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Surface Meteorology and Solar Energy (SSE) Data Release 5.1

The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].

Arctic heating

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.

International Satellite Cloud Climatology Project (ISCCP) Stage D1 3-Hourly Cloud Product - Revised Algorithm in Hierarchical Data Format (ISCCP_D1)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 Km; Longitude_Resolution=280 Km; Temporal_Resolution=3 Hourly].

CLOUD LIQUID WATER PATH

International Satellite Cloud Climatology Project (ISCCP) Stage D1 3-Hourly Cloud Product - Revised Algorithm in Native (NAT) Format (ISCCP_D1_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 Km; Longitude_Resolution=280 Km; Temporal_Resolution=3 Hourly].

GRID DATA

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base

International Satellite Cloud Climatology Project (ISCCP) TIROS Operational Vertical Sounder (TOVS) Product in Native (NAT) Format (ISCCP_TOVS_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 degree; Longitude_Resolution=280 degree; Temporal_Resolution=Daily - < Monthly].

PRECIPITABLE WATER PROFILES

Customizing NASA's Earth Science Research Products for addressing MENA Water Challenges

As projected by IPCC 2007 report, by the end of this century the Middle East North Mrica (MENA) region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. In late 2011, the World Bank, USAID and NASA have joined hands to establishing integrated, modem, up to date NASA developed capabilities for various countries in the MENA region for addressing water resource issues and adapting to climate change impacts for improved decision making for societal benefits. The main focus of this undertaking is to address the most pressing societal issues which can be modeled and solved by utilizing NASA Earth Science remote sensing data products and hydrological models. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. NASA has over fifteen satellites and thirty instruments operating on these space borne platforms and generating over 2000 different science products on a daily basis. Some of these products are soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gasses, ice and snow measurements, and many more. All of the data products, models and research results are distributed via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, drought assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Training is an important component under this activity and adequate level of training will be offered to build basic capacity to work with NASA provided data products, models for their future use. This paper provides a comprehensive introduction to NASA's Earth Science mission for understanding the behavior of our home Planet, projecting its health for future generations and applying research results solving societal issues.

Habib, Shahid

Techniques of Validation of Aerosol and Water Vapor Retrievals From MODIS

Aerosols are extremely important for global climate studies and modeling in the quest to characterize the global radiation budget and forcing. The physical characteristics, composition, abundance, and spatial distribution and dynamics of aerosols are still very poorly known. Aerosol column optical thickness and other parameters as well as column precipitable water vapor amount are some of the main atmospheric parameters retrieved from the MODIS instrument on board the Terra satellite. To ensure the reliability of these parameters, we have embarked on a very massive validation effort. This involves cross correlation between the retrievals from the satellite data and those obtained from sunphotometer measurements at a large number of ground stations spread throughout the globe. Notable among these ground stations is a large network of over 100 stations coordinated under the Aerosol Robotic Network (AERONET) project. Whereas MODIS retrieves the aerosol parameters throughout the globe once or twice a day during the daytime, the ground measurements cover only discrete locations of the earth, though the retrievals are done several times a day. We have devised a method to. match the MODIS and ground retrievals through spatial statistics for the MODIS data and temporal statistics for the ground data. This has produced good comparisons and has enabled the validation of MODIS aerosol and water vapor retrievals at over 100 discrete locations in various parts of the earth both over the land and over the ocean. Currently, the validation statistical data is produced routinely by the MODIS aerosol group and is even available not only for validation but also for use by the science community for short and long term studies at various parts of the earth. One important advantage is that the system can be expanded to incorporate more locations where ground measurements and other studies may be conducted at any time during the lifetime of MODIS.

Ichoku, Charles

International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Product - Revised Algorithm in Hierarchical Data Format (ISCCP_D2)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 Km; Longitude_Resolution=280 Km; Temporal_Resolution=Monthly].

CLOUD TOP PRESSURE

International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Product - Revised Algorithm in Native (NAT) Data Format (ISCCP_D2_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 Km; Longitude_Resolution=280 Km; Temporal_Resolution=Monthly].

CLOUD OPTICAL THICKNESS

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.

Examining Weathering of Magnesite in an Arid Environment: Implications For Jezero Crater

Introduction:Orbiter data indicatethe presence of carbonates in severallocations on the surface of Mars[1],but Jezero crater, landing site of the Perseverancerover,is the only known location where carbonatesap-pear coincident with evidence of fluvialand lacustrineactivity [2].On Earth, carbonates in close proximity to these paleoenvironments mayindicatethe presence of past microbial life,like stromatolites[3], that could re-sult inbiosignatures [2]. However,in other cases,car-bonates can also form throughthe alteration of mafic materialwiththe introductionof carbonic acid[4].Hy-drated magnesites have also been found in evaporative environments along lake shores, and in playas[5,6,7].Correctly interpreting past carbonates on Mars is there-fore critical in the search for past signs of life. In Jezero crater,both thenorthernand western fans haveMg-rich carbonates intermixed with olivine-rich material[8].According to CRISM data, magnesite(MgCO3), along with hydromagnesite(Mg5(CO3)4(OH)2•4H2O), arepotential candidatesfor these Mg-carbonates [2]. Considering the spatial con-text with olivine,there aremultiplepotential explana-tions for the presence ofMg-carbonatesin this locationincludingin-situformation via alterationof olivine-rich materialwith carbonic acid,transportationfrom farther up in the watershed, or precipitation of lacustrine car-bonates[2]. The formation of hydromagnesite rather than magnesite is favored when Mg2+saturated solutions have a high CO32-/HCO3-ratio, which, on Earth, is thought to be caused byinflow of groundwater [4]. Additionally, Mg-carbonates tend to precipitate under high pH condi-tions and are unstable at lower pH conditions [5]. Hy-dromagnesite is stable at atmospheric CO2pressure and temperature conditions common to most Earth surface environments [9]. However, it is subject to transfor-mation to magnesite after dehydration and concomitant brucite formation or dissolution and reprecipitation [10].Previousresearch suggests that hydrated car-bonates, including hydromagnesite, can formas weath-ering productsof mafic minerals in the presenceof H2O and CO2in subfreezing temperatures and would not de-hydrate under Martian atmospheric conditions [11,12].It is critical to understand the formation conditions of Mg-carbonatesbecause of the different implications for the past history of Martian environments. Therefore, in this work we are investigating the weathering of Mg-carbonatesin arid environments to helpbetter understand Mg-carbonates in Jezero crater. Study Area:The Ala-Mar Mines(East and West)near Ely, NVare the site ofmultiple magnesitedepositsfound within a calcareous tuff formationthat overlies Tertiary aged volcanic rocks.Here,magnesiteis formed via the alteration of the calcareous tuff and occurs innodules, veins,and lenses[13]. Previous work suggests magnesite deposits are associated with faults [13]. Within the West Mine, magnesite can be found in two maincontexts: (1) relatively circular zones of cauli-flower-like material found within (2) a more massivelensthat is heavily fractured on the surface.Methods.Samplesof both the cauliflower texture and more massive materialwere collectedat Ala Mar West Mine. Both samples were thenpowdered, sieved and analyzed with an inXitu Terra Portable XRD. The program QualX was used to identify potential mineral phases [14].Both samples were also optically inspected using 10x and 20x hand lenses.Figure 1. XRD patterns for the cauliflower magnesite (top) and massive magnesite (bottom). Ongoing and future work on the samples discussed above includes scanning electron microscopy (SEM), electron microprobe analysis (EMPA), and near-infra-red spectroscopy to determine whether hydromagnesite is present. Separation and analysis of the clay-size frac-tionby XRD will helpto better identify any phyllosili-cate phases present. Results and Discussion:Both textures are a white to light tan with a porcelain luster on weathered sur-faces, along with minor iron staining in some areas. Likewise, both textures are white with a porcelain luster on fresh surfaces. When broken apart, the massive mag-nesite shows macroscopic crystals, unlike the cauli-flower magnesite. XRD analysis shows that both samples have high concentrationsof magnesite with lesser amounts of thecarbonatemineral huntite(Mg3Ca(CO3)4; Figure1).The more massive samplecontainsa serpentine-groupmineral,with lizardite being apotential candidate. The cauliflower sample has several minor peaks that may correspond to hydromagnesite(Figure 1), although more work is needed to confirm this.Additionally, thecauliflower deposits closely resemble hydromagnesite deposits found in southwestern Turkey, formed via mi-crobialites[15].As such, it is likely that moreaqueous alterationor weatheringis occurring at the locations where the cauliflower magnesite is present. However, additional field work will need to be conducted to con-firm this hypothesis. Conclusions and Future Work:Future work will include field mapping of fault locations andadditional samplingof the different magnesite types as well as of the calcareous tuffmaterial.We will also look specifi-cally for potential weathering products of magnesite in this arid location, which may yield important insight into the Mg-carbonates located in Jezero crater. XRD analyses on aPANalytical XRDusing non-ambient stages will be used to investigate the stability of hydro-magnesiteat different humiditiesand temperatures, which has implications for samples to bereturned to Earth in the future. Additionally, thermal and evolved gas analysis of magnesite and hydromagnesite will be compared to results from Gale Craterto help interpret the mineralogy inthat location[16]. The results of this research will further ourunderstanding of carbonate for-mationin volcanic settingsandtheirweathering pro-cessesin arid environments. Acknowledgments:We acknowledge funding for this research from Jacobs Technology at the Johnson Space Center.We would also like to thank Ngoc Luu, Christopher Adcock, Richard Allanson, and the rest of the UNLV Soil Science Teamfor their continued sup-portwith troubleshooting and otherlab work. References:[1] Ehlmann, B.L., and Edwards, C.S. (2014) Annual Review of Earth and Planetary Sci., 42, 291–315. [2] Horgan, B.H.N., et al. (2020) Icarus, 339, 113526. [3] Bosak, T., et al. (2013) Annual Review of Earth and Planetary Sci, 41, 21–44. [4] Pohl, W.L. (1989) Gebriider Borntraege, 28, 1-13. [5] Müller, G., et al. (1972) Die Naturwissenschaften, 59, 158–164. [6] Walter, M.R., et al. (1973) Journal of Sedimentary Pe-trology, 43, 1021–1030. [7] Braithwaite, C.J.R., and Zedef, V. (1994) Sedimentary Geology, 92, 1–5. [8] Goudge, T.A., et al. (2015) JGR: Planets, 120, 775–808. [9] Langmuir, D. (1965) Journal of Geology, 73, 730–754. [10] Zhang, P., et al. (2000) Applied Geo-chem., 286, 1748–1753. [11] Calvin, W.M., et al. (1994) JGR, 99, 14659-14675. [12]Russell, M.J., et al. (1999) Journal of the Geological Society of London, v. 156, p. 869–888. [13] Faust, G.T., and Callaghan, E. (1948) GSA Bulletin, 59, 11–74. [14] Altomare, A., et al. (2015) J. of Applied Crystallography, 48, 598–603. [15] Zedef, V.,et al. (2000) Economic Geology, 95, 429–445. [16] Leshin, L.A. et al., (2013) Science, 341, 1–9

A W Provow