high-resolution verification for temperature ( in northern italy)
DESCRIPTION
High-Resolution verification for Temperature ( in northern Italy). Maria Stefania Tesini COSMO General Meeting 6-10 September 2010 Moscow. Domain and dataset. SYNOP STATION. REGIONAL NETWORK. - PowerPoint PPT PresentationTRANSCRIPT
General MeetingMoscow, 6-10 September 2010
High-Resolution verification for High-Resolution verification for Temperature Temperature ((in northern Italy)in northern Italy)
Maria Stefania TesiniMaria Stefania Tesini COSMO General MeetingCOSMO General Meeting
6-10 September 20106-10 September 2010MoscowMoscow
General MeetingGeneral Meeting
Moscow, 6-10 September 2010Moscow, 6-10 September 2010
Domain and datasetDomain and dataset
SYNOP STATION
REGIONAL NETWORK
Models involved in this verification are Models involved in this verification are COSMO-I7 (in different configuration), COSMO-I7 (in different configuration), COSMO-I2, det.CLEPS COSMO-I2, det.CLEPS and IFS-ECMWF for comparisonand IFS-ECMWF for comparison
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Moscow, 6-10 September 2010Moscow, 6-10 September 2010
MotivationMotivation
The choice of the verification domain depends The choice of the verification domain depends on the on the fact that we started the verification over that we started the verification over the region where we work the region where we work We focus on this area, even if we can extend the We focus on this area, even if we can extend the verification to the rest of Italy, because the verification to the rest of Italy, because the results on 2m temperature seems to be peculiar results on 2m temperature seems to be peculiar of this region of this region High resolution network allows to group stations High resolution network allows to group stations with same characteristics (e.g. height of the with same characteristics (e.g. height of the station) in order to perform significant statisticsstation) in order to perform significant statistics
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One of the peculiarity…One of the peculiarity…
Spring 2007: Spring 2007: COSMO-I7 didn’t forecast temperature below zero despite some observed frosts in the Po valley The “0 °C” threshold has a physical meaning so is more noticeable, but the overestimation in the early morning happens at all temperature ranges and in all the seasons
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Another peculiarity…Another peculiarity…
In valley stations the MAE of COSMO-I7 00UTC run at In valley stations the MAE of COSMO-I7 00UTC run at 3UTC and 6UTC decrease with the increasing of the 3UTC and 6UTC decrease with the increasing of the forecast timeforecast time
• d1
• d2
• d3
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In the other stations, for other forecast time and for In the other stations, for other forecast time and for 12UTC run fortunately the error follow “the right order”, 12UTC run fortunately the error follow “the right order”, even if the difference among the lines are smalleven if the difference among the lines are small
• d1
• d2
• d3
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T2m COSMO-I7: SON2009T2m COSMO-I7: SON2009
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T2m Other models: SON2009T2m Other models: SON2009
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T2m COSMO-I7 00UTC: LAST YEART2m COSMO-I7 00UTC: LAST YEAR
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T2m COSMO-I7 00UTC: WINTER SEASONT2m COSMO-I7 00UTC: WINTER SEASON
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Remarks on Remarks on COSMO-I7 errors features COSMO-I7 errors features
Different configuration of COSMO-I7 behave in a very Different configuration of COSMO-I7 behave in a very similar waysimilar wayErrors depend on seasons but the same season Errors depend on seasons but the same season presents different errors in different years presents different errors in different years Dependence on height of the stations, in particular for Dependence on height of the stations, in particular for biasbias– In In valley stations: overestimation from 18 UTC to 6 UTC, sudden stations: overestimation from 18 UTC to 6 UTC, sudden
underestimation from 9 UTC to 15 UTCunderestimation from 9 UTC to 15 UTC– In other stations: the cycle seems to be the same as valley In other stations: the cycle seems to be the same as valley
station but shifted towards negative value, masking some errors station but shifted towards negative value, masking some errors
No relevant difference between 00UTC and 12UTC runs, No relevant difference between 00UTC and 12UTC runs, a part for the error at the start of 00UTC runa part for the error at the start of 00UTC run
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Trying to understand the Trying to understand the problems…problems…
1. Test (or Experimental) suite: how the nudging of 2m Temperature (from synop stations) impact on the forecast? [in the operational version only the dew-point temperature is assimilated…]
2. Observed weather conditions in the Po valley: do temperature forecast errors depend on the type of weather?
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COSMO-I7/Test suite “day by day” COSMO-I7/Test suite “day by day” errors:errors:
T2mT2m - FCT+00 - 00UTC - FCT+00 - 00UTC
COSMO-I7 TEST ECMWF COSMO-I7 TEST ECMWF
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Some remarks on COSMO-I7/Test suite Some remarks on COSMO-I7/Test suite “day by day” “day by day” errors at +00 fcsterrors at +00 fcst
The impact of 2mT assimilation is very evident in valley stations:– the bias is considerably reduced by T2m
assimilations
– since the bias is mainly positive, the MAE is reduce consequently reduced
In the stations above 100m the impact is non particularly evident
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Cosmo-I7 / test suite SON2009 Cosmo-I7 / test suite SON2009 T2mT2m – FCT +00 – FCT +00 +72 step 3h +72 step 3h
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Cosmo-I7 / test suite SON2009 Cosmo-I7 / test suite SON2009 Td2mTd2m – FCT +00 – FCT +00 +72 step 3h +72 step 3h
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Cosmo-I7 / test suite SON2009 Cosmo-I7 / test suite SON2009 RHRH – FCT +00 – FCT +00 +72 step 3h +72 step 3h
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Remarks on Cosmo-I7 / test suite Remarks on Cosmo-I7 / test suite for SON2009for SON2009
2m Temperaturepositive impact of the 2m temperature only for the first 6-9 hours of forecast and mainly in valley stationsno significant differences between the two versions for stations above 100 m and for the following forecast steps
2m Dew-point TemperatureSignificant differences in bias. The test-suits tends to become more “dry” increasing the forecast timeTest-suite MAE is better for the first day of forecast, than tends to get worse especially for station above 100 m
2m Relative Humidity Confirm the test-suite tendency to become more “dry” with forecast timea worsening of test-suite MAE for stations below 100 m is observed, while for other stations the differences are small
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Is there an impact on Is there an impact on precipitations?precipitations?
Verification performed comparing the forecast and observed mean (or maximum) in squared boxes
The stations are more ore less the same used for temperature verification
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Cosmo-I7 / test suite SON2009Cosmo-I7 / test suite SON2009 TPTP – FCT +00 – FCT +00 +72 step 6h +72 step 6h
COSMO-I7
Mean > 1 mm/6h
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Cosmo-I7 / test suite SON2009Cosmo-I7 / test suite SON2009 TPTP – FCT +00 – FCT +00 +72 step 6h +72 step 6h
TEST SUITE
Mean > 1 mm/6h
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Cosmo-I7 / test suite SON2009Cosmo-I7 / test suite SON2009 TPTP – FCT +00 – FCT +00 +72 step 6h +72 step 6h
Mean > 5 mm/6h
COSMO-I7
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Cosmo-I7 / test suite SON2009Cosmo-I7 / test suite SON2009 TPTP – FCT +00 – FCT +00 +72 step 6h +72 step 6h
TEST SUITE
Mean > 5 mm/6h
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Cosmo-I7 / test suite SON2009Cosmo-I7 / test suite SON2009 TPTP – FCT +00 – FCT +00 +72 step 6h +72 step 6h
MAX > 10 mm/6h
COSMO-I7
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Cosmo-I7 / test suite SON2009Cosmo-I7 / test suite SON2009 TPTP – FCT +00 – FCT +00 +72 step 6h +72 step 6h
TEST SUITE
MAX > 10 mm/6h
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Remarks on Cosmo-I7 / test suite Remarks on Cosmo-I7 / test suite for SON2009for SON2009
Precipitation
Positive impact for the first 12 hours of forecast for low thresholds
Negative impact for high thresholds in terms of POD
General decrease in FAR joined to reduction of BIAS
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Summary on Cosmo-I7 / test Summary on Cosmo-I7 / test suite comparisonsuite comparison
The assimilation of T2m improve the The assimilation of T2m improve the forecast only in the first 6-12 hoursforecast only in the first 6-12 hours
In the following steps the forecasts get In the following steps the forecasts get worse, especially for variable related to worse, especially for variable related to humidity (Td, RH, precipitation)humidity (Td, RH, precipitation)
We need further investigation on how We need further investigation on how surface parameters such as T2m and surface parameters such as T2m and TD2m propagate to higher layer TD2m propagate to higher layer
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Observed weather conditions in the Observed weather conditions in the Po valleyPo valley
Days are classified on the basis of the observed weather conditions in plain region in a subjective wayThey are divided in 4 classes:– Clear– Partly cloudy– Mostly cloudy/Cloudy– Rain/Snow
Verification has been performed for days in each group
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Observed weather conditions in the Observed weather conditions in the Po valley: daily time seriesPo valley: daily time series
T2m OBSERVED
T2m COSMO-I7
T ground COSMO-I7
MEAN TEMPERATURE of valley stations
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – COSMO-I7 00 UTCvalley: MAM2010 – COSMO-I7 00 UTC
29 days 15 days 10 days 38 days 92 days
The groups are made using weather conditions in plain region
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – COSMO-I7 00 UTCvalley: MAM2010 – COSMO-I7 00 UTC
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – ECMWF 00 UTCvalley: MAM2010 – ECMWF 00 UTC
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – COSMO-I7 12 UTCvalley: MAM2010 – COSMO-I7 12 UTC
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – valley: MAM2010 – DetCLEPSDetCLEPS 12 UTC 12 UTC
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – valley: MAM2010 – DetCLEPS-testDetCLEPS-test
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Observed weather conditions in the Po Observed weather conditions in the Po valley: MAM2010 – ECMWF 12 UTCvalley: MAM2010 – ECMWF 12 UTC
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Remarks on “Observed weather Remarks on “Observed weather conditions in the Po valley”conditions in the Po valley”
Verification show a strong dependence of errors on weather conditions in valley regionModel perform better when is raining or cloudy and worst when is clearThe stratification of the errors is very evident also in “other stations” – note that the selection of the weather condition is based on the weather in plain region
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CONCLUSIONCONCLUSION
The assimilation of T2m improve the forecast only in the first 6-12 hours, but in the following hours the forecasts get worse, especially for variable related to humidity (Td, RH, precipitation)Weather conditions in Po valley influence the magnitude of errors in Temperature
Which are the parameters involved?– Soil moisture, radiation, heat fluxes….?
Ideas?
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Thank you for yor attentionThank you for yor attention