This paper presents an analysis of the relationship between land surface temperatures (LST) and screen‐level air temperatures (T2m) using in situ observations from 19 Atmospheric Radiation ...Measurement (ARM) deployments located in a range of geographical regimes. The diurnal cycle is resolved using 1 min observations: a particular focus of the study is on the relationship between daily extremes of LST (LSTmax, LSTmin) and T2m (Tmax, Tmin). Temperature differences are analyzed with respect to cloud, wind speed, and snow cover. Under cloud‐free, low wind speed conditions, daytime LST is often several degrees Celsius (°C) higher than T2m at low‐to‐middle latitudes and at high latitudes during the summer months. In contrast, LST and T2m are often close (e.g., within 2°C) under cloudy and/or moderate‐to‐high wind speed conditions or when solar insolation is low or absent. LSTmin and Tmin are generally well correlated (r > 0.8, often r > 0.9), while seasonal correlations between LSTmax and Tmax are weaker (r > 0.6, often r > 0.8). At high latitudes, LST and T2m are well coupled in spring/autumn/winter; the relationship between LST and T2m tends to weaken with decreasing latitude. The timing of daily extremes is also investigated and it is found that LSTmin and Tmin typically occur close to sunrise, with Tmin occurring slightly after LSTmin. LSTmax occurs close to solar noon, with Tmax typically occurring 1–3 hours later. This study will inform temperature data users on differences between LST and T2m and aid development of methods to estimate T2m using satellite LSTs.
Key Points
The land skin‐air temperature relationship is characterized using in situ data from the Atmospheric Radiation Measurement program
Example diurnal temperature evolutions are presented, and the timing and magnitude of daily extreme temperatures are analyzed
Cloud, wind, and snow cover are found to affect the land skin‐air temperature relationship
Pakistan is one of the most vulnerable countries of the world to temperature extremes due to its predominant arid climate and geographic location in the fast temperature rising zone. Spatial ...distribution of the trends in annual and seasonal temperatures and temperature extremes over Pakistan has been assessed in this study. The gauge-based gridded daily temperature data of Berkeley Earth Surface Temperature (BEST) having a spatial resolution of 1° × 1° was used for the assessment of trends over the period 1960–2013 using modified Mann-Kendall test (MMK), which can discriminate the multi-decadal oscillatory variations from secular trends. The results show an increase in the annual average of daily maximum and minimum temperatures in 92 and 99% area of Pakistan respectively at 95% level of confidence. The annual temperature is increasing faster in southern high-temperature region compared to other parts of the country. The minimum temperature is rising faster (0.17–0.37 °C/decade) compared to maximum temperature (0.17–0.29 °C/decade) and therefore declination of diurnal temperature range (DTR) (− 0.15 to − 0.08 °C/decade) in some regions. The annual numbers of both hot and cold days are increasing in whole Pakistan except in the northern sub-Himalayan region. Heat waves are on the rise, especially in the hot Sindh plains and the Southern coastal region, while the cold waves are becoming lesser in the northern cold region. Obtained results contradict with the findings of previous studies on temperature trends, which indicate the need for reassessment of climatic trends in Pakistan using the MMK test to understand the anthropogenic impacts of climate change.
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.
Variability and change in near‐surface air temperature at 17 Antarctic stations is examined using data from the SCAR READER database. We consider the relationships between temperature, and ...atmospheric circulation, sea ice concentration and forcing by the tropical oceans. All 17 stations have their largest inter‐annual temperature variability during the winter and the annual mean temperature anomalies are dominated by winter temperatures. The large inter‐annual temperature variability on the western Antarctic Peninsula has decreased over the instrumental period as sea ice has declined. Variability in the phase of the SAM exerts the greatest control of temperatures, although tropical Pacific forcing has also played a large part, along with local atmospheric circulation variability at some locations. The relationship of positive (negative) SAM and high (low) Peninsula and low (high) East Antarctic temperatures was not present before the mid‐1970s. Thirteen of the 17 stations have experienced a positive trend in their annual mean temperature over the full length of their record, with the largest being at Vernadsky (formerly Faraday) (0.46° ± 0.15°C·dec−1) on the western side of the Antarctic Peninsula. The deepening of the Amundsen Sea low as a result of the more positive SAM and changes in the IPO and PDO have contributed to the warming of the Peninsula. Beyond the Antarctic Peninsula there has been little significant change in temperature. The two plateau stations had a small cooling from the late 1970s to the late 1990s consistent with the SAM becoming positive, but have subsequently warmed. During spring there has been an Antarctic‐wide warming, with all but one station having experienced an increase in temperature, although the only trends that were significant were at Vostok, Scott base, Vernadsky and Amundsen‐Scott. In this season, much of the Peninsula/West Antarctic warming can be attributed to tropical Pacific forcing through the IPO/PDO.
Over recent decades, temperatures across the Antarctic continent have exhibited a complex picture of change with a marked warming of the Antarctic Peninsula but with little overall change elsewhere. The ozone hole has contributed significantly to the warming of the Peninsula, although tropical Pacific climate variability has also played a part. The largest seasonal Antarctic‐wide change has been a warming during the spring, with much of this attributable to tropical variability.
This study investigates the long‐term variability of surface air temperature (SAT) over the Arabian Peninsula (AP), using data from the Climate Research Unit (TS 3.22) for the 1960–2010 period. The ...long‐term climatology suggests that the warmest AP mean temperatures occur during summer, with the highest temperatures over the northern AP (NAP), due to the monsoon–desert mechanism. During winter, the NAP exhibits low SATs under the influence of western disturbances originating from the Mediterranean. The southwestern AP exhibits the lowest temperatures because of its proximity to the Arabian Sea cold waters, and also because of the orographic effects. The inter‐annual variability of the SAT is stronger during winters. A linear trend analysis reveals a significant increase in the SAT anomaly (0.10 °C/decade) across the AP, consistently with the global temperature anomalies. Besides the local convective heating, summer SAT variability is associated with the weakening of the Asian jet stream and a Rossby wave train from the Indian Ocean. This variability is also influenced by the anomalous low pressure over the North Atlantic and the Sahara, a high‐pressure system over Siberia and the northwest Pacific. Both in spring and autumn, sea surface temperature (SST) variations over the Indo‐western Pacific are highly influenced the AP SATs, whereas winter SATs are modulated by the subtropical jet stream and the Middle East jet stream. In all seasons, the AP SAT is strongly influenced by the SST variations over the tropical oceans. The temperature variability is closely associated with the El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO) and Arctic Oscillation (AO). The warm phase of ENSO (i.e., El Niño) is one possible reason behind the inter‐annual increase in SAT over the southern AP. The negative phases of NAO and AO also play a role in increasing AP SAT.
Seasonal and annual mean surface air temperature (°C, shaded) and standard deviation (contours) over the Arabian Peninsula for the period 1960–2010.
Although the importance of thermoregulation and plasticity as compensatory mechanisms for climate change has long been recognized, they have largely been studied independently. Thus, we know ...comparatively little about how they interact to shape physiological variation in natural populations. Here, we test the hypothesis that behavioral thermoregulation and thermal acclimatization interact to shape physiological phenotypes in a natural population of the diurnal lizard, Sceloporus torquatus. Every month for one year we examined thermoregulatory effectiveness and changes in the population mean in three physiological parameters: cold tolerance (Ctmin), heat tolerance (Ctmax), and the preferred body temperature (Tpref), to indirectly assess thermal acclimatization in population means. We discovered that S. torquatus is an active thermoregulator throughout the year, with body temperature varying little despite strong seasonal temperature shifts. Although we did not observe a strong signal of acclimatization in Ctmax, we did find that Ctmin shifts in parallel with nighttime temperatures throughout the year. This likely occurs, at least in part, because thermoregulation is substantially less effective at buffering organisms from selection on lower physiological limits than upper physiological limits. Active thermoregulation is effective at limiting exposure to extreme temperatures during the day, but is less effective at night, potentially contributing to greater plasticity in Ctmin than Ctmax. Importantly, however, Tpref tracked seasonal changes in temperature, which is one the factors contributing to highly effective thermoregulation throughout the year. Thus, behavior and physiological plasticity do not always operate independently, which could impact how organisms can respond to rising temperatures.
•Behavioral thermoregulation and plasticity shape physiological phenotypes.•We examined thermoregulation and plasticity in a wild lizard population.•Thermoregulation during the day potentially limits heat tolerance plasticity.•Limited thermoregulation at night potentially contributes to cold tolerance plasticity.•The preferred body temperature is labile across seasons, contributing to high thermoregulatory efficiency year-round.
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.
The absence of sunlight during the winter in the High Arctic results in a strong surface-based atmospheric temperature inversion, especially during clear skies and light surface wind conditions. The ...inversion suppresses turbulent heat transfer between the ground and the boundary layer. As a result, the difference between the surface air temperature, measured at a height of 2 m, and the ground skin temperature can exceed several degrees Celsius. Such inversions occur very frequently in polar regions, are of interest to understand the mechanisms responsible for surface-atmosphere heat, mass, and momentum exchanges, and are critical for satellite validation studies.
The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are ...clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.
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