Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
96,826
result(s) for
"air temperature"
Sort by:
Changes in Annual Extremes of Daily Temperature and Precipitation in CMIP6 Models
This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ∼7% °C−1. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.
Journal Article
Impacts of early autumn Arctic sea ice concentration on subsequent spring Eurasian surface air temperature variations
This study reveals a close relation between autumn Arctic sea ice change (SIC) in the Laptev Sea-eastern Siberian Sea-Beaufort Sea and subsequent spring Eurasian surface air temperature (SAT) variation. Specifically, more (less) SIC over the above regions in early autumn generally correspond to SAT warming (cooling) over the mid-high latitudes of Eurasia during subsequent spring. Early autumn Arctic SIC affects spring Eurasian SAT via modulating spring Arctic Oscillation (AO) associated atmospheric changes. The meridional temperature gradient over the mid-high latitudes decreases following the Arctic sea ice loss. This results in deceleration of prevailing westerly winds over the mid-latitudes of the troposphere, which leads to increase in the upward propagation of planetary waves and associated Eliassen-Palm flux convergence in the stratosphere over the mid-high latitudes. Thereby, westerly winds in the stratosphere are reduced and the polar vortex is weakened. Through the wave-mean flow interaction and downward propagation of zonal wind anomalies, a negative spring AO pattern is formed in the troposphere, which favors SAT cooling over Eurasia. The observed autumn Arctic SIC-spring Eurasian SAT connection is reproduced in the historical simulation (1850–2005) of the flexible global ocean-atmosphere-land system model, spectral version 2 (FGOALS-s2). The FGOALS-s2 also simulates the close connection between autumn SIC and subsequent spring AO. Further analysis suggests that the prediction skill of the spring Eurasian SAT was enhanced when taking the autumn Arctic SIC signal into account.
Journal Article
Extreme Temperatures in the Antarctic
We present the first Antarctic-wide analysis of extreme near-surface air temperatures based on data collected up to the end of 2019 as part of the synoptic meteorological observing programs. We consider temperatures at 17 stations on the Antarctic continent and nearby sub-Antarctic islands. We examine the frequency distributions of temperatures and the highest and lowest individual temperatures observed. The variability and trends in the number of extreme temperatures were examined via the mean daily temperatures computed from the 0000, 0600, 1200, and 1800 UTC observations, with the thresholds for extreme warm and cold days taken as the 5th and 95th percentiles. The five stations examined from the Antarctic Peninsula region all experienced a statistically significant increase (p < 0.01) in the number of extreme high temperatures in the late-twentieth-century part of their records, although the number of extremes decreased in subsequent years. For the period after 1979 we investigate the synoptic background to the extreme events using ECMWF interim reanalysis (ERA-Interim) fields. The majority of record high temperatures were recorded after the passage of air masses over high orography, with the air being warmed by the foehn effect. At some stations in coastal East Antarctica the highest temperatures were recorded after air with a high potential temperature descended from the Antarctic plateau, resulting in an air mass 5°–7°C warmer than the maritime air. Record low temperatures at the Antarctic Peninsula stations were observed during winters with positive sea ice anomalies over the Bellingshausen and Weddell Seas.
Journal Article
A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900
A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900–2014, 1979–2014 and 1998–2014. The best estimates of warming trends and there 95% confidence ranges for 1900–2014 are approximately 0.102 ± 0.006 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900–2014 and 1979–2014. For an even shorter and more recent period (1998–2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes.
Journal Article
An updated evaluation of the global mean land surface air temperature and surface temperature trends based on CLSAT and CMST
Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated global land surface air temperature and a land and marine surface temperature dataset, referred to as China global land surface air temperature (C-LSAT) and China merged surface temperature (CMST), to estimate trends in the global mean ST (combining land surface air temperature and sea surface temperature anomalies) with the data uncertainties being taken into account. Comparing with existing datasets, the statistical significance of the global mean ST warming trend during the past century (1900–2017) remains unchanged, while the recent warming trend during the “hiatus” period (1998–012) increases obviously, which is statistically significant at 95% level when fitting uncertainty is considered as in previous studies (including IPCC AR5) and is significant at 90% level when both fitting and data uncertainties are considered. Our analysis shows that the global mean ST warming trends in this short period become closer among the newly developed global observational data (CMST), remotely sensed/Buoy network infilled datasets, and reanalysis data. Based on the new datasets, the warming trends of global mean land SAT as derived from C-LSAT 2.0 for the period of 1979–2019, 1951–2019, 1900–2019 and 1850–2019 were estimated to be 0.296, 0.219, 0.119 and 0.081 °C/decade, respectively. The warming trends of global mean ST as derived from CMST for the periods of 1998–2019, 1979–2019, 1951–2019 and 1900–2019 were estimated to be 0.195, 0.173, 0.145 and 0.091 °C/decade, respectively.
Journal Article
Evidence for efficient nonevaporative leaf-to-air heat dissipation in a pine forest under drought conditions
• The drier climates predicted for many regions will result in reduced evaporative cooling, leading to leaf heat stress and enhanced mortality. The extent to which nonevaporative cooling can contribute to plant resilience under these increasingly stressful conditions is not well known at present.
• Using a novel, high accuracy infrared system for the continuous measurement of leaf temperature in mature trees under field conditions, we assessed leaf-to-air temperature differences (ΔT
leaf–air) of pine needles during drought.
• On mid-summer days, ΔT
leaf–air remained < 3°C, both in trees exposed to summer drought and in those provided with supplemental irrigation, which had a more than 10-fold higher transpiration rate. The nonevaporative cooling in the drought-exposed trees must be facilitated by low resistance to heat transfer, generating a large sensible heat flux, H. ΔT
leaf–air was weakly related to variations in the radiation load and mean wind speed in the lower part of the canopy, but was dependent on canopy structure and within-canopy turbulence that enhanced the H.
• Nonevaporative cooling is demonstrated as an effective cooling mechanism in needle-leaf trees which can be a critical factor in forest resistance to drying climates. The generation of a large H at the leaf scale provides a basis for the development of the previously identified canopy-scale ‘convector effect’.
Journal Article
Interdecadal Changes in the Relationship between Interannual Variations of Spring North Atlantic SST and Eurasian Surface Air Temperature
This study investigates interdecadal changes in the relationship between interannual variations of boreal spring sea surface temperature (SST) in the North Atlantic and surface air temperature (SAT) over the mid-to-high latitudes of Eurasia during 1948–2014. Analyses show that the connection between the spring North Atlantic tripole SST anomaly pattern and the Eurasian SAT anomalies has experienced marked interdecadal shifts around the early 1970s andmid-1990s. The connection is strong during 1954–72 and 1996–2014 but weak during 1973–91. A diagnosis indicates that interdecadal changes in the connection between the North Atlantic SST and Eurasian SAT variations are associatedwith changes in atmospheric circulation anomalies over Eurasia induced by the North Atlantic tripole SST anomaly pattern. Further analyses suggest that changes in atmospheric circulation anomalies over Eurasia are related to changes in the position of atmospheric heating anomalies over the North Atlantic, which may be due to the change in mean SST. Marked atmospheric heating anomalies appear over the tropical western North Atlantic during 1954–72 and 1996–2014 but over the subtropical central-eastern North Atlantic during 1973–91. Barotropic model experiments confirm that different background flows may also contribute to changes in anomalous atmospheric circulation over Eurasia.
Journal Article
Attributing Historical and Future Evolution of Radiative Feedbacks to Regional Warming Patterns using a Green’s Function Approach
Global radiative feedbacks have been found to vary in global climate model (GCM) simulations. Atmospheric GCMs (AGCMs) driven with historical patterns of sea surface temperatures (SSTs) and sea ice concentrations produce radiative feedbacks that trend toward more negative values, implying low climate sensitivity, over recent decades. Freely evolving coupled GCMs driven by increasing CO₂ produce radiative feedbacks that trend toward more positive values, implying increasing climate sensitivity, in the future. While this time variation in feedbacks has been linked to evolving SST patterns, the role of particular regions has not been quantified. Here, a Green’s function is derived from a suite of simulations within an AGCM (NCAR’s CAM4), allowing an attribution of global feedback changes to surface warming in each region. The results highlight the radiative response to surface warming in ascent regions of the western tropical Pacific as the dominant control on global radiative feedback changes. Historical warming from the 1950s to 2000s preferentially occurred in the western Pacific, yielding a strong global outgoing radiative response at the top of the atmosphere (TOA) and thus a strongly negative global feedback. Long-term warming in coupled GCMs occurs preferentially in tropical descent regions and in high latitudes, where surface warming yields small global TOA radiation change but large global surface air temperature change, and thus a less-negative global feedback. These results illuminate the importance of determining mechanisms of warm pool warming for understanding how feedbacks have varied historically and will evolve in the future.
Journal Article
How Well Do We Know ENSO’s Climate Impacts over North America, and How Do We Evaluate Models Accordingly?
The role of sampling variability in ENSO composites of winter surface air temperature and precipitation over North America during the period 1920–2013 is assessed for observations and ensembles of coupled model simulations in which sea surface temperature anomalies in the tropical eastern Pacific are nudged to those of the real world. The individual members of each model ensemble show a surprising amount of diversity in their ENSO composites, despite being constructed from the same observed set of 18 El Niño and 14 La Niña events. For a given model, this ensemble spread can only be due to sampling variability, that is, aliasing of internal variability that is unrelated to ENSO, which in turn is shown to arise from internal atmospheric dynamics rather than coupled ocean–atmosphere processes. Analogous ensemble spread is evident in 2000 synthetic ENSO composites based on observations using random sampling techniques. These synthetic composites provide information on the range of spatial patterns and amplitudes associated with imperfect estimation of the forced ENSO signal in the observational record. In some locations, the amplitude of the estimated ENSO signal can vary by more than a factor of two. This observational uncertainty necessitates an approach to model assessment that considers not only the model’s forced response to ENSO, given by its ensemble-mean ENSO composite, but also its representation of internal variability unrelated to ENSO. Such an approach is used to reveal fidelities and shortcomings in the Community Earth System Model, version 1.
Journal Article