Cloud physics from space

Stephens, Graeme L.; Christensen, Matthew; Andrews, Timothy; Haywood, Jim M.; Malavelle, Florent; Suzuki, Kentaroh; Jing, Xianwen; Lebsock, M. D.; Li, Jui‐Lin F.; Takahashi, H.; Sy, Ousmane O.

doi:10.1002/qj.3589

Cited by 19 publications

(12 citation statements)

References 111 publications

(163 reference statements)

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“…Warm Rain Processes . Cloudsat CPR in synergy with other A‐Train instruments has been instrumental in advancing our understanding of warm‐cloud physics (Stephens et al., 2019). The conversion rate of liquid water from cloud to rain is typically parameterized as a function of liquid water mixing ratio and number concentration, and its formulation involves a set of parameters determining how the conversion rate depends on the cloud properties.…”

Section: Current Spaceborne Radar Systemsmentioning

confidence: 99%

Spaceborne Cloud and Precipitation Radars: Status, Challenges, and Ways Forward

Battaglia

Kollias

Dhillon

et al. 2020

Reviews of Geophysics

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Spaceborne radars offer a unique three‐dimensional view of the atmospheric components of the Earth's hydrological cycle. Existing and planned spaceborne radar missions provide cloud and precipitation information over the oceans and land difficult to access in remote areas. A careful look into their measurement capabilities indicates considerable gaps that hinder our ability to detect and probe key cloud and precipitation processes. The international community is currently debating how the next generation of spaceborne radars shall enhance current capabilities and address remaining gaps. Part of the discussion is focused on how to best take advantage of recent advancements in radar and space platform technologies while addressing outstanding limitations. First, the observing capabilities and measurement highlights of existing and planned spaceborne radar missions including TRMM, CloudSat, GPM, RainCube, and EarthCARE are reviewed. Then, the limitations of current spaceborne observing systems, with respect to observations of low‐level clouds, midlatitude and high‐latitude precipitation, and convective motions, are thoroughly analyzed. Finally, the review proposes potential solutions and future research avenues to be explored. Promising paths forward include collecting observations across a gamut of frequency bands tailored to specific scientific objectives, collecting observations using mixtures of pulse lengths to overcome trade‐offs in sensitivity and resolution, and flying constellations of miniaturized radars to capture rapidly evolving weather phenomena. This work aims to increase the awareness about existing limitations and gaps in spaceborne radar measurements and to increase the level of engagement of the international community in the discussions for the next generation of spaceborne radar systems.

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Section: Current Spaceborne Radar Systemsmentioning

confidence: 99%

Spaceborne Cloud and Precipitation Radars: Status, Challenges, and Ways Forward

Battaglia

Kollias

Dhillon

et al. 2020

Reviews of Geophysics

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“…They are the prerequisite for precipitation, which are the intermediate stage between water vapor and precipitation. All moist processes in the atmosphere ultimately involve clouds, which play an important role in Earth's water cycle [4,5]. In addition, because clouds interact so strongly with sunlight and infrared radiation, they will bring significant climate feedback.…”

Section: Introductionmentioning

confidence: 99%

“…An inadequate way of representing cloud processes has long been identified as a main source of uncertainty in climate projections [6]. To predict changes in weather and climate brings the subject of clouds back to the forefront of atmospheric science and climate science [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Cloud Mask and Cloud Top Height from Fengyun-4A with MODIS Cloud Retrievals over the Tibetan Plateau

Lyu

2021

Remote Sensing

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The Tibetan Plateau (TP) has profound thermal and dynamic influences on the atmospheric circulation, energy, and water cycles of the climate system, which make the clouds over the TP the forefront of atmospheric and climate science. However, the highest altitude and most complex terrain of the TP make the retrieval of cloud properties challenging. In order to understand the performance and limitations of cloud retrievals over the TP derived from the state-of-the-art Advanced Geosynchronous Radiation Imager (AGRI) onboard the new generation of Chinese Geostationary (GEO) meteorological satellites Fengyun-4 (FY-4), a three-month comparison was conducted between FY-4A/AGRI and the Moderate Resolution Imaging Spectroradiometer (MODIS) for both cloud detection and cloud top height (CTH) pixel-level retrievals. For cloud detection, the AGRI and MODIS cloud mask retrievals showed a fractional agreement of 0.93 for cloudy conditions and 0.73 for clear scenes. AGRI tended to miss lower CTH clouds due to the lack of thermal contrast between the clouds and the surface of the TP. For cloud top height retrievals, the comparison showed that on average, AGRI underestimated the CTH relative to MODIS by 1.366 ± 2.235 km, and their differences presented a trend of increasing with height.

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“…A deeper understanding of these feedback processes is needed for better understanding climate [6]. NASA's CloudSat combined with other A-Train satellites produces a unique global view of the vertical structure of clouds and precipitation [7][8][9]. These data have provided new cloud physics and have changed our understanding of warm cloud with precipitation, demonstrating the effectiveness of the observation-based approach.…”

Section: Introductionmentioning

confidence: 99%

Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel

Takenaka

Sakashita²,

Higuchi

et al. 2020

Remote Sensing

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This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prompt reports. We have previously reported the quasi real-time analysis of solar radiation at the surface and top of the atmosphere using geostationary satellite data. Estimating atmospheric parameters and surface albedo requires accurate geolocation information to estimate the solar radiation accurately. The physical analysis algorithm for Earth observations is verified by the ground truth. In particular, downward solar radiation at the surface is validated by pyranometers installed at ground observation sites. The ground truth requires that the satellite observation data pixels be accurately linked to the location of the observation equipment on the ground. Thus, inaccurate geolocation information disrupts verification and causes complex problems. It is difficult to determine whether error in the validation of physical quantities arises from the estimation algorithm, satellite sensor calibration, or a geolocation problem. Geolocation error hinders the development of accurate analysis algorithms; therefore, accurate observational information with geolocation information based on latitude and longitude is crucial in atmosphere and land target analysis. This method provides the basic data underlying physical analysis, parallax correction, etc. Because the processing speed is important in geolocation correction, we used the phase-only correlation (POC) method, which is fast and maintains the accuracy of geolocation information in geostationary satellite observation data. Furthermore, two-dimensional fast Fourier transform allowed the accurate correction of multiple target points, which improved the overall accuracy. The reference dataset was created using NASA’s Shuttle Radar Topography Mission 1-s mesh data. We used HIMAWARI-8/Advanced HIMAWARI Imager data to demonstrate our method, with 22,709 target points for every 10-min observation and 5826 points for every 2.5 min observation. Despite the presence of disturbances, the POC method maintained its accuracy. Column offset and line offset statistics showed stability and characteristic error trends in the raw HIMAWARI standard data. Our method was sufficiently fast to apply to quasi real-time analysis of solar radiation every 10 and 2.5 min. Although HIMAWARI-8 is used as an example here, our method is applicable to all geostationary satellites. The corrected HIMAWARI 16 channel gridded dataset is available from the open database of the Center for Environmental Remote Sensing (CEReS), Chiba University, Japan. The total download count was 50,352,443 on 8 July 2020. Our method has already been applied to NASA GeoNEX geostationary satellite products.

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Cloud physics from space

Cited by 19 publications

References 111 publications

Spaceborne Cloud and Precipitation Radars: Status, Challenges, and Ways Forward

Spaceborne Cloud and Precipitation Radars: Status, Challenges, and Ways Forward

Evaluation of Cloud Mask and Cloud Top Height from Fengyun-4A with MODIS Cloud Retrievals over the Tibetan Plateau

Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel

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