Term
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Definition
state of atmospheric conditions
that exist over relatively short periods of time (hours to a couple of days). |
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Term
1.Weather includes which of the following?
thunderstorm, hurricane, blizzard, persistence of a heat wave, or a cold snap. |
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Definition
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Term
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Definition
| weather we expect over the period of a month, a season, a decade, or a century. |
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Term
| 1.weather conditions resulting from the mean state of the atmosphere-ocean-land system |
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Definition
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Term
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Definition
| departure from the expected average weather or climate normals |
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Term
| 1. 9 things that determine weather |
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Definition
Temperature
Elevation
Sun – differential heating
Axis of the earth
Wind patterns
Pressure and density
Humidity
Topography
Geography |
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Term
| 1. 5 things that determine climate |
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Definition
Latitude
Topography (mountains, nearness to large water bodies)
Land use
Average pressure (relates to high and low pressure systems)
Ocean currents and circulation |
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Term
| 1. what is an example of how latitude affects climate? |
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Definition
| Warm and moist at the equator, cold and dry at the poles |
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Term
| 1.what is an example of how altitude affects climate? |
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Definition
| Higher altitudes are colder and dryer |
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Term
| 1.what is an example of how proximity to large water bodies affects climate? |
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Definition
| Water moderates temperature and increases humidity |
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Term
| 1.what is an example of how orography affects climate? |
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Definition
| Mountains can cause clouds & precipitation on the windward side, dry conditions on the leeward side |
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Term
| 1.what atmosphere layer does weather happen? |
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Definition
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Term
| 1.What was Wladimir Köppen responsible for? |
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Definition
| he made the Koppen system which divided the world into 5 climate zones |
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Term
| 1.What instruments are used for direct observation of weather? |
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Definition
| thermometers, rain gauges, humidity measurements, wind gauges, ozone measureers |
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Term
| 1.How are balloon measurements taken and pros/cons` |
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Definition
| multiple in each state, regular daily observations, limited spatial distribution |
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Term
| 1.satellite data pros/cons |
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Definition
| continuous, atmospheric conditions, errors in derivation code, need to be transformed |
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Term
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Definition
| derived from historical records of other surrogate data that can be correlated with a climate variable, many factors can affect these numbers |
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Term
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Definition
| buoys, cruises, observational errors |
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Term
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Definition
| aircraft-based, few weeks, specific to a problem, limited area and period |
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Term
| 1.synthetic data pros/cons |
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Definition
| using weather models to fill in gaps, reanalysis, estimation- not truth, interpolated using physics-not stats |
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Term
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Definition
| Trapping of the Earth’s energy (originally absorbed from the Sun) in the lower atmosphere by greenhouse gases that are transparent to visual but opaque to IR |
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Term
| 1.Enhanced Greenhouse Effect |
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Definition
| An artificial increase in greenhouse gas levels in the atmosphere that leads to an increase in the magnitude of the greenhouse effect |
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Term
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Definition
| A rise in the temperature of the surface of the earth |
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Term
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Definition
| other symptoms caused by the enhanced greenhouse effect, many of which may be of greater concern than a simple warming of global temperature (flood, drought, heatwave, storms, sea level rise, hurricanes, etc.) |
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Term
| 2.What are some sources of error/uncertainty in station data? |
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Definition
-homogeneity-station conditions change over time
-lack of standardization-diff times, diff equipment, diff locations
-time scale- longer records more reliable
-instrument error-calibration, installation, drift, precision
-human error- reading and recording errors, election errors
-precision uncertainty and error- obs taken at different precisions, rounded differently |
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Term
| 2. How can you address station data errors? |
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Definition
| fit the data and delete outliers, select a balanced density of stations, choose high quality stations, use long records, filter out the UHI effect, note station changes, use error bars!, compare with other data sets |
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Term
| 2. urban heat island effect |
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Definition
| strongest at night and low winds, increases air pollution in cities bc of higher temps, more rain downwind |
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Term
2. Global temp change
Where is the world heating up fastest? |
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Definition
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Term
| 2. Big time implications: |
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Definition
| change is happening much faster than past, we are very adapted to this temp, cities are right at sea level, humans are driving warming for first time (should be cooling) |
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Term
| 2. 3 types of thermometers |
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Definition
bulb-liquid changes volume
bimetalic-two metals fused bend w/temp change
thermistor--change in resistance with change in temp |
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Term
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Definition
pressure
forecast short term weather
record long term changes |
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Term
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Definition
humidity
two thermometers- one dry one wet
wet one evaporates and cools...diff in temps |
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Term
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Definition
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Term
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Definition
| temp and dew point temperature |
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Term
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Definition
| temp at which air becomes saturated when cooled at a constant pressure |
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Term
| 2. present weather identifier |
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Definition
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Term
| 2. cloud height indicator |
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Definition
| height of bottom of clouds, laser |
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Term
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Definition
| optical flash and electrical field change |
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Term
| 2. forward scatter visibility sensor |
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Definition
| measures visibility, fog/haze/mist |
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Term
| 2. what do balloons measure? |
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Definition
temp
pressure
wind sp and dir
humidity
location in atmosphere |
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Term
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Definition
| Radio detection and ranging |
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Term
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Definition
target moving away returns energy at a low freq
target moving toward returns energy at a high freq |
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Term
2. Radar colors
blue-
green- |
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Definition
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Term
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Definition
| process of retrospectively creating a best estimate of the atmospheric state over a certain domain at some time interval using a present-day model |
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Term
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Definition
| data assimilation (combiness first guess from model w observation to produce best estimate of atmospheric state) |
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Term
| 3. how does reanalysis take spatially patchy data and make it more useful? |
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Definition
| incorporates spatially and temporally inconsistent observations into a regular gridded analysis |
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Term
| 3. Global NCEP/NCAR Reanalysis (GR |
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Definition
200km hor. resolution
28 ver. levels
Global spectral model (NCEP operational model)
6hr analyses since 1948 |
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Term
| 3. NCEP North American Regional Reanalysis (NARR) |
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Definition
32km hor. resolution
45 ver. levels
Eta gridpoint model (NCEP operational mesoscale model)
3 hr analyses since 1979
reforecsts to 72 hrs using global reeanalysis boundary conditions |
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Term
| 3. Which has higher resolution, NARR or GR? |
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Definition
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Term
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Definition
| to create an accurate, high-resolution, long-term spatially and temporally consistent North American climate record |
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Term
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Definition
| Combining a first-guess provided by a model short-term forecast and observations to produce a best estimate of the atmospheric state |
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Term
| 3. How do you get the "best guess"? |
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Definition
| a first guess from previous forecast and observations |
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Term
| 3. where does the data come from for assimilation? |
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Definition
- Cloud-track winds
- ACARS aircraft temperature, winds
- Radiosonde temperature, winds, RH
- Surface temperature, winds, altimeter |
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Term
| 3. what are reanalysis problems? |
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Definition
-Representativeness errors due to gross terrain mismatch
-Lack of background variance, Causes overconfidence in the first-guess
Model bias, Errors are spread throughout the domain |
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Term
| 4. how do you access hrothgar? |
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Definition
| open putty or bitvise and type in hrothgar.hpcc.ttu.edu connection SSH |
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Term
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Definition
Global Climate Model
or
General Circulation Model |
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Term
| 5. circulation of the atmosphere is mainly driven by ____ |
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Definition
| tropics receive more energy from the Sun than the poles |
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Term
| 5. what 6 concepts of basic science are used in climate modeling? |
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Definition
1. Conservation of momentum
2. Hydrostatic equation (how pressure varies with height - gravitational force balanced by pressure gradient force)
3. Conservation of energy (1st Law of Thermodynamics: change in energy is equal to net transfer across boundaries by advection, evaporation, condensation
4. Continuity equation (conservation of mass – mass is neither created nor destroyed)
5. Equation of state (thermodynamic state of atmosphere determined by pressure, temp, & density
6. Moisture conservation (accounts for changes in water vapor due to advection, condensation, evaporation |
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Term
| 5. How are basic science types of climate models different from ones that might be based on statistical relationships between variables? |
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Definition
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Term
| 5. How did climate models evolve? |
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Definition
70s-rain and CO2
80s-clouds, land, ice
FAR-shallow ocean
SAR-volcanic activity, sulphates, and deep ocean
TAR-aerosols, carbon cycle, ocean circulation, rivers
AR4-chemistry in atmos, vegetation
(AR=assessment report) |
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Term
| 5. what wavelength is reflected by clouds? |
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Definition
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Term
| How has resolution changed over time? |
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Definition
1990-500km
1995-250km
2000-180km
2005-110km
1 |
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Term
| 5. what is structural uncertainty? |
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Definition
Are all the important physical processes being correctly represented in the model? Is anything missing?
Processes we do have in the model, but don’t know if we’re even doing right or we know we’re not doing correctly
Processes we don’t have in the model (including the possibility for surprise), some of which we do know about and some of which we don’t
Both depend on FEEDBACKS: highly non-linear interactions between multiple components of the climate system |
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Term
| 5. what is parametric uncertainty? |
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Definition
How are processes that occur at spatial or temporal scales smaller than the model can resolve being represented?
Processes that cannot be explicitly represented by the basic dynamical and thermodynamic variables in the basic equations (dynamics, continuity, thermodynamic, equation of state |
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Term
| 5. What are examples of structural uncertainty? |
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Definition
CO2 levels and other mitigation efforts
ICE sheets
permafrost melting and methane
volcanic activity in the future
geothermal emissions |
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Term
| 5. What are examples of parametric uncertainty? |
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Definition
local scale circulation-small mountains or big hills
precipitaion-type, size, location, timing |
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Term
| 5. Explain the cloud pos feedback |
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Definition
warming > evap> more water vapour >more warming
more water vapor>more clouds> more heat trapped
more clouds> more sunlight reflected |
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Term
| 5. do high or low clouds trap heat/ reflect sunlight? |
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Definition
high clouds trap heat
low clouds reflect sunlight |
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Term
| 5.Explain the three types of parameterizations |
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Definition
1. Processes taking place on scales smaller than the grid-scale, which are therefore not explicitly represented by the resolved motion
2. Processes that contribute to internal heating (non-adiabatic)
3. Processes that involve variables additional to the basic model variables (e.g. land surface processes, carbon cycle, chemistry, aerosols, etc |
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Term
| 6. Why are high-res projections needed? |
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Definition
because we need to know what will happen on a local level to know how it will impact humans and natural systems
-also, there can be different signs of temp change within the same grid
-basic climate variables aren't enough...we're interested in things like days with snowfall
-to help policy makers, farmers, industry, tourism, health |
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Term
| 6. What three basic steps are needed in downscaling? |
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Definition
-Downscaling: dynamical or statistical
-Temp: comparing SD methods
-Precipitation:digging deeper |
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Term
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Definition
| the simulation of sub-gridscale variables from coarser-resolution fields BY INTRODUCING NEW INFORMATION |
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Term
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Definition
| the assumption that variables at finer resolution than the spatial or temporal scale of the input are a reproducible function of large-scale features resolvable by the input and available high-resolution information |
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Term
| 6. where does the new information come from for downscaling? |
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Definition
Observations (statistical models) or
higher resolution modeling of physical procsess (dynamical or regional climate models) |
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Term
| 6. pros/cons of statistical downscaling |
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Definition
pro: flexible and rapid, doesn't require as much CPU, can relate GCM variables directly to impact relevant variables not simulated by climate models
cons: assume stable large-to-small-scale forcing over decadal time scales..don't know if stats will hold in future
-sensitive to choice of predictors |
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Term
| 6.pros/cons of dynamic downscaling |
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Definition
pro: directly simulate sub grid scale processes and include dynamical changes in response to large scale forcing
cons: dependent on GCM performance, very expensive and time consuming
sensitive to initial boundary conditions |
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Term
| 6. What are the steps in downscaling? |
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Definition
STEP 1: Develop relationship between large-scale predictor and observed predictand
(statistical or dynamical)
STEP 2: Use relationship to generate high-resolution fields from large-scale forcing |
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Term
| 6. what is the assumption of local climate for statistical modeling? |
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Definition
| local climate= variability of large scale atmospheric/oceanic patterns, local topography and other time invariant factors, and stochastic noise |
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Term
| 6. What are the statistical modeling assumptions? |
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Definition
-Observations are “truth”
-GCM predictors are relevant to local climate and realistic at the large scale
-Relationships are stationary over time
-Predictors fully represent the climate change signal |
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Term
| 6. How is the observation data quality controlled in downscaling? |
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Definition
Identify abnormal high/low values for each weather station
Compare to neighboring stations to see if any of these stations (even one) also has an abnormally high or low value on the same day or one day before or after
Look for multiple repeats (5 days or more of same value)
Look for days where Tmax < Tmin, or values are higher or lower than maximum or minimum values ever recorded in North America
Standardize file formats: Year Month Day Value (degC, mm) |
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Term
| 6. How do you determine if statistical relationships are stationary over time? |
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Definition
| use a high resolution gcm as past and future "obs", use coarse resolution as past and future "model", then you look at diff between future obs and future downscaled |
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Term
| 6. Do predictors represent climate signal? |
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Definition
| Current temp/variables are currently linked, but not all may change much in future (sea level pressure-temp) |
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Term
| 6. Describe the Delta method |
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Definition
Take DELTA (Historic-future averages)
add Delta to Observation values
=future projections
This looks like a shift in the bell curve |
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Term
| 6. Describe the Bias Correction Spatial Disaggregation method |
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Definition
Take monthly observations and upscale them, add these to historical monthly GCM to correct for bias, train the quantile mapping model with upscaled monthly observations and bias correct GCM simulators. Use trained trained quantile mapping model and future GCM simulations to generate monthly projections. Add daily observations to monthly projections and generate daily projections by scaling daily values of random selected OBS month and downscaled GCM value
This looks like a shifted and rounded bell curve |
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Term
| 6. Describe the analogue approach method |
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Definition
Take daily observations and assemble library of daily high res weather patterns. Upscale daily weather and downscale GCM resolution. Select upscaled observed patterns similar to global model pattern and combine into a consrtucted analog using lsr.
Use regression coefficients to |
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Term
| 6. How would yo downscale Lubbock using DELTA method? |
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Definition
You'd calculate the average for 1960 to 2013. Then for a future 30 years. Take future- historical
add to observations, giving you future conditions |
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Term
| 6. What are three valid comparisons of SDM's |
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Definition
1. relative to obs used in training period
2. relative to obs from an independ. evaluation period
3. relative to future high-resolution simulations |
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Term
| 6. what are invalid comparisons of SDMs? |
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Definition
1. relative to obs not used to train data
2. relative to specific days or years |
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Term
| 6. Name 4 differences between regional and global models |
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Definition
R=domain limited &rectangular
G=domain wraps around earth, spherical
R=needs dynamical boundaries
G=external forcing only
R=needs nat variability as input
G=generates own nat variability
R=topography and physics
G=coarse res of topography and physics |
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Term
| 6. name 6 similarities between regional and global models |
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Definition
1. same physical properties
2.physical equations on a regular grid
3.G=full century, R=run decades, but CAN run a century
4.calculate conditions on day, mo, and year scale
5. same variables calculated
6. limited by parameterization and structural uncert. |
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Term
| 6. structural uncertainty |
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Definition
| things in the model that are modeled wrong or not included |
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Term
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Definition
| things that are too small spatially or temporally to model or things that change over time |
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Term
| 6. what are the some downfalls of statistical and dynamical models |
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Definition
1. produce diff predictions under climate forcing scenarios
2. only as good as the GCM projections
3. neglect 2-way interactions btw R&G climate
4. can fail to capture impt feedback processes |
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Term
| 6. Sources of error in downscaling |
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Definition
-measurement error and missing obs
-parameterization could be wrong
-avg across a grid cell to smoooth variability
-between model error
-bias relative to observations
-bias and error downscaled from GCM |
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Term
| 7. How do you evaluate RCM's |
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Definition
-GCM driven climatologies to gridded observations at RCM scale
-Reanalysis driven climatologies AND events to gridded observations |
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Term
| 7. What can we learn from RCMs? |
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Definition
Quantify biases due to resolution
understand limitations to parameter.
identify structural improvements |
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Term
| 8.Name 4 types of uncertainty in future projections |
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Definition
Human/scenarios
natural variability
modeling and climate science
errors |
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Term
| 8. What are the human/scenario uncertainties? |
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Definition
Scenario uncertainty
Future emissions
Technology
Policies
Population
Response to change (adaptation)
Mitigation (reducing emissions) |
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Term
| 8. What are the natural variability uncertainties? |
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Definition
Chaotic weather
Natural events (e.g. volcanoes |
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Term
| 8. What are the modeling and climate science uncertainties? |
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Definition
Earth’s response to human activities
Model uncertainty
Over- and under-fitting
Physics – incorrect or unknown or badly parameterized
Model limitations (strengths and weaknesses – good at some things, not at others) |
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Term
| 8. What are the error uncertainties? |
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Definition
Human error – doing something you shouldn’t (on anything from small to large scales)
Data quality (including errors)
Computational errors |
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Term
| 8. 4 main reasons future projections are uncertain: |
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Definition
1. Future emissions uncertain
2. earth sensitivity uncertain
3. limited ability to model climate system at regional scale
4. ongoing nat variations are chaotic |
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Term
| 8. KNOW THE blue/green/orange graphs! |
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Definition
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Term
| 8. ____ is the greates source of uncertainty in projections in the next 20-30 years |
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Definition
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Term
| 8. ___is the greatest source of uncertainty in projections for next 40-60 yrs |
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Definition
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Term
| 8. ___greatest source of uncertainty in precipitation beyond 60-70 yrs for many regions (except Alaska or the Southwest) |
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Definition
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Term
| 8. ____are greatest source of uncertainty in temperature projections beyond 60-70 yrs |
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Definition
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Term
| 8. Global mean temperature change likely between ___ for 20-30 yrs, 40-60 yrs, 60-70 yrs |
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Definition
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Term
| 8. What recommendations are given for minimizing natural variability uncertainty? |
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Definition
| use mult simulations to cover range of likely variability |
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Term
| 8. What recommendations are given for minimizing model uncertainty? |
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Definition
| use simulations from multiple climate models to cover an adequate range of climate sensitivity |
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Term
| 8. What recommendations are given for minimizing scenario uncertainty? |
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Definition
| : use multiple scenarios covering a range from high to low. At minimum, SRES A1fi/B1 or RCP 8.5/2.8. |
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Term
| 8. What is the major source of uncertainty in projected temperature changes over: the near-term? By mid-century? Out beyond the middle of the century? |
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Definition
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Term
| 8. How is uncertainty in precipitation different than temperature? |
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Definition
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Term
| 8. How are the sources of uncertainty at high latitudes different from uncertainty at lower latitudes? |
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Definition
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Term
| 8. Three types of climate sensitivity |
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Definition
Transient climate response (years to decades)
Equilibrium climate sensitivity (centuries)
Earth system sensitivity (millennia) |
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Term
| 8. what 4 interfaces do feedbacks happen |
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Definition
land to atm
atm to ocean
surf ocean to deep
lithoshphere to atm and ocean |
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Term
| 8. Where does transient climate sens occur? what temp change for 2xCO2? |
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Definition
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Term
| 8. Where does equilibrium climate sens occur? what temp change for 2xCO2? |
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Definition
water vapor, sea ice, snow cover
2-4.5C |
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Term
| 8. Where does earth system climate sens occur? what temp change for 2xCO2? |
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Definition
| carbon cycle, destabilization of methane deposits, melting of land ice, ocean circulation |
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Term
| 8. Why don't we know future emissions? |
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Definition
| depend on pop/technology/economy |
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Term
| 8. What's a big problem with socio-economic models? |
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Definition
| they divide up to socio-economic regions- not physical boundaries (Rest of World) |
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Term
| 8. Describe the 3 sets of IPCC scenarios |
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Definition
1992-IPCC Scenarios- based on lit and UN and IEA info
2000-SRES Special Report on Emission Scenarios- based on storylines of pop and economy changes
2010 RCP Repres. Concentration Pathway scenarios-- storylines developed in parallel |
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Term
| 8. What's diff btwn SRES and RCP? |
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Definition
| RCP represent a broader range at end, similar at beginning. None represent "business as usual" |
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Term
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Definition
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