An official website of the United States government
Abstract Global Forecast System (GFS), North American Mesoscale Forecast System (NAM), and High-Resolution Rapid Refresh (HRRR) 2-m temperature, 10-m wind speed, and precipitation accumulation forecasts initialized at 1200 UTC are verified against New York State Mesonet (NYSM) observations from 1 January 2018 through 31 December 2021. NYSM observations at 126 site locations are used to calculate standard error statistics (e.g., forecast error, root-mean-square error) for temperature and wind speed and contingency table statistics for precipitation across forecast hours, meteorological seasons, and regions. The majority of the focus is placed on the first 18 forecast hours to allow for comparison among all three models. A daily NYSM station-mean temperature error analysis identified a slight cold bias at temperatures below 25°C in the GFS, a cool-to-warm bias as forecast temperatures warm in the HRRR, and a warm bias at temperatures above 30°C in each model. Differences arise when considering temperature biases with respect to lead times and seasons. Wind speeds are overforecast at all ranges in each season, and forecast wind speeds ≥ 18 m s−1are rarely observed. Performance diagrams indicate overall good forecast performance at precipitation thresholds of 0.1–1.5 mm, but with a high frequency bias in the GFS and NAM. This paper provides an overview of deterministic forecast performance across New York State, with the aim of sharing common biases associated with temperature, wind speed, and precipitation with operational forecasters and is the first step in developing a real-time model forecast uncertainty prediction tool.
more »
« less
Record Warmth of 2023 and 2024 was Highly Predictable and Resulted From ENSO Transition and Northern Hemisphere Absorbed Shortwave Anomalies
Abstract Global mean temperature rapidly warmed during 2023, making 2023 the second warmest year on record at 1.45°C above pre‐industrial climate, and 2024 became the first year on record to surpass 1.5°C. Here we explore the likelihood, mechanisms, and predictability of the rapid warming during 2023 with CMIP simulations and a fully‐coupled forecast ensemble initialized on 1 November 2022. The year‐to‐year (Y2Y) warming for the second half of 2023 of 0.49°C equaled the largest on record since 1850, and is simulated as a 1 in 6,000 years event. The forecast ensemble‐mean predicts about 75% of the observed warming during 2023. The remaining 25% of the warming lies within the forecast spread, with members that forecast a strong 2023 El Niño and positive absorbed shortwave anomalies more likely to forecast the entirety of the observed warming. The forecast ensemble succesfully predicts 2024 to be the first year on record above 1.5°C.
more »
« less
- Award ID(s):
- 2233421
- PAR ID:
- 10593987
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 52
- Issue:
- 10
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract. In 2020 the International Maritime Organization (IMO) implemented strict new regulations on the emissions of sulphate aerosol from the world's shipping fleet. This can be expected to lead to a reduction in aerosol-driven cooling, unmasking a portion of greenhouse gas warming. The magnitude of the effect is uncertain, however, due to the large remaining uncertainties in the climate response to aerosols. Here, we investigate this question using an 18-member ensemble of fully coupled climate simulations evenly sampling key modes of climate variability with the NCAR CESM2 model. We show that while there is a clear physical response of the climate system to the IMO regulations, including a surface temperature increase, we do not find global mean temperature influence that is significantly different from zero. The 20-year average global mean warming for 2020–2040 is +0.03 °C, with a 5–95 % confidence range of [-0.09, 0.19], reflecting the weakness of the perturbation relative to internal variability. We do, however, find a robust, non-zero regional temperature response in part of the North Atlantic. We also find that the maximum annual-mean ensemble-mean warming occurs around a decade after the perturbation in 2029, which means that the IMO regulations have likely had very limited influence on observed global warming to date. We further discuss our results in light of other, recent publications that have reached different conclusions. Overall, while the IMO regulations may contribute up to at 0.16 °C [-0.17, 0.52] to the global mean surface temperature in individual years during this decade, consistent with some early studies, such a response is unlikely to have been discernible above internal variability by the end of 2023 and is in fact consistent with zero throughout the 2020–2040 period.more » « less
-
null (Ed.)Abstract El Niño and La Niña events show a wide range of durations over the historical record. The predictability of event duration has remained largely unknown, although multiyear events could prolong their climate impacts. To explore the predictability of El Niño and La Niña event duration, multiyear ensemble forecasts are conducted with the Community Earth System Model, version 1 (CESM1). The 10–40-member forecasts are initialized with observed oceanic conditions on 1 March, 1 June, and 1 November of each year during 1954–2015; ensemble spread is created through slight perturbations to the atmospheric initial conditions. The CESM1 predicts the duration of individual El Niño and La Niña events with lead times ranging from 6 to 25 months. In particular, forecasts initialized in November, near the first peak of El Niño or La Niña, can skillfully predict whether the event continues through the second year with 1-yr lead time. The occurrence of multiyear La Niña events can be predicted even earlier with lead times up to 25 months, especially when they are preceded by strong El Niño. The predictability of event duration arises from initial thermocline depth anomalies in the equatorial Pacific, as well as sea surface temperature anomalies within and outside the tropical Pacific. The forecast error growth, on the other hand, originates mainly from atmospheric variability over the North Pacific in boreal winter. The high predictability of event duration indicates the potential for extending 12-month operational forecasts of El Niño and La Niña events by one additional year.more » « less
-
Abstract The weather of the McMurdo Dry Valleys, Antarctica, the largest ice‐free region of the Antarctica, has been continuously monitored since 1985 with currently 14 operational meteorological stations distributed throughout the valleys. Because climate is based on a 30‐year record of weather, this is the first study to truly define the contemporary climate of the McMurdo Dry Valleys. Mean air temperature and solar radiation based on all stations were −20°C and 102 W m−2, respectively. Depending on the site location, the mean annual air temperatures on the valleys floors ranged between −15°C and −30°C, and mean annual solar radiation varied between 72 and 122 W m−2. Surface air temperature decreased by 0.7°C per decade from 1986 to 2006 at Lake Hoare station (longest continuous record), after which the record is highly variable with no trend. All stations with sufficiently long records showed similar trend shifts in 2005 ±1 year. Summer is defined as November through February, using a physically based process: up‐valley warming from the coast associated with a change in atmospheric stability.more » « less
-
Abstract Global and regional impacts of El Niño-Southern Oscillation (ENSO) are sensitive to the details of the pattern of anomalous ocean warming and cooling, such as the contrasts between the eastern and central Pacific. However, skillful prediction of such ENSO diversity remains a challenge even a few months in advance. Here, we present an experimental forecast with a deep learning model (IGP-UHM AI model v1.0) for theE(eastern Pacific) andC(central Pacific) ENSO diversity indices, specialized on the onset of strong eastern Pacific El Niño events by including a classification output. We find that higher ENSO nonlinearity is associated with better skill, with potential implications for ENSO predictability in a warming climate. When initialized in May 2023, our model predicts the persistence of El Niño conditions in the eastern Pacific into 2024, but with decreasing strength, similar to 2015–2016 but much weaker than 1997–1998. In contrast to the more typical El Niño development in 1997 and 2015, in addition to the ongoing eastern Pacific warming, an eXplainable Artificial Intelligence analysis for 2023 identifies weak warm surface, increased sea level and westerly wind anomalies in the western Pacific as precursors, countered by warm surface and southerly wind anomalies in the northern Atlantic.more » « less
