scholarly journals An Evaluation of Temperature-Based Agricultural Indices Over Korea From the High-Resolution WRF Simulation

2021 ◽  
Vol 9 ◽  
Author(s):  
Eun-Soon Im ◽  
Subin Ha ◽  
Liying Qiu ◽  
Jina Hur ◽  
Sera Jo ◽  
...  
Keyword(s):  
Heat Stress ◽  
High Resolution ◽  
Dynamical Downscaling ◽  
Initial Conditions ◽  
Added Value ◽  
Stress Index ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Hourly Temperature

This study evaluates the performance of dynamical downscaling of global prediction generated from the NOAA Climate Forecast System (CFSv2) at subseasonal time-scale against dense in-situ observational data in Korea. The Weather Research and Forecasting (WRF) double-nested modeling system customized over Korea is adopted to produce very high resolution simulation that presumably better resolves geographically diverse climate features. Two ensemble members of CFSv2 starting with different initial conditions are downscaled for the summer season (June-July-August) during past 10-year (2011–2020). The comparison of simulations from the nested domain (5 km resolution) of WRF and driving CFSv2 (0.5°) clearly demonstrates the manner in which dynamical downscaling can drastically improve daily mean temperature (Tmean) and daily maximum temperature (Tmax) in both quantitative and qualitative aspects. The downscaled temperature not only better resolves the regional variability strongly tied with topographical elevation, but also substantially lowers the systematic cold bias seen in CFSv2. The added value from the nested domain over CFSv2 is far more evident in Tmax than in Tmean, which indicates a skillful performance in capturing the extreme events. Accordingly, downscaled results show a reasonable performance in simulating the plant heat stress index that counts the number of days with Tmax above 30°C and extreme degree days that accumulate temperature exceeding 30°C using hourly temperature. The WRF simulations also show the potential to capture the variation of Tmean-based index that represents the accumulation of heat stress in reproductive growth for the mid-late maturing rice cultivars in Korea. As the likelihood of extreme hot temperatures is projected to increase in Korea, the modeling skill to predict the ago-meteorological indices measuring the effect of extreme heat on crop could have significant implications for agriculture management practice.

scholarly journals The Attribution of Land–Atmosphere Interactions on the Seasonal Predictability of Drought

2015 ◽  
Vol 16 (2) ◽  
pp. 793-810 ◽  
Author(s):  
Joshua K. Roundy ◽  
Eric F. Wood
Keyword(s):  
Statistical Models ◽  
Initial Conditions ◽  
Seasonal Prediction ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Seasonal Predictability ◽  
Climate Forecast System ◽  
Drought Prediction ◽  
Intermountain Region

Abstract Drought has significant social and economic impacts that could be reduced by preparations made possible through seasonal prediction. During the convective season, when the potential of extreme drought is the highest, the soil moisture can provide a means of improved predictability through land–atmosphere interactions. In the past decade, there has been a significant amount of work aimed at better understanding the predictability of land–atmosphere interactions. One such approach classifies the interactions between the land and the atmosphere into coupling states. The coupling states have been shown to be persistent and were used to demonstrate the existence of strong biases in the coupling of the NCEP Climate Forecast System, version 2 (CFSv2). In this work, the attribution of the coupling state on the seasonal prediction of precipitation and temperature and the extent to which the bias in the coupling state hinders the prediction of drought is analyzed. This analysis combines the predictions from statistical models with the predictions from CFSv2 as a means to isolate and attribute the predictability. The results indicate that the intermountain region is a hotspot for seasonal prediction because of local persistence of initial conditions. In addition, the local persistence of initial conditions provides some level of drought prediction; however, accounting for the spatial interactions provides a more complete prediction. Furthermore, the statistical models provide more skillful predictions of precipitation during drought than the CFSv2; however, the CFSv2 predictions are more skillful for daily maximum temperature during drought. The implication, limitations, and extensions of this work are also discussed.

Summer infertility in pigs: its incidence and characteristics in an Australian commercial piggery

1978 ◽  
Vol 18 (94) ◽  
pp. 698 ◽  
Author(s):  
AM Paterson ◽  
I Barker ◽  
DR Lindsay
Keyword(s):  
Heat Stress ◽  
High Temperature ◽  
Litter Size ◽  
Ovarian Function ◽  
Embryonic Mortality ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Fertilization Failure ◽  
Summer Temperatures

The records of five years' production in an 800 sow commercial piggery were examined and the relationships between summer temperatures, returns to service and litter size were considered. When mean daily maximum temperature exceeded 32�C during the week of service there was an increase in the number of sows failing to hold to service. The number of sows that returned to service 15-25 days after mating remained constant throughout the year, and summer infertility was characterized by an increase in the number of sows that exhibited extended, irregular return-to-service intervals. The litter size of sows that conceived during the period of summer infertility was not significantly different from that of sows conceiving at other times of the year. The data suggest that summer infertility is not due simply to fertilization failure, embryonic mortality or an increased incidence of abortions in sows mated during periods of high temperature. Neither does boar fertility appear to be in question. It seems most likely that heat stress around the time of mating may affect ovarian function, resulting in temporary infertility and an endocrine imbalance, which causes delayed, irregular returns to oestrus.

Comparison of MK-PRISM according to horizontal resolution in South Korea

2020 ◽  
Author(s):  
Maeng-Ki Kim ◽  
Jeong Sang ◽  
Ji-hyun Yun ◽  
Ji-Seon Oh
Keyword(s):  
High Resolution ◽  
Group Performance ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Data Sets ◽  
Grid Data ◽  
The Impact ◽  
Resolution Data

<p>In this study, we produced grid climate data sets of 1km×1km and 5km×5km horizontal resolutions based on MK (Modified Korean)-PRISM (Parameter-elevation Regressions on Independent Slopes Model), a statistical method that can estimate grid data of horizontal high-resolution using observational station data in Korea. To compare the MK-PRISM performance according to resolution, RMSEs of 1km resolution data and 5km resolution data were calculated and analyzed. The RMSEs of the two data sets were similar, but the results classified according to the elevation were different. The 1km high resolution estimated data was shown to better reflect the impact of the terrain for the daily mean temperature and daily maximum temperature, whereas the difference between the two data sets for daily minimum temperature was not statistically significant at each elevation. Furthermore, we also divided the temperature data into 9-classes based on the observed temperatures, and then compared the estimated performance of the two data sets according to elevation. For the low temperature group, performance of the 1 km resolution data at high elevations outperformed that of the 5 km resolution data, regardless of the season. In addition, we have verified the improved PRIDE (PRism based Dynamic downscaling Error correction) model, which can produce future high-resolution scenarios data using the results of RCM and MK-PRISM.</p>

scholarly journals Assessing the Climatological Relationship between Heatstroke Risk and Heat Stress Indices in 47 Prefectures in Japan

GeoHazards ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 321-331
Author(s):  
Yuki Iwamoto ◽  
Yukitaka Ohashi
Keyword(s):  
Heat Stress ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Index ◽  
Daily Maximum ◽  
Stress Indices ◽  
Wet Bulb Globe Temperature ◽  
Thermal Climate ◽  
Globe Temperature ◽  
Northern Japan

This study provides a decade-long link between summer heatstroke incidence and certain heat stress indices in 47 prefectures of Japan. The results for each prefecture were determined from the age-adjusted heatstroke incidence rate (TRadj) with heatstroke patients transported by ambulance, as well as from the daily maximum temperature (TEMPmax), maximum wet-bulb globe temperature (WBGTmax), and maximum universal thermal climate index (UTCImax) recorded from July to September of 2010–2019. The UTCImax relatively increased the vulnerability in many prefectures of northern Japan more distinctly than the other indices. In the following analysis, the ratio of the TRadj of the hottest to coolest months using the UTCImax was defined as the heatstroke risk of the hottest to coolest (HRHC). Overall, the HRHC varied approximately from 20 to 40 in many prefectures in the past decade. In contrast, for the same analysis performed in each month, HRHC ratios in July and August fell within 2–4 in many prefectures, whereas in September, the average and maximum HRHC ratios for all prefectures were 7.0 and 32.4, respectively. This difference can be related to the large difference in UTCImax between the maximum and minimum for a decade.

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

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