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Since 2011, the Global Energy and Water cycle Exchanges (GEWEX) Water Vapor Assessment (G-VAP) has provided performance analyses for state-of-the-art reanalysis and satellite water vapour products to the GEWEX Data and Analysis Panel (GDAP) and the user community in general. A significant component of the work undertaken by G-VAP is to characterise the quality and uncertainty of these water vapour records to (i) ensure full exploitation and (ii) avoid incorrect use or interpretation of results. This study presents results from the second phase of G-VAP, where we have extended and expanded our analysis of total column water vapour (TCWV) from phase 1, in conjunction with updating the G-VAP archive. For version 2 of the archive, we consider 28 freely available and mature satellite and reanalysis data products, remapped to a regular longitude–latitude grid of 2° × 2° and on monthly time steps between January 1979 and December 2019. We first analysed all records for a "common" short period of 5 years (2005–2009), focusing on variability (spatial and seasonal) and deviation from the ensemble mean. We observed that clear-sky daytime-only satellite products were generally drier than the ensemble mean, and seasonal variability/disparity in several regions up to 12 kg m -2 related to original spatial resolution and temporal sampling. For 11 of the 28 data records, further analysis was undertaken between 1988–2014. Within this "long period", key results show (i) trends between - 1.18 ± 0.68 to 3.82 ± 3.94 kg m -2 per decade and - 0.39 ± 0.27 to 1.24 ± 0.85 kg m -2 per decade were found over ice-free global oceans and land surfaces, respectively, and (ii) regression coefficients of TCWV against surface temperatures of 6.17 ± 0.24 to 27.02 ± 0.51 % K -1 over oceans (using sea surface temperature) and 3.00 ± 0.17 to 7.77 ± 0.16 % K -1 over land (using surface air temperature). It is important to note that trends estimated within G-VAP are used to identify issues in the data records rather than analyse climate change. Additionally, breakpoints have been identified and characterised for both land and ocean surfaces within this period. Finally, we present a spatial analysis of correlations to six climate indices within the long period, highlighting regional areas of significant positive and negative correlation and the level of agreement among records. [ABSTRACT FROM AUTHOR]

Since 2011 the Global Energy and Water cycle Exchanges (GEWEX) Water Vapor Assessment (G-VAP) has provided performance analyses for state-of-the-art reanalysis and satellite water vapour products to the GEWEX Data and Analysis Panel (GDAP) and the user community in general. A significant component of the work undertaken by G-VAP is to characterise the quality and uncertainty of these water vapour records to; i) ensure full exploitation and ii) avoid incorrect use or interpretation of results. This study presents results from the second phase of G-VAP, where we have extended and expanded our analysis of Total Column Water Vapour (TCWV) from phase 1, in conjunction with updating the G-VAP archive. For version 2 of the archive, we consider 28 freely available and mature satellite and reanalysis data products, remapped to a regular longitude-latitude grid of 2°× 2°, and on monthly time steps between January 1979 and December 2019. We first analysed all records for a 'common' short period of five years (2005–2009), focusing on variability (spatial & seasonal) and deviation from the ensemble mean. We observed that clear-sky daytime-only satellite products were generally drier than the ensemble mean, and seasonal variability/disparity in several regions up to 12 kg/m2 related to original spatial resolution and temporal sampling. For 11 of the 28 data records, further analysis was undertaken between 1988–2014. Within this 'long period', key results show i) trends between -1.18±0.68 to 3.82±3.94 kg/m2/decade and -0.39±0.27 to 1.24±0.85 kg/m2/decade were found over ice-free global oceans and land surfaces respectively, and ii) regression coefficients of TWCV against surface temperatures of 6.17±0.24 to 27.02±0.51 %/K over oceans (using sea surface temperature) and 3.00±0.17 to 7.77±0.16 %/K over land (using surface air temperature). It is important to note that trends estimated within G-VAP are used to identify issues in the data records rather than analyse climate change. Additionally, breakpoints have been identified and characterised for both land and ocean surfaces within this period. Finally, we present a spatial analysis of correlations to six climate indices within the "long period", highlighting regional areas of significant positive and negative correlation and the level of agreement among records. [ABSTRACT FROM AUTHOR]

This study presents the first full annual cycle (2019–2020) of ambient surface aerosol particle number concentration measurements (condensation nuclei > 20 nm , N20) collected at Summit Station (Summit), in the centre of the Greenland Ice Sheet (72.58 ∘ N, - 38.45 ∘ E; 3250 ma.s.l.). The mean surface concentration in 2019 was 129 cm-3 , with the 6 h mean ranging between 1 and 1441 cm-3. The highest monthly mean concentrations occurred during the late spring and summer, with the minimum concentrations occurring in February (mean: 18 cm-3). High- N20 events are linked to anomalous anticyclonic circulation over Greenland and the descent of free-tropospheric aerosol down to the surface, whereas low- N20 events are linked to anomalous cyclonic circulation over south-east Greenland that drives upslope flow and enhances precipitation en route to Summit. Fog strongly affects particle number concentrations, on average reducing N20 by 20 % during the first 3 h of fog formation. Extremely-low- N20 events (< 10 cm-3) occur in all seasons, and we suggest that fog, and potentially cloud formation, can be limited by low aerosol particle concentrations over central Greenland. [ABSTRACT FROM AUTHOR]

This study presents the first full annual cycle (2019-2020) of ambient surface aerosol number concentration (condensation nuclei > 20 nm, N20) measurements collected at Summit Station, in the centre of the Greenland Ice Sheet (72.58° N, -38.45° E, 3250 m asl). The mean surface N20 concentration in 2019 was 129 cm-3, with the 6 h mean ranging between 1 cm-3 and 1441 cm-3. The highest monthly mean concentrations occurred during the late spring and summer, with the minimum concentrations occurring in February (mean: 18 cm-3), demonstrating an opposite seasonal cycle in aerosol concentrations compared to low altitude Arctic stations (with latitudes > 66°N). High aerosol concentration events are linked to anomalous anticyclonic circulation over Greenland and the descent of free tropospheric aerosol down to the surface, whereas low aerosol concentration events are linked to cyclonic circulation over south-east Greenland that drives upslope flow and enhances precipitation en-route to Summit. Fog strongly effects N[sub 20] concentrations, on average reducing N20 by 20% during the first three hours of fog formation. Extremely low N20 concentrations (< 10 cm-3) occur in all seasons, and we suggest that fog, and potentially cloud formation, can be limited by low aerosol concentrations over central Greenland. [ABSTRACT FROM AUTHOR]

We use the CloudSat 2006–2016 data record to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high-snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200 m above the local topography as defined by IceBridge. We then use ground-based millimeter wavelength cloud radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z – S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z – S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34±7.5 cm yr -1 liquid equivalent (where the uncertainty is determined by the range in values between the three different Z – S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30 cm yr -1 liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24 cm yr -1 , depending on the assumed snowpack density and from CloudSat 23±4.5 cm yr -1. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned underestimation during summer months. [ABSTRACT FROM AUTHOR]

Marine stratocumulus (Sc) clouds play an essential role in the earth radiation budget. Here, we compare liquid water path (LWP), cloud optical thickness (τ ), and cloud droplet effective radius (re) retrievals from 2 years of collocated Spinning Enhanced Visible and Infrared Imager (SEVIRI), Moderate Resolution Imaging Spectroradiometer (MODIS), and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations; estimate the effect of biomass burning smoke on passive imager retrievals; and evaluate the diurnal cycle of South Atlantic marine Sc clouds. The effect of absorbing aerosols from biomass burning on the retrievals was investigated using the aerosol index (AI) obtained from the Ozone Monitoring Instrument (OMI). SEVIRI and MODIS LWPs were found to decrease with increasing AI relative to TMI LWP, consistent with well-known negative visible/near-infrared (VIS/NIR) retrieval biases in τ and re. In the aerosol-affected months of July--August--September, SEVIRI LWP -- based on the 1.6 µm re -- was biased low by 14 g m-2 (~ 16 %) compared to TMI in overcast scenes, while MODIS LWP showed a smaller low bias of 4 g m-2 (~ 5 %) for the 1.6 µm channel and a high bias of 8 g m-2 (~ 10 %) for the 3.7 µm channel compared to TMI. Neglecting aerosol-affected pixels reduced the mean SEVIRI--TMI LWP bias considerably. For 2 years of data, SEVIRI LWP had a correlation with TMI and MODIS LWP of about 0.86 and 0.94, respectively, and biases of only 4-8 g m-2 (5 %-10 %) for overcast cases. The SEVIRI LWP diurnal cycle was in good overall agreement with TMI except in the aerosol-affected months. Both TMI and SEVIRI LWP decreased from morning to late afternoon, after which a slow increase was observed. Terra and Aqua MODIS mean LWPs also suggested a similar diurnal variation. The relative amplitude of the 2-year-mean and seasonal-mean LWP diurnal cycle varied between 35% and 40% from morning to late afternoon for overcast cases. The diurnal variation in SEVIRI LWP was mainly due to changes in τ, while re showed only little diurnal variability. [ABSTRACT FROM AUTHOR]

Marine stratocumulus (Sc) clouds play an essential role in the earth radiation budget. Here, we compare liquid water path (LWP), optical thickness (COT), and effective radius (CER) retrievals from two years of collocated Spinning Enhanced Visible and InfraRed Imager (SEVIRI), MODerate resolution Imaging Spectroradiometer (MODIS), and Tropical Rainfall Measuring Mission Microwave Imager (TMI) observations, estimate the effect of biomass burning smoke on passive imager retrievals, as well as evaluate the diurnal cycle of South Atlantic marine Sc clouds. The effect of absorbing aerosols from biomass burning on the retrievals was investigated using aerosol index (AI) obtained from the Ozone Monitoring Instrument (OMI). SEVIRI and MODIS LWPs were found to decrease with increasing AI relative to TMI LWP, consistent with well-known negative visible/near-infrared retrieval biases in COT and CER. In the aerosol-affected months of July–August–September, SEVIRI LWP – based on the 1.6-µm CER – was biased low by 14 g m−2 (~ 16 %) compared to TMI in overcast scenes, while MODIS LWP showed a smaller low bias of 4 g m−2 (~ 5 %) for the 1.6-µm channel and a high bias of 8 g m−2 (~ 10 %) for the 3.7-µm channel compared to TMI. Neglecting aerosol-affected pixels reduced the mean SEVIRI-TMI LWP bias considerably. On a two-year data base, SEVIRI LWP had a correlation with TMI and MODIS LWP of about 0.86 and 0.94, respectively, and biases of only 4–8 g m−2 (5–10 %) for overcast cases. The SEVIRI LWP diurnal cycle was in good overall agreement with TMI except in the aerosol-affected months. Both TMI and SEVIRI LWP decreased from morning to late afternoon, after which a slight increase was observed. Terra and Aqua MODIS mean LWPs also suggested a similar diurnal variation. The relative amplitude of the two-year mean and seasonal mean LWP diurnal cycle varied between 35–40 % from morning to late afternoon for overcast cases. The diurnal variation in SEVIRI LWP was mainly due to changes in COT, while CER showed only little diurnal variability. [ABSTRACT FROM AUTHOR]

A novel method for classifying Arctic precipitation using ground based remote sensors is presented. Using differences in the spectral variation of microwave absorption and scattering properties of cloud liquid water and ice, this method can distinguish between different types of snowfall events depending on the presence or absence of condensed liquid water in the clouds that generate the precipitation. The classification reveals two distinct, primary regimes of precipitation over the Greenland Ice Sheet (GIS): one originating from fully glaciated ice clouds and the other from mixed-phase clouds. Five years of co-located, multiinstrument data from the Integrated Characterization of Energy, Clouds, Atmospheric state and Precipitation at Summit (ICECAPS) are used to examine cloud and meteorological properties and patterns associated with each precipitation regime. The occurrence and accumulation of the precipitation regimes are identified and quantified. Cloud and precipitation observations from additional ICECAPS instruments illustrate distinct characteristics for each regime. Additionally, reanalysis products and back-trajectory analysis show different synoptic-scale forcings associated with each regime. Precipitation over the central GIS exhibits unique microphysical characteristics due to the high surface elevations as well as connections to specific large-scale flow patterns. Snowfall originating from the ice clouds is coupled to deep, frontal cloud systems advecting up and over the southeast Greenland coast to the central GIS. These events appear to be associated with individual storm systems generated by low pressure over Baffin Bay and Greenland lee cyclogenesis. Snowfall originating from mixed-phase clouds is shallower and has characteristics typical of supercooled cloud liquid water layers, and slowly propagates from the south and southwest of Greenland along a quiescent flow above the GIS. [ABSTRACT FROM AUTHOR]

The Global Energy and Water cycle Exchanges (GEWEX) Data and Assessments Panel (GDAP) initiated the GEWEX Water Vapor Assessment (G-VAP), which has the main objectives to quantify the current state of art in water vapour products being constructed for climate applications and to support the selection process of suitable water vapour products by GDAP for its production of globally consistent water and energy cycle products. During the construction of the G-VAP data archive, freely available and mature satellite and reanalysis data records with a minimum temporal coverage of 10 years were considered. The archive contains total column water vapour (TCWV) as well as specific humidity and temperature at four pressure levels (1000, 700, 500, 300 hPa) from 22 different data records. All data records were remapped to a regular longitude/latitude grid of 2° × 2°. The archive consists of four different folders: 22 TCWV data records covering the period 2003-2008, 11 TCWV data records covering the period 1988-2008, as well as seven specific humidity and seven temperature data records covering the period 1988-2009. The G-VAP data archive is referenced under the following digital object identifier (doi): doi:10.5676/EUM_SAF_CM/GVAP/V001. Within G-VAP, the characterisation of water vapour products is, among other ways, achieved through intercomparisons of the considered data records, as a whole and grouped into three classes of predominant retrieval condition: clear-sky, cloudy-sky and all-sky. Associated results are shown using the 22 TCWV data records. The standard deviations among the 22 TCWV data records have been analysed and exhibit distinct maxima over central Africa and the tropical warm pool (in absolute terms) as well as over the poles and mountain regions (in relative terms). The variability in TCWV within each class can be large and prohibits conclusions on systematic differences in TCWV between the classes. [ABSTRACT FROM AUTHOR]

A novel method for classifying Arctic precipitation using ground based remote sensors is presented. Using differences in the spectral variation of microwave absorption and scattering properties of cloud liquid water and ice, this method can distinguish between different types of snowfall events depending on the presence or absence of condensed liquid water in the clouds that generate the precipitation. The classification reveals two distinct, primary regimes of precipitation over the Greenland Ice Sheet (GIS): one originating from fully glaciated ice clouds and the other from mixed-phase clouds. Five years of co-located, multi-instrument data from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit (ICECAPS) are used to examine cloud and meteorological properties and patterns associated with each precipitation regime. The occurrence and accumulation of the precipitation regimes are identified and quantified. Cloud and precipitation observations from additional ICECAPS instruments illustrate distinct characteristics for each regime. Additionally, reanalysis products and back-trajectory analysis show different synoptic-scale forcings associated with each regime. Precipitation over the central GIS exhibits unique microphysical characteristics due to the high surface elevations as well as connections to specific large-scale flow patterns. Snowfall originating from the ice clouds is coupled to deep, frontal cloud systems advecting up and over the southeast Greenland coast to the central GIS. These events appear to be associated with individual storm systems generated by low pressure over Baffin Bay and Greenland lee cyclogenesis. Snowfall originating from mixed-phase clouds is shallower and has characteristics typical of supercooled cloud liquid water layers, and slowly propagates from the south and southwest Greenland along a quiescent flow above the GIS. [ABSTRACT FROM AUTHOR]

We present and evaluate a climatology of cloud droplet number concentration (CDNC) based on 13 years of Aqua-MODIS observations. The climatology provides monthly mean 1×1° CDNC values plus associated uncertainties over the global ice-free oceans. All values are incloud values, i.e. the reported CDNC value will be valid for the cloudy part of the grid box. Here, we provide an overview of how the climatology was generated and assess and quantify potential systematic error sources including effects of broken clouds, and remaining artefacts caused by the retrieval process or related to observation geometry. Retrievals and evaluations were performed at the scale of initial MODIS observations (in contrast to some earlier climatologies, which were created based on already gridded data). This allowed us to implement additional screening criteria, so that observations inconsistent with key assumptions made in the CDNC retrieval could be rejected. Application of these additional screening criteria led to significant changes in the annual cycle of CDNC in terms of both its phase and magnitude. After an optimal screening was established a final CDNC climatology was generated. Resulting CDNC uncertainties are reported as monthly-mean standard deviations of CDNC over each 1Γ1° grid box. These uncertainties are of the order of 30% in the stratocumulus regions and 60 to 80% elsewhere. [ABSTRACT FROM AUTHOR]

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua-MODIS (Moderate Resolution Imaging Spectroradiometer) collections 5.1 (C5.1) and 6 (C6) cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1° ×1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS cloud product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above-cloud emission, cloud-top pressure (CTP), and pixel registration. Global results show a neutral to positive (> 50 cm--3) change for C6-derived CDNC relative to C5.1 for the 1.6 and 2.1 μm channel retrievals, corresponding to a neutral to--2 μm difference in droplet effective radius (re/. For 3.7 μm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning --25 to +50 cm--3 related to a +2.5 to --1 μm transition in effective radius. Cloud optical thickness (τ) differences were small relative to effective radius and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant inter-collection differences in aggregated values of effective radius due to changes to the precomputed retrieval lookup tables (LUTs) for ocean scenes, changes to retrieved cloud-top pressure, solar irradiance, or above-cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS-derived climatologies and validation studies of effective radius and CDNC. [ABSTRACT FROM AUTHOR]

The microwave radiometers (MWRs) on board the European Remote Sensing Satellites 1 and 2 (ERS-1 and ERS-2) and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new total column water vapour (TCWV) and wet tropospheric correction (WTC) dataset that builds on this time series. We use a one-dimensional variational approach to derive TCWV from MWR observations and ERAInterim background information. A particular focus of this study lies on the intercalibration of the three different instruments, which is performed using constraints on liquid water path (LWP) and TCWV. Comparing our MWR-derived time series of TCWV against TCWV derived from Global Navigation Satellite System (GNSS) we find that the MWR-derived TCWV time series is stable over time. However, observations potentially affected by precipitation show a degraded performance compared to precipitation-free observations in terms of the accuracy of retrieved TCWV. An analysis of WTC shows further that the retrieved WTC is superior to purely ERA-Interim-derived WTC for all satellites and for the entire time series. Even compared to the European Space Agency's (ESA) operational WTC retrievals, which incorporate in addition to MWR additional observational data, the here-described dataset shows improvements in particular for the mid-latitudes and for the two earlier satellites, ERS-1 and ERS-2. [ABSTRACT FROM AUTHOR]

Representative parameters of the scan geometry are empirically determined for the Global Precipitation Measurement (GPM) Microwave Imager (GMI). Effective fields of view (EFOVs) are computed for the GMI's 13 channels, taking into account the blurring effect of the measurement interval on the instantaneous fields of view (IFOVs). Using a Backus-Gilbert procedure, coefficients are derived that yield an approximate spatial match between synthetic EFOVs of different channels, using the 18.7 GHz channels as a target and with due consideration of the tradeoff between the quality of the fit and noise amplification and edge effects. Modest improvement in resolution is achieved for the 10.65 GHz channels, albeit with slight "ringing" in the vicinity of coastlines and other sharp brightness temperature gradients. For all other channels, resolution is coarsened to approximate the 18.7 GHz EFOV. It is shown that the resolution matching procedure reduces nonlinear correlations between channels in the presence of coastlines as well as enables the more efficient separation of large brightness temperature variations due to coastlines from the much smaller variations due to other geophysical variables. As a byproduct of this work, we report accurate EFOV resolutions as well as a self-consistent set of parameters for modeling the scan geometry of the GMI. [ABSTRACT FROM AUTHOR]

The Microwave Radiometers (MWR) on-board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new Total Column Water Vapour (TCWV) and Wet Tropospheric Correction (WTC) dataset that builds on this time series. We use a one-dimensional variational approach to derive TCWV from MWR observations and ERA-Interim background information. A particular focus of this study lies on the intercalibration of the three different instruments, which is performed using constraints on liquid water path (LWP) and TCWV. Comparing our MWR-derived time series of TCWV against TCWV derived from Global Navigation Satellite System (GNSS) we find that the MWR-derived TCWV time series is stable over time. However, observations potentially affected by precipitation show a degraded performance compared to precipitation-free observations in terms of the accuracy of retrieved TCWV. An analysis of WTC shows further that the retrieved WTC is superior to purely model-derived WTC for all satellites and for the entire time series. Even compared to operational WTC retrievals, which incorporate additional observational data, the here-described dataset shows improvements in particular for the mid-latitudes and for the two earlier satellites ERS-1 and ERS-2. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001. [ABSTRACT FROM AUTHOR]

Differences in cloud effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1°×1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all channel pairs are successfully retrieved for each pixel and for cases where one or more channel pairs are successful. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored. Global results show a neutral to positive (>50cm-3) change for C6-derived CDNC relative to C5.1 for the 1.6 and 2.1μm channel retrievals corresponding to a neutral to -2μm difference in droplet effective radius. For 3.7μm retrievals, CDNC results show a negative change in the tropics, with differences transitioning towards positive values with increasing latitude spanning (-25 to +50cm-3) related to a (+2.5 to -1μm) transition in effective radius. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each retrieval channel pair. Results from this study indicate significant intercollection differences in aggregated values of microphysical parameters which may have implications for existing MODIS derived climatologies and validation studies. [ABSTRACT FROM AUTHOR]

Representative parameters of the scan geometry are empirically determined for the Global Precipitation Measurement (GPM) Microwave Imager (GMI). Effective fields-of-view (EFOVs) are computed for the GMI's 13 channels taking into account the blurring effect of the measurement interval on the instantaneous fields-of-view (IFOVs). Using a Backus-Gilbert procedure, coefficients are derived that yield an approximate spatial match between synthetic EFOVs of different channels, using the 18.7 GHz channels as a target and with due consideration of the tradeoff between the quality of the fit and noise amplification and edge effects. Modest improvement in resolution is achieved in for the 10.65 GHz channels, albeit with slight "ringing" in the vicinity of coastlines and other sharp brightness temperature gradients. For all other channels, resolution is coarsened to approximate the 18.7 EFOV. [ABSTRACT FROM AUTHOR]

Multi-instrument, ground-based measurements provide unique and comprehensive data sets of the atmosphere for a specific location over long periods of time and resulting data compliment past and existing global satellite observations. This paper explores the effect of ice hydrometeors on ground-based, high-frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland, from 2010 to 2013. Data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 gm-2 or less, the cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high-frequency microwave channels: 90, 150, and 225 GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. This measured ice signature was then compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single-scattering properties for several ice habits. Initial model results compare well against the 4 years of summer season isolated ice signature in the highfrequency microwave channels. [ABSTRACT FROM AUTHOR]