scholarly journals Estimating One-Minute Rain Rate Distributions in the Tropics From TRMM Satellite Data (October 2017)

2018 ◽  
Vol 11 (10) ◽  
pp. 3660-3667
Author(s):  
Geraldine Rangmoen Rimven ◽  
Kevin S. Paulson ◽  
Timothy Bellerby
Keyword(s):  
Satellite Data ◽  
Rain Rate ◽  
The Tropics

scholarly journals Global and long-term comparison of SCIAMACHY limb ozone profiles with correlative satellite data (2002–2008)

2011 ◽  
Vol 4 (4) ◽  
pp. 4867-4910
Author(s):  
S. Mieruch ◽  
M. Weber ◽  
C. von Savigny ◽  
A. Rozanov ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Satellite Data ◽  
Convective Cloud ◽  
Residual Effects ◽  
Statistical Hypothesis ◽  
Systematic Bias ◽  
Statistical Hypothesis Testing ◽  
Trend Model ◽  
The Tropics ◽  
Linear Trends

Abstract. SCIAMACHY limb scatter ozone profiles from 2002 to 2008 have been compared with MLS (2005–2008), SABER (2002–2008), SAGE II (2002–2005), HALOE (2002–2005) and ACE-FTS (2004–2008) measurements. The comparison is performed for global zonal averages and heights from 10 to 50 km in one km steps. The validation was performed by comparing monthly mean zonal means and by comparing averages over collocated profiles within a zonal band and month. Both approaches yield similar results. For most of the stratosphere SCIAMACHY agrees to within 10 % or better with other correlative data. A systematic bias of SCIAMACHY ozone of up to 100 % between 10 and 20 km in the tropics points to some remaining issues with regard to convective cloud interference. Statistical hypothesis testing reveals at which altitudes and in which region differences between SCIAMACHY and other satellite data are statistically significant. We also estimated linear trends from monthly mean data for different periods where SCIAMACHY has common observations with other satellite data using a classical trend model with QBO and seasonal terms in order to draw conclusions on potential instrumental drifts as a function of latitude and altitude. SCIAMACHY exhibits a statistically significant negative trend in the range of of about 1–3 % per year depending on latitude during the period 2002–2005 (overlapping with HALOE and SAGE II) and somewhat less during 2002–2008 (overlapping with SABER) in the altitude range of 30–40 km, while in the period 2004–2008 (overlapping with MLS and ACE-FTS) no significant trends are observed. The statistically significant negative trends only observed with SCIAMACHY data point at some residual effects from errors in the tangent height registration.

scholarly journals Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

2015 ◽  
Vol 8 (9) ◽  
pp. 3685-3699 ◽  
Author(s):  
A. Chandra ◽  
C. Zhang ◽  
P. Kollias ◽  
S. Matrosov ◽  
W. Szyrmer
Keyword(s):  
Rain Rate ◽  
Tropical Indian Ocean ◽  
Rain Gauge ◽  
Signal Attenuation ◽  
Ka Band ◽  
Automated Algorithm ◽  
Atmospheric Radiation Measurement ◽  
Microphysical Processes ◽  
The Tropics ◽  
Rain Rates

Abstract. The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong signal attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-band (35-GHz) ARM (Atmospheric Radiation Measurement) zenith radars (KAZR). A 1-dimensional, simple, steady state microphysical model is used to estimate impacts of microphysical processes and attenuation on the profiles of radar observables at 35-GHz and thus provide criteria for identifying situations when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for signal saturation and wet radome effects. The algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity–rain rate (Ze–R) relation. Observations collected by the KAZR, rain gauge, disdrometer and scanning precipitating radars during the DYNAMO/AMIE field campaign at the Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The differences in the rain accumulation from the proposed algorithm are quantified. The results indicate that the proposed algorithm has a potential for deriving continuous rain rate statistics in the tropics.

scholarly journals The use of QBO, ENSO, and NAO perturbations in the evaluation of GOME-2 MetOp A total ozone measurements

2019 ◽  
Vol 12 (2) ◽  
pp. 987-1011
Author(s):  
Kostas Eleftheratos ◽  
Christos S. Zerefos ◽  
Dimitris S. Balis ◽  
Maria-Elissavet Koukouli ◽  
John Kapsomenakis ◽  
...  
Keyword(s):  
Satellite Data ◽  
Total Ozone ◽  
Southern Oscillation ◽  
Model Calculations ◽  
Ozone Data ◽  
Ozone Monitoring ◽  
Mean Differences ◽  
The Tropics ◽  
The Impact

Abstract. In this work we present evidence that quasi-cyclical perturbations in total ozone (quasi-biennial oscillation – QBO, El Niño–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite total ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A total ozone with ground observations shows mean differences of about -0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A total ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of total ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB total ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A total ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on total ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced total ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.

scholarly journals Analysis of HCl and ClO time series in the upper stratosphere using satellite data sets

2011 ◽  
Vol 11 (11) ◽  
pp. 5321-5333 ◽  
Author(s):  
A. Jones ◽  
J. Urban ◽  
D. P. Murtagh ◽  
C. Sanchez ◽  
K. A. Walker ◽  
...  
Keyword(s):  
Time Series ◽  
Satellite Data ◽  
Atmospheric Chemistry ◽  
Linear Trend ◽  
Montreal Protocol ◽  
Data Sets ◽  
Sigma Level ◽  
Chlorine Monoxide ◽  
Significant Downward Trend ◽  
The Tropics

Abstract. Previous analyses of satellite and ground-based measurements of hydrogen chloride (HCl) and chlorine monoxide (ClO) have suggested that total inorganic chlorine in the upper stratosphere is on the decline. We create HCl and ClO time series using satellite data sets extended to November 2008, so that an update can be made on the long term evolution of these two species. We use the HALogen Occultation Experiment (HALOE) and the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) data for the HCl analysis, and the Odin Sub-Millimetre Radiometer (SMR) and the Aura Microwave Limb Sounder (Aura-MLS) measurements for the study of ClO. Altitudes between 35 and 45 km and two mid-latitude bands: 30° S–50° S and 30° N–50° N, for HCl, and 20° S–20° N for ClO and HCl are studied. ACE-FTS and HALOE HCl anomaly time series (with QBO and seasonal contributions removed) are combined to produce all instrument average time series, which show HCl to be reducing from peak 1997 values at a linear estimated rate of −5.1 % decade−1 in the Northern Hemisphere and −5.2 % decade−1 in the Southern Hemisphere, while the tropics show a linear trend of −5.8 % per decade (although we do not remove the QBO contribution there due to sparse data). Trend values are significantly different from a zero trend at the 2 sigma level. ClO is decreasing in the tropics by −7.1 % ± 7.8 % decade−1 based on measurements made from December 2001 to November 2008. The statistically significant downward trend found in HCl after 1997 and the apparent downward ClO trend since 2001 (although not statistically significant) confirm how effective the 1987 Montreal protocol objectives and its amendments have been in reducing the total amount of inorganic chlorine.

scholarly journals Monitoring Land Cover Changes in the Tropics using Satellite Remote Sensing Data

2019 ◽  
Vol 8 (12) ◽  
pp. 3631-3636
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Change Detection ◽  
Land Cover Change ◽  
Satellite Data ◽  
Land Cover Changes ◽  
Classification Methods ◽  
Land Covers ◽  
The Tropics ◽  
Land Cover Change Detection

Changes in land cover are inevitable phenomena that occur in all parts of the world. Land cover changes can occur due to natural phenomena that include runoff, soil erosion and sedimentation besides man-made phenomena that include deforestation, urbanization and conversion of land covers to suit human needs. Several works on change detection have been carried out elsewhere, however there were lack of effort in analyzing the issues that affect the performance of existing change detection techniques. The study presented in this paper aims to detect changes of land covers by using remote sensing satellite data. The study involves detection of land cover changes using remote sensing techniques. This makes use satellite data taken at different times over a particular area of interest. The data has resolution of 30 m and records surface reflectance at approximately 0.4 to 0.7 micrometers wavelengths. The study area is located in Selangor, Malaysia and occupied with tropical land covers including coastal swamp water, sediment plumes, urban, industry, water, bare land, cleared land, oil palm, rubber and coconut. Initially, region of interests (ROI) were drawn on each of the land covers in order to extract the training pixels. Landsat satellite bands 1, 2, 3, 4, 5 and 7 were then used as the input for the three supervised classification methods namely Support Vector Machine (SVM), Maximum Likelihood (ML) and Neural Network (NN). Different sizes of training pixels were used as the input for the classification methods so that the performance can be better understood. The accuracy of the classifications was then assessed by analyzing the classifications with a set of reference pixels using a confusion matrix. The classification methods were then used to identify the conversion of land cover from year 2000 to 2005 within the study area. The outcomes of the land cover change detection were reported in terms quantitative and qualitative analyses. The study shows that SVM gives a more accurate and realistic land cover change detection compared to ML and NN mainly due to not being much influenced by the size of the training pixels. The findings of the study serve as important input for decision makers in managing natural resources and environment in the tropics systematically and efficiently.

scholarly journals Temporal Downscaling of TRMM Rain-Rate Images Using Principal Component Analysis during Heavy Tropical Thunderstorm Seasons

2015 ◽  
Vol 16 (5) ◽  
pp. 2264-2275 ◽  
Author(s):  
M. Rizaludin Mahmud ◽  
Hiroshi Matsuyama ◽  
Tetsuro Hosaka ◽  
Shinya Numata ◽  
Mazlan Hashim
Keyword(s):  
Principal Component Analysis ◽  
Satellite Data ◽  
Rain Rate ◽  
Daily Rainfall ◽  
Principal Component ◽  
Component Analysis ◽  
Eastern Coast ◽  
Rain Gauges ◽  
Hourly Rainfall ◽  
Rainfall Estimates

Abstract This paper examines the utility of principal component analysis (PCA) in obtaining accurate daily rainfall estimates from 3-hourly Tropical Rainfall Measuring Mission (TRMM) satellite data during heavy precipitation in a humid tropical environment. A large bias during heavy thunderstorms in humid tropical catchments is indicated by the TRMM satellite and is of profound concern because it is a conspicuous constraint for practical hydrology applications and requires proper treatment, particularly in areas with sparse rain gauges. The common procedure of calculating daily rainfall estimates by direct accumulation (DA) of a series of 3-hourly rainfall estimates caused a large bias because of temporal uncertainties, upscaling effects, and different mechanisms. In this study, PCA was used to transform correlated 3-hourly rain-rate images into a minimum effective principal component and to compute the corresponding rain-rate proportion based on correlation strength. This study was conducted on 91 rainy days of various intensity, acquired from three different years, during the wettest season on the eastern coast of peninsular Malaysia. Results showed that PCA reduced the bias and daily root-mean-square error by an average of 62% and 22%, respectively, compared with the DA approach. The PCA transformation was able to produce more precise daily rainfall estimates compared to the DA approach without the use of any rain gauge references. However, the performance was varied by the threshold selection and rainfall intensity. The results of this study indicate that PCA can be a useful tool in effective temporal downscaling of TRMM satellite data during heavy thunderstorm seasons in areas where rain gauges are sparse and satellite data are pivotal as a secondary source of rainfall data.

scholarly journals Mapping Global Solar Radiation from Long-Term Satellite Data in the Tropics Using an Improved Model

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
S. Janjai ◽  
I. Masiri ◽  
S. Pattarapanitchai ◽  
J. Laksanaboonsong
Keyword(s):  
Solar Radiation ◽  
Satellite Data ◽  
Precipitable Water ◽  
Global Solar Radiation ◽  
Digital Data ◽  
Radiation Absorption ◽  
Monthly Average ◽  
Main Input ◽  
Improved Model ◽  
The Tropics

This paper presents an improved model and its application for mapping global solar radiation from satellite data in the tropics. The model provides a more complete description of the absorption and scattering of solar radiation in the earth-atmosphere system as compared to the earlier models. The study is conducted in the tropical environment of Thailand. Digital data from the visible channel of GMS4, GMS5, GOES9, and MTSAT-1R satellites collected during a 15-year period (1995–2009) are used as a main input to the model. Satellite gray levels are converted into earth-atmospheric reflectivity and used to estimate the cloud effect. The absorption of solar radiation due to water vapour is computed from precipitable water derived from ambient temperature and relative humidity. The total ozone column data from TOMS/EP and OMI/AURA satellites are used to compute solar radiation absorption by ozone. The depletion of solar radiation due to aerosol is estimated from visibility data. In order to test its performance, the model is employed to calculate monthly average daily global solar radiation at 36 solar monitoring stations across the country. It is found that solar radiation calculated from the model and that obtained from the measurement are in good agreement, with a root mean square difference of 5.3% and a mean bias difference of 0.3%. The model is used to calculate the monthly average daily global solar radiation over the entire country, and results are displayed as monthly and yearly maps. These maps reveal that the geographical distribution of solar radiation in Thailand is strongly influenced by the tropical monsoons and local geographical features.

scholarly journals Global HCFC-22 measurements with MIPAS: retrieval, validation, global distribution and its evolution over 2005–2012

2016 ◽  
Vol 16 (5) ◽  
pp. 3345-3368 ◽  
Author(s):  
M. Chirkov ◽  
G. P. Stiller ◽  
A. Laeng ◽  
S. Kellmann ◽  
T. von Clarmann ◽  
...  
Keyword(s):  
Time Series ◽  
Satellite Data ◽  
Lower Stratosphere ◽  
Positive Trend ◽  
Altitude Range ◽  
Quasi Biennial Oscillation ◽  
Near Surface ◽  
Upper Troposphere ◽  
The Tropics ◽  
Balloon Measurements

Abstract. We report on HCFC-22 data acquired by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) in the reduced spectral resolution nominal observation mode. The data cover the period from January 2005 to April 2012 and the altitude range from the upper troposphere (above cloud top altitude) to about 50 km. The profile retrieval was performed by constrained nonlinear least squares fitting of modelled spectra to the measured limb spectral radiances. The spectral ν4-band at 816.5 ± 13 cm−1 was used for the retrieval. A Tikhonov-type smoothing constraint was applied to stabilise the retrieval. In the lower stratosphere, we find a global volume mixing ratio of HCFC-22 of about 185 pptv in January 2005. The rate of linear growth in the lower latitudes lower stratosphere was about 6 to 7 pptv year−1 in the period 2005–2012. The profiles obtained were compared with ACE-FTS satellite data v3.5, as well as with MkIV balloon profiles and cryosampler balloon measurements. Between 13 and 22 km, average agreement within −3 to +5 pptv (MIPAS – ACE) with ACE-FTS v3.5 profiles is demonstrated. Agreement with MkIV solar occultation balloon-borne measurements is within 10–20 pptv below 30 km and worse above, while in situ cryosampler balloon measurements are systematically lower over their full altitude range by 15–50 pptv below 24 km and less than 10 pptv above 28 km. MIPAS HCFC-22 time series below 10 km altitude are shown to agree mostly well to corresponding time series of near-surface abundances from the NOAA/ESRL and AGAGE networks, although a more pronounced seasonal cycle is obvious in the satellite data. This is attributed to tropopause altitude fluctuations and subsidence of polar winter stratospheric air into the troposphere. A parametric model consisting of constant, linear, quasi-biennial oscillation (QBO) and several sine and cosine terms with different periods has been fitted to the temporal variation of stratospheric HCFC-22 for all 10°-latitude/1-to-2-km-altitude bins. The relative linear variation was always positive, with relative increases of 40–70 % decade−1 in the tropics and global lower stratosphere, and up to 120 % decade−1 in the upper stratosphere of the northern polar region and the southern extratropical hemisphere. Asian HCFC-22 emissions have become the major source of global upper tropospheric HCFC-22. In the upper troposphere, monsoon air, rich in HCFC-22, is instantaneously mixed into the tropics. In the middle stratosphere, between 20 and 30 km, the observed trend is inconsistent with the trend at the surface (corrected for the age of stratospheric air), hinting at circulation changes. There exists a stronger positive trend in HCFC-22 in the Southern Hemisphere and a more muted positive trend in the Northern Hemisphere, implying a potential change in the stratospheric circulation over the observation period.

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