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Fine-scale comparisons of satellite estimates
Chris Kidd
School of Geography, Earth and Environmental Sciences
University of Birmingham
Rationale for finescale comparisons
Daily and monthly estimates hide algorithm problems:• Rain areas/occurrence• Rain intensities
- Temporal and spatial smoothing reduces irregularities
Daily products also have sampling issues – which can cause strobe-like effects with rain movement
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Which UK validation data set?
Gauges
'Ideal' choice – representing 'true' 'at surface' rainfall, but:• daily coverage good – hourly sparse (even in the UK)• poor immediacy (~1-2 months delay)• higher-temporal resolution available, but poor intensity
resolution (tips/min logging = 6 mm/h min rain rate)
Radar
Temporally and spatially superior (down to 5min, 2km), available within an hour of collection: but,
• ground clutter & bright band (despite corrections applied)
• range dependency (ditto)
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Daily vs hourly gauge dataDaily gauge network
06-06Z Hourly gauge network
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Radar: advantages/disadvantages
Blue = radar rain / IR no-rainRed = IR rain / radar no-rainDaily total (mm) 14 Sept 2006
IR:radar matching
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Time skill scores of rain retrievals
Radar
PMW
IR
Rainfall is temporally very fickle
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Finescale Comparisons
Instantaneous comparisons:• Results at instantaneous / 5 km resolutions• AMSR L2 rainfall product (GPROF)• PCT (thresholds set – Kidd 1998 → dT×0.04+dT2×0.005)
• data remapped and processed on European IPWG polar-stereographic projection
Future comparisons…
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
SSMI PCT 06-09-02 06:36
SSMI PCT 06-09-02 07:12
SSMI PCT 06-09-02 09:18
AMSR PCT 06-09-02 03:31
AMSR-L2 06-09-02 13:30
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PCT
L2
Correlations : instantaneous cases
AMSR PCT & GPROF
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Ratio – accumulation : instan. cases
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rain
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PCT ratio
L2 ratio
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Ratio – occurrence : instan. cases
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L2
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Need for case-classification
- rather than the wholesale 'lumping' all data into large temporal results – need to look at the component meteorology associated with the estimates:
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Statistics: blame it on the weather!
Movement:Is the movement perpendicular or along the rain band?
IntensityWhat is the range of values within the rain area?
Size/variabilityWhat is the size and variability of the rain area(s)?
Statistical success has as much to do with meteorology as the algorithms ability…
So… what now?
i) we must remember that PM instantaneous results are better than Vis/IR-based techniques – including merged techniques
ii) high temporal and spatial data can produce very good statistics – if the data is of good quality
iii) prescribed temporal and spatial sampling is not always ideal – are these applicable to applications?
• At present, comparisons at fixed regions and time scales
• Need for flexibility – to match user requirements
• Initial step at thinking about user-defined spatial and temporal time scales
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Current 'interactive' comparison
User dataUser text
Radar datagenerate time slots;copy radar files;accumulate data Graphics
'Standard' IPWG EU region
Statistics:bias, ratio, RMSE, CC, HSS etc
Disk-store
E-mail User
QC checksfile size;byte order;data range
Info checkse-mail;date range;time range
The User
FTP
Why FTP?Simple to use and set up batch jobs…
Why e-mail?Puts the results on the User's desktop…
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Maybe a Javaversion too?
Conclusions
Finescale – instantaneous / ~5km important: it allows us • to disentangle algorithm performance• to assess performance under different conditions• address issues of rain occurrence and intensities
But, issues over:• data integrity (data reliability – flagging of bad pixels)• instrument noise (e.g. AMSR – and RFI)
Need for fine-resolution test cases: particularly with common input data sets.
3rd IPWG workshop, Melbourne, Australia. 23-28 October 2006
Freezing levels“Only one thing we do know is that the freezing level is relatively stable” Tom Wilheit
Effects and contribution of surface variability to precipitation retrievals.
V19 stddevV37 stddevV85 stddev
Surface Variability
4th International GPM Planning Meeting, DC : 15-17 June 2004
-0.5
Rain/no-rain induced biases
-1.0
• Differences in rain/no-rain boundaries reveal regional variations that do not exist in reality
• Further complicated since rain/no-rain boundaries tend to differ over land/sea areas
Trends in Global Water Cycle Variables, UNESCO, Paris. 3-5 November 2004
Conclusions
PMW estimates are capable of retrieving light rainfall
Statistics often confuse the issue: more light rain tends to produce poorer statistics
Instrument noise can be problematic (e.g. AMSR)
Surface screening - potential problems with 'false alarms' over cold/snow surfaces
Lack of 'common' data sets – different algorithms use different source data – different Q.C.
Products
Raw Data Algorithms
Radar
Gauges
Remapping to polar
stereographicprojection
globalquick-look
images
Statisticalanalysis &
imagegeneration
Daily 00-24Zresults
User-definedperiods
(& resolutions)
