Retrieval of column-integrated water vapour from MODIS and analysis of its monthly and seasonal variability over several typical cities in China

Column-integrated water vapour also called Precipitable Water Vapour (PWV), is one of the main parameters influencing the global climate change. Due to its high spatial and temporal variability PWV has been found to be a good tracer of atmospheric motions. Retrieving PWV from Moderate Resolution Imaging Spectroradiometer (MODIS) data has the merits of high spatial resolution and low cost. In this paper, an algorithm for retrieving PWV using several MODIS near-IR channels data is first presented. Six typical cities in China with different climate are selected for study. These are Beijing, Shanghai, Guangzhou, Chengdu, Wuhan and Lanzhou. The variations of PWV in recent13 years (2001-2013) over six cities have been analyzed. The study brings out an increasing trend of annual average of water vapour over these cities in recent 13 years. The results also indicate that PWV reaches the highest value in summer, decreases in autumn, further decrease in spring, and is lowest in winter. PWV in summer over the six cities have been increasing in recent 13 years, but PWV in autumn and winter have been decreasing over inland cities, such as Wuhan and Beijing. Possible reasons for such observed trends are given in this paper.

Integrated water vapour from GPS

Water vapour is highly variable in space and time, and plays a large role in atmospheric processes that act over a wide range of temporal and spatial scales on global climate to micrometeorology. This paper deals with a new approach to remotely sense the water vapour based on the Global Position System (GPS). The signal propagating from GPS satellites to ground based receivers is delayed by atmospheric water vapour. The delay is parameterized in terms of time varying Zenith-Wet Delay (ZWD), which is retrieved by stochastic filtering of GPS data. With the help of surface pressure and temperature readings at the GPS receiver, the retrieved ZWD can be transformed into Integrated Water Vapour (IWV) overlying at the receiver with little additional uncertainties. In this study the Zenith Total time Delay (ZTD) data without met package is retrieved using the GAMIT (King and Bock, 1997) GPS data processing software developed by Massachusetts Institute of Technology (MIT) for the period of January 2003 to February 2003 for two stations New Delhi and Bangalore .The IWV retrieved from GPS and its comparison with Limited Area Model (LAM) retrieved IWV shows fairly good agreement.

Estimation of precipitable water vapour from GPS during winter season 2003

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A Model for the Relationship between Rainfall, GNSS-Derived Integrated Water Vapour, and CAPE in the Eastern Central Andes

Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.

Integrated water vapour observations in the Caribbean arc from a network of ground-based GNSS receivers during EUREC⁴A

Ground-based Global Navigation Satellite System (GNSS) measurements from nearly 50 stations distributed over the Caribbean arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality integrated water vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the trade winds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD)-to-IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams International Airport (GAIA), Bridgetown, Barbados. A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2), where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a collocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth-generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS-derived IWV peaks. Two successive peaks are observed on 22 January and 23–24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organization for five representative GNSS stations across the Caribbean arc using visible satellite images. A statistically significant link was found between the cloud patterns and the local IWV observations from the GNSS sites as well as the larger-scale IWV patterns from the ECMWF ERA5 reanalysis. The reprocessed ZTD and IWV data sets from 49 GNSS stations used in this study are available from the French data and service centre for atmosphere (AERIS) (https://doi.org/10.25326/79; Bock, 2020b).

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC⁴A

In the framework of the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2, which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2, reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre (https://en.aeris-data.fr/, last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively.

Sensitivity of segmentation of GNSS IWV time series and trend estimates to data properties

<p>Homogenization is an important step to improve the quality of long-term observational data sets and estimate climatic trends. In this work, we use the GNSSseg/GNSSfast segmentation packages that were developed by Quarello et al., 2020, for the detection of abrupt changes in the mean of Integrated Water Vapour (IWV) data derived from GNSS measurements. The method works on the difference of the IWV time series (GNSS – reference) in order to cancel out the common climatic variations and enhance the discontinuities due to the inhomogeneities in the GNSS series. This segmentation method accounts for changes in the variance on fixed intervals (monthly) and a periodic bias (annual) due to representativeness differences between GNSS and the reference (in our case, a global atmospheric reanalysis). <br>The goal of this study is to analyze the sensitivity of the segmentation method to the data properties, particularly the GNSS data processing method. Two reprocessed GNSS solutions are considered: IGS repro1, covering the period 1995-2010, and CODE REPRO2015 + OPER, covering the period 1994-2018. Next, the impact of the length of time series and missing data are investigated. Finally, the use of two different reference series is considered (ERA-Interim and ERA5 reanalyses).<br>The segmentation results are screened for outliers (multiple detections occurring within a distance of 80 days) and validated with respect to known equipment changes (from GNSS metadata). The impact of the data properties is analyzed by comparing the number and position of detected change-points and the fraction of validated change-points. The influence of the variance of the IWV difference series and the magnitude of the periodic bias is examined. Finally, the results are compared in terms of estimated linear trends taking the detected change-points into account.<br>From the multiple comparisons, we found that about 30 % of change points are similar when the GNSS processing method changed, while 60 % are similar when the CODE series is shortened to match the length of the repro1 series. These tests highlight that the segmentation results are processing-dependent and are affected by the length of the series. The impact of the data properties on the IWV trends and associated uncertainties are also quantified. Besides, it is important to note that the best segmentation result is found when the ERA5 reanalysis is used as a reference.</p>

First insight into thermodynamic profiles, IWV and LWP from ground-based microwave radiometers during MOSAiC

<p>The Arctic is currently experiencing a more rapid warming compared to the rest of the<br>world. This phenomenon, known as Arctic Amplification, is the result of several processes.<br>Within the Collaborative Research Centre on Arctic Amplification: Climate Relevant Atmospheric<br>and Surface Processes and Feedback Mechanisms (AC)3, our research focuses<br>on the influence of water vapour, the strongest greenhouse gas. The collection of data<br>about water vapour is essential to understand its impact on Arctic Amplification. Over<br>the past decades, a positive trend in integrated water vapour in the Arctic has been<br>identified using radiosondes and reanalyses for certain regions and seasons. However, inconsistent<br>magnitudes of the moistening trend in the reanalyses cause the need of a more<br>thorough investigation. While radiosondes offer precise measurements of thermodynamic<br>(temperature and humidity) profiles, they fail to capture the variability of water vapour<br>because of the low sampling rate (two to four sondes per day) and spatial coverage. To<br>obtain a more complete picture of water vapour variability, remote sensing instruments<br>(satellite- and ground-based) are used. Microwave radiometers (MWRs) onboard polar<br>orbiting satellites allow the coverage of the entire Arctic but suffer from uncertainties<br>related to surface emission. Observations at the surface gathered during the Multidisciplinary<br>drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign can<br>serve as reference measurements in the central Arctic for the assessment of water vapour<br>products from reanalyses, models and satellite retrievals.<br><br>In this study, we give a first insight into the variability of integrated water vapour (IWV),<br>liquid water path (LWP) and thermodynamic profiles retrieved from two ground-based<br>MWRs onboard the research vessel Polarstern throughout the MOSAiC campaign. The<br>first radiometer is a standard low frequency HATPRO system and the other one is the<br>high-frequency MiRAC-P, which is particularly suited for low water vapour contents. The<br>retrieved quantities are compared with radiosonde measurements. A first analysis reveals<br>that the IWV is very well captured by the MWR measurements. Over the observation<br>period (October 2019 - October 2020), a large variety of meteorological conditions occurred.<br>Besides the considerable seasonal cycle, which is especially interesting because of<br>the contrast between polar night and polar day, several synoptic events contribute to the<br>variety of conditions, which will be highlighted as well.</p><p><br>We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research<br>Foundation) — Project 268020496 — TRR 172, within the Transregional Collaborative Research Center<br>"Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms<br>(AC)3". Data used in this manuscript was produced as part of the international Multidisciplinary drifting<br>Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 and the<br>Polarstern expedition AWI_PS122_00.</p>

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A

<p>In the framework of the EUREC4A campaign, integrated water vapour (IWV) contents were retrieved over the open Tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels : R/V Atalante, R/V Maria S. Merian, and R/V Meteor. This study describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the ECMWF fifth ReAnalysis (ERA5), from the MODIS infra-red products, and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWVs retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (-1.62 kg/m2 for R/V Atalante and +0.65 kg/m2 for R/V Meteor) and a RMS difference about ~2.3 kg/m2. The results for the R/V Maria S. Merian are found  to be of poorer quality, with RMS difference of about 6 kg/m2 which are very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infra-red product show large RMS differences of 5-7 kg/m2, reflecting the enhanced uncertainties of this satellite product in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil.</p>