Benefits of a Closely-Spaced Satellite Constellation of Atmospheric Polarimetric Radio Occultation Measurements

The climate and weather forecast predictive capability for precipitation intensity is limited by gaps in the understanding of basic cloud-convective processes. Currently, a better understanding of the cloud-convective process lacks observational constraints, due to the difficulty in obtaining accurate, vertically resolved pressure, temperature, and water vapor structure inside and near convective clouds. This manuscript describes the potential advantages of collecting sequential radio occultation (RO) observations from a constellation of closely spaced low Earth-orbiting satellites. In this configuration, the RO tangent points tend to cluster together, such that successive RO ray paths are sampling independent air mass quantities as the ray paths lie “parallel” to one another. When the RO train orbits near a region of precipitation, there is a probability that one or more of the RO ray paths will intersect the region of heavy precipitation, and one or more would lie outside. The presence of heavy precipitation can be discerned by the use of the polarimetric RO (PRO) technique recently demonstrated by the Radio Occultations through Heavy Precipitation (ROHP) receiver onboard the Spanish PAZ spacecraft. This sampling strategy provides unique, near-simultaneous observations of the water vapor profile inside and in the environment surrounding heavy precipitation, which are not possible from current RO data.

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Assessment of global navigation satellite system (GNSS) radio occultation refractivity under heavy precipitation

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-11697-2018 ◽

2018 ◽

Vol 18 (16) ◽

pp. 11697-11708 ◽

Cited By ~ 7

Author(s):

Ramon Padullés ◽

Estel Cardellach ◽

Kuo-Nung Wang ◽

Chi O. Ao ◽

F. Joseph Turk ◽

...

Keyword(s):

Radio Occultation ◽

Three Dimensional ◽

Heavy Precipitation ◽

Satellite System ◽

Specific Humidity ◽

Positive Bias ◽

Actual Measurement ◽

Excess Phase ◽

Global Navigation Satellite ◽

Ray Paths

Abstract. A positive bias at heights between 3 and 8 km has been observed when comparing the radio-occultation (RO)-retrieved refractivity with that of meteorological analyses and reanalyses in cases where heavy precipitation is present. The effect of precipitation in RO retrievals has been investigated as a potential cause of the bias, using precipitation measurements interpolated into the actual three-dimensional RO ray paths to calculate the excess phase induced by precipitation. The study consisted of comparing the retrievals when such extra delay is removed from the actual measurement and when it is not. The results show how precipitation itself is not the cause of the positive bias. Instead, we show that the positive bias is linked to high specific-humidity conditions regardless of precipitation. This study also shows a regional dependence of the bias. Furthermore, different analyses and reanalyses show a disagreement under high specific-humidity conditions and, in consequence, heavy precipitation.

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Evaluation of a Nonlocal Quasi-Phase Observation Operator in Assimilation of CHAMP Radio Occultation Refractivity with WRF

Monthly Weather Review ◽

10.1175/2007mwr2042.1 ◽

2008 ◽

Vol 136 (1) ◽

pp. 242-256 ◽

Cited By ~ 21

Author(s):

Hui Liu ◽

Jeffrey Anderson ◽

Ying-Hwa Kuo ◽

Chris Snyder ◽

Alain Caya

Keyword(s):

Water Vapor ◽

Radio Occultation ◽

Weather Research And Forecasting ◽

Nonlocal Operator ◽

Observation Operator ◽

Ensemble Data ◽

Data Assimilation System ◽

Assimilation System ◽

Ray Paths ◽

Rms Errors

Abstract A nonlocal quasi-phase radio occultation (RO) observation operator is evaluated in the assimilation of Challenging Minisatellite Payload (CHAMP) radio occultation refractivity using a Weather Research and Forecasting (WRF) ensemble data assimilation system at 50-km resolution. The nonlocal operator calculates the quasi phase through integration of the model refractivity along the observed ray paths. As a comparison, a local refractivity operator that calculates the model refractivity at the observed ray perigee points is also evaluated. The assimilation is done over North America during January 2003 in two different situations: in conjunction with dense, high-quality radiosonde observations and with only satellite cloud drift wind observations. Analyses of temperature and water vapor with the RO refractivity assimilated using the local and nonlocal operator are verified against nearby withheld radiosonde observations. The bias and RMS errors of the analyses of water vapor and temperature using the nonlocal operator are significantly reduced compared with those using the local operator in the troposphere when the only additional observations are satellite cloud drift winds. The reduction of the bias and RMS errors is reduced when radiosonde observations are assimilated.

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Retrieval of water vapor profiles with radio occultation measurements using an artificial neural network

Advances in Atmospheric Sciences ◽

10.1007/bf02918719 ◽

2005 ◽

Vol 22 (5) ◽

pp. 759-764 ◽

Cited By ~ 3

Author(s):

Wang Xin ◽

Lu Daren

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Water Vapor ◽

Radio Occultation ◽

Artificial Neural

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The effects of aerosols on precipitation and dimensions of subtropical clouds: a sensitivity study using a numerical cloud model

Atmospheric Chemistry and Physics ◽

10.5194/acp-6-67-2006 ◽

2006 ◽

Vol 6 (1) ◽

pp. 67-80 ◽

Cited By ~ 149

Author(s):

A. Teller ◽

Z. Levin

Keyword(s):

Water Vapor ◽

Climate Models ◽

Cloud Model ◽

Cloud Condensation Nuclei ◽

Sensitivity Study ◽

Meteorological Conditions ◽

Dust Particles ◽

Noticeable Effect ◽

Convective Clouds ◽

Ice Nuclei

Abstract. Numerical experiments were carried out using the Tel-Aviv University 2-D cloud model to investigate the effects of increased concentrations of Cloud Condensation Nuclei (CCN), giant CCN (GCCN) and Ice Nuclei (IN) on the development of precipitation and cloud structure in mixed-phase sub-tropical convective clouds. In order to differentiate between the contribution of the aerosols and the meteorology, all simulations were conducted with the same meteorological conditions. The results show that under the same meteorological conditions, polluted clouds (with high CCN concentrations) produce less precipitation than clean clouds (with low CCN concentrations), the initiation of precipitation is delayed and the lifetimes of the clouds are longer. GCCN enhance the total precipitation on the ground in polluted clouds but they have no noticeable effect on cleaner clouds. The increased rainfall due to GCCN is mainly a result of the increased graupel mass in the cloud, but it only partially offsets the decrease in rainfall due to pollution (increased CCN). The addition of more effective IN, such as mineral dust particles, reduces the total amount of precipitation on the ground. This reduction is more pronounced in clean clouds than in polluted ones. Polluted clouds reach higher altitudes and are wider than clean clouds and both produce wider clouds (anvils) when more IN are introduced. Since under the same vertical sounding the polluted clouds produce less rain, more water vapor is left aloft after the rain stops. In our simulations about 3.5 times more water evaporates after the rain stops from the polluted cloud as compared to the clean cloud. The implication is that much more water vapor is transported from lower levels to the mid troposphere under polluted conditions, something that should be considered in climate models.

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Scanning 10-W Water Vapor DIAL for the Investigation of Atmospheric Turbulence and Land-Atmosphere Feedback

10.5194/egusphere-egu21-12925 ◽

2021 ◽

Author(s):

Andreas Behrendt ◽

Florian Spaeth ◽

Volker Wulfmeyer

Keyword(s):

Heat Flux ◽

Water Vapor ◽

Latent Heat ◽

Atmospheric Turbulence ◽

Latent Heat Flux ◽

Climate Models ◽

Weather Forecast ◽

Surface Characteristics ◽

Scanning System ◽

Forecast Models

We will present recent measurements made with the water vapor differential absorption lidar (DIAL) of University of Hohenheim (UHOH). This scanning system has been developed in recent years for the investigation of atmospheric turbulence and land-atmosphere feedback processes.The lidar is housed in a mobile trailer and participated in recent years in a number of national and international field campaigns. We will present examples of vertical pointing and scanning measurements, especially close to the canopy. The water vapor gradients in the surface layer are related to the latent heat flux. Thus, with such low-elevation scans, the latent heat flux distribution over different surface characteristics can be monitored, which is important to verify and improve both numerical weather forecast models and climate models.The transmitter of the UHOH DIAL consists of a diode-pumped Nd:YAG laser which pumps a Ti:sapphire laser. The output power of this laser is up to 10 W. Two injection seeders are used to switch pulse-to-pulse between the online and offline signals. These signals are then either directly sent into the atmosphere or coupled into a fiber and guided to a transmitting telescope which is attached to the scanner unit. The receiving telescope has a primary mirror with a dimeter of 80 cm. The backscatter signals are recorded shot to shot and are typically averaged over 0.1 to 1 s.

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Sounding Heavy Precipitating Vertical Cloud Structures with Polarimetric Radio Occultations aboard PAZ

10.5194/egusphere-egu21-9405 ◽

2021 ◽

Author(s):

Ramon Padullés ◽

Estel Cardellach ◽

F. Joseph Turk ◽

Chi O. Ao ◽

Kuo Nung Wang ◽

...

Keyword(s):

Radio Occultation ◽

Deep Convection ◽

Heavy Precipitation ◽

Current Data ◽

Data Availability ◽

The Status ◽

Potential Applications ◽

Initial Hypothesis ◽

Forecast Models ◽

Electromagnetic Signals

The Radio Occultation and Heavy Precipitation (ROHP) experiment aboard the Spanish PAZ satellite was activated in May 2018 with the objective to demonstrate the Polarimetric Radio Occultation (PRO) concept for rain detection. This technique enhances standard RO by measuring GNSS signals at two orthogonal linear polarizations (H and V). Owing to hydrometeor asymmetry, electromagnetic signals propagating through regions of heavy precipitation would experience a differential phase delay expected to be measurable by the ROHP experiment. After 2+ years of operations, the initial hypothesis has been verified and the main scientific goals have been achieved. Soon after the activation of the experiment it became clear that PRO observables were sensitive to heavy precipitation, showing positive signatures correlated with the presence and intensity of precipitation. After a thorough on-orbit calibration, it has been demonstrated that the PAZ polarimetric observable can be used as a proxy for heavy precipitation. Furthermore, PRO measurements were shown to be sensitive to the horizontally oriented frozen hydrometeors present throughout the vertical cloud extent, providing valuable information on the vertical structure of precipitating clouds. In addition, PRO can retrieve standard thermodynamic RO products such as temperature, pressure, and water vapor. These products, provided with high vertical resolution, globally distributed and seamlessly over ocean and over land, make PRO observations a unique dataset, with potential applications ranging from the study of deep convection processes to the evaluation and diagnosis of NWP forecast models. In this presentation we will report on the status of the experiment and current data availability. We will also show the results of the sensitivity studies to heavy precipitation and frozen particles, performed using collocated observations between PAZ and GPM-DPR, GPM-GMI, and other radiometers from the GPM constellation, as well as a-priory information from the Cloudsat radar. Finally, we will address potential level-2 products we can expect from PAZ observations.

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Tracking an Atmospheric River in a Warmer Climate: from Water Vapor to Economic Impacts

10.5194/esd-2017-64 ◽

2017 ◽

Cited By ~ 1

Author(s):

Francina Dominguez ◽

Sandy Dall'erba ◽

Shuyi Huang ◽

Andre Avelino ◽

Ali Mehran ◽

...

Keyword(s):

Water Vapor ◽

Economic Impacts ◽

Heavy Precipitation ◽

Integrated Modeling ◽

Vapor Transport ◽

Water Vapor Transport ◽

Economic Losses ◽

Radiative Forcings ◽

Hypothetical Scenario ◽

Western Washington

Abstract. Atmospheric rivers (ARs) account for more than 75 % of heavy precipitation events and nearly all of the extreme flooding events along the Olympic Mountains and western Cascade mountains of western Washington state. In a warmer climate, ARs in this region are projected to become more frequent and intense, primarily due to increases in atmospheric water vapor. However, it is unclear how the changes in water vapor transport will affect regional flooding and associated economic impacts. In this work, we present an integrated modeling system to quantify the atmospheric-hydrologic-hydraulic and economic impacts of the December 2007 AR event that impacted the Chehalis river basin in western Washington. We use the modeling system to project impacts under a hypothetical scenario where the same December 2007 event occurs in a warmer climate. This method allows us to incorporate different types of uncertainty including: a) alternative future radiative forcings, b) different responses of the climate system to future radiative forcings and c) different responses of the surface hydrologic system. In the warming scenario, AR integrated vapor transport increases, however, these changes do not translate into generalized increases in precipitation throughout the basin. The changes in precipitation translate into spatially heterogeneous changes in sub-basin runoff and increased streamflow along the entire Chehalis main stem. Economic losses due to stock damages increased moderately, but losses in terms of business interruption were significant. Our integrated modeling tool provides communities in the Chehalis region with a range of possible future physical and economic impacts associated with AR flooding.

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Frequency of deep convective clouds in the tropical zone from ten years of AIRS data

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-10009-2013 ◽

2013 ◽

Vol 13 (4) ◽

pp. 10009-10047

Author(s):

H. H. Aumann ◽

A. Ruzmaikin

Keyword(s):

Water Vapor ◽

Brightness Temperature ◽

Frequency Of Occurrence ◽

Tropical Zone ◽

Convective Clouds ◽

Atmospheric Window ◽

Deep Convective Clouds ◽

Sst Anomaly ◽

The Difference ◽

Global Precipitation

Abstract. Deep Convective Clouds (DCC) have been widely studied because of their association with heavy precipitation and severe weather events. To identify DCC with Atmospheric Infrared Sounder (AIRS) data we use three types of thresholds: (1) thresholds based on the absolute value of an atmospheric window channel brightness temperature; (2) thresholds based on the difference between the brightness temperature in an atmospheric window channel and the brightness temperature centered on a strong water vapor absorption line; and (3) a threshold using the difference between the window channel brightness temperature and the tropopause temperature based on climatology. We find that DCC identified with threshold (2) (referred to as DCCw4) cover 0.16% of the area of the tropical zone and 72% of them are identified as deep convective, 39% are overshooting based on simultaneous observations with the Advanced Microwave Sounding Unit-HSB (AMSU-HSB) 183 GHz water vapor channels. In the past ten years the frequency of occurrence of DCC decreased for the tropical ocean, while it increased for tropical land. The land increase-ocean decrease closely balance, such that the DCC frequency changed at an insignificant rate for the entire tropical zone. This pattern of essentially zero trend for the tropical zone, but opposite land/ocean trends, is consistent with measurements of global precipitation. The changes in frequency of occurrence of the DCC are correlated with the Niño34 index, which defines the SST anomaly in the East-Central Pacific. This is also consistent with patterns seen in global precipitation. This suggests that the observed changes in the frequency are part of a decadal variability characterized by shifts in the main tropical circulation patterns, which does not fully balance in the ten year AIRS data record. The regional correlations and anti-correlations of the DCC frequency anomaly with the Multivariate ENSO Index (MEI) provides a new perspective for the regional analysis of past events, since the SST anomaly in the Nino34 region is available in the form of the extended MEI since 1871. Depending on the selected threshold, the frequency of DCC in the tropical zone ranges from 0.06% to 0.8% of the area. We find that the least frequent, more extreme DCC also show the largest trend in frequency, increasing over land, decreasing over ocean. This finding fits into the framework of how weather extremes respond to climate change.

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Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

Journal of Sensors ◽

10.1155/2018/3428303 ◽

2018 ◽

Vol 2018 ◽

pp. 1-13 ◽

Cited By ~ 6

Author(s):

Qin Zhang ◽

Junhua Ye ◽

Shuangcheng Zhang ◽

Fei Han

Keyword(s):

Water Vapor ◽

Radio Occultation ◽

Weather Prediction ◽

Precipitable Water ◽

Reanalysis Data ◽

Precipitable Water Vapor ◽

Reanalysis Dataset ◽

High Positive Correlation ◽

Advantages And Disadvantages ◽

Ecmwf Reanalysis

Precipitable water vapor (PWV) content detection is vital to heavy rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV. In general, these methods can be divided into two categories, ground-based or space-based. In this study, we analyze the advantages and disadvantages of these technologies, compare retrieved atmosphere parameters by different RO (radio occultation) observations, like FORMOSAT-3/COSMIC (Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate) and FY3C (China Feng Yun 3C), and assess retrieved PWV precision with a radiosonde. Besides, we interpolate PWV from NWP (numerical weather prediction) reanalysis data for more comparison and analysis with RO. Specifically, ground-based GNSS is of high precision and continuous availability to monitor PWV distribution; in our paper, we show cases to validate and compare GNSS retrieving PWV with a radiosonde. Except GNSS PWV, we give two different radio occultation sounding results, COSMIC and FY3C, to validate the precision to monitor PWV from space in a global area. FY3C results containing Beidou (China Beidou Global Satellite Navigation System) radio occultation events need to be emphasized. So, in our study, we get the retrieved atmospheric profiles from GPS and Beidou radio occultation observations and derive atmosphere PWV by a variational retrieval method based on these data over a global area. Besides, other space-based methods, such as microwave satellite, are also useful in detecting PWV distribution situations in a global area from space; in this study, we present a case of retrieved PWV using microwave satellite observation. NWP reanalysis data ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim and the new-generation reanalysis data ERA5 provide global grid atmosphere parameters, like surface temperature, different-level pressures, and precipitable water. We show cases of retrieved PWV and validate the precision with radiosonde results and compare new reanalysis dataset ERA5 with ERA-Interim, finding that ERA5 can get higher precision-retrieved atmosphere parameters and PWV. In the end, from our comparison, we find that the retrieved PWV from RO (FY3C and COSMIC) and ECMWF reanalysis data (ERA-Interim and ERA5) have a high positive correlation and that almost all R2 values exceed 0.9, compare retrieved PWV with a radiosonde, and find that whether it is RO and ECMWF reanalysis data, ground-based GNSS, or microwave satellite, they all show small biases.

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A Novel Approach for the Detection of Developing Thunderstorm Cells

Remote Sensing ◽

10.3390/rs11040443 ◽

2019 ◽

Vol 11 (4) ◽

pp. 443 ◽

Cited By ~ 6

Author(s):

Richard Müller ◽

Stéphane Haussler ◽

Matthias Jerg ◽

Dirk Heizenreder

Keyword(s):

Water Vapor ◽

Main Idea ◽

Probability Of Detection ◽

Base Case ◽

Convective Clouds ◽

Critical Success ◽

Novel Approach ◽

Forecast Lead Time ◽

Spatio Temporal ◽

Atmospheric Motion Vectors

This study presents a novel approach for the early detection of developing thunderstorms. To date, methods for the detection of developing thunderstorms have usually relied on accurate Atmospheric Motion Vectors (AMVs) for the estimation of the cooling rates of convective clouds, which correspond to the updraft strengths of the cloud objects. In this study, we present a method for the estimation of the updraft strength that does not rely on AMVs. The updraft strength is derived directly from the satellite observations in the SEVIRI water vapor channels. For this purpose, the absolute value of the vector product of spatio-temporal gradients of the SEVIRI water vapor channels is calculated for each satellite pixel, referred to as Normalized Updraft Strength (NUS). The main idea of the concept is that vertical updraft leads to NUS values significantly above zero, whereas horizontal cloud movement leads to NUS values close to zero. Thus, NUS is a measure of the strength of the vertical updraft and can be applied to distinguish between advection and convection. The performance of the method has been investigated for two summer periods in 2016 and 2017 by validation with lightning data. Values of the Critical Success Index (CSI) of about 66% for 2016 and 60% for 2017 demonstrate the good performance of the method. The Probability of Detection (POD) values for the base case are 81.8% for 2016 and 89.2% for 2017, respectively. The corresponding False Alarm Ratio (FAR) values are 22.6% (2016) and 36.4% (2017), respectively. In summary, the method has the potential to reduce forecast lead time significantly and can be quite useful in regions without a well-maintained radar network.

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