RESUMEN
Enhanced warming of the Arctic region relative to the rest of the globe, known as Arctic amplification, is caused by a variety of diverse factors, many of which are influenced by the Atlantic meridional overturning circulation (AMOC). Here, we quantify the role of AMOC changes in Arctic amplification throughout the twenty-first century by comparing two suites of climate model simulations under the same climate change scenario but with two different AMOC states: one with a weakened AMOC and another with a steady AMOC. We find that a weakened AMOC can reduce annual mean Arctic warming by 2 °C by the end of the century. A primary contributor to this reduction in warming is surface albedo feedback, related to a smaller sea ice loss due to AMOC slowdown. Another major contributor is the changes in ocean heat uptake. The weakened AMOC and its associated anomalous ocean heat transport divergence lead to increased ocean heat uptake and surface cooling. These two factors are inextricably linked on seasonal timescales, and their relative importance for Arctic amplification can vary by season. The weakened AMOC can also abate Arctic warming via lapse rate feedback, creating marked cooling from the surface to lower-to-mid troposphere while resulting in relatively weaker cooling in the upper troposphere. Additionally, the weakened AMOC increases the low-level cloud fraction over the North Atlantic warming hole, causing significant cooling there via shortwave (sw) cloud feedback despite the overall effect of sw cloud feedback being a slight warming of the average temperature over the Arctic.
RESUMEN
The global-mean surface temperature has experienced a rapid warming from the 1980s to early-2000s but a muted warming since, referred to as the global warming hiatus in the literature. Decadal changes in deep ocean heat uptake are thought to primarily account for the rapid warming and subsequent slowdown. Here, we examine the role of ocean heat uptake in establishing the fast warming and warming hiatus periods in the ERA-interim through a decomposition of the global-mean surface energy budget. We find the increase of carbon dioxide alone yields a nearly steady increase of the downward longwave radiation at the surface from the 1980s to the present, but neither accounts for the fast warming nor warming hiatus periods. During the global warming hiatus period, the transfer of latent heat energy from the ocean to atmosphere increases and the total downward radiative energy flux to the surface decreases due to a reduction of solar absorption caused primarily by an increase of clouds. The reduction of radiative energy into the ocean and the surface latent heat flux increase cause the ocean heat uptake to decrease and thus contribute to the slowdown of the global-mean surface warming. Our analysis also finds that in addition to a reduction of deep ocean heat uptake, the fast warming period is also driven by enhanced solar absorption due predominantly to a decrease of clouds and by enhanced longwave absorption mainly attributed to the air temperature feedback.
RESUMEN
Using CALIPSO-CloudSat-Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectrometer data set, this study documents the seasonal variation of sea ice, cloud, and atmospheric properties in the Arctic (70°N-82°N) for 2007-2010. A surface-type stratification-consisting Permanent Ocean, Land, Permanent Ice, and Transient Sea Ice-is used to investigate the influence of surface type on low-level Arctic cloud liquid water path (LWP) seasonality. The results show significant variations in the Arctic low-level cloud LWP by surface type linked to differences in thermodynamic state. Subdividing the Transient Ice region (seasonal sea ice zone) by melt/freeze season onset dates reveals a complex influence of sea ice variations on low cloud LWP seasonality. We find that lower tropospheric stability is the primary factor affecting the seasonality of cloud LWP. Our results suggest that variations in sea ice melt/freeze onset have a significant influence on the seasonality of low-level cloud LWP by modulating the lower tropospheric thermal structure and not by modifying the surface evaporation rate in late spring and midsummer. We find no significant dependence of the May low-level cloud LWP peak on the melt/freeze onset dates, whereas and September/October low-level cloud LWP maximum shifts later in the season for earlier melt/later freeze onset regions. The Arctic low cloud LWP seasonality is controlled by several surface-atmosphere interaction processes; the importance of each varies seasonally due to the thermodynamic properties of sea ice. Our results demonstrate that when analyzing Arctic cloud-sea ice interactions, a seasonal perspective is critical.
RESUMEN
Rapid and, in many cases, unprecedented Arctic climate changes are having far-reaching impacts on natural and human systems. Despite state-of-the-art climate models capturing the rapid nature of Arctic climate change, termed Arctic amplification, they significantly disagree on its magnitude. Using a regional, process-oriented surface energy budget analysis, we argue that differences in seasonal energy exchanges in sea ice retreat regions via increased absorption and storage of sunlight in summer and increased upward surface turbulent fluxes in fall/winter contribute to the inter-model spread. Models able to more widely disperse energy drawn from the surface in sea ice retreat regions warm more, suggesting that differences in the local Arctic atmospheric circulation response contribute to the inter-model spread. We find that the principle mechanisms driving the inter-model spread in Arctic amplification operate locally on regional scales, requiring an improved understanding of atmosphere-ocean-sea ice interactions in sea ice retreat regions to reduce the spread.
RESUMEN
A paradoxical negative greenhouse effect has been found over the Antarctic Plateau, indicating that greenhouse gases enhance energy loss to space. Using 13 years of NASA satellite observations, we verify the existence of the negative greenhouse effect and find that the magnitude and sign of the effect varies seasonally and spectrally. A previous explanation attributes this effect solely to stratospheric CO2; however, we surprisingly find that the negative greenhouse effect is predominantly caused by tropospheric water vapor. A recently developed principle-based concept is used to provide a complete account of the Antarctic Plateau's negative greenhouse effect indicating that it is controlled by the vertical variation of temperature and greenhouse gas absorption. Our findings indicate that unique climatological conditions over the Antarctic Plateau-a strong surface-based temperature inversion and scarcity of free tropospheric water vapor-cause the negative greenhouse effect.
RESUMEN
The 2016-17 Arctic sea ice growth season (October-March) exhibited the lowest end-of-season sea ice volume and extent of any year since 1979. An analysis of MERRA2 atmospheric reanalysis data and CERES radiative flux data reveals that a record warm and moist Arctic atmosphere supported the reduced sea ice growth through two pathways. First, numerous regional episodes of increased atmospheric temperature and moisture, transported from lower latitudes, increased the cumulative energy input from downwelling longwave surface fluxes. Second, in those same episodes, the efficiency that the atmosphere cooled radiatively to space was reduced, increasing the amount of energy retained in the Arctic atmosphere and reradiated back toward the surface. Overall, the Arctic radiative cooling efficiency shows a decreasing trend since 2000. The results presented highlight the increasing importance of atmospheric forcing on sea ice variability demonstrating that episodic Arctic atmospheric rivers, regions of elevated poleward water vapor transport, and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea ice.
RESUMEN
Recently launched cloud observing satellites provide information about the vertical structure of deep convection and its microphysical characteristics. In this study, CloudSat reflectivity data is stratified by cloud type, and the contoured frequency by altitude diagrams reveal a double-arc structure in deep convective cores (DCCs) above 8 km. This suggests two distinct hydrometeor modes (snow versus hail/graupel) controlling variability in reflectivity profiles. The day-night contrast in the double arcs is about four times larger than the wet-dry season contrast. Using QuickBeam, the vertical reflectivity structure of DCCs is analyzed in two versions of the Superparameterized Community Atmospheric Model (SP-CAM) with single-moment (no graupel) and double-moment (with graupel) microphysics. Double-moment microphysics shows better agreement with observed reflectivity profiles; however, neither model variant captures the double-arc structure. Ultimately, the results show that simulating realistic DCC vertical structure and its variability requires accurate representation of ice microphysics, in particular the hail/graupel modes, though this alone is insufficient.
RESUMEN
Since Chaney's report, the range of global warming projections in response to a doubling of CO2-from 1.5 °C to 4.5 °C or greater -remains largely unscathed by the onslaught of new scientific insights. Conventional thinking regards inter-model differences in climate feedbacks as the sole cause of the warming projection spread (WPS). Our findings shed new light on this issue indicating that climate feedbacks inherit diversity from the model control climate, besides the models' intrinsic climate feedback diversity that is independent of the control climate state. Regulated by the control climate ice coverage, models with greater (lesser) ice coverage generally possess a colder (warmer) and drier (moister) climate, exhibit a stronger (weaker) ice-albedo feedback, and experience greater (weaker) warming. The water vapor feedback also inherits diversity from the control climate but in an opposite way: a colder (warmer) climate generally possesses a weaker (stronger) water vapor feedback, yielding a weaker (stronger) warming. These inherited traits influence the warming response in opposing manners, resulting in a weaker correlation between the WPS and control climate diversity. Our study indicates that a better understanding of the diversity amongst climate model mean states may help to narrow down the range of global warming projections.
RESUMEN
Climate and reanalysis models contain large water and energy budget errors over tropical land related to the misrepresentation of diurnally forced moist convection. Motivated by recent work suggesting that the water and energy budget is influenced by the sensitivity of the convective diurnal cycle to atmospheric state, this study investigates the relationship between convective intensity, the convective diurnal cycle, and atmospheric state in a region of frequent convection-the Amazon. Daily, 3-hourly satellite observations of top of atmosphere (TOA) fluxes from Clouds and the Earth's Radiant Energy System Ed3a SYN1DEG and precipitation from Tropical Rainfall Measuring Mission 3B42 data sets are collocated with twice daily Integrated Global Radiosonde Archive observations from 2002 to 2012 and hourly flux tower observations. Percentiles of daily minimum outgoing longwave radiation are used to define convective intensity regimes. The results indicate a significant increase in the convective diurnal cycle amplitude with increased convective intensity. The TOA flux diurnal phase exhibits 1-3 h shifts with convective intensity, and precipitation phase is less sensitive. However, the timing of precipitation onset occurs 2-3 h earlier and the duration lasts 3-5 h longer on very convective compared to stable days. While statistically significant changes are found between morning atmospheric state and convective intensity, variations in upper and lower tropospheric humidity exhibit the strongest relationships with convective intensity and diurnal cycle characteristics. Lastly, convective available potential energy (CAPE) is found to vary with convective intensity but does not explain the variations in Amazonian convection, suggesting that a CAPE-based convective parameterization will not capture the observed behavior without incorporating the sensitivity of convection to column humidity.
RESUMEN
Amazonian deep convection experiences a strong diurnal cycle driven by the cycle in surface sensible heat flux, which contributes to a significant diurnal cycle in the top of the atmosphere (TOA) radiative flux. Even when accounting for seasonal variability, the TOA flux diurnal cycle varies significantly on the monthly timescale. Previous work shows evidence supporting a connection between variability in the convective and radiative cycles, likely modulated by variability in monthly atmospheric state (e.g., convective instability). The hypothesized relationships are further investigated with regression analysis of the radiative diurnal cycle and atmospheric state using additional meteorological variables representing convective instability and upper tropospheric humidity. The results are recalculated with three different reanalyses to test the reliability of the results. The radiative diurnal cycle sensitivity to upper tropospheric humidity is about equal in magnitude to that of convective instability. In addition, the results are recalculated with the data subdivided into the wet and dry seasons. Overall, clear-sky radiative effects have a dominant role in radiative diurnal cycle variability during the dry season. Because of this, even in a convectively active region, the clear-sky radiative effects must be accounted for in order to fully explain the monthly variability in diurnal cycle. Finally, while there is general agreement between the different reanalysis-based results when examining the full data time domain (without regard to time of year), there are significant disagreements when the data are divided into wet and dry seasons. The questionable reliability of reanalysis data is a major limitation.
RESUMEN
Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and midtropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500 m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.