The impact of assimilating radar-estimated rain rates on simulation of precipitation in the 17–18 July 1996 Chicago floods

2010 ◽  
Vol 27 (2) ◽  
pp. 195-210 ◽  
Author(s):  
Xingbao Wang ◽  
M. K. Yau ◽  
B. Nagarajan ◽  
Luc Fillion
Keyword(s):  
2016 ◽  
Vol 17 (11) ◽  
pp. 2905-2922 ◽  
Author(s):  
David E. Kingsmill ◽  
Paul J. Neiman ◽  
Allen B. White

Abstract This study examines the impact of microphysics regime on the relationship between orographic forcing and orographic rain in the coastal mountains of Northern California using >4000 h of data from profiling Doppler radars, rain gauges, and a GPS receiver collected over 10 cool seasons. Orographic forcing is documented by hourly upslope flow, integrated water vapor (IWV), and IWV flux observed along the coast at Bodega Bay (BBY; 15 m MSL). Microphysics regime is inferred in the coastal mountains at Cazadero (CZC; 478 m MSL), where hourly periods of brightband (BB) and nonbrightband (NBB) rain are designated. BB rain is associated with a microphysics regime dominated by the seeder–feeder process while NBB rain is associated with a microphysics regime dominated by the warm-rain process. Mean BBY upslope flow, IWV, and IWV flux are ~16%, ~5%, and ~19% larger, respectively, for NBB rain compared to BB rain, while mean CZC rain rate is ~33% larger for BB rain compared to NBB rain. The orographic enhancement ratio of CZC to BBY rain rate is 3.7 during NBB rain and 2.7 during BB rain. Rain rate at CZC increases as orographic forcing at BBY increases. For a given amount of BBY orographic forcing, mean CZC rain rates are larger for BB rain compared to NBB rain. Correlation coefficients associated with the relationship between CZC rain rate and BBY orographic forcing are smaller for NBB rain relative to BB rain, but these differences are not statistically significant.


2014 ◽  
Vol 53 (11) ◽  
pp. 2524-2537 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini ◽  
Ali Tokay

AbstractA framework based on measured raindrop size distribution (DSD) data has been developed to assess uncertainties in DSD models employed in Ku- and Ka-band dual-wavelength radar retrievals. In this study, the rain rates and attenuation coefficients from DSD parameters derived by dual-wavelength algorithms are compared with those directly obtained from measured DSD spectra. The impact of the DSD gamma parameterizations on rain estimation from the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) is examined for the cases of a fixed shape factor μ as well as for a constrained μ—that is, a μ–Λ relation (a relationship between the shape parameter and slope parameter Λ of the gamma DSD)—by using 11 Particle Size and Velocity (Parsivel) disdrometer measurements with a total number of about 50 000 one-minute spectra that were collected during the Iowa Flood Studies (IFloodS) experiment. It is found that the DPR-like dual-wavelength techniques provide fairly accurate estimates of rain rate and attenuation if a fixed-μ gamma DSD model is used, with the value of μ ranging from 3 to 6. Comparison of the results reveals that the retrieval errors from the μ–Λ relations are generally small, with biases of less than ±10%, and are comparable to the results from a fixed-μ gamma model with μ equal to 3 and 6. The DSD evaluation procedure is also applied to retrievals in which a lognormal DSD model is used.


2021 ◽  
Author(s):  
Moshe Armon ◽  
Francesco Marra ◽  
Chaim Garfinkel ◽  
Dorita Rostkier-Edelstein ◽  
Ori Adam ◽  
...  

<p>Heavy precipitation events (HPEs) in the densely populated eastern Mediterranean trigger natural hazards, such as flash floods and urban flooding. However, they also supply critical amounts of fresh water to this desert-bounded region. The impact of global warming on such events is thus vital to the inhabitants of the region. HPEs are poorly represented in global climate models, leading to large uncertainty in their sensitivity to climate change. Is total rainfall in HPEs decreasing, as projected for the mean annual rainfall? Are short duration rain rates decreasing, or rather increasing as expected from the higher atmospheric moisture content? Where are the changes more pronounced, near the sea or farther inland towards the desert? To answer these questions, we have identified 41 historical HPEs from a long weather radar record (1990-2014) and simulated them in the same resolution (1 km<sup>2</sup>) using the convection-permitting weather research and forecasting (WRF) model. Results were validated versus the radar data, and served as a control group to simulations of the same events under ‘pseudo global warming’ (PGW) conditions. The PGW methodology we use imposes results from the ensemble mean of 29 Coupled Model Intercomparison Project Phase 5 (CMIP5) models for the end of the century on the initial and boundary conditions of each event simulated. The results indicate that HPEs in the future may become more temporally focused: they are 6% shorter and exhibit maximum local short-duration rain rates which are ~20% higher on average, with larger values over the sea and the wetter part of the region, and smaller over the desert. However, they are also much drier; total precipitation during the future-simulated HPEs decreases substantially (~-20%) throughout the eastern Mediterranean. The meteorological factors leading to this decrease include shallower cyclones and the projected differential land-sea warming, which causes reduced relative humidity over land. These changing rainfall patterns are expected to amplify water scarcity – a known nexus of conflict and strife in the region – highlighting the urgent need for deeper knowledge, and the implementation of adaptation and mitigation strategies.</p>


Author(s):  
Mampi Sarkar ◽  
Paquita Zuidema ◽  
Virendra Ghate

AbstractPrecipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.


2020 ◽  
Author(s):  
Maximilian Graf ◽  
Christian Chwala ◽  
Julius Polz ◽  
Harald Kunstmann

<p>In recent years, so-called opportunistic sensors for measuring rainfall, are attracting more notice due to their broad availability and low financial effort for the scientific community. These sensors are existing devices or infrastructure, which were not intentionally built to measure rainfall, but can deliver rainfall information. One example of such an opportunistic measurement system are Commercial Microwave Links (CMLs), which provide part of the backbone of modern mobile communication. CMLs can deliver path-averaged rainfall information through the relation between rainfall and attenuation along their paths. Before such an opportunistic data source can be used, either as an individual or a merged data product, its performance compared to other rainfall products must be evaluated.</p><p>We discuss the selection of performance metrics, spatial and temporal aggregation and rainfall thresholds for the comparison between a German-wide CML network and a gauge-adjusted radar product provided by the German Weather Service. The CML data set consists of nearly 4000 CMLs with minutely readings from which we will present a year of data. </p><p>First, we show the influence of the temporal aggregation on the comparability. With higher resolution, the impact due to small temporal deviations increases. Second, CMLs represent path-averaged rainfall information, while the radar product is gridded. We discuss the choice whether the comparison should be performed on the point, line or grid scale. This choice depends on the desired future applications which already should be considered when selection evaluation tools. Third, the decision to exclude rain rates below a certain threshold or the calculation of performance metrics for certain intervals gives us a more detailed insight in the behavior of both rainfall data sets.</p>


2007 ◽  
Vol 46 (9) ◽  
pp. 1480-1497 ◽  
Author(s):  
Olivier P. Prat ◽  
Ana P. Barros

Abstract The focus of this paper is on the numerical solution of the stochastic collection equation–stochastic breakup equation (SCE–SBE) describing the evolution of raindrop spectra in warm rain. The drop size distribution (DSD) is discretized using the fixed-pivot scheme proposed by Kumar and Ramkrishna, and new discrete equations for solving collision breakup are presented. The model is evaluated using established coalescence and breakup parameterizations (kernels) available in the literature, and in that regard this paper provides a substantial review of the relevant science. The challenges posed by the need to achieve stable and accurate numerical solutions of the SCE–SBE are examined in detail. In particular, this paper focuses on the impact of varying the shape of the initial DSD on the equilibrium solution of the SCE–SBE for a wide range of rain rates and breakup kernels. The results show that, although there is no dependence of the equilibrium DSD on initial conditions for the same rain rate and breakup kernel, there is large variation in the time that it takes to reach steady state. This result suggests that, in coupled simulations of in-cloud motions and microphysics and for short time scales (<30 min) for which transient conditions prevail, the equilibrium DSD may not be attainable except for very heavy rainfall. Furthermore, simulations for the same initial conditions show a strong dependence of the dynamic evolution of the DSD on the breakup parameterization. The implication of this result is that, before the debate on the uniqueness of the shape of the equilibrium DSD can be settled, there is critical need for fundamental research including laboratory experiments to improve understanding of collisional mechanisms in DSD evolution.


2016 ◽  
Vol 33 (8) ◽  
pp. 1779-1792 ◽  
Author(s):  
Xinxin Xie ◽  
Raquel Evaristo ◽  
Silke Troemel ◽  
Pablo Saavedra ◽  
Clemens Simmer ◽  
...  

AbstractThis study analyzes radar observations of evaporation in rain and investigates its impact on surface rainfall and atmospheric cooling rates. A 1D model is used to examine the impact of raindrop evaporation on the evolution of the initial raindrop size distribution (DSD), the resulting reflectivity (Z), and differential reflectivity (ZDR) and surface rain rates. Raindrop evaporation leads to a decrease of Z and an increase of ZDR toward the surface because of the depletion of small raindrops that evaporate first and thus enhance the mean raindrop size. The latter effect, however, can be reduced because of the increasing temperature toward the surface and may even lead to a decrease of ZDR toward the surface. Two events with significant rain evaporation, observed simultaneously by a polarimetric X-band radar and a K-band Micro Rain Radar (MRR), offer quite detailed insight into the evaporation process. During the first event, which exhibits an initial ZDR > 1.5 dB in the upper rain column, raindrops undergo relatively weak evaporation as deduced from the decrease of the small raindrop fraction observed by the MRR. The second event is characterized by a lower initial ZDR < 0.5 dB with all raindrops evaporating before reaching the ground. A retrieval scheme for estimating the evaporation-related cooling rate and surface precipitation from polarimetric radar observations below the bright band is derived based on MRR observations. The algorithm is then used to simulate polarimetric X-band radar observations, which might mitigate uncertainties in the surface rainfall retrievals due to evaporation at far distances from the radars and in the case of beam blocking.


2015 ◽  
Vol 72 (9) ◽  
pp. 3340-3355 ◽  
Author(s):  
Zhujun Li ◽  
Paquita Zuidema ◽  
Ping Zhu ◽  
Hugh Morrison

Abstract The sensitivity of nested WRF simulations of precipitating shallow marine cumuli and cold pools to microphysical parameterization is examined. The simulations differ only in their use of two widely used double-moment rain microphysical schemes: the Thompson and Morrison schemes. Both simulations produce similar mesoscale variability, with the Thompson scheme producing more weak cold pools and the Morrison scheme producing more strong cold pools, which are associated with more intense shallow convection. The most robust difference is that the cloud cover and LWP are significantly larger in the Morrison simulation than in the Thompson simulation. One-dimensional kinematic simulations confirm that dynamical feedbacks do not mask the impact of microphysics. These also help elucidate that a slower autoconversion process along with a stronger accretion process explains the Morrison scheme’s higher cloud fraction for a similar rain mixing ratio. Differences in the raindrop terminal fall speed parameters explain the higher evaporation rate of the Thompson scheme at moderate surface rain rates. Given the implications of the cloud-cover differences for the radiative forcing of the expansive trade wind regime, the microphysical scheme should be considered carefully when simulating precipitating shallow marine cumulus.


2014 ◽  
Vol 7 (2) ◽  
pp. 1807-1833
Author(s):  
A. Chandra ◽  
C. Zhang ◽  
P. Kollias ◽  
S. Matrosov ◽  
W. Szyrmer

Abstract. The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from profiling Ka-band (35-GHz) ARM zenith radars (KAZR). A 1-D simple, steady state microphysical model is used to estimate the impact of microphysical processes and attenuation on the profiles of the radar observables at 35-GHz and thus provide criteria for identifying when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for saturation and wet radome effects. The proposed algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while lower rain rates by the Ze–R (reflectivity-rain rate) relation is implemented. Observations collected by the KAZR, disdrometer and scanning weather radars during the DYNAMO/AMIE field campaign at Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The results indicate that the proposed algorithm can be used to derive robust statistics of rain rates in the tropics from KAZR observations.


2014 ◽  
Vol 31 (11) ◽  
pp. 2392-2408 ◽  
Author(s):  
Bradley W. Klotz ◽  
Eric W. Uhlhorn

AbstractSurface wind speeds retrieved from airborne stepped frequency microwave radiometer (SFMR) brightness temperature measurements are important for estimating hurricane intensity. The SFMR performance is highly reliable at hurricane-force wind speeds, but accuracy is found to degrade at weaker wind speeds, particularly in heavy precipitation. Specifically, a significant overestimation of surface wind speeds is found in these conditions, suggesting inaccurate accounting for the impact of rain on the measured microwave brightness temperature. In this study, the wind speed bias is quantified over a broad range of operationally computed wind speeds and rain rates, based on a large sample of collocated SFMR wind retrievals and global positioning system dropwindsonde surface-adjusted wind speeds. The retrieval bias is addressed by developing a new SFMR C-band relationship between microwave absorption and rain rate (κ−R) from National Oceanic and Atmospheric Administration WP-3D aircraft tail Doppler radar reflectivity and in situ Droplet Measurement Technologies Precipitation Imaging Probe measurements to more accurately model precipitation impacts. Absorption is found to be a factor of 2 weaker than is estimated by the currently operational algorithm. With this new κ–R relationship, surface wind retrieval bias is significantly reduced in the presence of rain at wind speeds weaker than hurricane force. At wind speeds greater than hurricane force where little bias exists, no significant change is found. Furthermore, maximum rain rates computed using the revised algorithm are around 50% greater than operational measurements, which is more consistent with maximum reflectivity-estimated rain rates in hurricanes.


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