Homogenization of the Global Radiosonde Temperature Dataset through Combined Comparison with Reanalysis Background Series and Neighboring Stations

2012 ◽  
Vol 25 (23) ◽  
pp. 8108-8131 ◽  
Author(s):  
Leopold Haimberger ◽  
Christina Tavolato ◽  
Stefan Sperka
Keyword(s):  
Time Series ◽  
Size Estimation ◽  
Climate Data ◽  
Weather Forecasts ◽  
Temperature Trends ◽  
Radiosonde Observation ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
The Cost

Abstract This article describes progress in the homogenization of global radiosonde temperatures with updated versions of the Radiosonde Observation Correction Using Reanalyses (RAOBCORE) and Radiosonde Innovation Composite Homogenization (RICH) software packages. These are automated methods to homogenize the global radiosonde temperature dataset back to 1958. The break dates are determined from analysis of time series of differences between radiosonde temperatures (obs) and background forecasts (bg) of climate data assimilation systems used for the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the ongoing interim ECMWF Re-Analysis (ERA-Interim). RAOBCORE uses the obs−bg time series also for estimating the break sizes. RICH determines the break sizes either by comparing the observations of a tested time series with observations of neighboring radiosonde time series (RICH-obs) or by comparing their background departures (RICH-τ). Consequently RAOBCORE results may be influenced by inhomogeneities in the bg, whereas break size estimation with RICH-obs is independent of the bg. The adjustment quality of RICH-obs, on the other hand, may suffer from large interpolation errors at remote stations. RICH-τ is a compromise that substantially reduces interpolation errors at the cost of slight dependence on the bg. Adjustment uncertainty is estimated by comparing the three methods and also by varying parameters in RICH. The adjusted radiosonde time series are compared with recent temperature datasets based on (Advanced) Microwave Sounding Unit [(A)MSU] radiances. The overall spatiotemporal consistency of the homogenized dataset has improved compared to earlier versions, particularly in the presatellite era. Vertical profiles of temperature trends are more consistent with satellite data as well.

scholarly journals Effect of Exclusion of Anomalous Tropical Stations on Temperature Trends from a 63-Station Radiosonde Network, and Comparison with Other Analyses

2003 ◽  
Vol 16 (13) ◽  
pp. 2288-2295 ◽  
Author(s):  
James K. Angell
Keyword(s):  
Global Changes ◽  
Station Network ◽  
Temperature Trends ◽  
A Value ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Stratospheric Cooling ◽  
The Tropics ◽  
Large Standard Error

Abstract A 63-station radiosonde network has been used for many years to estimate temperature variations and trends at the surface and in the 850–300-, 300–100-, and 100–50-mb layers of climate zones, both hemispheres, and the globe, but with little regard for the quality of individual station data. In this paper, nine tropical radiosonde stations in this network are identified as anomalous based on unrepresentatively large standard-error-of-regression values for 300–100-mb trends for the period 1958–2000. In the Tropics the exclusion of the 9 anomalous stations from the 63-station network for 1958–2000 results in a warming of the 300–100-mb layer rather than a cooling, a doubling of the warming of the 850–300-mb layer to a value of 0.13 K decade−1, and a greater warming at 850–300-mb than at the surface. The global changes in trend are smaller, but include a change to the same warming of the surface and the 850–300-mb layer during 1958–2000. The effect of the station exclusions is much less for 1979–2000, suggesting that most of the data problems are before this time. Temperature trends based on the 63-station network are compared with the Microwave Sounding Unit (MSU) and other radiosonde trends, and agreement is better after the exclusion of the anomalous stations. There is consensus that in the Tropics the troposphere has warmed slightly more than the surface during 1958–2000, but that there has been a warming of the surface relative to the troposphere during 1979–2000. Globally, the warming of the surface and the troposphere are essentially the same during 1958–2000, but during 1979–2000 the surface warms more than the troposphere. During the latter period the radiosondes indicate considerably more low-stratospheric cooling in the Tropics than does the MSU.

ASSESSMENT OF THE APPLICABILITY OF LARAWAN TECHNOLOGIES FOR THE ORGANIZATION OF A BACKUP COMMUNICATION CHANNEL FOR METEOROLOGICAL SUPPORT OF AIRFIELDS

2021 ◽  
pp. 25-31
Author(s):  
Д.К. Тунеголовец
Keyword(s):  
Communication Channel ◽  
Block Diagram ◽  
Essential Feature ◽  
Spatial And Temporal Variability ◽  
Weather Forecasts ◽  
Economic Problems ◽  
Present Information ◽  
The Cost ◽  
Positive Results

В настоящее время информация о состоянии атмосферы широко используется как при составлении прогнозов погоды, так и при решении многих экономических задач. Существенная особенность метеорологических явлений - их пространственно-временная изменчивость. Это вызывает необходимость такой организации наблюдений, которая позволит своевременно отметить возникновение явления и проследить за ходом его развития. Статистика показывает, что в период с 1997 по 2000 годы произошло порядка 193 авиационных инцидентoв, которые обусловлены недостатками метеорологического обеспечения полетов. Поэтому задача повышения качества метеорологического обеспечения является актуальной. На основе модельных и практических экспериментов показано, что беспроводной канал связи LoRaWaN способен объединить весь поток данных, поступающих с удаленных метеорологических датчиков, которые используют разные протоколы для взаимодействия друг с другом. В ходе выполнения эксперимента получены положительные результаты, доказывающие возможность организации таких каналов связи для задач метеообеспечения аэродромов. Также приводится структурная схема для организации канала связи. При этом не требуется прокладка кабельных коммуникаций связи, когда стоимость такого вида работ, включая согласование, зачастую значительно превышает стоимость самого метеорологического оборудования At present, information on the state of the atmosphere is widely used both in the preparation of weather forecasts and in solving many economic problems. An essential feature of meteorological phenomena is their spatial and temporal variability. This makes it necessary to organize observations in such a way that will allow timely noting the occurrence of the phenomenon and monitoring the progress of its development. Statistics show that in the period from 1997 to 2000 there were about 193 aviation incidents, which were caused by shortcomings in the meteorological support of flights. Therefore, the task of improving the quality of meteorological support is urgent. This article shows, based on model and practical experiments, that the LaRaWAN wireless communication channel is able to combine the entire data stream coming from remote meteorological sensors using various communication protocols among themselves. During the experiment, I obtained positive results, proving the possibility of organizing such communication channels for the tasks of meteorological support of airfields. A block diagram for the organization of a communication channel is also provided. At the same time, the laying of cable communications is not required, when the cost of this type of work, including coordination, often significantly exceeds the cost of the meteorological equipment itself

scholarly journals Temperature decadal trends, and their relation to diurnal variations in the lower thermosphere, stratosphere, and mesosphere, based on measurements from SABER on TIMED

2021 ◽  
Vol 39 (2) ◽  
pp. 327-339
Author(s):  
Frank T. Huang ◽  
Hans G. Mayr
Keyword(s):  
Local Time ◽  
Lower Thermosphere ◽  
3D Models ◽  
Diurnal Variations ◽  
Local Times ◽  
Temperature Trends ◽  
Microwave Sounding Unit ◽  
Lidar Measurements ◽  
Microwave Sounding ◽  
Thermal Tides

Abstract. We have derived the behavior of decadal temperature trends over the 24 h of local time, based on zonal averages of SABER data, for the years 2012 to 2014, from 20 to 100 km, within 48∘ of the Equator. Similar results have not been available previously. We find that the temperature trends, based on zonal mean measurements at a fixed local time, can be different from those based on measurements made at a different fixed local time. The trends can vary significantly in local time, even from hour to hour. This agrees with some findings based on nighttime lidar measurements. This knowledge is relevant because the large majority of temperature measurements, especially in the stratosphere, are made by instruments on sun-synchronous operational satellites which measure at only one or two fixed local times, for the duration of their missions. In these cases, the zonal mean trends derived from various satellite data are tied to the specific local times at which each instrument samples the data, and the trends are then also biased by the local time. Consequently, care is needed in comparing trends based on various measurements with each other, unless the data are all measured at the same local time. Similar caution is needed when comparing with models, since the zonal means from 3D models reflect averages over both longitude and the 24 h of local time. Consideration is also needed in merging data from various sources to produce generic, continuous, longer-term records. Diurnal variations of temperature themselves, in the form of thermal tides, are well known and are due to absorption of solar radiation. We find that at least part of the reason that temperature trends are different for different local times is that the amplitudes and phases of the tides themselves follow trends over the same time span of the data. Many of the past efforts have focused on the temperature values with local time when merging data from various sources and on the effect of unintended satellite orbital drifts, which result in drifting local times at which the temperatures are measured. However, the effect of local time on trends has not been well researched. We also derive estimates of trends by simulating the drift of local time due to drifting orbits. Our comparisons with results found by others (Advanced Microwave Sounding Unit, AMSU; lidar) are favorable and informative. They may explain, at least in part, the bridge between results based on daytime AMSU data and nighttime lidar measurements. However, these examples do not form a pattern, and more comparisons and study are needed.

scholarly journals Connecting the Time Series of Microwave Sounding Observations from AMSU to ATMS for Long-Term Monitoring of Climate

2014 ◽  
Vol 31 (10) ◽  
pp. 2206-2222 ◽  
Author(s):  
Xiaolei Zou ◽  
Fuzhong Weng ◽  
H. Yang
Keyword(s):  
Time Series ◽  
Atmospheric Temperature ◽  
Advanced Technology ◽  
Central Frequency ◽  
Brightness Temperatures ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Cross Calibration ◽  
Term Monitoring

Abstract The measurements from the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit-A (AMSU-A) on board NOAA polar-orbiting satellites have been extensively utilized for detecting atmospheric temperature trend during the last several decades. After the launch of the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite on 28 October 2011, MSU and AMSU-A time series will be overlapping with the Advanced Technology Microwave Sounder (ATMS) measurements. While ATMS inherited the central frequency and bandpass from most of AMSU-A sounding channels, its spatial resolution and noise features are, however, distinctly different from those of AMSU. In this study, the Backus–Gilbert method is used to optimally resample the ATMS data to AMSU-A fields of view (FOVs). The differences between the original and resampled ATMS data are demonstrated. By using the simultaneous nadir overpass (SNO) method, ATMS-resampled observations are collocated in space and time with AMSU-A data. The intersensor biases are then derived for each pair of ATMS–AMSU-A channels. It is shown that the brightness temperatures from ATMS now fall well within the AMSU data family after resampling and SNO cross calibration. Thus, the MSU–AMSU time series can be extended into future decades for more climate applications.

scholarly journals Robustness of Tropospheric Temperature Trends from MSU Channels 2 and 4

2006 ◽  
Vol 19 (17) ◽  
pp. 4234-4242 ◽  
Author(s):  
Celeste M. Johanson ◽  
Qiang Fu
Keyword(s):  
Training Dataset ◽  
Retrieval Algorithm ◽  
Tropospheric Temperature ◽  
Temperature Trends ◽  
Combining Data ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
The Mean ◽  
Stratospheric Cooling ◽  
Global Mean

Abstract Tropospheric temperature trends based on Microwave Sounding Unit (MSU) channel 2 data are susceptible to contamination from strong stratospheric cooling. Recently, Fu et al. devised a method of removing the stratospheric contamination by linearly combining data from MSU channels 2 and 4. In this study the sensitivity of the weights of the two channels in the retrieval algorithm for the tropospheric temperatures to the choice of period of record used in the analysis and to the choice of training dataset is examined. The weights derived using monthly temperature anomalies are within about 10% of those obtained by Fu et al. irrespective of the choice of analysis period or training dataset. The trend errors in the retrieved global-mean tropospheric temperatures tested using two independent radiosonde datasets are less than about 0.01 K decade−1 for all time periods of 25 yr or longer with different starting and ending years during 1958–2004. It is found that the retrievals are more robust if they are interpreted in terms of the layer-mean temperature for the entire troposphere, rather than the mean of the 850–300-hPa layer. Because large spurious jumps remain in the reanalyses, especially prior to 1979, one should be cautious when using them as training datasets and in testing the trend errors.

scholarly journals A method for merging nadir-sounding climate records, with an application to the global-mean stratospheric temperature data sets from SSU and AMSU

2015 ◽  
Vol 15 (16) ◽  
pp. 9271-9284 ◽  
Author(s):  
C. McLandress ◽  
T. G. Shepherd ◽  
A. I. Jonsson ◽  
T. von Clarmann ◽  
B. Funke
Keyword(s):  
Michelson Interferometer ◽  
Data Sets ◽  
Climate Data ◽  
Data Set ◽  
Linear Temperature ◽  
Temperature Changes ◽  
Stratospheric Temperature ◽  
Temperature Trends ◽  
Microwave Sounding ◽  
Global Mean

Abstract. A method is proposed for merging different nadir-sounding climate data records using measurements from high-resolution limb sounders to provide a transfer function between the different nadir measurements. The two nadir-sounding records need not be overlapping so long as the limb-sounding record bridges between them. The method is applied to global-mean stratospheric temperatures from the NOAA Climate Data Records based on the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit-A (AMSU), extending the SSU record forward in time to yield a continuous data set from 1979 to present, and providing a simple framework for extending the SSU record into the future using AMSU. SSU and AMSU are bridged using temperature measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is of high enough vertical resolution to accurately represent the weighting functions of both SSU and AMSU. For this application, a purely statistical approach is not viable since the different nadir channels are not sufficiently linearly independent, statistically speaking. The near-global-mean linear temperature trends for extended SSU for 1980–2012 are −0.63 ± 0.13, −0.71 ± 0.15 and −0.80 ± 0.17 K decade−1 (95 % confidence) for channels 1, 2 and 3, respectively. The extended SSU temperature changes are in good agreement with those from the Microwave Limb Sounder (MLS) on the Aura satellite, with both exhibiting a cooling trend of ~ 0.6 ± 0.3 K decade−1 in the upper stratosphere from 2004 to 2012. The extended SSU record is found to be in agreement with high-top coupled atmosphere–ocean models over the 1980–2012 period, including the continued cooling over the first decade of the 21st century.

scholarly journals Estimation of Tropospheric Temperature Trends from MSU Channels 2 and 4

2006 ◽  
Vol 23 (3) ◽  
pp. 417-423 ◽  
Author(s):  
Roy W. Spencer ◽  
John R. Christy ◽  
William D. Braswell ◽  
William B. Norris
Keyword(s):  
Radiosonde Data ◽  
Training Dataset ◽  
Tropospheric Temperature ◽  
Ancillary Data ◽  
Temperature Trends ◽  
Time Period ◽  
Microwave Sounding Unit ◽  
Target Layer ◽  
Microwave Sounding ◽  
Temperature Measure

Abstract The problems inherent in the estimation of global tropospheric temperature trends from a combination of near-nadir Microwave Sounding Unit (MSU) channel-2 and -4 data are described. The authors show that insufficient overlap between those two channels’ weighting functions prevents a physical removal of the stratospheric influence on tropospheric channel 2 from the stratospheric channel 4. Instead, correlations between stratospheric and tropospheric temperature fluctuations based upon ancillary (e.g., radiosonde) information can be used to statistically estimate a correction for the stratospheric influence on MSU 2 from MSU 4. Fu et al. developed such a regression relationship from radiosonde data using the 850–300-hPa layer as the target predictand. There are large errors in the resulting fit of the two MSU channels to the tropospheric target layer, so the correlations from the ancillary data must be relied upon to provide a statistical minimization of the resulting errors. Such relationships depend upon the accuracy of the particular training dataset as well as the dataset time period and its global representativeness (i.e., temporal and spatial stationarity of the statistics). It is concluded that near-nadir MSU channels 2 and 4 cannot be combined to provide a tropospheric temperature measure without substantial uncertainty resulting from a necessary dependence on ancillary information regarding the vertical profile of temperature variations, which are, in general, not well known on a global basis.

Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies

2015 ◽  
Vol 28 (6) ◽  
pp. 2274-2290 ◽  
Author(s):  
Stephen Po-Chedley ◽  
Tyler J. Thorsen ◽  
Qiang Fu
Keyword(s):  
Diurnal Cycle ◽  
General Circulation ◽  
Circulation Model ◽  
Tropospheric Temperature ◽  
University Of Alabama ◽  
Temperature Trends ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
The University ◽  
Diurnal Correction

Abstract Independent research teams have constructed long-term tropical time series of the temperature of the middle troposphere (TMT) using satellite Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) measurements. Despite careful efforts to homogenize the MSU/AMSU measurements, tropical TMT trends beginning in 1979 disagree by more than a factor of 3. Previous studies suggest that the discrepancy in tropical TMT trends is caused by differences in both the NOAA-9 warm target factor and diurnal drift corrections. This work introduces a new observationally based method for removing biases related to satellite diurnal drift. Over land, the derived diurnal correction is similar to a general circulation model (GCM) diurnal cycle. Over ocean, the diurnal corrections have a negligible effect on TMT trends, indicating that oceanic biases are small. It is demonstrated that this method is effective at removing biases between coorbiting satellites and biases between nodes of individual satellites. Using a homogenized TMT dataset, the ratio of tropical tropospheric temperature trends relative to surface temperature trends is in accord with the ratio from GCMs. It is shown that bias corrections for diurnal drift based on a GCM produce tropical trends very similar to those from the observationally based correction, with a trend difference smaller than 0.02 K decade−1. Differences between various TMT datasets are explored further. Large differences in tropical TMT trends between this work and that of the University of Alabama in Huntsville (UAH) are attributed to differences in the treatment of the NOAA-9 target factor and the diurnal cycle correction.

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