Fog detection product

Transcription

1 Fog detection product derived from RGB recipes Takumi Maruyama, Haruma Ishida and Koetsu Chubachi Meteorological Satellite Center / Japan Meteorological Agency Meteorological Research Institute / Japan Meteorological Agency HAREX CORPORATION RGB Experts and Developers Workshop 2017 JMA Headquarters, Tokyo, Japan, 7-9 Nov HIMAWARI HIMAWARI-9

2 Introduction Seasonal variability of Night microphysics RGB Night microphysics RGB is useful for monitoring low cloud (fog) in nighttime. However, the colors are changed by depending on seasonal variations and climate characteristics (regional dependence). Fog/St Fog/St Summer Jun, 5, UTC Winter Jan, 3, UTC The variability of the colors brings forecasters some difficulties to understand the meaning of the colors. 2

3 Outline of Fog Detection Satellite based threshold Nighttime NWP(T, RH) based threshold Radiosonde (Kushiro) Night microphysics RGB Daytime black : T ( ) blue : Td ( ) Night microphysics RGB hutched area : NWP_RH(Surf) > 90% Natural color RGB General features of (radiation) Fog Relative humidity is high (almost 100%) at surface. Cloud top height is low and the cloud top temperature is similar to the ground surface temperature. Capped inversion layer is formed at cloud top and relative humidity is low above the cloud top. 3

4 Example : RGB imagery with Fog detection product (Near Japan) Night Microphysics RGB Day/Night Fog Detection Product Fog/St Natural color RGB Fog/St Yellow:Nighttime Red:Daytime Meso-Scale Model (MSM) is used for NWP. Spatial resolution : 0.02 Time resolution : 10 minutes Jun, 05, UTC Jun, 05, UTC 4

5 Threshold in nighttime (Satellite) Fog Low cloud Clear sky horizontal axis : BT(B07, 3.9μm) BT(B13, 10.4μm) vertical axis : BT(B13, 10.4μm) ( ) color : BT(B13, 10.4μm) BT(B15, 12.4μm) BT(B07) BT(B13) value is lower than -1.5 in many fog cases. BT(B13) value is higher than -10 in many fog cases. It may suggest that ice fog cases are very few. BT : Brightness Temperature SYNOP (Jul, 1, 2015 Jul, 31, 2016) 5

6 Threshold in nighttime (NWP) Fog Low cloud Clear sky horizontal axis : NWP_RH(Surf) (%) vertical axis : NWP_T(Surf) BT(B13, 10.4μm) color(red) : NWP_RH(Surf) > NWP_RH(700hPa, 850hPa, 925hPa) color(blue) : NWP_RH(Surf) =< NWP_RH(700hPa, 850hPa, 925hPa) BT : Brightness Temperature NWP_T : NWP Temperature NWP_RH : NWP Relative Humidity NWP_T(Surf) BT(B13) value is lower than 10 in many fog cases. NWP_RH(Surf) value is higher than 85% in many fog cases. NWP_RH(Surf) value is highest under 700hPa in many fog cases. SYNOP (Jul, 1, 2015 Jul, 31, 2016) 6

7 Process flow in nighttime Start BT(B13) > NWP_T(700hPa) and NWP_RH(700hPa) < 90% high/middle cloud elimination No Yes BT(B07) BT(B13) < -1.5 low cloud extraction No No Yes BT : Brightness Temperature REF : Reflectance NWP_T : NWP Temperature NWP_RH : NWP Relative Humidity fog extraction1 NWP_T(Surf) BT(B13) < 10 and BT(B13) > 10 Yes NWP_RH(Surf)>=85% and NWP_RH(Surf) > NWP_RH (700hPa, 850hPa, 925hPa) Result=Not fog No fog extraction2 Yes Result=Fog B07 : 3.9μm B13 : 10.4μm End 7

8 Threshold in daytime (Satellite) Fog Low cloud Clear sky horizontal axis : REF(B03, 0.64μm) vertical axis : REF(B05, 1.6μm) / REF(B04, 0.86μm) color : BT(B13, 10.4μm) ( ) BT : Brightness Temperature REF : Reflectance When REF(B03) value is high but REF(B05) / REF(B04) value is low, land surface may be covered with snow/ice. REF(B03) value is lower than 0.3 in many clear sky (land surface) cases. SYNOP (Jul, 1, 2015 Jul, 31, 2016) 8

9 Threshold in daytime (NWP) Fog Low cloud Clear sky horizontal axis : NWP_RH(Surf) (%) vertical axis : NWP_T(Surf) BT(B13, 10.4μm) color(red) : NWP_RH(Surf) > NWP_RH(700hPa, 850hPa, 925hPa) color(blue) : NWP_RH(Surf) =< NWP_RH(700hPa, 850hPa, 925hPa) BT : Brightness Temperature NWP_T : NWP Temperature NWP_RH : NWP Relative Humidity NWP_T(Surf) BT(B13) value is lower than 10 in many fog cases. NWP_RH(Surf) value is higher than 85% in many fog cases. NWP_RH(Surf) value is highest under 700hPa in many fog cases. SYNOP (Jul, 1, 2015 Jul, 31, 2016) 9

10 Process flow in daytime Start BT(B13) >T_NWP(700hPa) and RH_NWP(700hPa)<90% high/middle cloud elimination No Yes REF(B03) > 0.3 and REF(B05) / REF(B04) > 0.5 low cloud extraction snow/ice elimination No No Yes BT : Brightness Temperature REF : Reflectance T_NWP : NWP Temperature RH_NWP : NWP Relative Humidity fog extraction1 T_NWP(Surf) BT(B13) < 10 and BT(B13) > 10 Yes RH_NWP(Surf)>=85% and RH_NWP(Surf)>RH_NWP (700hPa, 850hPa, 925hPa) Result=Not fog No fog extraction2 Yes Result=Fog B03 : 0.64μm Snow/ice area is eliminated by B04 : 0.86μm End B05 : 1.6μm visible and near-infrared bands B13 : 10.4μm in daytime. 10

11 Evaluation by ground observations (SYNOP) Aug, 1, 2015 Jul, 31, 2016 Threat Score= FO/(FO+FX+XO) Bias Score=(FO+FX)/(FO+XO) Hit Ratio = (FO+XX)/N Misdetection Ratio= FX/(FO+FX) Undetected Ratio = XO/M SYNOP total Fog Not Fog Misdetection Fog Fog Hit(FO) FO+FX (FX) Detection Not Undetected Product Hit(XX) XO+XX Fog (XO) total M X N Requirement Clear sky or Low cloud or Fog by SYNOP Sun zenith angle > 93 (nighttime) or < 85 (daytime) BT(B13, 10.4μm) > NWP_T(700hPa) NWP_T(700hPa) < 90% Meso-Scale Model (MSM) is used for NWP. SYNOP Day/Night (24 Hour) Fog Detection Product Daytime Nighttime Number of data Threat Score Bias Score Hit Ratio Misdetection Ratio Undetected Ratio Nearest grid to SYNOP is evaluated. Accuracy is almost same between day and night. Main reason of misdetection and undetected is failure of distinguishing between fog and low cloud (especially stratus). 11

12 Pros/Cons of the fog product Pros Can detect fog at day and night boundary. Can detect fog visible through the gap between the high/middle clouds Cons Can t detect fog under the high/middle clouds. Can t detect ice fog for fear of misdetection of clear sky over snow/ice area. Can t detect local fog such as valley fog that is smaller than the product resolution Fog detection area depends on NWP accuracy and characteristics 12

13 Summary Night microphysics RGB is useful for monitoring low cloud (fog) in nighttime. However, colors of RGB imagery is changed by some features (regional dependence, seasonal dependence). This variability brings forecasters some difficulties to understand the meaning of the colors. We developed Day/Night Fog Detection product. It can display fog area in the same color without regional and seasonal dependence. Main reason of misdetection and undetected is failure of distinguishing between fog and low cloud (especially stratus). Even though we use NWP data, it is difficult to distinguish them. 13

14 Thank you for your kind attention! 14

15 Appendix 15

16 Example : RGB imagery with Fog detection product (Full Disk) Night Microphysics RGB Day/Night Fog Detection Product True Color Reproduction Image (m) Yellow:Nighttime Red:Daytime Global Spectral Model (GSM) is used for NWP. Spatial resolution : 0.02 Time resolution : 10 minutes Oct, 07, UTC SYNOP fog observation point and visibility (color) We also plan to develop full disk fog detection product which uses Global Spectral Model (GSM). 16

17 What s Night Microphysics RGB? UTC R : B15(I2 12.3)-B13(IR 10.4) Range : -4~2 [K] Gamma : 1.0 G : B13(IR 10.4)-B07(I4 3.9) Range : 0~10 [K] Gamma : 1.0 Thick Upper Cloud How Low the Cloud or Surface B : B13(IR 10.4) (Reverse) Range : 243~293 [K] Gamma : 1.0 Lower Water Cloud 17

18 Night Microphysics Cold, thick, high level cloud Very cold (< 50 C), thick, high level cloud Thin Cirrus cloud Thick, mid level cloud Thin, mid level cloud Low level cloud (high latitudes) Low level cloud (low latitudes) Ocean Land Note: Based on SEVIRI/EUMETSAT interpretation 18

19 19

20 Misdetection of low cloud Daytime Low cloud Nighttime It is difficult to distinguish between fog and stratus. horizontal axis : NWP_RH(Surf) (%) vertical axis : NWP_T(Surf) BT(B13, 10.4μm) 0(blue):Cumulonimbus 1(green):Cumulus 2(yellow):Cumulus and Stratocumulus 3(orange):Stratocumulus 4(red):Stratus BT : Brightness Temperature NWP_T : NWP Temperature NWP_RH : NWP Relative Humidity SYNOP (Jul, 1, 2015 Jul, 31, 2016) 20

21 Evaluation by ground observations (SHIP) Aug, 1, 2015 Jul, 31, 2016 Threat Score= FO/(FO+FX+XO) Bias Score=(FO+FX)/(FO+XO) Hit Ratio = (FO+XX)/N Misdetection Ratio= FX/(FO+FX) Undetected Ratio = XO/M SHIP total Fog No Fog Misdetection Fog Fog Hit(FO) FO+FX (FX) Detection Not Undetected Product Hit(XX) XO+XX Fog (XO) total M X N Requirement Clear sky or Low cloud or Fog by SHIP Sun zenith angle > 93 (nighttime) or < 85 (daytime) BT(B13, 10.4μm) > NWP_T(700hPa) NWP_T(700hPa) < 90% SHIP Day/Night (24 Hour) Fog Detection Product Daytime Nighttime Number of data Threat Score Bias Score Hit Ratio Misdetection Ratio Undetected Ratio Nearest grid to SHIP is evaluated. Meso-Scale Model (MSM) is used for NWP. 21

22 Evaluation by ground observations (SHIP) Aug, 1, 2016 Jul, 31, 2017 Threat Score= FO/(FO+FX+XO) Bias Score=(FO+FX)/(FO+XO) Hit Ratio = (FO+XX)/N Misdetection Ratio= FX/(FO+FX) Undetected Ratio = XO/M SHIP total Fog No Fog Misdetection Fog Fog Hit(FO) FO+FX (FX) Detection Not Undetected Product Hit(XX) XO+XX Fog (XO) total M X N Requirement Clear sky or Low cloud or Fog by SHIP Sun zenith angle > 93 (nighttime) or < 85 (daytime) BT(B13, 10.4μm) > NWP_T(700hPa) NWP_T(700hPa) < 90% SHIP Day/Night (24 Hour) Fog Detection Product Daytime Nighttime Number of data Threat Score Bias Score Hit Ratio Misdetection Ratio Undetected Ratio Nearest grid to SHIP is evaluated. Meso-Scale Model (MSM) is used for NWP. 22

23 Evaluation by ground observations (SYNOP) Aug, 1, 2016 Jul, 31, 2017 Threat Score= FO/(FO+FX+XO) Bias Score=(FO+FX)/(FO+XO) Hit Ratio = (FO+XX)/N Misdetection Ratio= FX/(FO+FX) Undetected Ratio = XO/M SYNOP total Fog Not Fog Misdetection Fog Fog Hit(FO) FO+FX (FX) Detection Not Undetected Product Hit(XX) XO+XX Fog (XO) total M X N Requirement Clear sky or Low cloud or Fog by SYNOP Sun zenith angle > 93 (nighttime) or < 85 (daytime) BT(B13, 10.4μm) > NWP_T(700hPa) NWP_T(700hPa) < 90% SYNOP Day/Night (24 Hour) Fog Detection Product Daytime Nighttime Number of data Threat Score Bias Score Hit Ratio Misdetection Ratio Undetected Ratio Nearest grid to SYNOP is evaluated. Meso-Scale Model (MSM) is used for NWP. 23

24 Evaluation by ground observations (SYNOP) Aug, 1, 2015 Jul, 31, 2016 Threat Score= FO/(FO+FX+XO) Bias Score=(FO+FX)/(FO+XO) Hit Ratio = (FO+XX)/N Misdetection Ratio= FX/(FO+FX) Undetected Ratio = XO/M SYNOP total Fog Not Fog Misdetection Fog Fog Hit(FO) FO+FX (FX) Detection Not Undetected Product Hit(XX) XO+XX Fog (XO) total M X N Requirement Clear sky or Low cloud or Fog by SYNOP Sun zenith angle > 93 (nighttime) or < 85 (daytime) BT(B13, 10.4μm) > NWP_T(700hPa) NWP_T(700hPa) < 90% SYNOP Day/Night (24 Hour) Fog Detection Product Daytime Nighttime Number of data Threat Score Bias Score Hit Ratio Misdetection Ratio Undetected Ratio Nearest grid to SYNOP is evaluated. Global Spectral Model (GSM) is used for NWP. 24

25 Evaluation by ground observations (SHIP) Aug, 1, 2015 Jul, 31, 2016 Threat Score= FO/(FO+FX+XO) Bias Score=(FO+FX)/(FO+XO) Hit Ratio = (FO+XX)/N Misdetection Ratio= FX/(FO+FX) Undetected Ratio = XO/M SHIP total Fog No Fog Misdetection Fog Fog Hit(FO) FO+FX (FX) Detection Not Undetected Product Hit(XX) XO+XX Fog (XO) total M X N Requirement Clear sky or Low cloud or Fog by SHIP Sun zenith angle > 93 (nighttime) or < 85 (daytime) BT(B13, 10.4μm) > NWP_T(700hPa) NWP_T(700hPa) < 90% SHIP Day/Night (24 Hour) Fog Detection Product Daytime Nighttime Number of data Threat Score Bias Score Hit Ratio Misdetection Ratio Undetected Ratio Nearest grid to SHIP is evaluated. Global Spectral Model (GSM) is used for NWP. 25