Validating a rapid-update satellite precipitation analysis across telescoping space and time scales

In order to properly utilize remotely sensed precipitation estimates in hydrometeorological applications, knowledge of the accuracy of the estimates are needed. However, relatively few ground validation networks operate with the necessary spatial density and time-resolution required for validation of high-resolution precipitation products (HRPP) generated at fine space and time scales (e.g., hourly accumulations produced on a 0.25° spatial scale). In this article, we examine over-land validation statistics for an operationally designed, meteorological satellite-based global rainfall analysis that blends intermittent passive microwave-derived rainfall estimates aboard a variety of low Earth-orbiting satellite platforms with sub-hourly time sampling capabilities of visible and infrared imagers aboard operational geostationary platforms. The validation dataset is comprised of raingauge data collected from the dense, nearly homogeneous, 1-min reporting Automated Weather Station (network of the Korean Meteorological Administration during the June to August 2000 summer monsoon season. The space-time RMS error, mean bias, and correlation matrices were computed using various time windows for the gauge averaging, centered about the satellite observation time. For ±10 min time window, a correlation of 0.6 was achieved at 0.1° spatial scale by averaging more than 3 days; coarsening the spatial scale to 1.8° produced the same correlation by averaging over 1 h. Finer than approximately 24-h and 1° time and space scales, respectively, a rapid decay of the error statistics was obtained by trading-off either spatial or time resolution. Beyond a daily time scale, the blended estimates were nearly unbiased and with an RMS error of no worse than 1 mm day^?1.     

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.     

A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer(IASI) channels was re-selected from 314 EUMETSAT channels.In selecting channels,we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis(1D-Var) for the Unified Model(UM) data assimilation system at the Met Office,using the channel score index(CSI) as a figure of merit.Then,200 channels were selected in order by counting each individual channel's CSI contribution.Compared with the operationally used 183 channels for the UM at the Met Office,the new set shares 149 channels,while the other 51 channels are new.Also examined is the selection from the entropy reduction method with the same 1D-Var approach.Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method.This is because the most important channels can be selected across the whole IASI observation spectrum.In the experimental trial runs using the UM global assimilation system,the new channels had an overall neutral impact in terms of improvement in forecasts,as compared with results from the operational channels.However,upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels.The reduction of moist biases was mainly due to the additional water vapor channels,which are sensitive to the upper-tropospheric water vapor.     

Diurnal variation of outgoing longwave radiation associated with high cloud and UTH changes from Meteosat-5 measurements

Diurnal variations of outgoing longwave radiation (OLR) are examined in conjunction with diurnal variations of high cloud and upper tropospheric humidity (UTH) over the Indian Ocean and surrounding land areas using Meteosat-5 measurements. Most land areas exhibit a significant diurnal variation of OLR with the largest amplitude over the Arabian Peninsula, whereas the diurnal variation of OLR is much weaker over the Indian Ocean. While diurnal maxima of OLR are found in the early afternoon over many regions of the analysis domain following the diurnal cycle of solar heating, convectively active regions of both land and ocean where high cloud and UTH exhibit distinct diurnal variations show OLR maxima before local noon. These results indicate that high cloud development in the afternoon induces a shift in local time of OLR maxima over convective regions. In agreement with earlier studies it is shown that UTH diurnal variations are less important in regard to their impact on the OLR variations.     

Two Types of Diurnal Variations in Heavy Rainfall during July over Korea※

This study examined the characteristics of the diurnal variations of heavy rainfall (≥110 mm in 12 hours) in Korea and the related atmospheric circulation for July from 1980?2020. During the analysis period, two dominant pattens of diurnal variation of the heavy rainfall emerged: all-day heavy rainfall (AD) and morning only heavy rainfall (MO) types. For the AD-type, the heavy rainfall is caused by abundant moisture content in conjunction with active convection in the morning (0000?1200, LST; LST = UTC + 9) and the afternoon hours (1200?2400 LST). These systems are related to the enhanced moisture inflow and upward motion induced by the strengthening of the western North Pacific subtropical high and upper-tropospheric jet. For the MO-type, heavy rainfall occurs mostly in the morning hours; the associated atmospheric patterns are similar to the climatology. We find that the atmospheric pattern related to severe heavy rainfalls in 2020 corresponds to a typical AD-type and resembles the 1991 heavy-rainfall system in its overall synoptic/mesoscale circulations. The present results imply that extremely heavy rainfall episodes in Korea during the 2020 summer may occur again in the future associated with the recurring atmospheric phenomenon related to the heavy rainfall.     

Evidence of the recent decade change in global fresh water discharge and evapotranspiration revealed by reanalysis and satellite observations

Variations of global evapotranspiration (ET) and fresh water discharge from land to oceans (D) are important components of global climate change, but have not been well monitored. In this study, we present an estimate of twenty years (1989 to 2008) variations of global D and ET derived from satellite remote-sensed measurements and recent reanalysis products, ERA-Interim and CFSR, by using a novel application of the water balance equations separately over land and over oceans. Time series of annual mean global D and ET from both satellite observations and reanalyses show clear positive and negative trends, respectively, as a result of modest increase of oceanic evaporation (E _o ). The inter-annual variations of D are similar to the in-situ-based observations, and the negative trend of ET supports the previous result that relative humidity has decreased while temperature has increased on land. The results suggest considerable sensitivity of the terrestrial hydrological cycles (e.g., D and ET) to small changes in precipitation and oceanic evaporation.     

Intercomparison of height assignment methods for opaque clouds over the tropics

Several methods of determining the height of opaque clouds over the tropics were compared using geostationary satellite measurements. The possible use of ozone channel measurements around the 9.7-μm ozone absorption band was examined in conjunction with the infrared window (IRW; 10.8 μm), H₂O (6.3 μm), and CO₂ (13.4 μm) channels, which are generally used for the assignment of cloud heights. Cloud top heights were retrieved from Meteosat-8 measurements with the aid of radiative transfer calculations using reanalysis data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) as inputs. By using cloud top heights from collocated CloudSat observations as a reference, cloud top heights were determined from the one-channel radiance, two-channel brightness temperature difference (BTD), and two-channel radiance ratio methods, and the respective results were then compared for clouds with geometrical thicknesses of > 4 km. Overall, the retrievals from the CO₂-IRW ratio and O₃-CO₂ ratio methods are in substantial agreement with CloudSat observations, while the other methods either underestimate cloud top heights or demonstrate a lower ratio of successful height assignment. The O₃-CO₂ ratio method appears to be less practical than the CO₂-IRW ratio method because it requires two absorption channels. Our comparison also shows that the BTD between the ozone and IRW channels yields information that is similar to that of the IRW channel alone. It further shows that the O₃-IRW combination is not appropriate for the two-channel radiance ratio method. These results suggest that the inclusion of the ozone channel in BTD and ratio methods may not offer any significant improvement in convective cloud height retrieval over the tropics. In conclusion, the CO₂-IRW ratio method appears to provide the most accurate retrievals for opaque clouds.     

An accurate and efficient radiative transfer model for simulating all-sky images from Fengyun satellite radiometers

Science China Earth Sciences - Forward radiative transfer models (RTM) are an indispensable tool for quantitative applications of satellite radiometers, e.g., for data calibration, instrument...     

Physical explanation of the weakened brightness temperature difference signal over the yellow sea during a dust event: Case study for March 15–16, 2009

This paper attempts to explain the cause of weakening or disappearing brightness temperature difference (BTD) signatures, in particular, over the Yellow Sea during the March 15–16, 2009 dust event. Using a simple correction approach that removes the effects of emissivity difference and water vapor effect difference, we confirmed that the weakening or disappearing BTD signatures noted over the Yellow Sea are largely due to the spectral emissivity contrast between land and ocean. The weakening or disappearing dust is hypothesized to be pronounced when the dust loading is weak because of the surface contribution to the top of atmosphere radiance, and that it is mainly due to the difference in spectral emissivity over the window band between land and ocean. It is further suggested that water vapor may be considered as a correction factor in spite of its smaller contribution.