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NIO Tropical Action 2011


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It may be a result of wikipedia influencing web sites, but I havent seen anyone but jorge list it above 125 mph...not saying jorge's excellent site is wrong, just that i'm a little suspicious given the satellite presentation at landfall+the lack of corroborating documentation anywhere

Oh, I agree with your skepticism about it-- it doesn't look like a Cat 4 to me-- but I trust that Jorge's site is pulling the official data. It's either JTWC or the New Delhi folks, I believe.

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TCFA issued for 98A. GFS remains the only model going for it, but it takes a major into Iran/Pakistan

The hi-res EnKF-based GFS has been even more bullish with this system than the operational GFS, but has typically been on the left side of the operational track (typically taking it on a turn toward Oman/UAE at the end of its journey (example below from yesterday's 18z run). This is a near real-time, experimental (demonstration) configuration being run by my colleagues at NOAA/ESRL (both a deterministic T574 GFS run from the EnKF mean analysis, as well as a 20 member ensemble forecast).....

mslp2011060818_98A_gfsenkf_cntrl_f120.gif

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The hi-res EnKF-based GFS has been even more bullish with this system than the operational GFS, but has typically been on the left side of the operational track (typically taking it on a turn toward Oman/UAE at the end of its journey (example below from yesterday's 18z run). This is a near real-time, experimental (demonstration) configuration being run by my colleagues at NOAA/ESRL (both a deterministic T574 GFS run from the EnKF mean analysis, as well as a 20 member ensemble forecast).....

How is that different than the 3D-VAR GFS currently employed?

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It may be a result of wikipedia influencing web sites, but I havent seen anyone but jorge list it above 125 mph...not saying jorge's excellent site is wrong, just that i'm a little suspicious given the satellite presentation at landfall+the lack of corroborating documentation anywhere

IBTraCs (which is the source I use) use the official WMO RSMC for their data. The Indian Meteorological Department would be the official RSMC in this case. The official data is here:

http://www.imd.gov.i...ic/bestrack.htm

They have it as a 105kt 10min sustained wind at landfall. I estimate 1min (dividing it by 0.88) to be able to give it a SS category. Wikipedia is probably using JTWC data.

BTW, looks are deceiving, as you well know...Kenna was worse looking... but the IMD is not my favorite RSMC either.

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IBTraCs (which is the source I use) use the official WMO RSMC for their data. The Indian Meteorological Department would be the official RSMC in this case. The official data is here:

http://www.imd.gov.i...ic/bestrack.htm

They have it as a 105kt 10min sustained wind at landfall. I estimate 1min (dividing it by 0.88) to be able to give it a SS category. Wikipedia is probably using JTWC data.

BTW, looks are deceiving, as you well know...Kenna was worse looking... but the IMD is not my favorite RSMC either.

I've not been too impressed with the products I've seen issued from there. Re: Kenna, that was a special case, as it was changing rapidly as it came ashore, a la Michelle 2001 in Cuba. This cyclone was not changing too much-- seemed to be steady state.

Jorge, are you going to add an option on your site to pull JTWC data, too? I think you said that was coming at some point.

Sorry to hijack the thread, Adam. Interesting what the GFS is showing for this. Would be cool if it really did develop into a big cyclone after all.

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How is that different than the 3D-VAR GFS currently employed?

The generation of initial conditions is drastically different, using a serial, square-root ensemble Kalman filter (80 ensemble members). There's a ton of literature....but basically, an ensemble is used to try to capture (sample) the flow-dependent background errors. The update to the short term forecast, to create the analysis, is then done with more comprehensive knowledge about the spatial/temporal error characteristics (in 3DVAR, this is not easily done). Additionally, the use of the ensemble results in a much better multivariate correction to the short term forecast (as one example, the coupling between water vapor and the other variables is sorted out naturally through the ensemble....so you don't have to come up with some sort of ad-hoc/statistical model update moisture based on observations of temperature/wind, and vice versa).

This is way too simplistic of an explanation...but the bottom line is it is a more advanced data assimilation technique (some folks have argued that with the right configuration, it can even beat 4DVAR).

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The generation of initial conditions is drastically different, using a serial, square-root ensemble Kalman filter (80 ensemble members). There's a ton of literature....but basically, an ensemble is used to try to capture (sample) the flow-dependent background errors. The update to the short term forecast, to create the analysis, is then done with more comprehensive knowledge about the spatial/temporal error characteristics (in 3DVAR, this is not easily done). Additionally, the use of the ensemble results in a much better multivariate correction to the short term forecast (as one example, the coupling between water vapor and the other variables is sorted out naturally through the ensemble....so you don't have to come up with some sort of ad-hoc/statistical model update moisture based on observations of temperature/wind, and vice versa).

This is way too simplistic of an explanation...but the bottom line is it is a more advanced data assimilation technique (some folks have argued that with the right configuration, it can even beat 4DVAR).

Thanks. EnKF keeps coming up when I read modeling studies, but I never actually knew what it was.

How is the EnKF-GFS performing compared to the operational model?

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Thanks. EnKF keeps coming up when I read modeling studies, but I never actually knew what it was.

How is the EnKF-GFS performing compared to the operational model?

Sorry to continue the OT discussion....

There are papers from real-time demonstrations for the 2009 and 2010 seasons, though their focus has generally been on the ensemble forecasting component, and not necessarily the deterministic forecasts).

I'm actually working on something called hybrid DA (blending EnKF with 3dvar/4dvar) for my phd research. In my experience for the tropics (include TCs), EnKF and hybrid-based forecasts are almost always superior to the operational. I have to head out for a bit, but I can dig up some references / figures later on today (and send them to you offline, or post some of the verification figs in the thread).

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Here are two fairly recent publications that describe EnKF-initialized GFS (and GEFS) forecasts. Both of the manuscripts focus more heavily on ensemble forecasting, though there is some good stuff in there for deterministic runs as well. There is also a pretty good comparison of operational center performance for these two seasons.

Global Ensemble Predictions of 2009’s Tropical Cyclones Initialized with an Ensemble Kalman Filter

Thomas M. Hamill, Jeffrey S. Whitaker, Michael Fiorino, Stanley G. Benjamin

Monthly Weather Review

Volume 139, Issue 2 (February 2011) pp. 668-688

doi: 10.1175/2010MWR3456.1

Abstract here (with links to the full manuscript)

Predictions of 2010's tropical cyclones using the GFS and ensemble-based data assimilation methods

Thomas M. Hamill, Jeffrey S. Whitaker, Daryl T. Kleist, Michael Fiorino, Stanley G. Benjamin

Monthly Weather Review

doi: 10.1175/MWR-D-11-00079.1

Abstract here (with link to pdf)

The second paper is not yet published but has been accepted (so there is an early-release pdf / unformatted draft available online).

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Excuse the ignorance here, KF refers to the convective parameterization scheme? If so, how does that differ from the op GFS?

Uhhhhh, Ed...

How is that different than the 3D-VAR GFS currently employed?

The generation of initial conditions is drastically different, using a serial, square-root ensemble Kalman filter (80 ensemble members). There's a ton of literature....but basically, an ensemble is used to try to capture (sample) the flow-dependent background errors. The update to the short term forecast, to create the analysis, is then done with more comprehensive knowledge about the spatial/temporal error characteristics (in 3DVAR, this is not easily done). Additionally, the use of the ensemble results in a much better multivariate correction to the short term forecast (as one example, the coupling between water vapor and the other variables is sorted out naturally through the ensemble....so you don't have to come up with some sort of ad-hoc/statistical model update moisture based on observations of temperature/wind, and vice versa).

This is way too simplistic of an explanation...but the bottom line is it is a more advanced data assimilation technique (some folks have argued that with the right configuration, it can even beat 4DVAR).

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Still not sure if its Northerly or Northeasterly shear, or it is just too close to India and ingesting dry air, but it looks pretty sad, and JTWC forecast keeps it as a minimal TC until landfall.

Could be both dry air and shear...

Getting past the secondary peak in May

There are two TC seasons in the North Indian Ocean, namely, before and after the summer monsoon ( Fig. 3.12). The maximum occurrence is in November with a secondary peak in May. Tropical cyclone formation is suppressed during the monsoon season. The reason for the decreased activity is two folds. Firstly, the ITCZ shifts northward to a location over the Indian subcontinent. This decreases the moisture supply necessary for TC formation. Secondly, there is a large vertical wind shear during this season, with the southwesterly monsoonal flow underlying the upper-level easterly jet. This vertical wind shear inhibits TC formation by removing the heating due to convection, which is necessary to lower the surface pressures and create a cyclonic circulation.

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Here are two fairly recent publications that describe EnKF-initialized GFS (and GEFS) forecasts. Both of the manuscripts focus more heavily on ensemble forecasting, though there is some good stuff in there for deterministic runs as well. There is also a pretty good comparison of operational center performance for these two seasons.

Global Ensemble Predictions of 2009’s Tropical Cyclones Initialized with an Ensemble Kalman Filter

Thomas M. Hamill, Jeffrey S. Whitaker, Michael Fiorino, Stanley G. Benjamin

Monthly Weather Review

Volume 139, Issue 2 (February 2011) pp. 668-688

doi: 10.1175/2010MWR3456.1

Abstract here (with links to the full manuscript)

Predictions of 2010's tropical cyclones using the GFS and ensemble-based data assimilation methods

Thomas M. Hamill, Jeffrey S. Whitaker, Daryl T. Kleist, Michael Fiorino, Stanley G. Benjamin

Monthly Weather Review

doi: 10.1175/MWR-D-11-00079.1

Abstract here (with link to pdf)

The second paper is not yet published but has been accepted (so there is an early-release pdf / unformatted draft available online).

Thanks, dtk. I'll take a look at this today and PM you questions, if necessary.

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The monsoon has set in across much of Southern India. Looks like we're done in this basin until autumn.

This thing was a huge disappointment.....but at least it will provide a good case study for us. I could/should post this in the other tropical threads (I may do so when there is actually something interesting), but the near real-time EnKF/GFS runs are available online at:

http://ruc.noaa.gov/hfip/gfsenkf/

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