Investigation of the atmospheric water-vapor content in Crimea via long-term photometric solar observations

2013 ◽  
Vol 109 (1) ◽  
pp. 80-85 ◽  
Author(s):  
E. I. Terez ◽  
G. A. Terez ◽  
A. V. Kozak ◽  
S. V. Kuz’min
2020 ◽  
Author(s):  
Hongru Yan ◽  
Jianping Huang ◽  
Yongli He ◽  
Yuzhi Liu ◽  
Tianhe Wang ◽  
...  

Author(s):  
Анжелика Андреевна Косторная ◽  
Алексей Николаевич Рублев ◽  
Владимир Викторович Голомолзин

Представлена методика определения интегрального влагосодержания в безоблачной атмосфере над океанскими и морскими акваториями по измерениям микроволнового радиометра МТВЗА-ГЯ, устанавливаемого на российских гидрометеорологических спутниках серии “Метеор-М”. Определение влагосодержания осуществляется с помощью регрессий, предикторами которых являются измеренные интенсивности излучения в выбранных каналах радиометра. В их число могут входить каналы с рабочими спектральными диапазонами внутри и вне полос поглощения водяного пара. Адаптивный поиск оптимального набора каналов для различных районов земного шара проводится в зависимости от типа поверхности и климатической зоны. Критерием выбора каналов и вида регрессии является минимальная среднеквадратичная невязка получаемых оценок влагосодержания атмосферы с контрольными значениями, рассчитанными по данным реанализа Национального центра экологического прогнозирования (NCEP) и специальных атмосферных моделей, разработанных в Европейском центре среднесрочных прогнозов погоды (ECMWF) The determination of the total atmospheric water vapor content over the cloudless ocean using the MTVZA-GY measurements in microwave range is described. The microwave scanning radiometer MTVZA-GY is located on the Russian meteorological satellites “Meteor-M” and outgoing radiation of the surface-atmosphere system is measured in 29 channels. To calculate the integrated water vapor, the adaptive searching of the optimal set of channels using regression analysis was proposed. Frequencies that are not related to water-vapor absorption lines are used as predictors. The minimum of total approximation error was obtained for selected channels and corresponding regression coefficients values. The quality control of retrieval integrated water vapor (kg/m) was conducted with the help of the set of atmospheric profiles obtained by M. Matricardi and NCEP/NCAR Reanalysis as a priori data using the proposed method. Standard deviations (RMS) obtained by determined adaptive search for the predictors are about 3 kg/m2. Application of the method for cloudless water areas allowed finding a set of 6 channels MTVZA GY (18.7H, 23.8V, 23.8H, 57+0.32+0.025H, 57+0.32+0.01H и 183+1.4V) for which the RMS values are minimal - 4.4 kg/m. The use of all channels of the device in the search allows reducing the error in determining the integrated water vapor content. The proposed method for recovering the content of water vapor from measurements in the channels of the MTVZA-GYa device allows an adaptive search for an optimal set of channels for different regions of the globe and find the best combinations for various climatic zones and surface types


2009 ◽  
Vol 9 (22) ◽  
pp. 8987-8999 ◽  
Author(s):  
R. Sussmann ◽  
T. Borsdorff ◽  
M. Rettinger ◽  
C. Camy-Peyret ◽  
P. Demoulin ◽  
...  

Abstract. We present a method for harmonized retrieval of integrated water vapor (IWV) from existing, long-term, measurement records at the ground-based mid-infrared solar FTIR spectrometry stations of the Network for the Detection of Atmospheric Composition Change (NDACC). Correlation of IWV from FTIR with radiosondes shows an ideal slope of 1.00(3). This optimum matching is achieved via tuning one FTIR retrieval parameter, i.e., the strength of a Tikhonov regularization constraining the derivative (with respect to height) of retrieved water profiles given in per cent difference relative to an a priori profile. All other FTIR-sonde correlation parameters (intercept=0.02(12) mm, bias=0.02(5) mm, standard deviation of coincident IWV differences (stdv)=0.27 mm, R=0.99) are comparable to or better than results for all other ground-based IWV sounding techniques given in the literature. An FTIR-FTIR side-by-side intercomparison reveals a strong exponential increase in stdv as a function of increasing temporal mismatch starting at Δt≈1 min. This is due to atmospheric water vapor variability. Based on this result we derive an upper limit for the precision of the FTIR IWV retrieval for the smallest Δt(=3.75 min) still giving a statistically sufficient sample (32 coincidences), i.e., precision(IWVFTIR)<0.05 mm (or 2.2% of the mean IWV). The bias of the IWV retrievals from the two different FTIR instruments is nearly negligible (0.02(1) mm). The optimized FTIR IWV retrieval is set up in the standard NDACC algorithm SFIT 2 without changes to the code. A concept for harmonized transfer of the retrieval between different stations deals with all relevant control parameters; it includes correction for differing spectral point spacings (via regularization strength), and final quality selection of the retrievals (excluding the highest residuals (measurement minus model), 5% of the total). As first application examples long-term IWV data sets are retrieved from the FTIR records of the Zugspitze (47.4° N, 11.0° E, 2964 m a.s.l.) and Jungfraujoch (46.5° N, 8.0° E, 3580 m a.s.l.) NDACC sites. Station-trend analysis comprises a linear fit after subtracting an intra-annual model (3 Fourier components) and constructing an uncertainty interval [95% confidence] via bootstrap resampling. For the Zugspitze a significant trend of 0.79 [0.65, 0.92] mm/decade is found for the time interval [1996–2008], whereas for the Jungfraujoch no significant trend is found. This confirms recent findings that strong variations of IWV trends do occur above land on the local to regional scale (≈250 km) in spite of homogeneous surface temperature trends. This paper provides a basis for future exploitation of more than a dozen existing, multi-decadal FTIR measurement records around the globe for climate studies.


1998 ◽  
Vol 37 (21) ◽  
pp. 4678 ◽  
Author(s):  
Victoria E. Cachorro ◽  
Pilar Utrillas ◽  
Ricardo Vergaz ◽  
Plinio Durán ◽  
Angel M. de Frutos ◽  
...  

2020 ◽  
Vol 125 (23) ◽  
Author(s):  
Hongru Yan ◽  
Jianping Huang ◽  
Yongli He ◽  
Yuzhi Liu ◽  
Tianhe Wang ◽  
...  

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