NOAA SBIR Project (Phase I):

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1 NOAA SBIR Project (Phase I): Climate Change Drought Decision Support System -C2D2S2- JFRCCVS Monthly Meeting, 11/21/2008 Graeme Aggett Marc Baldo

2 Outline SBIR Program Background Technical Goals of C2D2S2 Project System Elements Hydrologic Modeling Climate Change Data Data Products Opportunities for JFRCCVS and WAS?

3 SBIR Program Objectives Stimulate technological innovation in private sector Strengthen role of SB in meeting Federal R&D needs Increase commercial application of data and innovations derived from Federal research Widgets

4 SBIR Program Objectives Three-Phase Program: Phase I Feasibility Research Phase II Research and Development Phase III Commercialization

5 SBIR Program Objectives Phase I focus: Exploration and initial phase of development of the DST Phase II focus is on full development of the tool and mechanisms for commercialization of the product Subtopic: Decision Support Tools for Water Resources Management

6 SBIR Program Objectives A current goal of NOAA is to understand climate variability and change to enhance society s ability to plan and respond. Enhanced decision making through better use of information about the impacts of climate variability on climate-sensitive decisions and sectors: Water management Agriculture Public health

7 SBIR Program Objectives (2008).proposals should focus on developing and transitioning products to support drought planning and the communication of climate impact information tailored to regional needs, including products and services of relevance to the US Drought Portal (USDP) initiative

8 C2D2S2 Background Increasing number of academic studies have combined climate and water management models Demonstrated application of physicallybased hydrologic models coupled with simulated warming trends from GCMs in scenario based approaches

9 C2D2S2 Background Many water managers recognize climate change as significant issue Requesting detailed information in an understandable form suitable for planning Academic studies academic in nature - limitations

10 C2D2S2 Background Information may be inconsistent with: specific periods of the historic streamflow record water management models for water planning studies Users therefore less prone to consider results applicable Commissioning of more relevant study (e.g. geographically and system focused) is expensive updated evaluations sometimes necessary

11 C2D2S2 Background Goal of C2D2S2 is thus to: Develop web-based DSS Provide widespread access to tools that can generate climate change scenarios of future streamflow and drought conditions Affordable Used readily within margins of stakeholders current planning frameworks expert general

12 Determine: Elements to develop C2D2S2 system R&D to develop prototype system under Phase II funding Phase I: develop data, methods, tools, and infrastructure necessary to build and power the full C2D2S2 system Feasibility study will develop each element sufficiently that they can be loosely coupled in order to test data exchanges Output and evaluate real data

13 SBIR - This is research! Results will be different than JFRCCVS Naturalized flows will be different Selected scenarios could be different

14

15

16 System Elements and Architecture Data Tier Presentation Tier Home/Intro Login Admin Configure Run View Products Users Cleanup Logs Downscale Business Tier Downscaling API Model API Reporting API Admin API Other System(s) C2D2S2 GCM / Other Software Models TSTool

17 Run View Products Technical Goals of C2D2S2 Project Cleanup Logs Downscale Business Tier Downscaling API Model API Reporting API Admin API Other System(s) C2D2S2 GCM / Other Software Hydro Model TSTool Data Tier Data API GCM, Input, Results, etc. Other System(s) C2D2S2 Data GIS/ Other Sqlite3 Output

18 Hydrologic Modeling RTi NWS Experience Extensive Experience Calibrating and Implementing NWSRFS

19 NWS Model Environment Models operate on a 6-hour timestep Calibrated to physical system responses Include natural and regulation effects Lumped operation basin level resolution Inputs MAT Mean Areal Temperature MAP Mean Areal Precipitation

20 NWS Model Environment Output Predicted streamflow Naturalized streamflow (depending on implementation) Regulation effects Caveats No water rights in system Regulation effects could be lumped

21 Continued Updates MBRFC (Missouri Basin River Forecast Center) RTi Calibrated SAC/SMA parameters

22 Web Implementation Speed issues GCM datasets are large NWSRFS model

23 SAC/SMA Modeling Temperature

24 Penman-Montieth Method Calibrated ET parameters in each NWS basin model Tmin/Tmax station parameters for each weather station in the basin area Adjusted Tmin/Tmax based on climate change scenario

25 Drought Monitoring & Prediction SAC/SMA model provides Soil Moisture States Predicted Naturalized Flows Snow model provides Snow Water Equivalent (SWE) Temperature based energy balance Total system state SAC/SMA, SWE, Reservoir status

26 Climate Change Data ukmo_hadgem1 and NCAR model. Emissions scenarios B1 and A2 Integrating previously downscaled and archived GCM data (USBR) Climate projections at finer spatial resolution Potential to feed C2D2S2 Support several types of C2D2S2 analyses in Phase II: Impacts assessments for social and natural systems Risk-based exploration of planning and policy responses. USBR data available on monthly timestep Downscaled to 1/8 degree grid cell Bias removed from models

27 Climate Change Data - SDSM

28 Climate Change Data SDSM DST for assessing local climate change impacts using a statistical downscaling technique Facilitates development of multiple scenarios of surface weather variables under future climate forcing Performs ancillary tasks of predictor variable screening, model calibration, diagnostic testing, statistical analyses and graphing of climate data

29 Data Products Source:

30 Data Products

31 Data Products Historical mean Historical runoff (simulated) Predicted runoff, H&D, constant delta applied

32 Data Products

33 Data Products

34 Data Products

35 Data Products

36 Landsat TM NASA Research ET and CU Albedo Land Use BBE NDVI Ts LAI Rn Zom G

37 C2D2S2 Web Site

38 C2D2S2 Web Site

39 C2D2S2 Web Site

40

41 C2D2S2 Web Site Are Multi-decadal Climate Forecasts Skillful? Originally posted on November 12, 2008 In one of our July 11, 2005 posts, climate was defined so that climate forecasts are forecasts of the future state of the atmosphere, oceans, land, and continental glaciers, as defined using physical, chemical, and biological variables that we can measure. We can apply local, regional, or global averages over any time period we choose to characterize the future state of the climate. Weather forecasts are a subset of climate forecasts, in that we limit our forecasts to weather conditions, averaged over 12-hour periods, for example, out to a week or more, and generally assume a number of climate variables, such as vegetation and sea-surface temperatures, are invariant over this time period. It is important to note that the averaging time is not what distinguishes weather from climate (e.g., although called seasonal climate predictions, these forecasts are more accurately seasonal-averaged weather predictions ). As a necessary condition, climate forecasts must be able to skillfully reconstruct the observed temporal and spatial variability and change of local, regional, and global climate variables, when the forecast models are only given the external forcings (such as solar irradiance, volcanic eruptions, CO2..

42 Discussion and Questions

43 Impacts of Climate Change Severe and frequent extreme weather events such as droughts, storms, floods, tornadoes, heat waves

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