scholarly journals Modeling Seasonal Changes in the Temperature Lapse Rate in a Northern Thailand Mountainous Area

2010 ◽  
Vol 49 (6) ◽  
pp. 1233-1246 ◽  
Author(s):  
Hikaru Komatsu ◽  
Hirofumi Hashimoto ◽  
Tomonori Kume ◽  
Nobuaki Tanaka ◽  
Natsuko Yoshifuji ◽  
...  
Keyword(s):  
Seasonal Changes ◽  
Temperature Data ◽  
Base Stations ◽  
Lapse Rate ◽  
Mountain Forest ◽  
Chiang Mai ◽  
Northern Thailand ◽  
Temperature Lapse Rate ◽  
Regional Circulation ◽  
The Difference

Abstract Temperature data in the mountain forest regions are often extrapolated from temperature data recorded at base stations at lower elevation. Such extrapolation is often based on elevation differences between target regions and base stations at low elevation assuming a constant temperature lapse rate throughout the year. However, this assumption might be problematic where slope circulation is active and decoupled from the regional circulation. To model the seasonal change in the lapse rate, the authors compared daily maximum (Tmax) and minimum temperatures (Tmin) observed at a mountain forest site (Kog–Ma; 1300-m altitude) with those observed at the bottom of the basin (Chiang–Mai; 314-m altitude) in northern Thailand, where slope circulation is active and decoupled from the regional circulation. The difference in Tmax between Kog–Ma and Chiang–Mai (ΔTmax; Kog–Ma minus Chiang–Mai) was relatively unchanged throughout the year. However, the difference in Tmin between Kog–Ma and Chiang–Mai (ΔTmin) changed seasonally. Thus, assuming a constant lapse rate throughout the year could cause large errors in extrapolating Tmin data in mountainous areas in northern Thailand. The difference ΔTmin was related to nighttime net radiation (Rn), suggesting that nocturnal drainage flow affects the determination of ΔTmin. This relationship would be useful in formulating seasonal changes in the lapse rate for Tmin. As Rn data are generally unavailable for meteorological stations, an index that relates to the lapse rate for Tmin and is calculated from Tmax and Tmin data is proposed. This index might be useful for accurately estimating Tmin values in mountainous regions in northern Thailand.

Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (2) ◽  
pp. 38
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Prashant Baral ◽  
Niraj Shankar Pradhananga
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann-Kendall test was employed to test the statistical significance of detected trends. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 °C year−1 to 0.035 °C year−1 with a mean increasing trend of 0.03 °C year−1 after 1971. Seasonal trends show highest warming trends in the monsoon season followed by winter, pre-monsoon, and the post-monsoon season. However, difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 °C m−1 with the steepest value (−0.0064 °C m−1) in pre-monsoon season and least negative (−0.0052 °C m−1) in winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate datasets shows reasonable correlation thus confirming the suitability of the gap filling methods.

A new approach for modeling near surface temperature lapse rate based on normalized land surface temperature data

2020 ◽  
Vol 242 ◽  
pp. 111746 ◽  
Author(s):  
Mohammad Karimi Firozjaei ◽  
Solmaz Fathololoumi ◽  
Seyed Kazem Alavipanah ◽  
Majid Kiavarz ◽  
Ali Reza Vaezi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temperature Data ◽  
Lapse Rate ◽  
Near Surface ◽  
New Approach ◽  
Temperature Lapse Rate ◽  
Surface Temperature Data

scholarly journals Comparison and Calculation of Different Atmospheric Delay Models Using Atmospheric Parameters of VLBI Stations of China

1993 ◽  
Vol 156 ◽  
pp. 212-212
Author(s):  
Zhigen Yang
Keyword(s):  
Elevation Angle ◽  
Mapping Function ◽  
Physical Models ◽  
Lapse Rate ◽  
Tropospheric Temperature ◽  
Atmospheric Parameters ◽  
Temperature Lapse Rate ◽  
Atmospheric Delay ◽  
Vlbi Observations ◽  
The Difference

The values of the atmospheric time delay for the “Chao”, “Marini” and “CfA−2.2” mapping function are calculated by using the atmospheric parameters in summer and winter at Shanghai, Kunming and Urumqi station respectively. A comparison among these values shows that the derivations of “Marini” from “Chao” and “CfA” are relatively large. On the other hand, the difference of values between the “Chao” and the “CfA” in the case of ∊ = 40° ∼ 10°, which is the average for the three stations, is from +1 mm to +47 mm for the “wet” part of the delay in summer, while is from −2 mm to −28 mm for the “dry” part in winter. For the case of low elevation angle ɛ ≐ 5°, the difference for the “wet” part can be about 400 mm in summer. Therefore, it is indispensable to make a further comparison between “Chao” and “CfA” mapping function by using the data of VLBI observations, in order to make a better revision to the adopted models of atmospheric delay.The monthly averages of the height of tropopause ht and the tropospheric temperature lapse rate βt for the three stations mentioned above are used to calculate the dry atmospheric delay by the “CfA” mapping function. The results show that the amplitudes of the annual changing of delay dτa, which is caused by ht and βt for the case of ∊ = 20° ∼ 10° at Urumqi station, are about 1 ∼ 5 mm and 2 ∼ 15 mm respectively. Therefore, taking the parameters of ht and βt of the stations into account in “CfA” model, instead of using fixed constants, would be much favourable for the requirements of 1 ps precision of VLBI physical models.

Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (2) ◽  
pp. 49
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Niraj Shankar Pradhananga ◽  
Prashant Baral
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann-Kendall test was employed to test the statistical significance of detected trends. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 ∘C year−1 to 0.035 ∘C year−1 with a mean increasing trend of 0.03 ∘C year−1 after 1971. Seasonal trends show highest warming trends in the monsoon season followed by winter, pre-monsoon, and the post-monsoon season. However, difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 ∘C m−1 with the steepest value (−0.0064 ∘C m−1) in pre-monsoon season and least negative (−0.0052 ∘C m−1) in winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate datasets show reasonable correlation thus confirming the suitability of the gap filling methods.

Spatial and temporal variation of surface air temperature at different altitude zone in recent 30 years over Nepal

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 417-428
Author(s):  
JANAK LAL NAYAVA ◽  
SUNIL ADHIKARY ◽  
OM RATNA BAJRACHARYA
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature Data ◽  
Lapse Rate ◽  
Spatial And Temporal Variation ◽  
Mountain Regions ◽  
Temperature Lapse Rate ◽  
Air Temperatures ◽  
Long Term Trend

This paper investigates long term (30 yrs) altitudinal variations of surface air temperatures based on air temperature data of countrywide scattered 22 stations (15 synoptic and 7 climate stations) in Nepal. Several researchers have reported that rate of air temperature rise (long term trend of atmospheric warming) in Nepal is highest in the Himalayan region (~ 3500 m asl or higher) compared to the Hills and Terai regions. Contrary to the results of previous researchers, however this study found that the increment of annual mean temperature is much higher in the Hills (1000 to 2000 m asl) than in the Terai and Mountain Regions. The temperature lapse rate in a wide altitudinal range of Nepal (70 to 5050 m asl) is -5.65 °C km-1. Warming rates in Terai and Trans-Himalayas (Jomsom) are 0.024 and 0.029 °C/year respectively.  

scholarly journals Trend Analysis of Temperature Data for the Narayani River Basin, Nepal

Sci ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Niraj Shankar Pradhananga ◽  
Prashant Baral
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

The study of spatiotemporal variation in temperature is vital to assess changes in climate, especially in the Himalayan region, where the livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in the Narayani River basin, a major river basin of Nepal, characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann–Kendall test was employed to test the statistical significance of detected trends. The results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 to 0.035 °C year−1 with a mean increasing trend of 0.03 °C year−1 after 1971. Seasonal trends show the highest warming trends in the monsoon season, followed by winter and the premonsoon and postmonsoon season. However, the difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 °C m−1 with the steepest value (−0.0064 °C m−1) in the premonsoon season and the least negative (−0.0052 °C m−1) in the winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate dataset show reasonable correlation, thus confirming the suitability of the gap filling methods.

Forensic and phylogeographic characterization of mtDNA lineages from northern Thailand (Chiang Mai)

2009 ◽  
Vol 123 (6) ◽  
pp. 495-501 ◽  
Author(s):  
Bettina Zimmermann ◽  
Martin Bodner ◽  
Sylvain Amory ◽  
Liane Fendt ◽  
Alexander Röck ◽  
...  
Keyword(s):  
Chiang Mai ◽  
Northern Thailand ◽  
Mtdna Lineages

scholarly journals A25 Collections of adult black flies attracted to human and to buffalo in Chiang Mai, northern Thailand

2002 ◽  
Vol 53 (Supplement) ◽  
pp. 42
Author(s):  
H. Takaoka ◽  
C. Aoki ◽  
M. Fukuda ◽  
C. Wej ◽  
J. Atchariya
Keyword(s):  
Black Flies ◽  
Chiang Mai ◽  
Northern Thailand

scholarly journals Thermal structure of intense convective clouds derived from GPS radio occultations

2012 ◽  
Vol 12 (12) ◽  
pp. 5309-5318 ◽  
Author(s):  
R. Biondi ◽  
W. J. Randel ◽  
S.-P. Ho ◽  
T. Neubert ◽  
S. Syndergaard
Keyword(s):  
Thermal Structure ◽  
Deep Convection ◽  
Lapse Rate ◽  
Orthogonal Polarization ◽  
Cold Temperatures ◽  
Temperature Lapse Rate ◽  
Convective Systems ◽  
Convective Clouds ◽  
Strong Inversion ◽  
Cloud Tops

Abstract. Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS occultations with CALIPSO profiles over deep convection. Results show a sharp spike in GPS bending angle highly correlated to the top of the clouds, corresponding to anomalously cold temperatures within the clouds. Above the clouds the temperatures return to background conditions, and there is a strong inversion at cloud top. For cloud tops below 14 km, the temperature lapse rate within the cloud often approaches a moist adiabat, consistent with rapid undiluted ascent within the convective systems.

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