Rapid urbanization of cities has greatly modified the thermal and dynamic profile in the urban boundary layer. This paper attempts to study the interaction of urban heating and the local topographic‐induced flow circulation for a tropical coastal city, Greater Kuala Lumpur, in Malaysia. The role of sea‐and‐valley‐breeze‐orientated synoptic flow (SBOS) on the interaction is determined by comparing two intermonsoon periods. A state‐of‐the‐art numerical model, Advanced Research Weather Research and Forecasting model, is used to identify the influence of urbanization through modification of urban surfaces. The model reasonably reproduces the vertical sounding data and near‐surface weather parameters. The diurnal urban heating pattern is attributed to three predominant factors: (i) weak under calm and clear‐sky condition (morning heating), (ii) weak under larger atmospheric moisture content (late afternoon convection), and (iii) largest (1.4°C) due to differential cooling rate of urban and rural surface at night. The interaction of urban thermals and upper level SBOS affects the effect of urbanization on local circulation during the day. The urban thermals reduce the weak opposing SBOS (2 m s⁻¹) suppresses the vertical lifting of urban thermals and decelerates the sea breeze front. It is discovered that the interaction of urban heating and topographic‐induced flow is interdependent while the synoptic flow plays a critical role in modifying both factors, respectively.

Soil moisture is a critical indicator for climate change and agricultural drought, but its measurement is challenging due to large variability with land cover, soil type, time, space and depth. Satellite estimates of soil moisture are highly desirable and have become more widely available over the past decade. This study investigates and compares the performance of four surface soil moisture satellite datasets over Canada, namely, Soil Moisture and Ocean Salinity Level 3 (SMOS L3), versions 3.3 and 4.2 of European Space Agency Climate Change Initiative (ESA CCI) soil moisture product and a recent product called SMOS-INRA-CESBIO (SMOS-IC) that contains corrections designed to reduce several known sources of uncertainty in SMOS L3. These datasets were evaluated against in situ networks located in mostly agricultural regions of Canada for the period 2012 to 2014. Two statistical comparison methods were used, namely, metrics for mean soil moisture and median of metrics. The results suggest that, while both methods show similar comparisons for regional networks, over large networks, the median of metrics method is more representative of the overall correlation and variability and is therefore a more appropriate method for evaluating the performance of satellite products. Overall, the SMOS products have higher daily temporal correlations, but larger biases, against in situ soil moisture than the ESA CCI products, with SMOS-IC having higher correlations and smaller variability than SMOS L3. The SMOS products capture daily wetting and drying events better than the ESA CCI products, with the SMOS products capturing at least 75% of observed drying as compared to 55% for the ESA CCI products. Overall, for periods during which there are sufficient observations, both SMOS products are more suitable for agricultural applications over Canada than the ESA CCI products, even though SMOS-IC is able to capture soil moisture variability more accurately than SMOS L3.