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Ping-Ping Rong and Darryn W. Waugh

Abstract

The evolution of the polar vortex in a shallow-water model with time-independent topographic forcing and relaxation to a constant equilibrium state is investigated for a range of topographic forcing amplitudes. For small forcing amplitudes there are only weak disturbances on the edge of the polar vortex and the vortex area remains constant, whereas for large amplitudes there are cycles where the vortex breaks down and then reforms (and zonal winds vacillate between westerlies and easterlies). Analysis of the mass within potential vorticity (PV) contours shows that these vacillations are due to out-of-phase variations in the mass fluxes across PV contours due to the relaxation and to hyperdiffusion. During the strong vortex stages Rossby wave breaking produces a cascade of PV to small scales, and these small-scale features are eventually eliminated by hyperdiffusion. This causes a decrease in the mass within the high PV contours and ultimately the destruction of the vortex. In contrast, during stages with no vortex there are very weak PV gradients, weak Rossby wave activity, and little cascade of PV to small scales. The vortex, and PV gradients, are then reestablished by the mass fluxes due to the diabatic relaxation term. These results suggest that the horizontal PV structure may play an important role in the vortex breakdown and recovery in three-dimensional models and in the real stratosphere.

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Richard J. Greatbatch and Ping-ping Rong

Abstract

Northern Hemisphere summer (July–August) data from the NCEP–NCAR and ECMWF 40-yr Re-Analysis (ERA-40) reanalyses are compared with each other and with Trenberth's sea level pressure (SLP) dataset. Discrepancies in SLP and 500 hPa are mostly confined to a band connecting North Africa and Asia. In the NCEP–NCAR reanalysis, there is a negative offset in SLP over North Africa and Asia prior to the late 1960s, together with a similar problem in 500-hPa height, and in Trenberth's data there is a negative offset in SLP over Asia prior to the early 1990s. Both these offsets magnify the linear trend from 1958 to 2002 over North Africa and Asia in the NCEP–NCAR and Trenberth datasets. On the other hand, the interannual variability in the three datasets is highly correlated during the periods between these offsets. Compared to SLP and 500-hPa height, there is a more extensive area of discrepancy in 2-m temperature that extends eastward from North Africa across the subtropics into the Pacific, with an additional area of discrepancy over the Arctic and parts of the American continent. At 500 and 100 hPa, the biggest differences in the temperature time series are found in the Tropics, with a marked jump being evident in the late 1970s in the NCEP–NCAR, but not in the ERA-40, reanalysis that is almost certainly associated with the introduction of satellite data. On the other hand, all three datasets agree well over Europe. The summer North Atlantic Oscillation (NAO), defined here as the first EOF of summer mean SLP over the Euro-Atlantic sector, agrees well between the different datasets. The results indicate that the upward trend in the summer index in the 1960s is part of a longer-period interdecadal cycle, with relatively high index values also being found during the 1930s. The running cross correlation between the central England temperature record and the summer NAO shows a strong correlation throughout the last half of the twentieth century, but much reduced correlation in the early part of the twentieth century. It is not clear whether the change in correlation is real, or a data artifact, a topic that requires further research.

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Yanchen Zheng, Jianzhu Li, Ting Zhang, Youtong Rong, and Ping Feng

Abstract

Model calibration has always been one major challenge in the hydrological community. Flood scaling properties (FS) are often used to estimate the flood quantiles for data-scarce catchments based on the statistical relationship between flood peak and contributing areas. This paper investigates the potential of applying FS and multivariate flood scaling properties [multiple linear regression (MLR)] as constraints in model calibration. Based on the assumption that the scaling property of flood exists in four study catchments in northern China, eight calibration scenarios are designed with adopting different combinations of traditional indicators and FS or MLR as objective functions. The performance of the proposed method is verified by employing a distributed hydrological model, namely, the Soil and Water Assessment Tool (SWAT) model. The results indicate that reasonable performance could be obtained in FS with fewer requirements of observed streamflow data, exhibiting better simulation of flood peaks than the Nash–Sutcliffe efficiency coefficient calibration scenario. The observed streamflow data or regional flood information are required in the MLR calibration scenario to identify the dominant catchment descriptors, and MLR achieves better performance on catchment interior points, especially for the events with uneven distribution of rainfall. On account of the improved performance on hydrographs and flood frequency curve at the watershed outlet, adopting the statistical indicators and flood scaling property simultaneously as model constraints is suggested. The proposed methodology enhances the physical connection of flood peak among subbasins and considers watershed actual conditions and climatic characteristics for each flood event, facilitating a new calibration approach for both gauged catchments and data-scarce catchments.

Significance Statement

This paper proposes a new hydrological model calibration strategy that explores the potential of applying flood scaling properties as constraints. The proposed method effectively captures flood peaks with fewer requirements of observed streamflow time series data, providing a new alternative method in hydrological model calibration for ungauged watersheds. For gauged watersheds, adopting flood scaling properties as model constraints could make the hydrological model calibration more physically based and improve the performance at catchment interior points. We encourage this novel method to be adopted in model calibration for both gauged and data-scarce watersheds.

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Yanchen Zheng, Jianzhu Li, Lixin Dong, Youtong Rong, Aiqing Kang, and Ping Feng

Abstract

Initial abstraction (Ia) is a sensitive parameter in hydrological models, and its value directly determines the amount of runoff. Ia, which is influenced by many factors related to antecedent watershed condition (AWC), is difficult to estimate due to lack of observed data. In the Soil Conservation Service curve number (SCS-CN) method, it is often assumed that Ia is 0.2 times the potential maximum retention S. Yet this assumption has frequently been questioned. In this paper, Ia/S and factors potentially influencing Ia were collected from rainfall–runoff events. Soil moisture and evaporation data were extracted from GLDAS-Noah datasets to represent AWC. Based on the driving factors of Ia, identified using the Pearson correlation coefficient and maximal information coefficient, artificial neural network (ANN)-estimated Ia was applied to simulate the selected flood events in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The results indicated that Ia/S varies over different events and different watersheds. Over 75% of the Ia/S values are less than 0.2 in the two study areas. The driving factors affecting Ia vary over different watersheds, and the antecedent precipitation index appears to be the most influential factor. Flood simulation by the HEC-HMS model using statistical Ia gives the best fitness, whereas applying ANN-estimated Ia outperforms the simulation with median Ia/S. For over 60% of the flood events, ANN-estimated Ia provided better fitness in flood peak and depth, with an average Nash–Sutcliffe efficiency coefficient of 0.76 compared to 0.71 for median Ia/S. The proposed ANN-estimated Ia is physically based and can be applied without calibration, saving time in constructing hydrological models.

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Justin Sheffield, Suzana J. Camargo, Rong Fu, Qi Hu, Xianan Jiang, Nathaniel Johnson, Kristopher B. Karnauskas, Seon Tae Kim, Jim Kinter, Sanjiv Kumar, Baird Langenbrunner, Eric Maloney, Annarita Mariotti, Joyce E. Meyerson, J. David Neelin, Sumant Nigam, Zaitao Pan, Alfredo Ruiz-Barradas, Richard Seager, Yolande L. Serra, De-Zheng Sun, Chunzai Wang, Shang-Ping Xie, Jin-Yi Yu, Tao Zhang, and Ming Zhao

Abstract

This is the second part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the twentieth-century simulations of intraseasonal to multidecadal variability and teleconnections with North American climate. Overall, the multimodel ensemble does reasonably well at reproducing observed variability in several aspects, but it does less well at capturing observed teleconnections, with implications for future projections examined in part three of this paper. In terms of intraseasonal variability, almost half of the models examined can reproduce observed variability in the eastern Pacific and most models capture the midsummer drought over Central America. The multimodel mean replicates the density of traveling tropical synoptic-scale disturbances but with large spread among the models. On the other hand, the coarse resolution of the models means that tropical cyclone frequencies are underpredicted in the Atlantic and eastern North Pacific. The frequency and mean amplitude of ENSO are generally well reproduced, although teleconnections with North American climate are widely varying among models and only a few models can reproduce the east and central Pacific types of ENSO and connections with U.S. winter temperatures. The models capture the spatial pattern of Pacific decadal oscillation (PDO) variability and its influence on continental temperature and West Coast precipitation but less well for the wintertime precipitation. The spatial representation of the Atlantic multidecadal oscillation (AMO) is reasonable, but the magnitude of SST anomalies and teleconnections are poorly reproduced. Multidecadal trends such as the warming hole over the central–southeastern United States and precipitation increases are not replicated by the models, suggesting that observed changes are linked to natural variability.

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Eric D. Maloney, Suzana J. Camargo, Edmund Chang, Brian Colle, Rong Fu, Kerrie L. Geil, Qi Hu, Xianan Jiang, Nathaniel Johnson, Kristopher B. Karnauskas, James Kinter, Benjamin Kirtman, Sanjiv Kumar, Baird Langenbrunner, Kelly Lombardo, Lindsey N. Long, Annarita Mariotti, Joyce E. Meyerson, Kingtse C. Mo, J. David Neelin, Zaitao Pan, Richard Seager, Yolande Serra, Anji Seth, Justin Sheffield, Julienne Stroeve, Jeanne Thibeault, Shang-Ping Xie, Chunzai Wang, Bruce Wyman, and Ming Zhao

Abstract

In part III of a three-part study on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) models, the authors examine projections of twenty-first-century climate in the representative concentration pathway 8.5 (RCP8.5) emission experiments. This paper summarizes and synthesizes results from several coordinated studies by the authors. Aspects of North American climate change that are examined include changes in continental-scale temperature and the hydrologic cycle, extremes events, and storm tracks, as well as regional manifestations of these climate variables. The authors also examine changes in the eastern North Pacific and North Atlantic tropical cyclone activity and North American intraseasonal to decadal variability, including changes in teleconnections to other regions of the globe. Projected changes are generally consistent with those previously published for CMIP3, although CMIP5 model projections differ importantly from those of CMIP3 in some aspects, including CMIP5 model agreement on increased central California precipitation. The paper also highlights uncertainties and limitations based on current results as priorities for further research. Although many projected changes in North American climate are consistent across CMIP5 models, substantial intermodel disagreement exists in other aspects. Areas of disagreement include projections of changes in snow water equivalent on a regional basis, summer Arctic sea ice extent, the magnitude and sign of regional precipitation changes, extreme heat events across the northern United States, and Atlantic and east Pacific tropical cyclone activity.

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