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L. Huang, J. Zhai, C. Y. Sun, J. Y. Liu, J. Ning, and G.S. Zhao

Abstract

Land-use changes (LUCs) strongly influence regional climates through both the biogeochemical and biogeophysical processes. However, many studies have ignored the biogeophysical processes, which in some cases can offset the biogeochemical impacts. We integrated the field observations, satellite-retrieved data, and a conceptual land surface energy balance model to provide new evidence to fill our knowledge gap concerning how regional warming or cooling is affected by the three main types of LUCs (afforestation, cropland expansion, and urbanization) in different climate zones of China. According to our analyses, similar LUCs presented varied, even reverse, biogeophysical forcing on local temperatures across different climate regimes. Afforestation in arid and semiarid regions has caused increased net radiation that has typically outweighed increased latent evapotranspiration, thus warming has been the net biogeophysical effect. However, it has resulted in cooling in subtropical zones because the increase in net radiation has been exceeded by the increase in latent evapotranspiration. Cropland expansion has decreased the net radiation more than latent evapotranspiration, which has resulted in biogeophysical cooling in arid and semiarid regions. Conversely, it has caused warming in subtropical zones as a result of increases in net radiation and decreases in latent evapotranspiration. In all climatic regions, the net biogeophysical effects of urbanization have generally resulted in more or less warming because urbanization has led to smaller net radiation decreases than latent evapotranspiration. This study reinforces the need to adjust land-use policies to consider biogeophysical effects across different climate regimes and to adapt to and mitigate climate change.

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Qiaozhen Mu, Maosheng Zhao, John S. Kimball, Nathan G. McDowell, and Steven W. Running

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse ecosocial impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. The authors have developed a method to generate a near-real-time remotely sensed drought severity index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly, and annual frequencies. The new DSI integrates and exploits information from current operational satellite-based terrestrial evapo-transpiration (ET) and vegetation greenness index [normalized difference vegetation index (NDVI)] products, which are sensitive to vegetation water stress. Specifically, this approach determines the annual DSI departure from its normal (2000–11) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (correlation coefficient r = 0.43) with the precipitation-based Palmer drought severity index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite-based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely sensed global terrestrial DSI enhances capabilities for nearreal-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

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Weiwei Li, Zhuo Wang, Gan Zhang, Melinda S. Peng, Stanley G. Benjamin, and Ming Zhao

Abstract

This study investigates the subseasonal variability of anticyclonic Rossby wave breaking (AWB) and its impacts on atmospheric circulations and tropical cyclones (TCs) over the North Atlantic in the warm season from 1985 to 2013. Significant anomalies in sea level pressure, tropospheric wind, and humidity fields are found over the tropical–subtropical Atlantic within 8 days of an AWB activity peak. Such anomalies may lead to suppressed TC activity on the subseasonal time scale, but a significant negative correlation between the subseasonal variability of AWB and Atlantic basinwide TC activity does not exist every year, likely due to the modulation of TCs by other factors. It is also found that AWB occurrence may be modulated by the Madden–Julian oscillation (MJO). In particular, AWB occurrence over the tropical–subtropical west Atlantic is reduced in phases 2 and 3 and enhanced in phases 6 and 7 based on the Real-Time Multivariate MJO (RMM) index. The impacts of AWB on the predictive skill of Atlantic TCs are examined using the Global Ensemble Forecasting System (GEFS) reforecasts with a forecast lead time up to 2 weeks. The hit rate of tropical cyclogenesis during active AWB episodes is lower than the long-term-mean hit rate, and the GEFS is less skillful in capturing the variations of weekly TC activity during the years of enhanced AWB activity. The lower predictability of TCs is consistent with the lower predictability of environmental variables (such as vertical wind shear, moisture, and low-level vorticity) under the extratropical influence.

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S. L. Gong, X. Y. Zhang, T. L. Zhao, X. B. Zhang, L. A. Barrie, I. G. McKendry, and C. S. Zhao

Abstract

A 44-yr climatology of spring Asian dust aerosol emission, column loading, deposition, trans-Pacific transport routes, and budgets during 1960–2003 was simulated with the Northern Aerosol Regional Climate Model (NARCM). Interannual variability in these Asian dust aerosol properties simulated by the model and its climate connections are analyzed with major climatic indices and records in ground observations. For dust production from most of the source regions, the strongest correlations were with the surface wind speed in the source region and the area and intensity indices of the Asian polar vortex (AIAPV and IIAPV, respectively). Dust emission was negatively correlated with precipitation and surface temperatures in spring. The strength of the East Asian monsoon was not found to be directly related to dust production but rather with the transport of dust from the Asian subcontinent. The interannual variability of dust loading and deposition showed similar relations with various climate indices. The correlation of Asian dust loading and deposition with the western Pacific (WP) pattern and Atmospheric Circulation Index (ACI) exhibited contrasting meridional and zonal distributions. AIAPV and IIAPV were strongly correlated with the midlatitude zonal distribution of dust loading and deposition over the Asian subcontinent and the North Pacific. The Pacific–North American (PNA) pattern and Southern Oscillation index (SOI) displayed an opposite correlation pattern of dust loading and deposition in the eastern Pacific, while SOI correlated significantly with dust loading over eastern China and northeast Asia. The Pacific decadal oscillation (PDO) was linked to variations of dust aerosol and deposition not only in the area of the eastern North Pacific and North America but also in the Asian dust source regions. The anomalies of transport flux and its divergence as well as dust column loading were also identified for eight typical El Niño and eight La Niña years. A shift of the trans-Pacific transport path to the north was found for El Niño years, which resulted in less dust storms and dust loading in China. In El Niño years the deserts in Mongolia and western north China closer to the polar cold air regions contributed more dust aerosol in the troposphere, while in La Niña years the deserts in central and eastern north China far from polar cold regions provided more dust aerosol in the troposphere. On the basis of the variability of Asian dust aerosol budgets, the ratio of inflow to North America to the outflow from Asia was found to be correlated negatively with the PNA index and positively with the WP index.

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T. L. Zhao, S. L. Gong, X. Y. Zhang, J-P. Blanchet, I. G. McKendry, and Z. J. Zhou

Abstract

The Northern Aerosol Regional Climate Model (NARCM) was used to construct a 44-yr climatology of spring Asian dust aerosol emission, column loading, deposition, trans-Pacific transport routes, and budgets during 1960–2003. Comparisons with available ground dust observations and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) measurements verified that NARCM captured most of the climatological characteristics of the spatial and temporal distributions, as well as the interannual and daily variations of Asian dust aerosol during those 44 yr. Results demonstrated again that the deserts in Mongolia and in western and northern China (mainly the Taklimakan and Badain Juran, respectively) were the major sources of Asian dust aerosol in East Asia. The dust storms in spring occurred most frequently from early April to early May with a daily averaged dust emission (diameter d < 41 μm) of 1.58 Mt in April and 1.36 Mt in May. Asian dust aerosol contributed most of the dust aerosol loading in the troposphere over the midlatitude regions from East Asia to western North America during springtime. Climatologically, dry deposition was a dominant dust removal process near the source areas, while the removal of dust particles by precipitation was the major process over the trans-Pacific transport pathway (where wet deposition exceeded dry deposition up to a factor of 20). The regional transport of Asian dust aerosol over the Asian subcontinent was entrained to an elevation of <3 km. The frontal cyclone in Mongolia and northern China uplifted dust aerosol in the free troposphere for trans-Pacific transport. Trans-Pacific dust transport peaked between 3 and 10 km in the troposphere along a zonal transport axis around 40°N. Based on the 44-yr-averaged dust budgets for the modeling domain from East Asia to western North America, it was estimated that of the average spring dust aerosol (diameter d < 41 μm) emission of ∼120 Mt from Asian source regions, about 51% was redeposited onto the source regions, 21% was deposited onto nondesert regions within the Asian subcontinent, and 26% was exported from the Asian subcontinent to the Pacific Ocean. In total, 16% of Asian dust aerosol emission was deposited into the North Pacific, while ∼3% of Asian dust aerosol was carried to the North American continent via trans-Pacific transport.

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Brian Medeiros, Bjorn Stevens, Isaac M. Held, Ming Zhao, David L. Williamson, Jerry G. Olson, and Christopher S. Bretherton

Abstract

Cloud effects have repeatedly been pointed out as the leading source of uncertainty in projections of future climate, yet clouds remain poorly understood and simulated in climate models. Aquaplanets provide a simplified framework for comparing and understanding cloud effects, and how they are partitioned as a function of regime, in large-scale models. This work uses two climate models to demonstrate that aquaplanets can successfully predict a climate model’s sensitivity to an idealized climate change. For both models, aquaplanet climate sensitivity is similar to that of the realistic configuration. Tropical low clouds appear to play a leading role in determining the sensitivity. Regions of large-scale subsidence, which cover much of the tropics, are most directly responsible for the differences between the models. Although cloud effects and climate sensitivity are similar for aquaplanets and realistic configurations, the aquaplanets lack persistent stratocumulus in the tropical atmosphere. This, and an additional analysis of the cloud response in the realistically configured simulations, suggests the representation of shallow (trade wind) cumulus convection, which is ubiquitous in the tropics, is largely responsible for differences in the simulated climate sensitivity of these two models.

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C. J. Stubenrauch, W. B. Rossow, S. Kinne, S. Ackerman, G. Cesana, H. Chepfer, L. Di Girolamo, B. Getzewich, A. Guignard, A. Heidinger, B. C. Maddux, W. P. Menzel, P. Minnis, C. Pearl, S. Platnick, C. Poulsen, J. Riedi, S. Sun-Mack, A. Walther, D. Winker, S. Zeng, and G. Zhao

Clouds cover about 70% of Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR sounders, and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature, or altitude), cloud thermodynamic phase, and cloud radiative and bulk microphysical properties (optical depth or emissivity, effective particle radius, and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.

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M. Susan Lozier, Sheldon Bacon, Amy S. Bower, Stuart A. Cunningham, M. Femke de Jong, Laura de Steur, Brad deYoung, Jürgen Fischer, Stefan F. Gary, Blair J. W. Greenan, Patrick Heimbach, Naomi P. Holliday, Loïc Houpert, Mark E. Inall, William E. Johns, Helen L. Johnson, Johannes Karstensen, Feili Li, Xiaopei Lin, Neill Mackay, David P. Marshall, Herlé Mercier, Paul G. Myers, Robert S. Pickart, Helen R. Pillar, Fiammetta Straneo, Virginie Thierry, Robert A. Weller, Richard G. Williams, Chris Wilson, Jiayan Yang, Jian Zhao, and Jan D. Zika

Abstract

For decades oceanographers have understood the Atlantic meridional overturning circulation (AMOC) to be primarily driven by changes in the production of deep-water formation in the subpolar and subarctic North Atlantic. Indeed, current Intergovernmental Panel on Climate Change (IPCC) projections of an AMOC slowdown in the twenty-first century based on climate models are attributed to the inhibition of deep convection in the North Atlantic. However, observational evidence for this linkage has been elusive: there has been no clear demonstration of AMOC variability in response to changes in deep-water formation. The motivation for understanding this linkage is compelling, since the overturning circulation has been shown to sequester heat and anthropogenic carbon in the deep ocean. Furthermore, AMOC variability is expected to impact this sequestration as well as have consequences for regional and global climates through its effect on the poleward transport of warm water. Motivated by the need for a mechanistic understanding of the AMOC, an international community has assembled an observing system, Overturning in the Subpolar North Atlantic Program (OSNAP), to provide a continuous record of the transbasin fluxes of heat, mass, and freshwater, and to link that record to convective activity and water mass transformation at high latitudes. OSNAP, in conjunction with the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array (RAPID–MOCHA) at 26°N and other observational elements, will provide a comprehensive measure of the three-dimensional AMOC and an understanding of what drives its variability. The OSNAP observing system was fully deployed in the summer of 2014, and the first OSNAP data products are expected in the fall of 2017.

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M. Ades, R. Adler, Rob Allan, R. P. Allan, J. Anderson, Anthony Argüez, C. Arosio, J. A. Augustine, C. Azorin-Molina, J. Barichivich, J. Barnes, H. E. Beck, Andreas Becker, Nicolas Bellouin, Angela Benedetti, David I. Berry, Stephen Blenkinsop, Olivier. Bock, Michael G. Bosilovich, Olivier. Boucher, S. A. Buehler, Laura. Carrea, Hanne H. Christiansen, F. Chouza, John R. Christy, E.-S. Chung, Melanie Coldewey-Egbers, Gil P. Compo, Owen R. Cooper, Curt Covey, A. Crotwell, Sean M. Davis, Elvira de Eyto, Richard A. M de Jeu, B.V. VanderSat, Curtis L. DeGasperi, Doug Degenstein, Larry Di Girolamo, Martin T. Dokulil, Markus G. Donat, Wouter A. Dorigo, Imke Durre, Geoff S. Dutton, G. Duveiller, James W. Elkins, Vitali E. Fioletov, Johannes Flemming, Michael J. Foster, Richard A. Frey, Stacey M. Frith, Lucien Froidevaux, J. Garforth, S. K. Gupta, Leopold Haimberger, Brad D. Hall, Ian Harris, Andrew K Heidinger, D. L. Hemming, Shu-peng (Ben) Ho, Daan Hubert, Dale F. Hurst, I. Hüser, Antje Inness, K. Isaksen, Viju John, Philip D. Jones, J. W. Kaiser, S. Kelly, S. Khaykin, R. Kidd, Hyungiun Kim, Z. Kipling, B. M. Kraemer, D. P. Kratz, R. S. La Fuente, Xin Lan, Kathleen O. Lantz, T. Leblanc, Bailing Li, Norman G Loeb, Craig S. Long, Diego Loyola, Wlodzimierz Marszelewski, B. Martens, Linda May, Michael Mayer, M. F. McCabe, Tim R. McVicar, Carl A. Mears, W. Paul Menzel, Christopher J. Merchant, Ben R. Miller, Diego G. Miralles, Stephen A. Montzka, Colin Morice, Jens Mühle, R. Myneni, Julien P. Nicolas, Jeannette Noetzli, Tim J. Osborn, T. Park, A. Pasik, Andrew M. Paterson, Mauri S. Pelto, S. Perkins-Kirkpatrick, G. Pétron, C. Phillips, Bernard Pinty, S. Po-Chedley, L. Polvani, W. Preimesberger, M. Pulkkanen, W. J. Randel, Samuel Rémy, L. Ricciardulli, A. D. Richardson, L. Rieger, David A. Robinson, Matthew Rodell, Karen H. Rosenlof, Chris Roth, A. Rozanov, James A. Rusak, O. Rusanovskaya, T. Rutishäuser, Ahira Sánchez-Lugo, P. Sawaengphokhai, T. Scanlon, Verena Schenzinger, S. Geoffey Schladow, R. W Schlegel, Eawag Schmid, Martin, H. B. Selkirk, S. Sharma, Lei Shi, S. V. Shimaraeva, E. A. Silow, Adrian J. Simmons, C. A. Smith, Sharon L Smith, B. J. Soden, Viktoria Sofieva, T. H. Sparks, Paul W. Stackhouse Jr., Wolfgang Steinbrecht, Dimitri A. Streletskiy, G. Taha, Hagen Telg, S. J. Thackeray, M. A. Timofeyev, Kleareti Tourpali, Mari R. Tye, Ronald J. van der A, Robin, VanderSat B.V. van der Schalie, Gerard van der SchrierW. Paul, Guido R. van der Werf, Piet Verburg, Jean-Paul Vernier, Holger Vömel, Russell S. Vose, Ray Wang, Shohei G. Watanabe, Mark Weber, Gesa A. Weyhenmeyer, David Wiese, Anne C. Wilber, Jeanette D. Wild, Takmeng Wong, R. Iestyn Woolway, Xungang Yin, Lin Zhao, Guanguo Zhao, Xinjia Zhou, Jerry R. Ziemke, and Markus Ziese
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Jennifer A. MacKinnon, Zhongxiang Zhao, Caitlin B. Whalen, Amy F. Waterhouse, David S. Trossman, Oliver M. Sun, Louis C. St. Laurent, Harper L. Simmons, Kurt Polzin, Robert Pinkel, Andrew Pickering, Nancy J. Norton, Jonathan D. Nash, Ruth Musgrave, Lynne M. Merchant, Angelique V. Melet, Benjamin Mater, Sonya Legg, William G. Large, Eric Kunze, Jody M. Klymak, Markus Jochum, Steven R. Jayne, Robert W. Hallberg, Stephen M. Griffies, Steve Diggs, Gokhan Danabasoglu, Eric P. Chassignet, Maarten C. Buijsman, Frank O. Bryan, Bruce P. Briegleb, Andrew Barna, Brian K. Arbic, Joseph K. Ansong, and Matthew H. Alford

Abstract

Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.

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