Presentation Outline. Results of Climate Change. Introductory Information Case Studies. Closing Remarks. Flood zones change
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1 Presentation Outline Introductory Information Case Studies Romania DESWAT Romania INTEROPERATE The Kingdom of Morocco Weather Radar Network Feasibility Studies Philippines Meteorological and Hydrological Telecommunications Upgrade Closing Remarks Results of Climate Change Flood zones change Flooding and droughts become less predictable Design standards are no longer adequate We loose the understanding of weather and storm water related dynamics
2 Developing Countries Ability to accurately predict weather does not always exist The US Trade & Development Agency (TDA) is funding Feasibility Studies to improve weather related facilities B&N managed four weather related international projects two in Romania, Morocco, and the Philippines. USTDA Mission: Advance economic development in developing and middle income countries Fund projects that support development of modern infrastructure and fair trade Stimulate American business Weather Related Activities Forecasting 6 hours to 10 days Now Casting 0 to 6 hours Real-time
3 Forecasting Upper air soundings Satellite Computer models Now Casting Doppler Radar Useful for observation of precipitation (measures freq. differences of microwave signals) Clouds Rain Hail Snow Real Time Data Precipitation Temperature Humidity Barometric pressure Wind speed & direction Stream flow Soil moisture
4 Weather Related Data Provides Advanced warning of dangerous storm events Flood and droughts become more predictable Used to establish design standards Land use planning Design of flood control structures Title Goes Here Bullets Go Here And Here Case Study: Romania DESWAT Case Study: Romania Destructive Waters (DESWAT) Feasibility Study Evaluation, Selection and Testing Process for Hydrologic and Hydraulic Flood Models for Use in Romania
5 Romania Model Review Process Eight models reviewed in US workshops Four models selected for consideration Vflo (Vieux Associates) RiverTrak (Riverside Technologies) River Forecast System (USNWS) Corps Water Management System (USCOE) Mapping Needs For Hydrologic modeling 1:50,000 For Hydraulic modeling 1:10,000 New mapping could be used for many purposes in addition to flood modeling Satellite mapping may be considered
6 Recommended Model Group Vflo for small basins to 200 KM2 RiverTrak for larger basins 200-5,000 KM2 RFS model basins over 5,000 KM2 Vidra model- basins over 500 KM2, as an interim approach, in parallel with Vflo and RiverTrak models Lapus Basin Pilot Demonstration Application of Vflo and Vidra models Vflo training in January 2003 Attended by 19 staff trainees Application included May 1970 storm Examples of input and resulting inundation maps Hourly Gauge Distribution Rainfall Hyetograph at Baia Mare and Lezer Gauges May 1970
7 Storm Total Rainfall Resulting Map of Storm Total Accumulations May 1970 Discharge at Lapusel Gauge Station Vflo: Discharge at Lapusel Gage May 1970 Flood Inundation Lapus Basin Modeled Flood Inundation in the Lapus Basin May 1970 Event
8 Vidra Application To Lapus Basin Application of May 1970 storm Examples of hydrographs and resulting inundation maps Flood Wave Hydrographs Vidra: Flood Wave Hydrographs Recorded at the Gauging Stations from the Lapus River Basin in May 1970 Q(m 3 /s) h h Lapus R.- Lapusel St. Lapus R.- Razoare St. Cavnic R.- Copalnic St. Sasar R.-Baia Mare St. Suciu R.- Suciu St Time(hour) Stations Razore and Lapusel Computed and Recorded Hydrographs at the Razore and Lapusel Stations in May 1970 Comparison Lapusel Station 1970 Comparison Razoare Station 1970 Q(m 3 /s) Computed Q(m 3 /s) Computed Recorded 600 Recorded Time(hours) Time(hours)
9 Modeled Flood Inundation Modeled Flood Induation in the Lapus Basin May 1970 (Bozanta Mare & Bozanta Mica) Modeled Flood Inundation Modeled Flood Inundation in the Lapus Basin May 1970 (Sacalaseni Area) Feasibility Study Conclusions Newer data available from radar makes faster modeling feasible Available models can make use of this data to rapidly model flood conditions and speed the warning and preparation process The Vflo, RiverTrak and NWS models are well suited to this upgrade The Vidra model should be continued as an interim approach on larger basins
10 Project Update Seven of the 11 basins are operational Lockheed Martin won the implementation $64 million of US equipment and services export A USTDA success story Title Goes Here Bullets Go Here And Here Case Study: Romania INTEROPERATE Case Study: Romania Case Study: Romania Integrated Climatology, Agro-meteorological, Air Pollution Forecast and Warning, Computation and Training Center (INTEROPERATE) Feasibility Study
11 Primary Project Goals Assess existing integrated system for meteorological surveillance, forecast, and alert system in Romania Analyze proposed enhancements to the forecast and alert systems Primary Project Goals General improvement of the forecasts, especially for severe weather events More accurate characterization of weather events (both in lead time and magnitude) Radar national coverage in Romania Needs Assessment Current Capabilities Computation Requirements Data Storage Requirements Operational Requirements
12 Current Capabilities Sun E4500 w/8 processors Generic Linux cluster of 28 processors 1.2 Terrabytes online Offline storage is varied Need hierarchical storage management system Computation Requirements MM5, WRF, ALADIN, LM, AROME All require a system with high memory bandwidth between processor and main memory Data Storage Requirements Computing data and imaging data must be stored (operational and archival) Desire 30 days of operational data Archival data may be permanent
13 Operational Requirements Redundancy and fault tolerance are critical elements of the system requirements During periods of critical threats or system faults, research applications will be interruptible in favor of operations INTEROPERATE RNMA Existing Data Storage Pools INTEROPERATE Typical Compute Node Configurations Note: A system achieving equivalent performance with a configuration different from the above would be equally satisfactory
14 INTEROPERATE Typical Service Node Configurations Note: A system achieving equivalent performance with a configuration different from the above would be equally satisfactory Training Needs Assessment Infuse developing science and technology into existing operations Maintain level of expertise current with national and international research Enhance and stimulate staff learning Assure effective use of existing and new equipment IT Training Program Categories Supercomputer for operators, administration, users and maintenance Databases for database and OS administrators, users and operators
15 Meteorology Training Program Categories Climate Variability Convective Weather Note - * indicates existing Emergency Management training program Hydrology/Flooding Mesoscale Meteorology* NWP (Modeling) Quantitative Precipitation Forecasting (QPF) Radar Meteorology and Nowcasting* Satellite Meteorology* Winter Weather Agro-Meteorology Modeling* Air Pollution Meteorology* INTEROPERATE Planned processes and products (very high resolution models 2 to 3 km grids) AROME Mesoscale model, non-hydrostatic with km grid using 300 to 600 x the comp ability of ALADIN now COSMO Project (Local Model - LM) - Tested at 2.8 & 7 km grid on generic LINUX cluster WRF A non-hydrostatic mesoscale US model which is an improvement on the MM5 model of PSU Project Update Computer building constructed International tender (RFP) on hold for super computer pending Romanian government funding
16 Title Goes Here Bullets Go Here And Here Case Study: Morocco Weather Radar Network Feasibility Study Mission: Establish an effective national system for forecasting environmental crises to guarantee security and stability Goal: Improve quality of life and promote economic development
17 General Statistics Moroccan GNP $85.2 billion Population 34,436,000 GNP per capita $2,474 Area 446,300 Sq. Km Typical Rainfall varies 50 to 800 mm per year Average Temperature 17 to 19 C Temperature range -7 to 25 C Normal Annual Rainfall Mohammadia 2002
18 Oujda 2008 Nador 2008 b6 Damage Caused by Flooding
19 Slide 54 b6 Fix so the legend can be seen by audience bouman, 8/30/2009
20 Estimated Losses Since the Mid 1990s Loss Description USD Percent of Total Human Loss 20,168, % Peopled touched 631, % Employment 1,479, % Industrial 66,726, % Agricultural 38,566, % Housing 22,648, % Public/Private property 15,641, % Road infrastructure 1,713, % Total 167,572, % b7 Existing Radar Coverage Larache Casablanca Fes Khouribga Bengrir Agadir Deficiencies of Existing Radar Sites Excessive overlap between radars at Casablanca, Khouribga Radars at Fez and Agadir have poor coverage due to interferences of the Atlas Mountains
21 Slide 56 b7 Pat let's discuss the dynamics of this slide bouman, 8/30/2009
22 b12 b13 Radar Coverage Radar Site Analysis b14 b15 Radar Coverage
23 Slide 58 b12 b13 Pat let's discuss the dynamics of this slide bouman, 8/30/2009 Have the new radars fly in sperately bouman, 8/30/2009 Slide 60 b14 b15 Pat let's discuss the dynamics of this slide bouman, 8/30/2009 Have the new radars fly in sperately bouman, 8/30/2009
24 Radar Citing Criteria 1. Improve public safety 2. Decrease economic loss to urban industry and agriculture 3. Improve forecasts 4. Improve aviation safety 5. Aide specific projects (hail suppression and snow enhancement) Conclusions for Morocco Areas between coast lines and the Atlas mountains are covered well by radar Existing radar systems have black spots that limit forecasting impact weather and flood forecasting capabilities No radar sites east of the Atlas Mountains New radar locations are being recommended Title Goes Here Bullets Go Here And Here Case Study: Philippines
25 Case Study Philippines Meteorological and Hydrological Telecommunications Upgrade General Stats of the Philippines Population 88 million Area 298,170 Sq. Km (slightly larger than (AZ) GNP $108 billion GNP per capita $1,300 Typical Rainfall 965 to 4,064 mm Average Temperature Range 25 to 29 C Project Objectives Recommend a reliable and redundant telecommunications system Implementation plan to transmit data to the main and regional centers
26 The Philippines b9 Satellite Images b16 Rainfall Data
27 Slide 68 b9 Fix heading to be consistent to other slides bouman, 8/30/2009 Slide 69 b16 Need to find a map of rainfall distribution... talk to Mark Hegglli bouman, 8/30/2009
28 Photos of Damages Existing and Proposed Radars
29 proposed new repeater North Backbone Apa Tug Aparri Radar Tuguegarao Ilagan Cauayan Baguio Radar Magat Carmen Rosales Yanbong Yan Cau Tarlac Mt. Ampucao Cabanatuan Gapan PAGASA DIC San Rafael existing repeater PAGASA Science Garden South Backbone Science Garden Polilio Baler Radar Tagaytay Lucban PAGASA - DIC Pili Atimonan Sipocot Gapas Bulan Malabog Virac Radar Tugas Legaspi Danao Cagayan de Oro Tac-Dan-Gui Dan-Mal Guiuan Radar Mactan Radar Malasag Legend: proposed new repeater existing repeater The Challenge Existing and proposed radars provide adequate coverage Existing backbone uses 800 MHz The NTC (Philippines FCC) sold the frequency (licensed Spectrum) and it is being used by cellular companies Backbone communications not functional due to interferences
30 Title Goes Here Bullets Go Here And Here Summary Conclusions of Presentation Many developing and middle income countries do not have adequate weather forecasting tools Forecasting tools provide an understanding of storm dynamics and impacts Knowledge is empowering saves lives and protects built environment Conclusions of Presentation Funding is available from USTDA for feasibility studies Other funding programs are available for implementation (USAID, World Bank, multi national banks, etc.) US engineering firms and public/private partners offer advanced technology and expertise of weather management systems
31 Conclusions of Presentation Weather management expertise includes Forecasting systems Now casting radar Real time data Communication systems Data management Modeling and warnings Land use planning and development Title Goes Here Bullets Go Here And Here Your Questions? Thank You!
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