This bibliography represents a compilation of many of the resources quoted on preceptaustin.org. Updated May, 2015
BRIEF SUMMARY OF POPULAR
Because the bibliographic listing does not mention every major Bible software product for each resource you will need to check the individual websites for available resources which are being added to continually...:
(1) Logos - This is the "Cadillac" of Bible software with over 20,000 resources available. The search engine is free, but the resources can be very expensive. Logos has a steep learning curve and requires a fast computer. If you have a blog or website be sure to consider adding the free Scripture popup tool - Reftagger - Official Site
(2) Wordsearch - Wordsearch and Logos are my favorite programs. Logos is "Wordsearch on steroids!" Wordsearch has a growing number of resources and is (1) generally (but not always) less expensive than Logos and (2) is easier to use. Wordsearch has partnered with Lifeway, so that it appears to be a program that is "here to stay".
(3) BibleWorks - This is my favorite tool for original language studies with a nice selection of add on lexicons. This is not the choice if you are looking for commentaries. I usually have this program opened to supplement my Logos and Wordsearch programs.
(4) TheWord Bible Program - Free program. In my opinion it rivals E-sword as best free program available. One nice feature is ability to scroll through verses which synch with all commentaries that have related notes. TheWord has most of the same resources (free) that are listed for E-Sword.
(5) E-Sword - Free program. For a general commentary of the entire Bible, I highly recommend David Guzik (Commentary on OT and NT). For one of the best (literal interpretation) commentaries available on the Revelation see Anthony Garland's book (Testimony of Jesus Christ).
(6) Online Study Bibles - Four are available and they are all very good.
(a) Holman Christian Standard Bible Study Bible - free
(b) Defender's Study Bible by Henry Morris - free
(c) NETBible Notes - free. Be sure to check this one out by reading the notes below. This is far more than a "study Bible" as you will discover.
(d) Reformation Study Bible Notes
(7) Online Study Resources - In my opinion the best sources of online resources are:
(a) Studylight.org - Bible Commentaries - largest selection on the web
(b) Biblehub.com- Has a few resources not found on Studylight
(c) Don't forget to check preceptaustin "Collections" on all 66 books of the Bible (see drop down list at top of page) - links to literally thousands of resources - commentaries, sermons, journal articles, devotionals
OLD AND NEW TESTAMENT
Also Sermons, Illustrations, Devotionals, etc
Note: For Logos software titles the best resource is Logos.com.
If you are interested in "old fashioned" (paper!) books, I recommend searching Amazon.com where you can search for used copies available (usually only a fraction of the cost of the new book -- I have purchased up to 50 used Christian books from Amazon and have yet to be disappointed -- just be sure to read the seller's notes on the condition of the book.
Be aware that many of the Christian writings prior to the early 1900's are now available online at no charge. I have found the Archive.org invaluable in this regard. It takes some practice but you will be amazed at what is now online at Archive.org. For example, just to get some idea of the amount of material which is online enter Spurgeon and under media type select Texts (otherwise you will get audios, etc) to retrieve over 350 resources!
|Ash, A. L. Philippians, Colossians & Philemon. The College Press NIV commentary. Joplin, Mo.: College Press. (1994)|
|Barclay, William. The Daily study Bible series, Rev. ed. Philadelphia: The Westminster Press.|
|Barnes, Albert. Barnes' Notes on the Bible|
"Albert Barnes is a learned and able divine, but his productions are unequal in value, the gospels are of comparatively little worth, but his other comments are extremely useful for Sunday School teachers and persons with a narrow range of reading, endowed with enough good sense to discriminate between good and evil. If a controversial eye had been turned upon Barnes's Notes years ago, and his inaccuracies shown up by some unsparing hand, he would never have had the popularity which at one time set rival publishers advertising him in every direction. His Old Testament volumes are to be greatly commended as learned and laborious, and the epistles are useful as a valuable collection of the various opinions of learned men. Placed by the side of the great masters, Barnes is a lesser light, but taking his work for what it is and professes to be, no minister can afford to be without it, and this is no small praise for works which were only intended for Sunday School teachers. (from Commenting and Commentaries by CH Spurgeon)
|Barton, B. B. Life Application Bible Commentary: Romans, Philippians, Colossians, et al. Wheaton, Ill.: Tyndale House Publishers.|
|Bible Knowledge Commentary:An Exposition of the Scriptures. Walvoord, J. F. Wheaton, IL: Victor Books.|
|Black, A. 1 & 2 Peter. The College Press NIV commentary. Joplin, Mo: College Press Pub. (1998)|
|Calvin, John: Commentariess|
|Carson, D. A. New Bible Commentary: Downers Grove, Ill., USA: Inter-Varsity Press. (1994)|
|Clarke, Adam: Clarke's Commentary|
|Cottrell, J.Romans : Vol 1. College Press NIV commentary. Volume 2. Joplin, Mo.: College Press Pub (1996-c1998)|
|Craigie, P. C. Ezekiel. The Daily Study Bible Series. Louisville: Westminster John Knox Press.|
|The New Defender's Study Bible by Henry M Morris|
Elwell, W. A. Evangelical Commentary on the Bible. Grand Rapids, Mich.: Baker Book House
|ESV Study Bible - Crossway (2008)|
|Exell, Joseph, Editor: The Biblical Illustrator: (1887)|
Gaebelein, F, et al: Expositor's Bible Commentary: Old and New Testament (12 Volumes)
Garland, Anthony: A Testimony of Jesus Christ (Commentary on the Revelation)
|Gill, John: John Gill's Exposition of the Entire Bible:|
|Guzik, David: Commentary on the Whole Bible (except a few books)|
|Haldane, Robert: An Exposition of Romans|
|Harris, R. L.Theological Wordbook of the Old Testament. Chicago: Moody Press.|
|Henry, Matthew: Commentary on the Whole Bible (1700's) This resource is also available free for download from "".|
|Hiebert, D. Edmond Commentaries: Gospel of Mark, 1, 2 Thes, 1, 2 Timothy, Titus, Philemon, James, 1, 2 Peter, 1-3 John|
|Hodge, C. Romans. Commentary on the Epistle to the Romans, 1835|
|Holman Christian Standard Bible -Study Bible (HCSB Study Bible)|
|Hughes, R. K. Colossians and Philemon: The supremacy of Christ. Crossway (1989)|
Hughes, R. K.Hebrews: Vol 1 & 2: An Anchor for the Soul: Preaching the Word (1993)
Hughes, R. K. Romans : Righteousness from heaven. (1991)
IVP New Testament Commentary Series: Towner, P. 1-2 Timothy & Titus. Downers Grove, Ill.: InterVarsity Press.
|Jamieson, R., Fausset, A. R. & Brown, D. A Commentary, Critical & Explanatory, on the Old and New Testaments.|
|Keener, C. S. The IVP Bible background commentary : New Testament. Downers Grove, Ill.: InterVarsity Press. (1993)|
|Keil & Delitzsch: Commentary on the Old Testament.|
|King James Version Study Bible (Radmacher, E. D., Allen, R. B., & House, H. W. (1997). The Nelson study Bible : New King James Version) Nashville: Thomas Nelson.|
|KJV Bible commentary. Nashville: Thomas Nelson.|
|Lenski, R. The Interpretation of 1 & 2 Epistles of Peter, the Three Epistles of John, and the Epistle of Jude. Ausburg Publishing. (1966)|
Lightfoot, J. B. Colossians and Philemon. The Crossway Classic Commentaries. Wheaton, Ill.: Crossway Books. (1996)
|Louw, Johannes & Nida, Eugene: Greek-English Lexicon of the New Testament based on Semantic Domains.|
|MacArthur, John: Commentaries on Multiple NT Books including: Romans, Philippians, Colossians, 1 Timothy , 2 Timothy, Titus.Hebrews Chicago: Moody Press.|
|MacArthur, John. The MacArthur Study Bible: Thomas Nelson (1997)|
|MacDonald, William & Farstad, A. Believer's Bible Commentary: Old and New Testaments. Nashville: Thomas Nelson.|
|McGee, J. Vernon. Thru the Bible Commentary. Nashville: Thomas Nelson.|
|Maclaren, Alexander: Expositions of Holy Scripture (1826-1910)|
|Marshall, I. H. 1 Peter. The IVP New Testament Commentary. Downers Grove, Ill.: InterVarsity Press. (1991).|
|Meyer, F B The Epistle to the Philippians. E-Sword Step program from Heritage Educational Systems.|
|Mills, M. Ruth: A Study Guide to the Book of Ruth . Dallas: 3E Ministries|
|Mounce, R. H.Romans. The New American Commentary. Nashville: Broadman & Holman Publishers.|
NET Bible notes: Study notes and much more in the free online version (see instructions below)!
|Newell, William: Romans Verse by Verse (published 1938) N|
|New Linguistic and Exegetical Key to the Greek New Testament, The by Fritz Rienecker, Cleon L., III Rogers|
|Pink, A W Expositions on numerous Old and New Testament books (1886-1952)|
|Piper, John. Desiring God Ministries|
|Pfeiffer, C. F. The Wycliffe Bible commentary: Old and New Testament. Chicago: Moody Press. (1962)|
|Pulpit Commentary by H. D. M. Spence and Joseph S. Exell|
|Radmacher, E. D.Nelson's New Illustrated Bible Commentary. Nashville: T. Nelson Publishers. (1999) (Note: Identical to Nelson's NKJV|
Richards, Lawrence O:
The Teacher's Commentary. Wheaton, Ill.: Victor Books. (1987)
The Bible Reader's Companion (BRC) Wheaton, Ill.: Victor Books.
The 365 Day Devotional Commentary. (365) Wheaton, Victor Books
Expository Dictionary of Bible Words. Zondervan(New Name for this work = New International Encyclopedia of Bible Words)
|Robertson, A. T. Word Pictures in the New Testament|
|Ryrie, Charles: The Ryrie Study Bible|
|Stedman, Ray. The Ray Stedman Library.Ray C. Stedman Memorial Home Page|
|10,000 Sermon Illustrations CD|
|Theological Dictionary of the New Testament. G. Kittel, G. W. Bromiley & G. Friedrich, Ed. Grand Rapids, MI: Eerdmans.|
|Theological Journal Library|
|Theological Wordbook of the Old Testament , Harris, R. L., Harris, R. L., Archer, G. L., & Waltke, B. K. (1999, c1980). Chicago: Moody Press.|
|UBS: Helps for translators; UBS handbook series: Bratcher, R. G., & Nida, E. A. (1993], c1977). New York: United Bible Societies.|
|Vincent, M. R.: Word Studies in the New Testament|
|Vine, W. E.The Collected Writings of W. E. Vine. Thomas Nelson|
|Vine, W. E. Vine'sComplete Expository Dictionary of Old and New Testament Words. Nashville: T|
|Wall, R. W. Colossians & Philemon. The IVP New Testament Commentary. Downers Grove, Ill.: InterVarsity Press. (1993).|
|Walvoord, J. F. The Bible Knowledge Commentary : An Exposition of the Scriptures. Wheaton, IL: Victor Books. A|
|Wiersbe, W. W. The Bible Exposition Commentary. Wheaton, Ill.: Victor Books|
Wiersbe, W. W: Wiersbe's Expository Outlines on the New Testament. Wheaton, IL: Victor Books
Wiersbe, W. W: Be Committed. An Old Testament Study. Ruth and Esther Wheaton, Ill.: Victor Books
Bible software: Logos; Wordsearch
|Word Biblical Commentary: Multi-volume set: Old and New Testament: Word Biblical Commentary Dallas: Word, Incorporated.|
|Wuest, K. S. Wuest's Word Studies from the Greek New Testament : For the English Reader. Grand Rapids: Eerdmans.|
|Zodhiates, S. The Complete Word Study Dictionary: New Testament and Old Testament Chattanooga, TN: AMG Publishers.|
Click chartcomparing Literalness of Various Versions
|ALT||Analytical-Literal Translation. Available on E-Sword|
|AMP||Amplified: Scripture quotations taken from the Amplified® Bible, Copyright © 1954, 1958, 1962, 1964, 1965, 1987 by The Lockman Foundation Used by permission. (www.Lockman.org)|
|ASV||American Standard Version (1901) Available on E-Sword|
|BBE||Bible in Basic English: No obvious copyright stated.|
|Brenton||English translation of the Lxx (Septuagint). Available on E-Sword|
|CEV||Contemporary English Version. Available on E-Sword|
|DNT||Darby's New Testament Available on E-Sword|
|DRB||Douay-Rheims Bible Available on E-Sword|
|ESV||English Standard Version: Scripture quotations are from The Holy Bible, English Standard Version, copyright © 2001 by Crossway Bibles, a division of Good News Publishers. Used by permission. All rights reserved.|
|GWT||God's Word Translation is a copyrighted work of God's Word to the Nations. Quotations are used by permission.|
|HCSB||Holman Christian Standard Bible: Copyright © 2002 by Holman Bible Publishers, Nashville Tennessee. All rights reserved.|
|ICB||International Children's Bible|
|ISV||International Standard Bible. Available on E-Sword|
|NASB||New American Standard Bible: Scripture quotations taken from the New American Standard Bible®,Copyright © 1960, 1962, 1963, 1968, 1971, 1972, 1973,1975, 1977, 1995 by The Lockman Foundation Used by permission.|
|LITV||Literal Translation. Available on E-Sword|
|LXX||Septuagint (Greek Translation of the Hebrew Old Testament). Available on E-Sword|
|MKJV||Modern KJV. Available on E-Sword|
The southern Amazon, which covers 30–40% of Amazonia, is a transitional region between tropical rainforests to the north and west and subtropical savanna and agricultural lands to the south and east (Fig. 1). Rainforests in this region, which play an important role in the global carbon cycle (1), are vulnerable to slight decreases in annual rainfall or increases in dry season length (2). This vulnerability is exacerbated by large-scale agricultural land use. The southern Amazon dry season has lengthened in recent decades, primarily due to delays in wet season onset (3). Model simulations suggest that continuation of this trend could trigger an abrupt transition of rainforest to savanna (2, 4), which would substantially reduce dry season rainfall over the southern Amazon and downwind agricultural regions (5, 6).
Rainforest vitality is known to depend on rainfall amount and dry season length (2, 7⇓–9), but major knowledge gaps remain regarding rainforest influences on wet season onset. Rainforest evapotranspiration (ET) accounts for 30–50% of regional rainfall (10⇓⇓–13), but it is unclear whether ET actively modifies or merely responds to rainfall seasonality. Credible assessments of land use contributions to recent increases in dry season length and the frequency of extreme droughts in this region (14, 15) require these gaps to be filled.
The Deep Convection Moisture Pump
Wet season onset in the tropics is generally associated with either monsoon reversals in the land–ocean temperature gradient or north–south migration of the Intertropical Convergence Zone (ITCZ), both of which are driven by seasonal changes in the distribution of solar radiation. However, wet season onset over the southern Amazon precedes the southward migration of the Atlantic ITCZ by 2–3 mo (16) and occurs without a reversal in the land–ocean surface temperature gradient (17, 18). Conventional mechanisms therefore cannot explain wet season onset over the southern Amazon. An alternative hypothesis holds that late dry season increases in rainforest transpiration may increase surface air humidity and buoyancy (18, 19). Lifting of this humid near-surface air by cold fronts moving northward from midlatitude South America (20) could cause large-scale increases in deep convection and upper-level heating (21), thereby initiating moisture transport from the tropical Atlantic. Large-scale moisture transport reinforces the conditions that favor deep convection, ultimately leading to wet season onset. We refer to this transition mechanism as the deep convective moisture pump (DCMP).
The exact processes that activate the DCMP have been unclear. Cold front incursions are strongest during the dry season (22), but deep convection is rare until lower tropospheric humidity rises late in the transition season (21). Moistening of the lowest 4 km of the atmosphere (pressures 600–700 hPa) therefore emerges as the likely key to activating the DCMP (23, 24). The source of this moisture and the processes by which moistening occurs have profound implications for understanding how land use and biomass burning affect the seasonal cycle of rainfall. For example, deforestation might sharpen the land–ocean temperature gradient (accelerating wet season onset under a conventional onset mechanism), but would also reduce surface moisture fluxes (delaying wet season onset under an ET-initiated onset mechanism).
To clarify the mechanisms involved in activating the DCMP, the first question that must be answered is whether the late dry season increase in lower tropospheric humidity primarily derives from rainforest transpiration or advection from the ocean. Previous studies on this topic have been overwhelmingly based on reanalysis products that combine available observations with numerical model simulations. These products are heavily influenced by the behavior of the underlying model in data-poor regions like Amazonia. Inadequate treatments of surface hydrology, vegetation, and turbulent mixing near the top of the atmospheric boundary layer (ABL) lead to large uncertainties in reanalysis estimates of ET, rainfall, and moisture flux convergence (MFC) (25). For example, the increase in rainfall over the southern Amazon during the dry-to-wet season transition occurs 2–3 wk earlier in the European Center for Medium-Range Weather Forecasting Interim Reanalysis (ERA-Interim) than in observations (SI Text). Enhanced rainfall and associated heating in the atmosphere directly affect reanalysis estimates of ET and MFC, potentially confounding moisture source attributions based on reanalysis products. In situ observations indicate that maximum ET leads the late dry season increase in rainfall (26⇓–28); however, it has been unclear whether modest increases in ET can contribute sufficient moisture above the ABL at regional scales. The potential influences of aerosols on the dry-to-wet season transition are an additional source of uncertainty (29), because the aerosol climatologies used by most reanalyses neglect or underestimate seasonal and interannual variations in aerosol loading in this region (30, 31). It is therefore necessary to examine the dry-to-wet season transition by using observable quantities.
Data Processing and Generation of Composites.
All analyzed fields are area-weighted spatial averages over the southern Amazon domain, defined as the area bounded by 5°S to 15°S and 50°W to 70°W (Fig. 1). Variables are averaged into discrete 5-d periods (pentads), where the first pentad of each year corresponds to 1–5 January, the second to 6–10 January, and so on. The annual cycle of each variable is then composited relative to wet season onset for each individual year, where wet season onset is defined as the first 5-d period for which (i) the rain rate exceeded the climatological mean; (ii) the rain rate in at least five of the eight preceding pentads was less than the climatological mean; and (iii) the rain rate in at least five of the eight subsequent pentads was greater than the climatological mean (19). Onset-relative composite time series are then constructed by averaging across years for the 40 pentads before onset and the 40 pentads after onset over six wet season transitions (2005–2006 through 2010–2011). This process yields composite time series 80 pentads (400 d) long, which are then filtered by applying and inverting fast Fourier transforms (FFTs) in the time dimension. The first six Fourier coefficients of the full time series are retained, removing variability at time scales <25 d.
Except where otherwise indicated (D, –D regression slopes, surface radiation, enhanced vegetation index (EVI), and fire CO2 emissions), uncertainties in the composite time series are represented by the filtered evolutions over the six transition seasons (seven for SIF; Table S1). Spatial variations within the southern Amazon are not considered in these uncertainty estimates, although separate analyses conducted for data separated by land cover (evergreen forest vs. all other land cover types; Fig. 1) indicate that the results are not sensitive to this distinction. All uncertainty estimates are calculated before applying FFTs, so that lower and upper bounds (where applicable) are smoothed identically to the composite mean. Fig. S7 shows full composite annual cycles for a subset of the variables included in Fig. 2, along with unfiltered onset-relative changes from each year. The latter illustrate the amplitude of the variations removed by the FFT-based low-pass filter.
The timing of wet season onset and the onset-relative composite time series of precipitation are determined using Version 7 of the TRMM 3B42 daily gridded precipitation product at resolution (51). These data are widely used and have been shown to correlate well with other observationally based estimates of rainfall in the Amazon region (3). Transitions between the wet and dry seasons are identified by using the area mean climatological mean precipitation rate calculated from 18 y (1998–2015) of TRMM data. The onset dates for the 2005–2013 wet seasons are listed in Table S1.
Energy and Moisture Fluxes.
Onset-relative composite time series of ET and MFC are constructed from the ERA-Interim (52). ET in units of mmd−1 (kgmd−1) is calculated by dividing the latent heat flux (in units of Wm−2) by the latent heat of vaporization for pure water at 20 °C ( Jkg−1). MFC is calculated by averaging the moisture flux divergence diagnostic provided in the ERA-Interim product over the southern Amazon domain. The sum of ET and MFC should approximately equal precipitation, with changes in atmospheric water storage as a residual. The sum of ET and MFC (and hence precipitation) in ERA-Interim is systematically nearly twice as large as TRMM precipitation through most of the dry season (Figs. S1A and S7). The annual cycle of precipitation based on these two datasets is broadly similar, but wet season onset based on ERA-Interim is typically earlier than wet season onset based on TRMM (Fig. 1A). Wet season onset based on ERA-Interim precipitation is on average pentads earlier than that based on TRMM during 1998–2015 (as much as 40 d earlier in 10 of 18 y) and pentads earlier during the 2005–2011 analysis period (as much as 25 d earlier in 5 of 7 y).
Cloud fraction and radiative fluxes are from Edition 3A of the Clouds and the Earth’s Radiant Energy System (CERES) Synoptic Radiative Fluxes and Clouds (SYN1deg) daily data product at spatial resolution (53, 54). Cloud fractions are retrieved by using observations from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Earth Observing System (EOS) Terra and Aqua satellites (55) and observations from geostationary satellites (56). Radiation fluxes are computed by using the Fu–Liou radiative transfer model based on observed cloud and aerosol distributions and atmospheric profiles calculated by using the Goddard Earth Observing System (GEOS) Data Assimilation System. The source of the assimilated atmospheric profiles was changed from GEOS-4.1 (57) to GEOS-5.2 (58) at the beginning of January 2008. CERES SYN1deg has been processed for December 2007 by using both GEOS-4.1 and -5.2. Comparison of these two datasets over the southern Amazon domain indicates that the effects of this change on the variables used in this study are small. Relative changes associated with the switch to GEOS-5.2 are 1% in area mean total cloud fraction, 5% in the vertical profile of cloud fraction, and 1% in net downward radiation flux.
There are considerable differences between the CERES SYN1deg and ERA-Interim estimates of surface solar radiation (Fig. S1B). ERA-Interim underestimates surface insolation relative to CERES during the middle dry season (day −120 through day −75 or so), primarily because it overestimates cloud cover (cf Fig. 2D and Fig. S1B; see also estimated cloud radiative effect in Fig. S2A). By contrast, ERA-Interim overestimates surface insolation during the late dry season (day −60 through day −10), primarily due to aerosol effects (Fig. S2C) that are inadequately represented by the climatological annual cycle of tropospheric aerosols used in the ERA-Interim reanalysis system. These potential errors in surface insolation in ERA-Interim, which represent an important source of uncertainty in the precise evolution of the surface sensible and latent heat fluxes (Fig. 2A and Fig. S1D), are on order 30 W m−2. This uncertainty highlights the importance of using observationally derived variables to provide additional validation for variations in the moisture budget.
Vegetation Metrics and Fire Emissions.
Land cover data at 500-m resolution (Fig. 1) were taken from the 2009 MODIS MCD12Q1 dataset; the SIF and EVI data shown in Fig. 2E and Fig. S4 are averaged over pixels matching the International Geosphere–Biosphere Program land cover type “evergreen broadleaf forest”. SIF, which is considered as a direct proxy for gross primary productivity, is inferred from measurements made by the Global Ozone Monitoring Instrument 2 (GOME-2) onboard the MetOp-A satellite (32). We use Version 2.6 data, which are publicly available at avdc.gsfc.nasa.gov. The original data were provided four times per month during 2007–2014, in 7- or 8-d bins depending on the number of days in the month. We use a linear regression to interpolate these data to 5-d resolution. The area-weighted mean is obtained by averaging SIF over broadleaf forest grid cells in the Southern Amazon region using a reduced-resolution version of the 2009 land cover dataset described above. SIF normalized by the cosine of the solar zenith angle (which removes the effects of seasonal variations in instantaneous incoming solar radiation across satellite overpasses) is shown in Fig. S4A for context.
EVI is used as an alternative measure of rainforest bioproductivity. EVI was computed at 500-m resolution in 16-d increments from MODIS-derived reflectance data standardized to constant view and solar geometry. MODIS Bidirectional Reflectance Distribution Function (BRDF) parameters were taken from the MCD43A1 dataset. Reflectance at nadir view and 30° solar zenith angle was estimated as the linear combination of coefficients in MCD43A1 and the RossThick and LiSparseR kernel functions computed at the specified angles. EVI was computed from reflectance in near-infrared, red, and blue bands (59) and masked outside of [−1, 1]. Sensitivity analysis indicated that the choice of solar zenith angle affected the mean value of the EVI, but not the phase or amplitude of the seasonal cycle. Pixels were masked based on quality flags in the MODIS MCD43A2 dataset. The most restrictive quality control retained only best quality pixels (full BRDF inversion with low residual error), whereas the more permissive quality control retained all pixels with potentially valid data (BRDF inversion completed). The range between these two estimates is shown in Fig. S4B as a measure of uncertainty in the mean evolution of EVI. We generate EVI data using 16-d means at 8-d resolution and linearly interpolate these data to 5-d resolution. Comparison of the seasonal evolutions of SIF and EVI (Fig. S4) shows that changes in SIF lead changes in EVI by 10–15 d, indicating that increases in photosynthesis lead increases in vegetation greenness during the late dry season in this region.
Daily estimates of CO2 emissions from fires are based on Version 3.1 of the Global Fire Emissions Database (GFED3) (60, 61). Error bars on GFED3 estimates of fire emissions indicate the minimum and maximum emissions during the 6-y analysis period.
Atmospheric Thermodynamic Variables.
Observations of water vapor and temperature are from Version 6 of the AIRS Level 3 daily gridded product at resolution (62, 63). We use the AIRS TqJoint product based on combined AIRS and Advanced Microwave Sounding Unit observations (AIRX3RET), which provides consistent gridded profiles of temperature and water vapor on a common vertical grid with eight pressure levels between 1,000 and 300 hPa (previous versions of the AIRS data have reported temperature and water vapor on slightly different vertical grids). We use TqJoint because it facilitates the calculation of equivalent potential temperature and other atmospheric stability metrics that require knowledge of temperature and water vapor at common locations in space and time. Only data from ascending orbits (13:30 local time) are used; this choice is justified by delays of almost 2 mo between the development of daytime convective instability and the development of nighttime convective instability (Fig. S3). The area mean equivalent potential temperature () is calculated from gridded AIRS data at daily time resolution according to the equation[S1]where is the dry potential temperature, is the latent heat of vaporization at 0°C, is the water vapor mass mixing ratio, is the specific heat of dry air at constant pressure, and is the temperature. The time rates of change in early afternoon and early morning are calculated as centered differences in the daily time series of area mean . Temperature and moisture contributions to changes in (Fig. S5) are calculated following the method used by Li and Fu (19). Calculations of CAPE and convective inhibition energy (CINE) (Fig. S3) include the virtual temperature correction (64). CAPE and CINE are calculated for all grid cells for which the necessary surface air and profile variables (pressure, temperature, and water vapor mass mixing ratio) are available within the TqJoint dataset. These gridded daily values are then aggregated into area-weighted 5-d (pentad) mean values.
The deuterium content of a water sample is expressed as the relative ratio D in parts per thousand (‰), where[S2] is the ratio of the number of HDO molecules () to the number of H2O molecules () and is the corresponding / ratio in a reference standard (here Vienna Standard Mean Ocean Water, for which ). Joint distributions of specific humidity () and D are from retrievals made using the TES on the EOS Aura satellite (49). The data have been processed by using Version 6 of the TES retrieval algorithm (v006_Litev01.00), which simultaneously estimates the volume mixing ratios of HDO, water vapor, methane, and nitrous oxide (36). Retrieving these four species together substantially improves the vertical resolution, and enables separate retrievals of D in the ABL (surface to 825 hPa) and free troposphere (FT) (750–348 hPa). The onset-relative evolution of these two quantities is shown in Fig. S8. The HDO averaging kernel is primarily sensitive to , where is the HDO/H2O ratio (36, 49). Fig. S9 shows a typical TES HDO averaging kernel for daytime retrievals over the southern Amazon during the late dry season (October 2006), which contains three rows that peak at pressures of 825 hPa or higher and six rows that peak between 750 and 350 hPa. The daytime retrievals are therefore capable of resolving the deuterium distribution in the ABL. Nighttime TES retrievals of water vapor and HDO over the southern Amazon are only weakly sensitive to levels between the surface and 825 hPa, so we omit estimates of ABL D from descending orbits (01:30 local time). We calculate pressure-weighted column mean and water vapor volume mixing ratio for the ABL and FT and then use these quantities to calculate D and water vapor mass mixing ratio in each layer. All valid observations over the southern Amazon region are then binned into onset-relative pentads before averaging or calculating best fit lines (Linear Fits).
The TES data have been screened by using recommended quality control criteria (36): The cloud effective optical depth must be 0.4, and the degrees-of-freedom for signal for the entire profile must be 1. Reasonable adjustments to the quality control criteria mainly affect the data yield and do not alter the qualitative nature of the results. Uncertainties for the TES time series are propagated from individual measurement uncertainties (49). Typical uncertainties in the free troposphere over the southern Amazon are 7–10% on and 3–5% on . The mean degrees of freedom for signal for the vertical layers used here is 0.5–0.6 in the ABL ( 825 hPa) and 1.21.6 in the free troposphere (750 348 hPa). These values indicate that the data are able to capture qualitative variations in both layers and quantitative variations in the free troposphere, but capture only 50–60% of the variability in ABL D (i.e., the seasonal variations in daytime ABL D may be larger than indicated by Fig. S8B). Evaluating ABL D by using observations between the surface and 908 hPa (i.e., omitting the 825 hPa level) reduces the degrees of freedom for signal by about half and shifts estimates of ABL D upward by 5 to 10‰, but the seasonal evolution is qualitatively unchanged.
Boundary Layer D.
The observed evolution of D in the ABL provides independent support for two of the key physical arguments discussed in the main text: strong rainforest transpiration (which maintains high D in ABL vapor) and a deepening boundary layer during the transition season (which increases the amount of high-D air within the ABL layers of the TES averaging kernel). Analysis of the TES averaging kernels (Fig. S9) allows us to reject the possibility that the observed increase in ABL D during the late dry season is explained by cross-correlations between the ABL and FT. The ABL retrieval partially depends on the FT retrieval because the full profile is estimated by using the equation[S3]where is the estimated vertical profile of , is the averaging kernel, is the a priori profile of used to regularize the retrieval, and is the true profile of . Changes in in the FT will therefore affect retrievals of in the ABL and vice versa (Fig. S8). Changes in the FT during the late dry season will have a larger impact on the ABL because the fractional increase in is larger in the FT and the retrieval is performed using , for which changes reflect fractional variability. We can estimate how much increases in the FT HDO/H2O ratio raise the ABL estimate by multiplying (for example) the 908-hPa row of the averaging kernel (red line with diamond located at 908 hPa in Fig. S9) by a vector containing values of ∼0.06 for the 750- to 348-hPa levels (corresponding to the magnitude of the increases in in the FT). This estimate gives an upper bound on the error from cross-correlation because the higher pressures show lower variability than the lower pressures, and shows that cross-correlation with the FT can account for at most a 4‰ increase in D in the ABL, a factor 4–5 smaller than the observed change. Using more realistic values that account for the vertical profile of fractional changes suggests a more likely error of 2‰. We can therefore reject the hypothesis that increases in ABL D are caused by cross-correlation with FT D.
Comparison with D in the ocean ABL further confirms that this increase cannot be attributed to advection from the nearby ocean. The mean value of D in the ABL over the southern Amazon during October 2006 (for example) was −54 6.2‰, whereas that in the ABL over the tropical Atlantic (0–10°N, 30–55°W) was −69 4.7‰ (Fig. S8B). These estimates imply a positive bias of as much as 10‰ in the ABL (D in the ABL over the tropical ocean is generally approximately −80‰), but the Atlantic ABL is nonetheless significantly more depleted than the southern Amazon ABL. Transport from the Atlantic therefore cannot be the source of the observed increase in ABL D. This increase must therefore be due to an increase in the transpiration contribution to the vapor observed in these layers by TES, as transpiration is the only moisture source that can increase the near-surface isotopic composition relative to observed values during the peak dry season (−59 9‰).
Linear fits between water vapor mass mixing ratio () and D (Fig. 2F) are calculated by using the same data points used to calculate mean D in the FT (Fig. S8A), but without separating the data into daytime and nighttime observations (this choice is justified by the lack of significant differences in FT