Interpretable Models Capture the Complex Relationship Between Climate Indices and Fire Season Intensity in Maritime Southeast Asia
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By analyzing geophysical fluids geographic distribution, we can isolate the regional provenance for some of the important signals in polar motion. An understanding of such will enable us to determine whether certain climate signals can have an impact on polar motion. Here we have compared regional patterns of three surficial fluids: the atmosphere, ocean and land-based hydrosphere. The oceanic excitation function of polar motion was estimated with the ECCO/JPL data - assimilating model, and the atmospheric excitation function was determined from NCEP/NCAR reanalyses. The excitation function due to land hydrology was estimated from the Gravity Recovery and Climate Experiment (GRACE) data by an indirect approach that determines water thickness. Our attention focuses on the regional distribution of atmospheric and oceanic excitation of the annual and Chandler wobbles during 1993-2010, and on hydrologic excitation of these wobbles during 2002.9-2011.5. It is found that the regions of maximum fractional covariance (those exceeding a value of 3 .10 -3) for the annual band are over south Asia, southeast Asia and south central Indian ocean, for hydrology, atmosphere and ocean respectively; and for the Chandler period, areas over North America, Asia, and South America; and scattered across the southern oceans for the atmosphere and oceans respectively
Biophysical vegetation responses to elevated atmospheric carbon dioxide (CO2) affect regional hydroclimate through two competing mechanisms. Higher CO2 increases leaf area (LAI), thereby increasing transpiration and water losses. Simultaneously, elevated CO2 reduces stomatal conductance and transpiration, thereby increasing rootzone soil moisture. Which mechanism dominates in the future is highly uncertain, partly because these two processes are difficult to explicitly separate within dynamic vegetation models. We address this challenge by using the GISS ModelE global climate model to conduct a novel set of idealized 2×CO2 sensitivity experiments to: evaluate the total vegetation biophysical contribution to regional climate change under high CO2; and quantify the separate contributions of enhanced LAI and reduced stomatal conductance to regional hydroclimate responses. We find that increased LAI exacerbates soil moisture deficits across the sub‐tropics and more water‐limited regions, but also attenuates warming by ∼0.5–1°C in the US Southwest, Central Asia, Southeast Asia, and northern South America. Reduced stomatal conductance effects contribute ∼1°C of summertime warming. For some regions, enhanced LAI and reduced stomatal conductance produce nonlinear and either competing or mutually amplifying hydroclimate responses. In northeastern Australia, these effects combine to exacerbate radiation‐forced warming and contribute to year‐round water limitation. Conversely, at higher latitudes these combined effects result in less warming than would otherwise be predicted due to nonlinear responses. These results highlight substantial regional variation in CO2‐driven vegetation responses and the importance of improving model representations of these processes to better quantify regional hydroclimate impacts.
The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial carbon dioxide fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem carbon dioxide exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated carbon dioxide fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r (exp 2) =0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r (exp 2)=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land carbon dioxide fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land carbon dioxide fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land carbon dioxide fluxes. These data-driven estimates can provide a new opportunity to assess carbon dioxide fluxes in Asia and evaluate and constrain terrestrial ecosystem models.
The evolution of remote sensing techniques in the developing countries of southeast Asia is reviewed. The use of the images for monitoring soil, water, and vegetation resources, in order to develop a national policy for conservation of the resources, is described. The remote sensing data are helpful in observing deforestation in southeast Asia; however, excessive cloud coverage does not allow accurate evaluation of the rice crop. The effects of the capabilities of the developing countries to process the data and remote sensing program of industrial countries on the future application of satellite imagery in developing countries are studied. The need for improved data banking and dissemination of the imagery is analyzed. Agreements on proprietary rights due to the improved ground resolution of orbital sensors are required. The designing of remote sensing equipment to meet the requirements of its users is discussed.
Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth's radiation and water budget. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds from the soil to the atmosphere; the hydrological cycle (i.e., run off and evaporation); land surface reflectivity and emissivity; as well as ecosystem biodiversity and stability. Analyses from satellite measurements reveal that smoke is frequently present solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by as much as 100 (20) W/sq m over the month of March 2000. In addition, the reduction in cloud spectral reflectance at 670 run is large enough to lead to significant errors in retrieving cloud properties (e.g., optical thickness and effective radius) from satellite measurements. The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Estimating the burning fuel (e.g., bark, branches, and wood), an important part of studying regional carbon cycle, may rely on utilizing a wide range of distinctive spectral features in the shortwave and longwave regions. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, networks of ground-based instruments and dedicated field experiments. A new initiative will be proposed and discussed.
Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth- atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth s radiation and water budget. Analyses from satellite measurements reveal the reflected solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by 100 (20) Watts per square meter over the month of March 2000. In addition, the reduction in cloud spectral reflectance is large enough to lead to significant errors in satellite retrievals of cloud properties (e.g., optical thickness and effective radius). The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, ground-based networks and dedicated field experiments. BASE-ASIA initiative has been proposed and will be discussed.
A primary goal of the Atmospheric Chemistry and Climate Model IntercomparisonProject (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100climate change in the current generation of climate models. Here we evaluate historicaland 5 future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of whichalso participated in the Coupled Model Intercomparison Project phase 5 (CMIP5).The models generally reproduce present-day climatological total aerosol opticaldepth (AOD) relatively well. components to this total, however, and most appear to underestimate AOD over East10 Asia. The models generally capture 1980-2000 AOD trends fairly well, though theyunderpredict AOD increases over the YellowEastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, SouthAmerica and Southern Hemisphere Africa.We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing AF, including direct andindirect effects). The models calculated all aerosol all-sky 1850 to 2000 global meanannual average RF ranges from 0.06 to 0.49 W m(sup -2), with a mean of 0.26 W m(sup -2) and a median of 0.27 W m(sup -2. Adjusting for missing aerosol components in some modelsbrings the range to 0.12 to 0.62W m(sup -2), with a mean of 0.39W m(sup -2). Screen20ing the models based on their ability to capture spatial patterns and magnitudes ofAOD and AOD trends yields a quality-controlled mean of 0.42W m(sup -2) and range of0.33 to 0.50 W m(sup -2) (accounting for missing components). The CMIP5 subset of ACCMIPmodels spans 0.06 to 0.49W m(sup -2), suggesting some CMIP5 simulations likelyhave too little aerosol RF. A substantial, but not well quantified, contribution to histori25cal aerosol RF may come from climate feedbacks (35 to 58). The mean aerosol AF during this period is 1.12W m(sup -2) (median value 1.16W m(sup -2), range 0.72 to1.44W m(sup -2), indicating that adjustments to aerosols, which include cloud, water vaporand temperature, lead to stronger forcing than the aerosol direct RF.
The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5 latitude by 2-3 longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia,Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DCD1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRAs precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphereocean controls on fire weather, and calibration of FWI-based fire prediction models.
Airborne dusts from northern China contribute a significant part of the air quality problem and, to some extent, regional climatic impact in Asia during spring-time. However, with the economical growth in China, increases in the emission of air pollutants generated from industrial and vehicular sources will not only impact the radiation balance, but adverse health effects to humans all year round. In addition, both of these dust and air pollution clouds can transport swiftly across the Pacific reaching North America within a few days, possessing an even larger scale effect. The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites (e.g., MODIS, SeaWiFS, TOMS, etc.) and its evolution monitored by satellites and surface network. Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth's radiation and water budget. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds from the soil to the atmosphere; the hydrological cycle (i.e., run off and evaporation); land surface reflectivity and emissivity; as well as ecosystem biodiversity and stability. Two new initiatives, EAST-AIRE (East Asian Study of Tropospheric Aerosols: an International Regional Experiment) and BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment) will be presented and discussed their contribution to better understand the impacts of aerosols on regional-to-global climate, hydrological and carbon cycles, and tropospheric chemistry.
In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001-2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia-regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes.
The open source revolution of Earth Observation (EO) science has resulted in increased openness of EO data, workflows to transform that data into end products (e.g. surface water extent maps), and the products themselves. However, this revolution has oversaturated decision-makers with products that can give conflicting results. Thus, it is increasingly crucial for scientists to communicate their methodologies and assumptions so scientific products can be used accurately. Recognizing this challenge, SERVIR – a joint initiative between NASA, USAID, and geospatial organizations in Asia, Africa, and Latin America – is conducting a regional intercomparison of open source surface water extent products and packages. SERVIR’s Hindu Kush Himalaya and Southeast Asia “hubs” have developed satellite-based surface water mapping services involving customizable code packages that are operationally run at each hub. These services are regionally and locally tailored to inform specific decisions and early actions. Conversely, the scientific community has released surface water products that are global or near-global, but are not customizable. These packages and products employ different methodologies and sensors, causing decision-makers to evaluate trade-offs related to physical sensor characteristics (e.g. spectral, temporal, and spatial resolution, and latency). We will discuss the tradeoffs, strengths, and weaknesses of the sensor characteristics and methodologies associated with each product/package, and provide preliminary results of a validation effort intercomparing products/packages for case studies in South and Southeast Asia. Understanding the strengths and weaknesses of these products is crucial in both the aftermath of a flood event and in preparing for future floods.
Geomagnetically induced currents (GICs) represent a significant space weather issue for power grid and pipeline infrastructure, particularly during severe geomagnetic storms. In this study, magnetometer data collected from around the world are analyzed to investigate the GICs caused by the 2015 St. Patricks Day storm. While significant GIC activity in the high-latitude regions due to storm time substorm activity is shown for this event, enhanced GIC activity was also measured at two equatorial stations in the American and Southeast Asian sectors. This equatorial GIC activity is closely examined, and it is shown that it is present both during the arrival of the interplanetary shock at the storm sudden commencement (SSC) in Southeast Asia and during the main phase of the storm approximately 10 h later in South America. The SSC caused magnetic field variations at the equator in Southeast Asia that were twice the magnitude of those observed only a few degrees to the north, strongly indicating that the equatorial electrojet (EEJ) played a significant role. The large equatorial magnetic field variations measured in South America are also examined, and the coincident solar wind data are used to investigate the causes of the sudden changes in the EEJ approximately 10 h into the storm. From this analysis it is concluded that sudden magnetopause current increases due to increases in the solarwind dynamic pressure, and the sudden changes in the resultant magnetospheric and ionospheric current systems, are the primary drivers of equatorial GICs.
Biomass-burning (BB) aerosols, acting as cloud condensation nuclei (CCN), can influence cloud microphysical and radiative properties. In this study, we present CCN measured near the BB source regions over northern Southeast Asia (Doi Ang Khang, Thailand) and at downwind receptor areas (Lulin Atmospheric Background Station, Taiwan), focusing exclusively on 13-20 March 2013 as part of 2013 spring campaign of the Seven SouthEast Asian Studies (7-SEAS) intensive observation. One of the campaigns objectives is to characterize BB aerosols serving as CCN in SouthEast Asia (SEA). CCN concentrations were measured by a CCN counter at 5 supersaturation (SS) levels: 0.15%, 0.30%, 0.45%, 0.60%, and 0.75%. In addition, PM2.5 and black carbon mass concentrations were analyzed by using a tapered element oscillating microbalance and an aethalometer. It was found the number-size distributions and the characteristics of hygroscopicity (e.g., activation ratio and k) of BB aerosols in SEA have a strong diurnal pattern, and different behaviors of patterns were characterized under two distinct weather systems. The overall average value was low (0.05-0.1) but comparable with previous CCN studies in other BB source regions. Furthermore, a large fraction of UV-absorbing organic material (UVBC) and high Delta-C among BB aerosols were also observed, which suggest the existence of substantial particulate organic matter in fresh BB aerosols. These data provide the most extensive characterization of BB aerosols in SEA until now.
Accurate estimates of the emissions and distribution of black carbon (BC) in the region referred to here as Southeastern Asia (70degE-l50degE, 11degS-55degN) are critical to studies of the atmospheric environment and climate change. Analysis of modeled BC concentrations compared to in situ observations indicates levels are underestimated over most of Southeast Asia when using any of four different emission inventories. We thus attempt to reduce uncertainties in BC emissions and improve BC model simulations by developing top-down, spatially resolved, estimates of BC emissions through assimilation of OMI observations of aerosol absorption optical depth (AAOD) with the GEOS-Chem model and its adjoint for April and October of 2006. Overwhelming enhancements, up to 500%, in anthropogenic BC emissions are shown after optimization over broad areas of Southeast Asia in April. In October, the optimization of anthropogenic emissions yields a slight reduction (1-5%) over India and parts of southern China, while emissions increase by 10-50% over eastern China. Observational data from in situ measurements and AERONET observations are used to evaluate the BC inversions and assess the bias between OMI and AERONET AAOD. Low biases in BC concentrations are improved or corrected in most eastern and central sites over China after optimization, while the constrained model still underestimates concentrations in Indian sites in both April and October, possibly as a. consequence of low prior emissions. Model resolution errors may contribute up to a factor of 2.5 to the underestimate of surface BC concentrations over northern India. We also compare the optimized results using different anthropogenic emission inventories and discuss the sensitivity of top-down constraints on anthropogenic emissions with respect to biomass burning emissions. In addition, the impacts of brown carbon, the formulation of the observation operator, and different a priori constraints on the optimization are investigated. Overall, despite these limitations and uncertainties, using OMI AAOD to constrain BC sources improves model representation of BC distributions, particularly over China.
Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM(Trop,Nat)) and drained (PEATCLSM(Trop,Drain)) tropical peatlands. Simulations with PEATCLSM(Trop,Nat) were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM(North,Nat)) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM(Trop,Drain) was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM(Trop,Drain) outperformed CLSM, PEATCLSM(North,Nat) and PEATCLSM(Trop,Nat) over drained sites. Despite the overall improvements of PEATCLSM(Trop,Nat) over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.
This work describes some of the most extensive ground-based observations of the aerosol profile collected in Southeast Asia to date, highlighting the challenges in simulating these observations with a mesoscale perspective. An 84-h WRF Model coupled with chemistry (WRF-Chem) mesoscale simulation of smoke particle transport at Kuching, Malaysia, in the southern Maritime Continent of Southeast Asia is evaluated relative to a unique collection of continuous ground-based lidar, sun photometer, and 4-h radiosonde profiling. The period was marked by relatively dry conditions, allowing smoke layers transported to the site unperturbed by wet deposition to be common regionally. The model depiction is reasonable overall. Core thermodynamics, including landsea-breeze structure, are well resolved. Total model smoke extinction and, by proxy, mass concentration are low relative to observation. Smoke emissions source products are likely low because of undersampling of fires in infrared sun-synchronous satellite products, which is exacerbated regionally by endemic low-level cloud cover. Differences are identified between the model mass profile and the lidar profile, particularly during periods of afternoon convective mixing. A static smoke mass injection height parameterized for this study potentially influences this result. The model does not resolve the convective mixing of aerosol particles into the lower free troposphere or the enhancement of near-surface extinction from nighttime cooling and hygroscopic effects.