README document for AphroClim_V1808 (Last updated 26 September, 2018) 1. Introduction A suite of precipitation products is being constructed by the Asian Precipitation -- Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE's water resources) project (Yatagai et al., 2011). APHRODITE first term was finished in 2010 and APHRODITE second term has begun in 2016, in collaboration with Hirosaki University, Kyoto University and Chiba University. To develop long-term daily gridded precipitation and temperature datasets from rain-gauge observation records over Asia by international collaborations with local meteorological/hydorlogical agencies and researchers. AphroClim_V1808 is climatological daily mean temperature product developed from the interim product of AphroTemp_V1808, 0.05 degree gridded daily product. More data is collected and analyzed than AphroTemp_V1204R1 and data period is also extended. Topographical effect scheme is introduced to interpolation algorithm. This README interprets the structure of AphroClim_V1808 data files (sections 2-5), explains changes from the previous versions (section 6), and gives relevant references (section 7). 2. General Information 2.1 Products The product we release is 0.05x0.05-degree climatology of daily mean temperature over Monsoon Asia (APHRO_MA_TAVE_CLM_V1808). The gridded fields of daily mean temperature are defined by interpolating gauge observations obtained from meteorological stations throughout the region. The algorithm for the new product is made with a few modification on that of APHRO_V1101.(Kamiguchi et al, 2010) We interpolate the subtraction of the daily mean temperature from the base climatology (WorldClim, Hijmans et al., 2005) at a resolution of 0.05 degrees, then add each gridded subtraction to each gridded climatology value day-by-day. A grid value is caluclated by using angular distance weighting function. Less weighted to the value in case elevation gap between the station and estimated grid is larger than the threshold. Climatological mean is derived from the average of daily product from 1981 to 2010.9-day running mean is applied to the average of 30 years. As for Feburary 29th, average of February 28th and March 1st of non-leap year is analyzed in addition to the leap year. Either February 28th or March 1st is missing, February 29th of that year is also missing. An indicator is introduced to represent the reliability of the interpolated daily temperature fields. This indicator, named NOBS, is the number of year(s) containing valid observation(s) for each grid. If the temperature field is averaged over 30 valid observation of the day, NOBS is 30. 2.2 Spatial and Temporal Coverage Spatial coverage : (MA) 60.0E - 150.0E, 15.0S - 55.0N Spatial resolution : 0.05 degree latitude/longitude Temporal coverage : 366 days (average for 1981-2010) Temporal resolution : Daily 2.3 Units Daily mean temperature : degC Number of valid observation for 30 years : 0-30 2.4 Missing Code Daily mean temperature : -99.9 Number of valid observation for 30 years : -99.9 3. Data Files and Their Structure The product is stored in one file. APHRO_MA_TAVE_CLM_005deg_V1808.grd 3.2 Structure of Data Files The file contains daily fields for 366 days. These daily fields are arranged according to the Julian calendar. Daily fields (data arrays) contain information on the daily mean temperature climatology and number of years containing valid obseravation of 30 years. Each field consists of a data array with longitude by latitude dimensions of 1800 x 1400 elements for monsoon Asia. The first element is a cell at the southwest corner centered at [60.025E, 14.975S], the second is a cell at [60.075E, 14.975S], ..., the 1800th is a cell at [149.975E, 14.975S], and the 1801st is a cell at [60.025E, 14.925S]. [Note for plain binary format] The data files are written in PLAIN DIRECT ACCESS BINARY. In each daily field, the array for temperature comes first, followed by information on the rain gauge. Each element (both temperature and rain gauge information) is written as a 4-byte floating-point number in little endian byte order. Users should swap the byte order to big endian if necessary. There are no 'space', 'end of record', or 'end of file' marks in between. In the case of the 0.05-degree APHRO_TAVE_MA product, the size of a file is 4 bytes x 1800 x 1400 x 2 fields x 366 days = 7,378,560,000 bytes. 4. Sample of GrADS Control Files Each data file needs a *.ctl file to be handled by the GrADS software (http://www.iges.org/grads/). Control file for AphroClim_V1808 is available in the same directory as for the corresponding gridded data. After saving the control file in the same location as the downloaded data, open this file after the "ga" prompt (e.g., ga-> open APHRO_TAVE_MA_CLM_005deg_V1808.ctl). 5. Sample Fortran 90 Program A sample program written in Fortran 90 (read_aphro_clm_v1808.f90) is available in the same directory as for the corresponding gridded data. Note that the little-endian byte order is assumed in this program. 6. References 6.1 How to cite AphroClim_V1808 We are preparing a paper that presents our algorithm for AphroClim_V1808. Should you refer to our product in your paper/presentation, please cite V1204 reference paper, Yasutomi et al. (2011), for the present. We will notice when AphroClim_V1808 reference paper is pubilshed to registered users. Yasutomi, N., A. Hamada and A. Yatagai (2011): Development of a long-term daily gridded temperature dataset and its application to rain/snow descrimination of daily precipitation, Global Environmental Research, V15N2, 165-172. When you write/publish papers, please access the "Research Activities" page of our website ( http://aphrodite.st.hirosaki-u.ac.jp/publications.html) to obtain the latest information on our reference papers that present our algorithms and products. 6.2 Reference for the related products The following are references of the related versions. 1) Yatagai, A., K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi and A. Kitoh (2012): APHRODITE: Constructing a Long-term Daily Gridded Precipitation Dataset for Asia based on a Dense Network of Rain Gauges, Bulletin of American Meteorological Society, doi:10.1175/BAMS-D-11-00122.1. 2) Yasutomi, N., A. Hamada and A. Yatagai (2011): Development of a long-term daily gridded temperature dataset and its application to rain/snow descrimination of daily precipitation, Global Environmental Research, V15N2, 165-172. 3) Hamada, A., O. Arakawa and A. Yatagai, 2011: An automated quality control method for daily rain-gauge data. Global Environmental Research, V15N2, pp183-192. 7. Points of concern 1) Lack of observation data (in Indonesia and Papua New Guinea) Input of daily observations over Indonesia and Papua New Guinea are lacked. A considerable number of temperature grids over New Guinea Island are missing until 1980's. Distribution of valid station observation is provided (NOBS) for each day. Users please pay attention to the density of observations. 2) Homogenization of observation We do not homogenize the observed time series of temperature data. Changes in gauges, location of the stations, and many other factors might cause discontinuity of observation data. 3) Improvement in calculation after Yasutomi et al.(2011) Anomaly interpolation method is introduced after publish of Yasutomi et al. (2011). Climatological mean temperature is based on WorldClim (Hijmans et al., 2005; http://www.worldclim.org/). First, we derive anomaly from climatology, next, anomalies are interpolated into 0.05 degree grid. Then summed up to climatology for 30 years. Then climatological mean is derived, and 9-day running mean is applied to the climatology. 8. Contacts Please contact APHRODITE project (led by Dr. Akiyo Yatagai of Hirosaki University) for further questions regarding this product. APHRODITE's Water Resources project http://aphrodite.st.hirosaki-u.ac.jp Technical inquiries APHRODITE project team aphrodite.precinfo@gmail.com General inquiries APHRODITE secretariat aphrdite.secretary@gmail.com (Contact) Dr. Natsuko Yasutomi Disaster Prevention Research Institute, Kyoto University Gokasho, Uji, Kyoto 611-0011, Japan Principal Investigator Prof. Akiyo Yatagai Course of Meteorology, Graduate School of Science and technology, Hirosaki University