Winter 2015/16: A Turning Point in ENSO-Based Seasonal Forecasts

Cohen, Judah; Pfeiffer, Karl P.; Francis, Jennifer A.

doi:10.5670/oceanog.2017.115

Cited by 23 publications

(33 citation statements)

References 39 publications

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“…In particular, Arctic sea ice loss has been correlated with a greater number of cold winter days (defined as 1.5 standard deviations below climatology) in the northern continents [7]. According to some analyses, Arctic sea ice loss and enhanced Arctic warming [8] have lead to changes in air pressure and circulation patterns that favor cold winters in the Eastern USA and Northern Eurasia [9,10], though this causative role is disputed [11,12]. A weakening stratospheric polar vortex may be a mediating factor [13].…”

Section: Introductionmentioning

confidence: 99%

Shifting Hardiness Zones: Trends in Annual Minimum Temperature

Krakauer

2018

Climate

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Work published in 2012 revealed that annual minimum temperatures over the coterminous United States (USA) have increased faster than mean temperatures, causing a pronounced poleward shift in the positions of hardiness zones defined by the expected annual minimum temperature. Here, estimates of increases in annual minimum temperatures are updated and extended to other land areas where station temperature records are available. Annual minimum temperatures have increased faster than mean temperatures in seasonally cold regions globally, but have warmed at about the same rate as mean temperatures in tropical climates. The mean increase in annual minimum temperature across the available weather stations was 2.0°C between 1970 and 2016 (or almost 0.5°C per decade), as compared to an increase of 1.2°C in mean temperature. Recent cold winters in regions such as Eastern North America did not clearly break with this trend and were within the range of variability seen in past decades. Overall, annual minimum temperatures appear to be increasing steadily, though with considerable inter-annual variability.

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Section: Introductionmentioning

confidence: 99%

Shifting Hardiness Zones: Trends in Annual Minimum Temperature

Krakauer

2018

Climate

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“…That noise component just happened to dominate the predictable seasonal signal in the last two winters. Cohen et al () note in addition that observed precipitation amounts for Seattle and Los Angeles were outside the range of the NMME ensemble predictions for DJF (December–February) 2015–2016, suggesting that these models may underestimate noise or miss predictable seasonal components attributable to certain remote large‐scale influences on California precipitation (Mo and Higgins, ; Hartmann, ; Hoell et al, ; Seager and Henderson, ; Cohen, ; Swain et al, ; Teng & Branstator, ; Paek et al, ; Wang et al, ).…”

Section: Introductionmentioning

confidence: 99%

Seasonal Noise Versus Subseasonal Signal: Forecasts of California Precipitation During the Unusual Winters of 2015–2016 and 2016–2017

Wang

Anichowski

Tippett

et al. 2017

Geophysical Research Letters

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Subseasonal forecasts of California precipitation during the unusual winters of 2015–2016 and 2016–2017 are examined in this study. It is shown that two different ensemble forecast systems were able to predict monthly precipitation anomalies in California during these periods with some skill in forecasts initialized near or at the start of the month. The unexpected anomalies in February 2016, as well as in January and February 2017, were associated with shifts in the position of the jet stream over the northeast Pacific in a manner broadly consistent with associations found in larger ensembles of forecasts. These results support the broader notion that what is unpredictable atmospheric noise at the seasonal time scale can become predictable signal at the subseasonal time scale, despite that the lead times and verification averaging times associated with these forecasts are outside the predictability horizons of canonical midrange weather forecasting.

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“…For example, Cohen et al . () argued that in the current era of the Arctic amplification, Arctic influences on mid‐latitude weather patterns should be considered in seasonal forecasts developed based on simulations of general circulation models (GCMs). Sigmond et al .…”

Section: Introductionmentioning

confidence: 99%

“…Consideration of other natural climate forcings such as the North Atlantic Oscillation (NAO), the Indian Ocean Dipole (IOD) and the Pacific-North-American (PNA) pattern has also provided improvement of the regional seasonal climate forecasts. Results of several recent studies have indicated that in order to add skill to seasonal climate forecasts, in addition to the abovementioned natural climate forcings, some other features of the climate system need to be adequately considered (Sigmond et al, 2013;Cohen et al, 2017). For example, Cohen et al (2017) argued that in the current era of the Arctic amplification, Arctic influences on mid-latitude weather patterns should be considered in seasonal forecasts developed based on simulations of general circulation models (GCMs).…”

mentioning

confidence: 99%

“…Results of several recent studies have indicated that in order to add skill to seasonal climate forecasts, in addition to the abovementioned natural climate forcings, some other features of the climate system need to be adequately considered (Sigmond et al, 2013;Cohen et al, 2017). For example, Cohen et al (2017) argued that in the current era of the Arctic amplification, Arctic influences on mid-latitude weather patterns should be considered in seasonal forecasts developed based on simulations of general circulation models (GCMs). Sigmond et al (2013) demonstrated that consideration of the stratosphere-troposphere interactions in climate models adds to the skill of seasonal forecasts.…”

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confidence: 99%

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Dynamical downscaling of CSIRO‐Mk3.6 seasonal forecasts over Iran with the regional climate model version 4

Alizadeh

2019

Intl Journal of Climatology

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Providing reliable seasonal forecasts of the climate system is essential to make decisions for resource management and planning, such that advances in seasonal forecasting by dynamical downscaling can bring significant socio‐economic benefits. A finer resolution Regional Climate Model version 4 (RegCM4) is nested within the large‐scale fields of the coarser CSIRO‐Mk3.6 general circulation model (GCM) to dynamically downscale outputs of CSIRO‐Mk3.6 over Iran in Southwest Asia. To this end, 120 6‐month‐long simulations were conducted. Starting from January 2007, each simulation run forwards 1 month compared to the previous run, altogether covering the period 2007–2016. Comparing model results with ERA‐Interim and CRU datasets indicated that RegCM4 is able to add some value to the driving CSIRO‐Mk3.6, particularly in low lands of central to eastern Iran where CSIRO‐Mk3.6 depicts significant cold biases. Nevertheless, relatively large biases in simulations of RegCM4 are found over some regions in Iran caused by propagation of errors from the driving GCM. It is also found that errors in prediction of different phases of the El Niño‐Southern Oscillation (ENSO) events in the driving CSIRO‐Mk3.6 significantly degrade the nested model simulations, such that associated with La Niña and El Niño, large warm and cold biases are found, respectively, over Iran. Improvements should be made in physics of the CSIRO‐Mk3.6 GCM to better simulate different phases of ENSO. Results also indicated that performance of RegCM4 in simulating 2‐m temperature is strongly related to the forecast lead time, such that model errors generally become larger when the forecast time increases.

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Winter 2015/16: A Turning Point in ENSO-Based Seasonal Forecasts

Cited by 23 publications

References 39 publications

Shifting Hardiness Zones: Trends in Annual Minimum Temperature

Shifting Hardiness Zones: Trends in Annual Minimum Temperature

Seasonal Noise Versus Subseasonal Signal: Forecasts of California Precipitation During the Unusual Winters of 2015–2016 and 2016–2017

Dynamical downscaling of CSIRO‐Mk3.6 seasonal forecasts over Iran with the regional climate model version 4

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