Column Water Vapor Research Articles

Investigation and Analysis of All-Day Atmospheric Water Vapor Content over Xi’an Using Raman Lidar and Sunphotometer Measurements

All-day atmospheric water vapor content measurements determined by Raman lidar and a sunphotometer were combined to investigate the all-day variation characteristics in the water vapor distribution in Xi’an, China (34.233°N, 108.911°E). To enhance the daytime lidar performance, the wavelet threshold de-noising method is used to filter out the strong solar background light, and effective denoised results are demonstrated with the following optimization: wavelet sym6, the improved threshold function, and the improved threshold selection. The denoised system signal-to-noise ratio (SNR) for the water vapor daytime measurement is validated, with an enhancement of ~3.4 times up to a height of 3 km compared to that of the original signal. The time series of the atmospheric water vapor mixing ratio profiles and the obtained precipitable water vapor (PWV) measured by Raman lidar are used to reveal the temporal and spatial variations in water vapor, and the comparisons with the total column water vapor content (TCWV) measured by a sunphotometer validate the daytime variation trend of the water vapor. All-day continuous observations clearly present a consistent variation trend in the water vapor between the sunphotometer and Raman lidar measurements. The correlation analysis between TCWV and PWV at the layers below 850 hPa and below 700 hPa yields a good positive correlation coefficient (>0.75), indicating that PWV determination in the bottom layer by Raman lidar can directly reflect the variations in the total water vapor content. Moreover, different diurnal variation trends in water vapor are also observed, that is, a downward trend from the afternoon to the night, or a tendency of being high in the morning and afternoon and low at noon, demonstrating the high temporal-spatial variation characteristics of water vapor and close correlation with weather changes. The results reflected and validated that the diurnal variation in water vapor is complicated and can be an indicator of the weather to a certain extent.

Spectral Signatures of Moisture–Convection Feedbacks over the Indian Ocean

Abstract Positive feedbacks between the cloud population and the environmental moisture field are central to theoretical expositions on the Madden–Julian oscillation (MJO). This study investigates the statistical incidence of positive moisture–convection feedbacks across multiple space and time scales over the tropical Indian Ocean. This work uses vertically integrated moisture budget terms from the ECMWF interim reanalysis [ERA-Interim (ERA-I)] in a framework proposed by Hannah et al. Positive moisture–convection feedbacks are primarily a low-frequency, low-wavenumber phenomenon with significant spectral signatures in the 32–48-day time scale. The efficacy of these feedbacks, however, is subject to horizontal moisture advection variations, whose relative importance varies with scale. Wave-filtered Tropical Rainfall Measuring Mission (TRMM) satellite precipitation is used to show that these moisture–convection feedbacks contribute more to moisture increases in the MJO than in other equatorial waves. A moving-window correlation analysis suggests that instances of moisture–convection feedbacks are more frequent in drier conditions, when column water vapor (CWV) is below its climatological mean value, with the implication that positive moisture–convection feedbacks shape the mean CWV field by moistening drier air columns, but that they are less effective in moistening already moist environments. Ground radar observations show that stratiform rain damps local CWV increases on short time scales (<2 days) and therefore precludes positive moisture–convection feedbacks in high-CWV environments. Vertical coherence structures from ERA-I confirm that relatively bottom-heavy cloud ensembles (i.e., peaks between 700 and 850 hPa) are more effective in inducing low-frequency positive moisture–convection feedbacks than ensembles with other vertical structures. Low-frequency horizontal advective drying damps moisture increases and is strongly coherent with upper-level rising motion.

Seasonal and interannual assessment of cloud cover and atmospheric constituents across the Amazon (2000–2015): Insights for remote sensing and climate analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (>80%) throughout the year, while low cloud cover (0–20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon – unlike previous droughts. The water vapor presents high concentration values (4.0–5.0 g cm−2) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content (∼0.3 g/cm2) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25–35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY

Abstract. Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total column water vapour (TCWV) datasets derived from ground-based GNSS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GNSS and satellite data are carried out for three reference Arctic observation sites (Sodankylä, Ny-Ålesund and Thule) where long homogeneous GNSS time series of more than a decade (2001–2014) are available. We select hourly GNSS data that are coincident with overpasses of the different satellites over the three sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GNSS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GNSS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high-latitude stations during autumn and winter). SCIAMACHY TCWV data are generally drier than GNSS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Ålesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankylä during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankylä. The MODIS bias at Sodankylä is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally dependent surface albedo and a better consideration of vertically resolved cloud cover are recommended if biases in satellite measurements are to be reduced in the polar regions.

The Madden‐Julian Oscillation and the Indo‐Pacific Warm Pool

AbstractA minimal model of the interaction of the Madden‐Julian oscillation (MJO) with the Indo‐Pacific warm pool is presented. This model is based on the linear superposition of the flow associated with a highly simplified treatment of the MJO plus the flow induced by the warm pool itself. Both of these components parameterize rainfall as proportional to the column water vapor, which in turn is governed by a linearized moisture equation in which WISHE (wind induced surface heat exchange) plays a governing role. The MJO component has maximum growth rate for planetary wavenumber 1 and is equatorially trapped with purely zonal winds. The warm pool component exhibits a complex flow pattern, differing significantly from the classical Gill model as a result of the mean easterly flow. The combination of the two produce a flow that reproduces many aspects of the observed global flow associated with the MJO.

Extensive validation of solar spectral irradiance meters at the World Radiation Center

A comprehensive uncertainty analysis validates a Solar Spectral Irradiance Meter (SolarSIM) for accurately resolving the spectral and broadband direct normal irradiances (DNI), spectral aerosol optical depth (AOD), precipitable water vapour and atmospheric total column ozone amounts. The derivation of these parameters from four SolarSIMs were compared to reference instrumentation at the Physikalisch-Meteorologisches Observatorium Davos and World Radiation Center (PMOD/WRC) in Davos, Switzerland in September 2015. The SolarSIMs are the first instruments to ever simultaneously participate in the 12th WMO International Pyrheliometer Comparison, Fourth Filter Radiometer Comparison, and First Spectroradiometer Comparison. The SolarSIMs’ DNI data were compared to the World Standard Group’s PMO2 absolute cavity radiometer, with World Radiometric Reference factors ranging from 0.999674 to 0.994610 for the best and the worst performing devices, respectively. In addition, the SolarSIMs’ spectral DNI data was compared against PMOD’s Precision Spectral Radiometer. The mean difference of the spectral DNI was found to be less than 5% for wavelengths above 400 nm. The SolarSIMs’ measurements of AOD data were compared against PMOD’s Precision Filter Radiometer triad. The median AOD differences and their standard deviations were found to be 0.0046 ± 0.0044, 0.0016 ± 0.0034, 0.0018 ± 0.0026, and 0.0041 ± 0.0022 for 368 nm, 412 nm, 500 nm, and 865 nm, respectively. The SolarSIMs’ measurements of precipitable water vapour were compared against PMOD’s Cimel CE318 sun photometer. The median difference and the corresponding standard deviation averaged 1 ± 0.2 mm for all SolarSIMs. Furthermore, the SolarSIMs’ measurements of total column atmospheric ozone were compared against PMOD’s Brewer MkIII spectrophotometer. The median difference and the corresponding standard deviation averaged 6 ± 7 DU for all SolarSIMs.

Validation of the Advanced Infra-Red Water Vapour Estimator (AIRWAVE) Total Column Water Vapour using Satellite and Radiosonde products.

The Along Track Scanning Radiometer (ATSR) instrument series, on board the European Space Agency (ESA)’s European Remote Sensing (ERS) satellites, ERS-1/2 and the ENVIronmental SATellite (ENVISAT), covered the time period from 1991 to 2012. Using the infra-red channels at 11 and 12 microns (available for both day and night and for all the three instruments) and combining nadir and forward geometries, Total Column Water Vapour (TCWV) fields have been obtained over the sea in cloud free scenarios. The retrieval scheme, named Advanced InfraRed Water Vapor Estimator (AIRWAVE), exploits the instrument physical characteristics (dual view and two channels), in combination with advanced radiative transfer models and a sea surface spectral emissivity database. The algorithm makes use of a set of tabulated parameters, fixed along the whole globe. Here, the AIRWAVE dataset is compared with the satellite data of the Special Sensor Microwave/Imager (SSM/I) and with available stations from the Analyzed RadioSoundings Archive (ARSA). Both comparisons demonstrated the good quality of the AIRWAVE dataset. However, they also highlighted the presence of a dry bias at high latitudes. Globally, we found an average correlative-AIRWAVE bias of 0.72 kg/m2 (RMSE=5.79 kg/m2) vs SSM/I and 0.80 kg/m2 (RMSE=7.77 kg/m2) vs ARSA.

The ESA GOME-Evolution “Climate” water vapor product: a homogenized time series of H<sub>2</sub>O columns from GOME, SCIAMACHY, and GOME-2

Abstract. We present time series of the global distribution of water vapor columns over more than 2 decades based on measurements from the satellite instruments GOME, SCIAMACHY, and GOME-2 in the red spectral range. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. Potentially systematic effects due to differences in ground pixel size are avoided by merging SCIAMACHY and GOME-2 observations to GOME spatial resolution, which also allows for a consistent treatment of cloud effects. In addition, the GOME-2 swath is reduced to that of GOME and SCIAMACHY to have consistent viewing geometries.Remaining systematic differences between the different sensors are investigated during overlap periods and are corrected for in the homogenized time series. The resulting Climate product v2.2 (https://doi.org/10.1594/WDCC/GOME-EVL_water_vapor_clim_v2.2) allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.

An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band

Land surface temperature (LST) is one of the sources of input data for modeling land surface processes. The Landsat satellite series is the only operational mission with more than 30 years of archived thermal infrared imagery from which we can retrieve LST. Unfortunately, stray light artifacts were observed in Landsat-8 TIRS data, mostly affecting Band 11, currently making the split-window technique impractical for retrieving surface temperature without requiring atmospheric data. In this study, a single-channel methodology to retrieve surface temperature from Landsat TM and ETM+ was improved to retrieve LST from Landsat-8 TIRS Band 10 using near-surface air temperature (Ta) and integrated atmospheric column water vapor (w) as input data. This improved methodology was parameterized and successfully evaluated with simulated data from a global and robust radiosonde database and validated with in situ data from four flux tower sites under different types of vegetation and snow cover in 44 Landsat-8 scenes. Evaluation results using simulated data showed that the inclusion of Ta together with w within a single-channel scheme improves LST retrieval, yielding lower errors and less bias than models based only on w. The new proposed LST retrieval model, developed with both w and Ta, yielded overall errors on the order of 1 K and a bias of −0.5 K validated against in situ data, providing a better performance than other models parameterized using w and Ta or only w models that yielded higher error and bias.

A southward withdrawal of the northern edge of the East Asian summer monsoon around the early 1990s

The northern edge of the East Asian summer monsoon (EASM) is identified using the pentad total column water vapor obtained from ERA-Interim reanalysis data during 1979–2015. Empirical orthogonal fu...

Tropical continental downdraft characteristics: mesoscale systems versus unorganized convection

Abstract. Downdrafts and cold pool characteristics for strong mesoscale convective systems (MCSs) and isolated, unorganized deep precipitating convection are analyzed using multi-instrument data from the DOE Atmospheric Radiation Measurement (ARM) GoAmazon2014/5 campaign. Increases in column water vapor (CWV) are observed leading convection, with higher CWV preceding MCSs than for isolated cells. For both MCSs and isolated cells, increases in wind speed, decreases in surface moisture and temperature, and increases in relative humidity occur coincidentally with system passages. Composites of vertical velocity data and radar reflectivity from a radar wind profiler show that the downdrafts associated with the sharpest decreases in surface equivalent potential temperature (θe) have a probability of occurrence that increases with decreasing height below the freezing level. Both MCSs and unorganized convection show similar mean downdraft magnitudes and probabilities with height. Mixing computations suggest that, on average, air originating at heights greater than 3 km must undergo substantial mixing, particularly in the case of isolated cells, to match the observed cold pool θe, implying a low typical origin level. Precipitation conditionally averaged on decreases in surface equivalent potential temperature (Δθe) exhibits a strong relationship because the most negative Δθe values are associated with a high probability of precipitation. The more physically motivated conditional average of Δθe on precipitation shows that decreases in θe level off with increasing precipitation rate, bounded by the maximum difference between surface θe and its minimum in the profile aloft. Robustness of these statistics observed across scales and regions suggests their potential use as model diagnostic tools for the improvement of downdraft parameterizations in climate models.

The Meandering Margin of the Meteorological Moist Tropics

AbstractBimodally distributed column water vapor (CWV) indicates a well‐defined moist regime in the Tropics, above a margin value near 48 kg m−2 in current climate (about 80% of column saturation). Maps reveal this margin as a meandering, sinuous synoptic contour bounding broad plateaus of the moist regime. Within these plateaus, convective storms of distinctly smaller convective and mesoscales occur sporadically. Satellite data composites across the poleward most margin reveal its sharpness, despite the crude averaging: precipitation doubles within 100 km, marked by both enhancement and deepening of cloudiness. Transported patches and filaments of the moist regime cause consequential precipitation events within and beyond the Tropics. Distinguishing synoptic flows that cross the margin from flows that move the margin is made possible by a novel satellite‐based Lagrangian CWV tendency estimate. Climate models do not reliably reproduce the observed bimodal distribution, so studying the moist mode's maintenance processes and the margin‐zone air mass transformations, guided by the Lagrangian tendency product, might importantly constrain model moist process treatments.

An optimization approach to estimate and calibrate column water vapour for hyperspectral airborne data

ABSTRACTThe article describes a novel approach to estimate and calibrate column water vapour (CWV), a key parameter for atmospheric correction of remote-sensing data. CWV is spatially and temporally variable, and image-based methods are used for its inference. This inference, however, is affected by methodological and numeric limitations, which likely propagate to reflectance estimates. In this article, a method is proposed to estimate CWV iteratively from target surface reflectances. The method is free from assumptions for at sensor radiance-based CWV estimation methods. We consider two cases: (a) CWV is incorrectly estimated in a processing chain and (b) CWV is not estimated in a processing chain. To solve (a) we use the incorrect estimations as initial values to the proposed method during calibration. In (b), CWV is estimated without initial information. Next, we combined the two scenarios, resulting in a generic method to calibrate and estimate CWV. We utilized the hyperspectral mapper (HyMap) and airborne prism experiment (APEX) instruments for the synthetic and real data experiments, respectively. Noise levels were added to the synthetic data to simulate real imaging conditions. The real data used in this research are cloud-free scenes acquired from the airborne campaigns. For performance assessment, we compared the proposed method with two state-of-the-art methods. Our method performed better as it minimizes the absolute error close to zero, only within 8–10 iterations. It thus suits existing operational chains where the number of iterations is considerable. Finally, the method is simple to implement and can be extended to address other atmospheric trace gases.

Atmospheric Moisture Content over Europe and the Northern Atlantic

Water vapor plays a major role in the process of radiation, cloud formation, energy exchange within a system, and remains a key component of the Earth’s atmosphere. The purpose of this study is to examine the water vapor content of the troposphere over Europe and the Northern Atlantic. Both temporal and spatial differences were examined for total column water vapor (TCWV) and vertically integrated water vapor flux (IWVF) based on ERA-Interim reanalysis data. The statistical relationship between circulation patterns, as expressed by empirical orthogonal function (EOF) modes, and TCWV were examined, as were statistical relationships between distinguished advection types and TCWV and IWVF. The study confirmed the significance of atmospheric circulation in the formation of moisture content in the winter season (i.e., January) and its markedly lower impact in other seasons. The relationships noted in the study are characterized by statistically significant spatial differentiation. Spatial pattern analysis was used to identify six regions with different moisture content over the course of the year. The boundaries of the regions confirm the significant role of local factors impacting moisture content.

Optical, microphysical and radiative properties of aerosols over a tropical rural site in Kenya, East Africa: Source identification, modification and aerosol type discrimination

A better understanding of aerosol optical, microphysical and radiative properties is a crucial challenge for climate change studies. In the present study, column-integrated aerosol optical and radiative properties observed at a rural site, Mbita (0.42°S, 34.20 °E, and 1125 m above sea level) located in Kenya, East Africa (EA) are investigated using ground-based Aerosol Robotic Network (AERONET) data retrieved during January, 2007 to December, 2015. The annual mean aerosol optical depth (AOD500 nm), Ångström exponent (AE440–870 nm), fine mode fraction of AOD500 nm (FMF500 nm), and columnar water vapor (CWV, cm) were found to be 0.23 ± 0.08, 1.01 ± 0.16, 0.60 ± 0.07, and 2.72 ± 0.20, respectively. The aerosol optical properties exhibited a unimodal distribution with substantial seasonal heterogeneity in their peak values being low (high) during the local wet (dry) seasons. The observed data showed that Mbita and its environs are significantly influenced by various types of aerosols, with biomass burning and/or urban-industrial (BUI), mixed (MXD), and desert dust (DDT) aerosol types contributing to 37.72%, 32.81%, and 1.40%, respectively during the local dry season (JJA). The aerosol volume size distribution (VSD) exhibited bimodal lognormal structure with a geometric mean radius of 0.15 μm and 3.86–5.06 μm for fine- and coarse-mode aerosols, respectively. Further, analysis of single scattering albedo (SSA), asymmetry parameter (ASY) and refractive index (RI) revealed dominance of fine-mode absorbing aerosols during JJA. The averaged aerosol direct radiative forcing (ARF) retrieved from the AERONET showed a strong cooling effect at the bottom of the atmosphere (BOA) and significant warming within the atmosphere (ATM), representing the important role of aerosols played in this rural site of Kenya. Finally, the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model revealed that aerosols from distinct sources resulted in enhanced loading during JJA.

Prediction of the day-ahead clear-sky downwelling surface solar irradiances using the REST2 model and WRF-CHIMERE simulations over the Arabian Peninsula

The forecasting of the downwelling surface solar irradiances is required by the operators of solar powered plants to predict the power output of the plant. The purpose of this study is to use aerosol optical depth and columnar water vapor forecasts by the chemistry transport model CHIMERE, coupled with the Weather Research and Forecast (WRF) model, as inputs in the REST2 model to predict the day-ahead clear-sky global horizontal, direct normal and diffuse horizontal irradiances at hourly steps. A dataset of quality-assured and cloud-screened surface solar irradiance measurements collected from 44 sites scattered throughout Saudi Arabia was used to validate the predicted surface solar irradiances. The validation for the day-ahead forecasting of the clear-sky global horizontal irradiance for the data of all 44 stations combined exhibits a bias (relative to the mean reference value) of 0%, a relative root mean square error of 4% and a correlation coefficient of 0.993. Respectively, the clear-sky direct normal irradiance exhibits values of 0%, 15% and 0.769, while the clear-sky diffuse horizontal irradiance values are 0%, 35% and 0.542. The errors in the inputs are also investigated. The results are satisfactory and pave the way to the inclusion of the attenuation due to clouds with the final aim of predicting the surface solar irradiance under all-sky conditions.

A Comparative Study of Atmospheric Moisture Recycling Rate between Observations and Models

AbstractPrecipitation and column water vapor data from 13 CMIP5 models and observational datasets are used to analyze atmospheric moisture recycling rate from 1988 to 2008. The comparisons between observations and model simulations suggest that most CMIP5 models capture two main characteristics of the recycling rate: 1) long-term decreasing trend of the global-average maritime recycling rate (atmospheric recycling rate over ocean within 60°S–60°N) and 2) dominant spatial patterns of the temporal variations of the recycling rate (i.e., increasing in the intertropical convergence zone and decreasing in subtropical regions). All models, except one, successfully simulate not only the long-term trend but also the interannual variability of column water vapor. The simulations of precipitation are relatively poor, especially over the relatively short time scales, which lead to the discrepancy of the recycling rate between observations and the CMIP5 models. Comparisons of spatial patterns also suggest that the CMIP5 models simulate column water vapor better than precipitation. The comparative studies indicate the scope of improvement in the simulations of precipitation, especially for the relatively short-time-scale variations, to better simulate the recycling rate of atmospheric moisture, an important indicator of climate change.

Development of a One-Month-Long, Westward-Propagating Subtropical Low in Boreal Summer

Abstract A strong MJO event produced an upper-tropospheric jet streak in northeast Asia and repeated wave breaking in the jet exit region along 150°E during July 1988. A midlatitude low moved equatorward and intensified in the presence of bandpass-filtered (15–100 day) Q vector forcing for upward motion associated with the wave breaking. This forced ascent helped to moisten the atmosphere enough to increase the column water vapor to above 55 mm. This value was sufficiently large to support a self-sustaining low even after the upper forcing weakened. The horizontal scale of the Q vector forcing was about 1500 km, consistent with the scale of most favorable convective response to quasigeostrophic forcing in the subtropics described by Nie and Sobel. The low lasted one month as it moved southwestward, then westward, while remaining north of 20°N. Maximum precipitation along the track of the low exceeded 700 mm, with an anomaly more than 400 mm. A climatology of long-lasting lows was carried out for the monsoon gyre cases studied previously. During El Niño, long-lasting lows often began near the equator in the central Pacific, and were likely to have a mixed Rossby–gravity wave or equatorial Rossby wave structure. It is speculated that the quasi-biweekly mode, the submonthly oscillation, the 20–25-day mode, and the Pacific–Japan pattern are each variations on this kind of event. During La Niña, long-lasting lows that originated in midlatitudes were more common. It is argued that these lows from midlatitudes represent a unique disturbance type in boreal summer.

Connections of Precipitable Water Vapor and Total Ozone Anomalies over European Russia with the North Atlantic Oscillation: Specific Features of Summer 2010

Based on the measurements of precipitable water vapor (PWV) and total column ozone (TCO) from the MODIS satellite instruments (Aqua/Terra platforms), the connections between the North Atlantic Oscillation (NAO) and the anomalies in PWV and TCO over European Russia (ER) in summer 2010 are analyzed. It is found that the PWV (TCO) anomalies over the northern ER in summer 2010 positively (negatively) correlated with the NAO, and the local correlations reached 0.68 (–0.55). The physical mechanisms of the correlations are discussed. A comparative analysis of the relationships between the NAO and the regional PWV and TCO anomalies over ER during the summer seasons of 2000–2015 is carried out.

Total column water vapor estimation over land using radiometer data from SAC-D/Aquarius

The aim of this study is retrieving atmospheric total column water vapor (CWV) over land surfaces using a microwave radiometer (MWR) onboard the Scientific Argentine Satellite (SAC-D/Aquarius). To research this goal, a statistical algorithm is used for the purpose of filtering the study region according to the climate type.A log-linear relationship between the brightness temperatures of the MWR and CWV obtained from Global Navigation Satellite System (GNSS) measurements was used. In this statistical algorithm, the retrieved CWV is derived from the Argentinian radiometer’s brightness temperature which works at 23.8 GHz and 36.5 GHz, and taking into account CWVs observed from GNSS stations belonging to a region sharing the same climate type. We support this idea, having found a systematic effect when applying the algorithm; it was generated for one region using the previously mentioned criteria, however, it should be applied to additional regions, especially those with other climate types.The region we analyzed is in the Southeastern United States of America, where the climate type is Cfa (Köppen - Geiger classification); this climate type includes moist subtropical mid-latitude climates, with hot, muggy summers and frequent thunderstorms. However, MWR only contains measurements taken from over ocean surfaces; therefore the determination of water vapor over land is an important contribution to extend the use of the SAC-D/Aquarius radiometer measurements beyond the ocean surface. The CWVs computed by our algorithm are compared against radiosonde CWV observations and show a bias of about −0.6 mm, a root mean square (rms) of about 6 mm and a correlation of 0.89.