Simulation of Ice Cloud Particle Size, Humidity and Temperature Measurements from the TWICE CubeSat
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Engineering topics
Publications and source records attributed to Su, Hui.
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Here, a version of the WRF-Chem model with fully coupled aerosol–meteorology–snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol–radiation interaction (ARI), aerosol–snow interaction (ASI), and aerosol–cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34–42° N, 117–124° W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about –0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about 7 % for precipitation, 3 % for SWE, and 7 % for surface runoff for the whole domain, while the corresponding numbers are 12, 10, and 10 % for the mountaintops. The reduction in SWE is more significant in a dry year, with 9 % for the whole domain and 16 % for the mountaintops. The maximum reduction of ~20 % in precipitation occurs in May and is associated with the maximum aerosol loading, leading to the largest decrease in SWE and surface runoff over that period. It is also found that dust aerosols can cause early snowmelt on the mountaintops and reduced surface runoff after April.
Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO 2 ) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable to a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. In addition, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.
The interactions between aerosols and ice clouds represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. In particular, the impact of aerosols on ice crystal effective radius (R ei ), which is a key parameter determining ice clouds' net radiative effect, is highly uncertain due to limited and conflicting observational evidence. Here we investigate the effects of aerosols on R ei under different meteorological conditions using 9-yearsatellite observations. We find that the responses of R ei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters. While there is a significant negative correlation between Rei and aerosol loading in moist conditions, consistent with the “Twomey effect” for liquid clouds, a strong positive correlation between the two occurs in dry conditions. Simulations based on a cloud parcel model suggest that water vapor modulates the relative importance of different ice nucleation modes, leading to the opposite aerosol impacts between moist and dry conditions. When ice clouds are decomposed into those generated from deep convection and formed in situ, the water vapor modulation remains in effect for both ice cloud types, although the sensitivities of R ei to aerosols differ noticeably between them due to distinct formation mechanisms. The water vapor modulation can largely explain the difference in the responses of R ei to aerosol loadings in various seasons. A proper representation of the water vapor modulation is essential for an accurate estimate of aerosol–cloud radiative forcing produced by ice clouds.
This study evaluates the distribution and variation of carbon monoxide (CO) in the upper troposphere and lower stratosphere (UTLS) during 2004-2012 as simulated by two chemical transport models, using the latest version of Aura Microwave Limb Sounder (MLS) observations. The simulated spatial distributions, temporal variations and vertical transport of CO in the UTLS region are compared with those observed by MLS. We also investigate the impact of surface emissions and deep convection on CO concentrations in the UTLS over different regions, using both model simulations and MLS observations. Global Modeling Initiative (GMI) and GEOS-Chem simulations of UTLS CO both show similar spatial distributions to observations. The global mean CO values simulated by both models agree with MLS observations at 215 and 147 hPa, but are significantly underestimated by more than 40% at 100 hPa. In addition, the models underestimate the peak CO values by up to 70% at 100 hPa, 60% at 147 hPa and 40% at 215 hPa, with GEOS-Chem generally simulating more CO at 100 hPa and less CO at 215 hPa than GMI. The seasonal distributions of CO simulated by both models are in better agreement with MLS in the Southern Hemisphere (SH) than in the Northern Hemisphere (NH), with disagreements between model and observations over enhanced CO regions such as southern Africa. The simulated vertical transport of CO shows better agreement with MLS in the tropics and the SH subtropics than the NH subtropics. We also examine regional variations in the relationships among surface CO emission, convection and UTLS CO concentrations. The two models exhibit emission-convection- CO relationships similar to those observed by MLS over the tropics and some regions with enhanced UTLS CO.
No abstract available
This paper gives an overview of August 2004 through July 2009 upper tropospheric (UT) water vapor (H2O) and ice water content (IWC) from the Aura Microwave Limb Sounder (MLS) and comparisons with outputs from the NASA Goddard Earth Observing System Version 5 (GEOS-5) data assimilation system. Both MLS and GEOS-5 show that high values of H2O and IWC at 215 to 147 hPa are associated with areas of deep convection. They exhibit good (within approximately 15%) agreement in IWC at these altitudes, but GEOS-5 H2O is approximately 50% (215 hPa) to approximately 30% (147 hPa) larger than MLS, possibility due to its higher temperatures at these altitudes. GOES-5 produces a weaker intertropical convergence zone than MLS, while a seasonally-migrating band of tropical deep convection is clearly evident in both the MLS and GEOS-5 UT H2O and IWC. MLS and GEOS-5 both show spatial anti-correlation between IWC and H2O at 100 hPa, where less H2O is associated with low temperatures in regions of tropical convection. At 100 hPa, GEOS-5 produces 50% less IWC and 15% less H2O in the tropics, and approximately 20% more H2O in the extra-tropics, than does MLS. Behavior of the 100 hPa H2O, which exhibits a quasi-biennial oscillation, appears consistent with it being controlled by temperature. The seasonal cycle in the vertical transport of tropical mean H2O from approximately 147 hPa to approximately 10 hPa appears much stronger in MLS than in GEOS-5. The UT IWC and H2O interannual variations, from both MLS and GEOS-5, show clear imprints of the El Nino-Southern Oscillation.
Two years of observations of upper tropospheric (UT) carbon monoxide (CO) from the Aura Microwave Limb Sounder are analyzed; in combination with the CO surface emission climatology and data from the NCEP analyses. It is shown that spatial distribution, temporal variation and long-range transport of UT CO are closely related to the surface emissions, deep-convection and horizontal winds. Over the Asian monsoon region, surface emission of CO peaks in boreal spring due to high biomass burning in addition to anthropogenic emission. However, the UT CO peaks in summer when convection is strongest and surface emission of CO is dominated by anthropogenic source. The long-range transport of CO from Southeast Asia across the Pacific to North America, which occurs most frequently during boreal summer, is thus a clear imprint of Asian anthropogenic pollution influencing global air quality.
The relationships of upper tropospheric water vapor (UTWV), cloud ice and sea surface temperature (SST) are examined in the annual cycles of ECMWF analyses and simulations from 15 atmosphere-ocean coupled models which were contributed to the IPCC AR4. The results are compared with the observed relationships based on UTWV and cloud ice measurements from MLS on Aura. It is shown that the ECMWF analyses produce positive correlations between UTWV, cloud ice and SST, similar to the MLS data. The rate of the increase of cloud ice and UTWV with SST is about 30% larger than that for MLS. For the IPCC simulations, the relationships between UTWV, cloud ice and SST are qualitatively captured. However, the magnitudes of the simulated cloud ice show a considerable disagreement between models, by nearly a factor of 10. The amplitudes of the approximate linear relations between UTWV, cloud ice and SST vary by a factor up to 4.
Recent simultaneous observations of upper tropospheric (UT) water vapor and cloud ice from the Microwave Limb Sounder (MLS) on the Aura satellite provide new evidence for tropical convective influence on UT water vapor and its associated greenhouse effect. The observations show that UT water vapor increases as cloud ice water content increases. They also show that, when sea surface temperature (SST) exceeds approx.300 K, UT cloud ice associated with tropical deep convection increases sharply with increasing SST. The moistening of the upper troposphere by deep convection leads to an enhanced positive water vapor feedback, about 3 times that implied solely by thermodynamics. Over tropical oceans when SST greater than approx.300 K, the 'convective UT water vapor feedback' inferred from the MLS observations contributes approximately 65% of the sensitivity of the clear-sky greenhouse parameter to SST.