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Christopher J. Anderson and Raymond W. Arritt

Abstract

Reanalysis datasets that are produced by assimilating observations into numerical forecast models may contain unrealistic features owing to the influence of the underlying model. The authors have evaluated the potential for such errors to affect the depiction of summertime low-level jets (LLJs) in the NCEP–NCAR reanalysis by comparing the incidence of LLJs over 7 yr (1992–98) in the reanalysis to hourly observations obtained from the NOAA Wind Profiler Network. The profiler observations are not included in the reanalysis, thereby providing an independent evaluation of the ability of the reanalysis to represent LLJs.

LLJs in the NCEP–NCAR reanalysis exhibit realistic spatial structure, but strong LLJs are infrequent in the lee of the Rocky Mountains, causing substantial bias in LLJ frequency. In this region the forecast by the reanalysis model diminishes the ageostrophic wind, forcing the analysis scheme to restore the ageostrophic wind. The authors recommend sensitivity tests of LLJ simulations by GCMs in which terrain resolution and horizontal grid spacing are varied independently.

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David W. Keith and James G. Anderson

Abstract

The character of data required to measure decade-to-century–scale climatic change is distinctly different from that required for weather prediction or for studies of meteorological processes. The data ought to possess the accuracy to detect the small secular climate changes of interest. To be useful to future investigators, the data must include convincing proof that a given level of accuracy was in fact attained.

Spectrally resolved infrared radiance is one of the most important quantities to measure accurately from space—it contains much of the fingerprint of climate response and of the forcing that causes it. The authors describe the physics of infrared radiance measurements, and demonstrate that trade-offs exist between instrument accuracy (required for climate data) and sensitivity (required for weather prediction). No such simple trade-off exists between spectral resolution and accuracy; in fact, spectral resolution can improve accuracy. The authors analyze the implications of these trade-offs for the design of climate-observing systems based on observation of infrared radiance. It is argued that convincing demonstrations of sensor accuracy requires a measurement approach founded on the overdetermination of instrument calibration, an approach that aims to reveal rather than conceal instrumental error. It is argued that the required accuracy can by achieved in simple instruments that provide spectral resolution if high sensitivity is not simultaneously demanded. Laboratory data are presented to illustrate the means by which radiometric calibration with the accuracy required for climate observation—about 0.1 K in the midinfrared—might be achieved in a practical instrument.

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F. Vitart, J. L. Anderson, and W. F. Stern

Abstract

Tropical storms simulated by a nine-member ensemble of GCM integrations forced by observed SSTs have been tracked by an objective procedure for the period 1980–88. Statistics on tropical storm frequency, intensity, and first location have been produced. Statistical tools such as the chi-square and the Kolmogorov–Smirnov test indicate that there is significant potential predictability of interannual variability of simulated tropical storm frequency, intensity, and first location over most of the ocean basins. The only common point between the nine members of the ensemble is the SST forcing. This implies that SSTs play a fundamental role in model tropical storm frequency, intensity, and first location interannual variability. Although the interannual variability of tropical storm statistics is clearly affected by SST forcing in the GCM, there is also a considerable amount of noise related to internal variability of the model. An ensemble of atmospheric model simulations allows one to filter this noise and gain a better understanding of the mechanisms leading to interannual tropical storm variability.

An EOF analysis of local SSTs over each ocean basin and a combined EOF analysis of vertical wind shear, 850-mb vorticity, and 200-mb vorticity have been performed. Over some ocean basins such as the western North Atlantic, the interannual frequency of simulated tropical storms is highly correlated to the first combined EOF, but it is not significantly correlated to the first EOF of local SSTs. This suggests that over these basins the SSTs have an impact on the simulated tropical storm statistics from a remote area through the large-scale circulation as in observations. Simulated and observed tropical storm statistics have been compared. The interannual variability of simulated tropical storm statistics is consistent with observations over the ocean basins where the model simulates a realistic interannual variability of the large-scale circulation.

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F. Vitart, J. L. Anderson, and W. F. Stern

Abstract

The present study examines the simulation of the number of tropical storms produced in GCM integrations with a prescribed SST. A 9-member ensemble of 10-yr integrations (1979–88) of a T42 atmospheric model forced by observed SSTs has been produced; each ensemble member differs only in the initial atmospheric conditions. An objective procedure for tracking-model-generated tropical storms is applied to this ensemble during the last 9 yr of the integrations (1980–88). The seasonal and monthly variations of tropical storm numbers are compared with observations for each ocean basin.

Statistical tools such as the Chi-square test, the F test, and the t test are applied to the ensemble number of tropical storms, leading to the conclusion that the potential predictability is particularly strong over the western North Pacific and the eastern North Pacific, and to a lesser extent over the western North Atlantic. A set of tools including the joint probability distribution and the ranked probability score are used to evaluate the simulation skill of this ensemble simulation. The simulation skill over the western North Atlantic basin appears to be exceptionally high, particularly during years of strong potential predictability.

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Christopher W. Landsea, Steve Feuer, Andrew Hagen, David A. Glenn, Jamese Sims, Ramon Perez, Michael Chenoweth, and Nicholas Anderson

Abstract

A reanalysis of the Atlantic basin tropical storm and hurricane database (“best track”) for the period from 1921 to 1930 has been completed. This reassessment of the main archive for tropical cyclones of the North Atlantic Ocean, Caribbean Sea, and Gulf of Mexico was necessary to correct systematic biases and random errors in the data as well as to search for previously unrecognized systems. The methodology for the reanalysis process for revising the track and intensity of tropical cyclone data has been detailed in a previous paper on the reanalysis. The 1921–30 dataset now includes several new tropical cyclones, excludes one system previously considered a tropical storm, makes generally large alterations in the intensity estimates of most tropical cyclones (both toward stronger and weaker intensities), and typically adjusts existing tracks with minor corrections. Average uncertainty in intensity and track values is estimated for both open-ocean conditions as well as landfalling systems. Highlights are given for changes to the more significant hurricanes to impact the United States, Central America, and the Caribbean for this decade.

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Rym Msadek, T. L. Delworth, A. Rosati, W. Anderson, G. Vecchi, Y.-S. Chang, K. Dixon, R. G. Gudgel, W. Stern, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang

Abstract

Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.

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G. A. Vecchi, T. Delworth, R. Gudgel, S. Kapnick, A. Rosati, A. T. Wittenberg, F. Zeng, W. Anderson, V. Balaji, K. Dixon, L. Jia, H.-S. Kim, L. Krishnamurthy, R. Msadek, W. F. Stern, S. D. Underwood, G. Villarini, X. Yang, and S. Zhang

Abstract

Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system; therefore, understanding and predicting TC location, intensity, and frequency is of both societal and scientific significance. Methodologies exist to predict basinwide, seasonally aggregated TC activity months, seasons, and even years in advance. It is shown that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basinwide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal time scales, and comprises high-resolution (50 km × 50 km) atmosphere and land components as well as more moderate-resolution (~100 km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux adjustment.” A suite of 12-month duration retrospective forecasts is performed over the 1981–2012 period, after initializing the climate model to observationally constrained conditions at the start of each forecast period, using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basinwide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally aggregated regional TC activity months in advance are feasible.

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