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(108) Numerical Modeling Fundamentals Exam With Complete Solutions
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(108) Numerical Modeling Fundamentals Exam WithComplete Solutions
Global/ Synoptic: - Answer Coarser/lower resolution: ~30 - 40km and fewer vertical
layers • Takes into account weather across the entire Earth, so boundary errors cannot
occur
Mesoscale/Microscale : - Answer Finer/High resolution: 1.67 - 15km and more vertical
layers • Limited area • The more data points and larger area = more compute power
needed • Needs a global model to provide boundary conditions
Base/Analysis time: - Answer Weather forecasting is an initial value problem. That is,
from eq. (20.17) you need to know the initial conditions on the RHS to predict the
temperature at later times (t + ∆t). Thus to make forecasts of real weather you need to
start with observations of real weather. • The first step is pre-processing in which
weather observations from around the globe and at various times are ingested and
unified onto a regular grid of initial conditions, called an analysis.
Valid time: - Solution Forecasts that occur AFTER the weather has already happened
are called hindcasts, represented by the shaded area in Fig. 20.12. The computer keeps
stepping the forecast ahead in time (C) in little time steps. As the NWP forecast reaches
key times, like 6, 12, 18, and 24 (=00) UTC, the forecasted fields are written off for
post-processing and display, F. Lead time is how far the forecast is ahead of real time.
For example, if the coarse-mesh model, C, produces weather-map products, F, for a
valid time of 18 UTC, then in this hypothetical example such a product would appear at
about 8 h before 18 UTC actually occurs.
Lead Time (tau): - Solution Lead time is how far ahead of real time a forecast is.
"Deterministic models" - Answer refers to NWP model systems with individual,
single-valued forecasts. No uncertainty is accounted for from either errors in the
forecast starting point - i.e. initial conditions - or from NWP model approximations made
in producing the forecast.
, "Probabilistic models", - Answer also called Ensemble Forecast or Ensemble Prediction
Systems (EFS or EPS), allow for uncertainty in initial conditions and/or model estimates.
In doing so they generate forecast probabilities of the exceedance of threshold values of
a variable, such as temperature and precipitation, from. Probabilistic models create
many forecasts, each started from a unique initial condition, and/or using a unique NWP
model configuration, and/or randomly perturbing the change in forecast variables at
fixed time intervals.
Ensemble - Solution Some forecast centers forecast the same time period, but for
different conditions. These differences can be provided, for example, by different initial
conditions, physical parameterizations, numerics and/or NWP models. Such a
procedure gives an ensemble of forecasts showing the sensitive dependence of
weather forecast depending on those different conditions. • The spread in the members
of the ensemble informs you about the uncertainty of the forecast. You have no clue
which of the ensemble members will be closest to reality. It is in this sense that by
averaging all the ensemble members together you can find an ensemble average
forecast that often is more skillful than any single member. This is one of the strengths
of the ensemble forecast.
Multi-model ensemble: - Answer Ensemble created using the average of multiple
models. • This can bring greater skill due to the use of multiple models. • If one model is
off it can lessen the overall skill of the forecast.
Coupled - Answer There are six equations of motion used in numerical modeling. • They
are also sometimes called the primitive equations, because they forecast fundamental
(primitive) variables, rather than derived variables such as vorticity. • These equations
of motion are nonlinear, because many of the terms in these equations consist of
products of two or more dependent variables. Also, they are coupled equations,
because each equation contains variables that are forecast or diagnosed from one or
more of the other equations. Thus, all 7 equations should be solved simultaneously.
Initial and boundary conditions: - Solution Initial Conditions: To start the whole NWP,
we need to have initial conditions (ICs). The initial conditions are produced by a
technique that merges weather observations with past forecasts, see the Data
Assimilation section. There are also ICs, which are usually known by the synoptic time of
most of the observations on which they were based; for example, the "00 UTC analysis",
the "00 UTC initialization", or the "00 UTC model run". In more modern assimilation
schemes it is possible to include asynoptic (off-hour) observations. • Boundary
Conditions: the state of the air along the edges of the forecast domain • Nested grids
can use one-way nesting, in which the coarse grid is solved first and its output is applied
as time-varying boundary conditions to the finer grid.
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