Sensitivity of North American monsoon rainfall to multisource sea surface temperatures in MM5

In this article, four continually processed sea surface temperature (SST) datasets, including the Reynolds SST (RYD), the global final analysis of skin temperature at oceans (FNL), and two Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua SSTs retrieved from thermal infrared imagery (TIR) and midinfrared imagery (MIR), were compared. The results show variations from each other. In comparison with the RYD SST, the FNL data have -0.5° ∼ 0.5°C perturbations, while the TIR and MIR SSTs possess larger deviations of -2° ∼ 1°C, mainly due to algorithm and/or sensor differences in these SST datasets. A regional model, the fifth-generation Pennsylvania State University-Na tional Center for Atmospheric Research (Penn State-NCAR) Mesoscale Model (MM5), was used to investigate whether model atmospheric predictions, especially those concerning precipitation during the North American monsoon season, are sensitive to these SST variations. A comparison of rainfall, atmospheric height, temperature, and wind fields produced by model results, reanalysis data, and observations indicates that, at monthly scale, the model shows changes in the simulations for three consecutive years; in particular, rainfall amounts, timing, and even patterns vary at some specific regions. Forced by the MODIS Aqua midinfrared SST (MIR), which includes large regions with SST values lower than the conventional Reynolds SST, the MM5 rain field predictions show reduced errors over land and oceans compared to when the model is forced by other SST data. Specifically, rainfall estimates are improved over the offshore of southern Mexico, the Gulf of Mexico, the coastal regions of southern and eastern Mexico, and the southwestern U.S. monsoon active region, but only slightly improved over the monsoon core and the high-elevated Great Plains. Using MIR SST data, one is also capable of improving geopotential height and temperature fields in comparison wit he reanalysis data. © 2005 American Meteorological Society

Meteorological satellite accomplishments

The various types of meteorological satellites are enumerated. Vertical sounding, parameter extraction technique, and both macroscale and mesoscale meteorological phenomena are discussed. The heat budget of the earth-atmosphere system is considered, along with ocean surface and hydrology

Assessing Biogeochemical Impacts and Environmental Conditions Associated with Cross-Shelf High Chlorophyll Plumes in the Northern Gulf of Mexico

The northern Gulf of Mexico is a complex marine system subject to episodic physical phenomena such as loop current eddies. Flow fields generated by these eddies can result in cross-shelf exchanges between riverine influenced shelf waters and the offshore water column. This study considers the impacts of high chlorophyll plumes (HCPs) resulting from cross-shelf exchanges to the bio-optical properties of affected waters and how these plumes are influenced by their environment. The seasonal, interannual and decadal chlorophyll cycles of the Gulf of Mexico and the northern Gulf of Mexico are described to provide context for evaluating the ecological effects of HCPs. To determine the ecological effects of such exchanges, a regional 2007 cross-shelf exchange event is investigated using remotely sensed observations. The offshore ratio of bio-optical signals observed during the exchange event implies a divergence in surface water composition from the typical composition. To explore the impact of this composition change on the regional carbon budget, net primary productivity (NPP) estimates during the exchange event are compared with the climatological estimates, revealing increases of up to 330% for the corresponding time period. Select HCP CHL fields are compared with physical parameters and environmental conditions to explore drivers of HCP formation and conditions affecting HCP characteristics. This work supports suppositions that HCPs form as the result of a complex river-wind-circulation system and adds to the current understanding of CHL dynamics in the northern Gulf of Mexico by showing an association between HCP frequency and environmental conditions

Spatio-Temporal Distribution of Deep Convection Observed along the Trans-Mexican Volcanic Belt

Complex terrain features - in particular, environmental conditions, high population density and potential socio-economic damage - make the Trans-Mexican Volcanic Belt (TMVB) of particular interest regarding the study of deep convection and related severe weather. In this research, 10 years of Moderate-Resolution Imaging Spectroradiometer (MODIS) cloud observations are combined with Climate Hazards Group Infrared Precipitation with Station (CHIRPS) rainfall data to characterize the spatio-temporal distribution of deep convective clouds (DCCs) and their relationship to extreme precipitation. From monthly distributions, wet and dry phases are identified for cloud fraction, deep convective cloud frequency and convective precipitation. For both DCC and extreme precipitation events, the highest frequencies align just over the higher elevations of the TMVB. A clear relationship between DCCs and terrain features, indicating the important role of orography in the development of convective systems, is noticed. For three sub-regions, the observed distributions of deep convective cloud and extreme precipitation events are assessed in more detail. Each sub-region exhibits different local conditions, including terrain features, and are known to be influenced differently by emerging moisture fluxes from the Gulf of Mexico and the Pacific Ocean. The observed distinct spatio-temporal variabilities provide the first insights into the physical processes that control the convective development in the study area. A signal of the midsummer drought in Mexico (i.e., “canícula”) is recognized using MODIS monthly mean cloud observations

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future