Using VIIRS Land Surface Temperature to Evaluate NCEP North American Mesoscale Model (NAM) Forecast
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1 Using VIIRS Land Surface Temperature to Evaluate NCEP North American Mesoscale Model (NAM) Forecast Zhuo Wang (University of Maryland) Yunyue Yu (NOAA/NESDIS/STAR) Peng Yu (University of Maryland) Yuling Liu (University of Maryland) Michael Ek (NOAA/NCEP/EMC) Yihua Wu (I. M. System Groups, Inc.) November 13,
2 Outline 1. Introduction 2. Data Processing Method 3. Comparison results between VIIRS LST and NAM 6-hr data, as well as NAM hourly forecast data 4. Summary 2
3 Introduction Purpose: To promote the use of satellite Land Surface Temperature (LST) product in the models, and investigate the difference between the model and satellite data, and try to understand how such difference can be helpful to model and satellite product. Available Predicted Surface Temperature from NCEP models: NAM (North American Mesoscale Model) over CONUS (4km, 12km) North American Land Data Assimilation System (NLDAS): 0.125, hourly, January 1, 1979 present Satellite retrieved LST from VIIRS: Granule based VIIRS LST (750 m at nadir) Case study: March 2012, NAM 4km LST 3
4 Data Processing Method 1. Temporal match: use linear interpolation between two closest time to get the corresponding NAM data at VIIRS granule time 2. Spatial match: convert both VIIRS and NAM data to 0.05 grid. 3. Use aggregation to get new VIIRS LST for 0.05 lat/lon grid, i.e., averaged all VIIRS pixels falling in the 0.05 grid to represent the value of new 0.05 grid. For surface type, use the dominant type to represent that grid. Only high quality data are used in the comparison. 4
5 6 Hour Analysis Data: Daily mean LST difference (NAM VIIRS) in March 2012 Day Night 5
6 1 Hour Forescat Data: Daily mean LST difference (NAM VIIRS) in March 2012, f00 Day Night 6
7 Monthly mean LST difference versus IGBP surface type (6Hr) (NAM VIIRS) Day Night 1. ENF 5. Mixed Forest 9. Savanna 13. Urban and Built-up 2. EBF 6. Closed Shrubland 10. Grasslands 14. Vegeration Mosaic 3. DNF 7. Open Shrubland 11. Permanent Wetlands 15. Snow and Ice 4. DBF 8. Woody Savanna 12. Croplands 16. Barren or Sparse vegtation 17. Water Bodies 7
8 Monthly mean LST difference versus IGBP surface type (1Hr, f00) (NAM VIIRS) Day Night 1. ENF 5. Mixed Forest 9. Savanna 13. Urban and Built-up 2. EBF 6. Closed Shrubland 10. Grasslands 14. Vegeration Mosaic 3. DNF 7. Open Shrubland 11. Permanent Wetlands 15. Snow and Ice 4. DBF 8. Woody Savanna 12. Croplands 16. Barren or Sparse vegtation 17. Water Bodies 8
9 Linear Interpolation for NAM Land Surface Temperature (6Hr, 1Hr) e.g., satellite view time= 19.5Hr Linear interpolation is more reasonable using 1hr NAM data. Hr 18 Hr 19 x Hr 20 x x x x x Hr 24 9
10 Model Performance 1 Spatial Map for 6-Hour Analysis Day NAM VIIRS Night Std Samples 10
11 Model Performance 1 Spatial Map for Hourly Forecast (f00) Day NAM VIIRS Night Std Samples 11
12 Distribution of VIIRS LST and NAM Hourly Forecast (Day) VIIRS LST NAM Std NAM VIIRS Surface Type 12
13 Distribution of VIIRS LST and NAM Hourly Forecast (Night) VIIRS LST NAM Std NAM VIIRS Surface Type 13
14 Match-up between Satellite View Time and NAM Hourly Forecast Time Satellite View Time (night) Hr=8 UTC, dt = 8 * 0 Hr x * x Satellite View Time (day) Hr=21 UTC, dt = 21 6 Hr dt = 2 x x dt = 15 dt = 20 dt = 9 12 Hr x x 18 Hr x dt = 14 x dt = 3 dt = Satellite View Time Forecast Starting Time (how far away from the start time in each forecast cycle) 14
15 Monthly Mean Comparison vs. Satellite&Forecast Time Difference 15
16 NAM data used in Comparison for [16 18Hr] 16
17 NAM data used in Comparison for [18 22Hr] 17
18 NAM data used in Comparison for [20 21Hr] 18
19 Surface Type Map: 4 Regions for Model-Satellite Data Comparison Reg 3: IGBP 4 Reg 2: IGBP 7 Reg 1: IGBP 10 Reg 4: IGBP 14 19
20 Reg1: IGBP10 (0.2 ) March 11 Monthly Day Night 20
21 Reg1: IGBP10 (1 ) March 11 Monthly Day Night 21
22 Reg1: IGBP10 (2 ) March 11 Monthly Day Night 22
23 Reg2: IGBP7 (1 ) March 14 Monthly Day Night 23
24 Reg3: IGBP4 (1 ) March 11 Monthly Day Night 24
25 Reg4: IGBP14 (1 ) March 13 Monthly Day Night 25
26 Table 1. The monthly mean difference and standard deviation of VIIRS and NAM LST over 4 regions for day and night time (NAM VIIRS) Day Monthly Night Monthly LST STD Samples LST STD Samples Reg1 (1 ) Reg1 (1 ) Reg2 (1 ) Reg2 (1 ) Reg3 (1 ) Reg3 (1 ) Reg4 (1 ) Reg4 (1 )
27 Snow and Ice Chart from U.S. National / Naval Ice Center March 14, 2012 The large LST Difference in Reg2 (open Shrubland) on March 14 is not Related to snow Large LST difference in high latitude may caused by snow. 27
28 Summary The patterns of NAM and VIIRS LST are consistent. The VIIRS LST variation is larger than NAM LST. NAM and VIIRS LST difference has zonal (dominant) and meridional distribution, which reflects the geographic features. The NAM-VIIRS LST difference does not show the time dependent feature. The 1 statistic map indicates that western region has larger bias than eastern region. The difference (including bias and std) between NAM and VIIRS LST at night is smaller than that during the daytime. The comparison results depend on surface type. e.g., the difference over open shrubland is larger than that over grassland and cropland. Snow is also related to large LST difference. 4 forecast cycle provides similar comparison results. 28
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