TEMPERATURE DIAGNOSIS AND FORECASTING 1 TEMPERATURES n BOTH

TEMPERATURE DIAGNOSIS AND FORECASTING 1

TEMPERATURES n BOTH MAX & MIN AFFECTED BY: Land elevation Ground cover Wind off nearby water bodies Wind mixing Cloud cover Moisture content of air Upslope/downslope flow 2

10°CTerrestrial radiation 15°C 10°C Cooled air drains into valley 5°C Land elevation 3

1) Elevation & Lapse Rates Saturated adiabatic lapse rate (SALR) is 0. 5 C per 100 m n Dry Adiabatic lapse rate (DALR) is 1 C per 100 m or with our mixed units => 3 C per 1000 ft n Generally, the higher the station elevation, the cooler the mean temperature, all things remaining equal n 4

Ground cover Albedo/Absorption Solar radiation Less reflection rock & soil More heating Much reflection evaporation & transpiration snow 5 Less heating

2) Exposure & Sun Angle South facing hill or mountain sides receive much more insolation than do those facing northward simply due to the angle of the sun n Sun angle can vary greatly depending on latitude, season, and time of day n 6

2) Albedo n n Is the percent of radiation returning from a surface compared to that which strikes it Represents the reflectivity of a surface n ALBEDO AND SURFACE TYPE OF SURFACE ALBEDO % Deep Ocean 3 -5 Ocean 3 -7 Green Forest 3 -6 Inland Waters 5 - 10 Bare Ground - Wet 8 -9 Bare Ground 10 - 20 Green Fields 10 - 15 Dry Grass 15 - 25 Clouds - thin 35 - 60 Clouds - thick 60 - 80 Ice - sparse snow cover 69 Snow - several days old 70 Fresh Snow 80 - 87 n n n n 7

3) Lake and Land Breezes Are related to insolation and thus show a strong diurnal variation n Effects can often carry several miles inland depending on the size of the water/land boundary and the difference in temperature between the two surfaces n 8

Wind off nearby waters Solar radiation Cool wind cool water Warms slowly Hot air rises Warms quickly warm land 9

Land Breeze Terrestrial radiation Cools quickly Warm water Cools slowly Cool land

Thus, stations near lakes or large rivers tend to be cooler during the day and warmer at night than those away from water bodies n And another side effect… n 11

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4) Vertical Mixing Wind strength, stability in the boundary layer (lapse rate) and terrain roughness all affect the degree of vertical mixing which in turn will have an effect on the temperature n As vertical mixing increases, the lapse rate approaches dry adiabatic through a deeper layer n 13

Turbulent Mixing - Day Cool air warm air Warm surface

Turbulent Mixing - Night Warmer air Cooler air Cold surface 15

Thus, a windy night will be much warmer than a calm night n Even a few knots of wind can make a big difference n 16

5) Cloud cover Albedo for a solid overcast sky is 55% n Blocks incoming shortwave radiation during the day n Traps outgoing longwave radiation during the night n 17

Cloud Cover Day Much Solar Radiation Reflected Cooler Days Slight Warming of Surface 18

Cloud Cover Night Cool air Long wave radiation absorbed Terrestrial Radiation Clouds Re-radiated long-waves Warmer nights 19

6) Moisture in the boundary layer n n n The release of latent heat due to the condensation of water vapour near the surface will slow a downward trend in temperature (night) Similarly, the evaporation of liquid water from the surface will slow down warming of the air due to the latent heat absorbed during evaporation (day) The evaporation of precipitation, especially at the onset of precipitation, tends to cool the air significantly until saturation is reached u Rain changes to snow due to evaporational cooling = BLOWN FORECAST – doh! 20

Moisture can limit nighttime minimum 21

7) Katabatic (cold) or drainage winds n Cold (drainage winds): result from downslope gravity flow of cold, dense air u The cold air pools into valleys u Happens frequently at night as radiation is lost to space u Can reach speeds of up to 14 km/h 22

7) Katabatic (warm) or Foehn winds n n n An air parcel originally at an upstream station at a lower elevation will be cooled adiabatically if forced to rise to a higher elevation downstream – first at the dry adiabatic lapse rate of 1 C per 100 metres and after saturation 0. 5 C per 100 metres Conversely forced subsidence will cause adiabatic warming by compression at the DALR The air temperature on the lee side can be significantly higher than the same air on the upslope side of the mountain 23

chinook Calgary 24

7) Anabatic (valley) winds n When a mountainside is heated by the sun, the katabatic wind of the night will break down, reverse and begin blowing upslope Dry, clear 25

DIURNAL TEMPERATURE TREND Balance of incoming and outgoing radiation decides normal timing (taking only radiation effects into account) of occurrence of maximum and minimum temperatures. n Temperature rises most rapidly in first few hours after sunrise. n Temperature cools most rapidly at sunset. n 26

6 A. M. 12 MIDNIGHT Sunset rap id w NOON 6 P. M. ling coo d rapi arm ing 12 6 A. M. Minimum Temperature Sunrise Maximum Temperature

TE MP ER AT EA HR RE W arm LA SO ing RT E IAT ION Cooling RG NE Cooling AD UR Y 00 06 12 LOCAL TIME 18 00

VLD 7 pm LCL

VLD 10 pm LCL

VLD 1 AM LCL

VLD 4 am LCL

VLD 7 am LCL

VLD 10 am LCL

VLD 1 pm LCL

VLD 4 pm LCL

VLD 7 pm LCL

VLD 10 pm LCL

VLD 1 am LCL

VLD 4 am LCL

VLD 7 am LCL

VLD 10 am LCL

VLD 1 pm LCL

VLD 4 pm LCL

VLD 7 pm LCL

REVERSAL OF NORMAL DIURNAL/NOCTURNAL TRENDS n Frontal passages (strong advection) n Increasing or decreasing cloud cover n Change in wind speeds n Flow off a water body 46

Short Range Temperature Forecasting Techniques 47

MAX TEMP WITH TEPHIGRAMS From one day to the next, total amount of incoming solar energy reaching the ground changes little except for cloud cover differences. n Tephigram method can be used if at least two consecutive days are mostly sunny. n It would be more accurate to calculate exact amount of energy expected for the day and apply it to a tephigram. n 48

MAX TEMP WITH TEPHIGRAMS METHOD n n Find the height to which the dry adiabat extended the previous day at 00 Z. On the 12 Z tephigram follow a dry adiabat from that height to the surface. This will give the approximate forecast max temp. If you are approximating for another location, adjust + or – 3 C for every 1000 ft difference in elevation Best used in well mixed, unstable airmasses (later spring, summer and early fall) 49

Things to keep in mind n n you can also use the forecast 850 mb temperature brought down a dry adiabat (if you are sure that a dry adiabatic lapse rate will form) Any advections should be taken into account Doesn’t work well over higher terrain – must use a higher pressure level Also be aware of superadiabatic lapse rates 50

Superadiabatic Lapse Rates n n Occurs when the temperature decreases with height at a rate >10 C per 1000 metres Usually occurs when there is intense heating at the surface (clear skies, low winds to limit vertical mixing and dry air to limit evaporational cooling) Can also occur over a warm lake when cold air moves over Can also occur in a downsloping wind when sinking air warmed with the dry adiabatic lapse rate is further heated at the surface 51

Superadiabatic lapse rate 52

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EXAMPLE OF MAX TEMP WITH TEPHIGRAMS n At 00 Z the height to which the dry adiabat extends is 770 h. Pa. n On the 12 Z tephigram a dry adiabat from that height to the surface gives a forecast max of 13. 54

An Example Height of dry adiabat last evening Draw dry adiabat down from same height on 12 Z tephi.

PROG TEPHI n Are a source of direct model output Available from: n http: //www. stormchaser. niu. edu/machine/fcstsound. html n See list of available stations (hand out) valid times every three hours You can get historical tephis from : http: //weather. uwyo. edu/upperair/sounding. html n n n 56

Use of Prog Tephis for max temperature forecasting Find the height to which the dry adiabat extended the previous day at 00 Z n BUT… keep in mind that the model surface of prog tephis may not be the actual elevation of the station n Add 3 C for every 1000 foot difference is lower n 57

PERSISTANCE FORECASTING Using the status quo n assumes no overall change in the weather pattern (no advections, no changes in cloud pattern) n Good for stagnant, ridge patterns n 58

MINIMUM TEMPERATURE FORECASTING n n n Forecast the minimum temperature 2 to 5 degrees colder than the current airmass dew point Under clear skies and light winds, the dew point temperature will fall by some 2 to 5 degrees this may be a good indication of minimum temperature since, in order for the temperature to fall below this temperature, considerable latent heat of condensation would be returned to the lower atmosphere 59

MINIMUM TEMPERATURE FORECASTING In the case of little advection, you can also use the same minimum temperature as last night n In the case of strong advection, the best method is to use thickness correlation n 60

MINIMUM TEMPERATURE FORECASTING n Use 850 mb temperature u If overcast and windy, extend 850 mb temp dry adiabatically to surface u If clear skies and windy, assume atmosphere is isothermal, i. e. 850 temp = surface temp u If clear skies and calm, subtract 3 to 4 C from 850 mb to account for radiation inversion n Doesn’t work at high elevations! 61

MINIMUM TEMPERATURE FORECASTING Follow a moist adiabat through the 850 mb dewpoint temperature down to the surface n Use only in an unchanging airmass n 62

THICKNESS/SYNOPTIC CORRELATION METHOD n n n Takes into account many factors that affect temperature all at once. This is because being in the same general synoptic area, wind and cloud cover tend to be the same. Differences in soil make-up and ground cover, as well differences in topography are not taken into account explicitly. Local wind effects and marine effects also not necessarily taken into account. Can’t use this method if reference point 24 hours previous for past maximum or minimum is over the ocean, as it would not relate well to the land area in question. 63

THICKNESS/SYNOPTIC CORRELATION METHOD Relationship between: Thicknesses & temperature; and A station’s position relative to synoptic weather features & temperature. n This method combines these two facts by: 1. Looking at the future (this evening’s or tomorrow’s) thickness and synoptic location for a site of interest, for appropriate valid times (00 Z=Max; 12 Z=Min); & 2. Checking for the same thickness and synoptic location upstream 24 hours previous to determine with what max/min temperature it was associated. 64 n

TODAY’S MAX TEMP REQUIREMENTS: 12 HR GEM prog based on this morning's 12 Z set, for surface isobars and 1000 -500 thickness in BC or 1000 -850 thickness elsewhere 00 HR prog (or analysis) VLD 00 Z from last evening, with same fields as . Yesterday’s maximum temperatures n 65

b) TODAY’S MAX TEMP PROCEDURE: Pinpoint 1000 -500 mb (or 1000 -850) thickness & synoptic location based on isobars and thickness pattern, for STN of interest on 12 hr prog of this morning’s 12 Z issue. Find same thickness (most important) and best synoptic location (relative to correct thickness value) upstream on 00 hr prog of last evening’s 00 Z issue. Determine maximum temperature for this location valid last evening. Expand window in area of interest for more detail. This is first guess. Adjust for any known local effect or synoptic differences (cloud cover, terrain effects, wind speeds. . . ) n 66

YAW Forecast Max for June 8 th, 2005 12 HR PROG VLD 00 Z June 9, 2005 This Evening’s Synoptic Situation 16 15 14 13 12 11 9 8 10 137 138

YAW Forecast Max for June 8 th, 2005 Last Evening’s Synoptic Situation 00 HR PROG VLD 00 Z June 8, 2005 137 138

Last Evenings Max for June 7 th

th Actual Values at YAW June 8 METAR CYAW 081200 Z CCA 27007 KT 4 SM BR BKN 004 BKN 080 BKN 250 14/14 A 2978 RMK SF 6 AC 1 CI 0 DA +454 FT VSBY LWR N SLP 086 53021 SKY 89= METAR CYAW 081300 Z 25004 KT 9 SM FEW 008 FEW 058 FEW 110 SCT 250 16/14 A 2978 RMK CF 1 SC 1 AC 1 CI 0 DA+714 FT VIS LWR SEAWD SLP 086 SKY 34= METAR CYAW 081400 Z 25005 KT 15 SM FEW 016 BKN 250 20/15 A 2979 RMK CF 1 CI 1 SKY 27= METAR CYAW 081500 Z 27005 KT 15 SM SCT 020 BKN 250 22/15 A 2979 RMK CU 3 CI 0 SKY 48= METAR CYAW 081600 Z 18005 KT 15 SM BKN 036 BKN 270 20/15 A 2980 RMK CU 5 CI 1 SKY 78= METAR CYAW 081700 Z 32008 KT 15 SM SCT 037 BKN 270 23/15 A 2981 RMK CU 3 CI 1 SKY 58= METAR CYAW 081800 Z 30011 G 17 KT 15 SM BKN 042 BKN 270 23/14 A 2983 RMK CU 5 CI 1 SKY 78 METAR CYAW 081900 Z 31008 KT 15 SM SCT 040 BKN 270 23/13 A 2984 RMK CU 3 CI 2 SKY 68= METAR CYAW 082000 Z 26012 KT 15 SM SCT 045 BKN 250 23/12 A 2985 RMK CU 3 CI 2 SKY 68= METAR CYAW 082100 Z 30009 G 15 KT 15 SM FEW 050 BKN 250 23/11 A 2987 RMK SC 2 CI 2 SKY 58 METAR CYAW 082200 Z 29007 KT 15 SM FEW 040 BKN 180 22/10 A 2989 RMK SC 2 AC 2 SKY 69= METAR CYAW 082300 Z 31006 KT 15 SM FEW 040 BKN 170 BKN 250 21/11 A 2992 RMK SC 2 AC 4 CI 1 SKY 89= CYAW 71601 HALIFAXSHEARWATER (WOD) NS CN until 14: 09 Jun 09 2005 HZ nl. Hmh. N VIS ww. WW MSLP TT TD DDFF Pmm_hr P_24 SND APPP MX/MN *************************************** 1200 662317 4. 0 2884 1008. 6 14. 0 13. 5 2605 0. 4 6 8. 0 +2. 1 14. 2/9. 8 1800 516016 15. 0 //// 1010. 3 22. 8 13. 8 3011 0. 4 +1. 3 24. 0/9. 8 0000 309727 12. 0 //// 1014. 0 19. 8 11. 4 3104 0. 4 +2. 3 24. 0/9. 9 0600 257002 10. 0 //// 1018. 0 14. 0 10. 8 0000 0. 4 +1. 4 24. 0/9. 9 1200 708707 8. 0 //// 1021. 5 15. 4 12. 1 0000 0. 0 +2. 1 24. 0/12. 8

STATISTICAL FORECASTS n Gradually becoming more reliable. n Tendency to avoid extreme temps (misses very low minimums and high maximums). n May be slow to react to sudden changes in temp with sharp frontal passages. n Available in different types of bulletins. 71

Perfect Prog Statistics n n n Produced using equations based on the relationship of co-existing observed weather elements which are then applied to raw output from the models – includes climate data No corrections made for possible biases in the model - model error decreases accuracy For stations lacking historical data, the surface temperature forecast is taken directly from the GEM model without any statistical processing 72

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UMOS n n Updateable Model Output Statistics Blends data from new model with data from the previous model to ensure stability of the equations and early use of data from the new model Incorporates several years of historical records which uses predictands together with model output Better skill in the longer range 74

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STATISTICAL FORECASTS n FOR British Columbia: Ø FMCN 32 CWAO– Perfect Prog Ø Max and min temps from the global model Ø FMCN 42 CWAO – Pefect Prog Ø Max and min temps from the GEM Ø FXCN 50 CWAO – UMOS Ø Spot temps, POP and wind forecasts Ø From GEM 76

STATISTICAL FORECASTS (cont’d) Ø FXCN 05 CWAO 1 – Perfect Prog Ø Ø 72 hour spot temps, opacity, POP from Global FXCN 09 CWAO 2 – Perfect Prog Ø 48 hour spot temps, opacity, POP from GEM Ø ** note for spot temperature, the max or min may fall between hours thus adjust accordingly Ø Also: FXCN 07 CWAO 1 – Perfect Prog Ø Day 3 -4 -5 clouds, POP, max & min forecasts from Global 77

FMCN 46 CWAO 171520 YGP 7 14 9 YCH 9 16 9 YYG 9 16 9 YQM 9 16 8 YFC 10 18 9 YSJ 9 18 8 YQI 9 17 9 YHZ 10 17 9 YQY 8 17 7 YYT 6 15 6 YQX 5 13 5 YJT 7 17 8 WAX 3 12 4 WDH 5 13 6 YDF 5 15 6 WDS 6 12 6 YAW 9 17 9 YZX 10 20 9 YCL 9 16 9 YGR 8 14 8 WHO 4 13 4 Syno/Thkns Max = 17°C FMCN 36 CWAO 171640 YGP 5 15 6 18 YCH 9 15 8 19 YYG 8 16 8 17 YQM 9 15 8 18 YFC 10 16 9 20 YSJ 10 17 9 18 YQI 9 15 8 16 YHZ 10 17 10 18 YQY 8 16 7 16 YYT 6 15 6 13 YQX 5 14 6 16 YJT 7 18 8 17 WAX 3 13 3 17 WDH 5 14 6 14 YDF 3 14 4 19 WDS 6 12 6 13 YAW 9 16 9 17 YZX 11 19 10 19 YCL 9 16 8 21 YGR 8 13 9 14 WHO 4 13 3 15 FXCN 50 CWAO 171200 NOVA SCOTIA / NOUVELLE-ECOSSE 1/1 UMOS FCSTS BASED ON THE REGIONAL GEM MODEL, FRI JUN 17 2005 12 Z SHEARWATER A NS CYAW 00 03 06 09 12 15 18 21 24 27 30 33 36 39 42 45 48 TT 9 11 12 12 11 10 9 9 10 13 14 13 13 12 11 9 11 POP 17 56 56 40 10 14 34 6 DEG 90 68 70 58 55 48 55 VRB 51 166 188 217 VRB 318 329 333 KMH 12 18 17 16 13 12 14 LGT 10 12 19 14 LGT 13 13 16

Syno/Thkns Max = 17°C FXCN 09 CWAO 8 171830 PART 1 OF 2 PP FCSTS BASED ON THE REGIONAL GEM MODEL, FRI JUN 17 2005 12 Z STN-SPOT TEMP, SPOT OPACITY-TENTHS, 6 HR POP, 12 HR POP GE. 2/ 2/10 MM YAW TTT O P 6 / P 12 / 1800 11 8 03 11 8 19 06 11 7 36/ 21/ 9 09 9 7 21 12 12 10 15 14 9 35 18 17 7 37/ 32/ 17 21 15 7 18 1900 12 7 03 12 8 17 06 11 8 29/ 12/ 11 09 9 6 15 12 12 7

Syno/Thkns Max = 17°C FXCN 05 CWAO 8 171830 (Global) PART 1 OF 2 PP FCSTS BASED ON FRI JUN 17 2005 12 Z STN-SPOT TEMP, SPOT OPACITY-TENTHS, 6 HR POP, 12 HR POP GE. 2 /2/10 MM YAW TTT O P 6 / P 12 / 1800 11 10 03 11 10 22 06 11 10 40/ 23/ 11 09 10 10 28 12 11 10 15 15 10 21 18 15 9 28/ 20/ 13 21 16 9 9 1900 14 8 03 11 8 4 06 10 8 13/ 10 09 11 10 9 12 13 10 15 13 9 0 18 14 8 0/ 0/ 0 21 14 8 0 2000 12 5 03 11 3 0 06 11 0 0/ 0/ 0 09 11 4 0 12 13 5

Direct Model Output (DMO) Output from NWP models n Only as good as model n Tend not to be as accurate as statistical forecasts, but occasionally outperform them n Good for determining point values, especially for calculating what the model forecasts for one spot precipitation amounts, versus guessing from a set of charts n 81

DIRECT MODEL OUTPUT (DMO) n n n Examples of DMO bulletins are: F 0 CN 02 CWAO (Global) – only available for select stations FOCN 03 CWAO 6 (GEM Regional) GEM forecast surface temp chart in SSW and WSW packages Available at: http: //www. weatheroffice. gc. ca/model_forecast/se vere_weather_e. html 82

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Data Mart Some of these bulletins can be found (free!) on Environment Canada’s datamart: n http: //dd. weatheroffice. gc. ca n FMCNs CWAO, FXCN 50 CWAO n NO: fxcn 05, 09 or FOCN bulletins n 84

FOCN 03 CWAO 1 171451 PART 1 OF 2 MODEL DATA 12 Z JUN 17 2005 STA R 1 R 2 R 3 /VVDDFF 158718 TBPT YAW 094077009 ///2402 626037 10// 06 098084008 11314 646137 11 3 12 073067013 11314 656138 11 0 18 078083012 01712 626037 10 1 24 019009078 62409 585936 10 0 30 072016054 02514 555836 13 0 36 095078024 -23409 555836 14 0 42 095073028 03413 535735 11 0 48 087033030 -20017 545835 11 0 Syno/Thkns Max = 17°C

FOCN 03 CWAO 8 Syno/Thkns Max = 17°C FOCN 03 CWAO 8 171453 PART 2 OF 2 MODEL DATA 12 Z JUN 17 2005 STN: YAW FCST H 06 12 18 24 30 36 42 48 VALID AT 1718 1800 1806 1812 1818 1900 1906 1912 FRLVL 128 131 108 115 100 94 90 100 X 8570 161 160 159 158 157 158 X 1085 137 138 137 136 135 T 850 13 14 12 11 9 8 7 7 T. 925 13 16 15 11 13 13 11 8 T 1000 11 11 9 10 14 13 11 11 TSFC 10 10 8 9 13 11 10 11 WND 700 2429 2225 2023 1815 2423 2613 2608 3313 WND 850 2120 2215 1815 2314 2620 2612 2812 3310 WND. 925 1313 1411 1713 2409 2516 3207 3111 0215 WND 1. 0 1007 0906 1003 2008 2303 3408 3508 VV 700 7 15 3 61 4 -19 -2 -15 VV 850 -7 -6 24 33 -12 4 -8 0 APP 3 H 4 10 8 9 2 14 7 11 KI 34 30 31 -15 8 29 27 13 SHR<. 750 7 6 6 4 4 4 5 4 SHR<. 925 9 11 13 8 7 7 11 7 RH. 925 98 99 100 94 86 85 85 96 PCPN 6 H 31 1 6 2 1 0

EXERCISE Jan 18 20 Z false colour 87

IR 19 Jan 1030 Z 88