HiRAD: A Real-Time System to HiRAD: A Real-Time System to Estimate Weather Conditions at Estimate Weather Conditions at

High ResolutionHigh Resolution

Presented to the WG/WIST …

June 7, 2006

HiRAD is a system to derive accurate, high-resolution surface weather observations

Uses multiple inputs, including in situ and remote sensors

Sensible weather estimates are central to the system

Phase II and III operational at TWC

On Local on the 8’s and weather.com

HiRAD SummaryHiRAD Summary

HiRAD SystemHiRAD System

Estimate 2

Estimate 1

Final Wx Estimate

Post Processing

RadarRadarCalibration &

Combination Radar

Fingerprinting LightningLightning

RUCRUC 2.5 -km

Downscaling

Satellite Data

Correctionswith recent obs

Climo Data

Surface Observations

HIRADHIRAD

Operational today @ 10,000 sites

2.5 km resolution gridded version is operational and flowing to MET systems

Observations updated every 20 min; processing in 5 min’s or less.

Gridded data soon available on many platforms

These samples are phase III gridded data

Operational SystemOperational System

81 Tiles running on 33 AMD dual-core server farm:81 Tiles running on 33 AMD dual-core server farm:

2.5 km Grid intersections in metro DC2.5 km Grid intersections in metro DC

National Scale ExamplesNational Scale Examples

HiRAD Local ExamplesHiRAD Local ExamplesFront Range Chinook Lake Effect Snows

DDEQC Schematically..DDEQC Schematically..

DEC-05 DDEQC statistics for all METAR ICAO’s used within HiRAD

Site Var StdErr ScalingKATL T 3.74F 2.5KATL Td 2.90F 2.5KATL U 4.12 mph 3.0KBOS T … etc…

METAR (LDM/NOAAPort) Feed

KLWD 221953Z AUTO 04005KT 4SM BR OVC001 M01/M02 A3029 RMK AO2 SLP272 T10061017 TSNO $= KMLU 221953Z 34006KT 10SM -RA BKN006 BKN010 OVC016 08/07 A3011 RMK AO2 CIG 003V007 SLP196 P0016 T00780067= KODX 221953Z AUTO 01004KT 10SM CLR 00/M06 A3032 RMK AO2 SLP294 T00001061= KSPS 221952Z VRB03KT 10SM FEW018 SCT060 BKN100 10/M01 A3021 RMK AO2 SLP230 T01001006 $= K9V9 221952Z AUTO VRB03KT M03/M10 A3035 RMK AO2 SLP301 T10331100 PWINO FZRANO TSNO $= KTOL 221952Z 04004KT 10SM CLR 03/M05 A3038 RMK AO2 SLP296 T00281050=

DDEQC & other QC FilterLogic

Rejection/Inspection Log..ddeqc20060125120507.log

KIPJ (72314038)

DewPoint 1142 UTC 3.200000 26.143440 2.500000 8.000000Not Available(-99999)

ddeqc20060125122505.log

KFQD (72315045)

DewPoint 1200 UTC 3.200000 25.903797 2.500000 8.000000Sunny(3200)

ddeqc20060125122505.log

KIPJ (72314038)

DewPoint 1202 UTC 3.200000 27.393620 2.500000 8.000000Not Available(-99999)

FAIL?PASS?

Core HiRAD Analysis

Bad wind gust .. Bad wind gust ..

KEVV 251754Z 27009KT 10SM SCT027 03/M04 A3042 RMK AO2 SLP304 T00331039 10033 21017 50015KEVV 251654Z 32010KT 10SM CLR 02/M04 A3042 RMK AO2 SLP305 T00221044KEVV 251554Z 31010KT 10SM CLR 01/M05 A3041 RMK AO2 SLP301 T00111050 $KEVV 251454Z 32011G142KT 10SM CLR 00/M05 A3037 RMK AO2 SLP289 T00001050 51023KEVV 251354Z 29011KT 10SM CLR M01/M06 A3035 RMK AO2 SLP281 T10061056KEVV 251254Z 29008KT 9SM CLR M01/M06 A3033 RMK AO2 SLP275 T10111056 $

Bad wind speeds or gusts generally

attributed to typos (?), and less to

instrumentation. They are rare but often

egregious.

A typical day in DDEQC .. A typical day in DDEQC ..

On January 25, 2006..

Fairly typical day; i.e. representative of total sample.

Total Observations: 75,781Flagged/Withheld: 141Hit Ratio 0.18%Unique ICAO 43

Variable Count % T 58 41.1% Td 79 56.0% U (sust. and gust) 4 1.8%

WIST thoughts w.r.t. HiRAD .. WIST thoughts w.r.t. HiRAD ..

Variational assimilation is a powerful technique

Shelters or isolates raw OBS on the input side .. however, single bad observations can now effect areas instead of single points..

Results can be provided as uniform outputs in time and space (grids)..

Downstream applications need only know their actual location on the earth’s surface and understand how to relate this location to the gridded data.

WIST thoughts w.r.t. HiRAD (cont)WIST thoughts w.r.t. HiRAD (cont)

The sensible weather (present weather, visibility, precipitation type and rate) should receive the lion’s share of attention

Is it possible to have an equivalent of the NLDN or USPLN for other weather variables? That is, very high resolution and very reliable and accurate, but low cost and only a sparse network of actual instruments?

Latency. Start with 0.00 minutes and resist every second of time that is added to the total delay and the resulting time of dissemination.

WIST thoughts w.r.t. HiRAD (cont)WIST thoughts w.r.t. HiRAD (cont)

We fear adding mesonet and other secondary obs sources to HiRAD because of bias, reliability, and q/c implications.

The knock on road sensors is reliability and quality control.

If these obstacles are overcome, it is an extremely valuable source of information.

Other gee-whiz sources must be demonstrated to be reliable, robust, and unbiased. Even 1% error rates are unacceptable and will eat you alive.