1. RAMS Input Data

2. Types of input data Meteorological data  First guess gridded data – NCEP, ECMWF, etc.  Surface observations (single level measurements at the ground)  Vertical profile observations (rawindsonde, multi-level met tower, wind profiler, RASS, sodar, etc.) Surface characteristic data  Topography  Water surface temperature  Land use/vegetation type  NDVI  Soil type

3. Easiest to use in GRIB format  NCEP Reanalysis/Reanalysis2/GFS data – http://nomad3.ncep.noaa.gov/ncep_data http://nomad3.ncep.noaa.gov/ncep_data GFS – ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/gfs/prodftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/gfs/prod  NCAR – some datasets online, others can be purchased  ECMWF – must go through EU country, difficult and expensive  INPE/CPTEC (Brasíl) – operational forecasts for South America, not sure if/how they distribute  Others? Where to get data? – Gridded data

4. Where to get data? - Surface, upper air A variety of formats available:  NCAR – past year available online for free, past years can be purchased http://dss.ucar.edu/datasets/ds464.0/ http://dss.ucar.edu/datasets/ds353.4/ ADP format – converter available on our web site  NCEP – current global obs in METAR format  Others?

5. Where to get data? - Topography Global 30-second resolution (about 1km) dataset available on our web site Many other sources Typically, local sources may have higher resolution

6. Where to get data? – Water temp Global 1-degree resolution climatological dataset available on our web site (monthly) Sea-surface temperature sometimes available in first-guess files NCEP has separate files (somewhere!) None of these sources do a good job with inland water (bays, rivers, lakes) because of coarse resolution Some higher-resolution, satellite-derived datasets available for US coast, any for Colombia?

7. Where to get data? – Land use Global 30-second resolution (about 1km) dataset available on our web site from USGS Any simulation should be carefully checked Many regions outside of the US used old data sources Local sources usually best for small regions Must be able to translate to RAMS vegetation class categories

8. Where to get data? – NDVI Only needed in RAMS v6.0 Global 30-second resolution (about 1km) dataset available on our web site (monthly) Used to determine several vegetation characteristics (roughness length, albedo, etc.) Should be checked carefully for any simulation For short runs and small areas, it may be better to use a specified constant value

9. Where to get data? – Soil type More specifically, soil textural class Only used in RAMS v6.0 Global dataset about 5km resolution available on our web site from UN/FAO Simulations not usually very sensitive, unless soil type is very wrong (e.g., sand vs. clay)

10. Format Conversions - Met data RAMS requires meteorological data to be in RALPH format (being renamed to GDF) Text format that is easily edited and transferred. Document describes the details Examples:

11. RALPH (GDF) gridded data 999999 2 2004 7 12 0 0 17 144 73 1 2.5000 2.5000 -90.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 1 1000 925 850 700 600 500 400 300 250 200 150 100 70 50 30 20 10 0.700 1.200 1.700 2.100 2.600 3.100 3.500 4.000 4.500 4.900 5.300 5.700 6.200 6.600 6.900 7.300 7.700 8.000 8.400 8.700 9.000 9.200 9.500 9.700 10.000 10.200 10.400 10.500 10.700 10.800 10.900 11.000 11.100 11.100 11.100 11.100 11.100 11.100 11.000 10.900 10.800 10.700 10.600 10.400 10.200 10.000 9.800 9.500 9.300 9.000 8.700 8.400 8.100 7.700 7.400 7.000 6.600 6.200 5.800 5.400 5.000 4.500 4.100 3.600 3.200 2.700 2.200 1.700 1.200 0.800 0.300 -0.200 -0.700 -1.200 -1.700 -2.100 -2.600 -3.100 -3.500 -4.000 -4.500 -4.900 -5.300 -5.700 -6.200 -6.600 -6.900 -7.300 -7.700 -8.000 -8.400 -8.700 -9.000 -9.200 -9.500 -9.700 -10.000 -10.200 -10.400 -10.500 -10.700 -10.800 -10.900 -11.000 -11.100 -11.100 -11.100 -11.100 -11.100 -11.100 -11.000 -10.900 -10.800 -10.700 -10.600 -10.400 -10.200 -10.000 -9.800 -9.500

12. RALPH (GDF) surface obs data 999999 2 5 WINDSPEED m/s WIND_DIRECTION deg TEMPERATURE C DEWPOINT C STN_PRES Pa 2004 07 10 2100 33663 48.450 27.780 78. 0.00 000 360. 000 19.8 000 17.7 000 99810.0 000 2004 07 10 2100 FTTJ 12.130 15.030 295. 1.54 000 140. 000 25.0 000 23.0 000 -999.0 999 2004 07 10 2100 DFFD 12.350 -1.520 316. 1.54 000 160. 000 28.0 000 23.0 000 -999.0 999 2004 07 10 2100 GOGS 12.400 -16.750 16. 3.60 000 280. 000 28.0 000 23.0 000 -999.0 999 2004 07 10 2100 GABS 12.530 -7.950 380. 1.03 000 300. 000 25.0 000 24.0 000 -999.0 999 2004 07 10 2100 GBYD 13.350 -16.800 36. 0.00 000 360. 000 28.0 000 25.0 000 -999.0 999 2004 07 10 2100 DRRN 13.480 2.170 223. 2.57 000 100. 000 30.0 000 25.0 000 -999.0 999

13. RALPH (GDF) upper air data 999999 2 2004 7 11 1200 01152 0036 0013 67.28000 14.45001 31.00000 100000.000 000 31.497 000 12.00 000 0.7214 000 92500.000 000 677.766 000 5.60 000 0.9320 000 85000.000 000 1367.511 000 4.40 000 0.6007 000 79300.000 000 1931.823 000 3.20 000 0.3466 000 78900.000 000 1972.813 000 2.80 000 0.5967 000 77900.000 000 2076.026 000 2.20 000 0.4365 000 77400.000 000 2128.052 000 2.00 000 0.5947 000 70000.000 000 2930.796 000 -4.10 000 0.7289 000 69900.000 000 2942.086 000 -4.10 000 0.7346 000 68200.000 000 3135.921 000 -5.70 000 0.6233 000 67700.000 000 3193.678 000 -5.30 000 0.1070 000 67500.000 000 3216.913 000 -5.10 000 0.1721 000 64800.000 000 3536.534 000 -7.10 000 0.3744 000 56700.000 000 4565.487 000 -13.50 000 0.1224 000 54700.000 000 4837.922 000 -15.10 000 0.2164 000 50000.000 000 5510.000 000 -20.70 000 0.2207 000 33.000 000 1.03 000 5.00 000 1367.000 000 4.12 000 220.00 000 2930.000 000 4.12 000 280.00 000 5510.000 000 8.23 000 320.00 000 7120.000 000 14.92 000 340.00 000 9070.000 000 14.92 000 340.00 000 10280.000 000 8.23 000 330.00 000 11780.000 000 2.06 000 335.00 000 13720.000 000 5.14 000 320.00 000 16440.000 000 4.12 000 40.00 000 18810.000 000 2.06 000 90.00 000 21040.000 000 6.17 000 75.00 000 24460.000 000 8.23 000 95.00 000

14. Format Conversions - Met data First-guess  GRIB format – fdgrib (from our web site)  Other formats – custom converter required Surface/upper-air observations  NCAR ADP format – dprep-ncar (from our web site - soon!)  Other formats - dprep-generic (from our web site)

15. Format Conversions – Surface data RAMS requires topography, SST, etc. in “blocked” form. Example file name: EL40N100W

16. Format Conversions – Surface data Converters  Topography, SST – mktopo.f (from our web site)  Land use – special version of mktopo.f (contact me)  Soil, NDVI for v6.0 – new version of mktopo.f (make_blocks), will be on our web site soon.