This PDF file contains the front matter associated with SPIE Proceedings Volume 10782, including the Title Page, Copyright information, Table of Contents, Introduction, Author and Conference Committee lists

Satellite-based rainfall estimates (SRE) have become a promising data source to overcome some limitations of ground-based rainfall measurements, in particular for hydrological and other environmental applications. This study evaluates the spatial and temporal performance of four long-term SRE products (TMPA 3B42v7, CHIRPSv2, MSWEPv1.1 and MSWEPv2.2) over the complex topography and climatic gradients of Chile. Time series of precipitation measured at 371 stations are compared against the corresponding grid cell of each SRE (in their original spatial resolution) at different temporal scales (daily, monthly, seasonal, annual). The modified Kling-Gupta efficiency along with its three individual components were used to assess the performance of each SRE, while two categorical indices (POD, and fBIAS) were used to evaluate the skill of each SRE to correctly capture different precipitation intensities.

Results revealed that all SREs performed best in Central-Southern Chile (32.18-36.4°S), in particular at lowand mid-elevation zones (0-1000 m a.s.l.). Seasonally, all products performed best in terms of KGE0 during the wet autumn and winter seasons (MAM-JJA) compared to summer (DJF). In addition, all SREs were able to correctly identify no rain events, but during rainy days all SREs that did not use a local dataset of precipitation to recalibrate their estimates presented a low skill in providing an accurate classification of different precipitation intensities.

Overall, MSWPEPv22 showed the best performance at all time scales and country-wide, due to the use of a Chilean dataset of daily data for calibrating its precipitation estimates, making it a good candidate for hydrological applications in Chile. Finally, we conclude that when the in situ precipitation dataset used in the evaluation of different SREs does not cover the headwaters of the catchments, the obtained performances should only be considered as first guess about how well a given SRE represent the real amount of water in an area.

Attempts to interpret the measurements of millimeter-wave radiometers over tropical storms must overcome the difficulty of modeling the scattering signatures of hydrometeors at these frequencies. Approaches to date try to retrieve surface precipitation, to which the observations are not directly sensitive. Millimeter wavelengths are most sensitive to the scattering from hydrometeors in the cloud upper levels. Millimeter-wavelength radiometers have a definite advantage over the lower frequency radiometers in that they have finer spatial resolution to resolve deep convection. Preliminary analyses indicate that the measurements are indeed sensitive to the depth and intensity of convection. The challenge is to derive a robust approach to estimate the characteristics of the convection directly from the observations, and conversely to derive a robust forward representation of the dependence of the radiances on the underlying moisture fields. This is done in a two-step semi-empirical approach.

Even though vertical motion is resolved within convection-permitting models, recent studies have demonstrated significant departures in predicted storm updrafts and downdrafts when compared with Doppler observations of the same events. Several previous studies have attributed these departures to shortfalls in the representation of microphysical processes, in particular those pertaining to ice processes. Others have suggested that our inabilities to properly represent processes such as entrainment are responsible. Wrapped up in these issues are aspects such as the model grid resolution, as well as accuracy of models to correctly simulate the environmental conditions. Four primary terms comprise the vertical momentum equation: advection, pressure gradient forcing, thermodynamics and turbulence. Microphysical processes including their impacts on latent heating and their contributions to condensate loading strongly impact the thermodynamic term. The focus of this study is on the thermodynamic contributions to vertical motion, the shortfalls that arise when modeling this term, and the observations that might be made to improve the representation of those thermodynamical processes driving convective updrafts and downdrafts.

In this paper we report the evidence of the potential role of diffluence in the 200hPa wind field off the coast of West Africa in the formation of a significant number of Category 4 and Category 5 hurricanes in the recent decade. It is shown that more than 80% cases of hurricanes at Category 4 and above is preceded by upper level diffluence in the Tropical Easterly Jet (TEJ) by 0–5 days. This TEJ is the outflow from the southern flank of the Tibetan anticyclone from the Asian monsoon region.

Forecasting rapid intensity changes in tropical cyclones (TCs) is hard as the factors responsible span many scales. External and internal dynamical and thermodynamical variables act simultaneously in a nonlinear fashion, either complementing, amplifying, inhibiting or not impacting the TC intensity at all. We try to address the following question: What is the relative importance of the external and vortex-scale variables that influence rapid intensity changes within a TC? Further, which of these variables must be prioritized from an observational standpoint? To answer these questions, a systematic analysis was conducted on a large number of representative TCs to make statistically significant conclusions using discriminant analyses of wavenumber (WN) - filtered fields, with a principal component analysis to detect over-fitting and identify the subset of variables (from the environment and the vortex) consistently correlated with rapid intensity change. Our analyses indicate that a small number of variables wield the most influence on TC rapid intensity changes. The most important variables within the vortex are the WN 0 of precipitation within the radius of maximum winds, the amplitudes of WN 1 of precipitation and the mid-level horizontal moisture flux convergence in the rain band region. Likewise, the most important environmental variables are the angle of the driest air from the shear vector and the magnitude of environmental wind shear. These variables must be prioritized in future observational and consequent data assimilation efforts.

Here we present preliminary results from the analysis of the low cloud cover (LCC) and cloud radiative effect (CRE) interannual changes in response to sea surface temperature (SST) forcings in two GISS climate models, and 12 other climate models. We further classify them as a function of their ability to reproduce the vertical structure of the cloud response to SST change against 10 years of CALIPSO observations: “the constrained models, which match the observation constraint, and the unconstrained models”. The constrained models replicate the observed interannual LCC change particularly well (ΔLCC_con=-3.49 ±1.01 %/K vs. ΔLCC_obs=-3.59 ±0.28 %/K) as opposed to the unconstrained models, which largely underestimate it (ΔLCC_unc = -1.32 ± 1.28 %/K). As a result, the amount of short-wave warming simulated by the constrained models (ΔCRE_con=2.60 ±1.13 W/m² /K) is in better agreement with the observations (ΔCRE_obs=3.05 ± 0.28 W/m² /K) than the unconstrained models (ΔCRE_con=0.87 ±2.63 W/m² /K). Depending on the type of low cloud, the observed relationship between cloud/radiation and surface temperature varies. Over the stratocumulus regions, increasing SSTs generate higher cloud top height along with a large decrease of the cloud fraction below as opposed to a slight decrease of the cloud fraction at each level over the trade cumulus regions. Our results suggest that the models must generate sustainable stratocumulus decks and moist processes in the planetary boundary layer to reproduce these observed features. Future work will focus on defining a method to objectively discriminate these cloud types that can be applied consistently in both the observations and the models.

Satellite laser range system measures the distance between the satellite and the surface of the earth by figuring out the transit time of laser pulse. The beam is refracted when it goes through the atmosphere. The atmosphere refraction effect causes laser propagation delay and path bending, which is one of the key factors to restrict the accuracy of laser ranging. In order to improve the accuracy of atmospheric refraction delay correction, it is necessary to strengthen the study of atmospheric group refractivity models and atmospheric refraction delay correction method. According to the data of Xuzhou upper air meteorological station, which are the monthly values of upper limit layers for 30 years (1981-2010) in China, three atmospheric group refractivity models were analyzed and compared. The atmospheric refraction delays to LiDAR were calculated by ray tracing method. The differences among the group refractivity models as a function of month or direction angle were given, which lay the foundation for the practical application and precision evaluation of LiDAR.

This study investigated the drop size distribution (DSD) observed by the Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) core satellite, which makes the world’s first dual-frequency preciptation observations by space-borne radar. Four years have passed since the launch of the GPM core satellite, and data have been accumulated. This study focuses on the characteristics of DSD derived from the GPM/DPR measurements. In this study, DSD parameters (especially for a mass-weighted mean diameter, Dm) which are estimated based on dual-frequency information derived from GPM/DPR are analyzed with seasonal variations and precipitation characteristics. Values of Dm are generally larger over land than over the oceans. DSD shows seasonal variation, especially over the mid-latitude ocean; Dm in the winter season over the mid-latitude ocean is larger than that in the summer season in both the Northern and Southern hemispheres. Focusing on the mid-latitude North Pacific Ocean close to Japan in winter, precipitation top height is lower and stratiform ratio is higher than those in summer. It suggests that differences of Dm are associated with those of precipitation regimes, such as organized precipitation system in summer season and extratropical frontal systems in winter season.

The analytical expressions of mode probability density (MPD) and crosstalk probability density (CPD) for LaguerreGaussian correlated Schell-mode (LGCSM) beams propagating through oceanic turbulence are established based on the geometrical optics approximation. Using the derived formulae and numerical simulation, the propagation characteristics of a single LGCSM beam in turbulent ocean are quantificationally analyzed in detail. The numerical results for the effects of all kinds of parameters on the MPD and CPD curves of a LGCSM beam propagating in the ocean environment are presented and illustrated. This research is expected to provide a convenient way and useful guidance to describe and treat the propagation of laser beam in turbulent medium.

Atmosphere visibility is one of the most important meteorological quantities in civil aviation domain. In practice the slant visibility is more important than the horizontal visibility for the pilot. With the help of the known Klett approach, a lidar can be used for determination of atmosphere extinction coefficient profiles. Consequently, the slant visibility can be obtained. However, the boundary value of the atmosphere extinction coefficient and the k factor in the relationship between atmosphere extinction coefficient and the atmosphere backscattering coefficient have to be firstly determined. In the present work we construct the nonlinear equations that the atmosphere extinction coefficient and the k factor must satisfy. As the solutions of the equations the atmosphere extinction coefficient and the k factor are for the first time obtained simultaneously. At the end the atmosphere extinction coefficients and the slant visibilities are obtained. The numerical simulations have been performed using the real lidar data and the aerosol optical depth observed by the installed sun photometer. The flights are demonstrated using the popular flight simulator Prepar3D under different visibilities.

Aerosols affect the earth’s radiation budget directly by scattering and absorbing solar radiation. In addition, aerosols may act as cloud condensation nuclei and ice nuclei, which then modify the radiative properties of clouds. Asia constitutes the largest aerosol loading worldwide. Moreover, aerosol distributions in Asia are complicated, as they are influenced by various sources. The major source of anthropogenic aerosols, such as sulfates and carbonaceous aerosols, is fuel combustion. Fuel combustion has increased since the mid-20th century in Asia. In general, aerosols exhibit remarkable effects near sources since their atmospheric lifespans are short. This suggests that aerosol impacts on climate are large over Asia. In this study, we investigated the response of aerosols over Asia to climate using model simulations. Our results indicate that aerosols reduce solar radiation and impose negative radiative forcing near the surface. Because cloud change is complicated, aerosols change cloud radiative properties, with positive or negative radiative forcing occurring near the surface. Changes in the radiation budget lead to temperature changes, which in turn influence precipitation.

Currently both RTTOV and CRTM have been used in the WRF data assimilation (DA) system for radiance assimilation under all-sky weathers. To well know the influence of both fast radiative transfer models on radiance, GPM/GMI is assimilated in WRFDA system for one storm case occurred on July 19-21, 2016, in Beijing, China，then compare the simulated brightness temperatures to their observed equivalents in this work. The comparisons show that at GMI low frequencies(10-23 GHz) the simulated Tbs from RTTOV seems better than those from CRTM due to using emissivity atlas in RTTOV since the low frequency channels are more sensitive to the land surface. For rainy pixels over land, both simulations for GMI mid-high frequency channels are significantly affected by the cloud and precipitation. For GMI 5-9 channel, the simulated Tbs from RTTOV is more consistent with the observations than those from CRTM which is dramatically lower than both the observations and the simulated Tb from RTTOV when observed Tb is lower than 260 K. For GMI channel 10-13, both simulations are quite close but far away from the observations. In a word, for GMI 1-7 channels, simulated Tbs from RTTOV are much close to the observations, while for GMI high frequency, such as higher than 89GHz, both RTTOV and CRTM still need more improved in rainy condition.