-LE to investigate two hydrometeorological compound event types in southern Norway:(1) Heavy rainfall on saturated soil during the summer months (June, July, August, September),(2) Concurrent heavy rainfall and snowmelt (also often referred to as rain-on-snow).Furthermore, the application of climate model data enables us to quantify the impact of climate change on the frequency and spatial distribution of both types of compound events. Thereby, we compare current climate conditions (1980-2009) with future conditions (2070-2099) under the high-emission scenario RCP 8.5. We find that the frequency of heavy rainfall on saturated soil increases by 38% until 2070-2099 on average. In contrast, the occurrence probability of rain-on-snow is projected to decrease by 48% over the whole study area, largely driven by decreases in snowfall. The spatial patterns of both events are found to shift. Additionally, we assess the range of the natural variability of the drivers and of the compound event probability within the 50 members of the CRCM5-LE. The univariate spread of the meteorological drivers is found to be relatively small, whereas the occurrence probability of both compound events shows a high inter-member variability. Hence, we conclude that the frequency of the joint occurrence of the contributing drivers is highly variable, which is why a SMILE is needed to assess this probability.Our current work shows the limitations of regional climate models, stressing the need for even higher-resolution setups to resolve the complex topography of Norway. However, it also highlights the benefits of SMILE simulations for the analysis of compound events.

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Climate Change in Queensland's Grazing Lands: Ii. An Assessment of the Impact on Animal Production From Native Pastures.

The Rangeland Journal ◽

10.1071/rj9980177 ◽

1998 ◽

Vol 20 (2) ◽

pp. 177 ◽

Cited By ~ 41

Author(s):

WB Hall ◽

GM Mckeon ◽

JO Carter ◽

KA Day ◽

SM Howden ◽

...

Keyword(s):

Climate Change ◽

Carrying Capacity ◽

Animal Production ◽

Limiting Factors ◽

Climate Change Scenarios ◽

Stock Management ◽

Grazing Land ◽

Change Models ◽

Native Pastures ◽

The Impact

The 160 million ha of grazing land in Queensland support approximately 10 million beef equivalents (9.8 million cattle and 10.7 million sheep) with treed and cleared native pastures as the major forage source. The complexity of these biophysical systems and their interaction with pasture and stock management, economic and social forces limits our ability to easily calculate the impact of climate change scenarios. We report the application of a systems approach in simulating the flow of plant dry matter and utilisation of forage by animals. Our review of available models highlighted the lack of suitable mechanistic models and the potential role of simple empirical relationships of utilisation and animal production derived from climatic and soil indices. Plausible climate change scenarios were evaluated by using a factorial of rainfall (f 10%) * 3260C temperature increase * doubling CO, in sensitivity studies at property, regional and State scales. Simulation of beef cattle liveweight gain at three locations in the Queensland black speargrass zone showed that a *lo% change in rainfall was magnified to be a f 15% change in animal production (liveweight gain per ha) depending on location, temperature and CO, change. Models of 'safe' carrying capacity were developed from property data and expert opinion. Climate change impacts on 'safe' carrying capacity varied considerably across the State depending on whether moisture, temperature or nutrients were the limiting factors. Without the effect of doubling CO,, warmer temperatures and +lo% changes in rainfall resulted in -35 to +70% changes in 'safe' carrying capacity depending on location. With the effect of doubling CO, included, the changes in 'safe' carrying capacity ranged from -12 to +115% across scenarios and locations. When aggregated to a whole-of-State carrying capacity, the combined effects of warmer temperature, doubling CO, and +lo% changes in rainfall resulted in 'safe' carrying capacity changes of +3 to +45% depending on rainfall scenario and location. A major finding of the sensitivity study was the potential importance of doubling CO, in mitigating or amplifying the effects of warmer temperatures and changes in rainfall. Field studies on the impact of CO, are therefore a high research priority. Keywords: climate change, Queensland, simulation, rangelands, beef production, cattle, carrying capacity, CO,, utilisation

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Climate Change Perceptions and Adaptations for Dairy Cattle Farmers in Jordan: Case Study in North East Region -Al-Dhulel Area

New Medit ◽

10.30682/nm2102g ◽

2021 ◽

Vol 20 (2) ◽

Author(s):

Keyword(s):

Climate Change ◽

Dairy Cattle ◽

Adaptation Strategies ◽

Limiting Factors ◽

Dairy Farmers ◽

North East ◽

Change Perceptions ◽

East Region ◽

Change Impact ◽

The Impact

"This study was designed to investigate how dairy farmers of AL-Dhulel cooperative Dairy Society (ACDS) perceive climate change, the adaptation strategies adopted by farmers to cope with the impact of climate change and the barriers to the adoption of these strategies. A 92 dairy farmers provided with a questionnaire that was developed to collect the data and covered farmers perception, adaptation strategies, and the barriers facing them towards adopting the strategies. The personal interviews with the farmers were performed during early January, 2020. The data was analyzed using the Statistical Package for Social Sciences (SPSS). The main result obtained from the study that most of dairy farmers were aware of the climate change impact on dairy cattle performance and health. Furthermore, the adaptation strategies that was suggested has limiting factors according to farmers as a result of governmental and agricultural institutions restriction polices. Therefore, recommendations regarding new polices was suggested to facilitate the way of getting benefit from grants and financial support for improving dairy farms and to mitigate the effect of climate change on dairy cattle."

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Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator

Earth System Dynamics ◽

10.5194/esd-12-621-2021 ◽

2021 ◽

Vol 12 (2) ◽

pp. 621-634

Author(s):

Manuela I. Brunner ◽

Eric Gilleland ◽

Andrew W. Wood

Keyword(s):

Climate Change ◽

United States ◽

The United States ◽

Weather Generator ◽

Spatial Extent ◽

Event Analysis ◽

Temperature And Precipitation ◽

Compound Event ◽

Compound Events ◽

Variable Weather

Abstract. Compound hot and dry events can lead to severe impacts whose severity may depend on their timescale and spatial extent. Despite their potential importance, the climatological characteristics of these joint events have received little attention regardless of growing interest in climate change impacts on compound events. Here, we ask how event timescale relates to (1) spatial patterns of compound hot–dry events in the United States, (2) the spatial extent of compound hot–dry events, and (3) the importance of temperature and precipitation as drivers of compound events. To study such rare spatial and multivariate events, we introduce a multi-site multi-variable weather generator (PRSim.weather), which enables generation of a large number of spatial multivariate hot–dry events. We show that the stochastic model realistically simulates distributional and temporal autocorrelation characteristics of temperature and precipitation at single sites, dependencies between the two variables, spatial correlation patterns, and spatial heat and meteorological drought indicators and their co-occurrence probabilities. The results of our compound event analysis demonstrate that (1) the northwestern and southeastern United States are most susceptible to compound hot–dry events independent of timescale, and susceptibility decreases with increasing timescale; (2) the spatial extent and timescale of compound events are strongly related to sub-seasonal events (1–3 months) showing the largest spatial extents; and (3) the importance of temperature and precipitation as drivers of compound events varies with timescale, with temperature being most important at short and precipitation at seasonal timescales. We conclude that timescale is an important factor to be considered in compound event assessments and suggest that climate change impact assessments should consider several timescales instead of a single timescale when looking at future changes in compound event characteristics. The largest future changes may be expected for short compound events because of their strong relation to temperature.

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Space-time dependence of compound hot-dry events in the United States: assessment using a multi-site multi-variable weather generator

10.5194/esd-2021-5 ◽

2021 ◽

Author(s):

Manuela I. Brunner ◽

Eric Gilleland ◽

Andrew W. Wood

Keyword(s):

Climate Change ◽

United States ◽

Time Scale ◽

The United States ◽

Weather Generator ◽

Spatial Extent ◽

Temperature And Precipitation ◽

Compound Event ◽

Compound Events ◽

Variable Weather

Abstract. Compound hot and dry events can lead to severe impacts whose severity may depend on their time scale and spatial extent. Despite their potential importance, the climatological characteristics of these joint events have received little attention regardless of growing interest in climate change impacts on compound events. Here, we ask how event time scale relates to (1) spatial patterns of compound hot-dry events in the United States, (2) the spatial extent of compound hot-dry events, and (3) the importance of temperature and precipitation as drivers of compound event occurrence. To study such rare spatial and multivariate events, we introduce a multi-site multi-variable weather generator (PRSim.weather), which enables generation of a large number of spatial compound hot-dry events. We show that the stochastic model realistically simulates distributional and temporal autocorrelation characteristics of temperature and precipitation at single sites, dependencies between the two variables, spatial correlation patterns, and spatial heat and drought indicators and their co-occurrence probabilities. The results of our compound event analysis demonstrate that (1) the Northwestern and Southeastern United States are most susceptible to compound hot-dry events independent of time scale and susceptibility decreases with increasing time scale, (2) the spatial extent and time scale of compound events are strongly related with sub-seasonal events (1–3 months) showing the largest spatial extents, and (3) the importance of temperature and precipitation as drivers of compound events varies with time scale where temperature is most important at short and precipitation at seasonal time scales. We conclude that time scale is an important factor to be considered in compound event assessments and suggest that climate change impact assessments should consider several instead of a single time scale when looking at future changes in compound event characteristics. The largest future changes may be expected for short compound events because of their strong relation to temperature.

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Impacts of Climate Change on Rainfall Indices Estimation in Some of Subbasins West of Iran

10.20944/preprints201705.0089.v2 ◽

2017 ◽

Author(s):

Hadi Nazaripouya

Keyword(s):

Climate Change ◽

Heavy Rainfall ◽

Climate Models ◽

Greenhouse Gas Emission ◽

Coupled Model ◽

Impact Of Climate Change ◽

Intensity Index ◽

Hamedan Province ◽

Relative Change ◽

The Impact

Future projections from climate models and recent studies shows impact of climate change on rainfall indices estimation. This study assesses the simulations of rainfall indices based on the Coupled Model Intercomparison Project CMIP5 and CMIP3 in the some of subbasin Hamedan Province West of Iran. The analysis of the rainfall indices are: simple rainfall intensity, very heavy rainfall days, maximum one-day rainfall and rainfall frequency has been carried out in this study to evaluating the impact of climate change on rainfall indices events. Relative change in three rainfall indices is investigated by GCMs under various greenhouse gas emission scenarious A1B and B1 and RCP8.5, RCP8.5 scenarios for the future periods 2020–2045 and 2045-2065. The ﬁnal results show that each of rainfall indices differs in stations under the three GCMs model (GIAOM, MIHR, MPEH5) and emission scenarios A1B and B1, and RCP2.5, RCP8.5 scenarios. Relative change of daily intensity index varies from -9.93% - 25%, very heavy rainfall days 20.71% - 25.9% and yearly rainfall depth -15.71% - 13% can be observed at study area in 50y for future periods (2046–2065). Rainfall indices of sum wet days, nday >1mm and maximum one-day rainfall are projected to decrease under the senariuos B1,A1B and sum wet days, simple daily intensity and heavy Rainfall days>10 projected to decrease under the RCP2.6.

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Impact of Climate Change on Flood Hazard at Airports on Pacific Islands: A Case Study of Faleolo International Airport, Samoa

Journal of Disaster Research ◽

10.20965/jdr.2021.p0351 ◽

2021 ◽

Vol 16 (3) ◽

pp. 351-362

Author(s):

Lianhui Wu ◽

Kenji Taniguchi ◽

Yoshimitsu Tajima ◽

◽

Keyword(s):

Climate Change ◽

Sea Level ◽

Heavy Rainfall ◽

Flood Hazard ◽

Drainage System ◽

Fringing Reef ◽

Impact Of Climate Change ◽

International Airport ◽

The Impact

Climate change is believed to have increased the intensity and frequency of heavy rainfall, and also to have caused sea level rises over this century and beyond. There is widespread concern that small-island nations are particularly vulnerable to increasing risk of inland flood due to such climate change. Understanding the impact of climate change on flood hazard is of great importance for these countries for the development of better protection and adaptation strategies. This study conducted a case study focusing on the impact of climate change on flood hazard at Faleolo International Airport (FIA), Samoa. FIA is a typical small islands airport, located on the lowland along the coast fronted by a fringing reef. Annual maximum daily rainfalls for different return periods were first estimated for the present and future climate around FIA. The estimated rainfalls were input as the forcing of a two-dimensional flood inundation model to investigate the flooding behavior and effectiveness of probable drainage systems. Results showed that a part of the runway can be inundated under heavy rainfall. Construction of drainage pipes significantly contributes to reducing the flood hazard level. Sensitivity analysis showed that the astronomical tide level has relatively little influence on the performance of the drainage system, while the combination of sea level rise and the sea level anomaly induced by stormy waves on the fringing reef could have non-negligible impacts on the drainage system. Location of the drainage pipe is also important to effectively mitigate flooding. The time-concentration of torrential rainfall may also significantly impact the overall performance of the drainage system.

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Impact of Climate Change on Rainfall Indices Estimation in Some of Subbasins West of Iran

10.20944/preprints201705.0089.v1 ◽

2017 ◽

Author(s):

Hadi Nazaripouya

Keyword(s):

Climate Change ◽

Heavy Rainfall ◽

Climate Models ◽

Greenhouse Gas Emission ◽

Coupled Model ◽

Climate Extremes ◽

Impact Of Climate Change ◽

Model Ensembles ◽

Hamedan Province ◽

The Impact

Weather and climate extremes affect every facet of society, economies, environments and cultures. Future projections from climate models and recent studies shows impact of climate change on rainfall indices estimation.The purpose of this study is thus to document changes in indices that are calculated in a consistent manner as simulated in the CMIP3 and CMIP5 model ensembles for analyzing impacts of climate change on cachment rainfall indices the some of subbasin Hamedan Province West of Iran. This study assesses the simulations of rainfall indices based on the Coupled Model Intercomparison Project CMIP5 and CMIP3. The analysis of the rainfall indices are : simple rainfall intensity, very heavy rainfall days , maximum one-day rainfall and rainfall frequency has been carried out in this study to evaluating the impact of climate change on rainfall indices events. Relative change in three rainfall indices is investigated by GCMs under various greenhouse gas emission scenarious A1B and B1 and RCP8.5, RCP8.5 scenarios for the future periods 2020–2045 and 2045-2065. Rainfall indices of sum wet days , nday >1mm and maximum one-day rainfall are projected to decrease under the senariuos B1,A1B and sum wet days , simple daily intensity and heavy Rainfall days>10 projected to decrease under the RCP2.6 .

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