Abstract

In this study, we used hourly observations to investigate the cooling effect of summer rainfall on surface air temperature (Ta) in a subtropical area, Guangdong province, South China. Data were categorized step-by-step by rainfall system (convection, monsoon, and typhoon), daily rainfall amount, and relative humidity (RH) level. Moreover, the average hourly Ta variation due to solar radiation was removed from all observations before statistical analysis. The results showed that the linear relationship between hourly Ta variation and rainfall intensity did not exist. However, the cooling effect of rainfall on Ta variation was dominant. In addition, convective rainfall does cause a greater temperature drop than the other two rainfall systems. After further partitioning all samples by RH level preceding the rainfall, the relationship between hourly Ta variation and rainfall intensity became distinctive. When RH was below 70%, rainfall-induced cooling became more substantial and scaled linearly with event intensity, but when RH exceeded 70%, the rainfall cooling effect was generally restrained by the RH increase. A strong correlation between hourly Ta variation and RH level preceding the rainfall suggests the importance of RH on the rainfall cooling effect.

Abstract

The drop size distribution (DSD) and drop shape relation (DSR) characteristics that were observed by a ground-based 2D video disdrometer and retrieved from a C-band polarimetric radar in the typhoon systems during landfall in the western Pacific, near northern Taiwan, were analyzed. The evolution of the DSD and its relation with the vertical development of the reflectivity of two rainband cases are fully illustrated. Three different types of precipitation systems were classified—weak stratiform, stratiform, and convective—according to characteristics of the mass-weighted diameter D_m , the maximum diameter, and the vertical structure of reflectivity. Further study of the relationship between the height H of the 15-dBZ contour of the vertical reflectivity profile, surface reflectivity Z, and the mass-weighted diameter D_m showed that D_m increased with a corresponding increase in the system depth H and reflectivity Z.

An analysis of DSDs retrieved from the National Central University (NCU) C-band polarimetric radar and disdrometer in typhoon cases indicates that the DSDs from the typhoon systems on the ocean were mainly a maritime convective type. However, the DSDs collected over land tended to uniquely locate in between the continental and maritime clusters. The average mass-weighted diameter D_m was about 2 mm and the average logarithmic normalized intercept N_w was about 3.8 log₁₀ mm⁻¹ m⁻³ in typhoon cases. The unique terrain-influenced deep convective systems embedded in typhoons in northern Taiwan might be the reason for these characteristics.

The “effective DSR” of typhoon systems had an axis ratio similar to that found by E. A. Brandes et al. when the raindrops were less than 1.5 mm. Nevertheless, the axis ratio tended to be more spherical with drops greater than 1.5 mm and under higher horizontal winds (maximum wind speed less than 8 m s⁻¹). A fourth-order fitting DSR was derived for typhoon systems and the value was also very close to the estimated DSR from the polarimetric measurements in Typhoon Saomai (2006).

Abstract

The accuracy of rain-rate estimation using polarimetric radar measurements has been improved as a result of better characterization of radar measurement quality and rain microphysics. In the literature, a variety of power-law relations between polarimetric radar measurements and rain rate are described because of the dynamic or varying nature of rain microphysics. A variational technique that concurrently takes into account radar observational error and dynamically varying rain microphysics is proposed in this study. Rain-rate estimation using the variational algorithm that uses event-based observational error and background rain climatological values is evaluated using observing system simulation experiments (OSSE), and its performance is demonstrated in the case of an epic Colorado flood event. The rain event occurred between 11 and 12 September 2013. The results from OSSE show that the variational algorithm with event-based observational error consistently estimates more accurate rain rate than does the “R(Z _HH, Z _DR)” power-law algorithm. On the contrary, the usage of ad hoc or improper observational error degrades the performance of the variational method. Furthermore, the variational algorithm is less sensitive to the observational error of differential reflectivity Z _DR than is the R(Z _HH, Z _DR) algorithm. The variational quantitative precipitation estimation (QPE) retrieved more accurate rainfall estimation than did the power-law dual-polarization QPE in this particular event, despite the fact that both algorithms used the same dual-polarization radar measurements from the Next Generation Weather Radar (NEXRAD).

Abstract

A variational algorithm for estimating measurement error covariance and the attenuation of X-band polarimetric radar measurements is described. It concurrently uses both the differential reflectivity Z _DR and propagation phase Φ_DP. The majority of the current attenuation estimation techniques use only Φ_DP. A few of the Φ_DP-based methods use Z _DR as a constraint for verifying estimated attenuation. In this paper, a detailed observing system simulation experiment was used for evaluating the performance of the variational algorithm. The results were compared with a single-coefficient Φ_DP-based method. Retrieved attenuation from the variational method is more accurate than the results from a single coefficient Φ_DP-based method. Moreover, the variational method is less sensitive to measurement noise in radar observations. The variational method requires an accurate description of error covariance matrices. Relative weights between measurements and background values (i.e., mean value based on long-term DSD measurements in the variational method) are determined by their respective error covariances. Instead of using ad hoc values, error covariance matrices of background and radar measurement are statistically estimated and their spatial characteristics are studied. The estimated error covariance shows higher values in convective regions than in stratiform regions, as expected. The practical utility of the variational attenuation correction method is demonstrated using radar field measurements from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) during 2008’s Southwest Monsoon Experiment/Terrain-Influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX). The accuracy of attenuation-corrected X-band radar measurements is evaluated by comparing them with collocated S-band radar measurements.

Abstract

Wind retrieval algorithms are required for Doppler weather radars. In this article, a new wind retrieval algorithm of single-Doppler radar with a support vector machine (SVM) is analyzed and compared with the original algorithm with the least squares technique. Through an analysis of coefficient matrices of equations corresponding to the optimization problems for the two algorithms, the new algorithm, which contains a proper penalization parameter, is found to effectively reduce the condition numbers of the matrices and thus has the ability to acquire accurate results, and the smaller the analysis volume is, the smaller the condition number of the matrix. This characteristic makes the new algorithm suitable to retrieve mesoscale and small-scale and high-resolution wind fields. Afterward, the two algorithms are applied to retrieval experiments to implement a comparison and a discussion. The results show that the penalization parameter cannot be too small, otherwise it may cause a large condition number; it cannot be too large either, otherwise it may change the properties of equations, leading to retrieved wind direction along the radial direction. Compared with the original algorithm, the new algorithm has definite superiority with the appropriate penalization parameters for small analysis volumes. When the suggested small analysis volume dimensions and penalization parameter values are adopted, the retrieval accuracy can be improved by 10 times more than the traditional method. As a result, the new algorithm has the capability to analyze the dynamical structures of severe weather, which needs high-resolution retrieval, and the potential for quantitative applications such as the assimilation in numerical models, but the retrieval accuracy needs to be further improved in the future.

Abstract

Crowdsourced meteorological data may provide a useful supplement to operational observations. However, the willingness of various parties to share their data remains unclear. Here, a survey on data applications was carried out to investigate the willingness to participate in crowdsourcing observations. Of the 21 responses, 71% expressed difficulty in meeting the requirement of data services using only their own observations and revealed that they would be willing to exchange data with other parties under some framework; moreover, 90% expressed a willingness to participate in crowdsourcing observations. The findings suggest that in a way the social foundation of crowdsourcing has been established in China. Additionally, a case study on precipitation monitoring was performed in Guangzhou, the capital city of Guangdong Province, South China. Three sources of hourly measurements were combined after data quality control and calibration and interpolated over Guangzhou (gridded precipitation was based on combined data, and it is referred to as the COM grid). Subsequently, the COM grid was compared with the grid data based only on observations from the China Meteorological Administration using three indices, namely, cumulative precipitation, precipitation intensity, and heavy rain hours. The results indicate that requirement for more observations could benefit from crowdsourced data, especially on uneven terrain and in regions covered by sparse surface stations.

Abstract

The ability to construct nitrate maps in the Southern Ocean (SO) from sparse observations is important for marine biogeochemistry research, as it offers a geographical estimate of biological productivity. The goal of this study is to infer the skill of constructed SO nitrate maps using varying data sampling strategies. The mapping method uses multivariate empirical orthogonal functions (MEOFs) constructed from nitrate, salinity, and potential temperature (N-S-T) fields from a biogeochemical general circulation model simulation Synthetic N-S-T datasets are created by sampling modeled N-S-T fields in specific regions, determined either by random selection or by selecting regions over a certain threshold of nitrate temporal variances. The first 500 MEOF modes, determined by their capability to reconstruct the original N-S-T fields, are projected onto these synthetic N-S-T data to construct time-varying nitrate maps. Normalized root-mean-square errors (NRMSEs) are calculated between the constructed nitrate maps and the original modeled fields for different sampling strategies. The sampling strategy according to nitrate variances is shown to yield maps with lower NRMSEs than mapping adopting random sampling. A k-means cluster method that considers the N-S-T combined variances to identify key regions to insert data is most effective in reducing the mapping errors. These findings are further quantified by a series of mapping error analyses that also address the significance of data sampling density. The results provide a sampling framework to prioritize the deployment of biogeochemical Argo floats for constructing nitrate maps.

Abstract

Numerous studies have indicated that the atmospheric heat source (AHS) over the Tibetan Plateau (TP) is highly correlated with the western North Pacific anomalous anticyclone (WNPAC) in summer. However, such an interannual relationship has been weakened since the late 1990s. The present work shows that the TP AHS was significantly and positively correlated with the WNPAC during the period 1979–99 (P1), while this relationship became insignificant hereafter [2000–20 (P2)]. From an atmospheric perspective, we identify that the long-term change in the upper-level atmospheric circulation over the TP is an important cause for weakening the relationship. An obvious upper-level anticyclonic trend occurred over the northeastern TP in the past four decades, with an easterly trend on the anticyclone’s southern flank, with anomalous westerlies during P1 but anomalous easterlies during P2 over the main portion of the TP. With the anomalous upper-level westerlies in P1, abnormal high pressure induced by the TP heating (i.e., AHS) extended downstream in the upper troposphere. Subsequently, anomalous descending motions formed over the northwestern Pacific due to the eastward-extended high pressure, together with the vertical transport of negative relative vorticity, favorable for the enhancement of the WNPAC. In P2, the TP heating-induced abnormal high pressure was confined over the southern TP due to the anomalous easterlies, suppressing its downstream influence and finally breaking the connection between the TP AHS and the WNPAC. Modeling results from both linear baroclinic model (LBM) sensitivity experiments and the CESM Large Ensemble dataset further confirm the important role of the change in background circulation in weakening the relationship.

Abstract

Southeast Asia lies at the heart of heavy precipitation on Earth, and a large amount of latent heat released here provides substantial energy for the global atmospheric circulation. Utilizing gauge-based daily precipitation and the self-organizing map technique, the summertime extreme and total precipitation over Southeast Asia during 1979–2019 are classified into three and five distinct patterns, respectively. The three extreme precipitation clusters are characterized by southern dry and northern wet (C1_extreme), overall wet (C2_extreme), and northern dry and southern wet (C3_extreme) structures. The frequencies of these patterns exhibit increasing trends during the analysis, although they are not statistically significant for C1_extreme. The C1_extreme pattern is accompanied by an anomalous cyclone over the South China Sea in response to negative Indian Ocean sea surface temperature anomalies (SSTAs). The C2_extreme and C3_extreme clusters are characterized by a westward extension of the western Pacific subtropical high, regulated by cool SSTAs over the tropical central-eastern Pacific that are induced by the tropical North Atlantic warming and the tropical Pacific and Atlantic SSTAs, respectively. For total precipitation, the first and second clusters show overall dry distributions, which are mainly composed of nonextreme precipitation. The spatial patterns and atmospheric and oceanic features associated with the other three clusters of total precipitation bear large resemblances to those of C1_extreme, C2_extreme, and C3_extreme, respectively, but their trends exhibit smaller similarities. Comparing the differences between extreme and total precipitation over Southeast Asia could improve our understanding of their regional variabilities and relationships, and potentially their global impacts.

Abstract

Icing is a weather phenomenon that is typical of cold climates. It impacts human activities through ice accretion on tower structures, transmission lines, and the blades of wind turbines. Icing on turbine blades, in particular, results in wind turbine performance degradation and/or safety shutdowns. The objective of this study is to explore the feasibility of using a coupled atmospheric and ice load model to simulate icing start-up, duration, and amount while also quantitatively evaluating power loss in wind plants related to icing events and mechanisms. Eight of 27 icing episodes identified for a wind plant in the Gaspé region of Québec (Canada) during the period 2008–10 were simulated using a mesoscale model (the Global Environmental Multiscale Limited-Area Model, or GEM-LAM). The simulations were verified using near-surface temperature, relative humidity, and wind speed, all of which compared well to in situ observations. Simulated wind speed, precipitation, cloud liquid water content, and median volume diameter of the droplets were used to drive ice load models to simulate the total ice load on a cylindrical structure. The three ice load models accounted for freezing rain, wet snow, and in-cloud icing, respectively, and in all three cases a sink term was added to account for melting due to radiation. The start-up and duration of ice were well captured by the coupled model, and a positive correlation was found between icing episodes and wind power reduction. This study demonstrates the improvements of the icing forecasts by using three ice load models, and provides a framework for both qualitative and quantitative evaluation of icing impact on wind turbine operations.