Winter Warming Indicated by Recent Temperature and Precipitation Anomalies

2003 ◽  
Vol 27 (4) ◽  
pp. 320-338 ◽  
Author(s):  
Wendell Tangborn
Keyword(s):  
Winter Warming ◽  
Temperature And Precipitation ◽  
Precipitation Anomalies

scholarly journals Winter warming detection using temperature and precipitation anomalies in arid and semi-arid areas

2021 ◽  
Author(s):  
Negar Siabi ◽  
Mohammad Mousavi Baygi ◽  
Seyed Majid Hasheminia ◽  
Mohammad Bannayan
Keyword(s):  
Precipitation Anomaly ◽  
Daily Temperature ◽  
Simultaneous Increase ◽  
Arid Areas ◽  
Maximum Daily Temperature ◽  
Winter Warming ◽  
Temperature And Precipitation ◽  
Mk Test ◽  
Precipitation Anomalies ◽  
Semi Arid

Abstract Extreme winter warming can affect many aspects of environmental and human related activities. It can be disastrous, especially in arid regions. However, no specific research has been carried out on detecting winter warming in Iran. To address this research gap, this study was performed to investigate winter warming in the arid and semi-arid areas located in northeastern Iran. For this purpose, anomalies of minimum and maximum daily temperature, average daily temperature, mean daily temperature range and mean daily precipitation were studied on monthly, seasonal, annual and decadal scales. Along with this, the trend in the data was analyzed using the Mann–Kendall (MK) test. The results showed that since the 1990s there has been a significant increase in temperature positive anomalies at most stations. In addition, the precipitation anomaly mutations occurred later than temperature. In most cases the increase in winter anomalies was higher than the average annual anomalies. As an example, the maximum winter temperature anomaly increased from 0.38 °C in the 1990s to 2.07 °C in the 2000s at Mashhad station. Due to the simultaneous increase in anomalies at most stations, the detected winter warming is more likely to be the result of global warming rather than local synoptic climate.

The Life Cycle and Variability of Antarctic Weak Polar Vortex Events

2022 ◽  
pp. 1-63
Keyword(s):  
Life Cycle ◽  
Polar Vortex ◽  
Southern Annular Mode ◽  
Austral Spring ◽  
Stratospheric Polar Vortex ◽  
Temperature And Precipitation ◽  
Scale Temperature ◽  
Precipitation Anomalies ◽  
Polar Stratosphere ◽  
The Antarctic

Abstract Motivated by the strong Antarctic sudden stratospheric warming (SSW) in 2019, a survey on the similar Antarctic weak polar events (WPV) is presented, including their life cycle, dynamics, seasonality, and climatic impacts. The Antarctic WPVs have a frequency of about four events per decade, with the 2002 event being the only major SSW. They show a similar life cycle to the SSWs in the Northern Hemisphere but have a longer duration. They are primarily driven by enhanced upward-propagating wavenumber 1 in the presence of a preconditioned polar stratosphere, i.e., a weaker and more contracted Antarctic stratospheric polar vortex. Antarctic WPVs occur mainly in the austral spring. Their early occurrence is preceded by an easterly anomaly in the middle and upper equatorial stratosphere besides the preconditioned polar stratosphere. The Antarctic WPVs increase the ozone concentration in the polar region and are associated with an advanced seasonal transition of the stratospheric polar vortex by about one week. Their frequency doubles after 2000 and is closely related to the advanced Antarctic stratospheric final warming in recent decades. The WPV-resultant negative phase of the southern annular mode descends to the troposphere and persists for about three months, leading to persistent hemispheric scale temperature and precipitation anomalies.

Can climate models capture the high amplitudes circumglobal waves and their surface imprints?  

2021 ◽  
Author(s):  
Fei Luo ◽  
Kai Kornhuber ◽  
Frank Selten ◽  
Dim Coumou
Keyword(s):  
Soil Moisture ◽  
Climate Models ◽  
Phase Locking ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Circulation Types ◽  
Temperature And Precipitation ◽  
Wave Patterns ◽  
Precipitation Anomalies ◽  
June July

<p>Pronounced circumglobal waves can trigger and maintain persistent summer weather conditions by remaining in their preferred phase-locked positions for several weeks in a row. This phenomenon, especially important for wave numbers 5 and 7, has been observed in recent years, but it is unclear whether climate models can reproduce circulation types and their surface imprints.</p><p>Here we assess three climate models (EC-Earth3, CESM1.2, and MIROC5)  for their representation of amplified circumglobal waves and associated surface imprints in summer (June, July and August) over 1979-2016. ERA5 reanalysis data is used as reference to assess the models’ performance. We run a series of modeling experiments to understand the source of biases in the climate models: free interactive atmosphere and soil moisture runs (AISI), atmospheric nudged runs (AFSI), soil moisture prescribed runs (AISF), and both atmosphere and soil moisture nudged experiments (AFSF).</p><p>We show that all models reasonably well reproduce the climatological wave spectra. Further, both wave 5 and wave 7 are found to exhibit phase-locking behaviors across all models, resulting in similar wave patterns across the hemisphere as compared to reanalysis. The surface imprints are observed in the models as well, but depending on the model, the results vary in strength. We also found the biases in surface temperature and precipitation anomalies mainly come from the atmospheric circulation in the models as these biases reduced considerably from AISI runs to AFSI and AFSF runs where upper atmosphere levels were nudged. Nudging soil moisture also minimizes some biases in the models but not as obvious as nudging the atmosphere. </p><div> <div> <div> </div> </div> </div>

scholarly journals Characterizing ENSO Coupled Variability and Its Impact on North American Seasonal Precipitation and Temperature*

2015 ◽  
Vol 28 (10) ◽  
pp. 4231-4245 ◽  
Author(s):  
Michelle L. L’Heureux ◽  
Michael K. Tippett ◽  
Anthony G. Barnston
Keyword(s):  
North American ◽  
Longwave Radiation ◽  
Climate Impacts ◽  
Spring Precipitation ◽  
Central Pacific ◽  
Complete Representation ◽  
Central Pacific Ocean ◽  
Temperature And Precipitation ◽  
Precipitation Anomalies ◽  
Coupled Variability

Abstract Two questions are addressed in this paper: whether ENSO can be adequately characterized by simple, seasonally invariant indices and whether the time series of a single component—SST or OLR—provides a sufficiently complete representation of ENSO for the purpose of quantifying U.S. climate impacts. Here, ENSO is defined as the leading mode of seasonally varying canonical correlation analysis (CCA) between anomalies of tropical Pacific SST and outgoing longwave radiation (OLR). The CCA reveals that the strongest regions of coupling are mostly invariant as a function of season and correspond to an OLR region located in the central Pacific Ocean (CP-OLR) and an SST region in the eastern Pacific that coincides with the Niño-3 region. In a linear context, the authors explore whether the use of a combined index of these SST and OLR regions explains additional variance of North American temperature and precipitation anomalies beyond that described by using a single index alone. Certain seasons and regions benefit from the use of a combined index. In particular, a combined index describes more variability in winter/spring precipitation and summer temperature.

On the Development and Demise of the Fall 2019 Southeast U. S. Flash Drought: Links to an Extreme Positive IOD

2020 ◽  
pp. 1-60
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Anthony M. DeAngelis ◽  
Hailan Wang ◽  
Randal D. Koster
Keyword(s):  
Indian Ocean ◽  
Rossby Wave ◽  
Wave Train ◽  
Temperature And Precipitation ◽  
Ocean Region ◽  
Dry Conditions ◽  
Underlying Causes ◽  
The Indian Ocean ◽  
Precipitation Anomalies ◽  
Rossby Wave Train

AbstractMuch of the southeast United States experienced record dry conditions during September of 2019, with the area in abnormally dry to exceptional drought conditions growing from 25% at the beginning of the month to 80% by the end of the month. The drought ended just as abruptly due to above normal rain that fell during the second half of October. In this study we employed MERRA-2 and the GEOS-5 AGCM to diagnose the underlying causes of the drought’s onset, maintenance, and demise. The basic approach involves performing a series of AGCM simulations in which the model is constrained to remain close to MERRA-2 over pre-specified areas that are external to the drought region. The start of the drought appears to have been forced by anomalous heating in the central/western tropical Pacific that resulted in low level anti-cyclonic flow and a tendency for descending motion over much of the southeast. An anomalous ridge associated with a Rossby wave train (emanating from the Indian Ocean region) is found to be the main source of the most intense temperature and precipitation anomalies that develop over the southeast during the last week of September. A second Rossby wave train (emanating from the same region) is responsible for the substantial rain that fell during the second half of October to end the drought. The links to the Indian Ocean Dipole (with record positive values) as well as a waning El Nino allow some speculation as to the likelihood of similar events occurring in the future.

Confronting Climate-Related Disasters in Asia and the Pacific

2014 ◽  
Vol 65 (2) ◽  
Author(s):  
Vinod Thomas
Keyword(s):  
Natural Disasters ◽  
Climate Adaptation ◽  
Heat Waves ◽  
Scientific Evidence ◽  
Population Exposure ◽  
Temperature And Precipitation ◽  
The Pacific ◽  
Precipitation Anomalies ◽  
Population Vulnerability ◽  
Policy And Planning

AbstractThe frequency of intense natural disasters has been on the rise worldwide over the past 40 years. Meanwhile, temperatures have risen on average, while both temperatures and precipitation have become more variable and more extreme. Their impacts are clearly visible in Asia and the Pacific region, which has seen some of the most damaging natural disasters.Recent scientific evidence points to the link between rising greenhouse gas concentrations in the atmosphere and climate variables such as temperature and precipitation that underlie floods, storms, droughts and heatwaves. Rising population exposure, greater population vulnerability, and increasing climate-related hazards are three main disaster risk factors behind the increased frequency of intense natural disasters. A study underlying this paper finds an association between more frequent climatological disasters (relating to droughts and heat waves) and rising temperatures; and between hydrometeorological disasters (relating to floods and storms) and people locating in harm’s way and precipitation anomalies.These findings underpin the necessity of greater prevention of natural disasters, and of integrating climate adaptation and mitigation in reducing disaster risks. With no let-up in the increasing costs of disasters to lives and livelihood, homes and infrastructure - such preventive measures must be part of policy and planning.

scholarly journals Information Content of Seasonal Forecasts in a Changing Climate

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Nir Y. Krakauer ◽  
Michael D. Grossberg ◽  
Irina Gladkova ◽  
Hannah Aizenman
Keyword(s):  
Information Gain ◽  
Seasonal Forecasts ◽  
Temperature And Precipitation ◽  
Skill Scores ◽  
The Usa ◽  
Precipitation Anomalies ◽  
The Mean ◽  
Climate Prediction Center

We study the potential value to stakeholders of probabilistic long-term forecasts, as quantified by the mean information gain of the forecast compared to climatology. We use as a case study the USA Climate Prediction Center (CPC) forecasts of 3-month temperature and precipitation anomalies made at 0.5-month lead time since 1995. Mean information gain was positive but low (about 2% and 0.5% of the maximum possible for temperature and precipitation forecasts, resp.) and has not increased over time. Information-based skill scores showed similar patterns to other, non-information-based, skill scores commonly used for evaluating seasonal forecasts but tended to be smaller, suggesting that information gain is a particularly stringent measure of forecast quality. We also present a new decomposition of forecast information gain into Confidence, Forecast Miscalibration, and Climatology Miscalibration components. Based on this decomposition, the CPC forecasts for temperature are on average underconfident while the precipitation forecasts are overconfident. We apply a probabilistic trend extrapolation method to provide an improved reference seasonal forecast, compared to the current CPC procedure which uses climatology from a recent 30-year period. We show that combining the CPC forecast with the probabilistic trend extrapolation more than doubles the mean information gain, providing one simple avenue for increasing forecast skill.

Sign in / Sign up

Export Citation Format

Share Document