Articles | Volume 3, issue 4
https://doi.org/10.5194/wcd-3-1183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-3-1183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Subseasonal precipitation forecasts of opportunity over central southwest Asia
Melissa L. Breeden
CORRESPONDING AUTHOR
Cooperative Institute for Research in Environmental Sciences,
University of Colorado Boulder, Boulder, CO, USA
NOAA Physical Sciences Laboratory, Boulder, CO, USA
John R. Albers
Cooperative Institute for Research in Environmental Sciences,
University of Colorado Boulder, Boulder, CO, USA
NOAA Physical Sciences Laboratory, Boulder, CO, USA
Andrew Hoell
NOAA Physical Sciences Laboratory, Boulder, CO, USA
Related authors
Melissa Leah Breeden, Andrew Hoell, Rochelle Pauline Worsnop, John Robert Albers, Michael T. Hobbins, Rachel Maya Robinson, and Daniel James Vimont
EGUsphere, https://doi.org/10.5194/egusphere-2025-115, https://doi.org/10.5194/egusphere-2025-115, 2025
Short summary
Short summary
We explore the predictability of saturation vapor pressure deficit (VPD), a key indicator of wildfire danger, one to 18 months in advance. Seasonal VPD forecasts are generated using a statistical dynamical model that produces high VPD skill related to a long-term warming trend and sea surface temperatures. Understanding where forecast skill comes from is important to for improving forecast models, and this study shows the role of multiple unique processes in contributing to VPD forecasts.
Melissa Leah Breeden, Andrew Hoell, John Robert Albers, and Kimberly Slinski
Weather Clim. Dynam., 4, 963–980, https://doi.org/10.5194/wcd-4-963-2023, https://doi.org/10.5194/wcd-4-963-2023, 2023
Short summary
Short summary
We compare the month-to-month evolution of daily precipitation over central southwest Asia (CSWA), a data-sparse, food-insecure area prone to drought and flooding. The seasonality of CSWA precipitation aligns with the seasonality of warm conveyor belts (WCBs), the warm, rapidly ascending airstreams associated with extratropical storms, most common from February–April. El Niño conditions are related to more WCBs and precipitation and La Niña conditions the opposite, except in January.
Dillon Elsbury, Amy H. Butler, John R. Albers, Melissa L. Breeden, and Andrew O'Neil Langford
Atmos. Chem. Phys., 23, 5101–5117, https://doi.org/10.5194/acp-23-5101-2023, https://doi.org/10.5194/acp-23-5101-2023, 2023
Short summary
Short summary
One of the global hotspots where stratosphere-to-troposphere transport (STT) of ozone takes place is over Pacific North America (PNA). However, we do not know how or if STT over PNA will change in response to climate change. Using climate model experiments forced with
worst-casescenario Representative Concentration Pathway 8.5 climate change, we find that changes in net chemical production and transport of ozone in the lower stratosphere increase STT of ozone over PNA in the future.
John R. Albers, Amy H. Butler, Andrew O. Langford, Dillon Elsbury, and Melissa L. Breeden
Atmos. Chem. Phys., 22, 13035–13048, https://doi.org/10.5194/acp-22-13035-2022, https://doi.org/10.5194/acp-22-13035-2022, 2022
Short summary
Short summary
Ozone transported from the stratosphere contributes to background ozone concentrations in the free troposphere and to surface ozone exceedance events that affect human health. The physical processes whereby the El Niño–Southern Oscillation (ENSO) modulates North American stratosphere-to-troposphere ozone transport during spring are documented, and the usefulness of ENSO for predicting ozone events that may cause exceedances in surface air quality standards are assessed.
John R. Albers, Amy H. Butler, Melissa L. Breeden, Andrew O. Langford, and George N. Kiladis
Weather Clim. Dynam., 2, 433–452, https://doi.org/10.5194/wcd-2-433-2021, https://doi.org/10.5194/wcd-2-433-2021, 2021
Short summary
Short summary
Weather variability controls the transport of ozone from the stratosphere to the Earth’s surface and water vapor from oceanic source regions to continental land masses. Forecasting these types of transport has high societal value because of the negative impacts of ozone on human health and the role of water vapor in governing precipitation variability. We use upper-level wind forecasts to assess the potential for predicting ozone and water vapor transport 3–6 weeks ahead of time.
Melissa L. Breeden, Amy H. Butler, John R. Albers, Michael Sprenger, and Andrew O'Neil Langford
Atmos. Chem. Phys., 21, 2781–2794, https://doi.org/10.5194/acp-21-2781-2021, https://doi.org/10.5194/acp-21-2781-2021, 2021
Short summary
Short summary
Prior research has found a maximum in deep stratosphere-to-troposphere mass/ozone transport over the western United States in boreal spring, which can enhance surface ozone concentrations, reducing air quality. We find that the winter-to-summer evolution of the north Pacific jet increases the frequency of stratospheric intrusions that drive transport, helping explain the observed maximum. The El Niño–Southern Oscillation affects the timing of the spring jet transition and therefore transport.
John R. Albers, Matthew Newman, Magdalena A. Balmaseda, William Sweet, Yan Wang, and Tongtong Xu
Ocean Sci., 21, 1761–1785, https://doi.org/10.5194/os-21-1761-2025, https://doi.org/10.5194/os-21-1761-2025, 2025
Short summary
Short summary
Providing early warning of coastal flooding is an emerging priority for the National Oceanic and Atmospheric Administration. We assess whether current operational forecast models can provide the basis for predicting the risks of higher-than-normal coastal sea level values up to 6 weeks in advance. For many United States coastal locations, models have sufficient prediction skill to be used as the basis for the development of a high tide flooding prediction system on subseasonal timescales.
Melissa Leah Breeden, Andrew Hoell, Rochelle Pauline Worsnop, John Robert Albers, Michael T. Hobbins, Rachel Maya Robinson, and Daniel James Vimont
EGUsphere, https://doi.org/10.5194/egusphere-2025-115, https://doi.org/10.5194/egusphere-2025-115, 2025
Short summary
Short summary
We explore the predictability of saturation vapor pressure deficit (VPD), a key indicator of wildfire danger, one to 18 months in advance. Seasonal VPD forecasts are generated using a statistical dynamical model that produces high VPD skill related to a long-term warming trend and sea surface temperatures. Understanding where forecast skill comes from is important to for improving forecast models, and this study shows the role of multiple unique processes in contributing to VPD forecasts.
Melissa Leah Breeden, Andrew Hoell, John Robert Albers, and Kimberly Slinski
Weather Clim. Dynam., 4, 963–980, https://doi.org/10.5194/wcd-4-963-2023, https://doi.org/10.5194/wcd-4-963-2023, 2023
Short summary
Short summary
We compare the month-to-month evolution of daily precipitation over central southwest Asia (CSWA), a data-sparse, food-insecure area prone to drought and flooding. The seasonality of CSWA precipitation aligns with the seasonality of warm conveyor belts (WCBs), the warm, rapidly ascending airstreams associated with extratropical storms, most common from February–April. El Niño conditions are related to more WCBs and precipitation and La Niña conditions the opposite, except in January.
Dillon Elsbury, Amy H. Butler, John R. Albers, Melissa L. Breeden, and Andrew O'Neil Langford
Atmos. Chem. Phys., 23, 5101–5117, https://doi.org/10.5194/acp-23-5101-2023, https://doi.org/10.5194/acp-23-5101-2023, 2023
Short summary
Short summary
One of the global hotspots where stratosphere-to-troposphere transport (STT) of ozone takes place is over Pacific North America (PNA). However, we do not know how or if STT over PNA will change in response to climate change. Using climate model experiments forced with
worst-casescenario Representative Concentration Pathway 8.5 climate change, we find that changes in net chemical production and transport of ozone in the lower stratosphere increase STT of ozone over PNA in the future.
John R. Albers, Amy H. Butler, Andrew O. Langford, Dillon Elsbury, and Melissa L. Breeden
Atmos. Chem. Phys., 22, 13035–13048, https://doi.org/10.5194/acp-22-13035-2022, https://doi.org/10.5194/acp-22-13035-2022, 2022
Short summary
Short summary
Ozone transported from the stratosphere contributes to background ozone concentrations in the free troposphere and to surface ozone exceedance events that affect human health. The physical processes whereby the El Niño–Southern Oscillation (ENSO) modulates North American stratosphere-to-troposphere ozone transport during spring are documented, and the usefulness of ENSO for predicting ozone events that may cause exceedances in surface air quality standards are assessed.
Amy McNally, Jossy Jacob, Kristi Arsenault, Kimberly Slinski, Daniel P. Sarmiento, Andrew Hoell, Shahriar Pervez, James Rowland, Mike Budde, Sujay Kumar, Christa Peters-Lidard, and James P. Verdin
Earth Syst. Sci. Data, 14, 3115–3135, https://doi.org/10.5194/essd-14-3115-2022, https://doi.org/10.5194/essd-14-3115-2022, 2022
Short summary
Short summary
The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams described here generate routine estimates of snow, soil moisture, runoff, and other variables useful for tracking water availability. These data are hosted by NASA and USGS data portals for public use.
John R. Albers, Amy H. Butler, Melissa L. Breeden, Andrew O. Langford, and George N. Kiladis
Weather Clim. Dynam., 2, 433–452, https://doi.org/10.5194/wcd-2-433-2021, https://doi.org/10.5194/wcd-2-433-2021, 2021
Short summary
Short summary
Weather variability controls the transport of ozone from the stratosphere to the Earth’s surface and water vapor from oceanic source regions to continental land masses. Forecasting these types of transport has high societal value because of the negative impacts of ozone on human health and the role of water vapor in governing precipitation variability. We use upper-level wind forecasts to assess the potential for predicting ozone and water vapor transport 3–6 weeks ahead of time.
Melissa L. Breeden, Amy H. Butler, John R. Albers, Michael Sprenger, and Andrew O'Neil Langford
Atmos. Chem. Phys., 21, 2781–2794, https://doi.org/10.5194/acp-21-2781-2021, https://doi.org/10.5194/acp-21-2781-2021, 2021
Short summary
Short summary
Prior research has found a maximum in deep stratosphere-to-troposphere mass/ozone transport over the western United States in boreal spring, which can enhance surface ozone concentrations, reducing air quality. We find that the winter-to-summer evolution of the north Pacific jet increases the frequency of stratospheric intrusions that drive transport, helping explain the observed maximum. The El Niño–Southern Oscillation affects the timing of the spring jet transition and therefore transport.
Cited articles
Agrawala, S., M. Barlow, H. Cullen, and Lyon, B.: The drought and humanitarian crisis in central and southwest Asia: A climate perspective, IRI Special Rep. 01–11, 24 pp., https://doi.org/10.7916/D8NZ8FHQ, 2001.
Albers, J. R. and Newman, M.: A priori identification of skillful
extratropical subseasonal forecasts, Geophys. Res. Lett., 46, 12527–12536,
https://doi.org/10.1029/2019GL085270, 2019.
Albers, J. R. and Newman, M.: Subseasonal predictability of the North
Atlantic Oscillation, Environ. Res. Lett., 16, 044024, https://doi.org/10.1088/1748-9326/abe781, 2021.
Albers, J. R., Newman, M., Hoell, A., Breeden, M. L., Wang, Y., and Lou, J.:
The February 2021 Cold Air Outbreak in the United States: a Subseasonal
Forecast of Opportunity, B. Am. Meteorol. Soc., https://doi.org/10.1175/BAMS-D-21-0266.1, online first, 2022.
Barlow, M., Cullen, H., and Lyon, B.: Drought in central and southwest Asia:
La Niña, the warm pool, and Indian Ocean precipitation, J. Climate, 15,
697–700, https://doi.org/10.1175/1520-0442(2002)015<0697:DICASA>2.0.CO;2, 2002.
Barlow, M., Wheeler, M., Lyon, B., and Cullen, H.: Modulation of daily
precipitation over southwest Asia by the Madden–Julian oscillation, Mon.
Weather Rev., 133, 3579–3594, https://doi.org/10.1175/MWR3026.1, 2005.
Barlow, M., Zaitchik, B., Paz, S., Black, E., Evans, J., and Hoell, A.: A
Review of Drought in the Middle East and Southwest Asia, J. Climate,
29, 8547–8574, 2016.
Barlow, M. A., Cullen, H., Lyon, B., and Wilhelmi, O.: Drought disaster in
Asia. Natural Disaster Hotspots Case Studies, edited by: Arnold, M., Chen, R. S., Deichmann, U., Dilley, M., Lerner-Lam, A. L., Pullen, R. E., and Trohanis, Z., Disaster Risk Management Series, No. 6, World Bank, 1–20, http://hdl.handle.net/10986/7091 (last access: 25 October 2022), 2006.
Breeden, M. L., Hoover, B. T., Newman, M., and Vimont, D. J.: Optimal North
Pacific Blocking Precursors and Their Deterministic Subseasonal Evolution
during Boreal Winter, Mon. Weather Rev., 148, 739–761, https://doi.org/10.1175/MWR-D-19-0273.1, 2020.
Breeden, M. L., Albers, J. R., Butler, A. H., and Newman, M.: The spring
minimum in subseasonal 2-meter temperature forecast skill over North
America, Mon. Weather Rev., 150, 2617–2628, 2022.
Cannon, F., Carvalho, L. M. V., Jones, C., Hoell, A., Norris, J., Kiladis, G. N., and Tahir, A. A.: The influence of tropical forcing on extreme winter
precipitation in the western Himalaya, Clim. Dynam., 48, 1213–1232,
https://doi.org/10.1007/s00382-016-3137-0, 2017.
Climate Hazards Center: CHIRPS: Rainfall Estimates from Rain Gauge and Satellite Observations, University of California Santa Barbara [data set],
https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_daily/netcdf/p25/, last access: 21 October 2021.
Commonwealth of Australia: Madden-Julian Oscillation, Australian Government Bureau of Meteorology [data set],
http://www.bom.gov.au/climate/mjo/graphics/rmm.74toRealtime.txt, last access: 1 February 2022.
de Andrade, F. M., Coelho, C. A. S., and Cavalcanti, I. F. A.: Global
precipitation hindcast quality assessment of the Subseasonal to Seasonal
(S2S) prediction project models, Clim. Dynam. 52, 5451–5475, https://doi.org/10.1007/s00382-018-4457-z, 2018.
Domeisen, D. I., Garfinkel, C. I., and Butler A. H.: The teleconnection of
El Niño Southern Oscillation to the stratosphere, Rev. Geophys.,
57, 5–47, https://doi.org/10.1029/2018RG000596, 2019.
Famine Early Warning Systems Network: Afghanistan Remote Monitoring Update,
6 pp., https://fews.net/sites/default/files/documents/reports/AFGHANISTAN_RMU_April%202022_FINAL.pdf, last access: 1 June 2022.
Farrell, B. F.: Optimal excitation of neutral Rossby waves, J. Atmos. Sci.,
45, 163–172, https://doi.org/10.1175/1520-0469(1988)045<0163:OEONRW>2.0.CO;2, 1988.
Farrell, B. F. and Ioannou, P. J.: Generalized stability theory. Part I:
autonomous operators, J. Atmos. Sci., 53, 2025–2040, 1996.
Funk, C., Peterson, P., Landsfeld, M. Pedreros, D., Verdin, J., Shukla, S.,
Husak, G., Rowland, J., Harrison, L., Hoell, A., and J. Michaelsen: The
climate hazards infrared precipitation with stations – a new environmental
record for monitoring extremes, Sci Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015.
Gehne, M., Kleeman, R., and Trenberth, K. E.: Irregularity and decadal
variation in ENSO: a simplified model based on Principal Oscillation
Patterns, Clim. Dynam., 43, 3327–3350, https://doi.org/10.1007/s00382-014-2108-6, 2014.
Henderson S. A., Vimont D. J., and Newman, M.: The critical role of
non-normality in partitioning tropical and extratropical contributions to
PNA growth, J. Climate, 33, 6273–95, https://doi.org/10.1175/JCLI-D-19-0555.1, 2020.
Hoell, A., Barlow, M., and Saini, R.: The leading pattern of intraseasonal
and interannual Indian Ocean precipitation variability and its relationship
with Asian circulation during the boreal cold season, J. Climate, 25,
7509–7526, https://doi.org/10.1175/JCLI-D-11-00572.1, 2012.
Hoell, A., Barlow, M., and Saini, R.: Intraseasonal and
Seasonal-to-Interannual Indian Ocean Convection and Hemispheric
Teleconnections, J. Climate, 26, 8850–8867, 2013.
Hoell, A., Funk, C., and Barlow, M.: The regional forcing of Northern
Hemisphere drought during recent warm tropical west Pacific Ocean La
Niña events, Clim. Dynam., 42, 3289–3311,
https://doi.org/10.1007/s00382-013-1799-4, 2014a.
Hoell, A., Funk, C., and Barlow, M.: La Niña diversity and northwest
Indian Ocean Rim teleconnections, Clim. Dynam., 43, 2707–2724,
https://doi.org/10.1007/s00382-014-2083-y, 2014b.
Hoell, A., Funk, C., and Barlow, M.: The forcing of southwestern Asia
teleconnections by low-frequency sea surface temperature variability during
boreal winter, J. Climate, 28, 1511–1526, https://doi.org/10.1175/JCLI-D-14-00344.1,
2015a.
Hoell, A., Shukla, S., Barlow, M., Cannon, F., Kelley, C., and Funk, C.: The
forcing of monthly precipitation variability over southwest Asia during the
boreal cold season, J. Climate, 28, 7038–7056,
https://doi.org/10.1175/JCLI-D-14-00757.1, 2015b.
Hoell, A., Barlow, M., Cannon, F., and Xu, T.: Oceanic Origins of Historical
Southwest Asia Precipitation During the Boreal Cold Season, J.
Climate, 30, 2885–2903, 2017.
Hoell, A., Barlow, M., Xu, T., and Zhang, T.: Cold Season Southwest Asia
Precipitation Sensitivity to El Niño–Southern Oscillation Events,
J. Climate, 31, 4463–4482, 2018a.
Hoell, A., Cannon, F., and Barlow, M.: Middle East and Southwest Asia Daily
Precipitation Characteristics Associated with the Madden–Julian Oscillation
during Boreal Winter, J. Climate, 31, 8843–8860, 2018b.
Japan Meteorological Agency: JRA-55: Japanese 55-year Reanalysis, Daily 3-Hourly and 6-Hourly Data, updated monthly, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D6HH6H41, 2013.
Jin, F. and Hoskins, B. J.: The Direct Response to Tropical Heating in a
Baroclinic Atmosphere, J. Atmos. Sci., 52, 307–319, 1995.
Johnson, N. C., Collins, D. C., Feldstein, S. B., L'Heureux, M. L., and Riddle,
E. E.: Skillful wintertime North American temperature forecasts out to 4
weeks based on the state of ENSO and the MJO, Weather Forecast., 29, 23–38,
https://doi.org/10.1175/WAF-D-13-00102.1, 2014.
Kalnay, E. and Dalcher, A.: Forecasting Forecast Skill, Mon. Weather
Rev., 115, 349–356, https://doi.org/10.1175/1520-0493(1987)115<0349:ffs>2.0.co;2, 1987.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
Kamahori, H., Kobayashi, C., Hirokazu, E., Miyaoka, K., and Takahashi, K.:
The JRA-55 reanalysis: General specifications and basic characteristics.
J. Meteorol. Soc. Jpn. Ser. II, 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015.
Lang A. L., Pegion K., and Barnes, E. A.: Introduction to special collection:
“bridging weather and climate: subseasonal- to-seasonal (S2S) prediction”,
J. Geophys. Res., 125, e2019JD031833, https://doi.org/10.1029/2019JD031833, 2020.
Li, S. and Robertson, A. W.: Evaluation of submonthly precipitation forecast
skill from global ensemble prediction systems, Mon. Weather. Rev.,
143, 2871–2889, 2015.
Mariotti, A., Baggett, C., Barnes, E. A., Becker, E., Butler, A., Collins,
D. C., Dirmeyer, P. A., Ferranti, L., Johnson, N. C., Jones, J., Kirtman, B.
P., Lang, A. L., Molod, A., Newman, M., Robertson, A. W., Schubert, S.,
Waliser, D. E., and Albers, J.: Windows of Opportunity for Skillful
Forecasts Subseasonal to Seasonal and Beyond, B. Am. Meteorol. Soc., 101, E608–E625, 2020.
Mayer, K. J. and Barnes, E. A.: Subseasonal forecasts of opportunity
identified by an explainable neural network, Geophys. Res. Lett.,
48, e2020GL092092, https://doi.org/10.1029/2020GL092092, 2021.
Nazemosadat, M. J. and Ghaedamini, H.: On the relation- ships between the
Madden–Julian oscillation and precipitation variability in southern Iran
and the Arabian Peninsula: Atmospheric circulation analysis, J. Climate, 23,
887–904, https://doi.org/10.1175/2009JCLI2141.1, 2010.
Nazemosadat, M. J. and Ghasemi, A. R.: Quantifying the ENSO-related shifts
in the intensity and probability of drought and wet periods in Iran, J.
Climate, 17, 4005–4018, https://doi.org/10.1175/1520-0442(2004)017<4005:QTESIT>2.0.CO;2, 2004.
Newman, M. and Sardeshmukh, P. D.: The impact of the annual cycle on the
North Pacific/North American response to remote low-frequency forcing,
J. Atmos. Sci., 55, 1336–1353, 1998.
Newman, M., Sardeshmukh, P. D., Winkler, C. R., and Whitaker, J. S.: A study
of subseasonal predictability, Mon. Weather Rev., 131, 1715–1732,
https://doi.org/10.1175//2558.1, 2003.
Newman, M., Sardeshmukh, P. D., and Penland, C.: How Important Is Air–Sea
Coupling in ENSO and MJO Evolution?, J. Climate, 22, 2958–2977,
2009.
Pegion, K., Kirtman, B. P., Becker, E., Collins, D. C., LaJoie, E., Burgman,
R., Bell, R., DelSole, T., Min, D., Zhu, Y., Li, W., Sinsky, E., Guan, H.,
Gottschalck, J., Metzger, E. J., Barton, N. P., Achuthavarier, D., Marshak,
J., Koster, R. D., Lin, H., Gagnon, N., Bell, M., Tippett, M. K., Robertson,
A. W., Sun, S., Benjamin, S. G., Green, B. W., Bleck, R., and Kim, H.: The
Subseasonal Experiment (SubX): A Multimodel Subseasonal Prediction
Experiment, B. Am. Meteorol. Soc., 100,
2043–2060, 2019.
Penland, C. and Sardeshmukh, P. D.: The optimal growth of tropical sea
surface temperature anomalies J. Climate, 8, 1999–2024, 1995.
Riddle, E. E., Stoner, M. B., Johnson, N. C., L'Heureux, M. L., Collins, D. C., and Feldstein, S. B.: The impact of the MJO on clusters of wintertime
circulation anomalies over the North American region, Clim. Dynam., 40,
1749–1766, https://doi.org/10.1007/s00382-012-1493-y, 2013.
Rodney, M., Lin, H., and Derome, J.: Subseasonal Prediction of Wintertime
North American Surface Air Temperature during Strong MJO Events, Mon.
Weather Rev., 141, 2897–2909, 2013.
Sardeshmukh, P. D. and Hoskins, B. J.: The Generation of Global Rotational
Flow by Steady Idealized Tropical Divergence, J. Atmos. Sci., 45, 1228–1251, 1988.
Sardeshmukh, P. D., Compo, G. P., and Penland, C.: Changes of Probability
Associated with El Niño, J. Climate, 13, 4268–4286, 2000.
Schrage, J. M., Vincent D. G. , and Fink A. H.: Modulation of intraseasonal
(25–70 day) processes by the superimposed ENSO cycle across the Pacific
basin, Meteorol. Atmos. Phys., 70, 15–27, 1999.
Shaman, J. and Tziperman E.: The Effect of ENSO on Tibetan Plateau Snow
Depth: A Stationary Wave Teleconnection Mechanism and Implications for the
South Asian Monsoons, J. Climate, 18, 2067–2079, 2005.
Shapiro, M., Wernli, H., Bond, N., and Langland, R.: The influence of the
1997–99 El NinÞo Southern Oscillation on extratropical baroclinic life cycles over the eastern North Pacific, Q. J. Roy. Meteor. Soc., 127, 331–342, 2001.
Thorncroft, C. D., Hoskins, B. J., and Wallace, J. M.: Two paradigms of
baroclinic-wave life-cycle behaviou, Q. J. Roy. Meteor. Soc., 119, 17–56,
1993.
Trenberth, K. E.: The definition of El Niño, B. Am. Meteorol. Soc., 78, 2771–2778, https://doi.org/10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2, 1997.
Trenberth, K. E. and Stepaniak, D. P.: Indices of El Niño evolution, J.
Climate, 14, 1697–1701, https://doi.org/10.1175/1520-0442(2001)014<1697:LIOENO>2.0.CO;2, 2001.
Tseng, K.-C., Barnes, E. A., and Maloney, E. D.: Prediction of the
midlatitude response to strong Madden-Julian oscillation events on S2S time
scales, Geophys. Res. Lett., 45, 463–470, https://doi.org/10.1002/2017GL075734, 2018.
Wheeler, M. C. and Hendon, H. H.: An all-season real-time multivariate MJO
index: Development of an index for monitoring and prediction, Mon. Weather Rev., 132, 1917–1932, https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2, 2004.
Winkler, C. R., Newman, M., and Sardeshmukh, P. D.: A linear model of
wintertime low-frequency variability. Part I: Formulation and forecast
skill, J. Climate, 14, 4474–4494, 2001.
Short summary
We use a statistical dynamical model to generate precipitation forecasts for lead times of 2–6 weeks over southwest Asia, which are needed to support humanitarian food distribution. The model signal-to-noise ratio is used to identify a smaller subset of forecasts with particularly high skill, so-called subseasonal forecasts of opportunity (SFOs). Precipitation SFOs are often related to slowly evolving tropical phenomena, namely the El Niño–Southern Oscillation and Madden–Julian Oscillation.
We use a statistical dynamical model to generate precipitation forecasts for lead times of 2–6...