Rainwater Path Research Articles

Long-term characteristics of hydrometeors in stratiform and convective precipitation over central eastern China and adjacent ocean

Based on the fifth generation atmospheric reanalysis (ERA5) hourly data from May to August during 1979–2020, the long-term features of four hydrometeors (cloud water, cloud ice, rain, and snow) in stratiform and convective precipitation over the central eastern China and its adjacent northwest Pacific Ocean, as well as their relationship with precipitation intensity were first investigated. Results show that the ERA5 hydrometeor data is generally reasonable over the study regions by comparing with 7-yr GPM retrievals. In stratiform precipitation, the cloud water profile presents a double-peak structure over land and ocean. The distribution of precipitation intensity is in agreement with that of cloud ice path, indicating that stratiform precipitation is more dominated by ice processes, and the deposition latent heating is the main heat source. In convective precipitation, the rain water mixing ratio is distinctly greater over ocean than that over land due to the higher conversion rate from cloud droplets to raindrops, along with abundant snow water there. The pattern of convective precipitation intensity is more consistent with that of rain water path, and the ice-phase hydrometeor path is 1–2 times that of liquid-phase hydrometeor, suggesting a comparable contribution of water and ice processes. The condensation latent heating with its upward transport is the main heat source in convection. It's found that the conversion rate from rain water to surface rainfall is higher in convective than in stratiform regimes, and is faster over land than over ocean, which should be attributed to the larger-size raindrops in the former. In addition, the continental precipitation diurnal circle exhibits a bimodal structure, while the oceanic precipitation has only a single peak. The peaks of ice-phase hydrometeors lag behind the peak of precipitation in the afternoon owing to the different moisture dynamic structures.

Climatological Characteristics of Hydrometeors in Precipitating Clouds over Eastern China and Their Relationship with Precipitation Based on ERA5 Reanalysis

Abstract The long-term characteristics of four 15 hydrometeor species (cloud water, cloud ice, rain, and snow) in precipitating clouds over eastern China (dividing into South China, Jianghuai, and North China) and their relationships with surface rainfall are first investigated using the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) hourly dataset from May to August during 1979-2020. The results show that the cloud water path decreases significantly from south to north owing to the large-scale circulation and water vapor distribution, with the maximum value of 180 g m−2 in South China and only half in North China. The slope in linear relationship between rain water path and precipitation intensity is the maximum (5.68 h−1) in South China, implying the highest conversion rate from rain water to precipitation in this region. When the precipitation rate exceeds 15 mm h−1, the ice-phase hydrometeor contents in South China become the largest among three regions, indicating the cold rain process is crucial to the heavy rainfall. The moisture-related processes play a dominant role in the precipitation intensity. Though the contribution of hydrometeor advection to precipitation is generally between −5% and 5%, we found that it can jointly modulate the location of heavy rainfall. In addition, the peaks of cloud water path commonly appear 2-3 h ahead of precipitation, while the peaks of ice-phase particles occur 2 h and 1 h behind the afternoon precipitation onset in South China and Jianghuai, which is mainly attributed to the different upward velocity and water vapor convergence in the middle-upper troposphere.

Analysis of the Influence of Deforestation on the Microphysical Parameters of Clouds in the Amazon

Studies have shown that deforestation can cause changes in energy, moisture, and precipitation flows, with implications for local and regional climate. These studies generally focus on understanding how the hydrological cycle is impacted by deforestation, but few studies have investigated these impacts on cloud microphysics in tropical forest regions. The objective of this study was to quantitatively evaluate the impacts of deforestation on the microphysical parameters of clouds, based on data extracted from active and passive orbital sensors from the TRMM satellite. The study area comprised the state of Rondônia, Brazil. The analyses of the microphysical parameters extracted from the Microwave Imager (TMI) and Precipitation Radar (PR) sensors of the 2A-CLIM and 2A25 products were performed considering a period of 14 years. The parameters analyzed were Rain Water Path (RWP), Ice Water Path (IWP), Surface Precipitation (SP), Freezing Level Height (FH), and Rainfall Type (RT). Land cover type data were extracted from the Project to Monitor Deforestation in the Legal Amazon (PMDA). Our results showed that local deforestation significantly altered the microphysical parameters of the study region. In general, the values of the microphysical parameters of the clouds in the transition areas (locations where forest pixels are neighbors to deforested pixels) were about 5–25% higher compared to forested and deforested areas associated with a higher frequency of episodes of convective rainfall possibly driven by mesoscale circulations. Correspondingly, forested areas had higher rainfall rates compared to deforested areas. Meanwhile, deforested areas had higher amounts for IWP, of around 1–16%, and FH, of around 2–8%, in relation to forested areas. Conversely, the RWP showed a decrease of around 2–20%. These results suggest that the microphysical structure of clouds has different characteristics when related to forested and deforested areas in the Amazon. This is useful for evaluation of simulations of cloud microphysical parameters in numerical models of weather and climate.

Large‐eddy simulations of drizzling shallow cumuli using a turbulence‐aware autoconversion parametrization

AbstractTurbulence in clouds enhances collision between cloud droplets, which is critical to drizzle formation in shallow cumulus clouds. In this study, we develop an autoconversion parametrization that considers the turbulence‐induced collision enhancement (TICE) obtained from a particle trajectory model. We implement the developed parametrization to a large‐eddy simulation model and simulate the Rain In Cumulus over the Ocean (RICO) case to investigate the effects of TICE on shallow cumulus clouds and their sensitivities to the cloud droplet number concentration and horizontal grid resolution. TICE significantly increases the autoconversion rate, leading to large increases in the accretion rate, rainwater path and surface rain rate. The simulations of shallow cumulus clouds are highly sensitive to the cloud droplet number concentration and horizontal grid resolution, and the inclusion of TICE overall reduces the sensitivities. For example, the large rainwater path and surface rain rate that appear when cloud droplet number concentration is relatively low are reduced by TICE, whereas the very small rainwater path and surface rain rate that appear when cloud droplet number concentration is relatively high are increased by TICE. Comparisons with two other TICE‐aware parametrizations based on direct numerical simulation results of droplet collisions in turbulence show that there are substantial differences in TICE effects for different parametrizations, which implies a large uncertainty in simulating turbulent clouds. Among the three parametrizations, the parametrization developed in this study shows intermediate TICE‐induced increases in rainwater path and surface rain rate.

Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil

The Northeast region of Brazil (NEB) has a high rate of deaths from lightning strikes (18% of the country’s total). The region has states, such as Piauí, with high mortality rates (1.8 deaths per million), much higher than the national rate (0.8) and the NEB rate (0.5). In this sense, the present work analyzes the microphysical characteristics of clouds with and without the occurrence of total lightning. For this purpose, data from the Lightning Imaging Sensor (LIS), TRMM Microwave Imager (TMI) and Precipitation Radar (PR), aboard the Tropical Rainfall Measuring Mission (TRMM) satellite from 1998 to 2013 were used. The TRMM data were analyzed to establish a relationship between the occurrence of lightning and the clouds’ microphysical characteristics, comparing them as a function of lightning occurrence classes, spatial location and atmospheric profiles. A higher lightning occurrence is associated with higher values of ice water path (>38.9 kg m−2), rain water path (>2 kg m−2), convective precipitation (>5 mm h−1) and surface precipitation (>7 mm h−1), in addition to slightly higher freezing level height values. Reflectivity observations (>36 dBZ) demonstrated typical convective profile curves, with higher values associated with classes with higher lightning densities (class with more than 6.8 flash km−2 year−1).

Inference of Precipitation in Warm Stratiform Clouds Using Remotely Sensed Observations of the Cloud Top Droplet Size Distribution

AbstractDrizzle is a common feature of warm stratiform clouds and it influences their radiative effects by modulating their physical properties and lifecycle. An important component of drizzle formation are processes that lead to a broadening of the droplet size distribution (DSD). Here, we examine observations of cloud and drizzle properties retrieved using colocated airborne measurements from the Research Scanning Polarimeter and the Third Generation Airborne Precipitation Radar. We observe a bimodal DSD as the aircraft transects drizzling open‐cells whereby the larger mode reaches a maximum size near cloud center and the smaller mode remains relatively constant in size. We review similarities between our observations with droplet growth processes and their connections with precipitation onset. We estimate droplet sedimentation using the cloud top DSD and find a correlation with rain water path of 0.82. We also examine how changes in liquid water paths and droplet concentrations may act to enhance or suppress precipitation.

Joint cloud water path and rainwater path retrievals from airborne ORACLES observations

Abstract. This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ∼10 %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

Exploring the Assimilation of ATMS Cloud Retrieval Products and its Benefits for CrIS All-sky Radiance Simulations

AbstractAimed at improving all-sky Cross-track Infrared Sounder (CrIS) radiance assimilation, this study explores the benefits for CrIS all-sky radiance simulations, focusing on the accuracy of background cloud information, through assimilating cloud liquid water path (LWP), ice water path (IWP), and rain water path (RWP) data retrieved from the Advanced Technology Microwave Sounder (ATMS). The Community Radiative Transfer Model (CRTM), which considers cloud scattering and absorption processes, is applied to simulate CrIS radiances. The Gridpoint Statistical Interpolation ensemble-variational data assimilation (DA) is updated by incorporating ensemble covariances of hydrometeor variables and observation operators of LWP, IWP, and RWP. First, two DA experiments named DActrl and DAcwp are conducted with (DAcwp) and without (DActrl) assimilating ATMS LWP, IWP, and RWP data. Assimilating ATMS cloud retrieval data results in better spatial distributions of hydrometers for both a Meiyu rainfall case and a typhoon case. Analyses of DActrl and DAcwp are then used as input to the CRTM to generate CrIS all-sky radiance simulations SMallsky_DActrl and SMallsky_DAcwp, respectively. Improvements in the DAcwp analyses of hydrometeor variables are found to benefit CrIS radiance simulations, especially in cloudy regions. A long period of statistics reveals that the biases and standard deviations of all-sky observations minus simulations from SMallsky_DAcwp are notably smaller than those from SMallsky_DActrl. This pilot study suggests the potential benefit of combining the use of microwave cloud retrieval products for all-sky infrared DA.

Investigating the liquid water path over the tropical Atlantic with synergistic airborne measurements

Abstract. Liquid water path (LWP) is an important quantity to characterize clouds. Passive microwave satellite sensors provide the most direct estimate on a global scale but suffer from high uncertainties due to large footprints and the superposition of cloud and precipitation signals. Here, we use high spatial resolution airborne microwave radiometer (MWR) measurements together with cloud radar and lidar observations to better understand the LWP of warm clouds over the tropical North Atlantic. The nadir measurements were taken by the German High Altitude and LOng range research aircraft (HALO) in December 2013 (dry season) and August 2016 (wet season) during two Next-generation Advanced Remote sensing for VALidation (NARVAL) campaigns. Microwave retrievals of integrated water vapor (IWV), LWP, and rainwater path (RWP) are developed using artificial neural network techniques. A retrieval database is created using unique cloud-resolving simulations with 1.25 km grid spacing. The IWV and LWP retrievals share the same eight MWR frequency channels in the range from 22 to 31 GHz and at 90 GHz as their sole input. The RWP retrieval combines active and passive microwave observations and is able to detect drizzle and light precipitation. The comparison of retrieved IWV with coincident dropsondes and water vapor lidar measurements shows root-mean-square deviations below 1.4 kg m−2 over the range from 20 to 60 kg m−2. This comparison raises the confidence in LWP retrievals which can only be assessed theoretically. The theoretical analysis shows that the LWP error is constant with 20 g m−2 for LWP below 100 g m−2. While the absolute LWP error increases with increasing LWP, the relative one decreases from 20 % at 100 g m−2 to 10 % at 500 g m−2. The identification of clear-sky scenes by ancillary measurements, here backscatter lidar, is crucial for thin clouds (LWP < 12 g m−2) as the microwave retrieved LWP uncertainty is higher than 100 %. The analysis of both campaigns reveals that clouds were more frequent (47 % vs. 30 % of the time) in the dry than in the wet season. Their average LWP (63 vs. 40 g m−2) and RWP (6.7 vs. 2.7 g m−2) were higher as well. Microwave scattering of ice, however, was observed less frequently in the dry season (0.5 % vs. 1.6 % of the time). We hypothesize that a higher degree of cloud organization on larger scales in the wet season reduces the overall cloud cover and observed LWP. As to be expected, the observed IWV clearly shows that the dry season is on average less humid than the wet season (28 vs. 41 kg m−2). The results reveal that the observed frequency distributions of IWV are substantially affected by the choice of the flight pattern. This should be kept in mind when using the airborne observations to carefully mediate between long-term ground-based and spaceborne measurements to draw statistically sound conclusions.

Characterizing the Radiative Effect of Rain Using a Global Ensemble of Cloud Resolving Simulations

AbstractThe effect of rain on radiative fluxes and heating rates is a process that is neglected in most of the large scale atmospheric models used for weather forecasting or climate prediction. Yet to our knowledge, the magnitude of the resulting radiative bias remains unquantified. This study aims to quantify the rain radiative effect (RRE) at a range of temporal and spatial scales, as a step toward determining whether the radiation schemes in these models should include rain. Using off‐line radiative transfer calculations with input from an ensemble of cloud resolving model simulations, we find that rain has a negligible effect on global mean radiative fluxes (less than 0.2 W m−2). Weekly mean RREs at specific locations may be larger (less than 4 W m−2). At the finest temporal and spatial resolutions, the RRE can occasionally be much larger again (greater than 100 W m−2), but values exceeding 10 W m−2 occur in less than 0.1% of cases. Using detailed analysis of case studies we demonstrate that the magnitude and direction of the RRE depend on the rain water path, its vertical location with respect to cloud, and, for longwave radiation, the temperature at which it occurs. Large RREs generally only occur when the rain water path is large and the cloud water path is small. These cases are infrequent and intermittent. As the RREs are generally small, we conclude that this missing process is unlikely to be important for large scale atmospheric models.

Effects of turbulence on warm clouds and precipitation with various aerosol concentrations

Abstract This study investigates the effects of turbulence-induced collision enhancement (TICE) on warm clouds and precipitation by changing the cloud condensation nuclei (CCN) number concentration using a two-dimensional dynamic model with bin microphysics. TICE is determined according to the Taylor microscale Reynolds number and the turbulent dissipation rate. The thermodynamic sounding used in this study is characterized by a warm and humid atmosphere with a capping inversion layer, which is suitable for simulating warm clouds. For all CCN concentrations, TICE slightly reduces the liquid water path during the early stage of cloud development and accelerates the onset of surface precipitation. However, changes in the rainwater path and in the amount of surface precipitation that are caused by TICE depend on the CCN concentrations. For high CCN concentrations, the mean cloud drop number concentration (CDNC) decreases and the mean effective radius increases due to TICE. These changes cause an increase in the amount of surface precipitation. However, for low CCN concentrations, changes in the mean CDNC and in the mean effective radius induced by TICE are small and the amount of surface precipitation decreases slightly due to TICE. A decrease in condensation due to the accelerated coalescence between droplets explains the surface precipitation decrease. In addition, an increase in the CCN concentration can lead to an increase in the amount of surface precipitation, and the relationship between the CCN concentration and the amount of surface precipitation is affected by TICE. It is shown that these results depend on the atmospheric relative humidity.

On the interaction between marine boundary layer cellular cloudiness and surface heat fluxes

Abstract. The interaction between marine boundary layer cellular cloudiness and surface fluxes of sensible and latent heat is investigated. The investigation focuses on the non-precipitating closed-cell state and the precipitating open-cell state at low geostrophic wind speed. The Advanced Research WRF (Weather Research and Forecasting) model is used to conduct cloud system-resolving simulations with interactive surface fluxes of sensible heat, latent heat, and of sea salt aerosol, and with a detailed representation of the interaction between aerosol particles and clouds. The mechanisms responsible for the temporal evolution and spatial distribution of the surface heat fluxes in the closed- and open-cell state are investigated and explained. It is found that the closed-cell state imposes its horizontal spatial structure on surface air temperature and water vapor, and, to a lesser degree, on the surface sensible and latent heat flux. The responsible mechanism is the entrainment of dry, free tropospheric air into the boundary layer. The open-cell state is associated with oscillations in surface air temperature, water vapor, and in the surface fluxes of sensible heat, latent heat, and of sea salt aerosol. Here, the responsible mechanism is the periodic formation of clouds, rain, and of cold and moist pools with elevated wind speed. Open-cell cloud formation, cloud optical depth and liquid water path, and cloud and rain water path are identified as good predictors of the horizontal spatial structure of surface air temperature and sensible heat flux, but not of surface water vapor and latent heat flux. It is shown that the open-cell state creates conditions conducive to its maintenance by enhancing the surface sensible heat flux. The open-cell state also enhances the sea salt flux relative to the closed-cell state. While the open-cell state under consideration is not depleted in aerosol and is insensitive to variations in sea salt fluxes, in aerosol-depleted conditions, the enhancement of the sea salt flux may replenish the aerosol needed for cloud formation and hence contribute to the maintenance of the open-cell state. Spatial homogenization of the surface fluxes is found to have only a small effect on cloud properties in the investigated cases.

The effect of smoke emission amount on changes in cloud properties and precipitation: A case study of Canadian boreal wildfires of 2007

AbstractWe investigate the influence of wildfire smoke aerosols on cloud microphysics and precipitation using a coupled aerosol‐cloud microphysics‐meteorology model WRF‐Chem‐SMOKE. The Wildfire Automated Biomass Burning Algorithm products are used to compute “online” hourly size‐ and composition‐resolved smoke emission fluxes during Canadian boreal wildfires in the summer of 2007. Comparisons with Moderate Resolution Imaging Spectroradiometer aerosol optical depth, Ozone Monitoring Instrument aerosol index, and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation vertical feature mask demonstrate that WRF‐Chem‐SMOKE captures both the horizontal and vertical spatial distribution of smoke. However, estimated smoke emissions result in much lower aerosol optical depth values than those of observations (by about tenfold). Modeling experiments with varying amounts of smoke emissions of 5 to 10 times as high as the original load reveal that low smoke load favors the collision‐coalescence process at a certain stage, leading to either positive or negative changes in the cloud water path (CWP) relative to smoke‐free conditions. For high smoke emissions, changes in CWP are positive, as large as 0.5 kg/m2. A domain‐integrated increase in CWP is proportional to smoke loading. By contrast, both positive and negative changes in the rain water path (RWP) and the snow water path (SWP) are found. While domain‐integrated changes in RWP are negative, those in SWP go from negative to positive under a high smoke load. Higher smoke loadings suppress precipitation initially, because of smoke‐induced reduction of the collision‐coalescence and riming processes, but ultimately cause an invigoration of precipitation. We found that precipitation is highly sensitive to 3‐D smoke fields and varies in a nonlinear manner with smoke loads.

Comparing rain retrievals from GPROF with ECMWF 1D‐Var products

AbstractBoth the Goddard Profiling Algorithm (GPROF) and European Centre for Medium‐Range Weather Forecasts (ECMWF) one‐dimensional + four‐dimensional variational analysis (1D+4D‐Var) rainfall retrievals are inversion algorithms based on Bayes' theorem. Differences stem primarily from the a priori information. The GPROF uses an observationally generated a priori database whereas ECMWF 1D‐Var uses the model forecast first guess (FG) fields. The relative similarity in the two approaches means that comparisons can shed light on the differences that are produced by the a priori information. Case studies have found that differences can be classified into four categories based upon the agreement in the brightness temperatures (Tbs) and in the microphysical properties of cloud water path (CWP) and rainwater path (RWP) space. A category of special interest is when both retrievals converge to similar Tb through minimization procedures but produce different CWP and RWP. The similarity in Tb can be attributed to comparable total water path (TWP) between the two retrievals while the disagreement in the microphysics is caused by their different degrees of constraint of the cloud/rain ratio by the observations. This situation occurs frequently and takes up 46.9% in the 1 month 1D‐Var retrievals examined. The two retrievals produce similar spatial patterns but with different magnitude. The allocation of a large amount of CWP in the 1D‐Var retrieval seems to be related to the stratiform portion of rain, which is produced by the large‐scale condensation scheme. To attain better‐constrained cloud/rain ratios and improved retrieval quality, this study suggests the implementation of higher microwave frequency channels in the 1D‐Var algorithm. Copyright © 2012 Royal Meteorological Society

Impact of Cloud-Nucleating Aerosols in Cloud-Resolving Model Simulations of Warm-Rain Precipitation in the East China Sea

Abstract Cloud-nucleating aerosols emitted from mainland China have the potential to influence cloud and precipitation systems that propagate through the region of the East China Sea. Both simulations from the Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) and observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveal plumes of pollution that are transported into the East China Sea via frontal passage or other offshore flow. Under such conditions, satellite-derived precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) frequently produce discrepancies in rainfall estimates that are hypothesized to be a result of aerosol modification of cloud and raindrop size distributions. Cloud-resolving model simulations were used to explore the impact of aerosol loading on three identified frontal-passage events in which the TMI and PR precipitation estimates displayed large discrepancies. Each of these events was characterized by convective and stratiform elements in association with a frontal passage. Area-averaged time series for each event reveal similar monotonic cloud and rain microphysical responses to aerosol loading. The ratio in the vertical distribution of cloud water to rainwater increased. Cloud droplet concentration increased and the mean diameters decreased, thereby reducing droplet autoconversion and collision–coalescence growth. As a result, raindrop concentration decreased, while the drop mean diameter increased; furthermore, average rainwater path magnitude and area fraction both decreased. The average precipitation rate fields reveal a complex modification of the timing and spatial coverage of rainfall. This suggests that the warm-rain microphysical response to aerosols, in addition to the precipitation life cycle, microphysical feedbacks, and evaporative effects, play an important role in determining surface rainfall.

Rainwater path in warm clouds derived from combined visible/near‐infrared and microwave satellite observations

The effects of warm rain on optical properties of clouds in the visible/near‐infrared (VNIR) and passive microwave (PMW) are studied using a simple conceptual cloud model. It is shown that the combined use of PMW and VNIR observations allows for the detection of precipitation and the derivation of rainwater path utilizing the different physical information content of the two observation types. Various potential error sources are studied and one month of combined geostationary visible/near infrared and Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E) passive microwave observations off the coast of South Africa are evaluated using the proposed approach. Comparisons with CloudSat radar reflectivities are used for an independent assessment. A gradual increase in retrieved rainwater path with column maximum radar reflectivity is found for reflectivity values larger than −10 dBz. For monthly mean values at 1 × 1 degree resolution, rainwater path is correlated with in‐cloud liquid water path (R2 = 0.50). The strongest correlation (R2 = 0.69) exists between rainwater path and the inverse of cloud droplet number concentration (N). This finding is consistent with other studies supporting a 1/N dependency of precipitation intensity on cloud droplet number concentration in warm clouds.

Lessons learnt from the operational 1D + 4D‐Var assimilation of rain‐ and cloud‐affected SSM/I observations at ECMWF

AbstractRain‐ and cloud‐affected Special Sensor Microwave/Imager (SSM/I) observations are assimilated operationally at the European Centre for Medium‐Range Weather Forecasts (ECMWF). The four‐dimensional variational analysis (4D‐Var) assimilates total column water vapour (TCWV) derived from one‐dimensional variational retrievals (1D‐Var). From the SSM/I radiances, 1D‐Var retrieves surface wind and the vertical profiles of temperature, humidity, cloud and precipitation. The main shortcoming of the ‘1D + 4D‐Var’ technique is that, of all this information, only TCWV gets into the 4D‐Var analysis. More information could be used: the rainwater path agrees well, in an instantaneous comparison, with observations from the precipitation radar on the Tropical Rainfall Measuring Mission. There are other issues, however: the simplified moist physics operators used in 1D‐Var produce roughly twice the observed amount of rain, but the problem is masked by a sampling bias, which comes from applying 1D + 4D‐Var when the observations are cloudy or rainy, but not when the first guess is rainy or cloudy and the observations are clear. The shortcomings of 1D + 4D‐Var will be addressed by moving to a direct 4D‐Var assimilation which includes all SSM/I observations, whether clear, cloudy or rainy, in the same stream. Copyright © 2008 Royal Meteorological Society

Information Content of Millimeter-Wave Observations for Hydrometeor Properties in Mid-Latitudes

For future remote sensing applications the potential of the millimeter wavelength range for precipitation observations from geostationary orbits is investigated. Therefore, a database consisting of hydrometeor profiles from various mid-latitude precipitation cases over Europe and corresponding simulated brightness temperatures at 18 microwave frequencies was built using the cloud resolving model Meso-NH and the radiative transfer model micro wave model. The information content of the database was investigated by applying simple statistical methods, as well as developing first-order retrieval approaches. The results show that, particularly for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 25% in dominantly stratiform precipitation cases over land and ocean surfaces. The performance for rain-water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain-water path are larger particularly over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain-water path. Algorithms with reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval because these are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suitable for geostationary applications due to their reduced demands concerning the antenna size.