3 research outputs found

    Assessing the Pattern Differences between Satellite-Observed Upper Tropospheric Humidity and Total Column Water Vapor during Major El Niño Events

    No full text
    As part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project, the consistency of satellite-observed upper tropospheric humidity (UTH) and total column water vapor (TCWV) is examined. The examination is focused on their respective patterns during major El Niño events. The analysis shows that the two datasets, consisting of one measurement of vertically averaged relative humidity in the upper troposphere and one of absolute water vapor integrated over the atmospheric vertical column with dominant contribution from the lower troposphere, are consistent over the equatorial central–eastern Pacific, both showing increases of water vapor during major El Niño events as expected. However, the magnitude of drying in the TCWV field over the western Pacific is much weaker than that of moistening over the central–eastern Pacific, while the UTH field exhibits equivalent magnitude of drying and moistening. Furthermore, the drying in the UTH field covers larger areas in the tropics. The difference in their patterns results in an opposite phase in the time series during a major El Niño event when a tropical average is taken. Both UTH and TCWV are closely correlated with major climate indices. However, they have significantly different lag correlations with the Niño 3.4 index in both the sign (positive or negative) and lag time over tropical oceans

    Assessing the Pattern Differences between Satellite-Observed Upper Tropospheric Humidity and Total Column Water Vapor during Major El Niño Events

    No full text
    As part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project, the consistency of satellite-observed upper tropospheric humidity (UTH) and total column water vapor (TCWV) is examined. The examination is focused on their respective patterns during major El Niño events. The analysis shows that the two datasets, consisting of one measurement of vertically averaged relative humidity in the upper troposphere and one of absolute water vapor integrated over the atmospheric vertical column with dominant contribution from the lower troposphere, are consistent over the equatorial central–eastern Pacific, both showing increases of water vapor during major El Niño events as expected. However, the magnitude of drying in the TCWV field over the western Pacific is much weaker than that of moistening over the central–eastern Pacific, while the UTH field exhibits equivalent magnitude of drying and moistening. Furthermore, the drying in the UTH field covers larger areas in the tropics. The difference in their patterns results in an opposite phase in the time series during a major El Niño event when a tropical average is taken. Both UTH and TCWV are closely correlated with major climate indices. However, they have significantly different lag correlations with the Niño 3.4 index in both the sign (positive or negative) and lag time over tropical oceans

    Changing state of the climate system

    Get PDF
    Chapter 2 assesses observed large-scale changes in climate system drivers, key climate indicators and principal modes of variability. Chapter 3 considers model performance and detection/attribution, and Chapter 4 covers projections for a subset of these same indicators and modes of variability. Collectively, these chapters provide the basis for later chapters, which focus upon processes and regional changes. Within Chapter 2, changes are assessed from in situ and remotely sensed data and products and from indirect evidence of longer-term changes based upon a diverse range of climate proxies. The time-evolving availability of observations and proxy information dictate the periods that can be assessed. Wherever possible, recent changes are assessed for their significance in a longer-term context, including target proxy periods, both in terms of mean state and rates of change
    corecore