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| Infrared satellite image of the earth.
(Source: ISCCP)
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This project deals with the question of how weather conditions will be different in a possible future warmer climate. In the middle latitudes, where most of the world's population lives, the major weather-makers are midlatitude storms that mix cold and warn air masses and produce high winds and precipitation. In order to explore how different the midlatitude weather of a warmer world will be from the weather that we experience today, it is important to understand how the properties of midlatitude storms may change as climate warms.
Midlatitude storms are disturbances that form along the jet-stream (the river of air that circumnavigates the globe in the Northern and Southern midlatitudes) and travel with it in an eastward direction. The jet-stream owns its existence and draws its energy from the large temperature differences that exist between the Earth's equator and poles. In a warmer climate, a smaller temperature difference between the two regions may result in a slower, less energetic jet-stream. Does this mean that a warmer world will experience fewer or weaker midlatitude storms? Keep in mind that storms, as they travel over the oceans, are fueled by the presence of warm waters underneath them, a condition that will be more prevalent in a warmer climate.
In an attempt to profile the storm of the future, the group will build on the knowledge that can be gained from studying the storms of the past. Tools that scan weather data to locate and track midlatitude storms as well as tools that collocate and correlate storm and cloud properties from weather and satellite observations should be used to fulfill the following objectives:
Combining the different parts of the analysis, attempt to resolve how the frequency and strength of midlatitude storms will change in a warmer climate and what such changes will mean in terms of the everyday weather in the midlatitude regions.
The tasks of locating and tracking storms and of isolating warm and cold time periods for storm comparisons involve the analysis of weather observations from the National Center for Environmental Prediction (NCEP) reanalysis products. The positions of low pressure centers are detected and tracked within continuous series of global, 12-hourly sea level pressure arrays, and monthly-mean surface temperature observations are used to determine the temperature differences between the Earth's equator and poles.
Using the Daily Weather Map series and the Mariner's Weather Log, validate a new algorithm which plots the continuous positions of sea level pressure (SLP) lows to define storm tracks. Then, using a 30-year storm track atlas constructed via the same technique, evaluate the storm tracks, frequencies, and intensities produced by the GISS climate model. Special attention will be given to the GCM's ability to reproduce the seasonal cycle appropriately. Finally, analyze the influence of ENSO and the North Pacific Oscillation on storm tracks, comparing observed data with simulated storm systems.
Analyze sea level pressure and temperature observations from the thirty-year record to examine trends in the midlatitude regions, with the objective to identify warm and cold time periods and examine differences in "midlatitude storminess" between those periods. The analysis will be done for all seasons and will take into account the influences on temperature of El Niño episodes.
Analyze tracks, intensities and frequencies of midlatitude storms and examine those storm properties during warm and cold time periods, with the objective to construct and compare profiles of typical midlatitude storms in those periods. Seasonal and El Niño related influences on those profiles will be investigated.
The tasks of collocating and correlating storm and cloud properties involves the analysis of both meteorological NCEP data and satellite observations from the International Satellite Cloud Climatology Project (ISCCP). Computer algorithms relate properties that define storm strength (wind speed, central pressure) to those relevant for clouds (height, thickness).
Examine relations between storm dynamical properties and cloud type distributions with the objective to determine how changes in the strength of a storm change the relative populations of thinner-drizzling and thicker-raining clouds in the vicinity of the storm. Investigate whether similar relations can be found in the GISS climate model simulations.