• Journal of Forest and Environmental Science
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• v.40 no.2
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• pp.99-110
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• 2024

According to the REDD+ program, it is necessary to monitor, quantify, and report forest conditions in protected land areas. The objectives of this work were to quantify the average monthly aerial net primary productivity (ANPP_MONTH) of semi-arid Chaco Forest at Copo National Park (CNP), Santiago del Estero, Argentina, during the period 2000-2023, as well as its spatial distribution and relationship, and its use efficiency (RUE) of average monthly rainfall (AMR). The ANPP_MONTH model accounted for 90% of the seasonal variability from October to May, the average seasonal ANPP_MONTH was 145 tons of dry matter per hectare (t dm/ha), being the maximum in January with 192 t dm/ha and the minimum in May with 91 t dm/ha. The surface area covered by ANPP_MONTH exhibited a consistent positive trend from October to May (t test=15.65, p<0.01). Strong and significant direct relationships were found between ANPP_MONTH and AMRs, linear models explaining 90% and 96% of the variability, respectively. The results obtained become reference values for assessing the capacity of the forest systems to stock carbon for global warming mitigation and for monitoring and controlling their response to extreme climatic adversities. The average ANPP_MONTH reduces uncertainty when defining the thresholds to monitor and quantify ANPP and forest area, thus facilitating the detection of negative changes in land use in CNP. Such results evidence the National Parks Administration's high effectiveness for the maintenance of protected area and for the high ANPP of the FCHS of CNP in the period 2000-2023.

• Journal of the korean society of oceanography
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• v.34 no.1
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• pp.1-21
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• 1999

A two-layer quasi-geostrophic numerical model is used to investigate the temporal variability of the East Korea Warm Current (EKWC), especially the separation from the Korean coast and the generation of warm eddies. An attention is given on the active role of the nonlinear boundary layer process. For this, an idealized flat bottom model of the East Sea is forced with the annual mean wind curl and with the inflow-outflow specified at the Korea (Tsushima) and Tsugaru Straits. Two types of separation mechanisms are identified. The first one is influenced by the westward movement of the recirculating leg of the EKWC (externally driven separation),the second one is solely driven by the boundary layer dynamics (internally driven separation). However, these two processes are not independent, and usually coexist. It is hypothesized that 'internally driven separation' arises as the result of relative vorticity production at the wall, its subsequent advection via the EKWC, and its accumulation up to a critical level characterized by the separation of the boundary flow from the coast. It is found that the sharp southeastern corner of the Korean peninsula provides a favorable condition for the accumulation of relative vorticity. The separation of the EKWC usually accompanies the generation of a warm eddy with a diameter of about 120 km. The warm eddy has a typical layer-averaged velocity of 0.3 m/s and its lifespan is up to a year. In general, the characteristics of the simulated warm eddy are compatible with observations. A conclusion is therefore drawn that the variability of the EKWC is at least partially self-excited, not being influenced by any sources of perturbation in the forcing field, and that the likely source of the variability is the barotropic instability although the extent of contribution from the baroclinic instability remains unknown. The effects of the seasonal wind curl and inflow-outflow strength are also investigated.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.268-272
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• 2010

The research presented here represents a collaborative effort with the SFWMD on developing scenarios for future climate for the SFWMD area. The project focuses on developing methodology for simulating precipitation representing both natural quasi-oscillatory modes of variability in these climate variables and also the secular trends projected by the IPCC scenarios that are publicly available. This study specifically provides the results for precipitation modeling. The starting point for the modeling was the work of Tebaldi et al that is considered one of the benchmarks for bias correction and model combination in this context. This model was extended in the framework of a Hierarchical Bayesian Model (HBM) to formally and simultaneously consider biases between the models and observations over the historical period and trends in the observations and models out to the end of the 21st century in line with the different ensemble model simulations from the IPCC scenarios. The low frequency variability is modeled using the previously developed Wavelet Autoregressive Model (WARM), with a correction to preserve the variance associated with the full series from the HBM projections. The assumption here is that there is no useful information in the IPCC models as to the change in the low frequency variability of the regional, seasonal precipitation. This assumption is based on a preliminary analysis of these models historical and future output. Thus, preserving the low frequency structure from the historical series into the future emerges as a pragmatic goal. We find that there are significant biases between the observations and the base case scenarios for precipitation. The biases vary across models, and are shrunk using posterior maximum likelihood to allow some models to depart from the central tendency while allowing others to cluster and reduce biases by averaging. The projected changes in the future precipitation are small compared to the bias between model base run and observations and also relative to the inter-annual and decadal variability in the precipitation.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.605-622
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• 2021

Seasonal forecasting has numerous socioeconomic benefits because it can be used for disaster mitigation. Therefore, it is necessary to diagnose and improve the seasonal forecast model. Moreover, the model performance is partly related to the ocean model. This study evaluated the hindcast performance in the upper ocean of the Global Seasonal Forecasting System version 5-Global Couple Configuration 2 (GloSea5-GC2) using a multivariable integrated evaluation method. The normalized potential temperature, salinity, zonal and meridional currents, and sea surface height anomalies were evaluated. Model performance was affected by the target month and was found to be better in the Pacific than in the Atlantic. An increase in lead time led to a decrease in overall model performance, along with decreases in interannual variability, pattern similarity, and root mean square vector deviation. Improving the performance for ocean currents is a more critical than enhancing the performance for other evaluated variables. The tropical Pacific showed the best accuracy in the surface layer, but a spring predictability barrier was present. At the depth of 301 m, the north Pacific and tropical Atlantic exhibited the best and worst accuracies, respectively. These findings provide fundamental evidence for the ocean forecasting performance of GloSea5.

• Atmosphere
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• v.33 no.5
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• pp.531-548
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• 2023

We developed the Aviation Convective Index (ACI) for predicting deep convective area using the operational global Numerical Weather Prediction model of the Korea Meteorological Administration. Seasonally optimized ACI (ACI_SnOpt) was developed to consider seasonal variabilities on deep convections in Korea. Yearly optimized ACI (ACI_YrOpt) in Part 1 showed that seasonally averaged values of Area Under the ROC Curve (AUC) and True Skill Statistics (TSS) were decreased by 0.420% and 5.797%, respectively, due to the significant degradation in winter season. In Part 2, we developed new membership function (MF) and weight combination of input variables in the ACI algorithm, which were optimized in each season. Finally, the seasonally optimized ACI (ACI_SnOpt) showed better performance skills with the significant improvements in AUC and TSS by 0.983% and 25.641% respectively, compared with those from the ACI_YrOpt. To confirm the improvements in new algorithm, we also conducted two case studies in winter and spring with observed Convectively-Induced Turbulence (CIT) events from the aircraft data. In these cases, the ACI_SnOpt predicted a better spatial distribution and intensity of deep convection. Enhancements in the forecast fields from the ACI_YrOpt to ACI_SnOpt in the selected cases explained well the changes in overall performance skills of the probability of detection for both "yes" and "no" occurrences of deep convection during 1-yr period of the data. These results imply that the ACI forecast should be optimized seasonally to take into account the variabilities in the background conditions for deep convections in Korea.

• Journal of Environmental Science International
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• v.17 no.11
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• pp.1243-1253
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• 2008

The seasonal variations of picoplankton including Prochlorococcus, Synechococcus and Picoeukayotes around Ulneung Island were investigated by flow cytometry in spring, summer and autumn in 2006. All groups of picoplankton showed clear seasonal patterns in population abundance. Among the group, Synechococcus showed the most prominent seasonal variation during the study period. The maximal abundance of Synechococcus occurred in summer and the lowest in autumn. The seasonal distribution of Prochlorococcus displayed the reverse tendency with that of Synechococcus. The abundance of Prochlorococcus ranged from $2.9{\times}10^3$ cells/ml in summer to $311{\times}10^3$ cells/ml in autumn. However, the seasonal distribution of Picoeukaryotes was shown to be relatively constant, and the maximal abundance was $81.5{\times}10^3$ cells/ml in summer. The highest abundance of Picoeukaryotes occurred in summer and the lowest in autumn and the seasonal distribution in abundance of Picoeukaryotes showed a similar trend with that of Synechococcus. The estimated total carbon biomass of picoplankton were ranged from $74.7\;mg\;C/m^2$ to $1,055.9\;mg\;C/m^2$. The highest total carbon biomass occurred in summer, but lowest occurred in autumn. The pattern of the contribution of three picoplankton to total autotrophic picoplankton carbon is different. The contribution of Synechococcus to total autotrophic picoplankton carbon is increased to 75%, but the contribution of Prochlorococcus dropped to 12% in summer. The contribution of Picoeukaryotes is ranged from 24% in summer to 72.5% in spring.

• Ocean Systems Engineering
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• v.10 no.2
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• pp.181-199
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• 2020

Cyclone Heat Potential (CHP) is an essential parameter for accurate prediction of the intensity of tropical cyclones. The variability of the heat storage in the near-surface layers and the vertical stratification near the surface due to large fresh water inputs create challenges in predicting the intraseasonal and interannual evolution of monsoons and tropical cyclones in the Bay of Bengal. This paper for the first time presents the D26- referenced cyclone heat potential observed in the Bay of Bengal during the period 2012-17 based on the in-situ data collected from 5.5 million demanding offshore instrument-hours of operation in the Ocean Moored Buoy Network for Northern Indian Ocean (OMNI) buoy network by the National Institute of Ocean Technology. It is observed that the CHP in the Bay of Bengal varied from 0-220 kJ/㎠ during various seasons. From the moored buoy observations, a CHP of ~ 90 kJ/㎠ with the D26 isotherm of minimum 100m is favorable for the intensification of the post-monsoon tropical cyclones. The responses of the D26 thermal structure during major tropical cyclone events in the Bay of Bengal are also presented.

• Atmosphere
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• v.28 no.1
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• pp.1-13
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• 2018

Characteristics of wind resources of offshore and coastal regions were compared using wind data obtained from HeMOSU-1 (Herald of Meteorological and Oceanographic Special Unit-1) meteorological mast located at Southwestern Sea, and ground-based LiDAR (Light Detection And Ranging) at Gochang observation site near it. The analysis includes comparison of basic wind statistics such as mean wind speed, wind direction, power law exponent and their temporal variability as well as site assessment items for the wind power plant such as turbulence intensity and wind power density at the two observation sites. It was found that the wind at HeMOSU-1 site has lower diurnal and seasonal variability than that at Gochang site, which lead to smaller turbulence intensity. Overall, the results of the comparative analysis show that the wind resource at HeMOSU-1 site located offshore has more favorable condition for wind power generation than the wind resource at Gochang which shows nature of coastal area.

• Journal of Korea Water Resources Association
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• v.38 no.10 s.159
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• pp.885-894
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• 2005

Since the 1970s, rapid Industrialization has brought urbanization nationwide. In this paper, thirty one years data(1973-2003) ate used to evaluate variability of major cities. Before assessing the context between urbanization and variability of rainfall, the rural areas are selected to compare with urban ones. Thus, average, trends, variations, and nonparametric frequency analysis methods were employed for evaluating variation of annual precipitation, seasonal precipitation, 1 hour annual maximum design rainfall and 24 hour annual maximum design rainfall for both urban and rural areas. The result have shown that summer precipitation relatively increased In urban areas compared to that in rural areas.

• The Korean Journal of Quaternary Research
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• v.19 no.2
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• pp.50-54
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• 2005

Some basic summer precipitation features over East Asia during the $20^{th}-21^{st}$ century as simulated / projected by the 22 coupled climate models under the IPCC AR4 program are investigated. Keeping in view that these are climate runs without prescribed SSTs, models perform well in simulating the regional annual cycle, spatial patterns (not shown) and the inter-annual variability. The projections under the 1% increase in $CO_2$ compounded until reaching double and held constant thereafter reveal that (a) Precipitation is likely to increase in all the months in particular during the summer monsoon (JJA) months. (b) The mean summer monsoon rainfall can increase from 4.2 to 13.5% and its variability is also likely to increase in the warming world due to increase in $CO_2$ (c) Extreme excess and deficient seasonal monsoons are likely to become more intense (not shown here) (d) Once the increase in $CO_2$ is cut-off, the system will reach a state of equilibrium, and then the rate of increase in precipitation is also expected to remain constant.