Elsevier

Advances in Space Research

Volume 68, Issue 10, 15 November 2021, Pages 3957-3970
Advances in Space Research

Calculation and analysis of cloud attenuation and other cloud parameters in India for earth-space links

https://doi.org/10.1016/j.asr.2021.07.028Get rights and content

Highlights

  • The cloud attenuation is higher during the SW monsoon season followed by NE monsoon, pre-monsoon and winter seasons at the places considered.

  • The maximum cloud attenuation of 1.67 dB/km is measured in Hyderabad by WVP-NTU cloud detection model at 24 GHz.

  • The WVP-NTU cloud detection model is more suitable for the five places considered as compared to the SU model.

Abstract

An effort is made to examine the cloud parameters over few stations in India for one year from October 2016 to September 2017. This study includes the investigation of cloud base height, cloud top height, zero degree isotherm height, number of cloud layers, cloud thickness, number of days cloud detected, cloud liquid water content and cloud attenuation at 6 GHz, 12.5 GHz and 24 GHz. Salonen Uppala (SU) model and Water Vapor Pressure-Nanyang Technological University (WVP-NTU) model are used for cloud detection using the radiosonde data at Bangalore, Hyderabad, Mumbai, Thiruvananthapuram and Chennai. The cloud parameters found using both the models are compared. WVP-NTU model shows enhanced values for most of the cloud parameters over SU model. Cloud base height calculated using these models are compared with METAR data and found that Cloud base height from WVP-NTU model matches well with METAR data. Cloud liquid water content and cloud attenuation values are calculated using the ITU-R model. The cumulative distributions (CDF) of cloud attenuation for one year are compared for the places considered. The seasonal CDFs of cloud attenuation using the WVP model are compared with the rain statistics. In this study, the maximum cloud attenuation of 1.67 dB/km is measured in Hyderabad by WVP-NTU combined ITU-R model at 24 GHz.

Introduction

Rapid growth in satellite services for Mobile Cellular Communication (MCC) and Direct-To-Home (DTH) based satellite services uses the frequency bands like L band (1 GHz/2GHz), S band (2 GHz/4GHz), C band (4 GHz/6GHz) and Ku band (12 GHz/14 GHz). Furthermore, utilization of Ka band (20 GHz/30 GHz) and the V band (40 GHz/50 GHz) in various satellites based services is under process and soon that may come to operation. Satellite based services at microwave frequencies are affected by various troposphere propagation impairments like atmospheric gases, clouds, rain etc. Although the effect of rain on radio waves is more than the effect due to clouds, the occurrence of cloud is always more than the rain (Athanasios et al., 2004).

The Cloud Liquid Water Content (CLWC) of clouds is the physical cause of cloud attenuation (Chakraborty and Maitra, 2013). The attenuation caused by the clouds becomes significant particularly for the systems operating at Ka and V bands. This significance becomes more prominent with increasing frequency and decreasing elevation angle.

Clouds are the random mixture of water droplets and ice crystals. The amount of water droplets and ice crystals present in a cloud depends on the type of the cloud. In general, clouds are classified as low level stratus clouds (0–2 km), middle level cumulus clouds (2–8 km) and high level cirrus clouds (6–18 km) (Donald Ahrens and Henson, 2018). The primary reason for cloud attenuation is absorption and the secondary reason is scattering, by the small water particles present in the cloud. Due to small refractive index and small in particle size the ice crystals does not constitute much absorption. Thus the attenuation due to ice crystals is negligible below 50 GHz. Therefore, high level cirrus clouds which have primarily ice crystals are not given due consideration for cloud attenuation calculation (Chakraborty and Maitra, 2013).

The attenuation caused by low level stratus clouds and middle level cumulus clouds depends on the CLWC of the cloud, the cloud temperature and the thickness of the cloud. Based on the thickness, clouds are classified as light, medium and thick clouds. The thickness of the cloud ranges from 1.5 km to 2.5 km. In general, light clouds, medium clouds and thick clouds have thickness of 0.2 km, 0.5 km and 1 km respectively. More thickness constitutes more CLWC which leads to more attenuation (Mandeep and Hassan, 2008).

The composition of clouds depends on the cloud temperature. The cloud consists of liquid if the cloud temperature is above 0 °C and ice crystals if the cloud temperature is below −20 °C. It is a mixture of ice crystals and water droplets if the cloud temperature varies from 0 °C to −20 °C, sometimes called as super cooled water. As explained before, ice crystals do not attenuate the radio waves. But the super cooled water causes sufficient attenuation at microwave frequencies (Maitra and Chakraborty, 2009).

The average size of cloud particles ranges from 9 μm to 20 μm whereas the average size of rain droplets ranges around 100 μm. The attenuation is worse because of big size rain droplets in rainy days. In tropical region clouds are often present, especially before the rain occurrence event. Just before the rain event, heavy or light dark clouds occupy the sky completely or partially. It is obvious that the clouds just before the rain event bear more liquid water content which is the main reason for cloud attenuation. So it is necessary for engineers to measure the cloud attenuation in a region where the liquid water density is more. During non-rainy period, the attenuation is mainly because of all time present clouds and atmospheric gases. As the focus of this paper is cloud attenuation values, the attenuation study due to gases is not considered here.

In a tropical region country like India, the occurrence of middle level cumulus clouds is frequent; so the cloud attenuation will be inexorable (Chakraborty and Maitra, 2013). The transmitter power needs to be standardized based on the receiver requirement in MCC and DTH services and other satellite links. A transmitter positioned in a cloudy region undergoes more cloud attenuation than a transmitter positioned or established in a non cloudy region. High power transmitter causes electromagnetic interference and radiation effect on the human beings. The high power radiated from transmitter affects medical apparatus. The transmitter power is major constraint. So it is important to consider cloud attenuation to design the power budget of earth space links (Athanasios et al., 2004).

Clouds were detected and CLWC was measured via many methods and instruments. Satellite beacon receiver at the ground station is used to analyze the clouds (Mandeep and Hassan, 2008, Mandeep et al., 2009, Luini et al., 2007, Yuan et al., 2017). A cloud profiling RADAR and LIDAR are used widely for cloud attenuation study (Yuan et al., 2017, Luini and Capsoni, 2016, Wang et al., 2018, Wang et al., 2017). Ground based microwave radiometer is utilized to study the cloud characteristics and cloud attenuation (Chakraborty and Maitra, 2013, Mandeep et al., 2009, Luini et al., 2007, Das et al., 2013). MODerate resolution Imaging Spectroradiometer (MODIS) on board TERRA satellite is also used to study the cloud attenuation and types (Luini and Capsoni, 2016, Tournadre et al., 2009). In (Molina García et al., 2018) cloud parameters were retrieved from Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) and analyzed. Cloud vertical structure data set measured by surface based weather observation is used in (Rossow and Zhang, 2010). Radiosonde data is mostly used as it has best vertical profiling of CLWC to calculate the cloud attenuation (Chakraborty and Maitra, 2013, Mandeep and Hassan, 2008, Maitra and Chakraborty, 2009, Mandeep et al., 2009, Luini et al., 2007, Yuan et al., 2017, Wang et al., 2018, Luini and Capsoni, 2014, Luini et al., 2013). By using the radiosonde data, the cloud has to be identified, CLWC needs to be calculated followed by the calculation of specific attenuation and then total cloud attenuation is calculated.

Substantial researches have been done to detect the clouds and to calculate the cloud attenuation. There are many cloud detection models (Mandeep and Hassan, 2008, Mandeep et al., 2009) available to calculate the CLWC. Among all, Salonen and Uppala (SU) (Salonen and Uppala, 1991) laid well foundation to the calculation of CLWC and the cloud attenuation relationship, by calculating the cloud attenuation accurately with less error in prediction as compared to existing methods/models (Luini et al., 2013). Specific cloud attenuation values of 0.40 dB/km at 20 GHz and 1.34 dB/km at 30 GHz (Ojo, 2017) are found at tropical regions Malaysia and Nigeria respectively using the SU model (cloud detection) and ITU-R model (Cloud attenuation calculation). Cloud attenuation values of 4 dB at Ka band in Kolkata (Das et al., 2013), around 2 dB at 11.172 GHz in Kolkata (De et al., 2017), 4 dB exceeding 0.01% of time at 18.9 GHz in Singapore (Yuan et al., 2017) and around 2.5 dB at 30 GHz in Athens (Lyras et al., 2017) are found using the SU model (cloud detection) and ITU-R model (cloud attenuation calculation). It is clear from the specific cloud attenuation and cloud attenuation values found at all the tropical regions are significant and cloud attenuation studies are essential. In India, the cloud attenuation study is done at Kolkata but the study is not extended for other places. This paper considers 5 different places from south India geographically located away from each other.

Recently, Water Vapor Pressure model is proposed by F. Yuan from Nanyang Technological University in (Yuan et al., 2016a) to detect the clouds for the tropical region. His model is named as WVP-NTU model and is also used in this paper for cloud detection in addition with SU model. Clouds are detected using the two mentioned models from the radiosonde data at Bangalore, Hyderabad, Mumbai, Thiruvananthapuram and Chennai for the period of one year from October 2016 to September 2017.

After the cloud detection, the cloud characteristic study is done to calculate Cloud Base Height (CBH), Cloud Top Height (CTH), Zero Degree Isotherm Height (ITH), Number of Cloud Layers (N-CL), Cloud Thickness (CT), Number of days Cloud Detected (N-CD) for all the five places considered in India for the period of one year from October 2016 to September 2017. CBH calculated for the clouds detected using the SU model and WVP-NTU model are compared with the CBH found from METAR data for Chennai in September 2017. The Cloud Liquid Water Content (CLWC) for the clouds detected is measured. Then, the specific cloud attenuation and total cloud attenuation are calculated using the ITU-R model for the period of one year from October 2016 to September 2017 for all the places considered. The calculated cloud attenuation values using SU and WVP-NTU models at different places are compared and the results are analyzed. A comparison with the rain events is also made to show the variation of cloud attenuation during the rainy day and a day without rain. The cumulative distribution of cloud attenuation exceeding percentages of time during one year is provided for all the mentioned places using both the cloud detection models. Rain statistics of the considered places from October 2016 to September 2017 is provided and annual and seasonal variations of cloud attenuation values are analyzed.

The remaining portions of the paper are structured as follows. An outline of the database used in this study is given in Section 2. In Section 3, the cloud detection models, cloud attenuation calculation methods and various measures that quantify the cloud attenuation are discussed. Section 4 explains the results and the corresponding discussions. Finally, the conclusion and future scope of this work is given in Section 5.

Section snippets

Experimental setup

The upper air profiling Radiosonde data, METAR data and rain data are used for cloud parameter and cloud attenuation calculations and analyzes. Radiosonde measures (Chakraborty and Maitra, 2012) the vertical profiles regularly but typically only two times a day. The radiosonde is the measuring instrument that measures atmospheric pressure, temperature and humidity profiles directly with high vertical resolution and near-global coverage, and has been operating for more than five decades. Global

Measurement of cloud parameters

The cloud detection models are necessary to identify the clouds. So this section starts with the cloud detection models.

Results and discussion

Radiosonde data, the vertical profiler of the atmosphere is used to analyze the clouds and its layers. Radiosonde data is available twice a day at 5.30AM (Indian Standard Time - IST) and 5.30PM (IST). The data collected at 05.30AM is used for the one year from October 2016 to September 2017 at the 5 places considered. The cloud parameters, ITH, CBH, CTH, N-CL, CT and ND-CD are detected from the radiosonde data at Bangalore, Hyderabad, Mumbai, Thiruvananthapuram and Chennai, for one year from

Conclusion

The propagation impairments on earth space links at various heights caused by the clouds in the tropical region at different microwave frequencies are outlined and analyzed. Two cloud detection models, the most popular SU model and WVP-NTU model are used for cloud detection. Clouds are detected using the two mentioned models from the radiosonde data at Bangalore, Hyderabad, Mumbai, Thiruvananthapuram and Chennai for one year from October 2016 to September 2017. The cloud characteristic study is

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The authors thank Ministry of Electronics and Information Technology (MeitY), Government of India for their financial assistance under Visvesvaraya PhD scheme for Electronics and IT. The authots would also like to thank National Institute of Technology Puducherry for providing the necessary facilities to carry out this research. Finally, the authors thank Indian Meteorological Department for providing the Radiosonde Data and the Rain Data.

Funding information

No funding received.

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