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HTTP/1.1 301 Moved PermanentlyContent-Type: text/html; charsetUTF-8Location: https://jp.agrimetsoft.com/Server: Microsoft-IIS/10.0X-Powered-By: ASP.NETX-Powered-By-Plesk: PleskWinDate: Tue, 10 Sep 2024 10:13:30 GMTContent-Length: 150 head>title>Document Moved/title>/head>body>h1>Object Moved/h1>This document may be found a HREFhttps://jp.agrimetsoft.com/>here/a>/body>
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HTTP/1.1 200 OKCache-Control: privateContent-Type: text/html; charsetutf-8Server: Microsoft-IIS/10.0X-AspNet-Version: 4.0.30319X-Powered-By: ASP.NETX-Powered-By-Plesk: PleskWinDate: Tue, 10 Sep 2024 10:13:31 GMTContent-Length: 54640 !DOCTYPE html>html>head>meta charsetutf-8 />meta nameviewport contentwidthdevice-width, initial-scale1, shrink-to-fitno />meta nameauthor contentSohrab Kolsoumi />link relicon href/img/icon/favicon.ico />title> AgriMetSoft/title> script typetext/javascript srcpath/to/helium.js>/script>script typetext/javascript> window.addEventListener(load, function(){ helium.init(); }, false);/script> !-- Bootstrap core CSS --> link relstylesheet hrefContent/bootstrap.css /> meta namedescription contentAgrimetsoft develops, maintains, and supports diverse software in meteorology, agriculture, and climate science.> meta namekeywords contentagricultural tools, climate tools, meteorology tools, climate software, modeing tools> link relcanonical hrefhttps://agrimetsoft.com/ /> link relalternate hrefhttps://agrimetsoft.com/ hreflangen-us />!-- Google Tag Manager -->script>(function(w,d,s,l,i){wlwl||;wl.push({gtm.start:new Date().getTime(),event:gtm.js});var fd.getElementsByTagName(s)0,jd.createElement(s),dll!dataLayer?&l+l:;j.asynctrue;j.srchttps://www.googletagmanager.com/gtm.js?id+i+dl;f.parentNode.insertBefore(j,f);})(window,document,script,dataLayer,GTM-P92V4DS);/script>!-- End Google Tag Manager -->/head>body>!-- Google Tag Manager (noscript) -->noscript>iframe srchttps://www.googletagmanager.com/ns.html?idGTM-P92V4DSheight0 width0 styledisplay:none;visibility:hidden>/iframe>/noscript>!-- End Google Tag Manager (noscript) --> header> div classcollapse bg-dark idnavbarHeader> div classcontainer> div classrow> div classcol-sm-8 col-md-7 py-4> h4 classtext-white>About/h4> p classtext-muted>Agrimetsoft is dedicated to creating a wide range of user-friendly software applications aimed at supporting scholars, researchers, and scientists in their endeavors to investigate, evaluate, and assess climate and environmental changes. Our software tools are designed to facilitate comprehensive analysis and interpretation of data, enabling users to gain valuable insights into the complexities of climate dynamics and its impact on the environment, agriculture, and other climate concepts. With a commitment to innovation and ease of use, Agrimetsoft strives to empower the scientific community with powerful tools that enhance their research capabilities and contribute to a deeper understanding of our changing world./p> /div> div classcol-sm-4 offset-md-1 py-4> h4 classtext-white>Menu/h4> ul classnavbar-nav mr-auto> li classnav-item active> a classnav-link href/default>Home span classsr-only>(current)/span>/a> /li> li classnav-item dropdown> a classnav-link dropdown-toggle href/products iddropdown01 data-toggledropdown aria-haspopuptrue aria-expandedfalse>Products/a> div classdropdown-menu aria-labelledbydropdown01> a classdropdown-item href/open_nc_file_for_coordinates>Open NC File/a> a classdropdown-item href/sd-gcm>SD-GCM/a> a classdropdown-item href/taylor_diagram_software>Taylor Diagram/a> a classdropdown-item href/dmap>DMAP/a> a classdropdown-item href/idf_curve>IDF Curve/a> a classdropdown-item href/data-tool>Data-Tool/a> a classdropdown-item 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target_blank>Hydrological tools/a> a classdropdown-item hrefhttps://youtube.com/playlist?listPLaT4Cfntnc9i5D-IMHqmhSaNQGcV_in6E target_blank>SPSS Tutorials/a> a classdropdown-item hrefhttps://youtube.com/playlist?listPLaT4Cfntnc9hm2HRuI0b69h7h0H-nYSMQ target_blank>ArcMap Online Learning/a> a classdropdown-item hrefhttps://youtube.com/playlist?listPLaT4Cfntnc9h6biCAgQBpoRR-M-u8cVan target_blank>CORDEX Data/a> a classdropdown-item hrefhttps://youtube.com/playlist?listPLaT4Cfntnc9hKcJ9F4PJk6MJ8cyvMHa1X target_blank>Online Calculator/a> a classdropdown-item hrefhttps://youtube.com/playlist?listPLaT4Cfntnc9gOXfwX4MsMFMV4TgzivIYZ target_blank>Regressions/a> a classdropdown-item hrefhttps://youtube.com/playlist?listPLaT4Cfntnc9ilxowCv1rFy8ohfi7CnW-i target_blank>Ncar Command Language/a> /div> /li> li classnav-item> a classnav-link href/faq>FAQ/a> /li> li classnav-item> a classnav-link href/about>About/a> /li> li classnav-item dropdown> a classnav-link dropdown-toggle hrefproducts iddropdown03 data-toggledropdown aria-haspopuptrue aria-expandedfalse>Online & Free & Old Tools/a> div classdropdown-menu aria-labelledbydropdown03> a classdropdown-item hrefMDM target_blank>MDM/a> a classdropdown-item hrefKBDIS target_blank>KBDIS/a> a classdropdown-item hrefcalculators target_blank>Calculators/a> a classdropdown-item hrefmaps.html target_blank>Maps/a> a classdropdown-item hrefNetCDF-Viewer target_blank>NetCDF-Viewer/a> a classdropdown-item hrefCordex Coordinate Rotation target_blank>CORDEX Rotation/a> a classdropdown-item href/distributions-calculator target_blank>Distribution Calculators/a> a classdropdown-item href/regressions target_blank>Regression/a> a classdropdown-item hrefCRUP target_blank>CRUP/a> a classdropdown-item hrefPADE target_blank>PADE/a> /div> /li> /ul> /div> /div> /div> /div> div classnavbar navbar-dark box-shadow stylebackground-color: #212F3C;> div classcontainer d-flex justify-content-between> a href/ classnavbar-brand d-flex align-items-center> strong>AgriMetSoft/strong> /a> button classnavbar-toggler typebutton data-togglecollapse data-target#navbarHeader aria-controlsnavbarHeader aria-expandedfalse aria-labelToggle navigation> span classnavbar-toggler-icon>/span> /button> /div> /div> /header> nav classnavbar navbar-expand-lg navbar-light> div classrow> div classcol-sm-auto> a classnavbar-brand href/> img srcimg/Icon/ams.jpg width30 classrounded altAgriMetSoft /> /a> /div> div classcol> div classcollapse navbar-collapse left idnavbarText> ul classnavbar-nav mr-auto> li classnav-item active> a classnav-link href\>Home span classsr-only>(current)/span>/a> /li> li classnav-item> a classnav-link href\products>Products/a> /li> li classnav-item> a classnav-link href\services>Services/a> /li> li classnav-item> a classnav-link href\about>About/a> /li> li classnav-item> a classnav-link href\faq\>FAQ/a> /li> /ul> /div> /div> /div> /nav> form methodpost action./ idform1>input typehidden name__VIEWSTATE id__VIEWSTATE value/wEPDwUKMTY1NDU2MTA1MmRkJl93HC9G8PtkTEE7KUJRr/ynC9k />input typehidden name__VIEWSTATEGENERATOR id__VIEWSTATEGENERATOR valueCA0B0334 /> div> main rolemain> section classjumbotron text-center> div classcontainer> h1 classjumbotron-heading>AgriMetSoft/h1> p classlead text-muted text-justify>Various software packages related to meteorology, agriculture and climate science are developed, maintained and supported by Agrimetsoft. In addition, we create free training courses on YouTube./p> p> a href# onclickmyfunction(1) idbut1 classbtn btn-primary my-2>Products/a> a href# onclickmyfunction(2) idbut2 classbtn btn-secondary my-2>Upcoming/a> a hrefbundles target_blank idbut3 classbtn btn-info my-2>Bundles/a> /p> /div> /section> div classd-block idproducts> div classalbum py-5 bg-light> div classcontainer> div classrow> div classcol-md-4> div classcard mb-4 box-shadow> div classtext-center> img classimg-fluid srcimg/1/fig1.jpg height250 altStatistical downscaling methods /> /div> div classcard-body> p classcard-text text-justify>strong>SD-GCM/strong>/p> p classcard-text text-justify>In this package, users can utilize three statistical downscaling methods on any CMIP5/CMIP6 models or gridded data. To begin, you will need to download historical and RCPs/SSPs NetCDF files from ESGF or other relevant websites. Additionally, ensure that you have access to station data. With these resources in hand, the tool can perform statistical downscaling using three methods: Delta, Quantile Mapping, and Empirical Quantile Mapping.br/>br/>br/>br/>br/>/p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(sd-gcm, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/sdgcm2, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/taylor.png height400 altTaylor Diagram Tool /> div classcard-body> p classcard-text text-justify>strong>Taylor Diagram Software/strong>/p> p classcard-text text-justify> Taylor diagrams offer a comprehensive way to evaluate and compare models based on multiple metrics at once. By visually comparing the positions of models on the Taylor diagram, their performance in matching observations can be assessed. Models closer to the reference point indicate better agreement with the observed data.br /> br /> br /> /p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(taylor_diagram_software, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/tds, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/oncf11.png altOpen NC File Tool /> div classcard-body> p classcard-text text-justify>strong>Open NC File/strong>/p> p classcard-text text-justify>The Open NC File tool is a versatile tool for extracting time series data from NetCDF files without limitations. It can read any NetCDF file, including rotated-pole grids like CORDEX data, in nc or nc4 formats. Users can extract data based on a list of station coordinates or rectangular regions. Multiple files can be temporarily merged by the tool, which supports unlimited dimensions. The tool automatically converts regular latitude and longitude to rotated ones. Overall, Open NC File provides powerful features for flexible data extraction from several NetCDF files at once./p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(open_nc_file_for_coordinates, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/rotat.png altnon-rotated and rotated coordinates /> div classcard-body> p classcard-text text-justify>strong>Cordex Coordinate Rotation/strong>/p> p classcard-text text-justify>This tool provides the capability to convert coordinates between non-rotated and rotated formats. The rotation pivot is based on CORDEX domains and can be customized as per your requirements. To extract data from CORDEX NetCDF files, you are required to convert your regular coordinates to rotated coordinates using this tool. Once the conversion is complete, you can proceed with data extraction using the rotated coordinates and rlat/rlon variables available in your file. Data extraction can be accomplished using any programming language or by utilizing the Netcdf Extractor provided on this website./p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(Cordex%20Coordinate%20Rotation, _blank);>Visit/button> /div> small classtext-muted>Free/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/idf.png altIDF Curve Tool /> div classcard-body> p classcard-text text-justify>strong>IDF Curve Tool/strong>/p> p classcard-text text-justify>The IDF curve tool offers various distributions for generating IDF (Intensity-Duration-Frequency) charts. There are two options available for inputting data. In the first tab, you can input your raw data at a scale ranging from 5 minutes to daily, and the IDF tool will calculate the corresponding maximum values in the second tab. Alternatively, you have the option to directly input the maximum values in the second tab instead of raw data. In the third tab, you can generate IDF graphs for specific return periods. A return period represents the average time or estimated average time between events, such as the occurrence of rainfall intensities. The tool allows you to save the IDF data in an Excel file and draw the IDF graphs within Excel./p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(idf_curve, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/idf-curve, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/dmap.png altDMAP /> div classcard-body> p classcard-text text-justify>strong>DMAP/strong>/p> p classcard-text text-justify> The DMAP software is equipped with advanced capabilities to calculate a diverse range of drought indices for three distinct types of drought: meteorological, agricultural, and hydrological. It offers a user-friendly feature that allows easy input of station data through Excel files. Furthermore, the software supports the utilization of NetCDF data from stations, rectangular regions, or shapefiles, providing flexibility in data sources. By utilizing this powerful tool, you can accurately evaluate and assess drought severity. Additionally, the software allows you to export all the results to an Excel file. With DMAP, you can conveniently calculate indices such as SPI, DI, PNI, CZI, MCZI, ZSI, RAI, EDI, PDSI, PHDI, RDI, SPEI, KBDI, ARI, SMDI, ETDI, SWSI, SDI. br /> br /> /p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(dmap, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/datatool.jpg altCard image cap /> div classcard-body> p classcard-text text-justify>strong>Data-Tool/strong>/p> p classcard-text text-justify> In summary, Data-Tool serves as an Excel add-in that empowers users to efficiently manipulate and analyze their data. With features like data reshaping, sorting, and the computation of various indices, it enables users to gain valuable insights from their data. Data-Tool is a powerful Excel add-in that simplifies data sorting and reshaping, enabling users to easily apply various indices to their data. To calculate these essential indices using Data-Tool, it is necessary to format the data in a specific manner that allows for seamless analysis. This Excel add-in provides a range of functionalities, including data reshaping and sorting, conversion of daily data to monthly or seasonal formats, and the computation of efficiency criteria such as Root Mean Square Error, Nash Sutcliffe model Efficiency coefficient, Mean Absolute Error, and more. Data-Tool also offers additional capabilities, such as generating CDF/PDF charts, performing multiple linear regression (MLR), and conducting Trend tests. Furthermore, we continuously enhance the tool by adding new functionalities to further support diverse data analysis needs.br /> br /> br /> /p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(data-tool, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/wdt-store, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/knn12.png altKNN-WG /> div classcard-body> p classcard-text text-justify>strong>KNN-WG/strong>/p> p classcard-text text-justify>The KNN Weather Generator is a powerful tool that enables users to simulate daily weather data using the K-nearest-neighbor approach. With this software, users can conveniently load seven different variables, including Tmin, Tmax, Rain, Srad, ETo, WSPD, and Humidity. This software offers various features to enhance the user experience. Users can visualize the generated data through interactive graphs and also calculate several efficiency criteria, such as d, NSE, RMSE, MBE, Pearson, and Spearman. Moreover, the KNN Weather Generator allows users to compare its outputs with results from other models. By importing the outputs of different models, users can make comprehensive comparisons and evaluate the effectiveness of the KNN Weather Generator in generating accurate weather data. One of the notable advantages of the KNN Weather Generator software is its flexibility in variable selection. Users have the freedom to choose any number of variables they desire, starting from a minimum of seven variables. Its range of features, including variable selection, graph visualization, efficiency criteria calculation, and result comparison, make it an invaluable resource for weather prediction and analysis./p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(knn-wg, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/knnwg, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/modis.png altMODIS Product Extractor /> div classcard-body> p classcard-text text-justify>strong>MODIS Product Extractor/strong>/p> p classcard-text text-justify>The MODIS Product Extractor is a specialized tool designed to extract data from MODIS HDF files of various products. This tool offers several features that facilitate data extraction based on specific requirements. With the MODIS Product Extractor, you can perform the following actions: Extract data from points or regions: The tool allows you to extract data from specific points or a list of points defined by their coordinates. Additionally, you can extract data from rectangular regions by specifying the corner coordinates. Furthermore, you have the flexibility to select a region of any shape on a map and extract data for that specific area. Export to Excel: The extracted data can be exported to Excel for further analysis or integration with other tools. This export functionality enables you to utilize the extracted data in a tabular format that is compatible with Excel or other spreadsheet software. The MODIS Product Extractor simplifies the process of extracting data from MODIS HDF files by providing a user-friendly interface and efficient extraction capabilities. It streamlines the workflow for accessing specific data points or regions of interest and offers the convenience of exporting the extracted data to Excel for further analysis or reporting./p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(modis_products_extractor, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/mod16a2-data-extractor, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/mat.jpg altModel Analyzer Tool /> div classcard-body> p classcard-text text-justify>strong>Model Analyzer Tool/strong>/p> p classcard-text text-justify>The Model Analyzer Tool is specifically designed for analyzing and evaluating model outcomes, with applications spanning diverse domains. Its features include QQ-Plots, which facilitate the visualization of residual distribution and aid in identifying deviations from normality. The tool utilizes Confidence and Prediction Bounds to represent the likely range of true values. Automatic calculations of efficiency indices, such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Nash-Sutcliffe Efficiency Coefficient (NSE), offer valuable insights into model performance. Additionally, the tool examines autocorrelation in model residuals, uncovering any persistent patterns or dependencies that may have been overlooked during the modeling process./p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(model_analyzer_tool, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/mat, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/emcd.jpg altEstimating Missing Climate Data /> div classcard-body> p classcard-text text-justify>strong>Estimating Missing Climate Data/strong>/p> p classcard-text text-justify>Estimating missing climate data is vital in climate research. When data is incomplete due to various reasons, our tool offers solutions. This tool has two sections to estimate missing climate data: one estimates using data from other stations, and the second uses historical records of the current station. In the first section, methods like MLR, Correlation Coefficient Weighting, IDW, and ANN address gaps. The second section utilizes LOCF, NOCB, Interpolation, and Substitute Statistics methods to fill in missing data./p> br /> br /> br /> br /> br /> br /> br /> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(Estimate_Missing_Climate_Data, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(https://agrimetsoft.onfastspring.com/estimate-missing-climate-data-tool, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/tp.jpg altTaylor Diagram Tool /> div classcard-body> p classcard-text text-justify>strong>Thiessen Polygon Tool/strong>/p> p classcard-text text-justify> Thiessen polygons, also referred to as Voronoi polygons or Thiessen regions, are a versatile method applied in geography, cartography, and spatial analysis. They divide an area into regions based on proximity to specific points or features. One notable application is the spatial distribution of rainfall data from multiple stations. The Thiessen polygon method effectively allocates rainfall measurements across an area by considering the proximity of each rain gauge station. This tool not only calculates station areas but also facilitates the determination of average rainfall for a given region. br /> br /> br /> br /> br /> /p> div classd-flex justify-content-between align-items-center> div classbtn-group> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(Thiessen_Polygon, _blank);>Visit/button> button typebutton classbtn btn-sm btn-outline-primary onclickjavascript:window.open(thiessen-polygon, _blank);>Buy a License/button> /div> small classtext-muted>Commercial/small> /div> /div> /div> /div> /div> /div> /div> /div> div classd-none idFutureProducts> div classalbum py-5 bg-light> div classcontainer> div classrow> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/thumb.jpg altEnsemble GCMs Models /> div classcard-body> p classcard-text text-justify>strong>Ensemble GCMs Models/strong>/p> p classcard-text text-justify> Ensemble Global Climate Models (GCMs) refer to a collection of multiple climate models employed to simulate and forecast the behavior of Earths climate system. This powerful tool involves combining several GCM models using various methods, allowing for a comprehensive assessment of climate predictions and associated uncertainties. By employing ensembles, scientists can gain insights into the range of potential outcomes and improve the reliability of climate projections. br /> br /> /p> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Developing Tool/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/thumb.jpg altPower-spectral-density /> div classcard-body> p classcard-text text-justify>strong>Power-spectral-density (PSD) Analysis/strong>/p> p classcard-text text-justify> In climate science, Power Spectral Density (PSD) analysis is a method used to study the frequency characteristics of climate time series data. It is a valuable tool for understanding the dominant frequencies and periodicities present in climatic data, which can provide insights into the underlying climate processes and variability. br /> br /> br /> br /> br /> /p> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Research About Methods/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/wam.png altTaylor Diagram Tool /> div classcard-body> p classcard-text text-justify>strong>Wavelet ANN Model/strong>/p> p classcard-text text-justify>The Wavelet Artificial Neural Network (Wavelet ANN) model is a hybrid approach that combines the mathematical framework of wavelet analysis with the powerful learning capabilities of artificial neural networks (ANNs). This model is commonly used for various types of data analysis and forecasting tasks, including time series prediction, image processing, and signal analysis. Our software includes two hybrid models of Wavelet and ANN based on the above flowcharts./p> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Writing Research Paper/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/thumb.jpg altNon-Stationary IDF /> div classcard-body> p classcard-text text-justify>strong>Non-Stationary IDF/strong>/p> p classcard-text text-justify>Non-stationary Intensity-Duration-Frequency (IDF) analysis is a concept in hydrology and climatology that takes into account changes in the statistical properties of extreme precipitation events over time. The traditional approach for estimating IDF curves assumes that the statistical characteristics of extreme rainfall, such as intensity, duration, and frequency, remain constant over time. However, with climate change and other environmental factors affecting weather patterns, this assumption of stationarity may no longer hold true. This tool is designed to perform Non-stationary Intensity-Duration-Frequency (IDF) analysis by considering changes in extreme precipitation characteristics over time./p> br /> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Developing Tool/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/scs.png altTaylor Diagram Tool /> div classcard-body> p classcard-text text-justify>strong>SCS-Runoff-Curve-Number-Method/strong>/p> p classcard-text text-justify> The Soil Conservation Service (SCS) Runoff Curve Number (RCN) Method, also known as the NRCS (Natural Resources Conservation Service) Curve Number Method, is a widely used hydrological technique for estimating direct runoff from rainfall events in a watershed. The method was developed by the United States Department of Agricultures Soil Conservation Service, now known as the Natural Resources Conservation Service, and is commonly applied in hydrology, engineering, and land management practices. This is a simple tool to calculate estimating direct runoff from rainfall events in a watershed based on SCS-Runoff-Curve-Number-Method br /> br /> br /> br /> br /> /p> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Make Tutorials/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/tts.png altTaylor Diagram Tool /> div classcard-body> p classcard-text text-justify>strong>Trend Test Software/strong>/p> p classcard-text text-justify>In this tool, you can input monthly climate data, and the tool will convert it into seasonal, season12, discrete all season12 items, and yearly data. The next step is to check the autocorrelation with a one-item lag to determine which method is suitable. The tool offers four methods to calculate the data trend on all time scales and wavelet components (approximation and details, and their composition). These methods include:/p> ul> li>Simple Mann-Kendall/li> li>Seasonal Mann-Kendall/li> li>Serial Correlation Mann-Kendall/li> li>Sequential Mann-Kendall/li> /ul> p classcard-text text-justify>Using these methods, the tool helps you analyze trends and patterns in your climate data at various time scales and wavelet components, making it a powerful tool./p> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Writting Research Paper/small> /div> /div> /div> /div> div classcol-md-4> div classcard mb-4 box-shadow> img classimg-fluid srcimg/1/thumb.jpg altWeather ata Sorter /> div classcard-body> p classcard-text text-justify>strong>Weather Data Sorter/strong>/p> p classcard-text text-justify>These tools calculate the indices that offer valuable insights into various aspects of climate and weather conditions and are commonly used by meteorologists, hydrologists, and climate scientists for analyzing climate patterns and understanding potential impacts on various sectors like agriculture, water resources, and energy demand. These indices are climate-related measures commonly used in climate analysis and impact studies. Each index represents a specific aspect of the climate or weather conditions. These indices is:/p> ul> li>Growing Degree Days (GDD)/li> li>Cooling Degree Days (CDD)/li> li>Heating Degree Days (HDD)/li> li>Wet Day/li> li>Number of Frost Days (N. Frost Day)/li> li>Consecutive Dry Days/li> li>Consecutive Wet Days/li> li>Annual Count of Rainy Days/li> li>Annual Count of Days With Precipitation Larger Than Value/li> li>Highest 5-day Precipitation Amount for Each Year/li> li>Simple Precipitation Intensity Index/li> /ul> div classd-flex justify-content-between align-items-center> small classtext-muted>Phase:/small> small classtext-muted>Developing Tool/small> /div> /div> /div> /div> /div> /div> /div> /div> /main> script> function myfunction(a) { var x document.getElementById(products); var y document.getElementById(FutureProducts); var b1 document.getElementById(but1); var b2 document.getElementById(but2); if (a 1) { x.classList.replace(d-none, d-block); y.classList.replace(d-block, d-none); b2.classList btn btn-secondary my-2; b1.classList btn btn-primary my-2; } else { y.classList.replace(d-none, d-block); x.classList.replace(d-block, d-none); b1.classList btn btn-secondary my-2; b2.classList btn btn-primary my-2; } } /script> /div> !-- Google Tag Manager (noscript) -->noscript>iframe srchttps://www.googletagmanager.com/ns.html?idGTM-WP35H89Wheight0 width0 styledisplay:none;visibility:hidden>/iframe>/noscript>!-- End Google Tag Manager (noscript) --> /form> br /> footer classblog-footer lef> div classjumbotron text-center> div classcontainer> button typebutton classbtn-sm btn-primary w-25 onclicklocation.href\contact>Contact/button> button typebutton classbtn-sm btn-primary w-25 onclicklocation.href\services>Services/button> button typebutton classbtn-sm btn-primary w-25 onclicklocation.href\products>All Products/button> /div> /div> br /> hr /> p classtext-center card-text text-justify>Copyright © 2023 AgriMetSoft. 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