Browsing by Author "Dessler, Andrew"

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Assessing the Impact of TTL Cirrus on the Climate System - CloudSat and CALIPSO Science Team Recompete/ROSES-2015
Atmospheric Sciences; TAMU; https://hdl.handle.net/20.500.14641/636; NASA-Langley Research Center
We use a forward Lagrangian trajectory model to diagnose mechanisms that produce the water vapor seasonal cycle observed by the Microwave Limb Sounder (MLS) and reproduced by the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) in the tropical tropopause layer (TTL). We confirm in both the MLS and GEOSCCM that the seasonal cycle of water vapor entering the stratosphere is primarily determined by the seasonal cycle of TTL temperatures. However, we find that the seasonal cycle of temperature predicts a smaller seasonal cycle of TTL water vapor between 10 and 40? N than observed by MLS or simulated by the GEOSCCM. Our analysis of the GEOSCCM shows that including evaporation of convective ice in the trajectory model increases both the simulated maximum value of the 100 hPa 10–40? N water vapor seasonal cycle and the seasonal-cycle amplitude. We conclude that the moistening effect from convective ice evaporation in the TTL plays a key role in regulating and maintaining the seasonal cycle of water vapor in the TTL. Most of the convective moistening in the 10–40? N range comes from convective ice evaporation occurring at the same latitudes. A small contribution to the moistening comes from convective ice evaporation occurring between 10? S and 10? N. Within the 10–40? N band, the Asian monsoon region is the most important region for convective moistening by ice evaporation during boreal summer and autumn.
Mechanisms Regulating Water Vapor And Clouds in the Tropical and Extratropical Lower Stratosphere
Atmospheric Sciences; TAMU; https://hdl.handle.net/20.500.14641/636; NASA-Washington
Climate models predict that stratospheric water vapor will increase over the 21st century. Here we conduct experiments using a trajectory model driven by meteorology from a chemistry-climate model to study the contribution of tropical tropopause layer (TTL) temperature and convective ice to the long-term trend of the stratospheric water vapor. We find that the moistening due to TTL warming is not large enough to explain the model’s trend. Adding convective ice evaporation to the trajectory model improves the simulation of water vapor entering the stratosphere, especially during boreal summer. Convective ice mainly evaporates over the Asian monsoon region and the tropical western Pacific region, and the convective ice evaporates faster over boreal summer than boreal winter. Net contribution from convective ice to stratospheric water vapor increases faster on higher level, and the net contribution above 400 K potential temperature contributes most to the stratospheric water vapor at the end of the 21st century. Our trajectory model simulation suggests that over the 21st century, 45% of the increase of the stratospheric water vapor content is due to direct increase in TTL temperatures, 13% of the increase is due to an increase in convective ice content, and 42% is due to increased evaporation allowed by a warming TTL.
Understanding Measurements Of Climate Sensitivity
Atmospheric Sciences; TAMU; https://hdl.handle.net/20.500.14641/636; National Science Foundation
The mean temperature of the earth is determined by the balance of incoming and outgoing radiant energy at the top of the atmosphere, and the outgoing energy generally increases and decreases with mean temperature. The temperature dependence of outgoing energy stabilizes earth's climate, as an increase in temperature produces an increase in outgoing energy which cools the planet, and a decrease in temperature has the opposite effect. The restoring effect of temperature on outgoing energy can be quantified by a climate feedback parameter which summarizes the net effect of a variety of mechanisms which together determine the global effect. For internally generated climate variability such as El Nino, which produces a temporary increase in global temperature, the feedback parameter determines how quickly the temperature will return to its long-term climatological value. For externally forced climate change, such as the warming produced by an increase in carbon dioxide (CO2), the feedback parameter determines the amount of warming that will ultimately occur as a result of the radiative effect of the CO2 increase. It is commonly assumed that the same feedback parameter applies very generally to global temperature changes produced by internal climate variability (like the temperature increase during El Nino events) and permanent climate change forced by increases in carbon dioxide (CO2) and other external factors. But preliminary work by the PI and others suggests a systematic difference between parameter values calculated from internal variability and forced change simulations in climate models, possibly due to differences in the spatial patterns of temperature anomalies associated with internal variability and forced change, and the fact that different feedback mechanisms are prominent in different regions. A difference in feedback strength between forced response and internal variability would complicate efforts to estimate the feedback parameter from observations, as the necessary observations include satellite measurements of the incoming and outgoing top-of-atmosphere radiative fluxes that are only available for a 15-year period. Changes in radiative fluxes over such a short period are dominated by internal variability, thus the feedback parameter value derived from them would only be representative of internal variability and should not be used to assess the sensitivity of climate to CO2 increases. A further issue identified by the PI is that the feedback parameter may have strong decade-to-decade variability, at least in long model simulations of climate under present-day conditions. Such variability, likely also related to the spatial patterns of temperature anomalies and their consequences for specific feedback mechanisms (for instance the albedo feedback associated with ice and snow which generally occur at higher latitudes), would also have to be taken into account when attempting to estimate climate sensitivity from observations. This project considers possible differences in feedback parameter between internal variability and forced change, as well as the possibility of decadal variability in the feedback parameter, using a combination of observations and model simulations. Much of the work focuses on an alternative feedback parameter based on the mean temperature at a mid-tropospheric level (500mb), as parameter values calculated at this level show greater agreement between observations and simulations than their counterparts based on surface temperature. This agreement motivates further examination of the processes contributing to differences in feedback parameter in model simulations, which have the advantage of very long periods of record and outputs which include detailed breakdowns of hard-to-observe quantities such as the longwave and shortwave radiative effects of clouds. The work has broader impacts due to the desirability of constraints on how much warming can result from increases in atmospheric CO2 and other greenhouse gases, particularly given the large uncertainty in estimates from model simulations. The project also supports two graduate students, thereby providing for the future workforce in this research area.