Abstract
Recent research demonstrates that dynamical models sometimes fail to represent observed teleconnection patterns associated with predictable modes of climate variability. As a result, model ...forecast skill may be reduced. We address this gap in skill through the application of a Bayesian postprocessing technique—the calibration, bridging, and merging (CBaM) method—which previously has been shown to improve probabilistic seasonal forecast skill over Australia. Calibration models developed from dynamical model reforecasts and observations are employed to statistically correct dynamical model forecasts. Bridging models use dynamical model forecasts of relevant climate modes (e.g., ENSO) as predictors of remote temperature and precipitation. Bridging and calibration models are first developed separately using Bayesian joint probability modeling and then merged using Bayesian model averaging to yield an optimal forecast. We apply CBaM to seasonal forecasts of North American 2-m temperature and precipitation from the North American Multimodel Ensemble (NMME) hindcast. Bridging is done using the model-predicted Niño-3.4 index. Overall, the fully merged CBaM forecasts achieve higher Brier skill scores and better reliability compared to raw NMME forecasts. Bridging enhances forecast skill for individual NMME member model forecasts of temperature, but does not result in significant improvements in precipitation forecast skill, possibly because the models of the NMME better represent the ENSO–precipitation teleconnection pattern compared to the ENSO–temperature pattern. These results demonstrate the potential utility of the CBaM method to improve seasonal forecast skill over North America.
There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is ...driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.
Prior research provides mixed evidence on whether the transition to IAS/IFRS deters or contributes to greater earnings management (smoothing). The dominant explanation for the conflicting results is ...self-selection. Early voluntary adopters had incentives to increase the transparency of their reporting in order to attract outside capital, while those firms that waited until IFRS adoption became mandatory in EU countries lacked incentives for transparent reporting leading to increases in earnings management (smoothing) after IFRS adoption. We maintain that the IFRS standards that went into effect in 2005 provide greater flexibility of accounting choices because of vague criteria, overt and covert options, and subjective estimates. This greater flexibility coupled with the lack of clear guidance on how to implement these new standards has led to greater earnings management (smoothing). Consistent with this view, we find an increase in earnings management (smoothing) from pre-2005 to post-2005 for firms in countries that allowed early IAS/IFRS adoption, as well as for firms in countries that did not allow early IFRS adoption. We find no evidence of changes in incentives that can explain these results.
THE SUBSEASONAL EXPERIMENT (SubX) Pegion, Kathy; Kirtman, Ben P.; Becker, Emily ...
Bulletin of the American Meteorological Society,
10/2019, Letnik:
100, Številka:
10
Journal Article
Recenzirano
Odprti dostop
The Subseasonal Experiment (SubX) is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving subseasonal forecasts. Seven global models have ...produced 17 years of retrospective (re)forecasts and more than a year of weekly real-time forecasts. The reforecasts and forecasts are archived at the Data Library of the International Research Institute for Climate and Society, Columbia University, providing a comprehensive database for research on subseasonal to seasonal predictability and predictions. The SubX models show skill for temperature and precipitation 3 weeks ahead of time in specific regions. The SubX multimodel ensemble mean is more skillful than any individual model overall. Skill in simulating the Madden–Julian oscillation (MJO) and the North Atlantic Oscillation (NAO), two sources of subseasonal predictability, is also evaluated, with skillful predictions of the MJO 4 weeks in advance and of the NAO 2 weeks in advance. SubX is also able to make useful contributions to operational forecast guidance at the Climate Prediction Center. Additionally, SubX provides information on the potential for extreme precipitation associated with tropical cyclones, which can help emergency management and aid organizations to plan for disasters.
Recent studies have shown that the Madden–Julian Oscillation (MJO) impacts the leading modes of intraseasonal variability in the northern hemisphere extratropics, providing a possible source of ...predictive skill over North America at intraseasonal timescales. We find that a k-means cluster analysis of mid-level geopotential height anomalies over the North American region identifies several wintertime cluster patterns whose probabilities are strongly modulated during and after MJO events, particularly during certain phases of the El Niño-Southern Oscillation (ENSO). We use a simple new optimization method for determining the number of clusters,
k
, and show that it results in a set of clusters which are robust to changes in the domain or time period examined. Several of the resulting cluster patterns resemble linear combinations of the Arctic Oscillation (AO) and the Pacific/North American (PNA) teleconnection pattern, but show even stronger responses to the MJO and ENSO than clusters based on the AO and PNA alone. A cluster resembling the positive (negative) PNA has elevated probabilities approximately 8–14 days following phase 6 (phase 3) of the MJO, while a negative AO-like cluster has elevated probabilities 10–20 days following phase 7 of the MJO. The observed relationships are relatively well reproduced in the 11-year daily reforecast dataset from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). This study statistically links MJO activity in the tropics to common intraseasonal circulation anomalies over the North American sector, establishing a framework that may be useful for improving extended range forecasts over this region.
We give a new construction of a
p
-adic
L
-function
L
(
f
,
Ξ
)
, for
f
a holomorphic newform and
Ξ
an anticyclotomic family of Hecke characters of
Q
(
-
d
)
. The construction uses Ichino’s triple ...product formula to express the central values of
L
(
f
,
ξ
,
s
)
in terms of Petersson inner products, and then uses results of Hida to interpolate them. The resulting construction is well-suited for studying what happens when
f
is replaced by a modular form congruent to it modulo
p
, and has future applications in the case where
f
is residually reducible.
The Northern Annular Mode (NAM) dominates variability of the Northern Hemisphere (NH) wintertime extratropical circulation in both the troposphere and stratosphere. Changes in the tropospheric NAM ...(i.e., changes in the position and strength of the polar jet stream) directly alter NH mid-latitude temperature and precipitation patterns, making forecasting these changes a significant priority for subseasonal-to-seasonal (S2S) forecasts during boreal winter. This study examines fundamental characteristics of the wintertime tropospheric circulation pattern in the hindcast simulations of the North American Multi-Model Ensemble (NMME) Phase-2 model suite through examining how the models capture sudden stratospheric warming (SSW) events, known to precede large changes in the tropospheric NAM by 2–6 weeks. Findings indicate that the NMME Phase-2 models have an overall mixed performance in capturing the characteristics of the NAM and its teleconnections. Biases are apparent in the dominant nodes of the tropospheric NAM pattern, storm tracks and associated wave fluxes in the Atlantic, and a systematic underestimation of intraseasonal variability of the NH stratospheric polar vortex in the models (i.e., the stratospheric NAM). We then investigate the ability of the models to simulate the life cycle of model-identified SSW events, including pre- and post-SSW circulation patterns and sensible weather conditions. Specific model biases include inconsistent geopotential height precursor fields, weaker-than-observed vertical wave propagation prior to SSW events, and incorrect surface temperature regimes following the events. Together, the results suggest potential pathways forward for improving subseasonal winter weather forecasts associated with the NAM using the NMME Phase-2 models.
A principal component decomposition of monthly sea surface temperature (SST) variability in the tropical Pacific Ocean demonstrates that nearly all of the linear trends during 1950–2010 are found in ...two leading patterns. The first SST pattern is strongly related to the canonical El Niño-Southern Oscillation (ENSO) pattern. The second pattern shares characteristics with the first pattern and its existence solely depends on the presence of linear trends across the tropical Pacific Ocean. The decomposition also uncovers a third pattern, often referred to as ENSO Modoki, but the linear trend is small and dataset dependent over the full 61-year record and is insignificant within each season. ENSO Modoki is also reflected in the equatorial zonal SST gradient between the Niño-4 region, located in the west-central Pacific, and the Niño-3 region in the eastern Pacific. It is only in this zonal SST gradient that a marginally significant trend arises early in the Northern Hemisphere spring (March–May) during El Niño and La Niña and also in the late summer (July–September) during El Niño. Yet these SST trends in the zonal gradient do not unequivocally represent an ENSO Modoki-like dipole because they are exclusively associated with significant positive SST trends in either the eastern or western Pacific, with no corresponding significant negative trends. Insignificant trends in the zonal SST gradient are evident during the boreal wintertime months when ENSO events typically mature. Given the presence of positive SST trends across much of the equatorial Pacific Ocean, using fixed SST anomaly thresholds to define ENSO events likely needs to be reconsidered.
Abstract
Previous work has shown that the combined influence of El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) significantly impacts the wintertime circulation over North ...America for lead times up to at least 4 weeks. These findings suggest that both the MJO and ENSO may prove beneficial for generating a seamless prediction link between short-range deterministic forecasts and longer-range seasonal forecasts. To test the feasibility of this link, wintertime (December–March) probabilistic 2-m temperature (T2m) forecasts over North America are generated solely on the basis of the linear trend and statistical relationships with the initial state of the MJO and ENSO. Overall, such forecasts exhibit substantial skill for some regions and some initial states of the MJO and ENSO out to a lead time of approximately 4 weeks. In addition, the primary ENSO T2m regions of influence are nearly orthogonal to those of the MJO, which suggests that the MJO and ENSO generally excite different patterns within the continuum of large-scale atmospheric teleconnections. The strong forecast skill scores for some regions and initial states confirm the promise that information from the MJO and ENSO may offer forecasts of opportunity in weeks 3 and 4, which extend beyond the current 2-week extended-range outlooks of the National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Center (CPC), and an intraseasonal link to longer-range probabilistic forecasts.
Abstract
Causes for genomic and morphological similarities among recently radiated species are often multifaceted and are further convoluted among species that readily interbreed. Here, we couple ...genomic and morphological trait comparisons to test the extent that ancestry and gene flow explain the retention of mallard-like traits within a sister species, the Mexican duck. First, we confirm that these taxa remain genetically structured, and that Mexican ducks exhibit an isolation-by-distance pattern. Despite the assumption of wide-spread hybridization, we found only a few late-stage hybrids, all from the southwestern USA. Next, assessing 23 morphological traits, we developed a genetically-vetted morphological key that is > 97% accurate in distinguishing across sex-age cohorts of Mexican ducks, mallards, and hybrids. During key development, we determined that 25% of genetically pure, immature male Mexican ducks of the northern population naturally displayed mallard-like traits in their formative plumage. In fact, applying this key to 55 museum specimens, we identified that only four of the 14 specimens originally classified as phenotypic hybrids were truly hybrids. We discuss how genomic and morphological comparisons shed light into the mechanism(s) underlying the evolution of complex phenotypic traits in recent radiations, and how misunderstanding the true morphological diversity within Mexican ducks resulted in taxonomic revisions that hindered conservation efforts.
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