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Anthony D. Del Genio and Audrey B. Wolf

Abstract

Satellite observations of low-level clouds have challenged the idea that increasing liquid water content with temperature combined with constant physical thickness will lead to a negative cloud optics feedback in a decadal climate change. The reasons for the satellite results are explored using 4 yr of surface remote sensing data from the Atmospheric Radiation Measurement Program Cloud and Radiation Testbed site in the southern Great Plains of the United States. It is found that low-cloud liquid water path is approximately invariant with temperature in winter but decreases strongly with temperature in summer, consistent with satellite inferences at this latitude. This behavior occurs because liquid water content shows no detectable temperature dependence while cloud physical thickness decreases with warming. Thinning of clouds with warming is observed on seasonal, synoptic, and diurnal timescales; it is most obvious in the warm sectors of baroclinic waves. Although cloud top is observed to slightly descend with warming, the primary cause of thinning is the ascent of cloud base due to the reduction in surface relative humidity and the concomitant increase in the lifting condensation level of surface air. Low-cloud liquid water path is not observed to be a continuous function of temperature. Rather, the behavior observed is best explained as a transition in the frequency of occurrence of different boundary layer types. At cold temperatures, a mixture of stratified and convective boundary layers is observed, leading to a broad distribution of liquid water path values, while at warm temperatures, only convective boundary layers with small liquid water paths, some of them decoupled, are observed. Our results, combined with the earlier satellite inferences, suggest a reexamination of the commonly quoted 1.5°C lower limit for the equilibrium global climate sensitivity to a doubling of CO2, which is based on models in which liquid water increases with temperature and cloud physical thickness is constant.

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Wendy L. Wolf and Ronald B. Smith

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Values of mountain pressure torque are calculated for the Rocky and Andes Mountains and for the Tibetan Plateau in order to evaluate their conuibufion to the observed anomalous length-of-day (LOD) and atmospheric angular momentum (AAM) change during the period from late January to mid-February 1983. A period of rapid increase in AAM and LOD is found to coincide with unusually high values of mountain torque on the Rocky Mountains, associated with a midcontinent high-pressure event and a sequence of Pacific frontal cyclone lows hitting California. A subsequent decrease in AAM is not correlated with mountain pressure torquesover the three regions tested, thus implicating other regions or other transfer mechanisms.

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Anthony D. Del Genio, Jingbo Wu, Audrey B. Wolf, Yonghua Chen, Mao-Sung Yao, and Daehyun Kim

Abstract

Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden–Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

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Ji-Young Gu, A. Ryzhkov, P. Zhang, P. Neilley, M. Knight, B. Wolf, and Dong-In Lee

Abstract

The ability of C-band polarimetric radar to account for strong attenuation/differential attenuation is demonstrated in two cases of heavy rain that occurred in the Chicago, Illinois, metropolitan area on 5 August 2008 and in central Oklahoma on 10 March 2009. The performance of the polarimetric attenuation correction scheme that separates relative contributions of “hot spots” (i.e., strong convective cells) and the rest of the storm to the path-integrated total and differential attenuation has been explored. It is shown that reliable attenuation correction is possible if the radar signal is attenuated by as much as 40 dB. Examination of the experimentally derived statistics of the ratios of specific attenuation Ah and differential attenuation A DP to specific differential phase K DP in hot spots is included in this study. It is shown that these ratios at C band are highly variable within the hot spots. Validation of the attenuation correction algorithm at C band has been performed through cross-checking with S-band radar measurements that were much less affected by attenuation. In the case of the Oklahoma storm, a comparison was made between the data collected by closely located C-band and S-band polarimetric radars.

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Patrick Minnis, Anthony D. Del Genio, Audrey B. Wolf, and Mandana M. Khaiyer

Abstract

Three years of surface and Geostationary Operational Environmental Satellite (GOES) data from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to evaluate the NASA GISS Single Column Model (SCM) simulated clouds from January 1999 to December 2001. The GOES-derived total cloud fractions for both 0.5° and 2.5° grid boxes are in excellent agreement with surface observations, suggesting that ARM point observations can represent large areal observations. Low (<2 km), middle (2–6 km), and high (>6 km) levels of cloud fractions, however, have negative biases as compared to the ARM results due to multilayer cloud scenes that can either mask lower cloud layers or cause misidentifications of cloud tops. Compared to the ARM observations, the SCM simulated most midlevel clouds, overestimated low clouds (4%), and underestimated total and high clouds by 7% and 15%, respectively. To examine the dependence of the modeled high and low clouds on the large-scale synoptic patterns, variables such as relative humidity (RH) and vertical pressure velocity (omega) from North American Regional Reanalysis (NARR) data are included. The successfully modeled and missed high clouds are primarily associated with a trough and ridge upstream of the ARM SGP, respectively. The PDFs of observed high and low occurrence as a function of RH reveal that high clouds have a Gaussian-like distribution with mode RH values of ∼40%–50%, whereas low clouds have a gammalike distribution with the highest cloud probability occurring at RH ∼75%–85%. The PDFs of modeled low clouds are similar to those observed; however, for high clouds the PDFs are shifted toward higher values of RH. This results in a negative bias for the modeled high clouds because many of the observed clouds occur at RH values below the SCM-specified stratiform parameterization threshold RH of 60%. Despite many similarities between PDFs derived from the NARR and ARM forcing datasets for RH and omega, differences do exist. This warrants further investigation of the forcing and reanalysis datasets.

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Hua Song, Wuyin Lin, Yanluan Lin, Audrey B. Wolf, Roel Neggers, Leo J. Donner, Anthony D. Del Genio, and Yangang Liu

Abstract

This study evaluates the performances of seven single-column models (SCMs) by comparing simulated surface precipitation with observations at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site from January 1999 to December 2001. Results show that although most SCMs can reproduce the observed precipitation reasonably well, there are significant and interesting differences in their details. In the cold season, the model–observation differences in the frequency and mean intensity of rain events tend to compensate each other for most SCMs. In the warm season, most SCMs produce more rain events in daytime than in nighttime, whereas the observations have more rain events in nighttime. The mean intensities of rain events in these SCMs are much stronger in daytime, but weaker in nighttime, than the observations. The higher frequency of rain events during warm-season daytime in most SCMs is related to the fact that most SCMs produce a spurious precipitation peak around the regime of weak vertical motions but rich in moisture content. The models also show distinct biases between nighttime and daytime in simulating significant rain events. In nighttime, all the SCMs have a lower frequency of moderate-to-strong rain events than the observations for both seasons. In daytime, most SCMs have a higher frequency of moderate-to-strong rain events than the observations, especially in the warm season. Further analysis reveals distinct meteorological backgrounds for large underestimation and overestimation events. The former occur in the strong ascending regimes with negative low-level horizontal heat and moisture advection, whereas the latter occur in the weak or moderate ascending regimes with positive low-level horizontal heat and moisture advection.

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Hua Song, Wuyin Lin, Yanluan Lin, Audrey B. Wolf, Leo J. Donner, Anthony D. Del Genio, Roel Neggers, Satoshi Endo, and Yangang Liu

Abstract

This study evaluates the performances of seven single-column models (SCMs) by comparing simulated cloud fraction with observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site from January 1999 to December 2001. Compared with the 3-yr mean observational cloud fraction, the ECMWF SCM underestimates cloud fraction at all levels and the GISS SCM underestimates cloud fraction at levels below 200 hPa. The two GFDL SCMs underestimate lower-to-middle level cloud fraction but overestimate upper-level cloud fraction. The three Community Atmosphere Model (CAM) SCMs overestimate upper-level cloud fraction and produce lower-level cloud fraction similar to the observations but as a result of compensating overproduction of convective cloud fraction and underproduction of stratiform cloud fraction. Besides, the CAM3 and CAM5 SCMs both overestimate midlevel cloud fraction, whereas the CAM4 SCM underestimates. The frequency and partitioning analyses show a large discrepancy among the seven SCMs: Contributions of nonstratiform processes to cloud fraction production are mainly in upper-level cloudy events over the cloud cover range 10%–80% in SCMs with prognostic cloud fraction schemes and in lower-level cloudy events over the cloud cover range 15%–50% in SCMs with diagnostic cloud fraction schemes. Further analysis reveals different relationships between cloud fraction and relative humidity (RH) in the models and observations. The underestimation of lower-level cloud fraction in most SCMs is mainly due to the larger threshold RH used in models. The overestimation of upper-level cloud fraction in the three CAM SCMs and two GFDL SCMs is primarily due to the overestimation of RH and larger mean cloud fraction of cloudy events plus more occurrences of RH around 40%–80%, respectively.

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Andrea Schneidereit, Dieter H. W. Peters, Christian M. Grams, Julian F. Quinting, Julia H. Keller, Gabriel Wolf, Franziska Teubler, Michael Riemer, and Olivia Martius

Abstract

Tropospheric forcing of planetary wavenumber 2 is examined in the prephase of the major stratospheric sudden warming event in January 2009 (MSSW 2009). Because of a huge increase in Eliassen–Palm fluxes induced mainly by wavenumber 2, easterly angular momentum is transported into the Arctic stratosphere, deposited, and then decelerates the polar night jet. In agreement with earlier studies, the results reveal that the strongest eddy heat fluxes, associated with wavenumber 2, occur at 100 hPa during the prephase of MSSW 2009 in ERA-Interim. In addition, moderate conditions of the cold phase of ENSO (La Niña) contribute to the eddy heat flux anomaly. It is shown that enhanced tropospheric wave forcing over Alaska and Scandinavia is caused by tropical processes in two ways. First, in a climatological sense, La Niña contributes to an enhanced anticyclonic flow over both regions. Second, the Madden–Julian oscillation (MJO) has an indirect influence on the Alaskan ridge by enhancing eddy activity over the North Pacific. This is manifested in an increase in cyclone frequency and associated warm conveyor belt outflow, which contribute to the maintenance and amplification of the Alaskan anticyclone. The Scandinavian ridge is maintained by wave trains emanating from the Alaskan ridge propagating eastward, including an enhanced transport of eddy kinetic energy. The MSSW 2009 is an extraordinary case of how a beneficial phasing of La Niña and MJO conditions together with multiscale interactions enhances tropospheric forcing for wavenumber 2–induced zonal mean eddy heat flux in the lower stratosphere.

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B. Wolf, C. Chwala, B. Fersch, J. Garvelmann, W. Junkermann, M. J. Zeeman, A. Angerer, B. Adler, C. Beck, C. Brosy, P. Brugger, S. Emeis, M. Dannenmann, F. De Roo, E. Diaz-Pines, E. Haas, M. Hagen, I. Hajnsek, J. Jacobeit, T. Jagdhuber, N. Kalthoff, R. Kiese, H. Kunstmann, O. Kosak, R. Krieg, C. Malchow, M. Mauder, R. Merz, C. Notarnicola, A. Philipp, W. Reif, S. Reineke, T. Rödiger, N. Ruehr, K. Schäfer, M. Schrön, A. Senatore, H. Shupe, I. Völksch, C. Wanninger, S. Zacharias, and H. P. Schmid

Abstract

ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.

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