Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

Precipitation measurements provide crucial information for hydrometeorological applications. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. This study examines the performance of NASA's Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM) satellite precipitation dataset in capturing the spatio-temporal variability of weather events compared to the German weather radar dataset RADOLAN RW. Besides quantity, also timing of rainfall is of very high importance when modeling or monitoring the hydrologic cycle. Therefore, detection metrics are evaluated along with standard statistical measures to test both datasets. Using indices like probability of detection allows a binary evaluation showing the basic categorical accordance of the radar and satellite data. Furthermore, a pixel-by-pixel comparison is performed to assess the ability to represent the spatial variability of rainfall and precipitation quantity. All calculations are additionally carried out for seasonal subsets of the data to assess potentially different behavior due to differences in precipitation schemes. The results indicate significant differences between the datasets. Overall, GPM IMERG overestimates the quantity of precipitation compared to RADOLAN, especially in the winter season. Moreover, shortcomings in detection performance arise in this season with significant erroneously-detected, yet also missed precipitation events compared to the weather radar data. Additionally, along secondary mountain ranges and the Alps, topographically-induced precipitation is not represented in GPM data, which generally shows a lack of spatial variability in rainfall and snowfall estimates due to lower resolution

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Spaceborne precipitation radars are powerful tools used to acquire adequate and high-quality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM) mission, which deployed the first spaceborne Ka- and Ku-dual frequency radar (DPR), was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM). This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR’s improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h) detected by GPM DPR are ~1.7 and ~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku) and single frequency (Ku) methods performed similarly. In both inner (the central 25 beams) and outer swaths (1–12 beams and 38–49 beams) of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type “other” from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02%) of stratiform (convective) precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB) height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne radar precipitation retrievals and benefit hydrological and meteorological research

Development of tools for water management in the Hatra watershed (Northwestern Iraq) using satellite technologies

“All around the world the demand for water is increasing, especially in arid and semi-arid regions, including Iraq which subject to continuous desertification that is worsening, more importantly the Jezira region in northwestern Iraq. Thus, it’s crucial to have a better strategy for water management. One of these strategies is to promote groundwater recharge for restoring the aquifer depletion. The successful groundwater recharge is limited by some potential data such as the annual water budge and precipitation measurements. The atomospheric and hydrological observations are limited by sparse population which tends to be less in arid and semi-arid regions. Therefore, an alternative to the ground measurement of rainfall is needed. Satellite-based measurements limit the restriction of ground station. However, the satellite products have significant uncertainty. Therefore, seven precipitation estimates have tested against rain gauges in Orange County and Los Angeles County, California. In order to establish a water management strategy in Jezira region, annual water budget should be known, which could be measure through observational discharge station. Unfortunately, only few months of discharge was measured manually in the north Jezira, which Hatra subwatershed. Computer model was used to recover the streamflow measurement. The Soil and Water Assessment Tool (SWAT) was great candidate to overcome the problem. The observational data of stream discharge was used to calibrate the model. In conclusion, water management is possible in ungauged arid and semi-arid regions by using remote sensing data and computer modeling”--Abstract, page iv

Ocean Vector Wind Measurement Potential from the Global Precipitation Measurement Mission using a Combined Active and Passive Algorithm

Ocean surface vector wind (OVW) is an essential parameter for understanding the physics and dynamics of the ocean-atmosphere system, thereby improving weather forecasting and climate studies. Satellite scatterometers, synthetic aperture radars, and polarimetric microwave radiometers have provided almost global coverage of ocean surface vector wind for the last four decades. Nonetheless, a consistent and uninterrupted long-time data record with the capability of resolving sub-diurnal variability has remained a critical challenge over the years. The Global Precipitation Measurement Mission (GPM) is a satellite mission designed to provide space-based precipitation information on a global scale with complete diurnal sampling. This dissertation presents a combined active and passive retrieval algorithm to investigate the feasibility of ocean surface vector wind measurements from the GPM core satellite by utilizing its Ku- and Ka-band Dual-frequency Precipitation Radar (DPR) and the multi-frequency GPM Microwave Imager (GMI) observations. The unique GPM active and passive geophysical model functions were empirically developed by characterizing the anisotropic nature of ocean backscatter of normalized radar cross-section (δ°) and brightness temperature (TB) at multiple bands. For passive GMF, the modified 2nd Stoke\u27s parameter (linear combination of V and H-pol TBs) was used to mitigate the atmospheric contamination and to enhance the anisotropic wind direction signal superimposed on GMI TBs. The GMFs were combined in a maximum likelihood estimation (MLE) algorithm to infer the OVW. Finally, the retrieval algorithm was validated by comparing OVW retrievals with collocated NASA Advanced Scatterometer (ASCAT) wind vectors. The wind speed and direction retrieval performance statistics are promising and comparable with those of conventional scatterometer and polarimetric radiometer data products. The algorithm demonstrates the capability of the GPM to provide a long-term OVW data record for the entire GPM-TRMM era, which may include unique monthly diurnal OVW statistics

Development of a new global rain model for radio regulation

Signal attenuation due to rain scatter is the dominant fade mechanism on the majority of high-capacity microwave telecommunications links, both terrestrial and Earth-space. These links carry a large proportion of the information that underpins the way modern life functions and is a vital component of national infrastructure. Many studies have established the virtuous cycle that exists between the development of telecommunications infrastructure and economic growth. Therefore, it is important that rain fade models exist for the design and optimisation of telecommunications networks, globally, but especially in developing countries.A set of internationally recognised and agreed radio propagation models is maintained by the International Telecommunications Union - Radiocommunication Sector (ITU-R) in the form of Recommendations. A fundamental input parameter to many of these models is the point one-minute rain rate exceeded for 0.01% (about 50 minutes) of an average year. Historically, the collection of one-minute rain rates has been rare and so very few regions of the world have measured this important parameter. Where local data are not available, the full distribution of one-minute rain rates, including the 0.01% exceeded rate, can be obtained from Rec. ITU-R P.837-7. The input parameters to this Recommendation are the average monthly temperatures and rain accumulations.The network of meteorological stations is very sparse in equatorial developing countries. This limits the reliability of monthly rain accumulation statistics. ITU-R models are validated against DBSG3: the database of link and meteorological measurements maintained by ITU-R Study Group 3. However, there is very little data from the Tropics in DBSG3. Therefore, there are legitimate concerns that the ITU-R P.837-7 model may not work accurately in the Tropics.This thesis uses rain rates derived from the satellite Earth observation Tropical Rain Measuring Mission, TRMM, to estimate point one-minute rain rate distributions in the Tropics. Two distinct uses of these data have been tested. Initially, the measured distributions of TRMM rain rates were used to estimate rain distributions in the Tropics. A method was developed to transform TRMM rain rate distributions to those needed for radio systems, based on UK rain radar data. In many cases, this method performed better than Rec. ITU-R P.837-7, particularly with databases of rain rates not included in DBSG3. To extend the work to global application, TRMM data were used to estimate the monthly rain rate distributions conditional upon monthly temperature and accumulation, as used in Rec. ITU-R P.837-7. These were then used to replace the analytic distributions in the Recommendation. The method worked well on several databases of measurements, but appeared to be biased in temperate regions. The measured TRMM conditional distributions were replaced by curve-fit approximations and a hybrid method was developed that combined the standard Rec. ITU-R P.837-7 prediction with the curve-fit TRMM prediction. This algorithm performed as well as or better than Rec. ITU-R P.837-7 for most test databases and at most time percentages.The direct use of satellite Earth observation data to produce distributions of point one-minute rain rates is a radical departure from methods used before. This thesis has shown the potential of satellite-based measurements to replace the current methods based on downscaling numerical weather prediction output. In the future when more satellite data are available, spanning the globe, this suggests that direct use of satellite data will become standard