AntAir: satellite-derived 1 km daily Antarctic air temperatures since 2003

Abstract. Air temperature is an important baseline parameter for terrestrial Antarctica in the context of patterns and processes in climatology, hydrology or ecology. There are still large uncertainties on how the Antarctic system responds to spatio-temporal variability of temperature. This can partly be attributed to the lack of high resolution datasets. In this paper, we present AntAir, a new dataset of gridded air temperatures in 1 km spatial and daily temporal resolution that is available since 2003. AntAir was created by modelling daily air temperature from MODIS land surface temperature using machine learning algorithms. Data from 70 weather stations was used as a reference. Daily temperatures could be estimated with a R2 of 0.91 and a RMSE of 5.07 °C validated on independent years. The performance to estimate the time series of a new spatial location was R2 = 0.78 and RMSE = 5.83 °C. Hence the high spatial and temporal resolution of the dataset as well as the high accuracy make AntAir an important baseline dataset for a wide range of applications in environmental science of Antarctica. The dataset is available at https://doi.pangaea.de/10.1594/PANGAEA.902166 (daily, Meyer et al., 2019a) and https://doi.pangaea.de/10.1594/PANGAEA.902193 (monthly, Meyer et al., 2019b).

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Constructing gridded hourly air temperature dataset

10.5194/egusphere-egu2020-17976 ◽

2020 ◽

Author(s):

Alexandru Dumitrescu ◽

Sorin Cheval

Keyword(s):

Air Temperature ◽

Land Surface ◽

Meteorological Data ◽

Surface Air Temperature ◽

Shuttle Radar Topography Mission ◽

National Network ◽

Research And Innovation ◽

Air Temperatures ◽

Spatio Temporal ◽

Mean Square Errors

Air temperature is one of the most important meteorological element, with major impact on the earth-atmosphere energy balance. The characteristics of the surface air temperature in locations without surface meteorological measurements are usually acquired by employing spatial statistics methods. Gridded surface meteorological data are essential for evaluating the performance of climatological models, for applying statistical downscaling methods and as input data for hydrological and agrometeorological models.In this work, we tested two categories of statistical methods (spatial and spatio-temporal) used for interpolating ground-based hourly air temperature data. The main input dataset used in this work was the quality controlled and homogenized hourly air temperatures measured between 2016 and 2017, obtained from four networks: Romanian National Meteorological Administration (ANM), National Network for Monitoring Air Quality (RNMCA), Regional Basic Synoptic Network (RBSN), and Meteorological Terminal Aviation Routine Weather Report network (METAR).&#160;The principal covariate used in the spatial interpolation procedures was the gap filled hourly LST data over Romania, available between 2016 to 2017, based on MSG-Seviri satellite images, which is an operational product of the Land Surface Analysis &#8211; Satellite Application Facility (LSA-SAF).&#160; The other predictors were derived from SRTM (Shuttle Radar Topography Mission) data and from CORINE Land Cover 2018 product. The gridding was performed in a Romanian National Grid (Stereo 70), at 1000 m &#215; 1000 m spatial resolution.The results of the tested methods show that the mean absolute errors (MAE) and root mean square errors (RMSE) of space&#8211;time predictions are considerably lower than those of the pure spatial estimation.This work was supported by a grant of Ministry of Research and Innovation, Romania, CNCS - UEFISCDI, project number&#160;PN-III-P1-1.1-PD-2016-1579, within PNCDI III.

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Spatio–Temporal Characterization of Land Surface Air Temperature Anomaly over Nigeria

Physical Science International Journal ◽

10.9734/psij/2019/v21i330108 ◽

2019 ◽

pp. 1-9

Author(s):

O. O. Ajileye ◽

S. S. Aladodo ◽

A. B. Rabiu

Keyword(s):

Air Temperature ◽

Land Surface ◽

Temperature Anomaly ◽

Surface Air Temperature ◽

Temporal Variations ◽

Capital City ◽

Percentage Increase ◽

Air Temperatures ◽

Spatio Temporal ◽

Air Temperature Anomaly

In this study, seventeen gridded stations across the latitude over Nigeria were selected with a view to determine and characterize land surface air temperature anomaly for both minimum and maximum values. The study intends to present graphic illustrations of spatial and temporal variations of land surface air temperature anomaly within a period 2008 – 2013. Long-term averages of minimum and maximum land surface air temperatures were obtained from National Aeronautic and Space Administration satellite meteorological dataset (1983 – 2007). Also, monthly and annual averages of land surface air temperatures were obtained from tutiempo.net to compute monthly anomaly, annual anomaly and percentage departure of minimum and maximum land surface air temperatures within a period of 2008 – 2013. The results showed that Jos had consistently experienced -10.8 and -4 percent decrease in minimum and maximum LSAT anomaly for the period under review. The implication is that Jos is getting colder than usual. The minimum LSAT anomaly declined by -2.8 percent in Lagos. Other stations across Nigeria showed a considerable percentage increase in minimum LSAT anomaly led by Yola (19.5%), Sokoto (18%) and Katsina (15.5%). Inland stations had percentage increase of minimum LSAT anomaly ranging between 5.8% and 10% except in Osogbo where the percentage increase was 1.8%. Osogbo is a less populated capital city of Osun state with active agricultural activities as heat sink. Percentage increase of minimum LSAT anomaly was not significant in Nigerian coastal areas most especially at Port Harcourt (0.5%). The spatial distribution of maximum LSAT anomaly across Nigerian latitudinal belt, unlike minimum LSAT anomaly, reduced in trend except in Lagos, Makurdi, Abuja, Bida, Minna and Kano. The minimum and maximum anomaly for maximum LSAT was observed at Jos and Makurdi respectively. There are 2 stations to be watched in terms of getting colder in the years to ahead namely Jos and Osogbo while Makurdi and Yola are gradually becoming hotspots.

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Effects of Air Temperature on Combustion Characteristics of LPG Diffusion Flame

Materials Science Forum ◽

10.4028/www.scientific.net/msf.1008.128 ◽

2020 ◽

Vol 1008 ◽

pp. 128-138

Author(s):

Ahmed M. Salman ◽

Ibrahim A. Ibrahim ◽

Hamada M. Gad ◽

Tharwat M. Farag

Keyword(s):

Air Temperature ◽

Diffusion Flame ◽

Nitrogen Addition ◽

Flame Length ◽

Combustion Characteristics ◽

Operating Conditions ◽

Low Oxygen ◽

Air Temperatures ◽

Air Stream ◽

Wide Range

In the present study, the combustion characteristics of LPG gaseous fuel diffusion flame at elevated air temperatures were experimentally investigated. An experimental test rig was manufactured to examine a wide range of operating conditions. The investigated parameters are the air temperatures of 300, 350, 400, 450, and 500 K with constant percentage of nitrogen addition in combustion air stream of 5 % to give low oxygen concentration of 18.3 % by mass at constant air swirl number, air to fuel mass ratio, and thermal load of 1.5, 30, and 23 kW, respectively. The gaseous combustion characteristics were represented as axial and radial temperatures distributions, temperatures gradient, visible flame length and species concentrations. The results indicated that as the air temperature increased, the chemical reaction rate increased and flame volume decreased, the combustion time reduced leading to a reduction in flame length. The NO concentration reaches its maximum values near the location of the maximum centerline axial temperature. Increasing the combustion air temperature by 200 K, the NO consequently O2 concentrations are increased by about % 355 and 20 % respectively, while CO2 and CO concentrations are decreased by about % 21 and 99 % respectively, at the combustor end.

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Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

The Cryosphere ◽

10.5194/tc-9-1879-2015 ◽

2015 ◽

Vol 9 (5) ◽

pp. 1879-1893 ◽

Cited By ~ 11

Author(s):

K. Atlaskina ◽

F. Berninger ◽

G. de Leeuw

Keyword(s):

Snow Cover ◽

Northern Hemisphere ◽

Air Temperature ◽

Land Surface ◽

Surface Albedo ◽

Vegetation Index ◽

Precipitation Amount ◽

Snow Cover Fraction ◽

Air Temperatures ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

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Pan-Arctic linkages between snow accumulation and growing-season air temperature, soil moisture and vegetation

Biogeosciences ◽

10.5194/bg-10-7575-2013 ◽

2013 ◽

Vol 10 (11) ◽

pp. 7575-7597 ◽

Cited By ~ 8

Author(s):

K. A. Luus ◽

Y. Gel ◽

J. C. Lin ◽

R. E. J. Kelly ◽

C. R. Duguay

Keyword(s):

Soil Moisture ◽

Air Temperature ◽

Land Surface ◽

Regional Scale ◽

Surface Characteristics ◽

Growing Season ◽

Snow Accumulation ◽

Snow Season ◽

Air Temperatures ◽

Land Surface Characteristics

Abstract. Arctic field studies have indicated that the air temperature, soil moisture and vegetation at a site influence the quantity of snow accumulated, and that snow accumulation can alter growing-season soil moisture and vegetation. Climate change is predicted to bring about warmer air temperatures, greater snow accumulation and northward movements of the shrub and tree lines. Understanding the responses of northern environments to changes in snow and growing-season land surface characteristics requires: (1) insights into the present-day linkages between snow and growing-season land surface characteristics; and (2) the ability to continue to monitor these associations over time across the vast pan-Arctic. The objective of this study was therefore to examine the pan-Arctic (north of 60° N) linkages between two temporally distinct data products created from AMSR-E satellite passive microwave observations: GlobSnow snow water equivalent (SWE), and NTSG growing-season AMSR-E Land Parameters (air temperature, soil moisture and vegetation transmissivity). Due to the complex and interconnected nature of processes determining snow and growing-season land surface characteristics, these associations were analyzed using the modern nonparametric technique of alternating conditional expectations (ACE), as this approach does not impose a predefined analytic form. Findings indicate that regions with lower vegetation transmissivity (more biomass) at the start and end of the growing season tend to accumulate less snow at the start and end of the snow season, possibly due to interception and sublimation. Warmer air temperatures at the start and end of the growing season were associated with diminished snow accumulation at the start and end of the snow season. High latitude sites with warmer mean annual growing-season temperatures tended to accumulate more snow, probably due to the greater availability of water vapor for snow season precipitation at warmer locations. Regions with drier soils preceding snow onset tended to accumulate greater quantities of snow, likely because drier soils freeze faster and more thoroughly than wetter soils. Understanding and continuing to monitor these linkages at the regional scale using the ACE approach can allow insights to be gained into the complex response of Arctic ecosystems to climate-driven shifts in air temperature, vegetation, soil moisture and snow accumulation.

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A Soil Moisture Spatial and Temporal Resolution Improving Algorithm Based on Multi-Source Remote Sensing Data and GRNN Model

Remote Sensing ◽

10.3390/rs12030455 ◽

2020 ◽

Vol 12 (3) ◽

pp. 455 ◽

Cited By ~ 5

Author(s):

Yaokui Cui ◽

Xi Chen ◽

Wentao Xiong ◽

Lian He ◽

Feng Lv ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Temporal Resolution ◽

Land Surface ◽

Regional Scale ◽

Remote Sensing Data ◽

The Tibetan Plateau ◽

Sensing Data ◽

Spatio Temporal ◽

Input Variables

Surface soil moisture (SM) plays an essential role in the water and energy balance between the land surface and the atmosphere. Low spatio-temporal resolution, about 25–40 km and 2–3 days, of the commonly used global microwave SM products limits their application at regional scales. In this study, we developed an algorithm to improve the SM spatio-temporal resolution using multi-source remote sensing data and a machine-learning model named the General Regression Neural Network (GRNN). First, six high spatial resolution input variables, including Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), albedo, Digital Elevation Model (DEM), Longitude (Lon) and Latitude (Lat), were selected and gap-filled to obtain high spatio-temporal resolution inputs. Then, the GRNN was trained at a low spatio-temporal resolution to obtain the relationship between SM and input variables. Finally, the trained GRNN was driven by the high spatio-temporal resolution input variables to obtain high spatio-temporal resolution SM. We used the Fengyun-3B (FY-3B) SM over the Tibetan Plateau (TP) to test the algorithm. The results show that the algorithm could successfully improve the spatio-temporal resolution of FY-3B SM from 0.25° and 2–3 days to 0.05° and 1-day over the TP. The improved SM is consistent with the original product in terms of both spatial distribution and temporal variation. The high spatio-temporal resolution SM allows a better understanding of the diurnal and seasonal variations of SM at the regional scale, consequently enhancing ecological and hydrological applications, especially under climate change.

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Field Measurements and Satellite Remote Sensing of Daily Soil Surface Temperature Variations in the Lower Colorado Desert of California

Climate ◽

10.3390/cli6040094 ◽

2018 ◽

Vol 6 (4) ◽

pp. 94 ◽

Cited By ~ 3

Author(s):

Dana Coppernoll-Houston ◽

Christopher Potter

Keyword(s):

Surface Temperature ◽

Air Temperature ◽

Land Surface ◽

Population Biology ◽

Soil Surface ◽

Field Measurements ◽

Ecosystem Change ◽

Colorado Desert ◽

Air Temperatures ◽

Landsat Satellite

The purpose of this study was to better understand the relationships between diurnal variations of air temperature measured hourly at the soil surface, compared with the thermal infra-red (TIR) emission properties of soil surfaces located in the Lower Colorado Desert of California, eastern Riverside County. Fifty air temperature loggers were deployed in January of 2017 on wooden stakes that were driven into the sandy or rocky desert soils at both Ford Dry Lake and the southern McCoy Mountains wash. The land surface temperature (LST) derived from Landsat satellite images was compared to measured air temperatures at 1 m and at the soil surface on 14 separate dates, until mid-September, 2017. Results showed that it is feasible to derive estimated temperatures at the soil surface from hourly air temperatures, recorded at 1 m above the surface (ambient). The study further correlated Landsat LST closely with site measurements of air and surface temperatures in these solar energy development zones of southern California, allowing inter-conversion with ground-based measurements for use in ecosystem change and animal population biology studies.

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Parental Care and the Development of Thermoregulation in Red Junglefowl

Behaviour ◽

10.1163/156853981x00103 ◽

1981 ◽

Vol 76 (3-4) ◽

pp. 250-279 ◽

Cited By ~ 23

Author(s):

D.F. Sherry

Keyword(s):

Body Temperature ◽

Air Temperature ◽

Behavioural Thermoregulation ◽

Thermal Environments ◽

Air Temperatures ◽

Red Junglefowl ◽

Wide Range ◽

In The Wild ◽

Elevated Body Temperature ◽

Brooding Behaviour

AbstractFew newly hatched birds are capable of maintaining a stable elevated body temperature at air temperatures encountered in the wild. The brooding behaviour of young red junglefowl (Gallus gallus spadiceus) and the changes in brooding that occur with the development of homeothermy were examined to determine the importance of thermal factors in parent-young contact. A fall in cooling rate and a rise in body temperature occur in junglefowl chicks in the days following hatching, and the young spend less time in contact with the hen as these changes occur. The length of brooding bouts is jointly determined by air temperature and the age of the young. Additional brooding at low air temperatures did not affect feeding by the parent or young. The general features of chick brooding persist when the hen is replaced with a model with brood patches at a temperature normal for maternal junglefowl. Brooding and huddling with other young are alternative thermoregulatory strategies. Behavioural thermoregulation by the young accounted for most features of contact between parent and young. Termination of brooding by the parent and reduction of chick heat loss by changes in parental posture may also influence brooding. Reliance on behavioural thermoregulation may permit development in a wide range of thermal environments.

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Analysis of the Spatio-Temporal Variability of Air Temperature Near the Ground Surface in the Central Baltic Area from 2005 to 2019

Atmosphere ◽

10.3390/atmos12010060 ◽

2020 ◽

Vol 12 (1) ◽

pp. 60

Author(s):

Agu Eensaar

Keyword(s):

Air Temperature ◽

Ground Surface ◽

Surface Air Temperature ◽

Entire Study ◽

Significance Level ◽

Average Surface ◽

Air Temperatures ◽

Spatio Temporal ◽

The Difference ◽

Baltic Area

In this study, we analyzed the changes in the average daily, monthly, seasonal, and annual surface air temperatures based on the temperature data obtained from seven stations (1 January 2005–31 December 2019; 15 years) belonging to the central Baltic area (Stockholm, Tallinn, Helsinki, Narva, Pärnu, Tartu, and Võru). The statistical analysis revealed that there was a strong correlation between the daily average surface air temperature of the studied cities (range: 0.95–0.99). We analyzed the frequency distribution of the average surface air temperatures in addition to the Kruskal–Wallis and Dunn’s tests (significance level of 0.05) to demonstrate that the difference in air temperatures between Narva, Tallinn, Tartu, and Stockholm are critical. The Welch’s t-test (significance level 0.05), used to study the differences in the average monthly air temperature of the cities in question, showed that the surface air temperatures in Stockholm do not differ from Tallinn air temperatures from May to August. However, the surface air temperatures of Narva were similar to those of Tallinn in September. According to our results, the trends in the changes of monthly average surface air temperatures have a certain course during the year (ranging from 1.8 °C (Stockholm) to 4.5 °C (Võru and Tartu) per decade in February). During the entire study period, in addition to February, the surface air temperature increased in all the studied cities in March, May, June, and December, and the surface air temperature did not increase in January or from July to October. During the study period, the average annual surface air temperature in the cities of the central Baltic area increased by 0.43 °C per decade. The results also confirm that the surface air temperature in the study area is changing differently in different cities. The acceleration of the surface air temperature is very alarming and requires a significant intensification of the measures taken to slow down the temperature rise.

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Ultrafast high-harmonic nanoscopy of magnetization dynamics

Nature Communications ◽

10.1038/s41467-021-26594-0 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Sergey Zayko ◽

Ofer Kfir ◽

Michael Heigl ◽

Michael Lohmann ◽

Murat Sivis ◽

...

Keyword(s):

Temporal Resolution ◽

Optical Switching ◽

Temporal Dynamics ◽

Spatial Scales ◽

High Harmonic ◽

Real Space ◽

Local Magnetization ◽

Magnetization Dynamics ◽

Wide Range ◽

Spatio Temporal

AbstractLight-induced magnetization changes, such as all-optical switching, skyrmion nucleation, and intersite spin transfer, unfold on temporal and spatial scales down to femtoseconds and nanometers, respectively. Pump-probe spectroscopy and diffraction studies indicate that spatio-temporal dynamics may drastically affect the non-equilibrium magnetic evolution. Yet, direct real-space magnetic imaging on the relevant timescales has remained challenging. Here, we demonstrate ultrafast high-harmonic nanoscopy employing circularly polarized high-harmonic radiation for real-space imaging of femtosecond magnetization dynamics. We map quenched magnetic domains and localized spin structures in Co/Pd multilayers with a sub-wavelength spatial resolution down to 16 nm, and strobosocopically trace the local magnetization dynamics with 40 fs temporal resolution. Our compact experimental setup demonstrates the highest spatio-temporal resolution of magneto-optical imaging to date. Facilitating ultrafast imaging with high sensitivity to chiral and linear dichroism, we envisage a wide range of applications spanning magnetism, phase transitions, and carrier dynamics.

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