A New Upper Air Data System—The Transosonde

1956 ◽  
Vol 37 (7) ◽  
pp. 342-350 ◽  
Author(s):  
Albert D. Anderson ◽  
Henry J. Mastenbrook

A new concept of upper-air data collection utilizes instrumented balloons controlled to float along given constant-pressure surfaces in the atmosphere. A system of instrumentation, named the transosonde (trans-oceanic-sonde) has been developed for implementing this concept. Field tests have established the technical and meteorological feasibility of the system. In the course of the tests, transosonde balloons were tracked over distances of thousands of miles using a network of shore-based high-frequency radio-direction-finder stations. Emphasis has been placed upon the trajectory of the balloon as the primary source of meteorological data. Wind velocities and accelerations can be derived directly from constant-pressure surface trajectories, providing valuable synoptic and research data. Balloon trajectories in passing through major troughs and ridges define these features, giving information of importance for synoptic analysis and long-range forecasting. In addition, a sequence of trajectories provides a measure of the acceleration and deceleration of these entities. The transosonde system has additional data-gathering potentials for temperature, lapse rate, wind shear and other parameters. It is concluded that the system can be employed over those regions of the globe where upper-air data are lacking at a cost competitive with present-day systems.

2013 ◽  
Vol 54 (63) ◽  
pp. 311-321 ◽  
Author(s):  
Martin Heynen ◽  
Francesca Pellicciotti ◽  
Marco Carenzo

AbstractWe investigate the sensitivity of a distributed enhanced temperature-index (ETI) melt model, in order to understand which parameters have the largest influence on model outputs and thus need to be accurately known. We use melt and meteorological data from two Alpine glaciers and one glacier in the Andes of Chile. Sensitivity analysis is conducted in a systematic way in terms of parameters and the different conditions (day, night, clear-sky, overcast), melt seasons and glaciers examined. The sensitivity of total melt to changes in individual parameters is calculated using a local method around the optimal value of the parameters. We verify that the parameters are optimal at the distributed scale and assess the model uncertainty induced by uncertainty in the parameters using a Monte Carlo technique. Model sensitivity to parameters is consistent across melt seasons, glaciers, different conditions and the daily statistics examined. The parameters to which the model is most sensitive are the shortwave-radiation factor, the temperature lapse rate for extrapolation of air temperature, the albedo parameters, the temperature threshold and the cloud transmittance factor parameters. A parameter uncertainty of 5% results in a model uncertainty of 5.6% of mean melt on Haut Glacier d’Arolla, Switzerland.


FLORESTA ◽  
2011 ◽  
Vol 41 (3) ◽  
Author(s):  
Christopher Thomas Blum ◽  
Carlos Vellozo Roderjan ◽  
Franklin Galvão

O estudo teve como objetivo caracterizar aspectos climáticos, com enfoque na temperatura e umidade relativa do ar e sua influência sobre a distribuição da vegetação numa encosta da Serra da Prata, Morretes, Paraná, coberta pelas formações Submontana e Montana da Floresta Ombrófila Densa. Entre julho de 2009 e junho de 2010 foram obtidos dados meteorológicos, aos 400 e 1.000 m s.n.m. As temperaturas médias no período foram 19,0 ºC (400 m) e 16,3 ºC (1.000 m). A taxa de redução térmica com a elevação altitudinal foi 0,44 ºC/100 m. Detectou-se uma região de transição climática em torno dos 700 m de altitude, com o clima Cfb acima e o Cfa abaixo. A isoterma da temperatura média de 13 ºC no mês mais frio, estimada para a região dos 800 m s.n.m., coincide com o limite inferior de ocorrência da formação Montana, denotando a influência das baixas temperaturas na diferenciação da vegetação. As médias de umidade relativa do ar foram elevadas, devido ao constante aporte das massas de ar úmido oriundas do oceano. As médias das amplitudes diárias de temperatura e umidade foram muito semelhantes para as duas altitudes, demonstrando que a variação altitudinal parece não exercer influência sobre suas variações diárias na encosta estudada.Palavras-chave:  Gradiente altitudinal; Serra do Mar; Floresta Atlântica; temperatura; umidade relativa do ar. AbstractClimate and his influence over the Atlantic Dense Rainforest distribution in the Prata Mountain Range, Morretes, Paraná, South Brazil. This study aimed to characterize climatic aspects, focusing air temperature and relative humidity, as well as its influence to vegetation distribution in a slope of Prata Mountain Range, Morretes, Paraná, covered by Submontane and Montane formations of the Atlantic Rainforest. Between July of 2009 and June of 2010 meteorological data was collected, at 400 and 1,000 m a.s.l. The average temperature along this period was 19.0 ºC (400 m) and 16.3 ºC (1,000 m). The temperature lapse rate was 0.44 ºC/100 m. It was detected a climatic transition region at about 700 m a.s.l., with the Cfb type above, and the Cfa type below. The isotherm of the average temperature of 13 ºC in the coldest month, estimated for the region of about 800 m a.s.l., agrees with the inferior limit of the Montane formation, denoting influence of low temperatures in the vegetation distinction. The air relative humidity average was high, because the regular arrival of moist air masses from the ocean. The average of daily amplitude of temperature and relative humidity were very similar for both studied altitudes, denoting not apparent influence of the altitudinal variation to the daily variation of these climatic variables in the slope.Keywords:              Altitudinal gradient; Serra do Mar; Atlantic Ombrophilous Dense Forest; temperature; air relative humidity.


2013 ◽  
Vol 8 (3) ◽  
pp. 297-305

In order to accurately predict the pollutant concentrations and the plume trajectory in the atmosphere, it is necessary to take into account the effects of interactions between the plume and the surrounding environment. In fact, the atmospheric conditions have a lot of influence on the plume behavior. Earlier models were based on statistical approach. However, this approach presents many shortcomings, in that way they are unable to take directly into account some atmospheric properties such as the moisture of the air. A complete model is the one that solves the entire set of momentum equation completed by energy and species equations. A number of approximate predictive methods for the plume flow in stratified surroundings have been developed in the literature such as Abraham (1965), Schwartz and Tulin (1972), Sneck and Brown (1974), Wright (1984) and Hwang and Chiang (1986). In this work, we use the lagrangian concept based on the so-called projected area entrainment in its latest formulation (Lee and Cheung 1990) to predict the effect of relative humidity on the plume behavior. Input-required data include source parameters such as the gas exhaust conditions (temperature release, exit velocity, mixing ratios), physical dimensions (diameter and height of stack) and meteorological data. In the present work, only idealized meteorological conditions which neglect the vertical variation of the wind speed, the temperature lapse rate and the relative humidity are considered. The output of the model gives an idea on characteristics parameters of the plume such as its trajectory, its temperature and mixing ratio distribution and its length of visibility. The model validation is accomplished through a comparison of the computed plume maximum height with results obtained using empirical formulas (Hanna, 1972). Also, the calculated plume visibility length is confronted to the ADMS results obtained by Carruthers et al. (2000). The effect of relative humidity is then investigated.


2021 ◽  
Author(s):  
Siebren de Haan ◽  
Paul M. A. de Jong ◽  
Jitze van der Meulen

Abstract. Some aircraft temperature observations, retrieved through the Aircraft Meteorological Data Relay (AMDAR), suffer from a significant warm bias when comparing observations with numerical weather prediction (NWP) model. In this manuscript we show that this warm bias of AMDAR temperature can be characterized and consequently reduced substantially. The characterization of this warm bias is based on the methodology of measuring temperature with a moving sensor and can be split into two separate processes. The first process depends on the flight phase of the aircraft and relates to difference of timing, as it appears that the time of measurement of altitude and temperature differ. When an aircraft is ascending or descending this will result in small bias in temperature due to the (on average) presence of an atmospheric temperature lapse rate. The second process is related to internal corrections applied to pressure altitude without feedback to temperature observation measurement. Based on NWP model temperature data combined with additional information on Mach number and true airspeed, we were able to estimate corrections using an 18 months period from January 2017 to July 2018. Next, the corrections were applied on AMDAR observations over the period from September 2018 to mid-December 2019. Comparing these corrected temperatures with (independent) radiosonde temperature observations demonstrates a reduction of the temperature bias from 0.5 K to around zero and reduction of standard deviation of almost 10 %.


2009 ◽  
Vol 48 (9) ◽  
pp. 1790-1802 ◽  
Author(s):  
David P. Duda ◽  
Patrick Minnis

Abstract A probabilistic forecast to accurately predict contrail formation over the conterminous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and the Rapid Update Cycle (RUC) combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The most common predictors selected for the SURFACE models tend to be related to temperature, relative humidity, and wind direction when the models are generated using RUC or ARPS analyses. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The most common predictors for the OUTBREAK models tend to be wind direction, atmospheric lapse rate, temperature, relative humidity, and the product of temperature and humidity.


2012 ◽  
Vol 12 (12) ◽  
pp. 5309-5318 ◽  
Author(s):  
R. Biondi ◽  
W. J. Randel ◽  
S.-P. Ho ◽  
T. Neubert ◽  
S. Syndergaard

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.


2018 ◽  
Vol 10 (10) ◽  
pp. 1617 ◽  
Author(s):  
Yun Qin ◽  
Guoyu Ren ◽  
Tianlin Zhai ◽  
Panfeng Zhang ◽  
Kangmin Wen

Land surface temperature (LST) is an important parameter in the study of the physical processes of land surface. Understanding the surface temperature lapse rate (TLR) can help to reveal the characteristics of mountainous climates and regional climate change. A methodology was developed to calculate and analyze land-surface TLR in China based on grid datasets of MODIS LST and digital elevation model (DEM), with a formula derived on the basis of the analysis of the temperature field and the height field, an image enhancement technique used to calculate gradient, and the fuzzy c-means (FCM) clustering applied to identify the seasonal pattern of the TLR. The results of the analysis through the methodology showed that surface temperature vertical gradient inversion widely occurred in Northeast, Northwest, and North China in winter, especially in the Xinjiang Autonomous Region, the northern and the western parts of the Greater Khingan Mountains, the Lesser Khingan Mountains, and the northern area of Northwest and North China. Summer generally witnessed the steepest TLR among the four seasons. The eastern Tibetan Plateau showed a distinctive seasonal pattern, where the steepest TLR happened in winter and spring, with a shallower TLR in summer. Large seasonal variations of TLR could be seen in Northeast China, where there was a steep TLR in spring and summer and a strong surface temperature vertical gradient inversion in winter. The smallest seasonal variation of TLR happened in Central and Southwest China, especially in the Ta-pa Mountains and the Qinling Mountains. The TLR at very high altitudes (>5 km) was usually steeper than at low altitudes, in all months of the year.


Sign in / Sign up

Export Citation Format

Share Document