Frost Predictions in Dieng using the Outputs of Subseasonal to Seasonal (S2S) Model

Agromet ◽  
2021 ◽  
Vol 35 (1) ◽  
pp. 30-38
Author(s):  
Erna Nur Aini ◽  
Akhmad Faqih
Keyword(s):  
Air Temperature ◽  
Spatial Data ◽  
Extreme Event ◽  
Negative Impact ◽  
Seasonal Prediction ◽  
Crop Damage ◽  
Lapse Rate ◽  
Observation Data ◽  
Ecmwf Model ◽  
Minimum Air Temperature

Dieng volcanic highland, where located in Wonosobo and Banjarnegara regencies, has a unique frost phenomenon that usually occurs in the dry season (July, August, and September). This phenomenon may attract tourism, but it has caused losses to farmers due to crop damage. Information regarding frost prediction is needed in order to minimize the negative impact of this extreme event. This study evaluates the potential use of the Subseasonal to Seasonal (S2S) forecast dataset for frost prediction, with a focus on two areas where frost usually occurs, i.e. the Arjuna Temple and Sikunir Hill. Daily minimum air temperature data used to predict frost events was from the outputs of the ECMWF model, which is one of the models contributed in the Subseasonal to Seasonal prediction project (S2S). The minimum air temperature observation data from the Banjarnegara station was used in conjunction with the Digital Elevation Model Nasional (DEMNAS) data to generate spatial data based on the lapse rate function. This spatial data was used as a reference to downscale the ECMWF S2S data using the bias correction approach. The results of this study indicated that the bias-corrected data of the ECMWF S2S forecast was able to show the spatial pattern of minimum air temperature from observations, especially during frost events. The S2S prediction represented by the bias-corrected ECMWF model has the potential for providing early warning of frost events in Dieng, with a lead time of more than one month before the event.

scholarly journals Current state and tendencies of distribution of ground frosts within the territory of Ukraine

2017 ◽  
pp. 37-42
Author(s):  
S. V. Klok
Keyword(s):  
Temperature Field ◽  
Air Temperature ◽  
Extreme Values ◽  
Negative Impact ◽  
Observation Data ◽  
Current State ◽  
Weather Phenomenon ◽  
Minimum Air Temperature ◽  
Observation Period ◽  
Made In

The purpose of this work consists in identifying the main trends of present-day formation and distribution of ground frosts throughout Ukraine. For this purpose the analysis of a minimum air temperature field has been conducted based on observation data at 186 stations of Ukraine for the period from 1991 to 2014. It is known that extreme values of air temperature are much more informative than its average values. Therefore analyses of meteorological extreme values usually lead to more substantial and qualitative results. In the course of the work, occurrences of frost in April, May and September have been studied separately from each other while these three months are deemed to be the most dangerous in terms of frosts' frequency and negative impact. In order to identify trends to occurrence of this dangerous weather phenomenon a comparison of two decades of 1991-2000 and 2001-2010 has been made. In addition, the latest observation period of 2011-2014 has been considered separately taking into account the results of comparative analysis of two preceding decades. The results of the work indicate a decrease of number of September days having this dangerous weather phenomenon during the last few years. However, recurrence of frosts remains stably high in April while in May it appears to be high only in certain years. The obtained results also indicate the fact that the northern and northeastern territories of Ukraine appear to be the most vulnerable to frosts. Thus it should be noted that a threat of adverse consequences caused by ground frosts is still there and remains to be quite high, especially for agriculture.

scholarly journals Assessment of High Resolution Air Temperature Fields at Rocky Mountain National Park by Combining Scarce Point Measurements with Elevation and Remote Sensing Data

2020 ◽  
Vol 13 (1) ◽  
pp. 113
Author(s):  
Antonio-Juan Collados-Lara ◽  
Steven R. Fassnacht ◽  
Eulogio Pardo-Igúzquiza ◽  
David Pulido-Velazquez
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Air Temperature ◽  
Land Surface ◽  
National Park ◽  
Rocky Mountain ◽  
Rocky Mountain National Park ◽  
Temperature Fields ◽  
Lapse Rate ◽  
Validation Experiment

There is necessity of considering air temperature to simulate the hydrology and management within water resources systems. In many cases, a big issue is considering the scarcity of data due to poor accessibility and limited funds. This paper proposes a methodology to obtain high resolution air temperature fields by combining scarce point measurements with elevation data and land surface temperature (LST) data from remote sensing. The available station data (SNOTEL stations) are sparse at Rocky Mountain National Park, necessitating the inclusion of correlated and well-sampled variables to assess the spatial variability of air temperature. Different geostatistical approaches and weighted solutions thereof were employed to obtain air temperature fields. These estimates were compared with two relatively direct solutions, the LST (MODIS) and a lapse rate-based interpolation technique. The methodology was evaluated using data from different seasons. The performance of the techniques was assessed through a cross validation experiment. In both cases, the weighted kriging with external drift solution (considering LST and elevation) showed the best results, with a mean squared error of 3.7 and 3.6 °C2 for the application and validation, respectively.

scholarly journals Spring Frost Damage to Tea Plants Can Be Identified with Daily Minimum Air Temperatures Estimated by MODIS Land Surface Temperature Products

2021 ◽  
Vol 13 (6) ◽  
pp. 1177
Author(s):  
Peijuan Wang ◽  
Yuping Ma ◽  
Junxian Tang ◽  
Dingrong Wu ◽  
Hui Chen ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Frost Damage ◽  
Estimation Model ◽  
Spring Frost ◽  
Tea Plants ◽  
Elevation Model ◽  
Minimum Air Temperature

Tea (Camellia sinensis) is one of the most dominant economic plants in China and plays an important role in agricultural economic benefits. Spring tea is the most popular drink due to Chinese drinking habits. Although the global temperature is generally warming, spring frost damage (SFD) to tea plants still occurs from time to time, and severely restricts the production and quality of spring tea. Therefore, monitoring and evaluating the impact of SFD to tea plants in a timely and precise manner is a significant and urgent task for scientists and tea producers in China. The region designated as the Middle and Lower Reaches of the Yangtze River (MLRYR) in China is a major tea plantation area producing small tea leaves and low shrubs. This region was selected to study SFD to tea plants using meteorological observations and remotely sensed products. Comparative analysis between minimum air temperature (Tmin) and two MODIS nighttime land surface temperature (LST) products at six pixel-window scales was used to determine the best suitable product and spatial scale. Results showed that the LST nighttime product derived from MYD11A1 data at the 3 × 3 pixel window resolution was the best proxy for daily minimum air temperature. A Tmin estimation model was established using this dataset and digital elevation model (DEM) data, employing the standard lapse rate of air temperature with elevation. Model validation with 145,210 ground-based Tmin observations showed that the accuracy of estimated Tmin was acceptable with a relatively high coefficient of determination (R2 = 0.841), low root mean square error (RMSE = 2.15 °C) and mean absolute error (MAE = 1.66 °C), and reasonable normalized RMSE (NRMSE = 25.4%) and Nash–Sutcliffe model efficiency (EF = 0.12), with significantly improved consistency of LST and Tmin estimation. Based on the Tmin estimation model, three major cooling episodes recorded in the "Yearbook of Meteorological Disasters in China" in spring 2006 were accurately identified, and several highlighted regions in the first two cooling episodes were also precisely captured. This study confirmed that estimating Tmin based on MYD11A1 nighttime products and DEM is a useful method for monitoring and evaluating SFD to tea plants in the MLRYR. Furthermore, this method precisely identified the spatial characteristics and distribution of SFD and will therefore be helpful for taking effective preventative measures to mitigate the economic losses resulting from frost damage.

The cattle lice of Great Britain Part I. Biology, with special reference to Haematopinus eurysternus

Parasitology ◽  
1941 ◽  
Vol 33 (3) ◽  
pp. 331-342 ◽  
Author(s):  
H. J. Craufurd-Benson
Keyword(s):  
Life Cycle ◽  
Great Britain ◽  
Special Reference ◽  
Incubation Period ◽  
Air Temperature ◽  
Average Length ◽  
Starvation Period ◽  
Complete Life Cycle ◽  
Threshold Of Development ◽  
Minimum Air Temperature

1. The geographical distribution of cattle lice in Britain is recorded in detail. Bovicola bovis is the commonest and most widely distributed species in Britain.2. The incubation period for the eggs was found to be: Haematopinus eurysternus, 9–19 days (av. 12); Bovicola bovis, 7–10 days (av. 8); Linognathus vitula, 10–13 days; Solenopotes capillatus, 10–13 days. With eggs of H. eurysternus it was found that the higher the minimum air temperature the shorter was the incubation period.3. In H. eurysternus the average length of the instars was: 1st, 4 days; 2nd, 4 days; 3rd, 4 days; pre-oviposition period, 3–4 days. The average time for the complete life cycle, egg to egg, was 28 days.4. The maximum longevity of H. eurysternus on the host was: males, 10 days; females, 16 days. No males or females of H. eurysternus survived a starvation period of 72 hr. at 20° C. and R.H. 70 or 0–10° C. and R.H. 70–85; but some nymphs survived this period at 20° C. and R.H. 70, but none survived 96 hr. starvation.5. The maximum number of eggs recorded for one female was 24; and eggs were laid at the rate of 1–4 a day.6. The threshold of development of the eggs of H. eurysternus appears to be about 27·5° C.

Hydro-meteorological data preparation for ecosystem hydrological modelling in the riparian forest of Hidegvíz Valley experimental catchment

2021 ◽  
Author(s):  
Csenge Nevezi ◽  
Tamás Bazsó ◽  
Zoltán Gribovszki ◽  
Előd Szőke ◽  
Péter Kalicz
Keyword(s):  
Air Temperature ◽  
Meteorological Parameters ◽  
Extreme Event ◽  
Riparian Forest ◽  
Meteorological Data ◽  
Rain Gauge ◽  
Hydrological Modelling ◽  
Data Preparation ◽  
Air Humidity ◽  
Groundwater Levels

<p>In the Hidegvíz Valley experimental catchment in Hungary the meteorological data have been collected since the 1990s and used for various purposes including hydrological studies. Current research began in 2018–19, that aimed to reveal the connections between the hydrological and botanical characteristics in riparian forests and a wet meadow. Changes that occurred in both ecosystems in the groundwater levels, soil moisture and vegetation, showed that the local meteorological events influence these factors. Therefore we decided to analyse longer periods in which meteorological extremes<br>strongly influenced hydrological conditions and so status of ecosystems. Further measurements and their analysis were also required because more accuracy and detail were needed for future water balance modelling.</p><p>The measured data between 2017–2020 were chosen as a starting database. For the first analysis we selected three meteorological parameters, i. e. the precipitation, the air temperature, and the air humidity. These parameters were measured by automated instruments, except for the precipitation. We found that the automated tipping-bucket rain gauge needs validation by a manual measurement (Hellmann-type rain gauge), because the data that collected by the automated device will be invalid if the rain intensity is too high.</p><p>In 2017 and 2018, the annual precipitation was distributed evenly, but in the following two years we observed some extremes. In 2019 and<br>2020, the spring was especially dry, the lowest monthly sum was 1.2 mm in 2020 April. 2019 April was similar (19.5 mm), but after the drought<br>period intense rainfall events arrived in May, resulted a monthly total of 214.1 mm. Air temperature and air humidity has not been showed such extremes as the precipitation.</p><p>This study showed that detailed analysis of meteorological parameters is crucial for hydrological modelling data preparation because errors and extreme event can cause serious problems during modelling process and, also in case of evaluation of model results.</p><p>The research has been supported by the Ministry of Agriculture in Hungary.</p>

Toe Temperatures During Dartmoor Training

1988 ◽  
Vol 74 (3) ◽  
pp. 181-186
Author(s):  
S. P. L. Travis
Keyword(s):  
Surface Temperature ◽  
Ambient Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Factors Associated ◽  
Recording Period ◽  
Exposure To Cold ◽  
Main Factors ◽  
Minimum Air Temperature

AbstractThe surface temperature of eight Royal Marine recruits was monitored in the field during Autumn training on Dartmoor (minimum air temperature 4.5°C). The lowest skin temperature recorded was 6.1°C. One subject experienced a toe temperature below 10° for 5.5 hours and below 15°C for 12.6 hours during a 24 hour recording period. Ambient temperature and inactivity during exposure to cold were the main factors associated with low toe temperatures but individual responses varied widely.

Modelling pavement temperature for winter maintenance operations

2004 ◽  
Vol 31 (2) ◽  
pp. 369-378 ◽  
Author(s):  
Aly Sherif ◽  
Yasser Hassan
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Negative Impact ◽  
Weather Conditions ◽  
Statistical Modelling ◽  
Dew Point ◽  
Road Maintenance ◽  
Winter Maintenance ◽  
Pavement Surface ◽  
Pavement Temperature

Road and highway maintenance is vital for the safety of citizens and for enabling emergency and security services to perform their essential functions. Accumulation of snow and (or) ice on the pavement surface during the wintertime substantially increases the risk of road crashes and can have negative impact on the economy of the region. Recently, road maintenance engineers have used pavement surface temperature as a guide to the application of deicers. Stations for road weather information systems (RWIS) have been installed across Europe and North America to collect data that can be used to predict weather conditions such as air temperature. Modelling pavement surface temperature as a function of such weather conditions (air temperature, dew point, relative humidity, and wind speed) can provide an additional component that is essential for winter maintenance operations. This paper uses data collected by RWIS stations at the City of Ottawa to device a procedure that maximizes the use of a data batch containing complete, partially complete, and unusable data and to study the relationship between the pavement surface temperature and weather variables. Statistical models were developed, where stepwise regression was first applied to eliminate those variables whose estimated coefficients are not statistically significant. The remaining variables were further examined according to their contribution to the criterion of best fit and their physical relationships to each other to eliminate multicollinearities. The models were further corrected for the autocorrelation in their error structures. The final version of the developed models may then be used as a part of the decision-making process for winter maintenance operations.Key words: winter maintenance, pavement temperature, statistical modelling, RWIS.

scholarly journals Increase in Air Temperature in The Region of South Sumatra Province as the Indicator of Global Warming and the Effect on Transpiration of Lansium domesticum Corr.

2019 ◽  
Author(s):  
Ari Sugiarto ◽  
Hanifa Marisa ◽  
Sarno
Keyword(s):  
Global Warming ◽  
Air Temperature ◽  
Transpiration Rate ◽  
Temperature Increase ◽  
Secondary Data ◽  
Temperature Data ◽  
Randomized Design ◽  
Maximum Air Temperature ◽  
Lansium Domesticum ◽  
Minimum Air Temperature

Abstract Global warming is one of biggest problems faced in the 21st century. One of the impacts of global warming is that it can affect the transpiration rate of plants that °Ccur. This study purpose to see how much increase in air temperature that occurred in the region of South Sumatra Province and to know the effect of increase in ari temperature in the region of South Sumatra Province on transpiration rate of Lansium domesticum Corr. This study used a complete randomized design with 9 treatments (22.9 °C, 23.6 °C, 24.6 °C, 26.3 °C, 27 °C, 27.8 °C, 31.7 °C, 32.5 °C, and 32.9 °C) and 3 replications. Air temperature data as secondary data obtained from the Meteorology, Climatology and Geophysics Agency (MCGA) Palembang Climatology Station in South Sumatra Province. The measurement of transpiration rate is done by modified potometer method with additional glass box. The data obtained are presented in the form of tables and graphs. Transpiration rate (mm3/g plant/hour) at temperture 22.9 °C = 4.37, 23.6 °C = 7.03, 24.6 °C = 8.03, 26.3 °C = 10.11, 27 °C = 13.13, 27.8 °C = 17.87, 31.7 °C = 23.21, 32.5 °C= 25.45 and 32.9 °C= 27.24. At the minimum air temperature in the region of South Sumatra Province there is increase in air temperature of 1.5 °C, average daily air temperature increase 1.3 °C and maximum air temperature increase 1.2 °C.

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