Prediction for coastal strong current

This data set shows characteristics change of ‘Kyucho’ caused by global warming. The Kyucho is Japanese word used among fisherman, means coastal strong current with potential of destroying fishing set-nets set along the Japanese coast. We used Global warming calculation product calculated by using SI-CAT02 that was ocean model whose horizontal resolution was 2km provided by Si-cat project. We adopted extracting method of Kyucho used for ‘Realtime prediction system of Kyucho’ operated by Fisheries Research Agency Japan to extract Kyucho event from the SI-cat02 product. Followings are outline of the method: 1) Averaged value and standard deviation in each grid were estimated by using data from 2001 to 2014 calculated by hindcast calculation version of Si-cat02; 2) Current speeds calculated by prediction/global warming calculation version of Si-cat02 were standardized by using 2 values indicated in 1) (The standardized vale was called Kyucho index). Temporal resolution of the current data of Si-cat02 was 1 hour. 4 values were estimated: (1) Strength of Kyucho, (2) Frequency of Kyucho occurrence, (3) Duration of Kyucho threat and (4) Month with highest frequency of Kyucho event. Following shows the data stored: (0)Kyucho Index # Kyucho Index (binary) kyucho/kindex └── kindex_YYYY_z08.out (YYYY=year) # Current speed of current averaged from 2006 to 2010 (binary) # These were used for Kyscho index calculation kyucho/uvave_sd └── uvmagnitude_aveall_k08_2006-2010.out # Standard deviation current from current averaged from 2006 to 2010(binary) # These were used for Kyscho index calculation kyucho/uvave_sd └── uv_sdall_k08_2006-2010.out (1)Strength of Kyucho (Maximum value of Kyucho Index) # Time series of strength of Kyucho of each region (text) # Yearly averaged values within each region kyucho/kindex_amplitude_timeseries └── ??_*.dat (??:Number of region，*:Name of region) # Increasing trends of Kyucho strength caused by global warming (binary) # Trend value estimated by linear regression by using kindex_amplitude_timeseries kyucho/kindex_amplitude └── YBGN-YEND‗08.bin (Trend values between YBGN and YEND) (2) Frequency of Kyucho occurrence # Frequency of Kyucho through a year (binary) #　Count number of Kyucho event whose Kyucho Index was over 3 kyucho/count_kindex └── threshold3.0_YYYY_z08.out (YYYY=year) # Time series of frequency of Kyucho of each region (text) kyucho/kindex_frequency_timeseries └── ??_*.dat (??:Number of region，*:Name of region) # Increasing trends of Kyucho frequency caused by global warming (binary) # Trend value estimated by linear regression by using kindex_frequency_timeseries kyucho/kindex_frequency └── YBGN-YEND‗08.bin (Trend values between YBGN and YEND) (3) Duration of Kyucho threat # Duration of Kyucho threat [month] (binary) # Averaged values of duration of Kyucho threat between YBGN and YEND. Durations of Kyucho threat were determined by quartile deviations estimated by using Kyucho event whose Kyucho Index was over 3 in each year. kyucho/kindex_period └── YBGN-YEND.bin (Averaged values between YBGN and YEND) # Increasing of duration of Kyucho threat caused by global warming [month] (binary) # Increasing of kindex_period caused by global warming kyucho/kindex_period_diff └── YBGN2-YEND2_YBGN1-YEND1.bin (Values obtained by subtracting (YBGN1-YEND1) from (YBGN2-YEND2)) (4) Month with highest frequency of Kyucho event # Month with highest frequency of Kyucho event [month] (binary) # Averaged values of months with highest frequency of Kyucho event between YBGN and YEND. Months with highest frequency of Kyucho event were chosen as months with median of Kyucho event whose Kyucho Index was over 3 in each year. Averaged values of months with highest frequency of Kyucho event between YBGN and YEND. kyucho/kindex_month └── YBGN-YEND.bin (Averaged values between YBGN and YEND) # Change of months with highest frequency of Kyucho event [month] (binary) # Change of kindex_month caused by global warming kyucho/kindex_month_diff └── YBGN2-YEND2_YBGN1-YEND1.bin (Values obtained by subtracting (YBGN1-YEND1) from (YBGN2-YEND2))