Evaluation of MERRA Land Surface Estimates in Preparation for the Soil Moisture Active Passive Mission

The authors evaluated several land surface variables from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) product that are important for global ecological and hydrological studies, including daily maximum (Tmax) and minimum (Tmin) surface air temperatures, atmosphere vapor pressure deficit (VPD), incident solar radiation (SWrad), and surface soil moisture. The MERRA results were evaluated against in situ measurements, similar global products derived from satellite microwave [the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E)] remote sensing and earlier generation atmospheric analysis [Goddard Earth Observing System version 4 (GEOS-4)] products. Relative to GEOS-4, MERRA is generally warmer (~0.5°C for Tmin and Tmax) and drier (~50 Pa for VPD) for low- and middle-latitude regions (\u3c50°N) associated with reduced cloudiness and increased SWrad. MERRA and AMSR-E temperatures show relatively large differences (\u3e3°C) in mountainous areas, tropical forest, and desert regions. Surface soil moisture estimates from MERRA (0–2-cm depth) and two AMSR-E products (~0–1-cm depth) are moderately correlated (R ~ 0.4) for middle-latitude regions with low to moderate vegetation biomass. The MERRA derived surface soil moisture also corresponds favorably with in situ observations (R = 0.53 ± 0.01, p \u3c 0.001) in the midlatitudes, where its accuracy is directly proportional to the quality of MERRA precipitation. In the high latitudes, MERRA shows inconsistent soil moisture seasonal dynamics relative to in situ observations. The study’s results suggest that satellite microwave remote sensing may contribute to improved reanalysis accuracy where surface meteorological observations are sparse and in cold land regions subject to seasonal freeze–thaw transitions. The upcoming NASA Soil Moisture Active Passive (SMAP) mission is expected to improve MERRA-type reanalysis accuracy by providing accurate global mapping of freeze–thaw state and surface soil moisture with 2–3-day temporal fidelity and enhanced (≤9 km) spatial resolution

Aerosol-cloud-precipitation interaction based on remote sensing and cloud-resolving modeling over the Central Himalayas

The Central Himalayan region experiences pronounced orographic precipitation related to the South Asian summer monsoon, typically occurring from June to September. Atmospheric aerosols can influence regional and global climate through aerosol-radiation (ARI) and aerosol-cloud interactions (ACI). The study of the aerosol-precipitation relationship over the Central Himalayan region during the summer monsoon season is important due to extreme pollution over the upwind Indo-Gangetic Plains, enhanced moisture supply through monsoonal flow, and steep terrain of the Himalayas modulating the orographic forcing. This dissertation aims to study the impact of atmospheric aerosols, from natural and anthropogenic sources, in modulating the monsoonal precipitation, cloud processes, and freezing isotherm over the central Himalayas. The long-term (2002 – 2017) satellite-retrieved and reanalysis datasets showed regardless of the meteorological forcing, compared to relatively cleaner days, polluted days with higher aerosol optical depth is characterized by the invigorated clouds and enhanced precipitation over the southern slopes and foothills of the Himalayas. The mean freezing isotherm increased by 136.2 meters in a polluted environment, which can be crucial and significantly impact the hydroclimate of the Himalayas. Due to the limitations of satellite-retrieved observational data, these results underlined the need for state-of-the-art Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in a cloud-resolving scale to better represent and study the impact of the aerosols from different sources through radiation and microphysics pathways over the complex terrain of the Central Himalayas. A cloud-resolving WRF-Chem simulation is performed to assess the impact of anthropogenic and remotely transported dust aerosols on the convective processes and elevation-dependent precipitation. Long-range transported dust aerosols significantly impacted cloud microphysical properties and enhanced the precipitation by 9.3% over the southern slopes of the Nepal Himalayas. The mid-elevation of the Central Himalayas, generally between 1000 and 3000 meters, acted as the region below and above which the diurnal variation and precipitation of various intensities (light, moderate, and heavy) responded differently for ARI, ACI, and the combined effect of aerosols. Due to the ARI effect of aerosols, the light precipitation is suppressed by 17% over the Central Himalayas. The ACI effect dominated and resulted in enhanced heavy precipitation by 12% below 2000 m ASL, which can potentially increase the risk for extreme events (floods and landslides). In contrast, above 2000 m ASL, the suppression of precipitation due to aerosols can be critical for the regional supply of water resources. The overview of the study suggests that the natural and anthropogenic aerosols significantly modulate the convective processes, monsoonal precipitation, and freezing isotherm over the Central Himalayan region, which could pose significant consequences to the changing Himalayan hydroclimate

Remote Sensing of Precipitation: Volume 2

Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne

Energy and Water Cycles in the Third Pole

As the most prominent and complicated terrain on the globe, the Tibetan Plateau (TP) is often called the “Roof of the World”, “Third Pole” or “Asian Water Tower”. The energy and water cycles in the Third Pole have great impacts on the atmospheric circulation, Asian monsoon system and global climate change. On the other hand, the TP and the surrounding higher elevation area are also experiencing evident and rapid environmental changes under the background of global warming. As the headwater area of major rivers in Asia, the TP’s environmental changes—such as glacial retreat, snow melting, lake expanding and permafrost degradation—pose potential long-term threats to water resources of the local and surrounding regions. To promote quantitative understanding of energy and water cycles of the TP, several field campaigns, including GAME/Tibet, CAMP/Tibet and TORP, have been carried out. A large amount of data have been collected to gain a better understanding of the atmospheric boundary layer structure, turbulent heat fluxes and their coupling with atmospheric circulation and hydrological processes. The focus of this reprint is to present recent advances in quantifying land–atmosphere interactions, the water cycle and its components, energy balance components, climate change and hydrological feedbacks by in situ measurements, remote sensing or numerical modelling approaches in the “Third Pole” region

ESTIMATING SURFACE LONGWAVE RADIATION AND APPLICATIONS TO HIGH LATITUDE ISSUES

Two models, with distinct advantages for calculating downwelling surface longwave (DSLW) radiation under all sky conditions are presented. Both models are driven with a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 cloud parameters and information from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim model. To compute the clear sky component of DSLW the first model DSLW/UMD v1 utilizes a globally applicable parameterization. The second generation model DSLW/UMD v2 utilizes a two layer feed-forward artificial neural network with sigmoid hidden neurons and linear output neurons. When computing the cloud contribution to DSLW, DSLW/UMD v1 implements a commonly used statistical model to calculate cloud vertical height while in DSLW/UMD v2 the cloud base temperature is estimated by using an independent artificial neural network based on spatially and temporally co- located MODIS and Cloudsat Cloud Profiling Radar (CPR) and the Cloud-Aerosol Lidar and Infrared Pathfiner Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. Daily average estimates of DSLW for 2003 to 2009 are compared against ground measurements from the Baseline Surface Radiation Network (BSRN) and show significant improvements over currently available model estimates. DSLW/UMD v2 as optimized for Polar Regions along with a UMD develop shortwave model are used to investigate the role of radiative components in Arctic sea ice anomalies. The correlation between downwelling surface longwave and shortwave radiation and sea ice anomaly for the period from 2003 to 2007 is investigated using the latest Moderate Resolution Imagining Spectroradiometer (MODIS) level-3 cloud parameters and information from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim model. All sky downwelling surface longwave radiation (DSLW), all sky downwelling shortwave radiation (DSSW), all sky total downwelling shortwave and longwave radiation (DSSW + DSLW), and cloud total cloud forcing are individually examined to determine their respective correlation to sea ice anomaly. It is determined that these radiation components are not the primary drivers for major sea ice anomalies that occur during the investigated time frame within the 120o E to 210o E region

Climate Change and Environmental Sustainability- Volume 5

This volume of Climate Change and Environmental Sustainability covers topics on greenhouse gas emissions, climatic impacts, climate models and prediction, and analytical methods. Issues related to two major greenhouse gas emissions, namely of carbon dioxide and methane, particularly in wetlands and agriculture sector, and radiative energy flux variations along with cloudiness are explored in this volume. Further, climate change impacts such as rainfall, heavy lake-effect snowfall, extreme temperature, impacts on grassland phenology, impacts on wind and wave energy, and heat island effects are explored. A major focus of this volume is on climate models that are of significance to projection and to visualise future climate pathways and possible impacts and vulnerabilities. Such models are widely used by scientists and for the generation of mitigation and adaptation scenarios. However, dealing with uncertainties has always been a critical issue in climate modelling. Therefore, methods are explored for improving climate projection accuracy through addressing the stochastic properties of the distributions of climate variables, addressing variational problems with unknown weights, and improving grid resolution in climatic models. Results reported in this book are conducive to a better understanding of global warming mechanisms, climate-induced impacts, and forecasting models. We expect the book to benefit decision makers, practitioners, and researchers in different fields and contribute to climate change adaptation and mitigation

Spatio-temporal assessment of WRF, TRMM and in situ precipitation data in a tropical mountain environment (Cordillera Blanca, Peru)

The estimation of precipitation over the broad range of scales of interest for climatologists, meteorologists and hydrologists is challenging at high altitudes of tropical regions, where the spatial variability of precipitation is important while in situ measurements remain scarce largely due to operational constraints. Three different types of rainfall products - ground based (kriging interpolation), satellite derived (TRMM3B42), and atmospheric model outputs (WRF - Weather Research and Forecasting) - are compared for 1 hydrological year in order to retrieve rainfall patterns at timescales ranging from sub-daily to annual over a watershed of approximately 10 000 km(2) in Peru. An ensemble of three different spatial resolutions is considered for the comparison (27, 9 and 3 km), as long as well as a range of timescales (annual totals, daily rainfall patterns, diurnal cycle). WRF simulations largely overestimate the annual totals, especially at low spatial resolution, while reproducing correctly the diurnal cycle and locating the spots of heavy rainfall more realistically than either the ground-based KED or the Tropical Rainfall Measuring Mission (TRMM) products. The main weakness of kriged products is the production of annual rainfall maxima over the summit rather than on the slopes, mainly due to a lack of in situ data above 3800 ma.s.l. This study also confirms that one limitation of TRMM is its poor performance over ice-covered areas because ice on the ground behaves in a similar way as rain or ice drops in the atmosphere in terms of scattering the microwave energy. While all three products are able to correctly represent the spatial rainfall patterns at the annual scale, it not surprisingly turns out that none of them meets the challenge of representing both accumulated quantities of precipitation and frequency of occurrence at the short timescales (sub-daily and daily) required for glacio-hydrological studies in this region. It is concluded that new methods should be used to merge various rainfall products so as to make the most of their respective strengths