Ensemble Prediction Flashcards

1
Q

What is the traditional method of making a weather forecast?

A

Take the best model available and run it until it loses its skill due to the growth of small errors in the initial conditions

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2
Q

Skill is typically lost after ____ days or so, depending on the season

A

6

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3
Q

An alternate method that produces forecasts with skill up to ____ days after the initial forecast uses what is called “____ _____”

A

15 days

“ensemble forecasting”

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4
Q

Instead of using just one model run, many runs with slightly different ____ conditions are made

A

initial

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5
Q

An average, or “____ _____” of the different forecasts is created

A

ensemble mean

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6
Q

Why will the ensemble mean likely have more skill?

A
  • It averages over the many possible initial states

- Smoothes the chaotic nature of climate

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7
Q

Is now possible to forecast probabilities of different conditions because of the ____ ensemble of forecasts available

A

large

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8
Q

Every day, at __Z, ___Z, __Z, and __Z global weather observations are collected, transmitted to major weather centers, and are used to produce a snapshot of the global atmosphere

A

00Z, 06Z, 12Z, and 18Z

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9
Q

What does the “snapshot” of the global atmos (i.e. the model analysis or 0-hour forecast) include?

A

Winds, pressure, moisture, temperature, etc. at multiple vertical levels in the atmos and at grid intersections of about 100 km

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10
Q

Why does an individual model run merely “ sample” one of many possible current and future states of the atmospheric circulation?

A
  • Because of the uncertainty in the initial conditions
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11
Q

What are some examples of uncertainty in initial conditions?

A
  • instrument error
  • spatial/temporal sampling error
  • lack of data
  • erroneous influences of the first guess background field
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12
Q

How does NCEP (and other weather centers) make many forecast runs out of a model out to 15 days?

A
  • Make initial conditions of the individual runs slightly perturbed
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13
Q

What is the most skillful numerical forecast that can be made given the chaotic nature of the atmospheric circulation?

A

The average of all these model integrations

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14
Q

Somewhere between ___ and ___ numerical model runs are executed daily using slightly altered initial conditions

A

12 and 30

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15
Q

These slight alterations are known as “____”.

A

perturbations

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16
Q

These 12 to 30 model runs using perturbed initial conditions are called the ____ ____, and theoretically represent the current _____ ____ of the distribution of atmos states expected in the atmos out to forecast times of 15 days

A

ensemble members

best estimate

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17
Q

One can also use the members to estimate probabilities of certain events, such as ____ ____ or ____ ____ normal temperatures

A

much below

much above

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18
Q

Such probabilities are dependent on the ____ in the forecasts of individual members

A

spread

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19
Q

The ensemble prediction approach attempts to define the ____ ____ ____ of atmosphere variables

A

Probability Density Function (PDF)

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20
Q

This forecast scatter between ensemble members ____ with forecast lead time and should eventually approach the ____ observed in everyday weather

A

increases

scatter

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21
Q

The scatter between separate ____ ____ should approach the ____ _____ scatter of the observed weather

A

model forecasts

normal climatological

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22
Q

What are the 5 steps of the NWP Process?

A

1) Gather Observations
2) Data Assimilation
3) Numerical Weather Predictions
4) Forecast Postprocessing
5) Issue forecasts and evaluate

23
Q

What are the 2 categories of problems with ensemble predictions?

A

1) Chaos

2) Model Error

24
Q

As forecast lead time ____ the ensemble mean maps get _____

A

increases

smoother

25
Q

This increasing ____ reflects the fact that there is more _____ in the predictions at ___ lead times or further into the future

A

smoothness
uncertainty
long lead times

26
Q

The “____ or _____” distribution of states at the initial time is becoming more ____ out as individual members sample different but plausible future solutions of the atmospheric circulation

A

tight or peaked

more spread out

27
Q

Even when there are only slight differences, it is these differences that will result in a very different forecast of the future atmospheric state (due to ____)

A

chaos

28
Q

As one goes further in to the future, the lines start showing more and more spread or scatter so that they look like ______

A

spaghetti

29
Q

Why is the ensemble mean a smoother damped wave pattern?

A

Troughs and ridges which are superimposed on one another from different ensemble members cancel each other out in the mean

30
Q

With ensemble means, information on individual storms is what?

A

Essentially lost so that one member may be predicting high pressure in a region while another is predicting low pressure

31
Q

_____ smoothes out these differences. However, there may still be useful information at these “long-lead” forecast times, especially for the ____ scales of motion

A

Averaging

larger scales of motion

32
Q

What do the two heavy green lines represent on spaghetti plots? And how often do they change?

A

The two climatological lines of 500 mb height that correspond to the red and blue forecast lines.

They change slightly every day and are based on about 30 years of global data

33
Q

By comparing the high latitude ___ line with the ___ lines and the lower latitude ___ line with the ___ line, one can determine how far removed from climatology a particular region is observed or predicted to be

A

green with blue

green with red

34
Q

This suggests that the ensemble mean is approaching ____

A

climatology

35
Q

Sometimes, even for predictions beyond ___ days, most of the predicted lines may remain ___ or ____ their respective climatological lines

A
10 days (240 hours)
remain above or below

(due to ocean SST departures due to El Nino)

36
Q

At the initial time the spread is small so that the distribution must be strongly ____
i.e.: there is relatively ____ confidence about the current state of the atmos

A

peaked

high confidence

37
Q

Any spread is due to the small _____ introduced in the initial conditions of individual ensemble members. Are generally within the range of observational errors

A

perturbations

38
Q

Early on in the forecast integration or cycle, many locations over the hemisphere are ____ removed from their climatological value

A

far

39
Q

As the forecast lead time ____, the departures from climatology get ____ and the spread gets ______

A

increases
smaller
larger

40
Q

This means that the probability distribution is becoming less ____ and at very ____ lead times it should approach the climatological distribution

A

peaked

long lead times

41
Q

Once this climatological distribution is reached, any predictive skill present in the initial conditions of the atmosphere has been ____ and the “forecast” would be __ ____ than using climatology

A

lost

no better

42
Q

Model errors and the manner whereby the initial conditions are perturbed produces a ____ distribution that may deviate from the ____ distribution

A

probability distribution

climatological distribution

43
Q

Individual ___ ____ can systematically contaminate all the ensemble forecasts run on that model, regardless of how the initial conditions are perturbed

A

model biases

44
Q

One solution is to generate ensembles from a ____ of different models.

Name one example

A

cluster

i.e.: the FSU Superensemble

45
Q

What is a big contributor to model error?

A

Parameterizations

46
Q

Much of the weather occurs at scales ____ than those resolved by the weather forecast model.

A

smaller

47
Q

Models must treat, or _____ the effects of the sub-gridscale on the resolved scale

A

parameterize

48
Q

What are five examples of parameterization?

A

1) land surface characteristics and processes
2) cloud microphysics
3) turbulent diffusion and interactions with surface
4) Orographic drag
5) radiative transfer

49
Q

What is a historical weather event which is very similar or closely parallel to the current event?

A

weather analog

50
Q

Even if NWP centers produce calibrated ensemble forecasts at ____ scale, much of the important weather happens at the _____

A

grid scale

sub-gridscale

51
Q

Can solve this problem by finding analogs from the ___, and then use ____ weather observations from these analogs

A

past

actual

52
Q

______ _______ help to compensate for some of the effects of chaos

A

ensemble forecasts

53
Q

ensemble forecast technology is ____; better probabilistic forecasts with each passing year

A

maturing

54
Q

Still can’t expect ____ ____ data to provide reliable weather input to drive extended local forecasts without some adjustment

A

raw ensemble