• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.3
• /
• pp.252-261
• /
• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.38 no.3
• /
• pp.253-263
• /
• 1993

Climatological informations have not been fully utilized by agricultural research and extension workers in Korea due mainly to inaccessbilty to the archived climate data. This study was initiated to improve access to historical climate data gathered from 72 weather stations of Korea Meteorological Administration for agricultural applications by using a microcomputer-based methodology. The climatological elements include daily values of average, maximum and minimum temperature, relative humidity, average and maximum wind speed, wind direction, evaporation, precipitation, sunshine duration and cloud amount. The menu-driven, user-friendly data retrieval system(CLIDAS) provides quick summaries of the data values on a daily, weekly and monthly basis and selective retrieval of weather records meeting certain user specified critical conditions. Growing degree days and potential evapotranspiration data are derived from the daily climatic data, too. Data reports can be output to the computer screen, a printer or ASCII data files. CLIDAS can be run on any IBM compatible machines with Video Graphics Array card. To run the system with the whole database, more than 50 Mb hard disk space should be available. The system can be easily upgraded for further expansion of functions due to the module-structured design.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.14 no.3
• /
• pp.119-123
• /
• 2012

The duration of low temperature in winter season is one of the important agrometeorological characteristics in crop growing fields. This study was conducted to develop a method to estimate the duration of low-temperature with monthly meteorological data. Using daily meteorological data from 61 observation sites from 1981 to 2010, we analyzed the relationships between the averages of monthly temperature minima and the durations of low-temperature ranging from -15 to $5^{\circ}C$, The monthly mean of the January minimum air temperature was appropriate for theestimation of the durations of lowtemperature below $0^{\circ}C$. We tested a simple second order equation to predict durations of low-temperature. To apply the equation to various temperature ranges, we suggested two different equations for the estimation of coefficients a and b, which are dependent on the base temperatures from -15 to $0^{\circ}C$. Thevalidation of the equations using other daily meteorological datasets from 1971 to 2000 showed that they were appropriate for the range from -10 to $0^{\circ}C$, but underestimated at $-15^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.1
• /
• pp.40-49
• /
• 2013

Current service system of the Korea Meteorological Administration (KMA) for blooming date forecasting in spring depends on regression equations derived from long term observations in both temperature and phenology at a given station. This regression based system does not allow a timely correction or update of forecasts that are highly sensitive to fluctuating weather conditions. Furthermore, the system cannot afford plant responses to climate extremes which were not observed before. Most of all, this method may not be applicable to locations other than that which the regression equations were derived from. This note suggests a way to replace the location restricted regression equations with a thermal time based phenology model to complement the KMA blooming forecast system. Necessary parameters such as reference temperature, chilling requirement and heating requirement were derived from phenology data for forsythia, azaleas and Japanese cherry at 29 KMA stations for the 1951-1980 period to optimize spring phenology prediction model for each species. Best fit models for each species were used to predict blooming dates and the results were compared with the observed dates to produce a correction grid across the whole nation. The models were driven by the KMA's daily temperature data at a 5km grid spacing and subsequently adjusted by the correction grid to produce the blooming date maps. Validation with the 1971-2012 period data showed the RMSE of 2-3 days for Japanese cherry, showing a feasibility of operational service; whereas higher RMSE values were observed with forsythia and azaleas.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.1
• /
• pp.27-35
• /
• 2017

This research was to elucidate the generation method of daily precipitation data from monthly data. We applied a combined method of Markov chain and gamma distribution function using 4 specific parameters of ${\alpha}$, ${\beta}$, p(W/W) and p(W/D) for generation of daily rainfall data using daily precipitation data for the past 30 years which were collected from the country's 23 meteorological offices. Four parameters, applied to use for the combination method, were calculated by maximum likelihood method in location of 23 sites. There are high correlations of 0.99, 0.98 and 0.98 in rainfall days, rainfall probability and mean amount of daily rainfall between measured and simulated data in case of those parameters. In case of using parameters estimated from monthly precipitation, correlation coefficients in rainfall days, rainfall probability and mean amount of daily rainfall are 0.84, 0.83 and 0.96, respectively. We concluded that a combination method with parameter estimation from monthly precipitation data can be applied, in practical purpose such as assessment of climate change in agriculture and water resources, to get daily precipitation data in Korea.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.4
• /
• pp.275-278
• /
• 2006

Google Earth enables people to easily find information linked to geographical locations. Google Earth consists of a collection of zoomable satellite images laid over a 3-D Earth model and any geographically referenced information can be uploaded to the Web and then downloaded directly into Google Earth. This can be achieved by encoding in Google's open file format, KML (Keyhole Markup Language), where it is visible as a new layer superimposed on the satellite images. We used KML to create and share fine resolution gridded temperature data projected to 3 climatological normal years between 2011-2100 to visualize the site-specific warming and the resultant earlier blooming of spring flowers over the Korean Peninsula. Gridded temperature and phonology data were initially prepared in ArcGIS GRID format and converted to image files (.png), which can be loaded as new layers on Google Earth. We used a high resolution LCD monitor with a 2,560 by 1,600 resolution driven by a dual link DVI card to facilitate visual effects during the demonstration.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.4
• /
• pp.217-224
• /
• 2010

This study was carried out to quantify potential effects of the surrounding ocean on the observed air temperature at coastal weather stations in the Korean Peninsula. Daily maximum and minimum temperature data for 2001-2009 were collected from 66 Korea Meteorological Administration (KMA) stations and the monthly averages were calculated for further analyses. Monthly data from 27 inland sites were used to generate a gridded temperature surface for the whole Peninsula based on an inverse distance weighting and the local temperature at the remaining 39 sites were estimated by recent techniques in geospatial climatology which are widely used in correction of small - scale climate controls like cold air drainage, urban heat island, topography as well as elevation. Deviations from the observed temperature were regarded as the 'apparent' sea effect and showed a quasi-logarithmic relationship with the distance of each site from the nearest coastline. Potential effects of the sea on daily temperature might exceed $6.0^{\circ}C$ cooling in summer and $6.5^{\circ}C$ warming in winter according to this relationship. We classified 25 sites within the 10 km distance from the nearest coastline into 'coastal sites' and the remaining 15 'fringe sites'. When the average deviations of the fringe sites ($0.5^{\circ}C$ for daily maximum and $1.0^{\circ}C$ for daily minimum temperature) were used as the 'noise' and subtracted from the 'apparent' sea effects of the coastal sites, maximum cooling effects of the sea were identified as $1.5^{\circ}C$ on the west coast and $3.0^{\circ}C$ on the east and the south coast in summer months. The warming effects of the sea in winter ranged from $1.0^{\circ}C$ on the west and $3.5^{\circ}C$ on the south and east coasts.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.14 no.4
• /
• pp.155-160
• /
• 2012

This study was conducted to develop a practical method for estimating the extremes of minimum air temperature with given return-period based on the frequency distribution of daily minimum air temperature in January. Daily temperature data were collected from 61 meteorological observatories country-wide from 1961 to 2010. Most of daily minimum temperature in January could be represented by a normal-distribution, so it is possible to predict stochastically the lowest temperature by the mean and standard deviation. We developed a quadratic function to estimate standard deviation in terms of daily minimum temperature in January. Also, we introduced a coefficient which can be used to predict an extreme of minimum temperature with mean and standard deviation, and is dependent on return-periods. Using this method, we were able to reproduce the past 30-year extremes with an error of 1.1 on average and 5.3 in the worst case.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.1
• /
• pp.1-9
• /
• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.16 no.4
• /
• pp.396-402
• /
• 2014

The spring season in Korea features a dynamic landscape with a variety of flowers such as magnolias, azaleas, forsythias, cherry blossoms and royal azaleas flowering sequentially one after another. However, the narrowing of south-north differences in flowering dates and those among the flower species was observed in 2014, taking a toll on economic and shared communal values of seasonal landscape. This study was carried out to determine whether the 2014 incidence is an outlier or a mega trend in spring phenology. Data on flowering dates of forsythias and cherry blossoms, two typical spring flower species, as observed for the recent 60 years in 6 weather stations of Korea Meteorological Administration (KMA) indicate that the difference spanning the flowering date of forsythias, the flower blooming earlier in spring, and that of cherry blossoms that flower later than forsythias was 30 days at the longest and 14 days on an average in the climatological normal year for the period 1951-1980, comparing with the period 1981-2010 when the difference narrowed to 21 days at the longest and 11 days on an average. The year 2014 in particular saw the gap further narrowing down to 7 days, making it possible to see forsythias and cherry blossoms blooming at the same time in the same location. 'Cherry blossom front' took 20 days in traveling from Busan, the earliest flowering station, to Incheon, the latest flowering station, in the case of the 1951-1980 normal year, while 16 days for the 1981-2010 and 6 days for 2014 were observed. The delay in flowering date of forsythias for each time period was 20, 17, and 12 days, respectively. It is presumed that the recent climate change pattern in the Korean Peninsula as indicated by rapid temperature hikes in late spring contrastive to slow temperature rise in early spring immediately after dormancy release brought forward the flowering date of cherry blossoms which comes later than forsythias which flowers early in spring. Thermal time based heating requirements for flowering of 2 species were estimated by analyzing the 60 year data at the 6 locations and used to predict flowering date in 2014. The root mean square error for the prediction was within 2 days from the observed flowering dates in both species at all 6 locations, showing a feasibility of thermal time as a prognostic tool.