WMO LC-LRFMME Website User Manual
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1 WMO LC-LRFMME Website User Manual World Meteorological Organization Lead Centre for Long-Range Forecast Multi-Model Ensemble Last update: August 2016
2 Contents 1. WMO LC-LRFMME Introduction Overview of WMO LC-LRFMME Information about Global Producing Centres WMO LC-LRFMME interface WMO LC-LRFMME Getting Started Signing up Logging in Products of WMO LC-LRFMME... 9
3 1. WMO LC-LRFMME Introduction 1.1. Overview of WMO LC-LRFMME Long-Range Forecast (LRF) model outputs are not fully used due to different standards. In order to maximize the effective use of LRF model outputs, linkages among Global Producing Centres (GPCs) and other organizations, including National Meteorological and Hydrological Services (NMHSs), Regional Climate Centres (RCCs), and Regional Climate Outlook Forums (RCOFs) are required. If many GPCs products are combined by Lead Centre for Long-Range Forecast Multi-model Ensemble (LC-LRFMME), seasonal and long-range prediction will be better than now and will contribute to disaster prevention and mitigation, and contribute to better socio-economic planning that accounts for variable climatic conditions. The goals of the LC-LRFMME are to provide a conduit for sharing model data for long-term climate predictions and to develop a well-calibrated Multi-Model Ensemble (MME) system in order to better mitigate the adverse impacts of unfavourable climate conditions or to maximize the benefits of favourable climate conditions. Background of WMO LC-LRFMME 1
4 1.2. Information about Global Producing Centres The seasonal forecast products from 12 GPCs for 2m temperature, precipitation, mean sea level pressure, 850hPa temperature, 500hPa geopotential height, and sea surface temperature (if available) are collected by LC-LRFMME between 1 st to 20 th of each month. The digital data for 3-month forecast in standard format (GRIB1 and GRIB2) are available through the LC-LRFMME website around 20 th of each month (the issue date or the participating GPC in MME can be subject to change). You can find the information for 3-month digital data from LC-LRFMME in the below table. 12 WMO Global Producing Centres 2
5 Information on the data configuration supplied by the 12 GPCs. A X indicates that data is not currently available in LC-LRFMME, because of data policy for each GPC. GPC Beijing (BCC) CPTEC (CPTEC) ECMWF (ECMWF) Exeter (UKMO) Melbourne (BoM) Montreal (MSC) Moscow (HMC) Pretoria (SAWS) Seoul (KMA) Tokyo (TCC) Toulouse (Meteo- France) Washington (NCEP) Forecast system 1-tier (coupled) 2-tier 1-tier (coupled) 1-tier (coupled) 1-tier (coupled) 1-tier (coupled) 2-tier 1-tier (coupled) 1-tier (coupled) 1-tier (coupled) 1-tier (coupled) 1-tier (coupled) Forecast Ensemble size Digital data O O X X O O O O O X X O Hindcast Period Ensemble size Digital data O O X X O O O O O X X O 3
6 1.3. WMO LC-LRFMME interface The browser based graphical interface is your main entry point to the LC-LRFMME. 4
7 Interface terminology In order to familiarize you with the concepts and terminology used in the user interface, a short overview is presented. a. LC-LRFMME tabs The LC-LRFMME tabs of the user interface are always present at the top. The tabsitems provide several basic functions. Home: In this tab, it is briefly introduced how seasonal forecasts, ensemble forecasting, and MME Forecasting are made. The types and methods of Deterministic MME (DMME) and Probabilistic MME (PMME), Verification Measures, and Energetics are also described. In addition, you can find the references regarding to LC-LRFMME. About us: Goals and objectives of WMO LC-LRFMME are introduced. Functions for achieving these goals are also shown. History of WMO LC-LRFMME is briefly introduced. News: You can find which variables of which GPCs data are uploaded in this tab. Web master regularly notifies the news to users. The news is also posted at main page of LC-LRFMME. In subtab System Requirements, it is described which system and environment users have to use and which program the users have to install for using this website. Data & Plot: Member GPCs, RCCs, NMHSs and related institutions which produce LRF data can submit and download data products through this tab. Related Sites: You can find addresses of websites related to LC-LRFMME. 5
8 b. LC-LRFMME Login status indicator and other menus The login status indicator is always available in the right top section. This graphical element indicates the current status of the user. Login: You can log in to LC-LRFMME homepage by clicking this button and entering your ID and password. Sign up: You can register on the website after signing up. Logout: You can log off from LC-LRFMME homepage by clicking this button. Account: You can view information which is submitted when you registered on this homepage. 6
9 2. WMO LC-LRFMME Getting Started 2.1. Signing up To register on the website, click Sign up button. At this page, minimal and key information-first name, last name, desired login ID, password, official , other , an identification question, answer, and country-are needed. Then, check each box I agree 7
10 under Terms of Service, Privacy Handling Policy, and Agreement to collecting personal information. To finish signing up, click Make a New Account. The authentication functionality is provided to restrict usage to bona fide users. After signing up, you can receive a mail Welcome to the LC-LRFMME website in account which you wrote at Sign up page. In the , click on hyperlink button [LINK]. At this link page, you can get authentication after entering ID and password and logging in. After that, the administrator will gives a membership grade like grade A, B, or C according to the user s affiliation. Membership Grade Grade A (GPCs) can upload and download digital data and can download image plots. Grade B (NMHSs and RCCs) can download digital data and image plots. Grade C (Others) can download only Multi-model ensemble image plots Logging in After the procedure of signing up, user can log in this website after clicking Login button. Please be careful not to confuse between upper and lower cases. This system is sensitive to upper and lower cases. 8
11 3. Products of WMO LC-LRFMME Below table shows the provided GPC digital data and graphical products in standard format available from LC-LRFMME. Members of GPCs, RCC, NMHSs and related institutions that produce LRF forecasts can download forecast and hindcast data products for the GPCs that allow redistribution of their digital data. The product display at the lead centre website includes monthly and seasonal mean anomalies from individual GPCs and also a synthesis of information in terms of consistency in the sign of anomalies from all GPCs. In addition to this, 4 types of deterministic MME (Simple Composite Mean, Regular Multiple Regression, Singular Value Decomposition and Genetic Algorithm) and probabilistic MME prediction are shown on the LC-LRFMME website. 9
12 Tab Data & Plot a. Data Exchange Policy You can read some policies regarding to data exchange. Date of submission, required variables, data format, spatial and temporal resolution, lead time, data period, etc. are described. b. Data Exchange Upload (for Grade A): Click the button Write at right bottom section. In next page, select country, cast type, period, and model. Drag and drop the file. After clicking button Submit, uploading data is finished Search/Download (for Grade A and B): Select model, cast type, start and end 10
13 year, month, and parameter and then click the button Search. The files would be listed. Click the filename and you can download data. If you want to download several data at once, check each box of data which you want and click Download button. c. Plot Direct Download (for Grade A and B): Select the cast type, model, year, month. Click the file name and you can download data. If you want to download several file at once, check each box of data what you want and click Selection Download button. There are eight categories in Plot tab: 1) Probabilistic Multi-Model Ensemble, 2) Deterministic Multi-Model Ensemble, 3) Individual Forecast, 4) Energetics, 5) Indices, 6) Verification: Hindcast, 7) Verification: Forecast, and 8) 6 month MME. 11
14 Probabilistic Multi-Model Ensemble (for all Grade) Definition: The probabilistic multi-model ensemble prediction system used at WMO LC-LRFMME is described with some diagrams and equations. Map Type: There are four types-below Normal, Near Normal, Above Normal, and Combined. Probabilistic forecasts are issued in the form of the probability of the below-normal, near-normal, and above-normal categories, with respect to climatology. Select Period: Select year, three months, and Mean or each month. Select Model: Click Select button and check the boxes of models you want. If you want to select all models, check the box of All. Select Parameters: Five parameters are provided. Push a radio button of a parameter which you want. Select Region: Select a region where you are interested. If selecting Arbitrary region, you can set up a range of longitude and latitude which you want. After setting up, click Plot and you can view pop-up window filled with the map. If you are a member of Grade C, you cannot select model. You can see and 12
15 download multi-model ensemble result only. Deterministic Multi-Model Ensemble (for all Grade) There are three methods: Simple ensemble mean, Regular Multiple Regression, and Singular Value Decomposition. Each method is described in Definition. Simple ensemble mean The systematic errors for forecast models can be removed by this method. Map Type: Only rectangular map is provided. Select Period: Select year, three months, and Mean or each month. Select Model: Click Select button and check the boxes of models you want. If you want to select all models, check the box of All. Select Parameters: Six parameters are provided. Push a radio button of a parameter which you want. Select Region: Select a region where you are interested. If selecting Arbitrary region, you can set up a range of longitude and latitude which you want. If you are a member of Grade C, you cannot select model. You can see and download multi-model ensemble result only. Regular Multiple Regression, Singular Value Decomposition (SVD), and 13
16 Genetic Algorithm (GA) A multi-model prediction by Regular Multiple Regression can be created by weighting at a fixed grid point according to predictability of each model. Singular Value Decomposition is similar to Regular Multiple Regression but can solve singular value problems from it. Genetic Algorithm is a probabilistic algorithm that iteratively transforms a set of mathematical objects. Map Type: Only rectangular map is provided. Select Period: Select year, three months, and Mean or each month. Select Parameters: Six parameters are provided. Push a radio button of a parameter which you want. Select Region: Select a region where you are interested. If selecting Arbitrary region, you can set up a range of longitude and latitude which you want. 14
17 Individual Forecast (for Grade A and B) There are six map types. According to these map types, what you have to select varies. Procedures are described below in accordance with map types. Rectangular and Time series Select Period: Select year, three months, and Mean or each month. Select Parameters: Six parameters are provided. Push a radio button of a parameter which you want. Select Region: Select a region where you are interested. If selecting Arbitrary region, you can set up a range of longitude and latitude which you want. Stereographic Map Project: Northern or Southern hemisphere is drawn. Select Period: Select year, three months, and Mean or each month. Select Parameters: Six parameters are provided. Push a radio button of a parameter which you want. All Map Select Period: Select year, three months, and Mean or each month. 15
18 Select Region: Select a region where you are interested. If selecting Arbitrary region, you can set up a range of longitude and latitude which you want. Select Parameters: Six parameters are provided. Push a radio button of a parameter which you want. Consistency Map and SST Plume Consistency map and SST Plume are plotted in PDF type. Select Period: Select year, three months, and Mean or each month. Energetics (for Grade A and B) Select period, month, model, and variable and then click Apply button. Definition The atmospheric energy in a model can be stored in the form of potential energy and kinetic energy, which can be described with energetics. The LC-LRFMME developed general circulation model assessment system based on balance equation. The energy cycle and the connecting links between the various energy forms are calculated. A schematic box diagram of energy cycle is as in the following: 16
19 Indices (for Grade A and B) PM : mean available potential energy PE : eddy available potential energy, which is composed of PSE and PTE PSE : stationary eddy available potential energy PTE : transient eddy available potential energy KM : mean kinetic energy KE : eddy kinetic energy, which is composed of KTE and KSE KTE : transient eddy kinetic energy KSE : stationary eddy kinetic energy C(A,B) : conversion rate of A to B There are ten indices. Select period, month, and model. 17
20 Acronyms AO Arctic Oscillation PNA Pacific-North American Pattern SOI Southern Oscillation Index NOI Northern Oscillation Index WNPMI Western North Pacific IMI Indian Monsoon Index summer Monsoon Index EAMI East Asian Monsoon Index EAWMI East Asian Winter Monsoon Index WYI Webster-Yang Index RM2 Regional Monsoon index for East Asia Verification : Hindcast (for Grade A and B) Select three months, a verification score, and a variable. 18
21 Verification : Forecast (for Grade A and B) Select year, three months, a verification score, and a variable. 6 month MME (for all Grade) Select year, six months, and three months. 19
22 d. System Configuration Information In this subtab, you can find the information of each GPC. Model resolution, ocean model, source of atmospheric and ocean initial conditions, hindcast period, etc. are described. 20
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